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High-energy gamma rays produced in inertial confinement fusion (ICF) experiments are crucial for studying implosion dynamics. These gamma rays, characterized by their extremely short durations, represent the least disturbed products of fusion, preserving vital birth information. To detect such γ-rays, ultrafast radiation detectors with high time resolution are necessary. This study introduces a newly developed Cherenkov optical image screen designed for ultra-fast gamma-ray imaging. Composed of pure quartz fiber material, the imaging screen features a single fiber pixel size of 0.6 mm and a thickness of 3 cm. Theoretical investigations explore the luminous time response and efficiency of the Cherenkov optical imaging screen under gamma-ray irradiation. Experimental validation was conducted using a steady-state gamma-ray source with an average energy of 1.25 MeV. Results demonstrate that the image screen achieves a spatial resolution limit of 0.75 mm. The temporal response exhibits a full width at half maximum of less than 0.4 ns when excited by a high-energy electron beam with a single pulse duration of several picoseconds.

Abstract The principal aim of this investigation is to identify pivotal biomarkers linked to the prognosis of osteosarcoma (OS) through the application of artificial intelligence (AI), with an ultimate goal to enhance prognostic prediction. Expression profiles from 88 OS cases and 396 normal samples were procured from accessible public databases. Prognostic models were established using univariate COX regression analysis and an array of AI methodologies including the XGB method, RF method, GLM method, SVM method, and LASSO regression analysis. Multivariate COX regression analysis was also employed. Immune cell variations in OS were examined using the CIBERSORT software, and a differential analysis was conducted. Routine blood data from 20,679 normal samples and 437 OS cases were analyzed to validate lymphocyte disparity. Histological assessments of the study's postulates were performed through immunohistochemistry and hematoxylin and eosin (HE) staining. AI facilitated the identification of differentially expressed genes, which were utilized to construct a prognostic model. This model discerned that the survival rate in the high-risk category was significantly inferior compared to the low-risk cohort (p

Abstract Gastric cancer (GC), known for its high incidence and poor prognosis, urgently necessitates the identification of reliable prognostic biomarkers to enhance patient outcomes. We scrutinized data from 375 GC patients alongside 32 non-cancer controls, sourced from the TCGA database. A univariate Cox Proportional Hazards Model (COX) regression was employed to evaluate expressions of ferroptosis-related genes. This was followed by the application of Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate COX regression for the development of prognostic models. The composition of immune cell subtypes was quantified utilizing CIBERSORT, with their distribution in GC versus control samples being comparatively analyzed. Furthermore, the correlation between the expressions of Cystathionine Gamma-Lyase (CTH) and Microtubule Associated Protein 1 Light Chain 3 Beta (MAP1LC3B) and the abundance of immune cell subtypes was explored. Our bioinformatics findings underwent validation through immunohistochemical analysis. Our prognostic models integrated CTH and MAP1LC3B. Survival analysis indicated that patients categorized as high-risk, as defined by the model, exhibited significantly lower survival rates compared to their low-risk counterparts. Notably, CTH expression inversely correlated with monocyte levels, while MAP1LC3B expression showed an inverse relationship with the abundance of M2 macrophages. Immunohistochemical validation corroborated lower expressions of CTH and MAP1LC3B in GC tissues relative to control samples, in concordance with our bioinformatics predictions. Our study suggests that the dysregulation of CTH, MAP1LC3B, and the accompanying monocyte-macrophage dynamics could be pivotal in the prognosis of GC. These elements present potential targets for prognostic assessment and therapeutic intervention.

Abstract Background Endothelial-to-Mesenchymal Transformation (EndMT) plays key roles in endothelial dysfunction during the pathological progression of atherosclerosis; however, its detailed mechanism remains unclear. Herein, we explored the biological function and mechanisms of upstream stimulating factor 1 (USF1) in EndMT during atherosclerosis. Methods The in vivo and in vitro atherosclerotic models were established in high fat diet-fed ApoE−/− mice and ox-LDL-exposed human umbilical vein endothelial cells (HUVECs). The plaque formation, collagen and lipid deposition, and morphological changes in the aortic tissues were evaluated by hematoxylin and eosin (HE), Masson, Oil red O and Verhoeff-Van Gieson (EVG) staining, respectively. EndMT was determined by expression levels of EndMT-related proteins. Target molecule expression was detected by RT-qPCR and Western blotting. The release of pro-inflammatory cytokines was measured by ELISA. Migration of HUVECs was detected by transwell and scratch assays. Molecular mechanism was investigated by dual-luciferase reporter assay, ChIP, and Co-IP assays. Results USF1 was up-regulated in atherosclerosis patients. USF1 knockdown inhibited EndMT by up-regulating CD31 and VE-Cadherin, while down-regulating α-SMA and vimentin, thereby repressing inflammation, and migration in ox-LDL-exposed HUVECs. In addition, USF1 transcriptionally activated ubiquitin-specific protease 14 (USP14), which promoted de-ubiquitination and up-regulation of NLR Family CARD Domain Containing 5 (NLRC5) and subsequent Smad2/3 pathway activation. The inhibitory effect of sh-USF1 or sh-USP14 on EndMT was partly reversed by USP14 or NLRC5 overexpression. Finally, USF1 knockdown delayed atherosclerosis progression via inhibiting EndMT in mice. Conclusion Our findings indicate the contribution of the USF1/USP14/NLRC5 axis to atherosclerosis development via promoting EndMT, which provide effective therapeutic targets.

