Brain-like position measurement method based on improved optical flow algorithm.

In this paper, a brain-like navigation scheme based on fuzzy kernel C-means (FKCM) clustering assisted pyramid Lucas Kanade (LK) optical flow algorithm is developed to measure the position of vehicle. The Speed Cell and Place Cell in animals' brain are introduced to construct the brain-like navigation mechanism which involves the optical flow method and image template matching to imitate the cells above-mentioned separately. To eliminate the singular values during optical flow calculation, the output of pyramid LK algorithm is clustered by FKCM algorithm firstly. Then, the velocity is calculated and integrated to get the position of the vehicle, and the brain-like navigation scheme is introduced to correct the position measurement errors by eliminating the accumulated errors resulting from velocity integration. The prominent advantages of the presented method are: (i) a pure visual brain-like position measurement method based on the concept of speed cells and place cells is proposed, making visual navigation more accurate and intelligent; (ii) the FKCM algorithm is used to eliminate the singular value of the pyramid LK algorithm, which improves the calculated velocity accuracy. Also, experimental comparison with classical pyramid LK algorithm is given to illustrate the superiority of the proposed method in position measurement.

Directional switches in network-organized swarming systems with delay.

Coordinated directional switches can emerge between members of moving biological groups. Previous studies have shown that the self-propelled particles model can well reproduce directional switching behaviors, but it neglects the impact of social interactions. Thus, we focus on the influence of social interactions on the ordered directional switching motion of swarming systems, in which homogeneous Erdös-Rényi networks, heterogeneous scale-free networks, networks with community structures, and real-world animal social networks have been considered. The theoretical estimation of mean switching time is obtained, and the results show that the interplay between social and delayed interactions plays an important role in regulating directional switching behavior. To be specific, for homogeneous Erdös-Rényi networks, the increase in mean degree may suppress the directional switching behaviors if the delay is sufficiently small. However, when the delay is large, the large mean degree may promote the directional switching behavior. For heterogeneous scale-free networks, the increase of degree heterogeneity can reduce the mean switching time if the delay is sufficiently small, while the increasing degree heterogeneity may suppress the ordered directional switches if the delay is large. For networks with community structures, higher communities can promote directional switches for small delays, while for large delays, it may inhibit directional switching behavior. For dolphin social networks, delay can promote the directional switching behavior. Our results bring to light the role of social and delayed interactions in the ordered directional switching motion.

High-performance subwavelength polarizer using "sandwich" structured substrates.

A subwavelength polarizer based on "sandwich" structured substrates is proposed in this study. The proposed subwavelength polarizer consists of three layers of subwavelength aluminum wires and dielectric substrate. The designed structure achieves an extinction ratio (ER) greater than 90 dB in a 400-800 nm visible wavelength region, achieving a maximum ER of 135 dB at 750 nm. Our results demonstrate significant improvements over the conventional single- and double-grid polarizers in terms of an ER and spectral range coverage. The proposed subwavelength polarizer in this paper has great potential in polarimetric imaging, liquid crystal display, and other optical fields.

Co-doped Fe-MIL-100 as an adsorbent for tetracycline removal from aqueous solution.

In the study, Fe-MIL-100 was modified by adding Co2+ in the synthesis process; Co/Fe-MIL-100 was successfully synthesized and used to adsorb tetracycline. The addition of Co2+ increased the thermal stability of Fe-MIL-100 without changing the crystal structure. It was found that Co/Fe-MIL-100 exhibited satisfactory performance in tetracycline removal, the tetracycline removal efficiency reached almost 100% in the initial concentration range of 10-40 mg/L, and it still reached 82.38% under the condition of 60 mg/L tetracycline. Besides, the factors of tetracycline concentration, pH and inorganic anion on removal efficiency were explored. The coexistence of inorganic anion decreased the adsorption capacity of tetracycline due to the competitive adsorption. CO32- had a more obvious inhibition effect on the adsorption efficiency of tetracycline than Cl-. The fitting correlation coefficient of Langmuir model was higher and the kinetics better fitted by pseudo-second-order, respectively. As a result of its high removal efficiency and excellent recycling performance, it has great potential in application fields such as removing tetracycline from wastewater.

Three-dimensional attitude determination strategy for fused polarized light and geomagnetism.

