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This article presents a distributed prescribed performance formation tracking control scheme for nonlinear multiagent systems with the consideration of collision avoidance. Specifically, a novel prescribed performance control (PPC) method is designed. Different from the existing results, the predefined tracking error convergence region and the predefined settling time can be set without constraints. Moreover, the PPC method can remove the initial condition-dependence restriction of tracking errors. In addition, a predefined-time distributed observer is produced to estimate the information of the reference signal. Contrary to the existing related literature, the estimation errors can asymptotically converge to zero within a predefined time, even in the case of unknown disturbances. Combining a Lyapunov–Barrier function and the PPC method, the proposed control protocol enables agents to avoid obstacles and ensures that the formation tracking errors reach the predefined convergence region within a predefined time. Finally, a simulation demonstrates the validity of the algorithm.

The continuous use of fossil energy will lead to a severe energy crisis. Hydrogen is a potential alternative energy due to its renewability, high energy density, and low emissions. However, hydrogen energy faces a huge challenge in terms of storage. Biomass-based porous carbon (BBPC) has attracted much attention owing to its advantages of wide sources and excellent pore structure with low manufacturing costs. This review focuses on recent advances in the application of BBPC in hydrogen storage, particularly performance enhancement methods. Based on the analysis of hydrogen storage mechanisms in BBPC materials, the preparation methods for hydrogen storage in recent years have been systematically reviewed. The strategies to improve hydrogen storage performance on BBPC materials are discussed in detail, including heteroatom doping, metal atomic modification, and multicomponent composite design. Finally, the challenges and future development of BBPC in hydrogen storage applications are summarized.

The development of architecturally unique molecular nanocarbons by bottom-up organic synthesis is essential for accessing functional organic materials awaiting technological developments in fields such as energy, electronics, and biomedicine. Herein, we describe the design and synthesis of a triptycene-based three-dimensional (3D) nanocarbon, GFN-1, with geometrical flexibility on account of its three peripheral π-panels being capable of interconverting between two curved conformations. An effective through-space electronic communication among the three π-panels of GFN-1has been observed in its monocationic radical form, which exhibits an extensively delocalized spin density over the entire 3D π-system as revealed by electron paramagnetic resonance and UV–vis–NIR spectroscopies. The flexible 3D molecular architecture of GFN-1, along with its densely packed superstructures in the presence of fullerenes, is revealed by microcrystal electron diffraction and single-crystal X-ray diffraction, which establish the coexistence of both propeller and tweezer conformations in the solid state. GFN-1exhibits strong binding affinities for fullerenes, leading to host–guest complexes that display rapid photoinduced electron transfer within a picosecond. The outcomes of this research could pave the way for the utilization of shape and electronically complementary nanocarbons in the construction of functional coassemblies.

Robots’ manipulation accuracy is heavily determined by the calibration accuracy of the tool center point (TCP). This article proposes posture-sequence particle swarm optimization (PS2O) for TCP calibration. First, the mechanism of the condition number and the minimum eigenvalue of the regression matrix on the calibration accuracy are analyzed. Second, a multiobjective optimization problem is constructed based on the condition number, the minimum eigenvalue, and the sum of adjacent posture distances. Finally, an optimized posture sequence is obtained by applying the particle swarm optimization (PSO) algorithm to the constructed multiobjective optimization problem. Simulations and experiments demonstrate that the error of TCP calibration can be characterized by the condition number and the minimum eigenvalue of the regression matrix. Compared with random posture sampling, the optimized posture sequence for sampling reduces the norm of the calibration error by 38.66%. Thus, PS2O has great potential to improve robots’ manipulation accuracy.

A long history has passed since electromyography (EMG) signals have been explored in human-centered robots for intuitive interaction. However, it still has a gap between scientific research and real-life applications. Previous studies mainly focused on EMG decoding algorithms, leaving a dynamic relationship between the human, robot, and uncertain environment in real-life scenarios seldomly concerned. To fill this gap, this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction (HREI) systems. The general processing framework is summarized, and three interaction paradigms, including direct control, sensory feedback, and partial autonomous control, are introduced. EMG-based intention decoding is treated as a module of the proposed paradigms. Five key issues involving precision, stability, user attention, compliance, and environmental awareness in this field are discussed. Several important directions, including EMG decomposition, robust algorithms, HREI dataset, proprioception feedback, reinforcement learning, and embodied intelligence, are proposed to pave the way for future research. To the best of what we know, this is the first time that a review of EMG-based methods in the HREI system is summarized. It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems, in which factors in human-robot interaction, robot-environment interaction, and state perception by human sensations are considered, which has never been done by previous studies.