Abstract Previous studies have demonstrated that bis-(3',5')-cyclic diguanosine monophosphate (bis-3',5'-c-di-GMP) is a ubiquitous second messenger employed by bacteria. Here, we report that 2',3'-cyclic guanosine monophosphate (2',3'-cGMP) controls the important biological functions, quorum sensing (QS) signaling systems and virulence in Ralstonia solanacearum through the transcriptional regulator RSp0980. This signal specifically binds to RSp0980 with high affinity and thus abolishes the interaction between RSp0980 and the promoters of target genes. In-frame deletion of RSp0334, which contains an evolved GGDEF domain with a LLARLGGDQF motif required to catalyze 2',3'-cGMP to (2',5')(3',5')-cyclic diguanosine monophosphate (2',3'-c-di-GMP), altered the abovementioned important phenotypes through increasing the intracellular 2',3'-cGMP levels. Furthermore, we found that 2',3'-cGMP, its receptor and the evolved GGDEF domain with a LLARLGGDEF motif also exist in the human pathogen Salmonella typhimurium. Together, our work provides insights into the unusual function of the GGDEF domain of RSp0334 and the special regulatory mechanism of 2',3'-cGMP signal in bacteria.

Abstract Background Chronic remote ischemic conditioning (CRIC) has been shown to improve myocardial ischemia in experimental animal studies; however, its effectiveness in patients with chronic stable angina (CSA) has not been investigated. We conducted a proof-of-concept study to investigate the efficacy and safety of a six-month CRIC treatment in patients with CSA. Methods The EARLY-MYO-CSA trial was a prospective, randomized, controlled trial evaluating the CRIC treatment in patients with CSA with persistent angina pectoris despite receiving ≥ 3-month guideline-recommended optimal medical therapy. The CRIC and control groups received CRIC (at 200 mmHg) or sham CRIC (at 60 mmHg) intervention for 6 months, respectively. The primary endpoint was the 6-month change of myocardial flow reserve (MFR) on single-photon emission computed tomography. The secondary endpoints were changes in rest and stress myocardial blood flow (MBF), angina severity according to the Canadian Cardiovascular Society (CCS) classification, the Seattle Angina Questionnaire (SAQ), and a 6-min walk test (6-MWT). Results Among 220 randomized CSA patients, 208 (105 in the CRIC group, and 103 in the control group) completed the treatment and endpoint assessments. The mean change in MFR was significantly greater in the CRIC group than in the control group (0.27 ± 0.38 vs. − 0.04 ± 0.25; P

Abstract This study aimed to determine the effect of short-term remote ischemic preconditioning (RIPC) on coronary blood flow and microcirculation function using the quantitative flow ratio (QFR) and index of microcirculatory resistance (IMR). We randomly divided 129 patients undergoing coronary angiography (CAG) into RIPC and control groups. Following the first CAG, we randomly divided the patients further into the unilateral upper limb and lower limb groups for four cycles of ischemia/reperfusion circulation; subsequently, we performed the second CAG. During each CAG, contrast-flow QFR (cQFR), fixed-flow QFR (fQFR), and IMR (in patients with cardiac syndrome X) were calculated and compared. We measured 253 coronary arteries in 129 patients. Compared to the control group, the average cQFR of the RIPC group increased significantly after RIPC. Additionally, 23 patients with cardiac syndrome X (IMR > 30) were included in this study. Compared to the control group, IMR and the difference between cQFR and fQFR (cQFR-fQFR) both decreased significantly after receiving RIPC. The application of RIPC can increase coronary blood flow and improve coronary microcirculation function.

Importance: The global COVID-19 pandemic does not appear to end in the near future. Currently, limited data are available on the risk factors for delayed viral clearance in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant infection. Objective: This study aimed to investigate the association of clinical characteristics and vaccination with prolonged viral clearance. Methods: This retrospective cohort included 16,985 patients who had contracted the SARS-CoV-2 Omicron variant between April 5 and May 30, 2022, in Shanghai, China, and had mild or no symptoms. The patients were admitted to the quarantine venue at the Shanghai New International Expo Center. Results: Of the 16,985 participants, the occurrence of viral clearance was ≤8 and > 8 days in 11,009 (64.8 %) and 5976 (35.2 %) participants, respectively. Risk factors related to patients who remained persistently polymerase chain reaction (PCR)-positive were sex (Male, odds ratio [OR] 1.221, p 35, OR 0.079, p

Green technology innovation (GTI) is one of the most important factors influencing agricultural carbon emission intensity (ACEI). Various studies have explored the impact of GTI on ACEI, but the path mechanism has not been fully explained. This study incorporates GTI and ACEI into the constant elasticity of substitution (CES) production function and constructs a theoretical model to analyse their direct impact mechanisms. Drawing on the substitution effect theory and the Marshall–Arrow–Romer (MAR) externalities theory, this study introduces two regulatory mechanisms: optimization of energy structure and agricultural industry agglomeration (AIG). Additionally, it explores the pathway mechanisms under the influence of spatial spillover effects based on Tobler’s first law of geography. Then, taking Jiangsu Province in China as a case study, empirical tests are conducted using LSDVC and dynamic spatial SAR models. The results are as follows. (1) GTI effectively inhibits ACEI directly, and has significantly positive spatial spillover effects on ACEI reduction in the short and long terms. (2) Energy structure optimization positively regulates the effect of GTI on ACEI reduction, and energy structure optimization in nearby cities may help GTI restrain ACEI in the local city in the short term. (3) AIG has a positive regulating effect on GTI reducing ACEI, and the moderating effect of AIG has positive spillover effects in the short term. (4) When both regulatory pathways are employed simultaneously, the moderating effect of AIG in local or neighbouring areas is expected to become ineffective. These findings are useful for solving the problem of ACEI reduction by managing the transfer and distribution of GTI between different regions, considering spatial spillover and moderating effects.

Abstract At present, the impact of cuproptosis-related genes in the study of osteosarcoma is largely unknown. Genome-wide data of osteosarcoma and controls were downloaded from 3 different databases, and specific diagnostic models associated with cuproptosis in osteosarcoma were constructed by support vector machines with artificial intelligence, random forest trees and LASSO regression. Differential analysis of immune cell infiltration was examined using routine blood data from 25,665 cases. Differential expression was examined using immunohistochemistry and PCR. PDHA1 and CDKN2A were obtained as specific cuproptosis-related biomarkers for osteosarcoma after artificial intelligence analysis. PDHA1, CDKN2A and neutrophils were differentially expressed in OS and control groups. PDHA1 and CDKN2A are significantly dysregulated in OS and are able to serve as biomarkers of OS.

