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In this work, a highly stretchable and sensitive strain sensor using silver nanowires (Ag NWs)/multi-walled carbon nanotubes (MWCNTs) on hair band is proposed. The fabrication process of such sensors enabled scalable and facile production with low cost by dipping hair band into Ag NWs/MWCNTs composites suspension. The sensing performance of the sensors was optimized by tuning the Ag NWs/MWCNTs mass ratio. The hair band based strain sensor with Ag NWs/MWCNTs mass ratio of 30 exhibited the best performance with high sensitivity of 416.0 and good stretchability up to 70%. Moreover, great repeatability and long-term stability could be achieved over 7500 cycles of stretch-release. This Ag NWs/MWCNTs-hair band sensor can be used for monitoring human motions and swallowing action.

Aerogels are nanoporous materials with excellent properties, especially super thermal insulation. However, owing to their serious high brittleness, the macroscopic forms of aerogels are not sufficiently rich for the application in some fields, such as thermal insulation clothing fabric. Recently, freeze spinning and wet spinning have been attempted for the synthesis of aerogel fibers. In this study, robust fibrous silica-bacterial cellulose (BC) composite aerogels with high performance were synthesized in a novel way. Silica sol was diffused into a fiber-like matrix, which was obtained by cutting the BC hydrogel and followed by secondary shaping to form a composite wet gel fiber with a nanoscale interpenetrating network structure. The tensile strength of the resulting aerogel fibers reached up to 5.4 MPa because the quantity of BC nanofibers in the unit volume of the matrix was improved significantly by the secondary shaping process. In addition, the composite aerogel fibers had a high specific area (up to 606.9 m2/g), low density (less than 0.164 g/cm3), and outstanding hydrophobicity. Most notably, they exhibited excellent thermal insulation performance in high-temperature (210 °C) or low-temperature (−72 °C) environments. Moreover, the thermal stability of CAFs (decomposition temperature was about 330 °C) was higher than that of natural polymer fiber. A novel method was proposed herein to prepare aerogel fibers with excellent performance to meet the requirements of wearable applications.

Turning behavior classification of oncoming vehicles is a critical step toward high-level scene understanding and motion planning tasks for autonomous vehicles. In this paper, we propose a new method for classifying an oncoming vehicle's turning behavior at intersection using 3D LIDAR, i.e., a Velodyne HDL-64E LIDAR, which collects rich point clouds from the surrounding environment. First, the vehicle pose is measured via a novel rectangle-based multi-frame fitting method applied to the vehicle point cloud extracted by a data pre-process procedure. Then, a Kalman filter integrates these measured vehicle poses to estimate and update vehicle kinematic parameters. Next, a hidden Markov model and Bayesian filtering are combined to recognize the vehicle's turning behavior using the heading angle and the acceleration components of the kinematic model. Real point clouds from intersection environments are used to train and validate the proposed turning behavior classification algorithm in the experiments. The results of the performance analysis and classification time measurements confirm that the proposed method can recognize the behavior of the oncoming vehicle at intersections correctly at an early stage of entering an intersection.

Inspired by information processing and communication of life based on complex molecular interactions, some artificial (bio)chemical systems have been developed for applications in molecular information processing or chemo/biosensing and imaging. However, little attention has been paid to simultaneously and comprehensively utilize the information computing, encoding, and molecular recognition capabilities of molecular-level systems (such as DNA-based systems) for multifunctional applications. Herein, a graphene-based steganographically aptasensing system was constructed for multifunctional application, which relies on specific molecular recognition and information encoding abilities of DNA aptamers ( Aeromonas hydrophila and Edwardsiella tarda-binding aptamers as models) and the selective adsorption and fluorescence quenching capacities of graphene oxide (GO). Although graphene-DNA systems have been widely used in biosensors and diagnostics, our proposed graphene-based aptasensing system can not only be utilized for fluorescence sensing and in vivo imaging of fish pathogens ( A. hydrophila and E. tarda), but can also function as a molecular-level logic computing system where the combination of matters (specific molecules or materials) as inputs produces the resulting product (matter level) or fluorescence (energy level) changes as two outputs. More importantly and interestingly, our graphene-based steganographically aptasensing system can also serve as a generally doubly cryptographic and steganographic system for sending different secret messages by using pathogen-binding DNA aptamers as information carriers, GO as a cover, and a pair of keys, that is, target pathogen as a public key, the encryption key used to encode or decode a message in DNA as a private key. Our study not only provides a novel nanobiosensing assay for rapid and effective sensing and in vivo imaging of fish pathogens, but also demonstrates a prototype of (bio)molecular steganography as an important and interesting extension direction of molecular information technology, which is helpful in probably promoting the development of multifunctional molecular-level devices or machines.

