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With the continuous expansion of satellite constellation, this paper analyzed the characteristics of mega constellation, and summarized the capability requirements of routing algorithms for mega constellation from two aspects of networking transmission and service requirements, included reducing signaling overhead, load balancing, fault recovery, and guaranteeing QoS.In addition, it introduced the routing methods, algorithms, and their performances that were applicable to mega constellation.It looked forward to the future related technology directions for mega constellation, included software defined network, area division management, artificial intelligence, and computing power routing, with the aim of providing reference for the construction of 6G satellite Internet.

Abstract Background Quantitative determination of the correlation between cognitive ability and functional biomarkers in the older brain is essential. To identify biomarkers associated with cognitive performance in the older, this study combined an index model specific for resting-state functional connectivity (FC) with a supervised machine learning method. Methods Performance scores on conventional cognitive test scores and resting-state functional MRI data were obtained for 98 healthy older individuals and 90 healthy youth from two public databases. Based on the test scores, the older cohort was categorized into two groups: excellent and poor. A resting-state FC scores model (rs-FCSM) was constructed for each older individual to determine the relative differences in FC among brain regions compared with that in the youth cohort. Brain areas sensitive to test scores could then be identified using this model. To suggest the effectiveness of constructed model, the scores of these brain areas were used as feature matrix inputs for training an extreme learning machine. classification accuracy (CA) was then tested in separate groups and validated by N-fold cross-validation. Results This learning study could effectively classify the cognitive status of healthy older individuals according to the model scores of frontal lobe, temporal lobe, and parietal lobe with a mean accuracy of 86.67%, which is higher than that achieved using conventional correlation analysis. Conclusion This classification study of the rs-FCSM may facilitate early detection of age-related cognitive decline as well as help reveal the underlying pathological mechanisms.

Abstract A large area of coarse-grained saline soil is distributed in saline soil areas, and chlorine saline soil with a high salt content is a typical representative. The dynamic resilient modulus was accurately predicted using the California-bearing ratio (CBR) value to determine the relationship between the dynamic resilient modulus of coarse-grained chloride saline soil and its CBR value. Indoor dynamic triaxial tests and CBR tests were conducted to investigate the evolution of the dynamic resilient modulus (M R) and CBR of coarse-grained chlorine saline soil under the influence of the stress level, water content, and salt content. The test results showed that the dynamic resilient modulus increased with an increase in the confining pressure and bulk stress and decreased as the deviator stress increased; however, the CBR increased with an increase in the corresponding unit pressure. The higher the salt and water contents, the more obvious the influence of stress on the dynamic resilient modulus and CBR value. Under the same stress level, the decrease in the dynamic resilient modulus and CBR gradually increased with increasing salt and moisture content, and the effect of salt tended to be more significant than that of water. Based on the correlation between the dynamic resilient modulus and CBR revealed by the experiment, a more widely applicable model was selected from the existing theoretical models related to CBR for the regression analysis of the test data, and a prediction model of the dynamic resilient modulus based on the CBR value was proposed (M R = 21.06CBR 0.52). This prediction model had a high correlation coefficient (R 2 = 0.893) and could effectively predict the dynamic resilient modulus of coarse-grained chlorine saline soil using CBR values. The results provide a simple and reliable method for determining the design parameters of a coarse-grained saline soil subgrade.

Intuitively, global video context could benefit video semantic segmentation (VSS) if it is designed to simultaneously model global temporal and spatial dependencies for a holistic understanding of the semantic scenes in a video clip. However, we found that the existing VSS approaches focus only on modeling local video context. This paper attempts to bridge this gap by learning global video context for VSS. Apart from the global nature, the video context should also be compact when considering the large number of video feature tokens and the redundancy among nearby video frames. Then, we embed the learned global and compact video context into the features of the target video frame to improve the distinguishability. The proposed VSS method is dubbed Global and Compact Video Context Embedding (GCVCE). With the compact nature, the number of global context tokens is very limited so that GCVCE is flexible and efficient for VSS. Since it may be too challenging to directly abstract a large number of video feature tokens into a small number of global context tokens, we further design a Cascaded Convolutional Downsampling (CCD) module before GCVCE to help it work better. 1.6% improvement in mIoU on the popular VSPW dataset compared to previous state-of-the-art methods demonstrate the effectiveness and efficiency of GCVCE and CCD for VSS. Code and models will be made publicly available.

