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About Vladimir Ilyich as a scientist, colleague, teacher and person are told by those who had the opportunity to cooperate with him at different times. His memories reflect his main personal characteristics: passionate devotion to the cause of science, integrity and attitude to people.

Zhan T, Zhu Q, Han Z, et al. Cancer Manag Res. 2020;12:1483–1492. The authors have advised Figure 4C on page 1490 is incorrect. Due to an error at the time of figure assembly Figure 4D and Figure 4C were inadvertently duplicated. The correct Figure 4 is shown below. Figure 4 miR-455-3p restrains Wnt/β-catenin signaling via TAZ. (A and B) Expression of β-catenin, Cyclin D and C-myc in pancreatic cancer cells transfected with miR-455-3p mimic or miR-455-3p mimic plus TAZ expression vector was detected by qPCR. (C and D) Western blot analysis of β-catenin, Cyclin D and C-myc in PANC1 and MIAPaCa2 cells transfected with miR-455-3p mimic or miR-455-3p mimic plus TAZ expression vector β-actin is used as loading control vs miR-455-3p mimics/mimic control group, miR-455-3p mimics/miR-455-3p mimics+TAZ group. *p

We aimed to investigate the timing of once-daily thoracic radiotherapy (TTRT) in patients with limited-stage small cell lung cancer (LS-SCLC) in the first-line concurrent chemoradiotherapy era. A total of 445 patients with LS-SCLC receiving concurrent chemoradiotherapy were reviewed. Nonlinear analysis by restricted cubic splines was used to determine the relationship between timing of TRT (TTRT) and PFS or OS. OS and PFS in different TTRT groups were compared using log-rank tests and multivariable analyses. The cumulative incidence of locoregional recurrence (LRR), brain metastases (BM), and extracranial distant metastases (EDM) were investigated using competing risk analyses. Adverse events were also compared. The median duration of follow-up was 64 months. There was a non-linear relationship between TTRT and PFS (P = 0.002) or OS (P < 0.001). When TRT started from 31 days to 63 days, improved 5-year PFS (37.0%; P = 0.001) and OS (49.7%; P < 0.001) and decreased 5-year EDM (27.9%; P = 0.009) were achieved compared with the ≤30-day group (19.5%; 32.0%; 43.3%) and >63-day group (23.7%; 24.2%; 43.5%). However, no significant difference in overall survival was observed in groups divided by actual chemotherapy cycle. A downward trend was seen in the incidence of myelosuppression of grade 3–4 in different TTRT groups (P = 0.04). Appropriate treatment timing window might exist in once-daily TRT with concurrent chemotherapy. Delaying in combination of TRT and prescribed chemotherapy cycle may impair the survival outcomes. [ABSTRACT FROM AUTHOR]

Abstract Sirolimus (SR) is a macrolide with antifungal and antitumor immunosuppressant properties, classified as a selective inhibitor of mammalian target of rapamycin (mTOR). In this study, an ionic in situ gel of SR (SR-SUS-ISG) was formulated using gellan gum, exhibiting stability regardless of temperature and pH variations, causing minimal irritation. Harnessing the physiological conditions of the eye, SR-SUS-ISG underwent gelation upon contact with ions, increasing drug viscosity and prolonging retention on the ocular surface. Concurrently, SR-SUS-ISG displayed favorable shear dilution properties, reducing viscosity at ambient temperature, enhancing fluidity, and facilitating convenient packaging and transport. Biocompatibility assessments on both human corneal epithelial cells and rabbit eyes demonstrated that SR-SUS-ISG could well be tolerated. Pharmacokinetic investigations in rabbit ocular aqueous humor revealed sustained release, improved corneal penetration, and enhanced bioavailability. Additionally, in a rat corneal alkali burn model, SR-SUS-ISG exhibited inhibitory effects on corneal neovascularization, associated with decreased levels of the inflammatory factors VEGF and MMPs. These findings suggested that SR-SUS-ISG held promise as an effective ocular drug delivery system. Graphical Abstract

Abstract The accurate perception of multiple flight parameters, such as the angle of attack, angle of sideslip, and airflow velocity, is essential for the flight control of micro air vehicles, which conventionally rely on arrays of pressure or airflow velocity sensors. Here, we present the estimation of multiple flight parameters using a single flexible calorimetric flow sensor featuring a sophisticated structural design with a suspended array of highly sensitive vanadium oxide thermistors. The proposed sensor achieves an unprecedented velocity resolution of 0.11 mm·s−1 and angular resolution of 0.1°. By attaching the sensor to a wing model, the angles of attack and slip were estimated simultaneously. The triaxial flight velocities and wing vibrations can also be estimated by sensing the relative airflow velocity due to its high sensitivity and fast response. Overall, the proposed sensor has many promising applications in weak airflow sensing and flight control of micro air vehicles.

