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Purpose Autonomous orbit determination using geomagnetic measurements is an important backup technique for safe spacecraft navigation with a mere magnetometer. The geomagnetic model is used for the state estimation of orbit elements, but this model is highly nonlinear. Therefore, many efforts have been paid to developing nonlinear filters based on extended Kalman filter (EKF) and unscented Kalman filter (UKF). This paper aims to analyze whether to use UKF or EKF in solving the geomagnetic orbit determination problem and try to give a general conclusion. Design/methodology/approach This paper revisits the problem and from both the theoretical and engineering results, the authors show that the EKF and UKF show identical estimation performances in the presence of nonlinearity in the geomagnetic model. Findings While EKF consumes less computational time, the UKF is computationally inefficient but owns better accuracy for most nonlinear models. It is also noted that some other navigation techniques are also very similar with the geomagnetic orbit determination. Practical implications The intrinsic reason of such equivalence is because of the orthogonality of the spherical harmonics which has not been discovered in previous studies. Thus, the applicability of the presented findings are not limited only to the major problem in this paper but can be extended to all those schemes with spherical harmonic models. Originality/value The results of this paper provide a fact that there is no need to choose UKF as a preferred candidate in orbit determination. As UKF achieves almost the same accuracy as that of EKF, its loss in computational efficiency will be a significant obstacle in real-time implementation.

The multi-directional forging process can achieve large plastic deformation, and has great application prospects in industrial production. The Mg-9.55Gd-3.28Y-1.77Zn-0.34Zr (wt%) alloy containing LPSO phase was deformed in different passes and then quenched immediately by the multi-directional forging process with decreasing temperature, and the microstructure and mechanical properties of the alloy were analyzed. It is found that as the number of deformation passes increases, the coarse grains decrease, and the dynamic recrystallization fraction increases. The dynamic recrystallization grains swallow the original grains, promote the continuous refinement of the grains, and greatly improve the uniformity of the microstructure. At the same time, the maximum texture intensity of the (0001) basal plane is significantly reduced, and the pole figure distribution is more dispersed, which is attributed to the random orientation of dynamic recrystallization. Due to the refinement of the microstructure and the weakening of the texture, the tensile strength and yield strength at room temperature increase significantly. After 3 passes of deformation, the alloy has the highest mechanical properties, with tensile strength, yield strength, and elongation reaching 317 MPa, 233 MPa, and 15%, respectively.

The spiral fluidity sample was poured by the liquid of Ti-45Al-8Nb-0.2W-0.25Cr alloy. The flow cessation mechanism of TiAl based alloys was investigated, and its model was built through the observation on the macrostructure of TiAl based alloys formed in the channel. The results showed that the morphology and size of the columnar crystal and equiaxial crystal changed a lot with the increase of flow length. The flow cessation mechanism of the alloy is the abundant growth of columnar crystal in the root, which causes to form the structure and finally give rise to the “necking” leading to flow cessation.

As green solvents, ionic liquids (ILs) are quite suitable for the absorption of volatile organic compounds (VOCs) such as benzene and its homologues. However, solvent selection is the key to the VOC absorption process. In the present study, a rapid solvent screening tool, Conductor-like Screening Model for Real Solvents (COSMO-RS), was used to predict the solubility of toluene in 816 ILs. The effects of four structure characters, namely, the type and alkyl chain length of the cations and anions on the solubility of toluene were discussed. The following conclusions were drawn from the results: (1) ILs with pyrrolidinium-based cations showed better solubility than pyridinium- and imidazolium-based ones. (2) The solubility of toluene in PF6-based ILs increased with the increasing alkyl chain length, while its solubility in Ac-based ILs exhibited the opposite trend. (3) Toluene showed greater solubility in Cl-based ILs than those based on other anions. (4) The solubility of toluene increased with the anion alkyl chain length. Ac-based ILs were chosen as the most promising potential solvents, and further studied to determine the relationship between various interaction energy parameters and toluene solubility. The results showed that the misfit energy played a dominant role during the absorption process. Furthermore, several ILs were selected for experimental verification of the predicted solubility behavior using liquid and gaseous toluene. The results demonstrated that COSMO-RS could be used to semi-quantitatively and qualitatively predict the solubility of toluene, and this model had promising prospects in screening ILs for VOCs absorption. In summary, this study provided a fundamental basis and practical data for the control and treatment of VOCs.

A novel integrated quantized- and event-based control (IQEC) scheme for intra-spacecraft with communication-saving ability is proposed to address the attitude tracking control problem. The IQEC scheme reduces the control updating frequency and the data length per transmission based on the event-based control and quantized communication techniques, thus reducing the system communication occupation. By suitable control system configuration, the purpose of communication-saving is achieved, from sensors to the computing unit and from the computing unit to actuators. The proposed algorithm’s effectiveness is verified via numerical simulation that uses a general actuator model with second-order dynamics.

In this paper, an analytical model of a closed-loop frequency-locked loop (FLL) based on a two-stage voltage-controlled oscillator (VCO) is proposed. Switch capacitor technology is used to accelerate the conversion speed of the frequency-to-voltage converter for reducing the locking time. The VCO is reduced to the minimum two-stage delay ring structure for outputting high-frequency signals with less variation caused by process, voltage, and temperature drift. Based on the strategy that focuses on the optimization of the loop bandwidth, a low jitter GHz clock with a wide swing and a strong capacitive load driving ability is realized. The proposed FLL is implemented in TSMC 0.35 μm 3.3 V CMOS process. From the experimental results, the output frequency is ranged from 750 MHz to 1.27 GHz, and the RMS jitter of the output clock is less than 36 ps under 1.039 GHz. The generated low-jitter clock is suitable for GHz gating applications in single-photon detection.

The bottom-up construction of enzyme-based artificial cells is generating increasing interest, but achieving artificial cells for "all artificial modules" remains challenging in synthetic biology. Here, we introduce a fully synthetic cell system by integration of biomimetic nanozymes into giant unilamellar vesicles (GUVs). To mimic native peroxidase for free radical generation by taking advantage of Fenton catalysis reactions, we designed and prepared a de novo artificial nanozyme composed of ferritin heavy-chain scaffold protein and catalytic Fe3O4 nanoparticles as the active center. As two examples in bioapplications, we showed this nanozyme-powered GUV system not only mimics intracellular oxidative stress pathways but also induces tumor cell death by sensing and responding to external chemical signals. Specifically, we recreated intracellular biochemical events, including DNA damage and lipid peroxidation, in the compartmentalized GUVs by taking advantage of nanozyme induction of defined catalytic reactions. Additionally, the GUV system also actively induced DNA double-strand breakage and lipid damage of tumor cells, in response to the high expression of H2O2 within the tumor microenvironment. This concept-of-proof study offers a promising option for defining catalysis in biological systems and gives new insights into the de novo creation of artificial cells in a fully synthetic manner.