Abstract Currently, there is a lack of effective treatments for spinal cord injury (SCI), a debilitating medical condition associated with enduring paralysis and irreversible neuronal damage. Extradural decompression of osseous as well as soft tissue components has historically been the principal objective of surgical procedures. Nevertheless, this particular surgical procedure fails to tackle the intradural compressive alterations that contribute to secondary SCI. Here, we propose an early intrathecal decompression strategy and evaluate its role on function outcome, tissue sparing, inflammation, and tissue stiffness after SCI. Durotomy surgery significantly promoted recovery of hindlimb locomotor function in an open‐field test. Radiological analysis suggested that lesion size and tissue edema were significantly reduced in animals that received durotomy. Relative to the group with laminectomy alone, the animals treated with a durotomy had decreased cavitation, scar formation, and inflammatory responses at 4 weeks after SCI. An examination of the mechanical properties revealed that durotomy facilitated an expeditious restoration of the injured tissue's elastic rigidity. In general, early decompressive durotomy could serve as a significant strategy to mitigate the impairments caused by secondary injury and establish a more conducive microenvironment for prospective cellular or biomaterial transplantation.

Abstract Objective To study the efficacy and safety of arbidol hydrochloride tablets as a treatment for influenza-like diseases. Methods In this multicenter, randomized, controlled, open label study, a total of 412 influenza-like cases were collected from 14 hospitals in seven regions of Hebei Province from September 2021 to March 2022. Patients were randomly divided into two groups. The control group (n = 207) were administered oseltamivir phosphate capsules for five days and the experimental group (n = 205) were administered arbidol hydrochloride tablets for five days. The primary endpoint was the time to normal body temperature, and the secondary endpoints included the time to remission of influenza symptoms, incidence of influenza-like complications, and incidence of adverse reactions. Results Before treatment, there was no significant difference between the two groups in general conditions, blood routine, body temperature, or symptom severity. After treatment, there was no significant difference between the groups in the mean time to fever remission (59.24 h ± 25.21 vs. 61.05 h ± 29.47) or the mean time to remission of influenza symptoms (57.31 h ± 30.19 vs. 62.02 h ± 32.08). Survival analyses using Log-rank and Wilcoxon bilateral tests showed that there was no significant difference in fever relief time or influenza symptom relief time between the two groups. Regarding the incidence of complications and adverse events, there was only one case of tracheitis, one case of nausea, one case of vomiting, and one case of dizziness in the control group. In the experimental group, there was one case of nausea, one case of vomiting, and one case of drowsiness. In addition, one patient in the control group was hospitalized for urinary calculi. Conclusion There was no significant difference between the patients with influenza-like cases treated with arbidol hydrochloride tablets and those treated with oseltamivir phosphate capsules. Further, the patients treated with arbidol hydrochloride tablets had fewer adverse reactions, and thus, the tablets were safe to use.

Can a robotic gripper only operate when attached to a robotic arm? The application space of the traditional gripper is limited by the robotic arm. Giving robot grippers the ability to move will expand their range of applications. Inspired by rich behavioral repertoire observed in octopus, we implement an integrated multifunctional soft robotic gripper with 6 independently controlled Arms. It can execute 8 different gripping actions for different objects, such as irregular rigid/soft objects, elongated objects with arbitrary orientation, and plane/curved objects with larger sizes than the grippers. Moreover, the soft gripper can realize omnidirectional crawling and swimming by itself. The soft gripper can perform highly integrated tasks of releasing, crawling, swimming, grasping, and retrieving objects in a confined underwater environment. Experimental results demonstrate that the integrated capabilities of multimodal adaptive grasping and omnidirectional motions enable dexterous manipulations that traditional robotic arms cannot achieve. The soft gripper may apply to highly integrated and labor-intensive tasks in unstructured underwater environments, including ocean litter collecting, capture fishery, and archeological exploration.

How to select suitable pavement materials for asphalt pavements according to the functional requirements of layers is still the focus of research by scholars in various countries. However, their effectiveness in combating high-temperature rutting and fatigue cracking in middle and lower layers is limited. To address this issue, a study optimized the incorporation of basalt fibers in different layers to improve road performance based on design specifications. Nine asphalt pavement structures with varying amounts of basalt fibers were assessed using an orthogonal test method. The optimal structure was determined considering factors such as fatigue life and overloading using the finite element method for modeling. Results showed that fiber dosage had a minimal impact on road surface bending subsidence and the location of tensile strain in the lower layer. Shear stresses were concentrated mainly at the outer edges of loads. Optimal dosages of basalt fiber were determined for different layers: 0.3% for the upper layer, 0.1% for the middle layer, and 0.3% for the lower layer. The optimal structure consists of a strong base with a thin-surfaced semi-rigid base layer, with 0.3% for the upper layer and 0.1% for the middle layer. This study provided valuable insights into designing basalt fiber asphalt pavement structures.