In view of bottlenecks encountered in the process of turnout laying and replacement on high-speed railways such as substantial construction difficulties, low efficiency, intensive labor workload, and high risk, this paper proposes a control method of intelligent turnout laying and replacement equipment with combined gantry cranes for high-speed railways. It is proposed to utilize a control strategy of asynchronous transverse movement and synchronous tilting of the combined gantry cranes to handle the rotation and longitudinal motion of large components respectively. A theoretical mathematical modeling analysis is performed for the turnout laying and replacement equipment with combined gantry cranes focusing on the rotation and longitudinal movement operations. Moreover, considering the flexible nature of chains in the real construction process of combined gantry cranes, a self-learning algorithm is incorporated to facilitate flexible and highly precise multi-crane cooperative micro-motion control. The experimental results from field operations showcases adopting the control method proposed in this article, stable and reliable rotation and longitudinal movement by the combined gantry cranes, with an operational error of less than 10 mm, achieving full compliance with the requirements of engineering applications demonstrates.

In this paper, a generalized-mode phase averaging technique is proposed to suppress air turbulence and random noise in optical shop testing. This approach eliminates the need to repeatedly unwrap and thus greatly improves processing efficiency. By removing the random tilt component of the wrapped phase, a set of wrapped phases that are corrupted by random vibrations can be unified into the same mode, some of which obey a circular distribution. Therefore, the circular mean technique can be used for wrapped phase averaging; only one unwrapping process is required for a set of wrapped phases. A criterion based on maximum likelihood estimation is proposed to determine scenarios for the use of this method. The effects of noise and air disturbances on this method are discussed. Finally, the effectiveness of the method is demonstrated by simulations and experiments.

As medical facilities are usually built at urban areas, special concrete aggregates and evaluation methods are needed to optimize the design of concrete walls by balancing density, thickness, material composition, cost, and other factors. Carbon treatment rooms require a high radiation shielding requirement, as the neutron yield from carbon therapy is much higher than the neutron yield of protons. In this case study, the maximum carbon energy is 430 MeV/u and the maximum current is 0.27 nA from a hybrid particle therapy system. Hospital or facility construction should consider this requirement to design a special heavy concrete. In this work, magnetite is adopted as the major aggregate. Density is determined mainly by the major aggregate content of magnetite, and a heavy concrete test block was constructed for structural tests. The compressive strength is 35.7 MPa. The density ranges from 3.65 g/cm3 to 4.14 g/cm3, and the iron mass content ranges from 53.78% to 60.38% from the 12 cored sample measurements. It was found that there is a linear relationship between density and iron content, and mixing impurities should be the major reason leading to the nonuniform element and density distribution. The effect of this nonuniformity on radiation shielding properties for a carbon treatment room is investigated by three groups of Monte Carlo simulations. Higher density dominates to reduce shielding thickness. However, a higher content of high-Z elements will weaken the shielding strength, especially at a lower dose rate threshold and vice versa. The weakened side effect of a high iron content on the shielding property is obvious at 2.5 μSv/h. Therefore, we should not blindly pursue high Z content in engineering. If the thickness is constrained to 2 m, then the density can be reduced to 3.3 g/cm3, which will save cost by reducing the magnetite composition with 50.44% iron content. If a higher density of 3.9 g/cm3 with 57.65% iron content is selected for construction, then the thickness of the wall can be reduced to 174.2 cm, which will save space for equipment installation.

AbstractImmune ophthalmopathy is a collection of autoimmune eye diseases. Immunosuppressants are drugs that can inhibit the body’s immune response. Considering drug side effects such as hepatorenal toxicity and the unique structure of the eye, incorporating immunosuppressants into ophthalmic nanodrug delivery systems, such as microparticles, nanoparticles, liposomes, micelles, implants, and in situ gels, has the advantages of improving solubility, increasing bioavailability, high eye-target specificity, and reducing side effects. This study reviews recent research and applications of this aspect to provide a reference for the development of an ophthalmic drug delivery system.