ABSTRACT Many bacteria use small molecules, such as quorum sensing (QS) signals, to perform intraspecies signaling and interspecies or interkingdom communication. Previous studies demonstrated that some bacteria regulate their physiology and pathogenicity by employing 4-hydroxybenzoic acid (4-HBA). Here, we report that 4-HBA controls biological functions, virulence, and anthranilic acid production in Shigella sonnei. The biosynthesis of 4-HBA is performed by UbiC (SSON_4219), which is a chorismate pyruvate-lyase that catalyzes the conversion of chorismate to 4-HBA. Deletion of ubiC caused S. sonnei to exhibit impaired phenotypes, including impaired biofilm formation, extracellular polysaccharide (EPS) production, and virulence. In addition, we found that 4-HBA controls the physiology and virulence of S. sonnei through the response regulator AaeR (SSON_3385), which contains a helix-turn-helix (HTH) domain and a LysR substrate-binding (LysR_substrate) domain. The same biological functions are controlled by AaeR and the 4-HBA signal, and 4-HBA-deficient mutant phenotypes were rescued by in trans expression of AaeR. We found that 4-HBA binds to AaeR and then enhances the binding of AaeR to the promoter DNA regions in target genes. Moreover, we revealed that 4-HBA from S. sonnei reduces the competitive fitness of Candida albicans by interfering with morphological transition. Together, our results suggested that the 4-HBA signaling system plays crucial roles in bacterial physiology and interkingdom communication. IMPORTANCE Shigella sonnei is an important pathogen in human intestines. Following previous findings that some bacteria employ 4-HBA as a QS signal to regulate biological functions, we demonstrate that 4-HBA controls the physiology and virulence of S. sonnei. This study is significant because it identifies both the signal synthase UbiC and receptor AaeR and unveils the signaling pathway of 4-HBA in S. sonnei. In addition, this study also supports the important role of 4-HBA in microbial cross talk, as 4-HBA strongly inhibits hyphal formation by Candida albicans. Together, our findings describe the dual roles of 4-HBA in both intraspecies signaling and interkingdom communication.

ObjectiveTo study the phenomenon of pulmonary hypostasis in corpses of various causes of death， and to explore the potential value of this phenomenon in assisting forensic pathological diagnosis of drowning.MethodsA total of 235 cases with clear cause of death through systematic autopsy were collected from January 2011 to June 2021 in Guangzhou. According to the location of body discovery, the cases were divided into the water body group （97 cases） and the non-water body group （138 cases）, and the water body group was further divided into the water drowning group （90 cases） and the water non-drowning group （7 cases）. Non-water body group was further divided into the non-water drowning group （1 case） and the non-water non-drowning group （137 cases）. Three senior forensic pathologists independently reviewed autopsy photos to determine whether there was hypostasis in the lungs. The detection rate of pulmonary hypostasis was calculated.ResultsThe detection rate of pulmonary hypostasis in the water drowning group （90 cases） was 0， and the negative rate was 100%. The detection rate of pulmonary hypostasis in the water non-drowning group （7 cases） was 100% and the negative rate was 0. The detection rate of pulmonary hypostasis in the water body group and in the non-water body group （after excluding 2 cases, 136 cases were calculated） was 7.22% and 87.50%， respectively. There were statistically significant differences in the detection rate of pulmonary hypostasis between water body group and non-water body group, and between water drowning group and water non-drowning group （P

Background. This study explored the efficacy of the “L-sandwich” strategy, which involves the implantation of stents in the main vessel (MV) and shaft of the side branch (SB) with a drug-coated balloon (DCB) applied to the SB ostium, for coronary true bifurcation lesions. Methods and Results. Of 99 patients with true bifurcation lesions, 38 patients underwent the “L-sandwich” strategy (group A), 32 patients underwent a two-stent strategy (group B), and 29 patients underwent a single-stent + DCB strategy (group C). Angiography outcomes (late lumen loss [LLL], minimum lumen diameter [MLD]), and clinical outcomes (major adverse cardiac events [MACEs]) were analyzed. At 6 months, the MLD of the SB ostium in groups A and B were similar (P>0.05) and group A larger than group C (P0.05), and patients in the other groups had no MACEs. Conclusions. The “L-sandwich” strategy was feasible for the treatment of true coronary bifurcation lesions. It is a simpler procedure with similar acute lumen gain than the two-stent strategy, results in a larger SB lumen than the single-stent + DCB strategy, and it can also be used as a remedy for dissection following the single-stent + DCB strategy.

A Venturi tube is typically used as the flow control element of hybrid rocket motors (HRMs) for the precise control of the flow of a liquid oxidizer, e.g., nitrous oxide, which can efficiently realize the thrust throttling of motors. The flow rate of nitrous oxide in the venturi tube was calculated for a heterogeneous non-equilibrium flow by considering the influence of the variation in the compressibility temperature. In addition, a nitrous-oxide flow rate measurement system was established to calibrate the flow rate coefficient and obtain the corresponding calculation parameters. Results revealed that upstream pressure is not affected by back pressure when the throat pressure is less than a saturated vapor pressure of 4.2 MPa at the local temperature for the venturi tube with a throat diameter of 1.65 mm; however, cavitation disappeared at a back pressure of greater than 6.35 MPa. A flow rate evaluation error of less than 6 wt% was achieved by using the experimentally determined non-equilibrium parameter in the flow rate calculation method.