Organic trisradicals featuring threefold symmetry have attracted significant interest because of their unique magnetic properties associated with spin frustration. Herein, we describe the synthesis and characterization of a triangular prism-shaped organic cage for which we have coined the name PrismCage6+and its trisradical trication─TR3(•+). PrismCage6+is composed of three 4,4′-bipyridinium dications and two 1,3,5-phenylene units bridged by six methylene groups. In the solid state, PrismCage6+adopts a highly twisted conformation with close to C3symmetry as a result of encapsulating one PF6–anion as a guest. PrismCage6+undergoes stepwise reduction to its mono-, di-, and trisradical cations in MeCN on account of strong electronic communication between its 4,4′-bipyridinium units. TR3(•+), which is obtained by the reduction of PrismCage6+employing CoCp2, adopts a triangular prism-shaped conformation with close to C2vsymmetry in the solid state. Temperature-dependent continuous-wave and nutation-frequency-selective electron paramagnetic resonance spectra of TR3(•+)in frozen N,N-dimethylformamide indicate its doublet ground state. The doublet–quartet energy gap of TR3(•+)is estimated to be −0.08 kcal mol–1, and the critical temperature of spin-state conversion is found to be ca. 50 K, suggesting that it displays pronounced spin frustration at the molecular level. To the best of our knowledge, this example is the first organic radical cage to exhibit spin frustration. The trisradical trication of PrismCage6+opens up new possibilities for fundamental investigations and potential applications in the fields of both organic cages and spin chemistry.

Energy transfer and exciplex emission are not only crucial photophysical processes in many living organisms but also important for the development of smart photonic materials. We report, herein, the rationally designed synthesis and characterization of two highly charged bischromophoric homo[2]catenanes and one cyclophane incorporating a combination of polycyclic aromatic hydrocarbons, i.e., anthracene, pyrene, and perylene, which are intrinsically capable of supporting energy transfer and exciplex formation. The possible coconformations of the homo[2]catenanes, on account of their dynamic behavior, have been probed by Density Functional Theory calculations. The unique photophysical properties of these exotic molecules have been explored by steady-state and time-resolved absorption and fluorescence spectroscopies. The tetracationic pyrene–perylene cyclophane system exhibits emission emanating from a highly efficient Förster resonance energy transfer (FRET) mechanism which occurs in 48 ps, while the octacationic homo[2]catenane displays a weak exciplex photoluminescence following extremely fast (<0.3 ps) exciplex formation. The in-depth fundamental understanding of these photophysical processes involved in the fluorescence of bischromophoric cyclophanes and homo[2]catenanes paves the way for their use in future bioapplications and photonic devices.

Triplet–triplet annihilation-based molecular photon upconversion (TTA-UC) is a photophysical phenomenon that can yield high-energy emitting photons from low-energy incident light. TTA-UC is believed to fuse two triplet excitons into a singlet exciton through several consecutive energy-conversion processes. When organic aromatic dyes─i.e., sensitizers and annihilators─are used in TTA-UC, intermolecular distances, as well as relative orientations between the two chromophores, are important in an attempt to attain high upconversion efficiencies. Herein, we demonstrate a host–guest strategy─e.g., a cage-like molecular container incorporating two porphyrinic sensitizers and encapsulating two perylene emitters inside its cavity─to harness photon upconversion. Central to this design is tailoring the cavity size (9.6–10.4 Å) of the molecular container so that it can host two annihilators with a suitable [π···π] distance (3.2–3.5 Å). The formation of a complex with a host:guest ratio of 1:2 between a porphyrinic molecular container and perylene was confirmed by NMR spectroscopy, mass spectrometry, and isothermal titration calorimetry (ITC) as well as by DFT calculations. We have obtained TTA-UC yielding blue emission at 470 nm when the complex is excited with low-energy photons. This proof-of-concept demonstrates that TTA-UC can take place in one supermolecule by bringing together the sensitizers and annihilators. Our investigations open up some new opportunities for addressing several issues associated with supramolecular photon upconversion, such as sample concentrations, molecular aggregation, and penetration depths, which have relevance to biological imaging applications.