The fatigue performance of dissimilar metal welded components has an important influence on the service reliability of spacecraft. The fatigue life and fatigue fracture mechanism of dissimilar metal welded joints of QCr0.8 copper alloy and 1Cr21Ni5Ti stainless steel were investigated. The copper-steel composite plate was properly prepared by electron beam welding. The microstructure and composition of welding seam were characterized and analyzed by metallographic microscope. Mechanical properties of welded joints were tested using electronic tensile testing machine and fatigue testing machines. Scanning electron microscopy was used to observe the fatigue fracture in different cycles. The results show that the overall metallurgical bonding of the two metals is good, however, the local fusion zone on the steel side has a large area and extends into the weld from the steel base. The tensile specimens of the copper-steel electron beam welding all fracture at the minimum section of the weld, and the average fatigue limit of the fatigue specimens is 48.04 MPa and they all fracture at the minimum section of the weld. In the high cycle fatigue sample, a single crack source is observed at the endpoint of the weld top surface, while in the low cycle fatigue sample, more crack sources are observed on the top and bottom surface and inside of the weld. The final fracture zone of both samples is located in the copper alloy matrix.It can be seen in the process of fatigue fracture, the number of crack sources is different between high and low cycle fracture, but in both cases, the cracks are easy to initiate at the minimum section of the weld and spread to the copper alloy matrix.

Abstract Growing evidence suggests altered oral and gut microbiota in autism spectrum disorder (ASD), but little is known about the alterations and roles of phages, especially within the oral microbiota in ASD subjects. We enrolled ASD (n = 26) and neurotypical subjects (n = 26) with their oral hygiene controlled, and the metagenomes of both oral and fecal samples (n = 104) are shotgun-sequenced and compared. We observe extensive and diverse oral phageome comparable to that of the gut, and clear signals of mouth-to-gut phage strain transfer within individuals. However, the overall phageomes of the two sites are widely different and show even less similarity in the oral communities between ASD and control subjects. The ASD oral phageome exhibits significantly reduced abundance and alpha diversity, but the Streptococcal phages there are atypically enriched, often dominating the community. The over-representation of Streptococcal phages is accompanied by enriched oral Streptococcal virulence factors and Streptococcus bacteria, all exhibiting a positive correlation with the severity of ASD clinical manifestations. These changes are not observed in the parallel sampling of the gut flora, suggesting a previously unknown oral-specific association between the excessive Streptococcal phage enrichment and ASD pathogenesis. The findings provide new evidence for the independent microbiome-mouth-brain connection, deepen our understanding of how the growth dynamics of bacteriophages and oral microbiota contribute to ASD, and point to novel effective therapeutics.

One of the key issues in climate risk management is to develop climate resilient infrastructure so as to ensure safety and sustainability of urban functioning systems as well as mitigate the adverse impacts associated with increasing climate hazards. However, conventional methods of assessing risks do not fully address the interaction of various subsystems within the city system and are unable to consolidate diverse opinions of various stakeholders on their assessments of sector-specific risks posed by climate change. To address this gap, this study advances an integrated-systems-analysis tool - Climate Risk Assessment of Infrastructure Tool (CRAIT), and applies it to analyze and compare the extent of risk factor exposure and vulnerability over time across five critical urban infrastructure sectors in Shanghai and Shenzhen, two cities that have distinctive geo-climate profiles and histories of infrastructure development. The results show significantly higher level of variation between the two cities in terms of vulnerability levels than that of exposure. More specifically, the sectors of critical buildings, water, energy, and information & communication in Shenzhen have significantly higher vulnerability levels than Shanghai in both the 2000s and the 2050s. We further discussed the vulnerability levels of subsystems in each sector and proposed twelve potential adaptation options for the roads system based on four sets of criteria: technical feasibility, flexibility, co-benefits, and policy compatibility. The application of CRAIT is bound to be a knowledge co-production process with the local experts and stakeholders. This knowledge co-production process highlights the importance of management advancements and nature-based green solutions in managing climate change risk in the future though differences are observed across the efficacy categories due to the geographical and meteorological conditions in the two cities. This study demonstrates that this knowledge co-creation process is valuable in facilitating policymakers' decision-making and their feedback to scientific understanding in climate risk assessment, and that this approach has general applicability for cities in other regions and countries.