Although convolutional neural networks (CNNs) show great abilities in image classification, improving their performance is still challenging for shallow networks. The redundancy of the network increases when more convolution kernels are adopted in the network. To alleviate this defect, we propose two methods including Weight Correlation Reduction (WCR) and Features Normalization (FN) to boost the performance of shallow networks. The formal method is designed to eliminate weight redundancy, while the latter is used to increase the sparsity of learned deep features. On benchmarks CIFAR-10 and STL-10, the accuracy rate increased by $$2.29\%$$ and $$4.79\%$$ for shallow networks, respectively, which indicates the effectiveness of the proposed methods.

Purpose The purpose of this paper is to study the general actuator modeling in spacecraft attitude control systems. Design/methodology/approach The proposed module in this paper provides various non-ideal factors such as the second-order dynamic time response, time-delay, bias torques, dead-zones and saturation. The actuator module can make the simulation as close to the practical situation as possible. Findings This paper presents a practical integrated module for the simulation of attitude control algorithms. Based on theoretical modeling, we give simulation modules and numerical examples. The proposed model can be directly used in spacecraft control simulation. Instead of considering only a few of them, it makes the simulation more convincing. Though it may not be perfect, it is better than totally ignoring the actuator dynamics. Originality/value The authors provide an integrated actuator model for spacecraft attitude control simulation, considering as many nonlinear factors as possible once time.

This paper proposes a novel quaternion-based attitude estimation method for land-vehicle applications by fusing the low-cost magnetic, angular rate, and gravity (MARG) sensors and global navigation satellite systems measured velocity (GNSS-V). A structure of three-layer cascaded indirect Kalman filter (IKF) is devised to minimize the interactions of heterogeneous error sources on attitude quaternion solutions. It sequentially fuses the Earth's gravity vector, magnetic vector, and GNSS-V vector pairs with quaternion state constraints from Euler angles in each local filter. To further ensure the robustness of quaternion-based attitude solution, the external acceleration term is adaptively compensated within a sliding window of GNSS-V information. Meanwhile, independent and cross check procedures for observation vectors are also established for excluding individual sensor fault by taking land-vehicle dynamics into account. It is of significant importance that, in this contribution, the GNSS measured velocity is fully utilized in all potential aspects of aiding attitude determination with MARG sensors. Real-world vehicular experiments are carried out to evaluate the performance of our proposed method. The presented results verify the validity and efficiency thus the developed method may be promising for implemention in land-vehicle applications.

Purpose Recent spacecraft attitude control systems tend to use wireless communication for cost-saving and distributed mission purposes while encountering limited communication resources and data exposure issues. This paper aims to study the attitude control problem with low communication frequency under the sampled-data. Design/methodology/approach The authors propose constructive control system structures based on quantization and event-triggered methods for intra-spacecraft and multi-spacecraft systems, and they also provide potential solutions to shield the control system's data security. The proposed control architectures can effectively save communication resources for both intra-spacecraft and multi-spacecraft systems. Findings The proposed control architectures no longer require sensors with trigger-ing mechanism and can achieve distributed control schemes. This paper also provides proposals of employing the public key encryption to secure the data in control-loop, which is transmitted by the event-triggered control mechanism. Practical implications Spacecraft attempts to use wireless communication, yet the attitude control system does not follow up promptly to accommodate these variations. Compared with existing approaches, the proposed control structures can save communication resources of control-loop in multi-sections effectively, and systematically, by rationally configuring the location of quantization and event-triggered mechanisms. Originality/value This paper presents several new control schemes and a necessary condition for the employment of encryption algorithms for control systems based on event-based communication.

The aromatic C–H bond etherification with alcohols is one of the most atom-efficient ways to construct aryl ethers. However, it often requires a large excess of alcohols as etherification reagents,...

Effective curative therapies for spinal cord injury (SCI), which is often accompanied by intestinal complications, are lacking. Potential therapeutic targets include astrocytes and their enteric nervous system counterpart, enteric glial cells (EGCs). Based on shared biomarkers and similar functions of both cell types, we designed an orally administered targeted delivery system in which the neuropeptide apamin, stabilized by sulfur replacement with selenium, was adopted as a targeting moiety, and the liposome surface was protected with a non-covalent cross-linked chitosan oligosaccharide lactate layer. The system effectively permeated through oral absorption barriers, targeted local EGCs and astrocytes after systemic circulation, allowing for comprehensive SCI therapy. Given the involvement of the gut-organ axis in a growing number of diseases, our research may shed light on new aspects of the oral administration route as a bypass for multiple interventions and targeted therapy.

Based on the chemical cross-linking method, this paper uses polydimethylsiloxane with various viscosities of 10 cSt, 20 cSt, 50 cSt, and 100 cSt to synthesize mesoporous and macroporous SiOC ceramics. Their thermal conductivities are measured by using 3ω method with high accuracy. Three typical models for their thermal conductivities, i.e., series model (SM), maxwell-Eucken 1 model (ME1), and effective medium theory (EMT) model, are utilized to derive the empirical formula through the multi-parameter linear optimization algorithm, which agrees well with the experimental results. The effects of pore size and specific surface area on the overall thermal conductivity of the porous structure are explored. Interestingly, it is found that the thermal conductivities of both gas phase and solid phase inside the porous structure increase with the increasing pore size at the nanometer scale, but the overall thermal conductivity of the porous structure decreases with the increasing pore size. Scanning electron microscopy graphs corroborate that the extension of the heat transfer route and the barrier of more pores between the solid phases together cause the reduction of the gas-solid coupling thermal conductivity of SiOC ceramics with larger pore size. On the contrary, the miniaturization of individual particles through modulating the synthesis parameters can increase the number of small pores in the sample itself to meet the pseudo-lattice vibration conditions, which results in the increment of the gas-solid coupling thermal conductivity and the overall thermal conductivity of the porous structure. These findings would provide meaningful guidance for designing SiOC porous ceramic super-insulation materials with extremely low thermal conductivity.