Using polarized light sensors to obtain only two-dimensional heading information does meet actual needs in navigation. Instead, an alternative method is proposed that uses the positional information of the Sun and geomagnetic information to calculate the three-dimensional attitude of a vehicle. First, the theoretical background of the polarization mode of skylight is described, and the scheme in using the atmospheric polarization pattern to calculate the solar position is presented. Second, the traditional three-axis attitude-determination (TRIAD) algorithm that exploits the solar position vector and the geomagnetic vector to obtain the three-dimensional attitude and the optimized TRIAD algorithm are introduced. Static and turntable experiments are described that verify the accuracy of the attitude calculation. Experimental results show that when using the optimized TRIAD algorithm, the root mean square errors for the roll angle, pitch angle, and heading angle are 0.1225°, 0.668°, and 1.0234°, respectively. This means that the optimized TRIAD algorithm performs significantly better than the traditional TRIAD algorithm and demonstrates that using the solar position and the geomagnetic information to obtain the three-dimensional attitude of the vehicle is very effective.

Synthetic velocity measurement algorithm of monocular vision based on square-root cubature Kalman filter.

The velocity measurement algorithm based on vision is widely used in unmanned aerial vehicle navigation. Under uneven illumination intensity distribution, the traditional Lucas-Kanade (LK) optical flow (OF) algorithm has problems arising from low computational accuracy and poor adaptability. To solve these problems, we propose a monocular vision integrated velocity measurement system based on the square-root cubature Kalman filter (SRCKF). The LK OF and the optimized oriented FAST and rotated BRIEF (ORB) algorithms are used to process the visual information obtained using a camera. The SRCKF algorithm is tasked with fusing the LK OF and optimized ORB information, thereby improving the accuracy of velocity and alleviating the sensitivity of the LK OF to variations in illumination conditions. Finally, an outdoor unmanned aerial vehicle flight test was undertaken. The experimental results show that the proposed method provides an accurate measurement of the velocity in variable illumination environments.

An optimized pulse coupled neural network image de-noising method for a field-programmable gate array based polarization camera.

The quality of polarization images is easy to be affected by the noise in the image acquired by a polarization camera. Consequently, a de-noising method optimized with a Pulse Coupled Neural Network (PCNN) for polarization images is proposed for a Field-Programmable Gate Array (FPGA)-based polarization camera in this paper, in which the polarization image de-noising is implemented using an adaptive PCNN improved by Gray Wolf Optimization (GWO) and Bi-Dimensional Empirical Mode Decomposition (BEMD). Unlike other artificial neural networks, PCNN does not need to be trained, but the parameters of PCNN such as the exponential decay time constant, the synaptic junction strength factor, and the inherent voltage constant play a critical influence on its de-noising performance. GWO is able to start optimization by generating a set of random solutions as the first population and saves the optimized solutions of PCNN. In addition, BEMD can decompose a complicated image into different Bi-Dimensional Intrinsic Mode Functions with local stabilized characteristics according to the input source image, and the decomposition result is able to lower the complexity of heavy noise image analysis. Moreover, the circuit in the polarization camera is accomplished by FPGA so as to obtain the polarization image with higher quality synchronously. These two schemes are combined to attenuate different types of noises and improve the quality of the polarization image significantly. Compared with the state-of-the-art image de-noising algorithms, the noise in the polarization image is suppressed effectively by the proposed optimized image de-noising method according to the indices of peak signal-to-noise ratio, standard deviation, mutual information, structural similarity, and root mean square error.

The influence of hydrophobicity on sludge dewatering associated with cationic starch-based flocculants.

Coagulation/flocculation is an extensive and effective pretreatment technology for improving the sludge dewaterability. A series of hydrophobically associated cationic starch-based flocculants (CS-DMRs) with different degrees of hydrophobicity but similar charge densities were designed and synthesized. The CS-DMRs exhibited excellent sludge dewatering performance. The dewaterability of sludge increased with the hydrophobicity of the CS-DMRs, and the filter cake moisture content (FCMC) and specific resistance to filtration (SRF) could be reduced from 95.47% and 7.09 × 1012 m/kg to 79.26% and 2.258 × 1012 m/kg, respectively, at a constant pressure of 0.05 MPa after conditioned by the starch-based flocculant with the highest hydrophobicity at its optimal dose. Moreover, due to their amphiphilic structures, CS-DMRs could closely interact with the negatively charged extracellular polymeric substances (EPS), efficiently compress the protein and polysaccharide in EPS, and release the bound water. A second-order polynomial model was proposed according to the phenomenological theory to quantitatively analyze the effect of hydrophobicity in these starch-based flocculants on the sludge dewaterability. The structure-activity relationship was built, and the optimal dose and corresponding FCMC could be theoretically estimated accordingly. The results were in good agreement with the experimental results. The dewatering mechanisms were also discussed in detail on the basis of the changes in the FCMC, SRF, capillary suction time, properties of sludge flocs, compression coefficient, microstructures of sludge cakes, EPS fractions and components, and spatial distributions of the proteins and polysaccharides. In addition to charge neutralization, the hydrophobic association effects of CS-DMRs played an important role in the formation of drainage channels and net-like porous structures in the sludge cake to improve its permeability and filterability. This study thus provided a good understanding of the structural effects of the starch-based flocculants on the sludge dewaterability. The results are greatly beneficial to the fabrication and utilization of environment-friendly and high-performance natural polymeric conditioners for sludge treatment.