AbstractFuture advances in nuclear power technologies call for enhanced operator advice and autonomous control capabilities that can leverage simpler designs and increased safety features to reduce reliance on human labor. One of the first tasks in the development of such capabilities is the formulation of symptom-based conditional failure probabilities for the plant structures, systems, and components (SSCs) of interest. The primary goal is to aid plant personnel in (1) deducing the probabilistic performance status of the monitored SSCs and (2) detecting impending faults/failures. The task of estimating conditional failure probability is a bidirectional inference problem, and a logical approach is to use the Bayesian network (BN) method. As a knowledge-based explainable artificial intelligence tool and a probabilistic graphical model, BN offers reasoning capability under uncertainty, graphical representation emulating physical behavior of the target SSC, and interpretability of the model structure and results. This paper provides a systematic overview of the BN technique and the software tools for implementing BN models, along with the associated knowledge representation and reasoning paradigm. Both operational data and expert judgment can be readily incorporated into the knowledge base of a BN model. The challenges with data availability are highlighted, and the general approach to target SSC identification is presented. The focus is on failure-prone and risk-important balance of plant assets, especially for cases with strong operator involvement. Two example case studies on the failure of (1) a centrifugal pump and (2) an electric motor are conducted to demonstrate the usefulness and technical feasibility of the proposed BN-based fault diagnostic system using an expert system shell.

When applying exoskeletons for walking assistance, one important consideration is to ensure that the users retain full control over the exoskeleton-provided assistance, which is quite limited in existing exoskeletons due to the absence of a suitable control system. In this article, a time-independent exoskeleton control system is developed based on a novel assistance profile generation method and an iterative force control method to enable continuous assistance adjustment. The assistance profile is formulated as a Gaussian function with a human state variable and can be updated online to adapt to different users. The proposed profile continuously self-adjusts along the movement of the user's leg, especially when users change their walking patterns. The proposed control system iteratively compensates for the force control lag and amplitude attenuation to enable precise tracking of the assistance profile during natural human walking. Experiments have been conducted using a soft exoskeleton on subjects with and without prior experience using an exoskeleton. The experimental results have shown the effectiveness of the proposed control system compared with a common time-dependent control system.

Direct estimation of body weight through noncontact methods is crucial for applications such as health monitoring, surveillance, and robot-assisted casualty rescue. Existing methods for body weight estimation from images are often affected by various factors, such as camera distance, human orientation, and body posture, which ignore the fact that bodies typically inhabit 3-D space. To address the problem, we propose an approach for estimating body weight based on virtual anthropometric measurements and deep features instead of estimating by reasoning pixels. Specifically, we develop a three-branch framework that includes face feature extraction, body feature extraction, and deep feature extraction and maps all features with a regressor. The developed method adds 3-D shape reconstruction to explicitly reason about virtual anthropometric measurements. To enable this, our model is trained to robustly compute anthropometric measurements in various orientations and postures. Furthermore, we evaluate our method on a public dataset and Image-VM-BMI, a new dataset of 4740 images, including body mass index (BMI) labels and virtual anthropometric measurement labels with paired 3-D reconstruction. Extensive experimental results demonstrate that the proposed method outperforms pixel-based analysis approaches on BMI estimation.

Molecular recognition, based on noncovalent bonding interactions, plays a central role in directing supramolecular phenomena in both chemical and biological environments. The identification and investigation of weakly associated recognition motifs, however, remains a major challenge, especially when the motifs are interlinked with and obscured by other robust binding modes in complicated systems. For example, although the host–guest recognition between the radical cations of both cyclobis(paraquat-p-phenylene) (CBPQT) and 4,4′-bipyridinium (BIPY) salts has been thoroughly investigated, the question of whether other binding modes exist between these two positively charged entities is the subject of some debate because of the complexity and dynamic nature of this supramolecular system. In order to address this conundrum, we have synthesized a [2]catenane─formed by mechanical interlocking between CBPQT and another BIPY-containing ring─which enhances the weak interactions between components and reduces significantly the complexity of the system for easier characterization. By employing this [2]catenane as a model compound, we have performed a full-spectrum investigation of radical interactions and revealed unambiguously a total of three possible binding modes between CBPQT and BIPY─to be specific, a bisradical tetracationic, a trisradical tricationic, and a bisradical dicationic association─as demonstrated by various methods of characterization including UV/vis/NIR, EPR, and NMR spectroscopies, electrochemical measurements and X-ray crystallography. The two newly discovered bisradical binding modes have potential applications in the construction of self-assembled materials and in mediating supramolecular catalysis. The mechanical bond-assisted approach used in this research is broadly applicable to investigating noncovalent bonding interactions.

Molecular recognition1–4and supramolecular assembly5–8cover a broad spectrum9–11of non-covalently orchestrated phenomena between molecules. Catalysis12of such processes, however, unlike that for the formation of covalent bonds, is limited to approaches13–16that rely on sophisticated catalyst design. Here we establish a simple and versatile strategy to facilitate molecular recognition by extending electron catalysis17, which is widely applied18–21in synthetic covalent chemistry, into the realm of supramolecular non-covalent chemistry. As a proof of principle, we show that the formation of a trisradical complex22between a macrocyclic host and a dumbbell-shaped guest—a molecular recognition process that is kinetically forbidden under ambient conditions—can be accelerated substantially on the addition of catalytic amounts of a chemical electron source. It is, therefore, electrochemically possible to control23the molecular recognition temporally and produce a nearly arbitrary molar ratio between the substrates and complexes ranging between zero and the equilibrium value. Such kinetically stable supramolecular systems24are difficult to obtain precisely by other means. The use of the electron as a catalyst in molecular recognition will inspire chemists and biologists to explore strategies that can be used to fine-tune non-covalent events, control assembly at different length scales25–27and ultimately create new forms of complex matter28–30.

