Nanjing Institute of Technology

BACKGROUND: Streptococcus suis serotype 2 (S. suis 2, SS2) is a major zoonotic pathogen that causes only sporadic cases of meningitis and sepsis in humans. Most if not all cases of Streptococcal toxic shock syndrome (STSS) that have been well-documented to date were associated with the non-SS2 group A streptococcus (GAS). However, a recent large-scale outbreak of SS2 in Sichuan Province, China, appeared to be caused by more invasive deep-tissue infection with STSS, characterized by acute high fever, vascular collapse, hypotension, shock, and multiple organ failure. METHODS AND FINDINGS: We investigated this outbreak of SS2 infections in both human and pigs, which took place from July to August, 2005, through clinical observation and laboratory experiments. Clinical and pathological characterization of the human patients revealed the hallmarks of typical STSS, which to date had only been associated with GAS infection. Retrospectively, we found that this outbreak was very similar to an earlier outbreak in Jiangsu Province, China, in 1998. We isolated and analyzed 37 bacterial strains from human specimens and eight from pig specimens of the recent outbreak, as well as three human isolates and two pig isolates from the 1998 outbreak we had kept in our laboratory. The bacterial isolates were examined using light microscopy observation, pig infection experiments, multiplex-PCR assay, as well as restriction fragment length polymorphisms (RFLP) and multiple sequence alignment analyses. Multiple lines of evidence confirmed that highly virulent strains of SS2 were the causative agents of both outbreaks. CONCLUSIONS: We report, to our knowledge for the first time, two outbreaks of STSS caused by SS2, a non-GAS streptococcus. The 2005 outbreak was associated with 38 deaths out of 204 documented human cases; the 1998 outbreak with 14 deaths out of 25 reported human cases. Most of the fatal cases were characterized by STSS; some of them by meningitis or severe septicemia. The molecular mechanisms underlying these human STSS outbreaks in human beings remain unclear and an objective for further study.

In recent years, it is remarkable to see the increasing number of studies related to the theory and application of fractional order controller (FOC), specially <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PI</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¿</sup> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¿</sup> controller, in many areas of science and engineering. Research activities are focused on developing new analysis and design methods for fractional order controllers as an extension of classical control theory. In this paper, a new tuning method for fractional order proportional and derivative ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PD</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¿</sup> ) or FO-PD controller is proposed for a class of typical second-order plants. The tuned FO-PD controller can ensure that the given gain crossover frequency and phase margin are fulfilled, and furthermore, the phase derivative w. r. t. the frequency is zero, i.e., the phase Bode plot is flat at the given gain crossover frequency. Consequently, the closed-loop system is robust to gain variations. The FOC design method proposed in the paper is practical and simple to apply. Simulation and experimental results show that the closed-loop system can achieve favorable dynamic performance and robustness.

The development of clean and efficient energy conversion and storage systems is becoming increasingly vital as a result of accelerated global energy consumption. Solid oxide fuel cells (SOFCs) as one key class of fuel cells have attracted much attention, owing to their high energy conversion efficiency and low emissions. However, some serious problems appeared because of the scorching operating temperatures of SOFCs (800–1000 °C), such as poor thermomechanical stability and difficult sealing, resulting in a short lifespan and high cost of SOFCs. Therefore, lowering the operating temperature of SOFCs to mid-range and even low range has become one of the main goals for SOFC development in the recent years. Looking for new cathode materials with high electrocatalytic activity and robust stability at relatively low temperatures is one of the essential requirements for intermediate-to-low-temperature SOFCs (ILT-SOFCs). During the past 15 years, we put considerable efforts into the development of alternative cathode materials for ILT-SOFCs. In this review, we give a summary of our progress from such efforts. We first summarize several strategies that have been adopted for developing cathode materials with high activity and durability toward reducing operating temperatures of SOFCs. Then, our new ideas and progress on cathode development with respect to activity and stability are provided. Both the cathodes of oxygen-ion-conducting SOFCs and protonic-conducting SOFCs are discussed. In the end, we outline the opportunities, challenges, and future approaches for the development of cathodes for ILT-SOFCs.

