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For advanced aero-engine design and research, modeling and simulation in a digital environment is indispensable, especially for engines of complicated configurations, such as variable cycle engines (VCE) and adaptive cycle engines (ACE). Also, in the research of future smart engines, reliable real-time digital twins are paramount. However, the 2 dominant methods that used in solving the simulation models, Newton-Raphson (N-R) method and volume-based method, are not fully qualified for the study requirements, because neither of them reaches the satisfactory balance of convergence rate and calculating efficiency. In this study, by deeply analyzing the mathematical principle of these 2 methods, a novel modeling and solving method for aero-engine simulation, which integrates the advantages of both N-R and volume-based methods, is established. It has distributed architecture and local quadratic convergence rate. And a novel modeling method for variable area bypass injectors (VABI) is put forward. These facilitate simulation of various configurations of aero-engines. The modeling cases, including a high bypass-ratio (BPR) turbofan and an ACE, illustrate that the novel technique decreases the iterations by about two-thirds comparing with volume-based method, while the success rate of convergence remains over 99%. This proves its superiority in both convergence and calculating efficiency over the conventional ones. This technique can be used in advanced gas turbine engine design and control strategy optimization, and study of digital twins.

slime water generally contains a large number of highly dispersed suspended particles, making solid-liquid separation difficult. Strengthening fluid mixing and particle collision by regulating turbulence is an effective way to achieve solid-liquid separation. Particle collision flocculation mostly occurs in turbulent environments where the motion of fine particles is strongly influenced by the turbulent minimum vortex scale. In this study, turbulent vortices are modulated by impinging flows to enhance the mixing of two different density suspensions and the collision of fine particles in the suspension. Two different solution models were used to simulate the mixing condition of the suspension and the distribution of the particles in the mixing drum in three dimensions. The water phase entering the mixing drum was considered as a continuous phase and the solid particles were considered as a continuous phase (suspension) or a secondary discrete phase (particles). The effects of different inlet fluid velocity ratios at different feed densities on the turbulent characteristic parameters and particle distribution in the mixing drum were analyzed. The results of the study show that the impact flow formed by the jets colliding vertically with each other can induce turbulent macro-vortices such as hairpin vortices, spanwise vortices and axial vortices. The velocity of particles moving in the turbulent macro-vortex is in the following order: Large particle size and density > Large particle size and small density > Small particle size and high density > Small particle size and density. The interaction between vortex and vortex and between vortex and the main fluid significantly increases the turbulent kinetic energy and decreases the vortex scale, resulting in a minimum scale vortex that is conducive to particle coalescence and collision; the minimum vortex scale generated in the flow field in the mixing drum is mainly smaller than the average minimum vortex scale. The minimum vortex scale tends to increase when the inlet flow rate and flow rate ratio increase from 1.258:1.87 to 1.882:1.258, independent of the inlet density. When the flow rate ratio is similar, the minimum vortex scale decreases only when the flow rate increases. An appropriate increase in the ratio of the upper and side feed flow rates helps fluid mixing and particle aggregation and collision, and the mixing density, apparent viscosity and particle coalescence are all optimal when the ratio of the upper and side feed flow rates is between 1.40 and 1.50. In addition, at the same flow rate ratio, the mixing uniformity and mixing strength are better than the case where the upper inlet feed density is greater than the side inlet feed density, which is more conducive to fluid mixing and particle collision. The study promotes slime water mixing and fine particle coalescence in mixing drums through the regulation of fluid hydraulic conditions, providing a new way of thinking about how to enhance the liquid-liquid mixing and solid-liquid separation process.

Spatiotemporal continuity of surface water datasets widely known for its significance in the surface water dynamic monitoring and assessments, are faced with drawbacks like cloud influence, which hinders the direct extraction of data from time-series remote sensing images. This study proposes a Time-series Surface Water Reconstruction method (TSWR). The initial stage of this method involves the effective use of remote sensing images to automatically construct multi-stage surface water boundaries based on Google Earth Engine (GEE). Then, we reconstructed regions the reconstruction of regions with missing water pixels using the distance relationship between the multi-stage water boundaries in previous and later periods. When applied to 10 large rivers around the world, this method yielded an overall accuracy of 98% for water extraction, an RMSE of 0.41 km2. Furthermore, time-series reconstruction tests conducted in 2020 on the Lancang and Danube rivers revealed a significant improvement in the image availability. These findings demonstrated that this method could not only be used to accurately reconstruct the surface water distribution missing water images, but also to depict a more pronounced time variation characteristic. The successful application of this method on GEE demonstrates its importance for use on large scales or in global studies.