The effectiveness of adaptive measures tackling the effects of climate change is dependent on robust climate projections. This becomes even more important in the face of intensifying extreme events. One example of these events is flooding, which embodies a major threat to highly vulnerable coastal urban areas. This includes eastern Asia, where multiple coastal megacities are located, e.g. Shanghai and Shenzhen. While the ability of general circulation models (GCMs) and regional climate models (RCMs) to project atmospheric changes associated with these events has improved, systematic errors (biases) remain. This study therefore assess capabilities of improving the quality of regional climate projections for eastern Asia. This is performed by evaluating an ensemble consisting of bias adjustment methods, GCM-RCM model runs and future emission scenarios based on representative concentration pathways (RCP) obtained from EAS-CORDEX. We show that bias adjustment significantly improves the quality of model output and best results are obtained by applying quantile delta mapping. Based on these results we evaluate potential future changes in crucial hydrometeorological predictors, univariate extreme events and compound extreme events, focusing on high wind speeds and extreme precipitation. Key findings include an increase in daily maximum temperature of 1.5 to nearly 4 °C, depending on the scenario, as well as increased levels of precipitation under RCP 8.5. Furthermore, a distinct intensification of extreme events including high temperatures and heavy precipitation is detected and this increase exceeds the increase of the overall mean of these predictors. The annual number of compound events including heavy precipitation and extreme wind speeds shows a significant increase of up to 50% for RCP 8.5 in the South China Sea as well as the adjacent coastal areas.

Hyperspectral image change detection can provide timely change information on the surface of the earth, which is essential for urban and rural planning and management. Due to the higher spectral resolution, hyperspectral images are often used to detect finer changes. Aiming at the problem of change detection by using hyperspectral image, a hyperspectral change detection method based on collaborative sparsity and nonlocal low-rank tensor is proposed. This method first obtains hyperspectral differential image at different time points, and then extracts different nonlocal similar block tensor clusters according to the nonlocal distribution characteristics of the image blocks in the differential image. Then, based on collaborative sparse regularization and low-rank regularization, a change detection model using collaborative sparsity and non-local low-rank tensor is established, and the representa-tion coefficient is obtained by solving the model using the alternating direction method of multipliers. Finally, the projection residuals of the tensor in different categories are obtained according to the representation coefficients, and then the projection residual minimization criterion is judged whether the tensor has changed. Experiments on Farm-land and Urban area in San Francisco City datasets demonstrate that the proposed method can achieve much better changes detection accuracy.

The increasing prevalence of non-alcoholic fatty liver disease (NAFLD), which is a progressive disease, has exerted huge a healthcare burden worldwide. New investigations have suggested that the gut microbiota closely participates in the progression of NAFLD through the gut–liver axis or gut–brain–liver axis. The composition of the microbiota can be altered by multiple factors, primarily dietary style, nutritional supplements, or exercise. Recent evidence has revealed that gut microbiota is involved in mitochondrial biogenesis and energy metabolism in the liver by regulating crucial transcription factors, enzymes, or genes. Moreover, microbiota metabolites can also affect mitochondrial oxidative stress function and swallow formation, subsequently controlling the inflammatory response and regulating the levels of inflammatory cytokines, which are the predominant regulators of NAFLD. This review focuses on the changes in the composition of the gut microbiota and metabolites as well as the cross-talk between gut microbiota and mitochondrial function. We thus aim to comprehensively explore the potential mechanisms of gut microbiota in NAFLD and potential therapeutic strategies targeting NAFLD management.

Climate change and rapid urbanization have made it difficult to predict the risk of pollution in cities under different types of rainfall. In this study, a data-driven approach to quantify the effects of rainfall characteristics on river pollution was proposed and applied in a case study of Shiyan River, Shenzhen, China. The results indicate that the most important factor affecting river pollution is the dry period followed by average rainfall intensity, maximum rainfall in 10 min, total amount of rainfall, and initial runoff intensity. In addition, an artificial neural network model was developed to predict the event mean concentration (EMC) of COD in the river based on the correlations between rainfall characteristics and EMC. Compared to under light rain (< 10 mm/day), the predicted EMC was five times lower under heavy rain (25–49.9 mm/day) and two times lower under moderate rain (10–24.9 mm/day). By converting the EMC to chemical oxygen demand in the river, the pollution load under non-point-source runoff was estimated to be 497.6 t/year (with an accuracy of 95.98%) in Shiyan River under typical rainfall characteristics. The results of this study can be used to guide urban rainwater utilization and engineering design in Shenzhen. The findings also provide insights for predicting the risk of rainfall-runoff pollution and developing related policies in other cities.