In order to realize the unsupervised segmentation of subtle defect images on the surface of small magnetic rings and improve the segmentation accuracy and computational efficiency, here, an adaptive threshold segmentation method is proposed based on the improved multi-scale and multi-directional 2D-Gabor filter bank. Firstly, the improved multi-scale and multi-directional 2D-Gabor filter bank was used to filter and reduce the noise on the defect image, suppress the noise pollution inside the target area and the background area, and enhance the difference between the magnetic ring defect and the background. Secondly, this study analyzed the grayscale statistical characteristics of the processed image; the segmentation threshold was constructed according to the gray statistical law of the image; and the adaptive segmentation of subtle defect images on the surface of small magnetic rings was realized. Finally, a classifier based on a BP neural network is designed to classify the scar images and crack images determined by different threshold segmentation methods. The classification accuracies of the iterative method, the OTSU method, the maximum entropy method, and the adaptive threshold segmentation method are, respectively, 85%, 87.5%, 95%, and 97.5%. The adaptive threshold segmentation method proposed in this paper has the highest classification accuracy. Through verification and comparison, the proposed algorithm can segment defects quickly and accurately and suppress noise interference effectively. It is better than other traditional image threshold segmentation methods, validated by both segmentation accuracy and computational efficiency. At the same time, the real-time performance of our algorithm was performed on the advanced SEED-DVS8168 platform.

Motion segmentation is a formidable computer vision task, aiming to segment moving targets from a dynamic scene. In this paper, we choose to introduce an additional modality to bolster the robustness. The event camera is a bio-inspired sensor that accurately detects and captures intensity changes with exceptional temporal resolution and dynamic range, which is an optimal choice for motion segmentation. Therefore, we present a novel framework for event-based motion segmentation and propose Multi-Scale Recurrent Neural Network (MSRNN) to fuse temporal information efficiently. To our best knowledge, it is the first time that a multi-scale recurrent architecture is implemented in event-based motion segmentation. The proposed framework is evaluated through experiments conducted on the EV-IMO dataset. Our method achieves a mean Intersection-over-Union (mIoU) of 82.0%, which sets a new state-of-the-art in motion segmentation. To further validate our approach in arduous real-world scenarios, we introduce the Event Challenging Motion dataset, consisting of 350 images and corresponding events, in which our method outperforms the other methods by 1.5% in Intersection-over-Union (IoU).

Abstract Claudins, the integral tight junction proteins that regulate paracellular permeability and cell polarity, are frequently dysregulated in cancer; however, their roles in regulating EGFR tyrosine kinase inhibitors (EGFR-TKIs) resistance in non-small cell lung cancer (NSCLC) are unknown. To this end, we performed GEO dataset analysis and identified that claudin1 was a critical regulator of EGFR-TKI resistance in NSCLC cells. We also found that claudin1, which was highly induced by continuous gefitinib treatment, was significantly upregulated in EGFR-TKI-resistant NSCLC cells. By knocking down claudin1 in cell lines and xenograft models, we established that gefitinib resistance was decreased. Moreover, claudin1 knockdown suppressed the expression levels of pluripotency markers (Oct4, Nanog, Sox2, CD133, and ALDH1A1). Claudin1 loss inhibited phosphorylated AKT (p-AKT) expression and reduced cancer cell stemness by suppressing AKT activation. Furthermore, SKL2001, a β-catenin agonist, upregulated the expression levels of claudin1, p-AKT, and pluripotency markers, and 1,25-dihydroxy-vitamin D3 (1,25(OH)2D3) reduced claudin1 expression, AKT activation, and cancer cell stemness by inhibiting β-catenin, and suppressed claudin1/AKT pathway mediated cancer stem-like properties and gefitinib resistance. Collectively, inhibition of claudin1-mediated cancer stem-like properties by 1,25(OH)2D3 may decrease gefitinib resistance through the AKT pathway, which may be a promising therapeutic strategy for inhibiting gefitinib resistance in EGFR-mutant lung adenocarcinoma.