A functional assembly framework based on implementable neurobionic material.

Neurobionic material is an emerging field in material and translational science. For material design, much focus has already been transferred from von Neumann architecture to the neuromorphic framework. As it is impractical to reconstruct the real neural tissue solely from materials, it is necessary to develop a feasible neurobionics framework to realize advanced brain function. In this study, we proposed a mathematical neurobionic material model, and attempted to explore advanced function only by simple and feasible structures. Here an equivalent simplified framework was used to describe the dynamics expressed in an equation set, while in vivo study was performed to verify simulation results. In neural tissue, the output of neurobionic material was characterized by spike frequency, and the stability is based on the excitatory/inhibitory proportion. Spike frequency in mathematical neurobionic material model can spontaneously meet the solution of a nonlinear equation set. Assembly can also evolve into a certain distribution under different stimulations, closely related to decision making. Short-term memory can be formed by coupling neurobionic material assemblies. In vivo experiments further confirmed predictions in our mathematical neurobionic material model. The property of this neural biomimetic material model demonstrates its intrinsic neuromorphic computational ability, which should offer promises for implementable neurobionic device design.

Long-term follow-up in patients with Brugada Syndrome in South China.

OBJECTIVE: To evaluate the presence of Brugada electrocardiogram (ECG) pattern, clinical characteristics, treatment, and long-term prognosis of Brugada syndrome in southern Chinese population. METHODS: This prospective study consisted of a consecutive series of patients with diagnostic coved type I Brugada ECG pattern at baseline between January 2007 and February 2020. Histories of symptoms including ventricular tachycardia (VT)/ventricular fibrillation (VF) episode, syncope, and family history of Brugada Syndrome (BrS) or unexplained sudden cardiac death were collected. Electrophysiological study and implantable cardioverter-defibrillator (ICD) were performed. All patients included in this study were followed up in the outpatient department every 6 months after baseline evaluation. Occurrences of syncope, VF, and sudden death were independently analyzed by two cardiologists. RESULTS: 45 (56.3%) patients were diagnosed with BrS. During a mean follow-up of 7.9 ± 3.6 years, six patients had experienced documented VF/sudden cardiac death (SCD) or recurrent syncope. Two patients experienced episodes of syncope more than once. Two patients experienced onset of electrical storm with a total of 11 episodes of VF. There were 50% of these events occurring in fever status. One of patient with BrS died of SCD. CONCLUSION: There was a very low prevalence of Brugada syndrome in southern Chinese population. The risk of arrhythmic events was low in asymptomatic patients. ICD was high effective in preventing SCD without adverse device outcome in long-term follow-up. Fever can lead to predispose to malignant arrhythmia, and aggressive treatment of febrile state in Brugada syndrome was recommended.

Tp-e and (Tp-e)/QT ratio as a non-invasive risk factors for malignant ventricular arrhythmia in patients with idiopathic ventricular premature complexes.

BACKGROUND: To evaluate the role of Tp-e and (Tp-e)/QT ratio in differentiating benign ventricular premature complex (VPC) and malignant polymorphic ventricular tachycardia (PVT). METHODS: From January 2017 to December 2017, patients with documented polymorphic ventricular tachycardia (PVT) or ventricular fibrillation (VF) were consecutive included and classified as PVT/VF group. Sixty age- and sex-matched healthy individuals were recruited as comparative control and subdivided into non-VPC and VPC group. Clinical characteristics and Tp-e and Tp-e/QT ratio between the three groups were compared. RESULTS: Tp-e and (Tp-e)/QT ratio were significantly higher in patients of PVT/VF group compared with the other two groups (P < .001). Episodes of syncope were more frequent in patients with PVT/VF (P < .05). The sensitivity and specificity of a Tp-e interval ≥86 ms for malignant arrhythmias triggered by VPCs were 88% and 66%, respectively, while the sensitivity and specificity of the Tp-e/QT ratio ≥0.24 were 82% and 70%, respectively. Five patients complained recurrence of syncope in the PVT/VF group and 1 patient died with mean follow-up of 18 months. CONCLUSION: Tp-e interval and the Tp-Te/QT ratio is significantly increased in patients with PVT/VF and may be used as a novel non-invasive marker of differentiating malignant and benign VPC.