Abstract With the quick development of flexible memory electronics, multifunctional organic materials have been the necessary for fabricating electronics. In this work, the highly transparent and flexible electrode was successfully prepared by coating the high‐performance silver nanowires (AgNWs) onto the colorless polyimide (PI) substrate. The prepared flexible PI–AgNWs electrodes exhibited a relatively low sheet resistance of 15 Ω/sq with the high transparency of 68% at the wavelength of 400 nm. A novel kind of polyimide TPC6FPI was successfully synthesized and characterized with the excellent thermostability and high glass transition temperature (Tg) above 250°C. Furthermore, a kind of flexible transparent PI–AgNWs/TPC6FPI/Al resistive memory device was prepared and exhibited good SRAM switching behavior with the threshold voltage of around 2.1 V and the ON/OFF current ratio of ˜104, which indicated that multifunctional PI‐based memory device showed the potential to the wearable devices.

Abstract Background Despite deeper understanding of the genetic landscape of acute myeloid leukemia (AML), the improvement of survival is still a great challenge. STK10 is overexpressed in several cancers with functions varying according to cancer types. But the functions of STK10 in AML has never been reported. Methods We analyzed the expression, prognosis and potential functions of STK10 utilizing public web servers. Metascape and the String database were used for functional and protein–protein interaction analyses. Results We found STK10 was enriched in blood & immune cells and overexpressed in AML. High STK10 expression was associated with poor overall survival, which was also identified in the subgroups of patients ≤ 60 years old and patients with non-high-risk cytogenetics. We demonstrated genes associated with STK10 were enriched in blood, spleen and bone marrow, influencing the immune function and biological process of AML. ITGB2 and ITGAM might directly interact with STK10 and were associated with poor prognosis. Besides, STK10 was associated with the infiltration of immune cells and immune checkpoints, like HLA-E, CD274 and GAL-9. Conclusions The present study was the original description of STK10 in AML and set the stage for developing STK10 as a new prognostic marker or therapeutic target for AML.

Spatiotemporal data fusion is a commonly-used and well-proven technique to enhance the application potential of multi-source remote sensing images. However, most existing methods have trouble in generating quality fusion results when areas covered by the images undergoes rapid land cover changes or images have substantial registration errors. While deep learning algorithms have demonstrated their capabilities for imagery fusion, it is challenging to apply deep-learning-based fusion methods in regions that experiences persistent cloud covers and have limited cloud-free imagery observations. To address these challenges, we developed a Multi-scene Spatiotemporal Fusion Network (MUSTFN) algorithm based on a Convolutional Neural Network (CNN). Our approach uses multi-level features to fuse images at different resolutions acquired by multiple sensors. Furthermore, MUSTFN uses the multi-scale features to overcome the effects of geometric registration errors between different images. Additionally, a multi-constrained loss function is proposed to improve the accuracy of imagery fusion over large areas and solve fusion and gap-filling problems simultaneously by utilizing cloud-contaminated images with the fine-tuning method. Compared with several commonly-used methods, our proposed MUSTFN performs better in fusing the 30-m Landsat-7 images and 500-m MODIS images over a small area that has undergone large changes (the average relative Mean Absolute Errors (rMAE) of the first four bands are 6.8% by MUSTFN as compared to 14.1% by the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), 12.8% by the Flexible Spatiotemporal Data Fusion (FSDAF), 8.4% by the Extended Super-Resolution Convolutional Neural Network (ESRCNN), 8.1% by the Spatiotemporal Fusion Using a Generative Adversarial Network (STFGAN)). In particularly for images at different resolutions with different registration accuracies (e.g., 16-m Chinese GaoFen-1 and 500-m MODIS), MUSTFN achieved fusion results of good quality with an average rMAE of 9.3% in spectral reflectance at the first four bands. Finally, we demonstrated the applicability of MUSTFN (average rMAE of 9.18%) when fusing long-term Landsat-8 composite images and MODIS images over a large region (830 km × 600 km). Overall, our results suggest the effectiveness of MUSTFN to address the challenges in imagery fusion, including rapid land cover changes between image acquisition dates, geometric misregistration between images and limited availabilities of cloud-free images. The program of MUSTFN is freely available at: https://github.com/qpyeah/MUSTFN.