The strength-formation mechanism for industrial-construction residue cement stabilization of crushed aggregate (IRCSCA) is not clear. To expand the application range for recycled micro-powders in road engineering, the dosages of eco-friendly hybrid recycled powders (HRPs) with different proportions of RBP and RCP affecting the strengths of cement-fly ash mortar at different ages, and the strength-formation mechanism, were studied with X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results showed that the early strength of the mortar was 2.62 times higher than that of the reference specimen when a 3/2 mass ratio of brick powder and concrete powder was mixed to form the HRP and replace some of the cement. With increasing HRP content substituted for fly ash, the strength of the cement mortar first increased and then decreased. When the HRP content was 35%, the compressive strength of the mortar was 1.56 times higher than that of the reference specimen, and the flexural strength was 1.51 times higher; XRD and SEM studies of the hydrated cement mixed with HRP showed that the amount of CH in the cement paste was reduced by the pozzolanic reaction of HRP at later hydration ages, and it was very useful in improving the compactness of the mortar. The XRD spectrum of the cement paste made with HRP indicated that the CH crystal plane orientation index R, with a diffraction angle peak of approximately 34.0, was consistent with the cement slurry strength evolution law, and this research provides a reference for the application of HRP to produce IRCSCA.

The flow behavior of Ti-6Al-4V alloy in superplastic forming (SPF) is studied, and a simple constitutive model is established based on the hyperbolic-sine equation. The constant strain rate high temperature tensile tests were performed at 890, 920, and 950℃, the selected strain rates are 10-2, 10-3, and 10-4/s. The calculation results of strain rate sensitivity index (m) indicates there are two dominant mechanisms of deformation: (i) grain boundary sliding (GBS) when the temperature is below 920℃ or strain rate is above 10-3/s; (ii) GBS and diffusion creep if the temperature is above 920℃ and strain rate is below 10-3/s. Besides, the higher temperatures or the lower strain rates, the smaller void volume fraction. The genetic algorithm (GA) is applied to optimize the parameters in the constitutive model, the average absolute relative error (AARE) between the prediction results and experimental data of stress is reduced from 11.10% to 5.52%. A new modeling method of strain compensation is provided, which is based on stress hardening and softening. The term K is introduced to describe the effects of strain on flow behavior in SPF, and a good agreement between the predicted results and experimental data can be obtained. In summary, the simple hyperbolic-sine constitutive model established in this work with parameter optimization can achieve high prediction accuracy.

With the development of computer vision and mobile computing, assistive navigation for people with visual impairment arouses the attention of research communities. As two key challenges of assistive navigation, “Where am I?” and “What are the surroundings?” are still to be resolved by taking advantage of visual information. In this paper, we leverage the prevailing compact network as the backbone to build a unified network featuring two branches that implement scene description and scene recognition separately. Based on the unified network, the proposed pipeline performs scene recognition and visual localization simultaneously in the scenario of assistive navigation. The visual localization pipeline involves image retrieval and sequence matching. In the experiments, different configurations of the proposed pipeline are tested on public datasets to search for the optimal parameters. Moreover, on the real-world datasets captured by the wearable assistive device, the proposed assistive navigation pipeline is proved to achieve satisfactory performance. On the challenging dataset, the top-5 precision of scene recognition is more than 80%, and the visual localization precision is over 60% under a recall of 60%. The related codes and datasets are open-source online at https://github.com/chengricky/ScenePlaceRecognition.

Asphalt concrete pavement is gradually being adopted in cement concrete pavement repair and paving due to its short construction period and low vibration to aircraft. However, the performance of the interlayer binder is the critical factor affecting the paving effect. For the preparation of interlayer high-performance emulsified asphalt suitable for airport pavement, the type and dosage of modifier and emulsifier were taken as factors and levels for the orthogonal test. Combined with the evaporation residue, softening point, penetration, ductility, and Engla viscosity indexes, the range analysis was carried out to determine the optimal dosage of modifier and emulsifier. Furthermore, the dynamic shear rheology test (DSR), fluorescence microscope test, TG-DSC test, and shear and tensile tests were used to evaluate the technical properties of SBS/SBR modified emulsified asphalt. These results showed that the best blending mass ratio of SBS/SBR modified emulsified asphalt is 1.5% SBS + 3% SBR + 1% emulsifier. Temperature sweep at 48°C, compared with SBS/SBR modified emulsified asphalt, the complex shear modulus (G∗) of SBS/SBR modified emulsified asphalt increased by 71% and 75%, while the rutting factor(G∗/sinδ) increased by 83% and 86%, respectively, which indicates that its shear deformation resistance and rutting resistance have been significantly improved. The Han curve indicates that the SBS/SBR modifier has excellent compatibility with asphalt and can maintain a stable state at a lower frequency. Before demulsification, SBS/SBR modifier and emulsified asphalt formed a stable spatial network structure. After demulsification, the continuous phase and the dispersed phase were more closely integrated, so that the emulsified asphalt exhibited better bonding performance. At different temperatures, by increasing the spraying volume, the shear and tensile strength of SBS/SBR modified emulsified asphalt increased first and then decreased. At 25°C, the maximum shear and tensile strengths are 0.86 MPa and 0.65 MPa. This study demonstrated that SBS/SBR modified emulsified asphalt formed a stable spatial network structure, giving it excellent technical properties, and can be widely used for tack coat on airport pavement.