Understanding the damage evolution of alloys during a plastic deformation process is significant to the structural design of components and accident prevention. In order to visualize the damage evolution in the plastic deformation of Ti–3Al–2Mo–2Zr alloy, a series of uniaxial tensile experiments for this alloy were carried out under the strain rates of 0.1–10 s−1 at room temperature, and the stress–strain curves were achieved. On the other hand, the finite element (FE) models of these uniaxial tensile processes were established. A microvoids proliferation model, Gurson–Tvergaard–Needleman (GTN) damage model, was implanted into the uniaxial tensile models, and the simulated stress–strain curves corresponding to different GTN parameter combinations were obtained. Based on the simulated and experimental stress–strain curves, the GTN parameters of this alloy were solved by response surface methodology (RSM). The solved GTN parameters suggest that higher strain rate can enhance the proliferation and coalescence of microvoids. Furthermore, the uniaxial tensile tests over different strain rates were simulated using the solved GTN parameters. Then, the damage processes were visualized and evaluated. The result shows that the degradation speed of this alloy is slow at the initial stage of the tensile deformation and then accelerates once the voids volume fraction reaches a critical value.

Targeted sequencing has been widely utilized for genomic molecular diagnostics and the emerging DNA data storage paradigm. However, the probe sequences used to enrich regions of interest have different hybridization kinetic properties, resulting in poor sequencing uniformity and setting limitations for the large-scale application of the technology. Here, a low-complexity deep learning model is proposed for prediction of sequencing depth from probe sequences. To capture the representation of probe and target sequences, we utilized a sequence-encoding model that incorporates k-mer and word embedding techniques, providing a streamlined alternative to the intricate computations involved in biochemical feature analysis. We employed bidirectional long short-term memory (Bi-LSTM) to effectively capture both long-range and short-range interactions within the representation. Furthermore, the attention mechanism was adopted to identify pivotal regions in the sequences that significantly influence sequencing depth. The ratio of the predicted sequencing depth to the actual sequencing depth was in the interval of 1/3—3 as the evaluation metric of model accuracy. The prediction accuracy was 94.3% in the human single-nucleotide polymorphism (SNP) panel and 99.7% in the synthetic DNA information storage sequence (SynDNA) panel. Our model substantially reduced data processing time (from 334 min to 4 min of CPU time in the SNP panel) and model parameters (from 300 k to 70 k) compared with the baseline model.

Breast cancer is one of the most common malignancies that threaten women’s health. Ultrasound testing is a widespread technique employed for the early detection of tumors. However, after receiving the paper ultrasound report, most patients often have to wait for several days to receive the diagnosis results, which can increase their psychological burden and may cause treatment delay. Based on deep learning, this study designed a computer-aided diagnostic system that directly classifies benign and malignant tumors in breast ultrasound images on paper reports taken by patients, helping them obtain auxiliary diagnostic results as soon as possible. In order to segment and denoise ultrasound report images of patients, this paper proposes a breast ultrasound report generation method, which mainly includes a segmentation model, a rotating classification model and a generative model. With this method, multiple high-quality individual breast ultrasound images can be obtained from a single ultrasound report photo, improving the performance of the breast ultrasound image classification model. In order to utilize high-quality breast ultrasound images and improve classification performance, this paper proposed a breast ultrasound report classification model that includes a feature extraction module, a channel attention module and a classification module. The accuracy of the model reached 89.31%, recall rate reached 88.65%, specificity reached 89.57%, F1 score reached 89.42% and AUC reached 94.53% when input images contained noise. The method proposed in this article is more suitable for practical application scenarios and it can quickly and accurately assist patients in obtaining the benign and malignant classification results of ultrasound reports.

Quorum sensing (QS) is widely employed by bacterial cells to control gene expression in a cell density-dependent manner. A previous study revealed that anthranilic acid from Ralstonia solanacearum plays a vital role in regulating the physiology and pathogenicity of R. solanacearum. We reported here that anthranilic acid controls the important biological functions and virulence of R. solanacearum through the receptor protein RaaR, which contains helix-turn-helix (HTH) and LysR substrate binding (LysR_substrate) domains. RaaR regulates the same processes as anthranilic acid, and both are present in various bacterial species. In addition, anthranilic acid-deficient mutant phenotypes were rescued by in trans expression of RaaR. Intriguingly, we found that anthranilic acid binds to the LysR_substrate domain of RaaR with high affinity, induces allosteric conformational changes, and then enhances the binding of RaaR to the promoter DNA regions of target genes. These findings indicate that the components of the anthranilic acid signaling system are distinguished from those of the typical QS systems. Together, our work presents a unique and widely conserved signaling system that might be an important new type of cell-to-cell communication system in bacteria.

Surface coating can greatly enhance the lifetime of cold extrusion die. It is a significant issue to evaluate the performance of coatings and even predict the lifetime of cold extrusion die. In this work, the titanium-based nitride coatings including TiN, TiAlN, and TiAlCrN were, respectively, deposited on the surface of high-speed steel substrate W6Mo5Cr4V2 (M2) by the physical vapor deposition technology. The hardness test, scratch test, Rockwell adhesion test, and pin-on-disc (POD) wear test were carried out aiming to investigate the performances of the three coatings including hardness, adhesion strength, and wear resistance. The results show that the TiAlCrN coating exhibits the highest hardness of 3,033 HV in comparison with TiN coating (1,222 HV) and TiAlN coating (1,916 HV), while it possesses poor adhesion strength and inferior wear resistance. Furthermore, the TiAlN coating presents the highest resistance to wear and spalling from the substrate. In addition, the Archard wear model of the coatings was solved and applied in the finite element model of cold extrusion to calculate the wear depth and lifetime of the cold extrusion dies. The results suggest that TiAlN coating is the optimal option for cold extrusion die as compared with TiAlCrN and TiN coatings. TiAlN coating can prolong the lifetime of the substrate die up to 260%.