Chromosome 1q21 aberration is one of the most common cytogenetic abnormalities in multiple myeloma, and is considered an important prognostic factor. The present study analyzed the clinical relevance and prognostic impact of 1q21 gain in 194 patients with newly diagnosed multiple myeloma treated with bortezomib-based regimens. 1q21 gain was detected in 45.9% (89/194) of patients, and those with 1q21 gain had a worse prognosis. Strikingly, our results showed that excluding the effects of other coinciding genetic anomalies, patients carrying at least four copies of 1q21 had worse survival outcome. Moreover, del(13q) strongly correlates with 1q21 gain, and the coexistence of del(13q) and 1q21 gain plays an important role in reducing PFS and OS times. Therefore, 1q21 gain should be considered a high-risk feature in multiple myeloma patients treated with a bortezomib-based regimen.

Efficient stimulus-responsive phosphorescence organic materials are attractive, but are extremely rare because of unclear design principles and intrinsically spin-forbidden intersystem crossing. Here, the authors present a facile strategy to achieve ultraviolet irradiation-responsive ultralong room-temperature phosphorescence in several simple amorphous polymer materials.

Floret-opening time (FOT) refers to the time between florets opening and closing within a day, and is a crucial agricultural trait for reproductive development, thermal tolerance and hybrid breeding in rice. However, little is known about the genetic basis and genes controlling FOT in rice. Here, we report the genetic mapping and transcriptome analysis of FOT in the japonica rice cultivar G23. Combining the QTLseqr and GradedPool-seq (GPS) methods, we located a major quantitative trait locus (QTL), qFOT6, on chromosome 6 in multiple years and under different environments. Integrating RNA-seq analysis, we selected 13 potential candidate genes in the qFOT6 interval that might be associated with FOT in G23. Taken together, our work uncovers a major QTL and potential candidate genes for FOT in rice, thus providing invaluable clues for rice breeding.

Tumor hypoxia can seriously impede the effectiveness of photodynamic therapy (PDT). To address this issue, two approaches, termed in situ oxygen generation and oxygen delivery, were developed. The in situ oxygen generation method uses catalysts such as catalase to decompose excess H2O2 produced by tumors. It offers specificity for tumors, but its effectiveness is limited by the low H2O2 concentration often present in tumors. The oxygen delivery strategy relies on the high oxygen solubility of perfluorocarbon, etc., to transport oxygen. It is effective, but lacks tumor specificity. In an effort to integrate the merits of the two approaches, we designed a multifunctional nanoemulsion system named CCIPN and prepared it using a sonication-phase inversion composition–sonication method with orthogonal optimization. CCIPN included catalase, the methyl ester of 2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid (CDDO-Me), photosensitizer IR780, and perfluoropolyether. Perfluoropolyether may reserve the oxygen generated by catalase within the same nanoformulation for PDT. CCIPN contained spherical droplets below 100 nm and showed reasonable cytocompatibility. It presented a stronger ability to generate cytotoxic reactive oxygen species and consequently destroy tumor cells upon light irradiation, in comparison with its counterpart without catalase or perfluoropolyether. This study contributes to the design and preparation of oxygen-supplementing PDT nanomaterials.

