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Circuits based on organic electrochemical transistors (OECTs) have great potential in the fields of biosensors and artificial neural computation due to their biocompatibility and neural similarity. However, the integration of OECT-based circuits lags far behind other emerging electronics. Here, ternary inverters based on antiambipolar vertical OECTs (vOECTs) and their integration with the establishment of neural networks are demonstrated. Specifically, by adopting a small molecule (t-gdiPDI) as the channel of vOECT, high antiambipolar performance, with current density of 33.9 ± 2.1 A cm -2 under drain voltage of 0.1 V, peak voltage ≈0 V, low driving voltage < ± 0.6 V, and current on/off ratio > 10 6 , are realized. Consequently, vertically stacked ternary circuits based solely on OECTs are constructed for the first time, showing three distinct logical states and high integration density. By further developing inverter array as the internal fundamental units of ternary weight network hardware circuits for ternary processing and computation, it demonstrates excellent data classification and recognition capabilities. This work demonstrates the possibility of constructing multi-valued logic circuits by OECTs and promotes a new strategy for high-density integration and multivalued computing systems based on organic circuits., (© 2024 Wiley‐VCH GmbH.)

Accurate localization of objects of interest in remote sensing images (RSIs) is of great significance for object identification, resource management, decision-making and disaster relief response. However, many difficulties, like complex backgrounds, dense target quantities, large-scale variations, and small-scale objects, which make the detection accuracy unsatisfactory. To improve the detection accuracy, we propose an Adaptive Adjacent Context Negotiation Network (A 2 CN-Net). Firstly, the composite fast Fourier convolution (CFFC) module is given to reduce the information loss of small objects, which is inserted into the backbone network to obtain spectral global context information. Then, the Global Context Information Enhancement (GCIE) module is given to capture and aggregate global spatial features, which is beneficial for locating objects of different scales. Furthermore, to alleviate the aliasing effect caused by the fusion of adjacent feature layers, a novel Adaptive Adjacent Context Negotiation network (A 2 CN) is given to adaptive integration of multi-level features, which consists of local and adjacent branches, with the local branch adaptively highlighting feature information and the adjacent branch introducing global information at the adjacent level to enhance feature representation. In the meantime, considering the variability in the focus of feature layers in different dimensions, learnable weights are applied to the local and adjacent branches for adaptive feature fusion. Finally, extensive experiments are performed in several available public datasets, including DIOR and DOTA-v1.0. Experimental studies show that A 2 CN-Net can significantly boost detection performance, with mAP increasing to 74.2% and 79.2%, respectively., Competing Interests: The authors declare there are no competing interests., (©2024 Dong et al.)

Advances in deep learning and computer vision have overcome many challenges inherent in the field of autonomous intelligent vehicles. To improve the detection accuracy and efficiency of EdgeBoard intelligent vehicles, we proposed an optimized design of EdgeBoard based on our PP-YOLOE+ model. This model innovatively introduces a composite backbone network, incorporating deep residual networks, feature pyramid networks, and RepResBlock structures to enrich environmental perception capabilities through the advanced analysis of sensor data. The incorporation of an efficient task-aligned head (ET-head) in the PP-YOLOE+ framework marks a pivotal innovation for precise interpretation of sensor information, addressing the interplay between classification and localization tasks with high effectiveness. Subsequent refinement of target regions by detection head units significantly sharpens the system's ability to navigate and adapt to diverse driving scenarios. Our innovative hardware design, featuring a custom-designed mainboard and drive board, is specifically tailored to enhance the computational speed and data processing capabilities of intelligent vehicles. Furthermore, the optimization of our Pos-PID control algorithm allows the system to dynamically adjust to complex driving scenarios, significantly enhancing vehicle safety and reliability. Besides, our methodology leverages the latest technologies in edge computing and dynamic label assignment, enhancing intelligent vehicles' operations through seamless sensor integration. Our custom dataset, specifically designed for this study, includes 4777 images captured by intelligent vehicles under a variety of environmental and lighting conditions. The dataset features diverse scenarios and objects pertinent to autonomous driving, such as pedestrian crossings and traffic signs, ensuring a comprehensive evaluation of the model's performance. We conducted extensive testing of our model on this dataset to thoroughly assess sensor performance. Evaluated against metrics including accuracy, error rate, precision, recall, mean average precision (mAP), and F1-score, our findings reveal that the model achieves a remarkable accuracy rate of 99.113%, an mAP of 54.9%, and a real-time detection frame rate of 192 FPS, all within a compact parameter footprint of just 81 MB. These results demonstrate the superior capability of our PP-YOLOE+ model to integrate sensor data, achieving an optimal balance between detection accuracy and computational speed compared with existing algorithms.