The paper deals with the evaluation of Sommerfeld integrals that appear in the rigorous analysis of radiating objects embedded in a layered medium. The discrete images of a horizontal electric dipole above or within a multilayered medium, can be obtained by numerically approximating the kernel in a Sommerfeld type integral, using a series of exponential functions with different complex coefficients. The distance limitation of the image theory expression is eliminated by cooperating the contribution of the surface waves. The validity of the image theory is examined by the method of numerical integration.

Ultra-Wide-Band (UWB) was recognized as its great potential in constructing accurate indoor position system (IPS). However, indoor environments were full of complex objects, the signals might be reflected by the obstacles. Compared with the Line-Of-Sight (LOS) signal, the signal transmitting path delay contained in None-Line-Of-Sight (NLOS) signal would induce positive distance errors and position errors. Before employing ranging information from the channels to calculate the position, LOS/NLOS classification or identification was necessary for selecting the “clean” channels. In conventional method, features extracted from the UWB channel impulse response (CIR) or some other signal properties were employed as the input vector of the machine learning methods, e.g. Support Vector Machine (SVM), Multi-layer Perception (MLP). Deep learning methods represented by Convolutional neural network (CNN) and Long Short-Term Memory (LSTM) had performed superior performance in dealing with time series data classification. In this pap er, deep learning method CNN-LSTM was employed in the UWB NLOS/LOS signal classification. UWB CIR data was directly input to the CNN-LSTM. CNN was employed for exploring and extracting the features automatically, and then, the CNN outputs were fed into the LSTM for classification. Open source datasets collected from seven different sites were employed in the experiments. Classification accuracy of CNN-LSTM with different settings was compared for analyzing the performance. The results showed that CNN-LSTM obtained stat e-of-art classification performance.

Solid oxide fuel cells (SOFCs) directly convert chemical energy that is stored in a wide range of fuels into direct current electricity, with high efficiency and low emissions, via a series of electrochemical reactions at elevated operating temperatures (generally 400–1000 °C). During such an energy conversion process, the properties of electrolyte materials determine the working principle and operating temperature of the SOFC. When considering the cost and stability, lowering the operating temperature is critical, and this has become one of the developing trends in SOFC research. The key point for realizing a reduction in operating temperature is to maintain low ohmic resistance of the electrolyte and low polarization resistance of the electrodes. In practice, the mechanical and chemical stability of the electrolyte is also a big concern. According to their differences in ion conduction mechanisms, there are three main types of electrolyte material available, namely, oxygen ion-conducting, proton-conducting, and dual ion-conducting electrolytes. In this review, we give a comprehensive summary of the recent advances in the development of these three types of electrolyte material for intermediate-temperature SOFCs. Both conductivity and stability are emphasized. In conclusion, the current challenges and future development prospects are discussed.

This technical note investigates the problem of extended dissipative finite-time control for Markov jump systems (MJSs) with cyber-attacks and actuator failures. A probabilistic event-triggered mechanism (PETM) is proposed to relieve the communication burden by exploiting both the pattern variation of triggering thresholds and the time-varying characteristic of transmission delays. To characterize the actual control inputs, a stochastic actuator failure model (SAFM) is established using a random variable of any discrete-time distribution over [0, 1]. First, based on the PETM and SAFM, static output-feedback controllers are devised, which may not switch with the system synchronously. Then, novel sufficient conditions with less conservatism are obtained to achieve the extended dissipative finite-time control performance of the closed-loop system under admissible cyber-attacks and actuator failures. Furthermore, controller gains with nonconvex constraints are calculated with the aid of a newly proposed lemma. Finally, an application oriented example is provided to verify the effectiveness and superiority of the proposed results.