Remote sensing is widely used for lake-water-quality monitoring, but the inversion of the total nitrogen (TN) and total phosphorus (TP) of rivers and non-optical parameters is still a difficult problem. The use of high spatial and temporal resolution multispectral imagery combined with machine learning techniques is an effective solution for this difficulty. Three machine learning methods based on support vector regression (SVR), neural network (NN) and random forest (RF) were used to invert TN and TP using actual water-quality measurement data and Sentine-2 remote-sensing images, and analyzed the factors influencing water quality in terms of pollutant emissions and land use. The results show that RF performs the best in both TN (R2 = 0.800, RMSE = 0.640, MSE = 0.400, MAE = 0.480) and TP (R2 = 0.830, RMSE = 0.033, MSE = 0.001, MAE = 0.022) inversion models, and that the optimal selection of feature variables improves model performance. The TN and TP concentrations in the Minjiang River Meishan Water Function Development Zone were the highest in the downstream section and in 2018. Analysis of the factors influencing water quality shows that pollution sources and amounts were closely related to land-use types, and land use in riparian zones at different spatial scales had different degrees of impact on water quality.

Nepheloid layers are widely distributed in the marine environment, and their formation and evolution pose many challenges to the current understanding of ocean dynamics and marine sedimentology. In sediment transport processes, nepheloid layers significantly contribute to the exchange of sediment between the continental shelf and the slope. In this paper, we summarize the global research trends on nepheloid layers. In total, 689 publications from 1990 to 2022 were collected from the Web of Science and analyzed using bibliographic software, including Bibliometrix, VOSviewer, CiteSpace, and CorText. Based on these publications, past and present popular research on nepheloid layers is examined and evaluated. The trends in nepheloid layer research are summarized by analyzing keywords, article references, countries, institutions, and authors. Finally, prospects and several key questions related to nepheloid layers are concluded, which can potentially guide future studies. The bibliographic analysis can provide new insights into the history of nepheloid layers. The results also provide valuable information for other researchers and programs investigating geological, geophysical, and biogeochemical processes.

In response to urban pluvial flooding and pollution, the Chinese government proposed a “sponge city” policy in 2013 that aims to improve urban stormwater management and promote sustainable urban development. However, at present, sponge city construction is still in its exploratory stage. It is still not clear which models are capable of simulating the six key processes (i.e., “retention,” “infiltration,” “storage,” “purification,” “discharge,” and “utilization”) of sponge city practices. Its various benefits (e.g., social, economic and environmental benefits) have not yet been systematically investigated in the context of the sponge city. In this study, we reviewed and compared 19 urban stormwater management models (including 13 hydrological models and 10 decision-support tools, as there are 4 overlap ones) and investigated their application in China. Firstly, we examined the mechanisms behind the hydrological models and compared the abilities of the models to simulate various processes. Secondly, we analyzed what kinds of benefits can be addressed by these decision support tools (DSTs). Finally, we discussed the applications and limitations of the models in various climate zones in China. The findings suggest that none of the models consider the impact of climate change on the sponge city practices (SCP) and none of DSTs can simulate the negative performance of SCP. Furthermore, the lack of sufficient databases in China limited the applications of many of the models. Additionally, we found that the hydrological processes corresponding to “storage” were given more attention in southern China, and “infiltration” of stormwater was of greater concern in northern China. In the context of sponge city construction, this paper provides suggestions for future model development of urban stormwater management in China, such as the development of a stormwater database and the incorporation of long-term climate change impacts into the model.

Coastal cities like Shenzhen are confronting escalating flood risks under the combined impact of climate change and rapid urbanization, especially the tropical cyclones (TC)-induced flood. Incorporating the impact of climate change and urbanization on the flood, this study constructed a new TC-induced flood model on western Shenzhen embedded with a unique statistical approach. Based on extensive historical data and machine learning techniques, the temporal characteristics and changes of flooding were revealed. The results reveal an increase in the frequency of TC-induced floods between 1964–2022, especially after the 1990s, which is attributed to a decrease in the distance of the location of the maximum intensity of TCs (observed within an 800 km range of the study area) relative to the land, averaging a reduction of 11.4 km per decade. This shift towards land is likely due to changes in the locations of TC genesis. Furthermore, the ‘rainfall sea level’ threshold for western Shenzhen was accordingly derived from the results of modelling, which would enable decision-makers to quickly assess TC-induced flood risks. The study’s proposed methods offer alternative approaches for predicting TC-induced floods in regions where the gathering of hydro-meteorological data is challenging or where economic and technological resources are limited.

