Optimal Distributed Finite-Time Fusion Method for Multi-Sensor Networks under Dynamic Communication Weight.

Aiming at the problem of distributed state estimation in sensor networks, a novel optimal distributed finite-time fusion filtering method based on dynamic communication weights has been developed. To tackle the fusion errors caused by incomplete node information in distributed sensor networks, the concept of limited iterations of global information aggregation was introduced, namely, fast finite-time convergence techniques. Firstly, a local filtering algorithm architecture was constructed to achieve fusion error convergence within a limited number of iterations. The maximum number of iterations was derived to be the diameter of the communication topology graph in the sensor network. Based on this, the matrix weight fusion was used to combine the local filtering results, thereby achieving optimal estimation in terms of minimum variance. Next, by introducing the generalized information quality (GIQ) calculation method and associating it with the local fusion result bias, the relative communication weights were obtained and embedded in the fusion algorithm. Finally, the effectiveness and feasibility of the proposed algorithm were validated through numerical simulations and experimental tests.

Optimal Linear Filter Based on Feedback Structure for Sensing Network with Correlated Noises and Data Packet Dropout.

This paper is concerned with the estimation of correlated noise and packet dropout for information fusion in distributed sensing networks. By studying the problem of the correlation of correlated noise in sensor network information fusion, a matrix weight fusion method with a feedback structure is proposed to deal with the interrelationship between multi-sensor measurement noise and estimation noise, and the method can achieve optimal estimation in the sense of linear minimum variance. Based on this, a method is proposed using a predictor with a feedback structure to compensate for the current state quantity to deal with packet dropout that occurs during multi-sensor information fusion, which can reduce the covariance of the fusion results. Simulation results show that the algorithm can solve the problem of information fusion noise correlation and packet dropout in sensor networks, and effectively reduce the fusion covariance with feedback.

Influence of the Reference Electrode on the Performance of Single-Electrode Triboelectric Nanogenerators and the Optimization Strategies.

Owing to their unique advantages, single-electrode triboelectric nanogenerators (SETENGs) have gained wide attention and have been applied in myriad areas, especially in the burgeoning flexible/wearable electronics. However, there is still a lack of a clear understanding of SETENGs. For example, previous simulation models generally put the reference electrode perpendicularly below the working part, but in practice, the reference electrode is designed in various scenarios and noticeable differences in outputs often occur when the reference electrode changes. With SETENGs developing towards wearability and portability, its reference electrode is often required to be constructed inside the device. Consequently, to achieve optimum performance, it is essential to understand the reference electrode's influence on the outputs. Here, the influence of the reference electrode on the performance of SETENGs is systematically investigated and the targeted optimization strategies are thoroughly revealed. First, theoretical simulations are conducted to investigate the reference electrode's effect on the performance of SETENGs with different structures and in various working modes. Secondly, the theoretical results are certified through corresponding experiments. Based on the results, the targeted optimization strategies for SETENGs are comprehensively demonstrated. This work provides fundamental guidance for the development of TENGs and the design and fabrication of new electronic devices.

Self-Powered Disinfection Using Triboelectric, Conductive Wires of Metal-Organic Frameworks.

Efficient water disinfection is vitally needed in rural and disaster-stricken areas lacking power supplies. However, conventional water disinfection methods strongly rely on external chemical input and reliable electricity. Herein, we present a self-powered water disinfection system using synergistic hydrogen peroxide (H2O2) assisted electroporation mechanisms driven by triboelectric nanogenerators (TENGs) that harvest electricity from the flow of water. The flow-driven TENG, assisted by power management systems, generates a controlled output with aimed voltages to drive a conductive metal-organic framework nanowire array for effective H2O2 generation and electroporation. The injured bacteria caused by electroporation can be further damaged by facile diffused H2O2 molecules at high throughput. A self-powered disinfection prototype enables complete disinfection (>99.9999% removal) over a wide range of flows up to 3.0 × 104 L/(m2 h) with low water flow thresholds (200 mL/min; ∼20 rpm). This rapid, self-powered water disinfection method is promising for pathogen control.

Robust Displacement Sensing by Direct-Current Triboelectric Nanogenerator Via Intelligent Waveform Recognition.