Secchi disk depth is a commonly measured parameter representing the optical properties of water bodies. Assessment of water transparency in seas is highly significant to marine-environment monitoring. In this study, an improved Secchi disk depth (ZSD) inversion algorithm was proposed based on the Poole–Atkins model by determining the parameter A in the original model. The Forel–Ule index (FUI) is a water color parameter that can be obtained from remote sensing data. Through the analysis of the International Ocean Color Coordinating Group dataset, it was found that there are strong logarithmic and quadratic correlations between the FUI and parameter A, whose R2 values are 0.929 and 0.925, respectively. Comparing the results derived from MODIS product data with the in situ measured data in the Yellow Sea showed that the RMSE and MRE of the quadratic formula are 1.83 m and 43.74%, respectively, which reflect better performance than the other empirical formulas. Thus, parameter A can be expressed in quadratic form with FUI as a variable. Finally, we mapped the ${Z_{{\rm{SD}}}}$ inversion results for the Yellow Sea and analyzed the spatial changes. This study provides new insight for inverting ZSD transparency algorithms and highlights the value of marine transparency monitoring.

Lake bathymetry plays a pivotal role in environmental monitoring, ecological management, water quality protection, etc. Hyperspectral remote sensing technology can provide large-scale coverage and more detailed spectral information for bathymetry estimation than traditional measurements or multispectral imagery techniques. In this study, a multiband linear model with successive projections algorithm (SPA-MLM) was developed to retrieve the bathymetry of Qinghai Lake, which is the largest inland saltwater lake in China. The three most sensitive spectral bands were first selected by the SPA, and a multiband linear model was established by the least squares method combined with the in situ measured water depth. Zhuhai-1 hyperspectral remotely sensed imagery is employed as the data source. In all, 98 in situ bathymetry measurements matched with the obtained images were obtained during three surveys performed in May, September, and October 2020. The results demonstrated that the established retrieval model can be used to accurately estimate the water depth in the study area, with an accuracy exceeding approximately 90%, which suggests that the proposed model performs better than those used in previous studies employing hyperspectral imagery. The correlation coefficient reaches 0.92, and the root-mean-square error is approximately 1.26 m. This demonstrates that bathymetry estimation obtained using remotely sensed hyperspectral data is an effective detection method and can provide large-scale, rapid monitoring data to the relevant decision-making departments.

BackgroundNeuromyelitis Optica spectrum disorder (NMOSD) is severe relapsing and disabling autoimmune disease of the central nervous system. Its optimal first-line treatment to reduce relapse rate and ameliorate neurological disability remains unclear. We will conduct a prospective, multicenter, randomized, placebo-controlled clinical trial to study the safety and effectiveness of human umbilical cord mesenchymal stem cells (hUC–MSCs) in treating NMOSD.MethodsThe trial is planned to recruit 430 AQP4-IgG seropositive NMOSD patients. It consists of three consecutive stages. The first stage will be carried out in the leading center only and aims to evaluate the safety of hUC—MSCs. Patients will be treated with three different doses of hUC–MSCs: 1, 2, or 5 × 106 MSC/kg·weight for the low-, medium-, and high-dose group, respectively. The second and third stages will be carried out in six centers. The second stage aims to find the optimal dosage. Patients will be 1:1:1:1 randomized into the low-, medium-, high-dose group and the controlled group. The third stage aims to evaluate the effectiveness. Patients will be 1:1 randomized into the optimal dose and the controlled group. The primary endpoint is the first recurrent time and secondary endpoints are the recurrent times, EDSS scores, MRI lesion numbers, OSIS scores, Hauser walking index, and SF-36 scores. Endpoint events and side effects will be evaluated every 3 months for 2 years.DiscussionAlthough hUC–MSC has shown promising treatment effects of NMOSD in preclinical studies, there is still a lack of well-designed clinical trials to evaluate the safety and effectiveness of hUC–MSC among NMOSD patients. As far as we know, this trial will be the first one to systematically demonstrate the clinical safety and efficacy of hUC–MSC in treating NMOSD and might be able to determine the optimal dose of hUC–MSC for NMOSD patients.Trial registrationThe study was registered with the Chinese Clinical Trial Registry (CHICTR.org.cn) on 2 March 2016 (registration No. ChiCTR-INR-16008037), and the revised trial protocol (Protocol version 1.2.1) was released on 16 March 2020.

The solution-aging treatment parameters, including solution temperature, cooling rate and aging temperature, have significant influences on the microstructures and comprehensive mechanical properties of titanium alloy. In this work, the detailed microevolution behaviors of Ti–10V–2Fe–3Al alloy under different solution and aging conditions have been investigated through a series of heat-treatment experiments. The results of solution-treatment experiments reveal that the content of αp-phase is reduced to zero as the solution temperature is raised to a certain α → β critical transformation point. Recrystallized β-grains can be observed at the solution temperature of 820°C. In addition, the cooling way (air cooling or water cooling) has little influence on the microevolution behaviors for this alloy during the solution-treatment process. As for the solution-aging-treatment experiments, the results reveal that αs-phases are precipitated from the supersaturated β-phase, and the fraction of αs-phase increases with increasing aging temperature. However, the precipitated α-grains intend to coalesce and coarsen as the aging temperature raises above 510°C. Therefore, the advocated solution-aging-treatment program is solution treatment at 820°C with air cooling followed by aging treatment at 510°C with air cooling.