The characteristics of surface appearances, mass loss, relative dynamic modulus of elasticity and strength loss of different recycled aggregate concretes(RAC) exposed to freeze-thaw cycles were analyzed. It was found that the freeze-thaw resistance of RAC could be determined by the recycled aggregate compositions and admixtures. Both the saturation degree and the air void structure were the key factors influencing the freeze-thaw damage on concrete. Some major proposed freeze-thaw deterioration mechanisms were utilized to interpret the freeze-thaw damage on recycled aggregate concrete. Meanwhile, some potential measures to enhance the freeze-thaw resistance of concrete were summarized and discussed.

Exploring high-performance and low-cost bifunctional electrocatalysts is crucial for developing highly efficient overall water splitting cells. In this work, a facile and cheap co-precipitation method, which is compatible with large-scale production, is applied to prepare amorphous Fe-doped CoWO4 bifunctional electrocatalysts. Low overpotentials of 259 and 118 mV to reach a current density of 10 mA cm−2 for the OER and HER in 1 M KOH are found, respectively. Moreover, no detectable potential decay is observed at 50 mA cm−2 for at least 15 h, revealing its excellent long-term stability. Finally, a highly efficient overall water splitting cell is assembled with amorphous Fe-doped CoWO4 as a bifunctional electrocatalyst. A low cell voltage of 1.55 V is required to achieve a current density of 10 mA cm−2, which surpasses the benchmark IrO2‖Pt/C cell.

The construction of artificial photosynthetic (AP) systems for the hydrogen evolution reaction (HER) and carbon dioxide reduction reaction (CRR) is one of the hottest topics in the field of energy and sustainability. A typical AP system is composed of three key components, a photosensitizer (PS) for visible light harvesting, a catalyst for redox reactions, and a sacrificial electron donor (SED) for consuming holes generated in the PS. Among these three components, the PS and catalyst affect the photocatalytic performance much. There are two main types of AP systems, heterogeneous systems using inorganic materials and homogeneous systems using molecules. In addition to these, a compromise strategy of using inorganic luminescent nanoparticles as photosensitizers and molecular metal complexes as catalysts to construct hybrid AP systems has been developed. Inorganic luminescent nanoparticles, such as colloidal quantum dots (QDs) and carbon quantum dots (CQDs), have advantages of robust photostability, multiple excitation, and easy preparation. Molecular catalysts feature high activity, modifiable structures, and atom economy. Research on the combination of these two different types of materials to construct hybrid systems for solar fuel production is blooming. In the last decade, a large number of hybrid AP systems have been reported, and various strategies for system construction were developed. Obvious improvements in the photocatalytic efficiency of solar fuel production were witnessed. This review focuses on hybrid AP systems for the HER and CRR. The mechanism, composition, system design, and photocatalytic performances of the reported hybrid AP systems are reviewed. The advances and challenges in this field are discussed.

In temperate forests, autumn leaf phenology signals the end of leaf growing season and shows large variability across tree-crowns, which importantly mediates photosynthetic seasonality, hydrological regulation, and nutrient cycling of forest ecosystems. However, critical challenges remain with the monitoring of autumn leaf phenology at the tree-crown scale due to the lack of spatially explicit information for individual tree-crowns and high (spatial and temporal) resolution observations with nadir view. Recent availability of the PlanetScope constellation with a 3 m spatial resolution and near-daily nadir view coverage might help address these observational challenges, but remains underexplored. Here we developed an integration of PlanetScope with drone observations for improved monitoring of crown-scale autumn leaf phenology in a temperate forest in Northeast China. This integration includes: 1) visual identification of individual tree-crowns (and species) from drone observations; 2) extraction of time series of PlanetScope vegetation indices (VIs) for each identified tree-crown; 3) derivation of three metrics of autumn leaf phenology from the extracted VI time series, including the start of fall (SOF), middle of fall (MOF), and end of fall (EOF); and 4) accuracy assessments of the PlanetScope-derived phenology metrics with reference from local phenocams. Our results show that (1) the PlanetScope-drone integration captures large inter-crown phenological variations, with a range of 28 days, 25 days, and 30 days for SOF, MOF, and EOF, respectively, (2) the extracted crown-level phenology metrics strongly agree with those derived from local phenocams, with a root-mean-square-error (RMSE) of 4.1 days, 3.0 days and 5.4 days for SOF, MOF, and EOF, respectively, and (3) PlanetScope maps large variations in autumn leaf phenology over the entire forest landscape with spatially explicit information. These results demonstrate the ability of our proposed method in monitoring the large spatial heterogeneity of crown-scale autumn leaf phenology in the temperate forest, suggesting the potential of using high-resolution satellites to advance crown-scale phenology studies over large geographical areas.

Ionic hydrogels are promising candidates for fabricating stretchable electronics, but the deficiency in drying and freezing tolerances severely limits their application. Here, we report a facile and versatile salt-percolated strategy to fabricate hydrogels with exceptional freezing and drying tolerances, high conductivity, and anti-swelling ability for sensitive temperature and strain detection within a broad temperature range. We discovered that lithium bromide (LiBr) was the most effective drying and freezing inhibitor for hydrogels among the various salts. The 50 wt% LiBr-percolated hydrogels retained ultrahigh stretchability (625% strain) and conductivity even at −78.5 °C or in ambient air for a year. The important role of LiBr in inhibiting the drying and freezing of hydrogels was understood using density functional theory (DFT) simulations on a molecular scale, revealing the formation of stable Li+–H2O and Br−–H2O clusters. It was found that the introduction of LiBr enhanced the temperature and strain sensing performance, e.g., the stability and working temperature range. Multifunctional transparent sensors exhibited a high thermal sensitivity (2.54%/°C), broad temperature detection range (−78.5 to 97 °C), low detection limit (0.1% strain), and low hysteresis and baseline drift in cycling strain sensing. Attributed to the high tolerance of hydrogels to a wide range of temperatures, the strain sensing ability was maintained even at −20 °C. Various physiological signals, such as facial expressions, word pronunciation and knee bending, are real-time monitored using hydrogel-based epidermal sensors.

In this work, Ni–Co alloy nanoparticles (NPs) on La-doped SiO2 showed excellent selectivity toward ethanol for direct ethanol synthesis via CO hydrogenation. Over the catalyst with an optimal ratio...