A triboelectric nanogenerator (TENG) facilitates the advancement of self-powered displacement sensors, which are important for many autonomous intelligent microsystems. However, the amplitude-based displacement sensing of conventional TENG-based sensors still suffers significantly from varying charge densities in harsh environments. Benefiting from the combination of intelligent signal processing algorithms and direct-current TENG sensors, this study proposes an environmentally robust character-based displacement sensing method that eliminates the influences of varying charge density in principle. The experimental results show that under drastically changing air humidity and other harsh environments, the sensing of threshold and maximum displacement has far superior consistency and stability than that of traditional amplitude-based TENG sensors, providing a novel route to realize reliable self-powered displacement sensing in environment-variable applications.

Design and Fabrication of Interdigital Supercapacitors as Force/Acceleration Sensors.

The integrated device for energy supply and sensing (IDESS) is a potential candidate for relieving the energy and space burdens caused by the rising integration degrees of microsystems. In this article, we propose a force sensor based on an interdigital supercapacitor (IDTSC). The capacitance and internal resistance of the IDTSC change under external loads, resulting in a transient current fluctuation at a constant bias voltage, which can be used to sense external force/acceleration. The IDTSC showed a specific energy and specific power of 4.16 Wh/kg and 22.26 W/kg (at 0.1 A/g), respectively, which could maintain an essential energy supply. According to the simulation analysis, the designed IDTSC's current response exhibited good linearity with the external force. In addition, benefiting from its light weight and the applied gel electrolytes, the IDTSC showed good high-g impact sensing performance (from 9.9 × 103× g to 3.2 × 104× g). This work demonstrated the feasibility of realizing an integrated energy supply and force-sensing device by empowering energy storage devices with sensing capabilities.

Optimal-Damage-Effectiveness Cooperative-Control Strategy for the Pursuit-Evasion Problem with Multiple Guided Missiles.

In this paper, an optimal-damage-effectiveness cooperative-control strategy based on a damage-efficiency model and a virtual-force method is proposed to solve the pursuit-evasion problem with multiple guided missiles. Firstly, different from the overly ideal assumption in the traditional pursuit-evasion problem, an optimization problem that maximizes the damage efficiency is established and solved, making the optimal-damage-effectiveness strategy more meaningful for practical applications. Secondly, a modified virtual-force method is proposed to obtain this optimal-damage-effectiveness control strategy, which solves the numerical solution challenges brought by the high-complexity damage function. Thirdly, adaptive gain is designed in this strategy based on guidance-integrated fuze technology to achieve robust maximum damage efficiency in unpredictable interception conditions. Finally, the effectiveness and robustness of the proposed strategy are verified by numerical simulations.

Numerical investigation on the ranging performance of forward pulsed laser radar affected by shock waves.

When an aircraft loaded with pulsed laser radar flies at supersonic speed, the laser beam will be distorted by the uneven outflow field, resulting in a significant reduction in ranging accuracy. In this study, the influence mechanism of the shock wave on the performance of forward pulsed laser radar is investigated. First, a novel semi-analytical method is proposed to model the pulsed laser echo wave affected by shock waves, which combines the laser radar equation with optical distortion parameters. Second, an improved ray tracing method based on inverse distance-weighted interpolation with a quadrilateral mesh is proposed to trace the trajectory of the laser beam passing through the flow field, and the effectiveness and superiority of the algorithm are verified. Thereafter, an evaluation method based on the optimal confidence interval is proposed to evaluate the ranging error of pulsed laser radar; which can effectively evaluate the ranging accuracy of pulsed laser radar under the influence of the shock wave. The simulation results show that the ranging performance of pulsed laser radar below Mach 3 is slightly affected, and the detection system error and random error reach the minimum and maximum at Mach 4, respectively. This study provides a theoretical basis for the suppression of the aero-optical effect of forward pulsed laser radar at supersonic speed.

A Multi-Mode Broadband Vibration Energy Harvester Composed of Symmetrically Distributed U-Shaped Cantilever Beams.