Human locomotor activity (LA) recognition is important in the control of exoskeletons and prostheses and in patient monitoring. This article presents a practical recognition approach that can classify level walking, stair ascent, and stair descent activities across different subjects and diverse gait patterns. The thigh angle is measured and utilized in this method to construct a phase curve in an activity-specific coordinate frame during a stride. The LA is recognized by matching the curvature of its phase curve to the expected one. The factors affecting the adaptability of the proposed method to gait variations are analyzed and compensated for. The proposed method is evaluated with eight subjects who are asked to perform the three types of activity at two different cadences: 70 steps/min and 110 steps/min. Experimental results show that the proposed classifier outperforms an existing phase variable based classifier in all validation experiments and a ${\boldsymbol{k}}$-nearest neighbor classifier when using nonsubject-specific training data, indicating that the proposed method has superior adaptability to changes in human and in strides. Moreover, the feature used in the proposed method has demonstrated the potential in quantitatively indicating the extent of neuromotor impairments of patients.

China has set carbon emission goals for 2030 and 2060. Renewable energy sources, primarily wind and photovoltaic power, are being considered as the future of power generation. The major limitation to the development of new energies is the limited flexibility of regulations on power system resources, resulting in insufficient consumption capacity. Thus, the flexible resource costs for peak shaving as well as the reasonable coordinated development and operation optimization of regional renewable energy need to be considered. In this study, a renewable energy development layout configuration analysis method was established by considering the composite cost of a power system, comprehensively analyzing the potential of various flexibility regulation resources for the power system and its composite peak shaving cost, and combining renewable energy output characteristics, load forecasting, grid development, and other factors. For the optimization of various flexible resource utilization methods, a peak shaving cost estimation method from the perspective of the entire power system was established by combining the on-grid electricity prices and operating costs of different power sources. A collaborative optimization model of power system operation that aims at the lowest peak shaving cost and satisfies the constraints of operation, safety, and environmental protection was proposed. Finally, a certain area of Gansu Province was used as an example to perform detailed analysis and calculation, which demonstrated that the model has an optimal effect. This model can provide an analysis method for regional renewable energy development layout configurations and system optimization operations.

The excited-state dynamics of a spiro-fused terrylene-3,4:11,12-bis(dicarboximide) (TDI) dimer (sTDI2) in toluene and 2-methyltetrahydrofuran (mTHF) were investigated as a function of temperature using femtosecond- and nanosecond-transient absorption spectroscopy, as well as two-dimensional electronic spectroscopy. The spiro conjugation and the corresponding geometry of this compound guarantee a short intermonomer distance along with a partial orbital overlap between the orthogonal TDI π-electron systems, providing electronic coupling between the TDIs. Photoexcitation of sTDI2in toluene, a low dielectric solvent, at 295 K, results in the ultrafast formation of a state composed of a coherent mixture of singlet 1(S1S0), multiexciton 1(T1T1), and charge-transfer (CT) electronic characters. This mixed species decays to decorrelated triplet states on the nanosecond timescale, completing the process of intramolecular singlet fission (SF) in sTDI2. Upon decreasing the temperature from 295 to 200 K, the contribution of the 1(T1T1) state to the mixed species decreases concurrently with an increase in the CT state character. We attribute this behavior to the variation in the vibrational energy level alignment between the states comprising the mixture due to changes in the temperature and hence the local dielectric environment. In contrast, photoexcitation of sTDI2in more polar mTHF at 295 K results in the formation of a mixed singlet and CT state before undergoing symmetry-breaking charge separation, owing to the increased stabilization of the CT state in the medium. However, in glassy mTHF at 85 K, photoexcited sTDI2exhibits discernible multiexciton character, comparable to that observed in toluene at 200 K, which we rationalize by the similarity of the dielectric constants under these two sets of conditions. These observations of mixed states of varying diabatic contributions over the range of experimental conditions show that the temperature and the static dielectric constant can directly control the composition of the electronically mixed excited state of sTDI2and thus the fate of the SF process.