The magnetic, angular rate, and gravity (MARG) sensor array has been widely used for attitude estimation tasks. In this article, we report our new advances on related fusion algorithm based on the gradient-descent algorithm (GDA). Combining with complementary filters, GDA has been very popular for attitude estimation in industrial applications. The integration of the Kalman filter introduces covariance information and significantly improves in-run quality control. Some useful results are derived to build up the framework of a novel linear Kalman filter called GDA-LKF. A new simplified linear measurement quaternion model is proposed. This article also deals with the analytical adaptive problem of determining gradient-descent step length. We, for the first time, give the solution in the sense of least square based on aided vector measurements. Simulations are carried out to validate the noise sensitivity and covariance characteristics. The proposed schemes are also evaluated by real-world experiments that provide the audience with comparisons on accuracy, convergence, and execution time consumption performances between the proposed GDA-LKFs and recent representative methods. The results show that the proposed GDA-LKF can accurately estimate attitude with fast convergence and high accuracy. Note to Practitioners —Attitude estimation using magnetic, angular rate, and gravity (MARG) sensors is very common for ground, air, and underwater vehicles. The novel findings in this article aim to give the engineers a brand new perspective on the related filter design according to the widely employed gradient-descent algorithm (GDA) method. Some specific techniques, e.g., optimal adaptive law of the designed scheme, will also bring flexibility to the implementation with multiple considerations of object motions.

Phase unwrapping is a fundamental task in phase-based profilometry. Existing spatial and temporal approaches are facing challenges such as error propagation and low efficiency. In this study, the authors propose a learning-based method that uses a support vector machine (SVM) to perform phase unwrapping, where the problem is solved as a classification task. To be specific, seven elements, extracted from the captured patterns and the wrapped phase, form the input feature vector and the fringe order is the output class. Besides, a radial basis function kernel SVM is adopted as the model. The proposed method is conducted independently for every pixel, and does not suffer from error propagation in the spatial unwrapping. Moreover, it needs fewer patterns than temporal unwrapping since only one phase map is required. Simulation and experimental results demonstrate that the proposed scheme produces precise depth maps, which are comparable with the complex quality-guided methods but at a much faster speed.

Alzheimer’s disease (AD) is a chronic neurodegenerative disease. Better imaging and early diagnosis of biomarkers of AD is extremely important for therapeutic interventions. The amyloid cascade hypothesis and its revised version identify insoluble β-amyloid deposition as a good diagnostic biomarker for AD. Moreover, lipid droplets may also act as an auxiliary biomarker related to AD pathology based on recent studies. Herein, two quinoline-based AIE probes were designed and synthesized for the imaging of Aβ plaques and lipid droplets. The probes exhibited remarkable turn-on fluorescence enhancements with the Aβ aggregates. The lipid droplets-targeting probe FB exhibited high selectivity and binding affinity towards the Aβ aggregates with a detection limit as low as 26.9 nM. Furthermore, FB was capable of readily imaging Aβ plaques and lipid droplets at the cellular level and in brain sections of transgenic AD mice. The probe FB can serve as a promising tool for developing early diagnosis and innovative therapeutics of AD.

3D bioprinting is one of the rapidly evolving fields of tissue engineering where microengineering meets cells biology within an unprecedented precision to construct tissue structures of various forms with complexity. However, enabling simultaneous printing of heterogeneous biomaterial along with scaffold components through the currently available printers is still considered as a major challenge due to the lack of instrumentation. Flow control is one of the major issues associated with the process. In this aspect, a microfluidic nozzle head equipped with two shape-memory alloy (SMA) actuators was proposed and integrated with a commercially available 3D printer to assist the biomaterial printing in a more systematic manner. The SMA actuator restrains the amount of flows for fabricating the desired scaffold components. Experimental results illustrated that the use of SMA actuator ensued a rapid and precise flow control of biomaterial and can further facilitate to maintain the width of any printed structures. As a proof of concept for the profound biomedical applications with the present manufacturing configuration, a 3D printed hydrogel platform was fabricated with demonstrated characters for later cell seeding after the printing further opens a new chapter in terms of biomaterial printing.

The geometric, electronic and optical properties of SrCO3 under pressure up to 20 GPa are studied based on the density functional theory. The optimised structure parameters are in good agreement wi...

Simultaneous enhancement in water flux and removal efficiency during the filtration process remains a big challenge for separation membranes. The porous structure of the filter paper can provide many channels for water transportation, but the separation performance is generally poor. The purpose of this study is to develop a new kind of filter paper consisting of ultralong hydroxyapatite (HAP) nanowires, cellulose fibers (CFs) and double metal oxide (LDO) nanosheets, and to achieve the simultaneous enhancement of both water flux and removal efficiency for high-performance dye separation. In this work, a novel kind of LDO/HAP/CF nanocomposite filter paper consisting of ultralong HAP nanowires and CFs and LDO nanosheets has been developed for rapid water filtration and highly efficient dye adsorption. Positively charged LDO nanosheets can adsorb on the surface of negatively charged ultralong HAP nanowires and embed in the porous networked structure of the LDO/HAP/CF nanocomposite filter paper, which can provide a porous structure for rapid water transportation and can adjust the pore size of the nanocomposite filter paper. As a result, the pure water flux of the LDO/HAP/CF nanocomposite filter paper can be adjusted. The optimized pure water flux of the LDO/HAP/CF nanocomposite filter paper can reach 783.6 L m-2 h-1 bar-1, which is 1.51 times that of the HAP/CF filter paper without LDO nanosheets (518.6 L m-2 h-1 bar-1). More importantly, the adsorption capacity of LDO nanosheets is high for dye molecules, the rejection percentage of Congo red (CR) by the as-prepared HAP/CF filter paper is only 59.8%, and its water flux is 534.7 L m-2 h-1 bar-1. The optimized rejection percentage and water flux of the LDO/HAP/CF nanocomposite filter paper for CR are significantly enhanced (98.3% and 736.8 L m-2 h-1 bar-1, respectively) compared to those of the HAP/CF filter paper. The size of LDO nanosheets has a significant effect on the water flux and dye rejection percentage of the LDO/HAP/CF nanocomposite filter paper. The as-prepared LDO/HAP/CF nanocomposite filter paper is promising for the applications in highly efficient purification of wastewater containing dye molecules.