The recycled powder produced in the process of crushing concrete and brick waste (C&BW) into recycled aggregate will cause environmental pollution. To realize the green full recycling of concrete and brick waste, the cement stabilization of crushed aggregate (CSCA) containing recycled brick-concrete composite micropowder (RBCP) and recycled brick-concrete composite aggregate (RBCA) is proposed. In this paper, RBCP, recycled brick-concrete composite fine aggregate (RBCFA), and recycled brick-concrete composite coarse aggregate (RBCCA) were the recycled materials from C&BW. The orthogonal test table was used to analyze the effects of the three recycled materials on the compaction characteristics, mechanical properties, and shrinkage behavior of CSCA at different dosages. The effects of RBCP, RBCCA, and RBCFA on the properties of CSCA are studied by variance analysis methods. On this basis, the micromorphology and the interface transition zone (ITZ) were studied for CSCA and the cement stabilization of crushed aggregate with RBCP, RBCFA, and RBCCA through scanning electron microscopy with energy dispersive spectroscopy (SEM/EDS), and the mechanism was revealed. The results indicate that the addition of RBCP and RBCA can increase the optimal water content while decreasing the optimal dry density of CSCA, and the influence of RBCCA on the optimal water content is greater than that of RBCFA. Three optimal composite replacement systems for CSCA, including 20% RBCP/20%RBCFA/40%RBCCA, are proposed and have the best mechanical and antishrinkage performance through the range analysis. Furthermore, the variance analysis test results show that RBCCA and RBCFA have the most significant effect on the compressive strength and shrinkage strain properties, while RBCP has the most significant effect on the bending tensile strength. It is found that RBCP played a filling effect and pozzolanic activity in the strength formation of CSCA. The SEM/EDS test shows that the CSCA with recycled materials produced the Ca/Si ratio in the interfacial zone between the cement paste and aggregate lower than the CSCA without recycled materials, the largest decline 52.83%. The research results of this paper can provide the potential application of RBCP and RBCA.

Tubulointerstitial fibrosis is one of the most common pathological features of diabetic nephropathy. Autophagy, an intracellular mechanism to remove damaged or dysfunctional cell parts and maintain metabolic homeostasis, is inhibited in diabetic neuropathy. Icariin is a traditional Chinese medicine extract known for nourishing the kidney and reinforcing Yang. In this study, we investigated the effects and mechanism of Icariin on renal function, autophagy, and fibrosis in type 2 diabetic nephropathic rats and in high-glucose-incubated human renal tubular epithelial cells and rat renal fibroblasts (in vitro). Icariin improved diabetes, renal function, restored autophagy, and alleviated fibrosis in type 2 diabetic neuropathic rats and in vitro. After we applied autophagy-related gene 5-small interfering RNA, we found that fibrosis improvement by Icariin was related to autophagy restoration. By detecting serum sex hormone levels, and using dihydrotestosterone, siRNA for androgen receptor, and the androgen receptor antagonist Apalutamide (ARN-509), we found that Icariin had an androgen-like effect and restored autophagy and reduced fibrosis by regulating the androgen receptor. In addition, miR-192-5p levels were increased under high glucose but reduced after dihydrotestosterone and Icariin treatment. Furthermore, dihydrotestosterone and Icariin inhibited miR-192-5p overexpression-induced fibrosis production and autophagy limitation. Glucagon-like peptide-1 receptor (GLP-1R) was downregulated by high glucose and overexpression of miR-192-5p and could be restored by dihydrotestosterone and Icariin. By using ARN-509, we found that Icariin increased GLP-1R expression by regulating the androgen receptor. GLP-1R-siRNA transfection weakened the effects of Icariin on autophagy and fibrosis. These findings indicate that Icariin alleviates tubulointerstitial fibrosis by restoring autophagy through the miR-192-5p/GLP-1R pathway and is a novel therapeutic option for diabetic fibrosis.