Electromyography (EMG) has already been broadly used in human-machine interaction (HMI) applications. Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution. Recently, many EMG pattern recognition tasks have been addressed using deep learning methods. In this paper, we analyze recent papers and present a literature review describing the role that deep learning plays in EMG-based HMI. An overview of typical network structures and processing schemes will be provided. Recent progress in typical tasks such as movement classification, joint angle prediction, and force/torque estimation will be introduced. New issues, including multimodal sensing, inter-subject/inter-session, and robustness toward disturbances will be discussed. We attempt to provide a comprehensive analysis of current research by discussing the advantages, challenges, and opportunities brought by deep learning. We hope that deep learning can aid in eliminating factors that hinder the development of EMG-based HMI systems. Furthermore, possible future directions will be presented to pave the way for future research.

Singlet fission in organic semiconductors provides an important opportunity to study high-spin states in electronically coupled chromophores. Photoexcitation of oriented, crystalline films of N,N-bis(pentadec-8-yl)terrylene-3,4:11,12-bis(dicarboximide) (TDI) and N,N-bis(pentadec-8-yl)quaterrylene-3,4:13,14-bis(dicarboximide) (QDI) result in the formation of the correlated triplet pair quintet state, 5(T1T1) and its subsequent dissociation into two triplet (T1) excitons. Time-resolved electron paramagnetic resonance (TREPR) spectroscopy and X-ray crystallography are used to show that the orientation dependence of 5(T1T1) spin dynamics is retained as it dissociates into two T1excitons, while such information is lost in a randomly oriented sample. In addition, the spin dynamics depend on how the molecules are oriented relative to the external applied magnetic field. Dissociation of 5(T1T1) to form two T1excitons is more efficient in TDIand leads to a longer T1lifetime than in QDI, making TDIa more viable candidate for photovoltaic applications. Since QDIreadily forms a highly oriented film, and the lifetime of its 5(T1T1) state is longer than that of TDI, it may be a good candidate for quantum information science applications that require the generation of a quantum-entangled, four-spin state.

The formation mechanism of volatile compounds in Tan lamb meat under different feeding regimes remains unclear. This study aimed to determine whether the volatile compounds in meat are related to lipid metabolism in an attempt to improve the theoretical basis for increasing the yield and quality of lamb production. Results showed that the specialized pasture grazing with indoor feeding (GF) and indoor feeding only (F) regimes had advantages in terms of growth and carcass traits compared to the specialized pasture grazing only (G) regime. Lamb meat qualities of the GF group were in an intergrade position compared to those of the F and G groups. Although the lamb meat of the three groups had different aroma attributes, as measured using SPME-GC-MS, GF lamb meat had the most pleasant active compounds. In contrast, the expression of lipid transport genes was altered in all three groups. In summary, Tan lambs had different growth performance, intramuscular fat content, and composition under the three feeding regimes, which might be due to the differences in energy and lipid transport, resulting in unique volatile compound profiles in meat from different groups.

AbstractAs part of the Consortium for Advanced Simulation of Light Water Reactors, the subchannel code CTF is being used for single-phase and two-phase flow analysis under light water reactor operating conditions. Accurate determination of flow distribution, pressure drop, and void content is crucial for predicting margins to thermal crisis and ensuring more efficient plant performance. In preparation for the intended applications, CTF has been validated against data from experimental facilities comprising the General Electric (GE) 3 × 3 bundle, the boiling water reactor full-size fine-mesh bundle tests (BFBTs), the Risø tube, and the pressurized water reactor subchannel and bundle tests (PSBTs). Meanwhile, the licensed, well-recognized subchannel code VIPRE-01 was used to generate a baseline set of simulations for the targeted tests and solution parameters were compared to the CTF results.The flow split verification problem and single-phase GE 3 × 3 results are essentially in perfect agreement between the two codes. For the two-phase GE 3 × 3 cases, flow and quality discrepancies arise in the annular-mist flow regime, yet significant improvement is observed in CTF when void drift and two-phase turbulent mixing enhancement are considered. The BFBT pressure drop benchmark shows close agreement between predicted and measured results in general, although considerable overprediction by CTF is observed at relatively high void locations of the facility. This overestimation tendency is confirmed by the Risø cases. While overall statistics are satisfactory, both BFBT and PSBT bubbly-to-churn flow void contents are markedly overpredicted by CTF.The issues with two-phase closures such as turbulent mixing, interfacial and wall friction, and subcooled boiling heat transfer need to be addressed. Preliminary sensitivity studies are presented herein, but more advanced models and code stability analysis require further investigation.