With the information system has been greatly improved, how to fast and effective crack the passwords can be of great significance to detect unknown information, obtain important information, prevent hacker attacks, and protect information security in detective work. Genetic algorithm is a kind of evolutionary algorithm. It searches for the optimal solution by mimicking the choice of nature and the mechanism of genetics. Genetic algorithm has three basic operators: selection, crossover, and mutation. The main method of numerical method for solving NP problem is an iterative operation. This paper studies the possible consequences of password cracking and how to quickly and effectively enter the system to decrypt the personal information. The main work is study the algorithmic process of genetic algorithm and solve the problem. First introduces the specific genetic process of genetic algorithm and then uses an example to show how genetic algorithm works. In the analysis of how genetic algorithms works, it is better we develop better method to avoid the information has been stolen.

Background: The effect of immunonutrition in patients undergoing hepatectomy remains unclear. This meta-analysis aimed to assess the impact of immunonutrition on postoperative clinical outcomes in patients undergoing hepatectomy. Methods: A literature search of PubMed, Cochrane Library, Web of Science, and Embase databases was performed to identify all randomized controlled trials (RCTs) exploring the effect of perioperative immunonutrition in patients undergoing hepatectomy until the end of March 10, 2020. Quality assessment and data extraction of RCTs were conducted independently by 3 reviewers. Mean difference (MD) and odds ratio (OR) with 95% confidence interval (CI) were calculated using a fixed-effects or random-effects model. The meta-analysis was performed with RevMan 5.3 software. Results: Nine RCTs involving a total of 966 patients were finally included. This meta-analysis showed that immunonutrition significantly reduced the incidences of overall postoperative complications (OR = 0.57, 95% CI: 0.34–0.95; p = 0.03), overall postoperative infectious complications (OR = 0.53, 95% CI: 0.37–0.75; p = 0.0003), and incision infection (OR = 0.50, 95% CI: 0.28–0.89; p = 0.02), and it shortened the length of hospital stay (MD = −3.80, 95% CI: −6.59 to −1.02; p = 0.007). There were no significant differences in the incidences of pulmonary infection (OR = 0.60, 95% CI: 0.32–1.12; p = 0.11), urinary tract infection (OR = 1.30, 95% CI: 0.55–3.08; p = 0.55), liver failure (OR = 0.54, 95% CI: 0.23–1.24; p = 0.15), and postoperative mortality (OR = 0.69, 95% CI: 0.26–1.83; p = 0.46). Conclusion: Given its positive impact on postoperative complications and the tendency to shorten the length of hospital stay, perioperative immunonutrition should be encouraged in patients undergoing hepatectomy.

Peptides with recognition, assembly, various activities exhibit strong power and application prospects in sensing, material science, biomedicine. However, peptide-based sensing and expanding application is still at an early stage. Herein, a peptide-based sensing and logic system was developed for highly sensitive and selective detection of Pb2+ and implementation of logic operations. Our Pb2+ assay method was ultra-rapid (less than 1 min), direct, simple with detection limit of 0.75 nM. Flexibility and scalability of peptide-based solution system facilitated the execution of sensing and logic operations from simple to complex. This research will not only inspire discovery and comprehensive applications (such as sensing and assembly) of more functional peptides, but also provide more opportunities for development and design of peptide-based systems and molecular information technologies.

In this paper, we investigate a multi-objective optimal design of a tuned vibration absorber for a two degrees-of-freedom linear system, in which we take white Gaussian noise as the excitation. We use the simple cell mapping method to obtain solutions to the multi-objective optimization problem. We optimize tuned vibration absorbers in two different configurations. As our objective, we take various features of the response of the power spectrum density function. Our results show that the primary mass vibration with the optimally designed absorber has a lower peak power spectrum value. In addition, the two natural frequencies of the optimized system are further apart than in the non-optimized system, which implies that the absorber has a wider effective region in the frequency domain.