Stretchable electronics have attracted tremendous attention amongst academic and industrial communities due to their prospective applications in personal healthcare, human-activity monitoring, artificial skins, wearable displays, human-machine interfaces, etc. Other than mechanical robustness, stable performances under complex strains in these devices that are not for strain sensing are equally important for practical applications. Here, a comprehensive summarization of recent advances in stretchable electronics with strain-resistive performance is presented. First, detailed overviews of intrinsically strain-resistive stretchable materials, including conductors, semiconductors, and insulators, are given. Then, systematic representations of advanced structures, including helical, serpentine, meshy, wrinkled, and kirigami-based structures, for strain-resistive performance are summarized. Next, stretchable arrays and circuits with strain-resistive performance, that integrate multiple functionalities and enable complex behaviors, are introduced. This review presents a detailed overview of recent progress in stretchable electronics with strain-resistive performances and provides a guideline for the future development of stretchable electronics., (© 2023 Wiley-VCH GmbH.)

In this article, a new distributed filtering problem is studied for a class of state-saturated time-varying systems over sensor networks under measurement censoring, where the censored measurements are described by the Tobit measurement model. To curb the data collision and ease communication burden, a random access protocol (RAP) is implemented onto the sensor-to-filter channels to orchestrate the transmission sequence of multiple sensor nodes. The purpose of the addressed problem is to construct a state-saturated distributed filter such that upper bounds (on filtering error covariances) are guaranteed and filter parameters are determined to accommodate both measurement censoring and state saturation under the RAP. By means of matrix difference equations, the desired upper bounds are first acquired and later minimized through appropriately designing filter parameters. Particularly, the sparsity issue with respect to the network topology is tackled via the employing certain matrix simplification technique. A simulation example is finally presented to showcase the applicability of the proposed state-saturated distributed filtering algorithm.

Flexible and stretchable bioelectronics provides a biocompatible interface between electronics and biological systems and has received tremendous attention for in situ monitoring of various biological systems. Considerable progress in organic electronics has made organic semiconductors, as well as other organic electronic materials, ideal candidates for developing wearable, implantable, and biocompatible electronic circuits due to their potential mechanical compliance and biocompatibility. Organic electrochemical transistors (OECTs), as an emerging class of organic electronic building blocks, exhibit significant advantages in biological sensing due to the ionic nature at the basis of the switching behavior, low driving voltage (<1 V), and high transconductance (in millisiemens range). During the past few years, significant progress in constructing flexible/stretchable OECTs (FSOECTs) for both biochemical and bioelectrical sensors has been reported. In this regard, to summarize major research accomplishments in this emerging field, this review first discusses structure and critical features of FSOECTs, including working principles, materials, and architectural engineering. Next, a wide spectrum of relevant physiological sensing applications, where FSOECTs are the key components, are summarized. Last, major challenges and opportunities for further advancing FSOECT physiological sensors are discussed., (© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.)

The emergence of ionic-junction devices has attracted growing interests due to the potential of serving as signal transmission and translation media between electronic devices and biological systems using ions. Among them, fiber-shaped iontronics possesses a great advantage in implantable applications owing to the unique one-dimensional geometry. However, fabricating stable ionic-junction on curved surfaces remains a challenge. Here, we developed a polyelectrolyte based ionic-junction fiber via an integrated opposite charge grafting method capable of large-scale continuous fabrication. The ionic-junction fibers can be integrated into functions such as ionic diodes and ionic bipolar junction transistors, where rectification and switching of input signals are implemented. Moreover, synaptic functionality has also been demonstrated by utilizing the fiber memory capacitance. The connection between the ionic-junction fiber and sciatic nerves of the mouse simulating end-to-side anastomosis is further performed to realize effective nerve signal conduction, verifying the capability for next-generation artificial neural pathways in implantable bioelectronics., (© 2023. The Author(s).)