Ethnopharmacological relevance:Scutellaria baicalensis georgi is one of the most widely studied TCMs; its effects in ALI have been studied in a large number of experiments, and the efficacy of volatile oil from TCM remains to be studied.Aim: The volatile component of Scutellaria baicalensis georgi was selected to act on the key target of acute lung injury and was preliminarily studied for its specific molecular mechanism.Methods: The volatile active substances of Scutellaria baicalensis georgi were extracted by GC–MS, and the active ingredients related with the occurrence and development of acute lung injury were searched and matched by the TCMSP database. The pharmacologic data and analysis platform of TCM were used to retrieve and screen for the volatile active components and the possible therapeutic targets of Scutellaria baicalensis georgi. In addition, acute lung injury was searched in the disease target database to identify the corresponding disease target proteins, thereby establishing a protein–protein interaction network. Finally, the effects of wogonin on the apoptotic and inflammatory factors in the acute lung injury cell model were analyzed experimentally.Results: We identified 100 candidate targets and successfully constructed a complex target network. The targets identified by the above gene enrichment analysis played important roles in the autoimmune disease cell cycle apoptosis and related signaling pathways. The KEGG pathway analysis showed that most of the target genes were involved in the inflammatory response regulation of the TRP, PI3K-Akt, and IL-17 signaling pathways. The participation of wogonin in the specific regulatory pathways of PI3K-Akt signaling and IL-17 signaling was verified through experiments. In the lung-injured cell model, the results showed that wogonin inhibited the apoptosis of injured lung cells by inhibiting the expression of BAD gene and the activation of cleaved caspase-3 gene while increasing Bcl-2 expression. In addition, wogonin inhibited the expression of the abovementioned inflammatory factors and further inhibited the inflammatory response in the lung injury cells.Conclusion: The results of pharmacological network analysis can predict and explain the regulation mechanism of multi-target and multi-pathway of TCM components. This study identified the potential target and important pathway of wogonin in regulating acute lung injury. At the same time, the accuracy of network pharmacological prediction is also preliminarily verified by molecular biology experiment.

Bandwidth is an important parameter for accelerometers, in some cases, even surpassing sensitivity. However, there are few studies focused on the relationship between bandwidth and environmental conditions in practical application of accelerometers. In this paper, we systematically analyze the influence of environment on the bandwidth of accelerometers, obtaining the amplitude–frequency response curves versus damping ratio and properties of materials, wherein temperature and humidity were found as the two dominant factors that influence the bandwidth of accelerometers. Common temperature and humidity variations can result in bandwidth degradation of about 25% according to our theoretical analysis. The finite element method (FEM) is introduced to verify our theoretical analysis, and the accordance of the FEM simulation results and the theoretical results confirmed the validity of our analysis. Furthermore, a modification design is proposed to compensate for the influence of temperature and humidity on the bandwidth of accelerometers. By choosing materials with an appropriate Young’s modulus and coefficient of thermal expansion, the degradation of the bandwidth was substantially diminished by more than one order of magnitude, which can serve as a strong guide for the future realization of accelerometers with a steady and large bandwidth.

Scene sonification is a powerful technique to help Visually Impaired People (VIP) understand their surroundings. Existing methods usually perform sonification on the entire images of the surrounding scene acquired by a standard camera or on the priori static obstacles acquired by image processing algorithms on the RGB image of the surrounding scene. However, if all the information in the scene are delivered to VIP simultaneously, it will cause information redundancy. In fact, biological vision is more sensitive to moving objects in the scene than static objects, which is also the original intention of the event-based camera. In this paper, we propose a real-time sonification framework to help VIP understand the moving objects in the scene. First, we capture the events in the scene using an event-based camera and cluster them into multiple moving objects without relying on any prior knowledge. Then, sonification based on MIDI is enabled on these objects synchronously. Finally, we conduct comprehensive experiments on the scene video with sonification audio attended by 20 VIP and 20 Sighted People (SP). The results show that our method allows both participants to clearly distinguish the number, size, motion speed, and motion trajectories of multiple objects. The results show that our method is more comfortable to hear than existing methods in terms of aesthetics.