To study the influence of the car cut-in situation on the stable car following behavior of following cars, a total of 36 male participants were recruited for real road experiments on the highway. Vehicle motion state and drivers’ eye movement data of the following cars were recorded using millimeter wave radar and eye tracker, respectively. Statistical methods were used to analyze the cutting-in position, velocity and drivers’ reaction time, as well as gaze distribution. The study found that more than 91% of following car drivers generally choose to continue driving in the current lane. Besides, drivers’ main attention focuses on the front view, paying more attention to the direction where the cut-in car emerged. Drivers respond quickly than the stable car following process. Research conclusion can be used to guide novice drivers to observe cut-in car and take measures properly.

Analysis of nonlinear dynamical systems including finding equilibrium states and stability boundaries often leads to a problem of finding zeros of vector functions. However, finding all the zeros of a set of vector functions in the domain of interest is quite a challenging task. This paper proposes a zero finding algorithm that combines the cell mapping methods and the subdivision techniques. Both the simple cell mapping (SCM) and generalized cell mapping (GCM) methods are used to identify a covering set of zeros. The subdivision technique is applied to enhance the solution resolution. The parallel implementation of the proposed method is discussed extensively. Several examples are presented to demonstrate the application and effectiveness of the proposed method. We then extend the study of finding zeros to the problem of finding stability boundaries of potential fields. Examples of two and three dimensional potential fields are studied. In addition to the effectiveness in finding the stability boundaries, the proposed method can handle several millions of cells in just a few seconds with the help of parallel computing in graphics processing units (GPUs).

In this article the Parallel Simple Cell Mapping (pSCM) is presented, a novel method for the numerical treatment of multi-objective optimization problems. The method is a parallel version of the simple cell mapping (SCM) method which also integrates elements from subdivision techniques. The classical SCM method exhibits nice properties for parallelization, which is used to speed up computations significantly. These statements are underlined on some classical benchmark problems with up to 10 decision variables and up to 5 objectives and provide comparisons to sequential SCM. Further, the method is applied on illustrative examples for which the method is also able to find the set of local optimal solutions efficiently, which is interesting in multi-objective multi-modal optimization, as well as the set of approximate solutions. The latter is of potential interest for the decision maker since it comprises an extended set of possible realizations of the given problem.

To improve the precision of short-term traffic flow prediction and to enhance the accuracy of programming as well as of traffic flow management, a novel short-term traffic flow prediction m...

Transient identification of condition monitoring data in nuclear reactor is important for system health assessment. Conventionally, the operating transients are correlated with the pre-designed ones by human operators during operations. However, due to necessary conservatism and significant differences between the operating and pre-designed transients, it has been less effective to manually identify transients, that usually contribute to different system degradation modes. This paper proposes a deep learning-based unsupervised representation clustering method for automatic transient pattern recognition based on the on-site condition monitoring data. Sample entropy is used as indicator for transient extraction, and a pre-training stage is implemented using an auto-encoder architecture for learning high-level features. An iterative representation clustering algorithm is further proposed to enhance the clustering effects, where a novel distance metric learning strategy is integrated. Experiments on a real-world nuclear reactor condition monitoring dataset validate the effectiveness and superiority of the proposed method, which provides a promising tool for transient identification in the real industrial scenarios. This study offers a new perspective in exploring unlabeled data with deep learning, and the end-to-end implementation scheme facilitates applications in the real nuclear industry.

In naturalistic driving environment, lane change is a necessary, frequent operation, and causes traffic accidents and fatalities. Current lane-change driver assistance system uses turn signals as start time; however, drivers show lane-change intention before turning on the signals. To identify lane-change intention, a driving experiment was designed and conducted, during which eye movement characteristics were recorded from 16 drivers. Time period data from 5 s before changing lanes and 5 s in lane-keeping period were analysed. Saccade speed, eye–head coordination mode, and other parameters were confirmed to be significantly different between two periods. Based on area division and Markov theory, attributes related to gaze transition were obtained, including one- and two-step gaze transition probabilities, main gaze transition paths, and regional gaze probabilities. In summary, all features extracted from eye movement characteristics, gaze transition paths, and gaze areas demonstrate that visual attention is more dispersed during the lane-change intention period. These parameters also lay the foundation for lane-change intention recognition systems and make lane change safer.