Environment has significant effects on the water absorption of concrete materials. This paper presents an experimental study of the influence of water absorption on the durability of concrete materials. A detailed analysis is also presented in order to establish useful relationship between them. Concrete specimens of different water absorption were prepared through different curing conditions, and results indicated that curing condition can significantly affect the surface water absorption. SEM photos also showed that different curing conditions caused different microstructure. After 28-days curing, compressive strength, permeability, sulfate attack, and chloride ion diffusion of concrete samples were investigated. As a result, both of surface sorptivity and internal sorptivity have no clear relationship with compressive strength. Results obtained also showed that only surface water absorption related to the performance of concrete including permeability, sulfate attack, and chloride ion diffusion. In addition, both impermeability and resistance to sulfate attack were linearly associated with surface sorptivity, and both correlation coefficients were not less than 0.9. Furthermore, chloride ion diffusion coefficient has exponent relation to surface water absorption with higher correlation coefficient. However, no apparent relationship was found between internal water absorption and durability like impermeability, resistance to sulfate attack, and chloride ion diffusion.

A fast reliable computational quality predictor is eagerly desired in practical image/video applications, such as serving for the quality monitoring of real-time coding and transcoding. In this paper, we propose a new perceptual image quality assessment (IQA) metric based on the human visual system (HVS). The proposed IQA model performs efficiently with convolution operations at multiscales, gradient magnitude, and color information similarity, and a perceptual-based pooling. Extensive experiments are conducted using four popular large-size image databases and two multiply distorted image databases, and results validate the superiority of our approach over modern IQA measures in efficiency and efficacy. Our metric is built on the theoretical support of the HVS with lately designed IQA methods as special cases.

The influences of particle breakage on the position of the critical state line (CSL) were systematically investigated in this paper through a series of large-scale triaxial compression tests on Tacheng rockfill material (TRM). It was found that the critical-state stress ratio of TRM (i.e., the gradient of the CSL in the p−q space) was approximately regarded as a constant. In the e−logp space, the CSL of TRM descended with a decrease in the initial void ratio, whereas the gradient of the CSL was constant. A procedure was established for evaluating the critical state point at a same particle breakage, which comprised the breakage critical state line (BCSL). An increase of the particle breakage led to not only a vertical translation but also a rotation on the BCSL of TRM in the e−logp space, which was similar to the observation of Dog’s Bay sand. Consequently, the initial gradation (or the corresponding initial void ratio) was the dominant factor that affected the position of the CSL of TRM in the e−logp space.

This article investigates the finite-time secure filter design of fuzzy switched cyber-physical systems equipped with a resource-constraint network that may undergo false data injection attacks (FDIAs). To strike a higher level balance between the resource consumption and filtering performance, a multidomain probabilistic event-triggered mechanism (MDPETM) is initially developed. And the mode mismatched phenomenon between the filter and the system is characterized through a delayed switching signal. Based on the MDPETM and a virtual delay partitioning approach, fuzzy mismatched secure filters are first devised whose modes could differ from the system. Then, filter-mode-dependent Lyapunov functionals are created to obtain new sufficient criteria such that the filtering error achieves finite-time boundedness with extended dissipativity subject to admissible FDIAs. The filter gains are obtained by solving a set of convex optimization problems. Finally, an application-oriented example is employed to test the effectiveness and advantages of the proposed results.

In this paper, a single-phase grid-connected transformerless photovoltaic inverter for residential application is presented. The inverter is derived from a boost cascaded with a buck converter along with a line frequency unfolding circuit. Due to its novel operating modes, high efficiency can be achieved because there is only one switch operating at high frequency at a time, and the converter allows the use of power MOSFET and ultrafast reverse recovery diode. It also features a robust structure because the phase leg does not have a shoot-through issue. This paper begins with theoretical analysis and modeling of this boost-buck converter-based inverter. And the model indicates that small boost inductance will lead to an increase in the resonant pole frequency and a decrease in the peak of Q, which results in easier control and greater stability. Thus, interleaved multiple phases structure is proposed to have small equivalent inductance; meanwhile, the ripple can be decreased, and the inductor size can be reduced as well. A two-phase interleaved inverter is then designed accordingly. Finally, the simulation and experiment results are shown to verify the concept and the tested efficiency under 1-kW power condition is up to 98.5%.