Recording the trajectory of table tennis balls in real-time enables the analysis of the opponent's attacking characteristics and weaknesses. The current analysis of the ball paths mainly relied on human viewing, which lacked certain theoretical data support. In order to solve the problem of the lack of objective data analysis in the research of table tennis competition, a target detection algorithm-based table tennis trajectory extraction network was proposed to record the trajectory of the table tennis movement in video. The network improved the feature reuse rate in order to achieve a lightweight network and enhance the detection accuracy. The core of the network was the "feature store & return" module, which could store the output of the current network layer and pass the features to the input of the network layer at the next moment to achieve efficient reuse of the features. In this module, the Transformer model was used to secondarily process the features, build the global association information, and enhance the feature richness of the feature map. According to the designed experiments, the detection accuracy of the network was 96.8% for table tennis and 89.1% for target localization. Moreover, the parameter size of the model was only 7.68 MB, and the detection frame rate could reach 634.19 FPS using the hardware for the tests. In summary, the network designed in this paper has the characteristics of both lightweight and high precision in table tennis detection, and the performance of the proposed model significantly outperforms that of the existing models.

Cost-effective fabrication of mechanically flexible low-power electronics is important for emerging applications including wearable electronics, artificial intelligence, and the Internet of Things. Here, solution-processed source-gated transistors (SGTs) with an unprecedented intrinsic gain of ~2,000, low saturation voltage of +0.8 ± 0.1 V, and a ~25.6 μW power consumption are realized using an indium oxide In 2 O 3 /In 2 O 3 :polyethylenimine (PEI) blend homojunction with Au contacts on Si/SiO 2 . Kelvin probe force microscopy confirms source-controlled operation of the SGT and reveals that PEI doping leads to more effective depletion of the reverse-biased Schottky contact source region. Furthermore, using a fluoride-doped AlO x gate dielectric, rigid (on a Si substrate) and flexible (on a polyimide substrate) SGTs were fabricated. These devices exhibit a low driving voltage of +2 V and power consumption of ~11.5 μW, yielding inverters with an outstanding voltage gain of >5,000. Furthermore, electrooculographic (EOG) signal monitoring can now be demonstrated using an SGT inverter, where a ~1.0 mV EOG signal is amplified to over 300 mV, indicating significant potential for applications in wearable medical sensing and human-computer interfacing.

Organic electrochemical transistors (OECTs) and OECT-based circuitry offer great potential in bioelectronics, wearable electronics and artificial neuromorphic electronics because of their exceptionally low driving voltages (<1 V), low power consumption (<1 µW), high transconductances (>10 mS) and biocompatibility 1-5 . However, the successful realization of critical complementary logic OECTs is currently limited by temporal and/or operational instability, slow redox processes and/or switching, incompatibility with high-density monolithic integration and inferior n-type OECT performance 6-8 . Here we demonstrate p- and n-type vertical OECTs with balanced and ultra-high performance by blending redox-active semiconducting polymers with a redox-inactive photocurable and/or photopatternable polymer to form an ion-permeable semiconducting channel, implemented in a simple, scalable vertical architecture that has a dense, impermeable top contact. Footprint current densities exceeding 1 kA cm -2 at less than ±0.7 V, transconductances of 0.2-0.4 S, short transient times of less than 1 ms and ultra-stable switching (>50,000 cycles) are achieved in, to our knowledge, the first vertically stacked complementary vertical OECT logic circuits. This architecture opens many possibilities for fundamental studies of organic semiconductor redox chemistry and physics in nanoscopically confined spaces, without macroscopic electrolyte contact, as well as wearable and implantable device applications., (© 2023. The Author(s).)

In recent years, electrochemical biosensors (ECBSs) have shown significant potential for real-time disease diagnosis and in situ physical condition monitoring. As a multi-constituent oral fluid comprising various disease signaling biomarkers, saliva has drawn much attention in the field of point-of-care (POC) testing. In particular, during the outbreak of the COVID-19 pandemic, ECBSs which hold the simplicity of a single-step assay compared with the multi-step assay of traditional testing methods are expected to relieve the human and economic burden caused by the massive and long-term sample testing process. Noteworthily, ECBSs for the detection of SARS-CoV-2 in saliva have already been developed and may replace current testing methods. Furthermore, the detection scope has expanded from routine indices such as sugar and uric acid to abnormal biomarkers for early-stage disease detection and drug level monitoring, which further facilitated the evolution of ECBSs in the last 5 years. This review is divided into several main sections. First, we discussed the latest advancements and representative research on ECBSs for saliva testing. Then, we focused on a novel kind of ECBS, organic electrochemical transistors (OECTs), which hold great advantages of high sensitivity and signal-to-noise ratio and on-site detection. Finally, application of ECBSs with integrated portable platforms in oral cavities, which lead to powerful auxiliary testing means for telemedicine, has also been discussed.