This topic is intended to describe and study a system, which is taking Jilin University as an example, based on the system feasibility and necessity of campus applications, this paper analyzes and investigates the problems existing in the process of functional design, application and development. So we propose a new system to satisfy the needs of students and teachers: including a learning-oriented multi-function mobile application, mainly about using Android Studio to build application interface, combined with Myeclipse, tomcat and MySQL database. The system equip with positioning, camera and other hardware plus web pages on the windows platform as an auxiliary system. After about 400 teachers and students using over 2 months, because of its good user experience and characteristics of learning, we gain lots of praise, now we are planning to promote it gradually.

This paper presents a numerical algorithm tuning aircraft landing gear control system with three objectives, including reducing relative vibration, reducing hydraulic strut force and controlling energy consumption. Sliding mode control is applied to the vibration control of a simplified landing gear model with uncertainty. A two-stage generalized cell mapping algorithm is applied to search the Pareto set with gradient-free scheme. Drop test simulations over uneven runway show that the vibration and force interaction can be considerably reduced, and the Pareto optimum form a tight range in time domain.

Pressure release tank is a key component of nuclear power plant safeguard. Evaluating the fluid thrust force against nearby structures from high pressure and high temperature flow jet under postulated accidents is an essential task for nuclear system design and safety estimation. In this work, flow jet impingement from pressure release tank to nearby building roof is computed via a two-stage strategy. First, the 1-dimensional RELAP5 code is applied to estimate thermal-hydraulic conditions at pressure release tank outlet. The thermal-hydraulic computational model includes key components of pressure release tank and its connection to the pressurizer. Based upon the thermal-hydraulic estimation at the pressure release tank outlet, detailed computational fluid dynamics (CFD) simulation is performed with full considerations of how flow thrust is applied on nearby structures. The two-stage computational strategy provides a practical paradigm of fluid thrust force estimation for industrial applications.

Focusing properties of linearly polarized Lorentz–Gauss beam with one on-axis optical vortex was investigated by vector diffraction theory. Results show that the focal pattern can be altered considerably by charge number of the optical vortex and the beam parameters. Many novel focal patterns may occur, such as dark hollow focus, multiple-peak focal pattern, and dark hollow focus chain. For certain beam parameter, the focal pattern changes more remarkably in the direction perpendicular to the incident polarized direction than that in polarized direction. Especially, there is one clear relation between the intensity distributions along the direction perpendicular to the polarized direction and the charge number of the optical vortex, which may be used as one measurement method of charge number.

The clothing containing phase change material (PCM) with function of absorbing the body-released heat has wide applications. In this paper, a novel protective clothing based phase change material was investigated. The results show that PCM has suitable melting temperature, large heat flow, stability after repeating applications, and it is convenient for application in cooling. Moreover, the manufacturing process has a great affect on the property of the titled material. The above inorganic composite was selected to prepare the temperature self-operating protective clothing, which can efficiently lighten the demic thermal stresses at high and low temperatures.

This paper presents an experimental study of robustness of multi-objective optimal sliding mode control, which is designed in a previous study. Inertial and stiffness uncertainties are introduced to a two degrees-of-freedom (DOF) under-actuated rotary flexible joint system. A randomly selected design from the Pareto set of multi-objective optimal sliding mode controls is used in the experiments. Three indices are introduced to evaluate the performance variation of the tracking control in the presence of uncertainties. We have found that the multi-objective optimal sliding mode control is quite robust against the inertial and stiffness uncertainties in terms of maintaining the stability and delivering satisfactory tracking performance as compared to the control of the nominal system, even when the uncertainty is not a small quantity. Furthermore, we have studied the effect of upper bounds of the model estimation error on the stability of the closed-loop system.

Background Only a few randomized trials have analyzed the clinical outcomes of elderly ST-segment elevation myocardial infarction (STEMI) patients (≥ 75 years old). Therefore, the best reperfusion strategy has not been well established. An observational study focused on clinical outcomes was performed in this population. Methods Based on the national registry on STEMI patients, the in-hospital outcomes of elderly patients with different reperfusion strategies were compared. The primary endpoint was defined as death. Secondary endpoints included recurrent myocardial infarction, ischemia driven revascularization, myocardial infarction related complications, and major bleeding. Multivariable regression analysis was performed to adjust for the baseline disparities between the groups. Results Patients who had primary percutaneous coronary intervention (PCI) or fibrinolysis were relatively younger. They came to hospital earlier, and had lower risk of death compared with patients who had no reperfusion. The guideline recommended medications were more frequently used in patients with primary PCI during the hospitalization and at discharge. The rates of death were 7.7%, 15.0%, and 19.9% respectively, with primary PCI, fibrinolysis, and no reperfusion (P < 0.001). Patients having primary PCI also had lower rates of heart failure, mechanical complications, and cardiac arrest compared with fibrinolysis and no reperfusion (P < 0.05). The rates of hemorrhage stroke (0.3%, 0.6%, and 0.1%) and other major bleeding (3.0%, 5.0%, and 3.1%) were similar in the primary PCI, fibrinolysis, and no reperfusion group (P > 0.05). In the multivariable regression analysis, primary PCI outweighs no reperfusion in predicting the in-hospital death in patients ≥ 75 years old. However, fibrinolysis does not. Conclusions Early reperfusion, especially primary PCI was safe and effective with absolute reduction of mortality compared with no reperfusion. However, certain randomized trials were encouraged to support the conclusion.