Brimonidine tartrate (BRT) is a highly selective α2 adrenergic receptor agonist as treatment for patients with open angle glaucoma and high intraocular pressure. The objective of this study was to formulate an ophthalmic ion-sensitive in situ gel (ISG) of BRT to increase the retention time of the drug and its bioavailability. The optimum formulation of 2 mg/mL BRT-ISG was obtained with 0.45% gellan gum as the gel matrix. In vitro release results showed that the water-soluble drug bromonidine tartrate in ocular in situ gels exhibited a high burst effect and fast release in solution. The results of dialysis membrane permeation showed that there was a significant difference between the commercially available and BRT-ISG groups after 45 min. The results of the pre-corneal retention study indicated that gellan gum can effectively prolong ocular surface retention. Preliminary stability results showed that it should be stored in a cool and dark place, and the formulation under long-term preservation can be basically stable. The pharmacokinetic study of the BRT-ISG in the anterior chamber of the rabbit eye was studied by microdialysis technique, and microdialysis samples were analyzed by LC-MS/MS. The pharmacokinetic study showed that the BRT-ISG reached Cmax (8.16 mg/L) at 93 min after administration, which was 2.7 times that of the BRT eye drops, and the AUC(0-t) (1397.08 mg·min/L) was 3.4 times that of the BRT eye drops. The optimal prescription can prolong the retention time of BRT in front of the cornea and significantly improve the bioavailability of BRT in the eye. Combined with the results of in vitro release, permeation and pre-corneal retention studies, the improvement of BRT-ISG bioavailability in rabbit eyes was found to be mainly due to the retention effect after the mixture of ISG and tears.

Unmanned Aerial Vehicles (UAVs) autonomous approaching and landing on mobile platforms always play an important role in various application scenarios. Such a complicated autonomous task requires an integrated multi-sensor system to guarantee environmental adaptability in contrast to using each sensor individually. Multi-sensor fusion perception demonstrates great feasibility to compensate for adverse visual events, undesired vibrations of inertia sensors, and satellite positioning loss. In this paper, a UAV autonomous landing scheme based on multi-sensor fusion is proposed. In particular, Ultra Wide-Band (UWB) sensor, Inertial Measurement Unit (IMU), and vision feedback are integrated to guide the UAV to approach and land on a moving object. In the approaching stage, a UWB-IMU-based sensor fusion algorithm is proposed to provide relative position estimation of vehicles with real time and high consistency. Such a sensor integration addresses the open challenge of inaccurate satellite positioning when the UAV is near the ground. It can also be extended to satellite-denied environmental applications. When the landing platform is detected by the onboard camera, the UAV performs autonomous landing. In the landing stage, the vision sensor is involved. With the visual feedback, a deep-learning-based detector and local pose estimator are enabled when the UAV approaches the landing platform. To validate the feasibility of the proposed autonomous landing scheme, both simulation and real-world experiments in extensive scenes are performed. As a result, the proposed landing scheme can land successfully with adequate accuracy in most common scenarios.

In this work, we use a three-dimensional computational fluid dynamics (CFD) simulation to comprehend how the two wing arrangement variables, i.e., inner/outer wing proportion and mid-stroke dihedral, affect the lift characteristic of a bat-inspired span foldable flapping wing. The employed flapping mechanism is based on previous work. In this study, the structure parameters of the flapping mechanism remain unchanged across all simulations. Based on the CFD results, the tendency and work point regarding maximum lift generation can be found by changing both of the variables. As a result, when modifying the inner/outer wing proportion without changing the total wing shape and area, the maximum time-averaged lift appears in the case of the inner wing occupying half of the semi-span. In addition, when changing the dihedral, the maximum time-averaged lift was obtained when the inner wing dihedral was equal to zero. To discuss the lift variation of the foldable flapping wing, pressure distribution and vorticity of the flow field at certain time points were provided corresponding to the instantaneous lift curves. The conclusions of this research are able to help understand the wing arrangement of birds and bats issued from natural selection, and also support the future design of flapping wing micro-aerial-vehicles.