AbstractWith the objective of providing long-term energy supply via actinide breeding and burning, the next-generation boiling water reactor (BWR) design, the Hitachi’s resource-renewable BWR (RBWR), has been proposed. Unlike a traditional square lattice BWR fuel bundle, the RBWR bundles are shorter with hexagonal tight lattice arrangement and heterogeneous axial fuel zoning. The RBWR’s different core geometry combined with the higher power-to-flow ratio and void fraction necessitates the reexamination of the standard BWR thermal-hydraulic models.For the prediction of dryout, the previously derived best-estimate empirical correlation showed significant scatter when compared to experimental data within its calibration database. In this work, the correlation is further calibrated and improved by supplementing tight bundle data with relevant critical power data for tubes and annuli to better quantify the effects of various parameters and by incorporating subchannel-level results to account for intra-assembly flow mixing. Another approach using the mechanistic three-field model is also investigated, and the minimum critical power ratio of the RBWR design is evaluated.For the prediction of void fraction, measurements and the three-field model in annular flow regime reveal that the common drift flux approaches tend to overestimate the void fraction at small hydraulic diameters. The void fraction dependence on hydraulic diameter below 10 mm requires further experimentation and high-fidelity mechanistic simulations.

Acupuncture is a traditional Chinese therapeutic method, recognized by western medicine as an important complementary therapy. However, the efficacy assessment of this traditional intervention has been mainly empirical rather than scientific. In this paper, we propose a surface electromyography (sEMG) based approach for quantitative assessment of acupuncture on Bell’s palsy. The assessment is made by comparing the muscle activities of healthy with diseased ones. A feature-vector of four individual sEMG features is introduced for more comprehensive representation of muscle activity. A clustering technique is then proposed to calculate quantitative differences between the muscle activities of the healthy and diseased sides. A regressive model is also proposed to predict the recovery trend of a patient based on the quantitative assessments during his/her clinical acupuncture history. As reported in the paper, a total of 20 selected Bell’s palsy patients have participated in the extensive experiments that were conducted to verify the performance of the proposed method. 针刺是一种传统的中医治疗手段, 已经在临床上得到广泛的应用. 但是, 针刺疗效目前缺乏客观精确的量化评估方法. 本文提出一种基于表面肌电信号的针刺治疗面瘫疗效量化评估方法, 主要包括以下几个部分: 首先, 采集患者健康侧与患侧的表面肌电信号, 并提取特征, 组建特征向量; 然后, 采用主元分析和 k均值方法, 对特征向量进行降维聚类, 以类别中心距离作为评估针刺疗效的指标; 最后, 利用类别中心距离构造自回归模型, 预测患者的康复趋势. 20 名面瘫患者参与到本实验中, 验证上述方法. 结果表明, 本文方法预测精度达到 92.8%以上.

The absence of tactile force information at the tip of a medical instrument makes precise minimally invasive surgery difficult and is prone to resulting in serious outcomes. In this paper, a fiber optic force sensor is fabricated based on Fabry-Pérot interferometry and integrated with a puncture needle. The force sensor is attached to the needle tip, where interactive force arises as it inserts into soft tissue. Needle insertion experiments have been conducted on ex vivo swine liver and belly with the calibrated force sensor. Using wavelet transform method, the acquired force data are analyzed and used to identify layered tissue types and boundaries. We found that the force amplitudes are not always identical, but the patterns of forces are almost the same, which enables us to identify layered tissues and to realize a safe needle insertion procedure under robot control.

The sEMG based movement recognition developed rapidly in recent years, which focus on intention estimation that velocity and angle of movement joint are not concerned. This paper proposed a quantitative analysis method of sEMG, with ability to estimate motion of human joints, which can be used to control rehabilitation robot system control by patient's own intention. The quantitative model of the relationship between sEMG signals and movement joint was established utilizing error Back Propagation artificial Neural Network and support vector machine with a Gaussian kernel, where the features of sEMG were taken as input. Considering of the actual demands of rehabilitation, the 1-DOF, 2-DOFs and 3-DOFs movement experiments were supposed to collect the information of joint angle and sEMG signals for model training. The result shows the angle prediction curve outputted by model of SVM has more than 90% consistency with the actual movement, while the model of BPNN gets a more imprecise output with complexity of movement arising. Initial online experiments on rehabilitation robot controlled by a healthy subject demonstrate that sEMG based movement control using the proposed method is feasible.

Quantitative analysis of pain is extremely difficult, because it is a subjective and individual sensation caused by the potential or existing observable tissue injury. For individuals with major cognitive or communicative impairments, it is necessary to carry out an effective method to quantify pain without self-report. Focusing on using physiological signals of the human body to evaluate pain, this paper proposes a new quantitative evaluation method with multiple physiological information to recognize the intensity of pain, which is induced by electrical stimulation that can be measured. When different intensity electrical stimulation applying on the subject, three-channel biosensors (BVP, ECG, SC) were used to obtain blood volume pulse, electrocardiogram and skin conductance. Experiments show that the proposed method can estimate the intensity of stimulation, which means that it can give the objective and quantitative evaluation of the pain.