Mesoscale eddies are typical mesoscale ocean phenomena that exist widely in all oceans and marginal seas around the world, playing important roles in ocean circulation and material transport. They also have important impacts on the safe navigation of ships and underwater acoustic communications. Traditional mesoscale eddy identification methods are subjective and usually depend on parameters that must be pre-defined or adjusted by experts, meaning that their accuracy cannot be guaranteed. With the rise of deep learning, the “you only look once” (YOLO) series target recognition models have been shown to present certain advantages in eddy detection and recognition. Based on sea level anomaly (SLA) data provided over the past 30 years by the Copernicus Marine Environment Monitoring Service (CMEMS), as well as deep transfer learning, we propose a method for oceanic mesoscale eddy detection and identification based on the “you only look once level feature” (YOLOF) model. Using the proposed model, the mesoscale eddies in the South China Sea from 1993 to 2021 were detected and identified. Compared with traditional recognition methods, the proposed model had a better recognition effect (with an accuracy of 91%) and avoided the bias associated with subjectively set thresholds; to a certain extent, the model also improved the detection of and the identification speed for mesoscale eddies. The method proposed in this paper not only promotes the development of deep learning in the field of oceanic mesoscale eddy detection and identification, but also provides an effective technical method for the study of mesoscale eddy detection using sea surface height data.

It is a significant issue to deeply understand the nature relationships between damage degradation and deforming parameters, and then identify the changes of initial ductile fracture time with processing parameters and further adjusting the forming processes for obtaining the fracture-free components. For Ti-6Al-4V alloy, the strain-stress data in the temperature range of 1023–1323 K and strain rate range of 0.01–10 s−1 were obtained by compression tests. The finite element model with stress-strain data was constructed to simulate the ductile damage cumulating processes under different conditions and obtained the maximum damage values. Subsequently, the ductile fracture criterion (DFC) of Ti-6Al-4V alloy was established and the effects of temperature and strain rate on DFC were discussed. The results show that the variation range of DFC under different deformation conditions is 0.07–0.15. Subsequently, the deformation conditions with higher fracture risk were identified as 1200∼1275 K & 1∼10 s−1 and verified with the experiment observations.

The automatic detection of diseases in images acquired through chest X-rays can be useful in clinical diagnosis because of a shortage of experienced doctors. Compared with natural images, those acquired through chest X-rays are obtained by using penetrating imaging technology, such that there are multiple levels of features in an image. It is thus difficult to extract the features of a disease for further diagnosis. In practice, healthy people are in a majority and the morbidities of different disease vary, because of which the obtained labels are imbalanced. The two main challenges of diagnosis though chest X-ray images are to extract discriminative features from X-ray images and handle the problem of imbalanced data distribution. In this paper, we propose a deep neural network called DeepCXray that simultaneously solves these two problems. An InceptionV3 model is trained to extract features from raw images, and a new objective function is designed to address the problem of imbalanced data distribution. The proposed objective function is a performance index based on cross entropy loss that automatically weights the ratio of positive to negative samples. In other words, the proposed loss function can automatically reduce the influence of an overwhelming number of negative samples by shrinking each cross entropy terms by a different extent. Extensive experiments highlight the promising performance of DeepCXray on the ChestXray14 dataset of the National Institutes of Health in terms of the area under the receiver operating characteristic curve.

Constitutive model of materials is one of the most requisite mathematical model in the finite element analysis, which describes the relationships of flow behaviors with strain, strain rate and temperature. In order to construct such constitutive relationships of ultra-high-strength BR1500HS steel at medium and low temperature regions, the true stress-strain data over a wide temperature range of 293–873 K and strain rate range of 0.01–10 s−1 were collected from a series of isothermal uniaxial tensile tests. The experimental results show that stress-strain relationships are highly non-linear and susceptible to three parameters involving temperature, strain and strain rate. By considering the impacts of strain rate and temperature on strain hardening, a modified constitutive model based on Johnson-Cook model was proposed to characterize flow behaviors in medium and low temperature ranges. The predictability of the improved model was also evaluated by the relative error (W(%)$W(\%)$), correlation coefficient (R) and average absolute relative error (AARE). The R-value and AARE-value for modified constitutive model at medium and low temperature regions are 0.9915 & 1.56 % and 0.9570 & 5.39 %, respectively, which indicates that the modified constitutive model can precisely estimate the flow behaviors for BR1500HS steel in the medium and low temperature regions.

Under the Belt and Road concepts of mutual benefit and win–win cooperation, China is strengthening its energy cooperation with other countries. We used several econometric models and social network analysis models to study the impacts of China’s outward foreign direct investment (OFDI) on the host and home countries. We first examined China’s OFDI location preference and analysed the effects of OFDI on energy consumption in host countries. Meanwhile, we observed the impact of the reverse spillover effect of OFDI on China’s energy efficiency. The results indicate that (1) the impact of China’s OFDI on energy consumption in host countries has been lower than that on neighbouring countries, and increased significantly after 2014. (2) The space network of energy consumption in Belt and Road countries has a strict hierarchical structure. However, it was disbanded by the Belt and Road policy in 2014. The network centres are situated primarily in Middle Eastern and European countries, and the network’s periphery is mainly in South-East and West Asian countries. (3) The reverse spillover effects of OFDI, FDI, domestic R&D absorptive capacity, human capital, and financial development levels are conducive to improving China’s energy efficiency whereas regional professionalism does the opposite.

Abstract The separation of leukocytes from whole blood is a prerequisite for many biological assays. Traditional methods require significant sample volumes and are often undesirable because they expose leukocytes to harsh physical or chemical treatment. Existing microfluidic approaches can work with smaller volumes, but lack selectivity. In particular, the selectivity of microfluidic systems based on microfiltration is limited by fouling due to clogging. Here, we developed a method to separate leukocytes from whole blood using the microfluidic ratchet mechanism, which filters the blood sample using a matrix of micrometer-scale tapered constrictions. Deforming single cells through such constrictions requires directionally asymmetrical forces, which enables oscillatory flow to create a ratcheting transport that depends on cell size and deformability. Simultaneously, oscillatory flow continuously agitates the cells to limit the contact time with the filter microstructure to prevent adsorption and clogging. We show this device is capable of isolating leukocytes from whole blood with 100% purity (i.e. no contaminant erythrocytes) and

Graphene is a gapless material with a linear energy-momentum dispersion relationship. Because of its unique band structure, graphene has been demonstrated as an ultra-broadband photon absorption material from the visible to terahertz frequency ranges. Here, we study the reverse process: photon emission from graphene. Using silica microsphere structures and femtosecond laser pulse excitation, photon emission enhancement at visible, near infrared, and terahertz ranges were achieved. These results help to promote graphene as a new type of light generation material, which can overcome the restriction that the emission wavelength is determined by the material bandgap. It is also found that the graphene's electrical properties, such as the nonlinear conductivity, changed significantly with the enhancement of the absorption during the ultrafast process.