Terrestrial laser scanning (TLS) has been recognized as an accurate means for non-destructively deriving three-dimensional (3D) forest structural attributes. These attributes include but are not limited to tree height, diameter at breast height, and leaf area density. As such, TLS has become an increasingly important technique in forest inventory practices and forest ecosystem studies. Multiple TLS scans collected at different locations are often involved for a comprehensive characterization of 3D canopy structure of a forest stand. Among which, multi-scan registration is a critical prerequisite. Currently, multi-scan TLS registration in forests is mainly based on a very time-consuming and tedious process of setting up hand-crafted registration targets in the field and manually identifying the common targets between scans from the collected data. In this study, a novel marker-free method that automatically registers multi-scan TLS data is presented. The main principle underlying our method is to identify shaded areas from the raw point cloud of a single TLS scan and to use them as the key features to register multi-scan TLS data. The proposed method is tested with 17 pairs of TLS scans collected in six plots across China with various vegetation characteristics (e.g., vegetation type, height, and understory complexity). Our results showed that the proposed method successfully registered all 17 pairs of TLS scans with equivalent accuracy to the manual registration approach. Moreover, the proposed method eliminates the process of setting up registration targets in the field, manually identifying registration targets from TLS data, and processing raw TLS data to extract individual tree attributes, which brings it the advantages of high efficiency and robustness. It is anticipated that the proposed algorithms can save time and cost of collecting TLS data in forests, and therefore improves the efficiency of TLS forestry applications.

Based on thin-section, argon-ion polished large-area imaging and nano-CT scanning data, the reservoir characteristics and genetic mechanisms of the Lower Silurian Longmaxi shale layers with different laminae and laminae combinations in the Sichuan Basin were examined. It is found that the shale has two kinds of laminae, clayey lamina and silty lamina, which are different in single lamina thickness, composition, pore type and structure, plane porosity and pore size distribution. The clayey laminae are about 100 μm thick each, over 15% in organic matter content, over 70% in quartz content, and higher in organic pore ratio and plane porosity. They have abundant bedding fractures and organic matter and organic pores connecting with each other to form a network. In contrast, the silty laminae are about 50 μm thick each, 5% to 15% in organic matter content, over 50% in carbonate content, higher in inorganic pore ratio, undeveloped in bedding fracture, and have organic matter and organic pores disconnected from each other. The formation of mud lamina and silt lamina may be related to the flourish of silicon-rich organisms. The mud lamina is formed during the intermittent period, and silt lamina is formed during the bloom period of silicon-rich organisms. The mud laminae and silt laminae can combine into three types of assemblages: strip-shaped silt, gradating sand-mud and sand-mud thin interlayers. The strip-shaped silt assemblage has the highest porosity and horizontal/vertical permeability ratio, followed by the gradating sand-mud assemblage and sand-mud thin interlayer assemblage. The difference in the content ratio of the mud laminae to silt laminae results in the difference in the horizontal/vertical permeability ratio.

One of the critical issues for electret/triboelectric devices is the poor charge viability and stability in humid environments. Herein, we propose a new origami-inspired “W-tube”-shaped triboelectric nanogenerator (W-TENG) with two thin-film electrets folded based on Miura-origami. The Miura-origami fold is capable of transforming flat materials with large surface areas into reduced and compressed complex 3D structures with parallelogram tessellations. The triboelectric power generation components can thus be hermetically sealed inside the “W-tube” to avoid contact with the external humid environment. Furthermore, the elastic nature of the Miura-origami fold endows the proposed W-TENG device with excellent deformability, flexibility, and stretchability. Therefore, it is capable of harvesting kinetic energy from various directions and forms of movement, including horizontal pressing, vertical tapping, and lateral bending. The compact, light weight, and self-rebounding properties of the origami structure also make it convenient for integration into wearable devices. Various parameters of the W-TENG are intensively investigated, including the number of power generation units, original height of the device, acceleration magnitude, excitation direction, and water-proof capability. Triggered by hand tapping impulse excitation in the horizontal and vertical directions, the instantaneous open-circuit voltages can reach 791 V and 116 V with remarkable optimum powers of 691 μW at 50 MΩ and 220 μW at 35 MΩ, respectively. The outcomes of this work demonstrate the fusion of the ancient art of origami, material science, and energy conversion techniques to realize flexible, multifunctional, and water-proof TENG devices. Researchers have used techniques from origami to engineer a flexible, resilient, water-proof power generator, which can be used with wearable devices. The device, designed by a team led by Kai Tao of China’s Northwestern Polytechnical University, consists of two thin films of dielectric material, which can generate power when deformed. This structure is then folded in a Miura fold, a pattern which compresses a large surface area into a smaller area. The resulting spring-like makes the device return to its original shape after deformation while also offering compactness and flexibility together. The device generated power when tapped or bent, and the origami structure hermetically sealed the components, making the generator water-proof. With this combination of origami and material science, researchers can design and build flexible energy-harvesting devices to power wearable devices or other flexible electronics.

The intensity of the micro-expression is weak, although the directional low frequency components in the image are preserved by many algorithms, the extracted micro-expression feature information is not sufficient to accurately represent its sequences. In order to improve the accuracy of micro-expression recognition, first, each frame image is extracted from its sequences, and the image frame is pre-processed by using gray normalization, size normalization, and two-dimensional principal component analysis (2DPCA); then, the optical flow method is used to extract the motion characteristics of the reduced-dimensional image, the information entropy value of the optical flow characteristic image is calculated by the information entropy principle, and the information entropy value is analyzed to obtain the eigenvalue. Therefore, more micro-expression feature information is extracted, including more important information, which can further improve the accuracy of micro-expression classification and recognition; finally, the feature images are classified by using the support vector machine(SVM). The experimental results show that the micro-expression feature image obtained by the information entropy statistics can effectively improve the accuracy of micro-expression recognition.

Low-molecular-weight organic acids (LMWOAs), a type of small organic molecules with one or more carboxyl groups present in soil, play an important role in the soil ecosystem. Greenhouse soil could ...