In this article, the asynchronous fault detection (FD) strategy is investigated in frequency domain for nonlinear Markov jump systems under fading channels. In order to estimate the system dynamics and meet the fact that not all the running modes can be observed exactly, a set of asynchronous FD filters is proposed. By using statistical methods and the Lynapunov stability theory, the augmented system is shown to be stochastic stable with a prescribed l 2 gain even under fading transmissions. Then, a novel lemma is developed to capture the finite frequency performance. Some solvable conditions with less conservatism are subsequently deduced by exploiting novel decoupling techniques and additional slack variables. Besides, the FD filter gains could be calculated with the aid of the derived conditions. Finally, the effectiveness of the proposed method is shown by an illustrative example.

Thin-film transistors using metal oxide semiconductors are essential in many unconventional electronic devices. Nevertheless, further advances will be necessary to broaden their technological appeal. Here, a new strategy is reported to achieve high-performance solution-processed metal oxide thin-film transistors (MOTFTs) by introducing a metallic micro-island array (M-MIA) on top of the MO back channel, where the MO is a-IGZO (amorphous indium-gallium-zinc-oxide). Here Al-MIAs are fabricated using honeycomb cinnamate cellulose films, created by a scalable breath-figure method, as a shadow mask. For IGZO TFTs, the electron mobility (µ e ) increases from ≈3.6 cm 2 V -1 s -1 to near 15.6 cm 2 V -1 s -1 for optimal Al-MIA dimension/coverage of 1.25 µm/51%. The Al-MIA IGZO TFT performance is superior to that of controls using compact/planar Al layers (Al-PL TFTs) and Au-MIAs with the same channel coverage. Kelvin probe force microscopy and technology computer-aided design simulations reveal that charge transfer occurs between the Al and the IGZO channel which is optimized for specific Al-MIA dimensions/surface channel coverages. Furthermore, such Al-MIA IGZO TFTs with a high-k fluoride-doped alumina dielectric exhibit a maximum µ e of >50.2 cm 2 V -1 s -1 . This is the first demonstration of a micro-structured MO semiconductor heterojunction with submicrometer resolution metallic arrays for enhanced transistor performance and broad applicability to other devices., (© 2022 The Authors. Advanced Materials published by Wiley-VCH GmbH.)

Signed digraphs with both positive and negative weighted edges are widely applied to explain cooperative and competitive interactions arising from various social, biological, and physical systems. This article formulates and solves the asynchronous tracking control problem of multiagent systems with input uncertainties on switching signed digraphs. In the interaction setting, we assume that the leader moves at a time-varying acceleration that cannot be measured by the followers accurately, and further suppose that each agent receives its neighbors' states information at certain instants determined by its own clock, which is not necessary to be synchronized with those of other agents. Using dynamically changing spanning subdigraphs of signed digraphs to describe graphically asynchronous interactions, the asynchronous tracking problem is equivalently transformed into a convergence problem of products of general substochastic matrices (PGSSM), in which the matrix elements are not necessarily non-negative and the row sums are less than or equal to 1. With the help of the matrix analysis technique and the composition of binary relations, we propose a new and original method to deal with the convergence problem of PGSSM, and further establish a spanning tree condition for asynchronous tracking control. Finally, the validity of the theoretical findings is verified through several numerical examples.

The existing studies for tracking consensus of multiagent systems (MASs) are all restricted to networks with only cooperative relationships among agents. Tracking consensus, however, requires beyond these traditional models due to the ubiquitous competition in many real-world MASs, such as biological systems and social systems. Taking into account this fact, this article aims to extend the dynamics of tracking consensus to signed networks containing both cooperative and competitive relationships among agents. A group of agents with general linear dynamics is considered. The cases of the fixed network as well as switching networks are analyzed, respectively. In the end, some algebraic conditions related to the network structure and the positive/negative edge weight are established to ensure the implementation of tracking consensus. Moreover, the single decoupling system is allowed to be strictly unstable in theory, and the upper bound of the eigenvalue modulus of the system matrix related to the system instability is given.