We propose a multiple-voting-based joint detection-decoding algorithm for nonbinary low-density parity-check (LDPC)-coded modulation systems. This algorithm is inspired from the reliability-based JDD algorithm for nonbinary LDPC-coded modulation systems, that has been proposed recently, in which the accumulated reliability of symbols based on one-step majority-logic decoding algorithm and the Chase-like local list decoding algorithm are used. However, the reliability-based JDD algorithm still has a significant performance degradation of at least 1 dB with low column weight (dv≤4). In order to reduce the performance degradation with low column weight, the proposed algorithm allows unfixed number of variable nodes to pass two symbols to the associated check node, in contrast with the reliability-based JDD algorithm, which allows only one variable node to pass two symbols to check node, when updating variable-to-check messages. Moreover, the votes are weighted differently according to the components of the list in the check-sum computation. Simulations show that the proposed algorithm yields better performance with low column weight, while still maintaining the low complexity feature.

The response of true stress to strain rate, temperature and strain is a complex three-dimensional (3D) issue, and the accurate description of such constitutive relationships significantly contributes to the optimum process design. To obtain the true stress–strain data of ultra-high-strength steel, BR1500HS, a series of isothermal hot tensile tests were conducted in a wide temperature range of 973–1,123 K and a strain rate range of 0.01–10 s−1 on a Gleeble 3800 testing machine. Then the constitutive relationships were modeled by an optimally constructed and well-trained backpropagation artificial neural network (BP-ANN). The evaluation of BP-ANN model revealed that it has admirable performance in characterizing and predicting the flow behaviors of BR1500HS. A comparison on improved Arrhenius-type constitutive equation and BP-ANN model shows that the latter has higher accuracy. Consequently, the developed BP-ANN model was used to predict abundant stress–strain data beyond the limited experimental conditions. Then a 3D continuous interaction space for temperature, strain rate, strain and stress was constructed based on these predicted data. The developed 3D continuous interaction space for hot working parameters contributes to fully revealing the intrinsic relationships of BR1500HS steel.

The deep understanding of flow behaviors of as-extruded 7050 aluminum alloy significantly contributes to the accuracy simulation for its various plastic forming processes. In order to obtain the improved Arrhenius-type equation with variable parameters for this alloy, a series of compression tests were performed at temperatures of 573 K, 623 K, 673 K, 723 K and strain rates of 0.01 s−1, 0.1 s−1, 1 s−1, 10 s−1 with a height reduction of 60% on Gleeble-1500 thermo-mechanical simulator. It is obvious that strain rate, strain and temperature all have a significant effect on the hot flow behaviors, and the true stress–true strain curves indicate three types after the peak value: decreasing gradually to a steady state with sustaining DRX softening till a balance with work hardening, decreasing continuously with sustaining increasing DRX softening beyond work hardening and maintaining higher stress level after the peak value with a balance between work hardening and DRV softening. Based on the experimental data, the improved Arrhenius-type constitutive model was established to predict the high temperature flow stress of as-extruded 7050 aluminum alloy. The accuracy and reliability of the improved Arrhenius-type model were further evaluated in terms of the correlation coefficient (R), here 0.98428, the average absolute relative error (AARE), here 3.5%. The results indicate that the improved Arrhenius-type constitutive model presents a good predictable ability.

The hot workability of Ti–6Al–4V alloy was investigated according to the measured stress–strain data and their derived forms from a series of hot compressions at the temperatures of 1,023–1,323 K and strain rates of 0.01–10 s−1 with a height reduction of 60%. As the true strain was 0.3, 0.5, 0.7 and 0.9, respectively, the response maps of strain rate sensitivity (m-value), power dissipation efficiency (η$\eta $-value) and instability parameter (ξ$\xi $-value) to temperature and strain rate were developed on the basis of dynamic material model (DMM). Then the processing map was obtained by superimposition of the power dissipation and the instability maps. According to the processing map, the stable regions (η>0$\eta \gt 0$ and ξ>0$\xi \gt 0$) and unstable regions (η$ \gt $0.3) corresponding to the ideal deformation mechanisms involving globularization and superplasticity were identified and recommended. The microstructures of the deformed samples were then observed by microscopy. And homogeneous microstructures with refined grains were found in the recommended parameter domains. The optimal working parameter domains identified by processing map and validated by microstructure observations contribute to the design in reasonable hot forming process of Ti–6Al–4V alloy without resorting to expensive and time-consuming trial-and-error methods.

The isothermal compressions of as-forged Ti-10V-2Fe-3Al alloy at the deformation temperature range of 948–1,123 K and the strain rates in the range of 0.001–10 s−1 with a height reduction of 60% were conducted on a Gleeble-3500 thermo-mechanical simulator. The flow behaviors show nonlinear sensitivity to strain, strain rate and temperature. Based on the experimental data, an artificial neural network (ANN) with back-propagation algorithm was developed to deal with the complex deformation behavior characteristics. In the present ANN model, strain, strain rate and temperature were taken as inputs, and flow stress as output. A comparative study on the constitutive relationships based on regression and ANN methods was conducted. According to the predicted and experimental results, the predictabilities of the two models have been evaluated in terms of correlation coefficient (R) and average absolute relative error (AARE). The R-value and the AARE-value at strain of 0.5 from the ANN model is 0.9998 and 0.572%, respectively, better than 0.9902 and 6.583% from the regression model. The predicted strain–stress curves outside of experimental conditions indicate similar characteristics with experimental curves. The results have sufficiently articulated that the well-trained ANN model with back-propagation algorithm has excellent capability to deal with the complex flow behaviors of as-forged Ti-10V-2Fe-3Al alloy.