In order to help visually impaired people to avoid obstacles, a K-band millimetre wave (MMW) radar system based on the principle of frequency-modulated continuous wave (FMCW) is proposed in this study. The FMCW basic principle and the signal processing algorithm are elaborated in detail. The prototype of the radar system has been designed and manufactured. The experiment results show the qualified detection accuracy in view of low deviation. The maximum deviations from the range measurement experiments for a person and a car are 0.14 and 0.47 m, respectively. As a wearable system, the radar system has the characteristics of low power and small size, which is very suitable for blind navigation application. In addition, the MMW radar has broad application prospects in the field of automotive blind spot detection and small robots.

Visual Place Recognition (VPR) addresses visual instance retrieval tasks against discrepant scenes and gives precise localization. During a traverse, the captured images (query images) would be traced back to the already existing positions in the database images, rendering vehicles or pedestrian navigation devices distinguish ambient environments. Unfortunately, diverse appearance variations can bring about huge challenges for VPR, such as illumination changing, viewpoint varying, seasonal cycling, disparate traverses (forward and backward), and so on. In addition, the majority of current VPR algorithms are designed for forward-facing images, which can only provide with narrow Field of View (FoV) and come with severe viewpoint influences. In this paper, we propose a panoramic localizer, which is based on coarse-to-fine descriptors, leveraging panoramas for omnidirectional perception and sufficient FoV up to 360∘. We adopt NetVLAD descriptors in the coarse matching in a panorama-to-panorama way, for their robust performances in distinguishing different appearances, utilizing Geodesc keypoint descriptors in the fine stage in the meantime, for their capacity of detecting detailed information, formatting powerful coarse-to-fine descriptors. A comprehensive set of experiments is conducted on several datasets including both public benchmarks and our real-world campus scenes. Our system is proved to be with high recall and strong generalization capacity across various appearances. The proposed panoramic localizer can be integrated into mobile navigation devices, available for a variety of localization application scenarios.

In recent years, with the development of depth cameras and scene detection algorithms, a wide variety of electronic travel aids for visually impaired people have been proposed. However, it is still challenging to convey scene information to visually impaired people efficiently. In this paper, we propose three different auditory-based interaction methods, i.e., depth image sonification, obstacle sonification as well as path sonification, which convey raw depth images, obstacle information and path information respectively to visually impaired people. Three sonification methods are compared comprehensively through a field experiment attended by twelve visually impaired participants. The results show that the sonification of high-level scene information, such as the direction of pathway, is easier to learn and adapt, and is more suitable for point-to-point navigation. In contrast, through the sonification of low-level scene information, such as raw depth images, visually impaired people can understand the surrounding environment more comprehensively. Furthermore, there is no interaction method that is best suited for all participants in the experiment, and visually impaired individuals need a period of time to find the most suitable interaction method. Our findings highlight the features and the differences of three scene detection algorithms and the corresponding sonification methods. The results provide insights into the design of electronic travel aids, and the conclusions can also be applied in other fields, such as the sound feedback of virtual reality applications.

Interferometric optomechanical accelerometers provide superior resolution, but the application is limited due to the non-ambiguity range that is always less than half of the wavelength, which corresponds to the order of mg. This paper proposes a novel acceleration measurement method based on synthetic wavelength and single wavelength superheterodyne interferometry to address this issue. Two acousto-optical modulators and several polarizers are introduced to the two-wavelength interferometry to create four beams with different frequencies and polarization states, and two ultra-narrow bandwidth filters are used to realize the single wavelength measurement simultaneously. This technique offers the possibility to expand the non-ambiguity range without compromising the high resolution. Also, the superheterodyne phase measurement and the corresponding processing algorithm are given to enable real-time measurement. A prototype is built and the preliminary experimental results are compared with the simulation results, showing good agreement. The results prove an estimated acceleration measurement resolution of around 10 μg and a non-ambiguity range of larger than 200 mg, which is more than 100 times that of the single wavelength-based optical accelerometer.

Localization systems play an important role in assisted navigation. Precise localization renders visually impaired people aware of ambient environments and prevents them from coming across potential hazards. The majority of visual localization algorithms, which are applied to autonomous vehicles, are not adaptable completely to the scenarios of assisted navigation. Those vehicle-based approaches are vulnerable to viewpoint, appearance and route changes (between database and query images) caused by wearable cameras of assistive devices. Facing these practical challenges, we propose Visual Localizer, which is composed of ConvNet descriptor and global optimization, to achieve robust visual localization for assisted navigation. The performance of five prevailing ConvNets are comprehensively compared, and GoogLeNet is found to feature the best performance on environmental invariance. By concatenating two compressed convolutional layers of GoogLeNet, we use only thousands of bytes to represent image efficiently. To further improve the robustness of image matching, we utilize the network flow model as a global optimization of image matching. The extensive experiments using images captured by visually impaired volunteers illustrate that the system performs well in the context of assisted navigation.