Realizing fully stretchable electronic materials is central to advancing new types of mechanically agile and skin-integrable optoelectronic device technologies. Here we demonstrate a materials design concept combining an organic semiconductor film with a honeycomb porous structure with biaxially prestretched platform that enables high-performance organic electrochemical transistors with a charge transport stability over 30-140% tensional strain, limited only by metal contact fatigue. The prestretched honeycomb semiconductor channel of donor-acceptor polymer poly(2,5-bis(2-octyldodecyl)-3,6-di(thiophen-2-yl)-2,5-diketo-pyrrolopyrrole-alt-2,5-bis(3-triethyleneglycoloxy-thiophen-2-yl) exhibits high ion uptake and completely stable electrochemical and mechanical properties over 1,500 redox cycles with 10 4 stretching cycles under 30% strain. Invariant electrocardiogram recording cycles and synapse responses under varying strains, along with mechanical finite element analysis, underscore that the present stretchable organic electrochemical transistor design strategy is suitable for diverse applications requiring stable signal output under deformation with low power dissipation and mechanical robustness., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

The advent of optogenetics provides a well-targeted tool to manipulate neurons because of its high time resolution and cell-type specificity. Recently, closed-loop neural manipulation techniques consisting of optical stimulation and electrical recording have been widely used. However, metal microelectrodes exposed to light radiation could generate photoelectric noise, thus causing loss or distortion of neural signal in recording channels. Meanwhile, the biocompatibility of neural probes remains to be improved. Here, five kinds of neural interface materials are deposited on flexible polyimide-based neural probes and illuminated with a series of blue laser pulses to study their electrochemical performance and photoelectric noises for single-unit recording. The results show that the modifications can not only improve the electrochemical performance, but can also reduce the photoelectric artifacts. In particular, the double-layer composite consisting of platinum-black and conductive polymer has the best comprehensive performance. Thus, a layer of polypeptide is deposited on the entire surface of the double-layer modified neural probes to further improve their biocompatibility. The results show that the biocompatible polypeptide coating has little effect on the electrochemical performance of the neural probe, and it may serve as a drug carrier due to its special micromorphology.

This article addresses the bipartite tracking consensus for a set of mobile autonomous agents over directed cooperation-competition networks. Here, cooperative and competitive interactions among the agents are described by positive and negative edges of the directed network topology, respectively. Both fixed and switching network topologies are considered. For the case with fixed network topology, the matrix product technique is utilized to derive the convergence result. For the case with switching network topologies, some key results related to the composition of binary relations are the main technical tools of analyzing the error system. In addition, the upper bound for the spectral radius of the system matrix is given to ensure the convergence of the system even if the single uncoupled system is strictly unstable. The applicability of the derived results is verified through two simulation experiments.

With the rapid increase in the use of optogenetics to investigate nervous systems, there is high demand for neural interfaces that can simultaneously perform optical stimulation and electrophysiological recording. However, high-magnitude stimulation artifacts have prevented experiments from being conducted at a desirably high temporal resolution. Here, a flexible polyimide-based neural probe with polyethylene glycol (PEG) packaged optical fiber and Pt-Black/PEDOT-GO (graphene oxide doped poly(3,4-ethylene-dioxythiophene)) modified microelectrodes was developed to reduce the stimulation artifacts that are induced by photoelectrochemical (PEC) and photovoltaic (PV) effects. The advantages of this design include quick and accurate implantation and high-resolution recording capacities. Firstly, electrochemical performance of the modified microelectrodes is significantly improved due to the large specific surface area of the GO layer. Secondly, good mechanical and electrochemical stability of the modified microelectrodes is obtained by using Pt-Black as bonding layer. Lastly, bench noise recordings revealed that PEC noise amplitude of the modified neural probes could be reduced to less than 50 µV and no PV noise was detected when compared to silicon-based neural probes. The results indicate that this device is a promising optogenetic tool for studying local neural circuits.

In this study, we reported an acoustic wave resonator for temperature monitorable kinetic analysis of human blood coagulation. The resonator is operated in both Lamb wave mode at 860 MHz and Rayleigh wave mode at 444 MHz. The electrical parameter variation of the resonator induced by the increased plasma viscosity can be used to monitor the coagulation process. The Lamb mode of the resonator is sensitive to both plasma viscosity and plasma temperature, while the Rayleigh mode responds only to the temperature which is not affected by viscosity. These unique characteristics of the two modes are due to different spatial distributions of the acoustic energy. Taking advantage of the aforementioned features, an acoustic wave resonator to study the human blood coagulation is designed to simultaneously monitor the temperature and plasma viscosity. The coagulation time and plasma temperature were provided by fitting the time-frequency curves. Our design holds great promise for biological reaction monitoring with possible temperature changes.