This paper proposes a novel fast deterministic quaternion attitude determination method for accelerometer and magnetometer combination (AMC). After taking insight to the attitude determination theory, an important relationship between the sensor outputs and the magnetometer’s reference vector is successfully derived. Based on the relationship, the optimal quaternion associated with the attitude of a certain object is easily calculated. The main breakthrough of this paper is that it significantly simplifies the determination of the magnetometer’s reference vector which always needs systematic calibration or iterative estimation in existing methods. We name the proposed method the Fast Accelerometer-Magnetometer Fusion (FAMF). Our proposed method has the advantages of better computation accuracy and less time consumption. Several experiments are carried out to illustrate the attitude determination results. Besides, comparisons with existing representative methods are also presented in the experimental section of this paper, which verify the effectiveness of the proposed FAMF. Finally, we experimentally show that the FAMF’s roll and pitch angles are immune to magnetic distortion, which ensures the robustness under complex environments for micro air vehicles (MAV).

This article presents a 50–112-Gb/s current-mode four-level pulse amplitude modulation (PAM-4) transmitter with a two-tap fractional-spaced feed-forward equalizer (FFE). The principle analysis shows that the fractional-spaced FFE can provide an extended compensation range beyond the Nyquist frequency without amplifying noise. For the transmitter prototype implementation, the tap delay is adjusted by a coarse–fine capacitor array-based delay cell located in the quarter-rate clock path. Dynamic latches, pseudo-AND2s, and bandwidth-enhanced 4:1 multiplexers are employed to guarantee an adequate timing margin and a sufficient bandwidth for the data rate of 112 Gb/s. A linearity-optimized FFE driver is employed to overcome the current compression caused by the channel-length modulation. Fabricated in a 65-nm CMOS process, the measurement results show that the proposed fractional-spaced FFE can significantly improve the eye-opening in terms of expanding the eye width and optimizing the eyelid thickness. The PAM-4 transmitter can operate in both full-rate PAM-4 and half-rate NRZ modes, achieving a maximum data rate of 112 Gb/s with an energy efficiency of 2.17 pJ/bit.

Recommending yet-unvisited points of interest (POIs) which may be of interest to users is one of the fundamental applications in location-based social networks. It mainly replies on the understanding of users, POIs, and their interactions. Previous studies either develop matrix factorization-based approaches or utilize deep learning frameworks to learn better representation of users and POIs in order to estimate users’ latent preference. However, most of existing methods still confront the challenges like in traditional recommender systems, such as data sparsity and cold-start. In particular, they have difficulties in fully utilizing rich semantic information, such as social influence, geographical constraints and interactions between users and POIs. To fill this research gap, we propose a new recommendation framework – Hybrid Graph convolutional networks with Multi-head Attention for POI recommendation (HGMAP). HGMAP constructs a spatial graph based on the geographical distance between pairs of POIs and leverages Graph Convolutional Networks (GCNs) to express the high-order connectivity among POIs, which not only incorporates the spatial constraints but also provides an effective way to alleviate the sparse check-in problem. In addition, HGMAP exploits the user social relationship with another GCN and differentiates user preference over different aspects of POIs with a multi-head attention mechanism. We conducted extensive experiments on three public datasets and the results demonstrate that HGMAP significantly improves the recommendation performance over several state-of-the-art models, for example, up to approximately 4.8% and 7% for Precision@10 and Recall@10, respectively.

Purpose The purpose of this paper is to investigate the attitude cooperation control of multi-spacecraft with in-continuous communication. Design/methodology/approach A decentralized state-irrelevant event-triggered control policy is proposed to reduce control updating frequency and further achieve in-continuous communication by introducing a self-triggered mechanism. Findings Each spacecraft transmits data independently, without the requirement for the whole system to communicate simultaneously. The local predictions and self-triggered mechanism avoid continuous monitoring of the triggering condition. Research limitations/implications This investigation is suitable for small Euler angle conditions. Practical implications The control policy based on event-triggered communication can provide potential solutions for saving communication resources. Originality/value This investigation uses event- and self-triggered policy to achieve in-communication for the multi-spacecraft system.

Although it is one of the most widely used methods in recommender systems, Collaborative Filtering (CF) still has difficulties in modeling non-linear user-item interactions. Complementary to this, recently developed deep generative model variants (e.g., Variational Autoencoder (VAE)) allowing Bayesian inference and approximation of the variational posterior distributions in these models, have achieved promising performance improvement in many areas. However, the choices of variation distribution - e.g., the popular diagonal-covariance Gaussians - are insufficient to recover the true distributions, often resulting in biased maximum likelihood estimates of the model parameters. Aiming at more tractable and expressive variational families, in this work we extend the flow-based generative model to CF for modeling implicit feedbacks. We present the Collaborative Autoregressive Flows (CAF) for the recommender system, transforming a simple initial density into more complex ones via a sequence of invertible transformations, until a desired level of complexity is attained. CAF is a non-linear probabilistic approach allowing uncertainty representation and exact tractability of latent-variable inference in item recommendations. Compared to the agnostic-presumed prior approximation used in existing deep generative recommendation approaches, CAF is more effective in estimating the probabilistic posterior and achieves better recommendation accuracy. We conducted extensive experimental evaluations demonstrating that CAF can capture more effective representation of latent factors, resulting in a substantial gain on recommendation compared to the state-of-the-art approaches.

We give a universal analytical solution to the hand-eye calibration problem ${AX} = {XB}$ with known matrices ${A}$ and ${B}$ and unknown variable ${X}$ , all in the set of special Euclidean group SE(3). The developed method relies on the 4-D Procrustes analysis. A unit-octonion representation is proposed for the first time to solve such a Procrustes problem through which an optimal closed-form eigendecomposition solution is derived. By virtue of such a solution, the uncertainty description of ${X}$ , being a sophisticated problem previously, can be solved in a simpler manner. The proposed approach is then verified using simulations and real-world experimentations on an industrial robotic arm. The results indicate that it owns better accuracy and better description of uncertainty and consumes much less computation time.