The flocculation that takes place in the central feedwell of the thickener plays a crucial role in the coal-slurry thickening process, which is not only complex but also largely influenced by the flow characteristics. A coupled computational fluid dynamics–population balance model (CFD–PBM) was used to model the complex flocculation-thickening behaviour in an industrial-scale gravity thickener. The initialisation parameters of the inlet flow were obtained through self-designed image-recognition experiments, and then the effects of different types of conical deflectors on the floc distribution were simulated and analysed using them. The results showed that, under the condition that the angle of the conical deflector’s sides in the vertical plane was known, a reasonable increase in the height of the bottom surface could reduce the annular spanwise vortices at the underflow of the feedwell, thereby avoiding the erosion of the inlet flow and the annular spanwise vortex on the floc deposition layer. However, excessive height on the part of the conical deflector could affect the flocculation effect of solid particles. For the same central feedwell size of the thickener as in the simulation, the best flocculation effect was achieved at an angle of α = 24° in the vertical plane of the conical deflector. Turbulence regulation of the conical deflector promotes the aggregation of fine particles in the fluid of the feedwell, providing a new method for the intensification of the flocculation-concentration process.

BackgroundMultiple myeloma (MM) is a highly heterogeneous disease with enormously variable outcomes. It remains to be a major challenge to conduct a more precise estimation of the survival of MM patients. The existing stratifications attached less importance to the prognostic significance of comorbidities. In the present study, we aimed to develop and validate a novel and simple prognostic stratification integrating tumor burden and comorbidities measured by HCT-CI.MethodWe retrospectively enrolled 385 consecutive newly diagnosed multiple myeloma (NDMM) patients in Xijing Hospital from January 2013 to December 2020. The cohort between January 2016 and December 2020 was selected as development cohort (N = 233), and the cohort between January 2013 and December 2015 was determined as validation cohort (N = 152). By using LASSO analysis and univariate and multivariable Cox regression analyses, we developed the MM-BHAP model in the way of nomogram composed of β2-MG, HCT-CI, ALB, and PBPC. We internally and externally validated the MM-BHAP model and compared it with ISS stage and R-ISS stage.ResultsThe MM-BHAP model was superior to the ISS stage and partially better than the R-ISS stage according to time-dependent AUC, time-dependent C-index, DCA, IDI, and continuous NRI analyses. In predicting OS, only the MM-BHAP stratification clearly divided patients into three groups while both the ISS stage and R-ISS stage had poor classifications in patients with stage I and stage II. Moreover, the MM-BHAP stratification and the R-ISS stage performed well in predicting PFS, but not for the ISS stage. Besides, the MM-BHAP model was also applied to the patients with age ≤65 or age >65 and with or without HRCA and could enhance R-ISS or ISS classifications.ConclusionsOur study offered a novel simple MM-BHAP stratification containing tumor burden and comorbidities to predict outcomes in the real-world unselected NDMM population.

The geolocation accuracy of spaceborne LiDAR (Light Detection And Ranging) data is important for quantitative forest inventory. Geolocation errors in Global Ecosystem Dynamics Investigation (GEDI) footprints are almost unavoidable because of the instability of orbital parameter estimation and GNSS (Global Navigation Satellite Systems) positioning accuracy. This study calculates the horizontal geolocation error of multiple temporal GEDI footprints using a waveform matching method, which compares original GEDI waveforms with the corresponding simulated waveforms from airborne LiDAR point clouds. The results show that the GEDI footprint geolocation error varies from 3.04 m to 65.03 m. In particular, the footprints from good orbit data perform better than those from weak orbit data, while the nighttime and daytime footprints perform similarly. After removing the system error, the average waveform similarity coefficient of multi-temporal footprints increases obviously in low-waveform-similarity footprints, especially in weak orbit footprints. When the waveform matching effect is measured using the threshold of the waveform similarity coefficient, the waveform matching method can significantly improve up to 32% of the temporal GEDI footprint datasets from a poor matching effect to a good matching effect. In the improvement of the ratio of individual footprint waveform similarity, the mean value of the training set and test set is about two thirds, but the variance in the test set is large. Our study first quantifies the geolocation error of the newest version of GEDI footprints (Version 2). Future research should focus on the improvement of the detail of the waveform matching method and the combination of the terrain matching method with GEDI waveform LiDAR.