A novel fuel cell device based on integrating the Schottky junction effect with the electrochemical principle is designed, constructed, and verified through experiments. It is found that the Schottky junction has a significant effect on the greatly enhanced device performance, and the fuel cell device incorporating the Schottky junction effect reaches a power output of 1000 mW cm−2 at 550 °C. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Abstract Catastrophically mechanical failure of soft self-healing materials is unavoidable due to their inherently poor resistance to crack propagation. Here, with a model system, i.e., soft self-healing polyurea, we present a biomimetic strategy of surpassing trade-off between soft self-healing and high fracture toughness, enabling the conversion of soft and weak into soft yet tough self-healing material. Such an achievement is inspired by vascular smooth muscles, where core-shell structured Galinstan micro-droplets are introduced through molecularly interfacial metal-coordinated assembly, resulting in an increased crack-resistant strain and fracture toughness of 12.2 and 34.9 times without sacrificing softness. The obtained fracture toughness is up to 111.16 ± 8.76 kJ/m 2 , even higher than that of Al and Zn alloys. Moreover, the resultant composite delivers fast self-healing kinetics (1 min) upon local near-infrared irradiation, and possesses ultra-high dielectric constants (~14.57), thus being able to be fabricated into sensitive and self-healing capacitive strain-sensors tolerant towards cracks potentially evolved in service.

Abstract Heteroatom doping engineering is desirable in tuning crystal structures and electrical properties, which is considered an opportunity to further develop microwave absorption materials. However, the competition mechanism and priority among doped atoms have not been revealed, which are insufficient to guide the most reasonable dielectric coupling model and design high‐performance absorbers. In this work, based on in situ N and O, ex situ S is introduced through external thermal driving, leading to fierce competition among anions. Specifically, S atoms replace pyrrole N, drive out lattice O, and create O vacancies, bringing more extensive local charge redistribution and stronger electron interaction, thus activating the defect‐induced polarization (3–6 times higher than conduction loss) in the middle/high‐frequency region. Therefore, the effective absorption bandwidth (EAB) of 9.03 GHz and the minimum reflection loss ( RL min ) of −64.05 dB at a filling rate of 10 wt.% are obtained, which improves the record of carbon absorbers as reported. Through macro‐designs, i.e., multi‐layer gradient metamaterial, or utilizing other advantages, e.g., cost‐effective, stable chemical properties and wide‐angle absorption, porous carbon may possess a great application prospect in the naval field.

Recently, there have been increasing interests in inferring mirco-expression from facial image sequences. Due to subtle facial movement of micro-expressions, feature extraction has become an important and critical issue for spontaneous facial micro-expression recognition. Recent works used spatiotemporal local binary pattern (STLBP) for micro-expression recognition and considered dynamic texture information to represent face images. However, they miss the shape attribute of face images. On the other hand, they extract the spatiotemporal features from the global face regions while ignore the discriminative information between two micro-expression classes. The above-mentioned problems seriously limit the application of STLBP to micro-expression recognition. In this paper, we propose a discriminative spatiotemporal local binary pattern based on an integral projection to resolve the problems of STLBP for micro-expression recognition. First, we revisit an integral projection for preserving the shape attribute of micro-expressions by using robust principal component analysis. Furthermore, a revisited integral projection is incorporated with local binary pattern across spatial and temporal domains. Specifically, we extract the novel spatiotemporal features incorporating shape attributes into spatiotemporal texture features. For increasing the discrimination of micro-expressions, we propose a new feature selection based on Laplacian method to extract the discriminative information for facial micro-expression recognition. Intensive experiments are conducted on three availably published micro-expression databases including CASME, CASME2 and SMIC databases. We compare our method with the state-of-the-art algorithms. Experimental results demonstrate that our proposed method achieves promising performance for micro-expression recognition.

Abstract Realizing ultra-wideband absorption, desirable attenuation capability at high temperature and mechanical requirements for real-life applications remains a great challenge for microwave absorbing materials. Herein, we have constructed a porous carbon fiber/polymethacrylimide (CP) structure for acquiring promising microwave absorption performance and withstanding both elevated temperature and high strength in a low density. Given the ability of porous structure to induce desirable impedance matching and multiple reflection, the absorption bandwidth of CP composite can reach ultra-wideband absorption of 14 GHz at room temperature and even cover the whole X-band at 473 K. Additionally, the presence of imide ring group in polymethacrylimide and hard bubble wall endows the composite with excellent heat and compressive behaviors. Besides, the lightweight of the CP composite with a density of only 110 mg cm −3 coupled with high compressive strength of 1.05 MPa even at 453 K also satisfies the requirements in engineering applications. Compared with soft and compressible aerogel materials, we envision that the rigid porous foam absorbing material is particularly suitable for environmental extremes.