The shales in the 2nd Member of Shanxi Formation in the east margin of the Ordos Basin were deposited in a marine-nonmarine transitional environment during the Permian. Based on the recent breakthroughs in the shale gas exploration and theoretical understandings on the shale gas of the study area, with a comparison to marine shale gas in the Sichuan Basin and marine-nonmarine transitional shale gas in the U.S., this study presents the geological characteristics and development potential of marine-nonmarine transitional gas in the study area. Four geological features are identified in the 2nd Member of the Shanxi Formation in the study area has: (1) stable sedimentary environment is conductive to deposition of widely distributed organic shale; (2) well-developed micro- and nano- scale pore and fracture systems, providing good storage capacity; (3) high content of brittle minerals such as quartz, leading to effectively reservoir fracturing; and (4) moderate reservoir pressure and relatively high gas content, allowing efficient development of shale gas. The 2nd Member of Shanxi Formation in the east margin of Ordos Basin is rich in shale gas resource. Three favorable zones, Yulin-Linxian, Shiloubei-Daning-Jixian, and Hancheng-Huangling are developed, with a total area of 1.28×104 km2 and resources between 1.8×1012 and 2.9×1012 m3, indicating a huge exploration potential. Tests of the 2nd Member of Shanxi Formation in vertical wells show that the favorable intervals have stable gas production and high reserves controlled by single well, good recoverability and fracability. This shale interval has sufficient energy, stable production capacity, and good development prospects, as evidenced by systematic well testing. The east margin of the Ordos Basin has several shale intervals in the Shanxi and Taiyuan formations, and several coal seams interbedded, so collaborative production of different types of natural gas in different intervals can be considered. The study results can provide reference for shale gas exploration and development and promote the rapid exploitation of shale gas in China.

This paper presents the results of the effects of tensile stress and corrosion environment on the performances of epoxy (EP) coating systems and fluorocarbon (FC) coating systems on steel bridge by accelerated exposure test. Gloss, color characteristic parameter, and blistering area were selected to be aging indexes of anticorrosive coatings. Four different stress levels were applied on coated steel panel specimens by using a three-point bend loading, and the stress coefficient is proposed in this paper. The results showed that coating corroded more severely in seawater than in freshwater. The tensile stress may accelerate the degradation of the coating. The degree of corrosion damage of the coatings increased with the increase of stress levels. Natural exposure tests of EP and FC coating systems were performed at Sanya test site and Qingdao test site in China, respectively. The correlation between natural exposure test and accelerated exposure test is presented by the acceleration coefficient. A life prediction model of anticorrosive coatings on steel bridge is proposed. The stress coefficient was presented in the life prediction model. The stress coefficient increases with the increase of stress applied on coatings. The proposed life prediction model can provide an important basis for quantitatively describing the failure of anticorrosive coatings and predicting the life of anticorrosive coatings on steel bridges.

PurposeThis paper investigates the policy changes made towards infrastructure public–private partnerships (PPPs). The purpose of this study is to empirically identify the policy risks associated with the development of PPPs and to assess their impacts on the projects.Design/methodology/approachA case study of the policy changes that have been implemented for PPPs in China over the past seven years has been undertaken and is presented in this study. The causal loop diagrams are applied to assess and illustrate the potential impacts of the risks as a result of such changes on PPPs.FindingsA sequence of the policy risks, which relate to PPP risk allocation, contract management and implementation, payment and abatement mechanisms and financing, has been identified. It is also found that the identified risks will generate significant but negative impacts on PPPs, leading to an ineffective project delivery, low revenue, poor service quality and even contract breach.Practical implicationsThis research provides the private-sector entities that will embark on PPPs with an insight into managing and controlling policy risks over the project's lifecycle.Originality/valuePPPs have been critical for infrastructure development worldwide. Nevertheless, they have been a controversy, as many of them were subjected to poor outputs. Consequently, a variety of political mechanisms has been implemented to enhance the governance for PPPs. Policy can bring not only benefits but also risks and, however, policy risks of PPPs with a particular assessment for their potential impacts have received limited attention. Therefore, the study presented in this paper will contribute to the identification and assessment of policy risks within the context of PPPs.

Severe plastic deformation can be produced by repetitive upsetting-extrusion process. Using the repetitive upsetting-extrusion (RUE) process at decreasing temperature, the Mg-12.0Gd-4.5Y-2.0Zn-0.4Zr (wt %) alloy was deformed by different RUE passes and then heat treated. The microstructure, texture and mechanical properties of the alloy were compared and analyzed. The results demonstrate that with the increase of deformation passes, the coarse grains of the alloy decreased, the dynamic recrystallization fraction increased, and the dynamic recrystallized grains phagocytized the original grains. This can promote the continuous refinement of the grains and the microstructure uniformity. The maximum texture intensity of the (0001) basal plane decreased significantly with the increase of processing passes and the dispersion degree of pole figure increased. The orientation of dynamic recrystallized grains was randomly distributed to weaken texture. Due to the refinement of microstructure and the weakening of texture, the tensile strength and yield strength of the alloy obviously increased at room temperature. The mechanical properties of the alloy reached the highest after 3 passes and heat treatment.

To address the low gas sensitivity of pristine graphene (Gr), chemical modification of Gr has been proved as a promising route. However, the existing chemical functionalization method imposes the u...

3D registration has always been performed invoking singular value decomposition (SVD) or eigenvalue decomposition (EIG) in real engineering practices. However, these numerical algorithms suffer from uncertainty of convergence in many cases. A novel fast symbolic solution is proposed in this paper by following our recent publication in this journal. The equivalence analysis shows that our previous solver can be converted to deal with the 3D registration problem. Rather, the computation procedure is studied for further simplification of computing without complex-number support. Experimental results show that the proposed solver does not loose accuracy and robustness but improves the execution speed to a large extent by almost %50 to %80, on both personal computer and embedded processor., Comment: 10 pages, 7 figures, 5 tables

In control practices, problems of parametric or time-varying uncertainties must be dealt with. Robust control based on norm theory and convex and non-convex optimization algorithms is a powerful tool to solve these problems in theory, but it is employed rarely in applications. In most engineering cases, Proportional-Integration-Derivative (PID) control is still the most popular method for its easy-to-tune and controllable properties. The control method proposed in this paper integrates the PID control into robust control formulation as a robust Structured Static Output Feedback (SSOF) problem of Linear-Parameter-Varying (LPV) systems, which can be converted into a Parameter Dependent Bilinear-Matrix-Inequality (PDBMI) optimization problem. A convex-concave decomposition based method is given to solve the proposed PDBMI problem. The proposed solution has a simple structure in PID form and can guarantee stability and robustness of the system being controlled in the whole operation range with less conservativeness than existing solution.