Gray consistency optical flow algorithm based on mask-R-CNN and a spatial filter for velocity calculation.

The optical flow method has been widely used to measure the vehicle velocity by observing the stationary ground with a camera looking-down. However, when there are moving objects on the stationary ground, the interfering optical flow field will be generated, which decreases the velocity measurement accuracy of a vehicle relative to the ground. In order to reduce the effects caused by moving objects, this paper integrates pyramid Lucas-Kanade (LK) algorithm with the gray consistency method to use the information of color images thoroughly. First, a mask region with convolutional neural network (Mask-R-CNN) is used to recognize the objects that have motions relative to the ground, and it covers them with masks to enhance the similarity between pixels and to reduce the impacts of the noisy moving pixels. Then images are decomposed into three channels, red, green, and blue (i.e., R, G, and B), and processed by median filter. Based on the gray consistency method, the optical flow can be obtained by the pyramid LK algorithm. Finally, the velocity is calculated by the optical flow value. The prominent advantages of the proposed algorithm are: (i) increase the velocity measurement accuracy of a vehicle relative to the ground; (ii) use the information of color images acquired with cameras thoroughly and obtain velocity calculation outputs with less fluctuation; (iii) reduce wrong values caused by noises that are from the origin image and introduced by similar color masks. Four experiments are conducted to test the proposed algorithm and results with superior precision and reliability show the feasibility and effectiveness of the proposed method for the velocity measurement accuracy of a vehicle relative to the ground.

Place recognition with deep superpixel features for brain-inspired navigation.

Navigation in primates is generally supported by cognitive maps. Such a map endows an animal with navigational planning capabilities. Numerous methods have been proposed to mimic these natural navigation capabilities in artificial systems. Based on self-navigation and learning strategies in animals, we propose in this work a place recognition strategy for brain-inspired navigation. First, a place recognition algorithm structure based on convolutional neural networks (CNNs) is introduced, which can be applied in the field of intelligent navigation. Second, sufficient images are captured at each landmark and then stored as a reference image library. Simple linear iterative clustering (SLIC) is used to segment each image into superpixels with multi-scale viewpoint-invariant landmarks. Third, highly representative appearance-independent features are extracted from these landmarks through CNNs. In addition, spatial pyramid pooling (SPP) layers are introduced to generate a fixed-length CNN representation, regardless of the image size. This representation boosts the quality of the extracted landmark features. The proposed SLIC-SPP-CNN place recognition algorithm is evaluated on one collected dataset and two public datasets with viewpoint and appearance variations.

A new DGT technique comprised in a hybrid sensor for the simultaneous measurement of ammonium, nitrate, phosphorus and dissolved oxygen.

A new diffusive gradients in thin films technique (ZrO-AT DGT) with zirconium oxide, A-62 MP and T-42H resins containing in a single binding gel was developed for simultaneous measurement of nitrate (NO3-N), ammonium (NH4-N) and phosphate (PO4-P). The DGT uptake was found to be independent of pH variation from 3.2-8.7. Ionic strengths below 5, 10 and 750 mmol·L-1 NaCl did not affect DGT uptake of NH4-N, NO3-N and PO4-P, respectively. This new DGT was deployed in natural freshwater environments, with in situ measurements of the three nutrients found to be accurate. It ensured that rinsing the exposed surface of the DGT device at 3-day intervals can prevent biofouling. Additionally, a hybrid sensor comprising the novel DGT binding layer overlying an O2 planar optrode was tested in sediments to evaluate the dynamics of O2 and the three nutrients. Results showed that PO4-P and NO3-N fluxes decreased while fluxes of NH4-N increased under aerobic conditions. Nearly simultaneous variation in O2 and NO3-N was observed at the sediment-water interface (SWI) and transformation of NO3-N and PO4-P was found to be sensitively influenced by O2 dynamics.

A critical review of the appearance of black-odorous waterbodies in China and treatment methods.