Using the piezoelectric effect to harvest energy from surrounding vibrations is a promising alternative solution for powering small electronic devices such as wireless sensors and portable devices. A conventional piezoelectric energy harvester (PEH) can only efficiently collect energy within a small range around the resonance frequency. To realize broadband vibration energy harvesting, the idea of multiple-degrees-of-freedom (DOF) PEH to realize multiple resonant frequencies within a certain range has been recently proposed and some preliminary research has validated its feasibility. Therefore, this paper proposed a multi-DOF wideband PEH based on the frequency interval shortening mechanism to realize five resonance frequencies close enough to each other. The PEH consists of five tip masses, two U-shaped cantilever beams and a straight beam, and tuning of the resonance frequencies is realized by specific parameter design. The electrical characteristics of the PEH are analyzed by simulation and experiment, validating that the PEH can effectively expand the operating bandwidth and collect vibration energy in the low frequency. Experimental results show that the PEH has five low-frequency resonant frequencies, which are 13, 15, 18, 21 and 24 Hz; under the action of 0.5 g acceleration, the maximum output power is 52.2, 49.4, 61.3, 39.2 and 32.1 µW, respectively. In view of the difference between the simulation and the experimental results, this paper conducted an error analysis and revealed that the material parameters and parasitic capacitance are important factors that affect the simulation results. Based on the analysis, the simulation is improved for better agreement with experiments.

Ultralow Quiescent Power-Consumption Wake-Up Technology Based on the Bionic Triboelectric Nanogenerator.

Wake-up circuits in smart microsystems make huge contributions to energy conservation of electronic networks in unmanned areas, which still require higher pressure-triggering sensitivity and lower power consumption. In this work, a bionic triboelectric nanogenerator (bTENG) is developed to serve as a self-powered motion sensor in the wake-up circuit, which captures slight mechanical disturbances and overcomes the drawback of conventional self-powered motion sensors in the wake-up circuit that the circuit can only be triggered when a considerable pressure is applied on the sensor. The bTENG mimics the structure of plants and the addition of the leaf-shaped tentacle structures can increase the electrical outputs by four times, which largely extends the detection range of the wake-up circuit. The bTENG can detect both noncontact and contact mechanical disturbances; and voltages generated from both situations can trigger the wake-up system. Moreover, the specially designed circuit that is compatible with the bTENG can help more accurately control the wake-up system and prolong the battery life of the electronic networks to 12.4 times. An intrusion detection system is established in the wake-up circuit to distinguish human motion and judge the scene. This work opens new horizons for wake-up technologies, and provides new routes for persistent sensing.

Self-Healing, Adhesive, and Highly Stretchable Ionogel as a Strain Sensor for Extremely Large Deformation.

Fabricating a strain sensor that can detect large deformation over a curved object with a high sensitivity is crucial in wearable electronics, human/machine interfaces, and soft robotics. Herein, an ionogel nanocomposite is presented for this purpose. Tuning the composition of the ionogel nanocomposites allows the attainment of the best features, such as excellent self-healing (>95% healing efficiency), strong adhesion (347.3 N m-1 ), high stretchability (2000%), and more than ten times change in resistance under stretching. Furthermore, the ionogel nanocomposite-based sensor exhibits good reliability and excellent durability after 500 cycles, as well as a large gauge factor of 20 when it is stretched under a strain of 800-1400%. Moreover, the nanocomposite can self-heal under arduous conditions, such as a temperature as low as -20 °C and a temperature as high as 60 °C. All these merits are achieved mainly due to the integration of dynamic metal coordination bonds inside a loosely cross-linked network of ionogel nanocomposite doped with Fe3 O4 nanoparticles.

Identification of Cofilin-1 and Destrin as Potential Early-warning Biomarkers for Gamma Radiation in Mouse Liver Tissues.

Gamma radiation causes cell injury and leads to an increased risk of cancer, so it is of practical significance to identify biomarkers for gamma radiation. We used proteomic analysis to identify differentially expressed proteins in liver tissues of C57BL/6J mice treated with gamma radiation from Cs for 360 d. We confirmed obvious pathological changes in mouse liver tissues after irradiation. Compared with the control group, 74 proteins showed a fold change of ≥1.5 in the irradiated groups. We selected 24 proteins for bioinformatics analysis and peptide mass fingerprinting and found that 20 of the identified proteins were meaningful. These proteins were associated with tumorigenesis, tumor suppression, catalysis, cell apoptosis, cytoskeleton, metabolism, gene transcription, T-cell response, and other pathways. We confirmed that both cofilin-1 and destrin were up regulated in the irradiated groups by western blot and real-time polymerase chain reaction. Our findings indicate that cofilin-1 and destrin are sensitive to gamma radiation and may be potential biomarkers for gamma radiation. Whether these proteins are involved in radiation-induced tumorigenesis requires further investigation.

Pressure Sensitivity Enhancement of Porous Carbon Electrode and Its Application in Self-Powered Mechanical Sensors.