Multi-channel surface electromyography (sEMG) recognition has been investigated extensively by researchers over the past several decades. However, due to the nature of sEMG sensors, the more sensors are used, the greater chance for the sEMG to be influenced by environment noise. Furthermore, it is not feasible to use multi-sensors in some cases because of the bulky size of the sensors and the limited area of muscles. This paper proposes a novel sEMG recognition method based on the decomposition of single-channel sEMG. At first, sEMG is acquired while the participant does 5 predetermined hand gestures. Then, this signal is decomposed into its component motor unit potential trains (MUAPTs), which includes 4 steps: 2-order differential filtering, spikes detection, dimension reduction and clustering with Gaussian Mixture Model (GMM). Finally, 5 MUAPTs are obtained and used for hand gestures classification: four features, integral of absolute value (IAV), maximum value (MAX), median value of non-zero value (NonZeroMed) and index of NonZeroMed (Ind) are extracted to form feature matrix, which is then classified with the algorithm of Linear Discriminate Analysis (LDA). The classification results indicate this method can achieve an accuracy of 74.7% while the accuracy of traditional classification method for single-channel sEMG is about 52.6%.

Artificial molecular pumps (AMPs), inspired by the active cellular transport exhibited in biological systems, enable cargoes to undergo unidirectional motion, courtesy of molecular ratchet mechanisms in the presence of energy sources. Significant progress has been achieved, using alternatively radical interactions and Coulombic repulsive forces to create working AMPs. In an attempt to widen the range of these AMPs, we have explored the effect of molecular pumping on the photophysical properties of a collecting chain on a dumbbell incorporating a centrally located pyrene fluorophore and two terminal pumping cassettes. The AMP discussed here sequesters two tetracationic cyclophanes from the solution, generating a [3]rotaxane in which the fluorescence of the dumbbell is quenched. The research reported in this Article demonstrates that the use of pumping cassettes allows us to generate the [3]rotaxane in which the photophysical properties of fluorophores can be modified in a manner that cannot be achieved with a mixture of the dumbbell and ring components of the rotaxane on account of their weak binding in solution.

To allow for single‐crystal nuclear magnetic resonance (scNMR) investigations, an existing narrow bore high‐field double‐resonance millicoil 19F and 1H solid‐state NMR probe was modified by adding a goniometer stage to the top. The goniometer was kept outside of the radiofrequency (RF) transceiver coil for improved filling factor and probe sensitivity. Because of the large size of single crystal grown, the transceiver coil was changed from a standard millicoil to a split‐millicoil, or crude helmholtz coil, design with effects on probe performance further studied herein. The type of goniometer and crystal sample holder chosen allows for accurate rotation of the single crystal in all three orthogonal planes (x, y, and z) while allowing for the sample to be easily removed forX‐ray diffraction study. Careful consideration was taken in selection of non‐fluorinated materials making up the probe head to reduce unwanted 19F background in the NMR signal. Goniometer functionality is demonstrated by 19F scNMR rotation spectra of 5‐fluoro‐DL‐tryptophan (5F‐DL‐Trp) required to determine the independent elements of its 19F chemical shielding anisotropic tensor. © 2007 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 31B: 203–208, 2007

Genetic studies in mouse and zebrafish have established the importance of activin receptor-like kinase 1 (ALK1) in formation and remodeling of blood vessels. Single-allele mutations in the ALK1gene have been linked to the human type 2 hereditary hemorrhagic telangiectasia (HHT2). However, how these ALK1mutations contribute to this disorder remains unclear. To explore the mechanism underlying effect of the HHT-related ALK1mutations on receptor activity, we generated 11 such mutants and investigated their signaling activities using reporter assay in mammalian cells and examined their effect on zebrafish embryogenesis. Here we show that some of the HHT2-related mutations generate a dominant-negative effect whereas the others give rise to a null phenotype via loss of protein expression or receptor activity. These data indicate that loss-of-function mutations in a single allele of the ALK1locus are sufficient to contribute to defects in maintaining endothelial integrity.

Genetic studies in mouse and zebrafish have established the importance of activin receptor-like kinase 1 (ALK1) in formation and remodeling of blood vessels. Single-allele mutations in the ALK1 gene have been linked to the human type 2 hereditary hemorrhagic telangiectasia (HHT2). However, how these ALK1 mutations contribute to this disorder remains unclear. To explore the mechanism underlying effect of the HHT-related ALK1 mutations on receptor activity, we generated 11 such mutants and investigated their signaling activities using reporter assay in mammalian cells and examined their effect on zebrafish embryogenesis. Here we show that some of the HHT2-related mutations generate a dominant-negative effect whereas the others give rise to a null phenotype via loss of protein expression or receptor activity. These data indicate that loss-of-function mutations in a single allele of the ALK1 locus are sufficient to contribute to defects in maintaining endothelial integrity.