A simplified theoretical model about the impact energy and maximum deflection was acquired based on the principle of virtual work while clamped beam subjected to low velocity impact. Finite element simulations have been undertaken to further understand the response of the clamped beam, the results show that: A good agreement has been obtained between theoretical model and numerical results, the dynamic response of the clamped beam is divided into four stages: elastic fluctuation, the overall structural response, unloading response and free vibration, the formation of plastic hinge occurred in the overall structural response stage.

Accurate prediction of driving behaviour is essential for an active safety system to ensure driver safety. A model for predicting lane-changing behaviour is developed from the results of naturalistic on-road experiment for use in a lane-changing assistance system. Lane changing intent time window is determined via visual characteristics extraction of rearview mirrors. A prediction index system for left lane changes was constructed by considering drivers' visual search behaviours, vehicle operation behaviours, vehicle motion states, and driving conditions. A back-propagation neural network model was developed to predict lane-changing behaviour. The lane-change-intent time window is approximately 5 s long, depending on the subjects. The proposed model can accurately predict drivers' lane changing behaviour for at least 1.5 s in advance. The accuracy and time series characteristics of the model are superior to the use of turn signals in predicting lane-changing behaviour.

Focal shaping plays an important role in many optical focusing systems. In this paper, the focusing properties of linearly polarized Lorentz beam with sine-azimuthal variation wavefront were investigated. Simulation results show that the focal pattern can be altered considerably by the beam parameters and the phase parameter that indicates the phase change frequency on increasing azimuthal angle. And some novel focus shape may appear, including multiple-peak focal pattern, wheel focal pattern. And some optical gradient force distributions were also given to show that the focusing properties of this kind of Lorentz beams may be used to construct tunable optical traps, which may pave the way for application of laser diode in tweezers technique.

It is generally difficult to design feedback controls of nonlinear systems with time delay to meet time domain specifications such as rise time, overshoot, and tracking error. Furthermore, these time domain specifications tend to be conflicting to each other to make the control design even more challenging. This paper presents a cell mapping method for multi-objective optimal feedback control design in time domain for a nonlinear Duffing system with time delay. We first review the multi-objective optimization problem and its formulation for control design. We then introduce the cell mapping method and a hybrid algorithm for global optimal solutions. Numerical simulations of the PID control are presented to show the features of the multi-objective optimal design.

The college library must be consolidated and the role of traditional paper-based information under the premise of information superiority, quickly adapt to the requirements of the development of network information in order to achieve the accuracy of book knowledge and information services, more focused and effective as a starting point, the formulation of development strategy, adjustment of service and thus achieve services from traditional literature to the literature and the transformation of modern information integrated services, expanding the scope of services, rich content services to meet the teachers and students, or special objects to the library information and knowledge and information needs of a variety of service products.

A Constant-gm CMOS Operational amplifier with Rail-to-Rail input common-mode voltage range has been designed. The input stage is based on two pairs of single p-channel differential pairs and two identical n-channel source followers as DC level shifters, which realizes rail-to-rail input swing. To attain a constant-gm over the whole common-mode input range, the compensation circuit which is based on processing signal currents has also been designed. The technique is universal in that the constant-gm can be obtained independent of I-V characteristic and is compatible with deep submicron CMOS devices. Using BSIM3v3 model of a standard 0.6µm CMOS process, simulation result shows that the input /output swing of the op amp circuit is rail-to-rail. The op-amp achieves open-loop gain of 113.57dB, unity–gain bandwidth of 11.9MHz and phase margin of 53°.