When a red blood cell (RBC) is driven by a pressure gradient through a microfluidic channel, its passage or blockage provides a measure of the rigidity of the cell. This has been developed as a means to separate RBCs according to their mechanical properties, which are known to change with pathological conditions such as malaria infection. In this study, we use numerical simulations to establish a quantitative connection between the minimum pressure needed to drive an RBC through a contracting microfluidic channel and the rigidity of the cell membrane. This provides the basis for designing such devices and interpreting the experimental data.

In order to investigate the tensile deformation behavior of ultra-high-strength-steel BR1500HS, a series of isothermal tensile experiments were carried out in a temperature range of 1023˜1123 K and a strain rate range of 0.01˜10 s−1 on a Gleeble-3500 thermo-mechanical simulator. The results indicate that the flow stress initially increases to a peak value and then decreases gradually to a steady state. Based on the analysis of the effect of strain, temperature and strain rate on flow stress, dynamic recrystallization (DRX) type softening characteristics of the stress-strain curve with single peak were identified. The flow stress level decreases with increasing temperature and decreasing strain rate. By regression analysis for Arrhenius type equation, the hot deformation activation energy Q and material constants (n, α, β and A) were calculated. Further, the Arrhenius-type constitutive equation of flow stress was developed by considering the effect of strain on the variable coefficients (including activation energy Q, material constants n, α, and A). The validity of the developed constitutive equation incorporating the influence of strain was evaluated through comparing the experimental and predicted data. Furthermore, the predictability of the developed model was also evaluated using two standard statistical parameters, correlation coefficient (R) and average absolute relative error (AARE). And R-value and AARE-value for the model are 0.997 and 4.06% respectively, which indicates that the developed model can precisely estimate the flow behavior for BR1500HS alloy throughout the entire temperature and strain rate range.

Background/Aim: Reduction in serum placental growth factor (PLGF) frequently co-occurs with preeclampsia (PE) and gestational diabetes mellitus (GDM). Recently, we reported that impairment in gestational beta-cell mass growth may result from PE-associated reduction in PLGF and lead to development of GDM. Here, we studied the underlying mechanisms. Methods: We co-cultured primary mouse beta cells with mouse islet endothelial cells (MS1), with or without PLGF. We also cultured beta cells in conditioned media from PLGF-treated MS1. Specific signal-pathway inhibitors were applied to cultured beta cells in conditioned media from PLGF-treated MS1. We analysed beta-cell proliferation by BrdU incorporation. We analysed changes in cell number by a MTT assay. We analysed protein levels of cell-cycle regulators in beta cells by Western blot. Results: PLGF itself failed to induce beta-cell proliferation, but significantly augmented proliferation of beta cells co-cultured with MS1, which resulted in significant increases in cell number. Conditioned media from the PLGF-treated MS1 cells similarly induced beta-cell proliferation, which was abolished by inhibition of PI3k/Akt signalling, but not by inhibition of either ERK/MAPK or JNK signalling. The induction of beta-cell proliferation by PLGF-treated MS1 cells appeared to involve decreases in cell-cycle inhibitors p21 and p27, and increases in cell-cycle activators CDK4 and CyclinD1. Conclusion: Gestational PLGF may target islet endothelial cells to release growth factors that activate PI3k/Akt signalling in beta cells to increase their proliferation. PE-associated reduction in PLGF impairs these processes to result in GDM.

In order to study the dynamic recrystallization (DRX) behavior of as-extruded 42CrMo high-strength steel, a series of isothermal upsetting experiments were carried out in a temperature range of 1123~1348 K and a strain rate range of 0.01~10 s-1 on Gleeble 1500. It was found that DRX softening is more recognizable at higher temperatures and lower strain rates, and stress level increases with increasing strain rate and decreasing deformation temperature. The types of flow stress evolution were distinguished by the following three characteristics: WH followed by DRX, WH followed by DRV, and WH followed by no dynamic softening. At a fixed temperature, the average grain size refined by DRX linearly decreases with increasing strain rate in log scale. At a fixed strain rate, the average grain size remains almost constant below 1273 K, while it rapidly increases above 1273 K. At a larger strain rate, data set of grain sizes has a smaller standard deviation to the average size value, and data have tightly grouped. This indicates that as strain rate increases, the microstructure becomes more and more uniform. The relationships between the average grain size and Zener-Hollomon parameter were nonlinearly fitted by the equation D A = 319.81202 - 13.6114 lnZ + 0.15322 (lnZ)². The results from this equation show that the average grain size decreases with increasing Zener-Hollomon parameter. On the plot of D A versus lnZ, the regions corresponding to DRV (lnZ 37.8) and DRX (lnZ 37.8) were clarified clearly.

In order to reduce data maintenance overhead, more and more enterprises outsource their data to the cloud storage, which provides flexible and on-demand storage service for companies. Data outsourcing also brings a lot of security problems, of which query integrity is a critical issue to be resolved. Current research mainly focuses on how to ensure correctness and completeness of the query integrity and pays little attention to freshness verification of query integrity. In this paper, we propose a scheme called MAC Chain for users to verify that their query results are correct, complete and fresh. Experiments show that our scheme does not only have a better performance but also support freshness verification.

The problem of privacy preserving inner product of vectors has been widely studied. Much work has been done on the scenario of two parties involved in the computation. In this paper, we consider the scenario where three parties are involved in the computing process of cloud computing. We propose a new privacy preserving scheme for inner product of two vectors in the cloud and give the correctness analysis and performance analysis for the scheme. The proposed scheme is based on homomorphic encryption, and the security can be guaranteed. Experiments show the efficiency of the scheme.