Microsystems with limited power supplies, such as electronic skin and smart fuzes, have a strong demand for self-powered pressure and impact sensors. In recent years, new self-powered mechanical sensors based on the piezoresistive characteristics of porous electrodes have been rapidly developed, and have unique advantages compared to conventional piezoelectric sensors. In this paper, in order to optimize the mechanical sensitivity of porous electrodes, a material preparation process that can enhance the piezoresistive characteristics is proposed. A flexible porous electrode with superior piezoresistive characteristics and elasticity was prepared by modifying the microstructure of the porous electrode material and adding an elastic rubber component. Furthermore, based on the porous electrode, a self-powered pressure sensor and an impact sensor were fabricated. Through experimental results, the response signals of the sensors present a voltage peak under such mechanical effects and the sensitive signal has less clutter, making it easy to identify the features of the mechanical effects.

Differential expression of NPM, GSTA3, and GNMT in mouse liver following long-term in vivo irradiation by means of uranium tailings.

Uranium tailings (UT) are formed as a byproduct of uranium mining and are of potential risk to living organisms. In the present study, we sought to identify potential biomarkers associated with chronic exposure to low dose rate γ radiation originating from UT. We exposed C57BL/6J mice to 30, 100, or 250 µGy/h of gamma radiation originating from UT samples. Nine animals were included in each treatment group. We observed that the liver central vein was significantly enlarged in mice exposed to dose rates of 100 and 250 µGy/h, when compared with nonirradiated controls. Using proteomic techniques, we identified 18 proteins that were differentially expressed (by a factor of at least 2.5-fold) in exposed animals, when compared with controls. We chose glycine N-methyltransferase (GNMT), glutathione S-transferase A3 (GSTA3), and nucleophosmin (NPM) for further investigations. Our data showed that GNMT (at 100 and 250 µGy/h) and NPM (at 250 µGy/h) were up-regulated, and GSTA3 was down-regulated in all of the irradiated groups, indicating that their expression is modulated by chronic gamma radiation exposure. GNMT, GSTA3, and NPM may therefore prove useful as biomarkers of gamma radiation exposure associated with UT. The mechanisms underlying those changes need to be further studied.

Monitoring Highway Stability in Permafrost Regions with X-band Temporary Scatterers Stacking InSAR.

Interferograms with short wavelength (e.g., X-band) are usually prone to temporal decorrelation in permafrost regions, leading to the unavailability of sufficient high-coherence interferograms for performing conventional time series InSAR analysis. This paper proposes the utilization of temporary scatterers for the stacking InSAR method, thus enabling extraction of subsidence in a permafrost region with limited SAR images and limited high-coherence interferograms. Such method is termed as the temporary scatterers stacking InSAR (TSS-InSAR). Taking the Gonghe-Yushu highway (about 30 km), part of G214 National Highway in Qinghai province (in a permafrost region), as a case study, this TSS-InSAR approach was demonstrated in detail and implemented. With 10 TerraSAR-X images acquired during the period from May 2015 to August 2015, the subsidence along this highway was extracted. In this case the lack of a consistent number of SAR acquisitions limits the possibility to perform other conventional time series InSAR analysis. The results show that the middle part of this highway is in the thermokarst and seasonal frozen soil area, and its accumulated subsidence reach up to 10 cm in 110 days. The thawing phenomena is still the main reason for the instability of highway. The results demonstrate that the TSS-InSAR method can effectively extract the subsidence information in a challenging scenario with limited X-band SAR images and limited high-coherence interferograms, where other time series InSAR-based techniques cannot be applied in a simple way.

Up-regulation of calreticulin in mouse liver tissues after long-term irradiation with low-dose-rate gamma rays.

The biological effects of low-dose or low-dose-rate ionizing radiation on normal tissues has attracted attention. Based on previous research, we observed the morphology of liver tissues of C57BL/6J mice that received <50, 50-500, and 500-1000 µGy/h of 137Cs radiation for 180 d. We found that the pathological changes in liver tissues were more obvious as the irradiation dose rates increased. Additionally, differential protein expression in liver tissues was analyzed using a proteomics approach. Compared with the matched group in the 2D gel analysis of the irradiated groups, 69 proteins had ≥ 1.5-fold changes in expression. Twenty-three proteins were selected based on ≥2.5-fold change in expression, and 22 of them were meaningful for bioinformatics and protein fingerprinting analysis. These molecules were relevant to cytoskeleton processes, cell metabolism, biological defense, mitochondrial damage, detoxification and tumorigenesis. The results from real-time PCR and western blot (WB) analyses showed that calreticulin (CRT) was up-regulated in the irradiated groups, which indicates that CRT may be relevant to stress reactions when mouse livers are exposed to low-dose irradiation and that low-dose-rate ionizing radiation may pose a cancer risk. The CRT protein can be a potential candidate for low-dose or low-dose-rate ionizing radiation early-warning biomarkers. However, the underlying mechanism requires further investigation.