As a favorable energy storage component, lithium-ion (Li-ion) battery has been widely used in the battery energy storage systems (BESS) and electric vehicles (EV). Data driven methods estimate the battery state-of-health (SOH) with the features extracted from the measurement. However, excessive features may reduce the estimation accuracy and also increases the human labor in the lab. By proposing an optimization process with nondominated sorting genetic algorithm II (NSGA-II), this article is able to establish a more efficient SOH estimator with support vector regression (SVR) and the short-term features from the current pulse test. NSGA-II optimizes the entire process of establishing a SOH estimator considering both the measurement cost of the feature and the estimation accuracy. A series of nondominated solutions are obtained by solving the multiobjective optimization problem, which also provides more flexibility to establish the SOH estimator at various conditions. The degradation features in this article are the knee points at the transfer instants of the voltage in the short-term current pulse test, which is fairly convenient and easy to be obtained in real applications. The proposed method is validated on the measurement from two LiFePO4/C batteries aged with the mission profile providing the primary frequency regulation (PFR) service to the grid.

As vehicles playing an increasingly important role in people's daily life, requirements on safer and more comfortable driving experience have arisen. Connected vehicles (CVs) can provide enabling technologies to realize these requirements and have attracted widespread attentions from both academia and industry. These requirements ask for a well-designed computing architecture to support the Quality-of-Service (QoS) of CV applications. Computation offloading techniques, such as cloud, edge, and fog computing, can help CVs process computation-intensive and large-scale computing tasks. Additionally, different cloud/edge/fog computing architectures are suitable for supporting different types of CV applications with highly different QoS requirements, which demonstrates the importance of the computing architecture design. However, most of the existing surveys on cloud/edge/fog computing for CVs overlook the computing architecture design, where they (i) only focus on one specific computing architecture and (ii) lack discussions on benefits, research challenges, and system requirements of different architectural alternatives. In this article, we provide a comprehensive survey on different architectural design alternatives based on cloud/edge/fog computing for CVs. The contributions of this article are: (i) providing a comprehensive literature survey on existing proposed architectural design alternatives based on cloud/edge/fog computing for CVs, (ii) proposing a new classification of computing architectures based on cloud/edge/fog computing for CVs: computation-aided and computation-enabled architectures, (iii) presenting a holistic comparison among different cloud/edge/fog computing architectures for CVs based on functional requirements of CV systems, including advantages, disadvantages, and research challenges, (iv) presenting a holistic overview on the design of CV systems from both academia and industry perspectives, including activities in industry, functional requirements, service requirements, and design considerations, and (v) proposing several open research issues of designing cloud/edge/fog computing architectures for CVs.

We report a Mg alloy Mg-2.2Nd-0.1Zn-0.4Zr (wt.%, denoted as JDBM-2) showing great potential in clinical vascular stent application by integrating the advantages of traditional medical stainless steel and polymer. This alloy exhibits high yield strength and elongation of 276 ± 6 MPa and 34.3 ± 3.4% respectively. The JDBM-2 with a stable degradation surface results in a highly homogeneous degradation mechanism and long-term structural and mechanical durability. In vitro cytotoxicity test of the Mg extract via human vascular endothelial cells (HUVECs) indicates that the corrosion products are well tolerated by the tested cells and potentially negligible toxic effect on arterial vessel walls. This alloy also exhibits compromised foreign body response (FBR) determined by human peripheral blood derived macrophage adhesion, foreign body giant cell (FBGC) formation and inflammatory cytokine and chemokine secretion. Finally, vascular stents manufactured from the JDBM-2 were implanted into rabbits for long-term evaluation. The results confirm excellent tissue compatibility and up to 6-month structural and mechanical integrity of the stent in vivo. Thus, the JDBM-2 stent with up to 6-month structural and mechanical integrity and excellent tissue compatibility represents a major breakthrough in this field and a promising alternative to traditional medical stainless steel and polymer for the clinical application.