The thermal conductivity of two-dimensional materials like graphene can efficiently be tuned by introducing holes, in which the density and distribution of the holes are the key parameters. Furthermore, the distribution of holes can induce a variation as high as 74% in the thermal conductivity for porous graphene with a given density of holes. Therefore, an existing challenge is to find the optimal distribution of holes that can minimize or maximize the thermal conductivity of porous graphene as the design space expands dramatically with increasing hole density. We therefore apply an inverse design methodology based on machine learning to reveal the relationship between hole distribution and thermal conductivity reduction in monolayer graphene. The methodology reveals that holes that are randomly distributed transverse to the direction of heat flow, but that exhibit some periodicity along the direction of heat flow, represent the optimal distribution to minimizing the thermal conductivity for porous graphene. Lattice dynamics calculations and wave packet simulations reveal that this spatial distribution effectively causes localization of the phonon modes in porous graphene, which reduces the thermal conductivity. Overall, this work demonstrates the power of machine learning-based design approaches to efficiently obtain new physical insights for scientific problems of interest.

Purpose For fixed-wing micro air vehicles, the attitude determination is usually produced by the horizon/Global Navigation Satellite System (GNSS) in which the GNSS provides yaw estimates, while roll and pitch are computed using horizon sensors. However, the attitude determination has been independently obtained from the two sensors, which will result in insufficient usage of data. Also, when implementing attitude determination algorithms on embedded platforms, the computational resources are highly restricted. This paper aims to propose a computationally efficient linear Kalman filter to solve the problem. Design/methodology/approach The observation model is in the form of a least-square optimization composed by GNSS and horizontal measurements. Analytical quaternion solution along with its covariance is derived to significantly speed up on-chip computation. Findings The reconstructed attitude from Horizon/GNSS is integrated with quaternion kinematic equation from gyroscopic data that builds up a fast linear Kalman filter. The proposed filter does not involve coupling effects presented in existing works and will be more robust encountering bad GNSS measurements. Originality/value Electronic systems are designed on a real-world fixed-wing plane. Experiments are conducted on this platform that show comparisons on the accuracy and computation execution time of the proposed method and existing representatives. The results indicate that the proposed algorithm is accurate and much faster computation speed in studied scenarios.

A facile, one-step hydrothermal route was exploited to prepare SnO2-decorated reduced graphene oxide hydrogel (SnO2/RGOH) with three-dimensional (3D) porous structures for NO2 gas detection. Various material characterizations demonstrate the effective deoxygenation of graphene oxide and in situ growth of rutile SnO2 nanoparticles (NPs) on 3D RGOH. Compared with the pristine RGOH, the SnO2/RGOH displayed much lower limit of detection (LOD) and an order of magnitude higher sensitivity, revealing the distinct impact of SnO2 NPs in improving the NO2-sensing properties. An exceptional low theoretical LOD of 2.8 ppb was obtained at room temperature. The p-n heterojunction formed at the interface between RGOH and SnO2 facilitates the charge transfer, improving both the sensitivity in NO2 detection and the conductivity of hybrid material. Considering that existing SnO2/RGO-based NO2 sensors suffer from great vulnerability to humidity, here we employed integrated microheaters to effectively suppress the response to humidity, with nearly unimpaired response to NO2, which boosted the selectivity. Notably, a flexible NO2 sensor was constructed on a liquid crystal polymer substrate with endurance to mechanical deformation. This work indicates the feasibility of optimizing the gas-sensing performance of sensors by combining rational material hybridization, 3D structural engineering with temperature modulation.

An artificial photosynthetic assembly (APA) of a hollow-rod structure was successfully constructed by using synthetic building blocks to mimic the structure and function of natural photosynthetic bacteria. The APA was formed by the incorporation of carbon nanoparticles as light harvesters into an enzyme-like polymer, PEI-Co, containing cobalt complexes as redox catalytic centres. The APA features a bacteria-like shape of ca. 2–3 μm length rods and a hollow structure positioning photosynthetic components at the surface. The APA integrates key components, the light harvester, redox catalyst, and proton relay group, of photosynthetic systems in assemblies formed from a polymeric framework. The APA system in aqueous solution converts protons to H2 under visible light irradiation with obvious advantages. It exhibits a 50-fold improvement in hydrogen production activity and has a broader pH response of photocatalytic H2 production compared with a non-assembled system.

Identifying the geographical locations of online social media users, a.k.a. user geolocation (UG), is an essential task for many location-based applications such as advertising, social event detection, emergency localization, etc. Due to the unwillingness of revealing privacy information for most users, it is challenging to directly locate users with the ground-truth geotags. Recent efforts sidestep this limitation through retrieving users’ locations by alternatively unifying user generated contents (e.g., texts and public profiles) and online social relations. Though achieving some progress, previous methods rely on the similarity of texts and/or neighboring nodes for user geolocation, which suffers the problems of: (1) location-agnostic problem of network representation learning, which largely impedes the performance of their prediction accuracy; and (2) lack of interpretability w.r.t. the predicted results that is crucial for understanding model behavior and further improving prediction performance. To cope with such issues, we proposed a Multiple-aspect Attentional Graph Neural Networks (MAGNN) – a novel GNN model unifying the textual contents and interaction network for user geolocation prediction. The attention mechanism of MAGNN has the ability to capture multi-aspect information from multiple sources of data, which makes MAGNN inductive and easily adapt to few label scenarios. In addition, our model is able to provide meaningful explanations on the UG results, which is crucial for practical applications and subsequent decision makings. We conduct comprehensive evaluations over three real-world Twitter datasets. The experimental results verify the effectiveness of the proposed model compared to existing methods and shed lights on the interpretable user geolocation.

It has been proved that silicon-substituted calcium phosphate ceramics possess superior bone regeneration and resorbability to HA, while the synthesis of single-phase nanocrystallized high Si-containing calcium phosphate is still a challenge. In the present work, a novel and facile aqueous precipitation method assisted with ultrasonic irradiation was adopted firstly to synthesise a single-phase nanocrystallized calcium silicophosphate (Ca5(PO4)2SiO4, CPS) biomaterial. Crystallization and morphology of Si-apatite precursors synthesized with or without ultrasonic assistance were primarily investigated and the related mechanism was discussed. Moreover, the sinterability, in vitro bioactivity and osteogenic activity of the synthesized CPS were studied in detail. Results showed that an ultrasonic cavitation effect could be beneficial to form a highly dispersive CPS precursor with a single Si-apatite phase, which greatly reduced the calcination temperature of CPS from 1350 °C to 1000 °C. Nanocrystallized CPS powders were obtained successfully under ultrasound-assisted conditions, which showed superior sinterability, in vitro bioactivity and osteogenic activity than those of micron-sized CPS and HA powders. It might be a promising candidate material for bone tissue regeneration applications.