After the iconic outburst of Zonag Lake in Hoh Xil of Tibetan Plateau (TP) in 2011, the causes of the collapse and its impact on the volume of water contained by the downstream lakes have highly been concerned, but the overall changes of the hydrological ecosystem and its impacts on the basin are yet not clear. This paper analyzes the hydrological system (lake area and hydrological connection) and ecosystem (sandstorm activity and vegetation growth status) changes and their impacts on the regional ecological environment after the outburst event, based on remotely sensed images from 2000 to 2020, meteorological observations, and field surveys. The results show that the outburst of Zonag Lake has not only changed the regional hydrology and ecosystem pattern but also caused a trend of degradation in the ecological environment of Zonag Lake Basin. Some lambing areas and active areas of Tibetan antelope in the area are being buried and eroded by the sandstorm. The downstream Yanhu Lake has risen to the highest level and overflowed through the emergency diversion engineering. These impacts are continuously threatening the health of the ecological environment of the world natural heritage site in Hoh Xil, the safety of Qinghai-Tibet highway, Qinghai-Tibet railway, and other engineering facilities, as well as the stability of fluvial geomorphology in the northern most sources of Yangtze River.

Artificial and natural water bodies, such as reservoirs, ponds, rivers and lakes, are important components of water-related ecosystems; they are also important indicators of the impact of human activities and climate change on surface water resources. However, due to the global and regional lack of artificial and natural water bodies data sets, understanding of the changes in water-related ecosystems under the dual impact of human activities and climate change is limited and scientific and effective protection and restoration actions are restricted. In this paper, artificial and natural water bodies data sets for China are developed for the years 2000, 2005, 2010, 2015 and 2020 based on satellite remote sensing surface water and artificial water body location sample data sets. The characteristics and causes of the temporal and spatial distributions of the artificial and natural water bodies are also analyzed. The results revealed that the area of artificial and natural water bodies in China shows an overall increasing trend, with obvious differences in spatial distribution during the last 20 years, and that the fluctuation range of artificial water bodies is smaller than that of natural water bodies. This research is critical for understanding the composition and long-term changes in China’s surface water system and for supporting and formulating scientific and rational strategies for water-related ecosystem protection and restoration.

Surface water is a highly dynamical object on the earth’s surface. At present, satellite remote sensing is the most effective way to accurately depict the temporal and spatial variation characteristics of surface water on a large scale. In this study, a region-adaptive random forest algorithm is designed on the Google Earth Engine (GEE) for automatic surface water mapping by using data from multi-sensors such as Landsat 7 ETM+, Landsat 8 OLI, and Sentinel-1 SAR images as source data, and China as a case study region. The visual comparison of the mapping results with the original images under different landform areas shows that the extracted water body boundary is consistent with the water range in the image. The cross-validation with the JRC GSW validation samples shows a very high precision that the average producer’s accuracy and average user’s accuracy of water is 0.933 and 0.998, respectively. The average overall accuracy and average kappa is 0.966 and 0.931, respectively. The independent verification results of lakes with different areas also prove the high accuracy for our method, with a maximum average error of 3.299%. These results show that the method is an ideal way for large-scale surface water mapping with a high spatial–temporal resolution.

Developing novel long-lived room-temperature polymer phosphorescence (RTPP) materials could significantly expand their application scope. Herein, a series of RTPP materials based on eight simple vanilla derivatives for security ink application are reported. Attributed to strong mutual hydrogen bonding with polyvinyl alcohol (PVA) matrix, vanilla-doped PVA films exhibit ultralong phosphorescence emission under ambient conditions observed by naked eyes, where methyl vanillate shows the longest emission time up to 7 s. Impressively, when vanilla-doped PVA materials are utilized as invisible security inks, and the inks not only present excellent luminescent emission stability under ambient conditions but also maintain perfect reversibility between room temperature and 65°C for multiple cycles. Owing to the unique RTPP performance, an advanced anticounterfeiting data encoding/reading strategy based on handwriting technology and complex pattern steganography is developed.