Oscillometry is the most popular technique for automatic blood pressure (BP) estimation. This method relies on recording the cuff deflation curve (CDC) from a high suprasystolic BP (SSBP) to a low subdiastolic BP (SDBP) and is very sensitive to noise caused by breathing, motion artifacts, muscle contraction and the environment. We developed a unified BP estimation method involving two integrated sub-procedures based on the arterial lumen area (ALA) model and applied it for continuous BP measurement. Our proposed method is coefficient free and continuous. No empirical coefficients are applied, and the CDC varies within a low-pressure range of 40-80 mm Hg, which can be sustainably imposed on our wrists. The first sub-procedure estimates the mean arterial pressure (MAP) and arterial compliance parameter b under a complete CDC period. In the second sub-procedure, the systolic BP (SBP) and diastolic BP (DBP) are estimated based on the dynamic-updated oscillometric waveform. We applied this method on 300 continuously oscillometric traces recorded from 20 male and female healthy subjects aged 20-60 years. The validated results were compared with those from a double stethoscope check. We observed mean absolute errors of 4.77 and 4.24 mm Hg in estimating the SBP and DBP, respectively.

Next generation implantable neural interfaces are targeting devices with mm-scale form factors that are freely floating and completely wireless. Scalability to more recording (or stimulation) channels will be achieved through distributing multiple devices, instead of the current approach that uses a single centralized implant wired to individual electrodes or arrays. In this way, challenges associated with tethers, micromotion, and reliability of wiring is mitigated. This concept is now being applied to both central and peripheral nervous system interfaces. One key requirement, however, is to maximize specific absorption rate (SAR) constrained achievable wireless power transfer efficiency (PTE) of these inductive links with mm-sized receivers. Chip-scale coil structures for microsystem integration that can provide efficient near-field coupling are investigated. We develop near-optimal geometries for three specific coil structures: in-CMOS, above-CMOS (planar coil post-fabricated on a substrate), and around-CMOS (helical wirewound coil around substrate). We develop analytical and simulation models that have been validated in air and biological tissues by fabrications and experimental measurements. Specifically, we prototype structures that are constrained to a 4 mm 4 mm silicon substrate, i.e., the planar in-/above-CMOS coils have outer diameters 4 mm, whereas the around-CMOS coil has an inner diameter of 4 mm. The in-CMOS and above-CMOS coils have metal film thicknesses of 3- m aluminium and 25- m gold, respectively, whereas the around-CMOS coil is fabricated by winding a 25-m gold bonding wire around the substrate. The measured quality factors (Q) of the mm-scale Rx coils are 10.5 @450.3 MHz (in-CMOS), 24.61 @85 MHz (above-CMOS), and 26.23 @283 MHz (around-CMOS). Also, PTE of 2-coil links based on three types of chip-scale coils is measured in air and tissue environment to demonstrate tissue loss for bio-implants. The SAR-constrained maximum PTE measured (together with resonant frequencies, in tissue) are 1.64% @355.8 MHz (in-CMOS), 2.09% @82.9 MHz (above-CMOS), and 3.05% @318.8 MHz (around-CMOS).

Vagus nerve stimulation is an emerging bioelectronic medicine to modulate cardiac function, as the nerve provides parasympathetic innervation to the heart. In this study, we developed a polyimide based 2D cuff electrode to wrap around on the vagus nerve. Thanks to the tiny size and bendable protruding structure of the contact tips of the device, the electrode sites are able to flexibly bend to touch the nerve, selectively record and stimulate the vagus nerve. Gold, platinum and platinum black materials were chosen to compose the electrodes for nerve stimulation and recording, respectively. Since the platinum black has ~30 times larger charge delivery capacity (CDC) than gold, Pt black electrode is used for nerve stimulation. The electrochemical impedance spectroscopy and cyclic voltammetry measurement of the three materials were conducted in vitro, revealing the results of 405 kΩ, 41 kΩ, 10.5 kΩ, @1 kHz and 0.81 mC/cm 2 , 4.26 mC/cm 2 , 25.5 mC/cm 2 , respectively (n = 3). The cuff electrodes were implanted into the right-sided vagus nerve of rats for in vivo experiment. Biphasic current configuration was implemented for nerve stimulation with frequency of 10 Hz, pulse during of 300 μs and various currents stimulus. The result shows the heart beat frequency drops up to 36% during the stimulation and was able to return the regular frequency as stimulation was removed. Subsequently, the vagus nerve signals were recorded with the four channel cuff electrodes. The magnitude of the compound nerve action potentials (CNAPs) is ~10 μV and the signal to noise ratio (SNR) is ~20., (Copyright © 2018 Elsevier B.V. All rights reserved.)