Harvesting Ambient Vibration Energy over a Wide Frequency Range for Self-Powered Electronics.

Vibration is one of the most common energy sources in ambient environment. Harvesting vibration energy is a promising route to sustainably drive small electronics. This work introduces an approach to scavenge vibrational energy over a wide frequency range as an exclusive power source for continuous operation of electronics. An elastic multiunit triboelectric nanogenerator (TENG) is rationally designed to efficiently harvest low-frequency vibration energy, which can provide a maximum instantaneous output power density of 102 W·m-3 at as low as 7 Hz and maintain its stable current outputs from 5 to 25 Hz. A self-charging power unit (SCPU) combining the TENG and a 10 mF supercapacitor gives a continuous direct current (DC) power delivery of 1.14 mW at a power management efficiency of 45.6% at 20 Hz. The performance of the SCPU can be further enhanced by a specially designed power management circuit, with a continuous DC power of 2 mW and power management efficiency of 60% at 7 Hz. Electronics such as a thermometer, hygrometer, and speedometer can be sustainably powered solely by the harvested vibration energy from a machine or riding bicycle. This approach has potential applications in self-powered systems for environment monitoring, machine safety, and transportation.

Calreticulin: a potential anti-cancer therapeutic target.

Calreticulin (CRT) is an endoplasmic reticulum luminal calcium-binding protein with multiple cellular functions, including intracellular Ca2+ homeostasis, oxidative stress responses, and lectin binding. CRT can also modulate cell adhesion, cell-cell interactions, migration, phagocytosis, integrin-dependent Ca2+ signaling, and immune responses, and plays an important role in cellular proliferation, differentiation, and apoptosis. Given these roles, it is not surprising that CRT function has important implications in health and disease. Considerable evidence in recent years suggests that CRT dysfunction is associated with cancer and that CRT could be a diagnostic marker and a target for cancer therapy. These topics are discussed in depth in this review.

Voltage Fluctuation in a Supercapacitor During a High-g Impact.

Supercapacitors (SCs) are a type of energy storage device with high power density and long lifecycles. They have widespread applications, such as powering electric vehicles and micro scale devices. Working stability is one of the most important properties of SCs, and it is of significant importance to investigate the operational characteristics of SCs working under extreme conditions, particularly during high-g acceleration. In this paper, the failure mechanism of SCs upon high-g impact is thoroughly studied. Through an analysis of the intrinsic reaction mechanism during the high-g impact, a multi-faceted physics model is established. Additionally, a multi-field coupled kinetics simulation of the SC failure during a high-g impact is presented. Experimental tests are conducted that confirm the validity of the proposed model. The key factors of failure, such as discharge currents and discharging levels, are analyzed and discussed. Finally, a possible design is proposed to avoid the failure of SCs upon high-g impact.

A highly shape-adaptive, stretchable design based on conductive liquid for energy harvesting and self-powered biomechanical monitoring.

The rapid growth of deformable and stretchable electronics calls for a deformable and stretchable power source. We report a scalable approach for energy harvesters and self-powered sensors that can be highly deformable and stretchable. With conductive liquid contained in a polymer cover, a shape-adaptive triboelectric nanogenerator (saTENG) unit can effectively harvest energy in various working modes. The saTENG can maintain its performance under a strain of as large as 300%. The saTENG is so flexible that it can be conformed to any three-dimensional and curvilinear surface. We demonstrate applications of the saTENG as a wearable power source and self-powered sensor to monitor biomechanical motion. A bracelet-like saTENG worn on the wrist can light up more than 80 light-emitting diodes. Owing to the highly scalable manufacturing process, the saTENG can be easily applied for large-area energy harvesting. In addition, the saTENG can be extended to extract energy from mechanical motion using flowing water as the electrode. This approach provides a new prospect for deformable and stretchable power sources, as well as self-powered sensors, and has potential applications in various areas such as robotics, biomechanics, physiology, kinesiology, and entertainment.