This study aimed to compare the efficacy of allogeneic stem cell transplantation (allo-SCT) versus autologous SCT (auto-SCT) in patients with relapsed or refractory B-cell non-Hodgkin lymphoma (B-NHL). Medline, CENTRAL, and EMBASE databases through December 31, 2019 were searched. The primary endpoints were overall survival (OS) and progression-free survival (PFS) rates. The secondary outcomes include transplant-related mortality (TRM), event-free survival, relapse/or progression, and nonrelapse mortality (NRM). The 18 retrospective studies enrolled 8,058 B-NHL patients (allo-SCT = 1,204; auto-SCT = 6,854). The OS was significantly higher in patients receiving auto-SCT than allo-SCT (pooled odds ratio [OR]: 1.69, 95% confidence interval [CI]: 1.29 to 2.22, P < 0.001), but no significant difference was found in PFS (pooled OR: 0.98, 95% CI: 0.69 to 1.38, P = 0.891). Auto-SCT patients also had lower TRM and NRM (TRM: OR = 0.23, P < 0.001; NRM: OR = 0.16, P < 0.001), but higher relapse or progression rate (OR = 2.37, P < 0.001) than allo-SCT patients. Subgroup analysis performed for different grades and subtypes of B-NHL showed higher OS in auto-SCT patients with high-grade B-NHL and diffused large B-cell lymphoma (DLBCL). There was, nevertheless, higher PFS in allo-SCT patients with low-grade B-NHL and follicular lymphoma (FL), and lower PFS in allo-SCT patients with DLBCL than their auto-SCT counterparts. In conclusion, the meta-analysis demonstrated that relapsed or refractory B-NHL patients who received auto-SCT have improved OS than those treated with allo-SCT, especially among those with DLBCL, but lower PFS among those with FL. However, the study is limited by a lack of randomized trials, patients’ heterogeneity, and possible selection bias.

The gas turbine engine is a widely used thermodynamic system for aircraft. The demand for quantifying the uncertainty of engine performance is increasing due to the expectation of reliable engine performance design. In this paper, a fast, accurate, and robust uncertainty quantification method is proposed to investigate the impact of component performance uncertainty on the performance of a classical turboshaft engine. The Gaussian process model is firstly utilized to accurately approximate the relationships between inputs and outputs of the engine performance simulation model. Latin hypercube sampling is subsequently employed to perform uncertainty analysis of the engine performance. The accuracy, robustness, and convergence rate of the proposed method are validated by comparing with the Monte Carlo sampling method. Two main scenarios are investigated, where uncertain parameters are considered to be mutually independent and partially correlated, respectively. Finally, the variance-based sensitivity analysis is used to determine the main contributors to the engine performance uncertainty. Both approximation and sampling errors are explained in the uncertainty quantification to give more accurate results. The final results yield new insights about the engine performance uncertainty and the important component performance parameters.

Supersonic civil aircraft is of a promising area in the development of future civil transport, and aircraft propulsion system is one of the key issues which determine the success of the aircraft. To get a good conceptual design and performance investigation of the supersonic civil aircraft engine, in this article, a fast, versatile as well as trust-worthy numerical simulation platform was established to analyze the Mach 4 turbine-based combined cycle (TBCC) engine concept so as to be applied to the supersonic civil aircraft. First, a quick and accurate task requirement analysis module was newly established to analyze the mission requirement of the Mach 4 supersonic civil aircraft. Second, the TBCC engine performance simulation model was briefly presented and the number of engines on the supersonic civil aircraft was analyzed, considering single engine inoperative. Third, the Stone model and the DLR method were investigated to estimate the engine jet noise and the NOx emission of the Mach 4 supersonic civil aircraft. Finally, a multiobjective optimization tool made up of a response surface method and a genetic algorithm was developed to optimize the design parameters and the control law of the TBCC engine, in order to make the Mach 4 supersonic civil aircraft engine with better performance, lower noise, and lower emissions. The uniqueness of the developed analysis tool lies in that it affords a numerical simulation platform capable of investigating the task requirement analysis module of the supersonic civil aircraft, engine jet noise prediction model, and the NOx emission prediction model, as well as a multiobjective performance optimization tool, which is beneficial for the conceptual design and performance research of Mach 4 supersonic civil aircraft’s propulsion system.