Black-odorous rivers and lakes are a serious environmental problem and are frequently reported in China. Despite this, there have been no comprehensive in-depth reviews of black-odorous water formation mechanisms, contributing factors and potential treatment technologies. Elements such as S, C and N play an important role in the biogeochemical cycle of black-odorous waterbodies, with water blackening caused by metal sulfides such as iron sulfide (FeS) and manganese sulfide (MnS). Volatile substances such as volatile organic sulfur compounds (VOSCs) are the main contributors of odor. Microorganisms such as sulfate reducing bacteria (SRB), Bacteroidetes and Proteobacteria play important roles in blackening and odor formation processes. Effectiveness of the commonly used treatments methods for black-odorous waterbodies, such as artificial aeration, sediment dredging, microbial enhanced technologies and constructed wetlands, varies significantly under different conditions. In contrast, bio-ecological engineering technologies exhibit comprehensive, long-lasting and economical treatment effects. The causes and mechanisms of black-odorous water formation require further investigation, as well as the optimal application conditions and mechanisms of treatment technologies. This study comprehensively reviews 1) the characteristics and current distribution of black-odorous waterbodies; 2) the compounds contributing to black-odorous phenomenon; 3) black-odorous waterbody production mechanisms; 4) treatment technologies for black-odorous waterbodies. Further studies on the mechanisms of blackening and odor formation are required, with treatment application conditions and mechanisms also requiring further clarification. In addition, the long-term ecological restoration of black-odorous rivers immediately after remediation is key issue that is easily overlooked but merits further investigation and development.

Multiplicative measurement noise can facilitate consensus of multiagent networks.

Measurement noise may have an important impact on the collective motion. Here, we investigate the consensus problem of multiagent networks with multiplicative measurement noise. Based on the stability theory of stochastic differential equations and the algebra graph theory, we obtain sufficient conditions for the consensus and nonconsensus. Both of our analytical and numerical results show that the multiplicative measurement noise can facilitate the emergence of the consensus: the convergence rate increases with respect to the noise intensity if the topologies of the underlying networks satisfy some conditions. Our results provide a better understanding of the constructive role of noise. We also report that the convergence rate of multiagent networks is strongly affected by the network topology and the group size.

Attitude calculation method based on full-sky atmospheric polarization mode.

In the natural world, insects such as bees and sand ants can navigate with the aid of polarized skylight. Inspired by this, bio-inspired navigation systems based on polarized skylight have attracted considerable attention recently. As an important navigation parameter, attitude information is critical for control and navigation of a vehicle. In this paper, the structural characteristics of full-sky atmospheric polarization mode are studied to calculate the attitude of a vehicle relative to the observation point. The heading angle is obtained by subtraction between two angles. One is the angle between the solar meridian and the geographic north. The other is the angle between the solar meridian and the body coordinate system, which can be obtained from the polarization data detected by the sensor. And the solar position can also gain from the polarization data. Then based on the solar position and the coordinates of solar projection point, the zenith point can be determined. With the coordinates of the zenith point in the body and the reference coordinate system, the pitch angle and roll angle are solved. Simulation and practical experiments are conducted to validate the performance of the attitude calculation method. Experiment results with high accuracy show its feasibility and effectiveness.

Realization of consensus of multi-agent systems with stochastically mixed interactions.

In this paper, we propose a new consensus model in which the interactions among agents stochastically switch between attraction and repulsion. Such a positive-and-negative mechanism is described by the white-noise-based coupling. Analytic criteria for the consensus and non-consensus in terms of the eigenvalues of the noise intensity matrix are derived, which provide a better understanding of the constructive roles of random interactions. Specifically, we discover a positive role of noise coupling that noise can accelerate the emergence of consensus. We find that the converging speed of the multi-agent network depends on the square of the second smallest eigenvalue of its graph Laplacian. The influence of network topologies on the consensus time is also investigated.

Self-assembly and emulsification of dopamine-modified hyaluronan.

Dopamine modified hyaluronan (HA-DOPA) with different grafting degree were synthesized and self-assembled into nanoparticles. The effects of pH and salinity changes on the structure of the HA-DOPA nanoparticles were investigated. Nanoparticles swelled under increased pH values, and disassociation started at pH values above 6.20. At a fixed pH of 6.20, the size of the nanoparticles decreased with increased salinity, and flocculation occurred when the salt concentration was higher than 0.3M. The emulsification performance of HA-DOPA nanoparticles at different pH values and salt concentrations demonstrated that nanoparticles with moderately swollen structures possess better emulsifying efficiency and emulsion stability. Additionally, HA-DOPA nanoparticles were able to stabilize various types of oils. These results suggest that HA-DOPA nanoparticles have promising potential as Pickering emulsifiers for applications in the cosmetics, medical, and food industries.