With the continuous exploration of 2D transition metal dichalcogenides (TMDs), novel high-performance devices based on the remarkable electronic and optoelectronic natures of 2D TMDs are increasingly emerging. As fresh blood of 2D TMD family, anisotropic MTe 2 and ReX 2 (M = Mo, W, and X = S, Se) have drawn increasing attention owing to their low-symmetry structures and charming properties of mechanics, electronics, and optoelectronics, which are suitable for the applications of field-effect transistors (FETs), photodetectors, thermoelectric and piezoelectric applications, especially catering to anisotropic devices. Herein, a comprehensive review is introduced, concentrating on their recent progresses and various applications in recent years. First, the crystalline structure and the origin of the strong anisotropy characterized by various techniques are discussed. Specifically, the preparation of these 2D materials is presented and various growth methods are summarized. Then, high-performance applications of these anisotropic TMDs, including FETs, photodetectors, and thermoelectric and piezoelectric applications are discussed. Finally, the conclusion and outlook of these applications are proposed.

This study develops a frequency feature based pulsed eddy current method. A frequency feature, termed frequency to zero, is proposed for subsurface defects and metal loss quantification in metallic specimens. A curve fitting method is also employed to generate extra frequency components and improve the accuracy of the proposed method. Experimental validation is carried out. Conclusions and further work are derived on the basis of the studies.

Precise control of the grid-connected current is a challenge in photovoltaic inverter research. Traditional Proportional-Integral (PI) control technology cannot eliminate steady-state error when tracking the sinusoidal signal from the grid, which results in a very high total harmonic distortion in the grid-connected current. A novel PI controller has been developed in this paper, in which the sinusoidal wave is discretized into an N-step input signal that is decided by the control frequency to eliminate the steady state error of the system. The effect of periodical error caused by the dead zone of the power switch and conduction voltage drop can be avoided; the current tracking accuracy and current harmonic content can also be improved. Based on the proposed PI controller, a 700 W photovoltaic grid-connected inverter is developed and validated. The improvement has been demonstrated through experimental results.

In this paper, the Back Propagation (BP) neural network based control strategy is proposed for the heating system of a polysilicon reduction furnace. It is applied to obtain the control signal I(d), which is used to adjust the heating power through operations of the silicon core temperature, furnace temperature, silicon core voltage, and resistance of the current control cycle. With the control signal I(d) the polycrystalline silicon can be heated from room temperature to the required temperature smoothly and steadily. The proposed BP network applied in this paper can obtain the accurate control signal I(d) and achieve the precise control purpose. This paper presents the principle of the BP network and demonstrates the effectiveness of the BP network in the heating system of a polysilicon reduction furnace by combining the simulation analysis with experimental results.

In this article, the state-of-the-art multi-wave and hybrid imaging techniques in the field of nondestructive evaluation and structural health monitoring were comprehensively reviewed. A new direction for assessment and health monitoring of various structures by capitalizing the advantages of those imaging methods was discussed. Although sharing similar system configurations, the imaging physics and principles of multi-wave phenomena and hybrid imaging methods are inherently different. After a brief introduction of nondestructive evaluation (NDE) , structure health monitoring (SHM) and their related challenges, several recent advances that have significantly extended imaging methods from laboratory development into practical applications were summarized, followed by conclusions and discussion on future directions.

Eddy Current Pulsed Thermography (ECPT), an emerging Non-Destructive Testing and Evaluation technique, has been applied for a wide range of materials. The lateral heat diffusion leads to decreasing of temperature contrast between defect and defect-free area. To enhance the flaw contrast, different statistical methods, such as Principal Component Analysis and Independent Component Analysis, have been proposed for thermography image sequences processing in recent years. However, there is lack of direct and detailed independent comparisons in both algorithm implementations. The aim of this article is to compare the two methods and to determine the optimized technique for flaw contrast enhancement in ECPT data. Verification experiments are conducted on artificial and thermal fatigue nature crack detection.