During the past decades, agents with novel mechanisms of action, such as monoclonal antibodies (MAbs) and histone deacetylase inhibitors (HDACis) have been applied to treat relapsed or refractory multiple myeloma (RRMM). The treatment outcomes of MAbs versus HDACi in combination with bortezomib or lenalidomide plus dexamethasone remain unknown. We conducted this meta-analysis to compare indirectly the efficacy and safety of MAbs and HDACis in combination with bortezomib or lenalidomide plus dexamethasone. Six trials (eight articles) were included in the meta-analysis with 3270 RRMM patients enrolled. We synthesized hazard ratios (HRs) for progression-free survival (PFS) and overall survival (OS), risk ratios (RRs) for complete response (CR),very good partial response (VGPR), overall response (OR), progressive disease plus stable disease (PD + SD) and common at least grade 3 adverse events, and their corresponding 95%confidence intervals (95% CI). Treatment with MAbs in combination with bortezomib or lenalidomide plus dexamethasone resulted in longer PFS (HR 0.83, 95% CI: 0.66–0.98), fewer incidences of at least grade 3 thrombocytopenia (RR 0.35, 95% CI: 0.23–0.53), neutropenia (RR 0.70, 95% CI: 0.51–0.96), and sense of fatigue (RR 0.37, 95% CI: 0.17–0.82) than HDACis. The daratumumab plus bortezomib or lenalidomide and dexamethasone might significantly improve PFS in comparison with HDACis plus bortezomib or lenalidomide and dexamethasone (HR 0.55, 95% CI: 0.40–0.74). In conclusion, MAbs may be superior to HDACis in achieving longer PFS and may be better tolerated when in combination therapy with bortezomib or lenalidomide plus dexamethasone.

One advantage of the adaptive cycle engine (ACE) is its ability of throttling with constant airflow by the combined control of variable geometries, resulting in an improvement of spillage drag. However, the improvement is achieved at risk of a complex technical solution and control. This article investigates the selection scheme of variable geometries and engine configuration. It focuses on the performance of a three-stream ACE during throttling, whose configuration and control schedule are simpler than other types of ACEs. Five variable geometries are selected from seven available options through comparison analysis. The uninstalled thrust decreases from 100% to 60.36% during the subsonic throttling and to 59.81% during the supersonic throttling. Benefitting from the decreased spillage drag, the installed performance of the three-stream ACE is improved to some degree during throttling. This improvement is less than the result of a three-bypass ACE, whose configuration and control schedule are more complex. Thus, the three-stream ACE is a compromise design considering the technical risk and variable cycle characteristic, which is a better platform to verify the component technology and control schedule for the further research on a more complex type of ACE.

In order to develop high-performance dielectric materials, poly(arylene ether nitrile)-based composites were fabricated by employing surface-hydroxylated calcium copper titanate (CCTO) particles. The results indicated that the surface hydroxylation of CCTO effectively improved the interfacial compatibility between inorganic fillers and the polymer matrix. The composites exhibit not only high glass transition temperatures and an excellent thermal stability, but also excellent flexibility and good mechanical properties, with a tensile strength over 60 MPa. Furthermore, the composites possess enhanced permittivity, relatively low loss tangent, good permittivity-frequency stability and dielectric-temperature stability under 160 °C. Therefore, it furnishes an effective path to acquire high-temperature-resistant dielectric materials for various engineering applications.

The most remarkable variable cycle characteristic of the variable cycle engine (VCE) is that it keeps airflow almost constant during subsonic cruise throttling by modulating variable geometries, which can efficiently decrease spillage drag and increase installed thrust. One of the most critical challenges for the modulation lies in completely maintaining airflow, as well as avoiding specific fuel consumption (SFC) degradation during throttling. This has resulted in a need to investigate the modulation regulation of the adaptive cycle engine (ACE) which is a new concept for VCE and has greater potential for flexibly modulating airflow and pressure ratio. Thus, the aim of this paper is to study the variable geometries’ modulation schedule of ACE in maintaining airflow during throttling. A configuration of an ACE concept and its modeling study are first put forward. Then, the control schedule is researched via the combination of sensibility analysis and basic working principle instead of optimizing them directly. Results show that when the net thrust decreases from 100% to about 55% during subsonic cruise and to 32% during the supersonic cruise, the demand airflow of the engine is kept almost constant, which greatly improves the installed performance during throttling.