Optical coupling between subwavelength grating pairs allows for the precise measurement of lateral or vertical displacement of grating elements and gives rise to different types of displacement and inertial sensors. In this paper, we demonstrate a design for a nano-optomechanical accelerometer based on a subwavelength grating pair that can be easily fabricated by a single Silicon-on-insulator (SOI) chip. The parameters of the subwavelength grating pair-based optical readout, including period, duty cycle, thickness of grating and metal film, and the distance of the air gap, were optimized by combining a genetic algorithm and rigorous coupled wavelength analysis (RCWA) to obtain the optimal sensitivity to the displacement of suspended grating element and the acceleration. A corresponding mechanical design was also completed to meet the highly sensitive acceleration measurement requirement while considering the mechanical cross-axis sensitivity, dynamic range, bandwidth, and fabrication feasibility. This device was verified by both RCWA and finite-different-time-domain methods, and a tolerance analysis was also completed to confirm that it is able to achieve the extremely high optical displacement sensitivity of 1.8%/nm, acceleration-displacement sensitivity of 1.56 nm/mg, and acceleration measurement sensitivity of more than 2.5%/mg, which is almost one order of magnitude higher than any reported counterparts. This work enables a single SOI-based high performance accelerometer, and provides a theoretical basis and fabrication guides for the design.

Navigational assistance aims to help visually-impaired people to ambulate the environment safely and independently. This topic becomes challenging as it requires detecting a wide variety of scenes to provide higher level assistive awareness. Vision-based technologies with monocular detectors or depth sensors have sprung up within several years of research. These separate approaches have achieved remarkable results with relatively low processing time and have improved the mobility of impaired people to a large extent. However, running all detectors jointly increases the latency and burdens the computational resources. In this paper, we put forward seizing pixel-wise semantic segmentation to cover navigation-related perception needs in a unified way. This is critical not only for the terrain awareness regarding traversable areas, sidewalks, stairs and water hazards, but also for the avoidance of short-range obstacles, fast-approaching pedestrians and vehicles. The core of our unification proposal is a deep architecture, aimed at attaining efficient semantic understanding. We have integrated the approach in a wearable navigation system by incorporating robust depth segmentation. A comprehensive set of experiments prove the qualified accuracy over state-of-the-art methods while maintaining real-time speed. We also present a closed-loop field test involving real visually-impaired users, demonstrating the effectivity and versatility of the assistive framework.

The use of RGB-Depth (RGB-D) sensors for assisting visually impaired people (VIP) has been widely reported as they offer portability, function-diversity and cost-effectiveness. However, polarization cues to assist traversability awareness without precautions against stepping into water areas are weak. In this paper, a polarized RGB-Depth (pRGB-D) framework is proposed to detect traversable area and water hazards simultaneously with polarization-color-depth-attitude information to enhance safety during navigation. The approach has been tested on a pRGB-D dataset, which is built for tuning parameters and evaluating the performance. Moreover, the approach has been integrated into a wearable prototype which generates a stereo sound feedback to guide visually impaired people (VIP) follow the prioritized direction to avoid obstacles and water hazards. Furthermore, a preliminary study with ten blindfolded participants suggests its effectivity and reliability.

The introduction of RGB-Depth (RGB-D) sensors into the visually impaired people (VIP)-assisting area has stirred great interest of many researchers. However, the detection range of RGB-D sensors is limited by narrow depth field angle and sparse depth map in the distance, which hampers broader and longer traversability awareness. This paper proposes an effective approach to expand the detection of traversable area based on a RGB-D sensor, the Intel RealSense R200, which is compatible with both indoor and outdoor environments. The depth image of RealSense is enhanced with IR image large-scale matching and RGB image-guided filtering. Traversable area is obtained with RANdom SAmple Consensus (RANSAC) segmentation and surface normal vector estimation, preliminarily. A seeded growing region algorithm, combining the depth image and RGB image, enlarges the preliminary traversable area greatly. This is critical not only for avoiding close obstacles, but also for allowing superior path planning on navigation. The proposed approach has been tested on a score of indoor and outdoor scenarios. Moreover, the approach has been integrated into an assistance system, which consists of a wearable prototype and an audio interface. Furthermore, the presented approach has been proved to be useful and reliable by a field test with eight visually impaired volunteers.