The chemical reaction between Ag nanoparticles (Ag NPs) and 7,7',8,8'- tetracycanoquinodimethane (TCNQ) microparticles (MPs) in aqueous solution for the formation of Ag-NP-decorated Ag-TCNQ nanowires is reported. Based on the results obtained by UV-vis spectroscopy and scanning electron microscopy (SEM), it is proposed that the reaction between Ag NPs and TCNQ MPs includes three stages, namely, aggregation of NPs and MPs, diffusion and reaction between NPs and MPs, and formation of Ag-TCNQ nanowires. The as-synthesized semiconducting Ag-TCNQ nanowires show good performance in nonvolatile memory devices with multiple write-read-erase-read (WRER) cycles in air., (Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Four 20 ns molecular dynamics simulations have been performed with two counterions, K+ or Na+, at two water contents, 15 or 20 H2O per nucleotide. A hexagonal simulation cell comprised of three identical DNA decamers [d(5'-ATGCAGTCAG) x d(5'-TGACTGCATC)] with periodic boundary condition along the DNA helix was used. The simulation setup mimics the DNA state in oriented DNA fibers or in crystals of DNA oligomers. Variation of counterion nature and water content do not alter averaged DNA structure. K+ and Na+ binding to DNA are different. K+ binds to the electronegative sites of DNA bases in the major and the minor grooves, while Na+ interacts preferentially with the phosphate groups. Increase of water causes a shift of both K+ and Na+ from the first hydration shell of O1P/O2P and of the DNA bases in the minor groove with lesser influence for the cation binding to the bases in the major groove. Mobility of both water and cations in the K-DNA systems is faster than in the Na-DNA systems: Na+ organizes and immobilizes water structure around itself and near DNA while for K+ water is less organized and more dynamic.

Antifreeze proteins (AFPs) help many organisms protect themselves from freezing in subzero temperatures. The most active AFPs found to date are those from insects, which possess exceptionally regular beta-helical structures. On the ice-binding surface of these proteins, regularly arrayed water molecules are observed within the repeating Thr-Xxx-Thr motif, but the exact role of these water molecules remains unknown. In this work, we have employed a number of computational methods to examine the role of these water molecules in an AFP from Tenebrio molitor (TmAFP). Our investigation involved a combination of molecular and quantum mechanical approaches. Properties such as stability, interaction energy, orbital overlap, and conformational analysis of various systems, including TmAFP-water, TmAFP-water-ice, and TmAFP-ice, were systematically evaluated and compared. The regularly arrayed water molecules were found to remain associated with TmAFP before ice binding, demonstrating that they are an intrinsic part of the protein. These water molecules may assist TmAFP in the process of ice recognition and binding. However, after facilitating the initial stages of ice recognition and binding, these water molecules are excluded in the final formation of the AFP-ice complex. The departure of these water molecules enables a better two-dimensional match between TmAFP and ice. These results agree with experimental observations showing that although these water molecules are aligned with the ice-binding hydroxyl groups of Thr residues in one dimension, they are in fact positioned slightly off in the second dimension, making a good two-dimensional match impossible.

Many organisms living in cold environments can survive subzero temperatures by producing antifreeze proteins (AFPs) or antifreeze glycoproteins. In this paper we investigate the ice-binding surface of type II AFP by quantum mechanical methods, which, to the best of our knowledge, represents the first time that molecular orbital computational approaches have been applied to AFPs. Molecular mechanical approaches, including molecular docking, energy minimization, and molecular dynamics simulation, were used to obtain optimal systems for subsequent quantum mechanical analysis. We selected 17 surface patches covering the entire surface of the type II AFP and evaluated the interaction energy between each of these patches and two different ice planes using semi-empirical quantum mechanical methods. We have demonstrated the weak orbital overlay phenomenon and the change of bond orders in ice. These results consistently indicate that a surface patch containing 19 residues (K37, L38, Y20, E22, Y21, I19, L57, T56, F53, M127, T128, F129, R17, C7, N6, P5, G10, Q1, and W11) is the most favorable ice-binding site for both a regular ice plane and an ice plane where water O atoms are randomly positioned. Furthermore, for the first time the computation results provide new insights into the weakening of the ice lattice upon AFP binding, which may well be a primary factor leading to AFP-induced ice growth inhibition.