This study focuses on the aerodynamics of the smallest flying insects’ bristled wings. We measured and analyzed wing morphological data from 38 specimens of Mymaridae. Bristled wing flight was numerically simulated at Reynolds numbers from 1 to 80. The aerodynamic force, power, and efficiency of bristled wings using lift-based stroke, drag-based stroke, and clap-and-fling mechanism were evaluated. An unusual clap-and-fling pattern considering bristle crossing was first proposed. Our study shows that with a reduction in the wingspan of Mymaridae, the proportion of the wingtip bristled area increases. A lift-based stroke is superior to a drag-based stroke in terms of vertical force production and aerodynamic efficiency at 5 ≤ Re ≤ 20. Bristled wings employing the clap-and-fling mechanism achieve both vertical force and efficiency augmentation, while bristle crossing incurs a substantial horizontal force and contributes little to vertical force augmentation.

By combining the flapping and rotary motion, a flapping wing rotor (FWR) shows unique kinematics of motion. It can produce a significantly higher aerodynamic efficiency and lift coefficient than insect-like flapping wings. However, due to the lack of controllable FWR aerial vehicles, the effect of different flapping parameters of the FWR on aerodynamic characteristics and efficiency remains to be evaluated experimentally. In this work, we conduct experimental studies to investigate the FWR’s lift performance based on our previous vehicle design, which has demonstrated sustained stable hover and maneuver. In particular, by using such flyable FWR as the test platform, the changes in attack angle of the wing, the torsion of wings, different neutral positions, different up and down flapping angles, and different flapping amplitudes, were studied respectively. CFD simulation was used as an auxiliary and supplementary means for validation. As a result, design essentials to lift maximization of the FWR are proposed. The result proves that changing the attack angle and the torsion of the wing will have a certain impact on the lift. In addition, the ideal lift force can be generated when the neutral position tend to zero degrees and the up and down flapping angles tend to be equal. With the growth of the flapping amplitude, the lift force increases continuously. These experimental results provide important design cues for maximizing lift and payload capability of FWR-MAVs.

Low-altitude flight in mountainous terrains is a difficult flight task applied in both military and civilian fields. The helicopter has to maintain low altitude to realize search and rescue, reconnaissance, penetration, and strike operations. It contains complex environment perception, multilevel decision making, and multi-objective flight control; thus, flight is currently mainly conducted by human pilots. In this work, a control framework is implemented to realize autonomous flight for unmanned helicopter operations in an unknown mountainous environment. The identification of targets and threats is introduced using a deep neural network. A 3D vector field histogram method is adopted for local terrain avoidance based on airborne Lidar sensors. In particular, we propose an intuitive direct-viewing method to judge and change the visibilities of the helicopter. On this basis, a finite state machine is built for decision making of the autonomous flight. A highly realistic simulation environment is established to verify the proposed control framework. The simulation results demonstrate that the helicopter can autonomously complete flight missions including a fast approach, threat avoidance, cover concealment, and circuitous flight operations similar to human pilots. The proposed control framework provides an effective solution for complex flight tasks and expands the flight control technologies for high-level unmanned helicopter operations.

Real-time and drift-free state estimation is essential for the flight control of Micro Aerial Vehicles (MAVs). Due to the vibration caused by the particular flapping motion and the stringent constraints of scale, weight, and power, state estimation divergence actually becomes an open challenge for flapping wing platforms’ longterm stable flight. Unlike conventional MAVs, the direct adoption of mature state estimation strategies, such as inertial or vision-based methods, has difficulty obtaining satisfactory sensing performance on flapping wing platforms. Inertial sensors offer high sampling frequency but suffer from flapping-introduced oscillation and drift. External visual sensors, such as motion capture systems, can provide accurate feedback but come with a relatively low sampling rate and severe delay. This work proposes a novel state estimation framework to combine the merits from both to address such key sensing challenges of a special flapping wing platform—micro flapping wing rotors (FWRs). In particular, a cross-fusion scheme, which integrates two alternately updated Extended Kalman Filters based on a convex combination, is proposed to tightly fuse both onboard inertial and external visual information. Such a design leverages both the high sampling rate of the inertial feedback and the accuracy of the external vision-based feedback. To address the sensing delay of the visual feedback, a ring buffer is designed to cache historical states for online drift compensation. Experimental validations have been conducted on two sophisticated microFWRs with different actuation and control principles. Both of them show realtime and drift-free state estimation.