Shape memory alloy (SMA) has been utilized as the material of smart actuators due to the miniaturization and lightweight. However, the nonlinearity and hysteresis of SMA material seriously affect the precise control. In this article, a novel disturbance compensation-based adaptive control scheme is developed to improve the control performance of SMA actuator system. Firstly, the nominal model is constructed based on the physical process. Next, an estimator is developed to online update not only the unmeasured system states but also the total disturbance. Then, the novel adaptive controller, which is composed of the nominal control law and the compensation control law, is designed. Finally, the proposed scheme is evaluated in the SMA experimental setup. The comparison results have demonstrated that the proposed control method can track reference trajectory accurately, reject load variations and stochastic disturbances timely, and exhibit satisfactory robust stability. The proposed control scheme is system independent and has some potential in other types of SMA-actuated systems.

Understanding singlet fission (SF) is an important strategy for extending the power conversion efficiency of next-generation solar cells beyond the Shockley–Queisser limit. Thus far, most studies of SF have focused on polycrystalline films, whose heterogeneity often makes it difficult to probe the electronic states involved in the formation of the correlated triplet biexciton state, 1(T1T1), and its decorrelation into free triplet excitons. Polarization-resolved, femtosecond transient absorption microscopy of a 1,6,9,14-tetraphenylterrylene-3,4:11,13-bis(dicarboximide) (Ph4TDI) single crystal reveals the formation of transient spectra in <200 fs having features characteristic of 1(T1T1), 1(S1S0), and Ph4TDI•+-Ph4TDI•–charge-transfer (CT) states. This indicates that either an ultrafast equilibrium between these states occurs or that the initially formed biexciton state is a mixture of these states. This spectrum evolves in time to give the Tn← T1spectrum of the free triplet excitons. We show further that this initially formed state has its optical transition polarized nearly perpendicular to that of the Tn← T1transition in the free triplet excitons. This indicates that the observed free triplet excitons have migrated from the π-stacked Ph4TDIcolumns where the 1(T1T1) state is produced to neighboring, nearly orthogonal π-stacked Ph4TDIcolumns, resulting in a weaker electronic interaction between the free triplet excitons essential to extending their lifetimes. However, the mobility of the 1(T1T1) state in the Ph4TDIπ-stacking direction results in significant annihilation of biexciton pairs limiting the yield of free triplet excitons to about 60%.

Investigating how electrons propagate through a single molecule is one of the missions of molecular electronics. Electrons, however, are also efficient catalysts for conducting radical reactions, a property that is often overlooked by chemists. Special attention should be paid to electron catalysis when interpreting single-molecule conductance results for the simple reason that an unexpected reaction mediated or triggered by electrons might take place in the single-molecule junction. Here, we describe a counterintuitive structure–property relationship that molecules, both linear and cyclic, employing a saturated bipyridinium–ethane backbone, display a similar conductance signature when compared to junctions formed with molecules containing conjugated bipyridinium–ethene backbones. We describe an ethane-to-ethene transformation, which proceeds in the single-molecule junction by an electron-catalyzed dehydrogenation. Electrochemically based ensemble experiments and theoretical calculations have revealed that the electrons trigger the redox process, and the electric field promotes the dehydrogenation. This finding not only demonstrates the importance of electron catalysis when interpreting experimental results, but also charts a pathway to gaining more insight into the mechanism of electrocatalytic hydrogen production at the single-molecule level.

Understanding the natural diet of grazing sheep can help fulfill their nutritional requirements and positively affect the quality of their meat. Emerging fecal DNA (fDNA) metabarcoding technology can provide more accurate estimates for the dietary composition of free-ranging animals. This study has shown that pasture feeding can promote deposition of n-3 polyunsaturated fatty acids (PUFAs) in Tan lambs’ muscle and decrease the ratio of n-6/n-3 fatty acids (FAs), and thus, we investigated the dietary composition of grazing lambs using fDNA metabarcoding to assess the prevalence of medicinal herbage plants in their diet. Herein, based on the full-time natural pasture grazing and 4-h natural pasture grazing with indoor feeding patterns, the herbage taxa (Bassia scoparia, Euphorbia humifusa, Arnebia euchroma, and Salsolasp.) most correlated to n-3 PUFAs were highlighted to elucidate how diversification in dietary components was associated with the muscle FA profile of lambs. Our findings provide experimental evidence for future feeding research.

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For Abstract see ChemInform Abstract in Full Text.