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A driver’s driving performance and behavior are highly related to their cognitive workload, which corresponds as well to the complexity of their driving scenarios. Their performance might be impacted when driving through downtown on a rainy night, compared with driving on a remote countryside road on a sunny afternoon. Therefore, advanced intelligent vehicles should have the ability to assess the complexity level of the current driving scenario and therefore understand a driver’s cognitive workload to prevent potential hazard situations. In this study, environmental information extracted from the OpenStreetMap (OSM) domain, surrounding vehicle information derived from the video, and prior environmental knowledge such as weather, time and driving location are employed to explore the capability of classifying the complexity level of driving scenarios. A 0.855 F1-score was achieved using the random forest algorithm and combining all features extracted from the environmental information. Conclusions with potential benefits of the development of intelligent vehicles and future study directions are also discussed.

The wireless devices in cyber-physical systems (CPS) play a primary role in transporting the information flows within such systems. Deploying wireless systems in industry has many advantages due to lower cost, ease of scale, and flexibility due to the absence of cabling. However, industrial wireless deployments in various industrial environments require having the proper models for industrial wireless channels. In this work, we propose and assess an algorithm for characterizing measured channel impulse response (CIR) of time-varying wireless industrial channels. The proposed algorithm performs data processing, clustering, and averaging for measured CIRs. We have deployed a dynamic time warping (DTW) distance metric to measure the similarity among CIRs. Then, an affinity propagation (AP) machine learning clustering algorithm is deployed for CIR grouping. Finally, we obtain the average CIR of various data clusters as a representation for the cluster. The algorithm is then assessed over industrial wireless channel measurements in various types of industrial environments. The goal of this work is to have a better industrial wireless channels representation that results in a better recognition to the nature of industrial wireless communications and allows for building more effective wireless devices and systems.

We report on the synthesis of Co- and Fe-based bimetallic nanocatalysts embedded in mesoporous carbon and g-C3N4 nanosheets (denoted as Co3O4/Fe3O4/mC@g-C3N4) for selectively simultaneous determination of ascorbic acid (AA), dopamine acid (DA), and uric acid (UA). These electrocatalysts consisting of bimetallic Co-Fe alloy nanoparticles encapsulated in N-doped carbon matrix were prepared via pyrolysis of Co/Fe-MOFs after grinding with high amounts of melamine. Chemical/crystal structures suggest high contents of mesoporous carbon in calcinated Co3O4/Fe3O4/mC nanocomposites, which exhibited enhanced electrocatalytic activity toward small biomolecules. The intrinsic performances of Co/Fe-MOFs with large specific surface area and regular nodes in the two-dimensional nanostructured g-C3N4 nanosheets endowed the as-prepared series of Co3O4/Fe3O4/mC@g-C3N4 nanocomposites with remarkable electrocatalytic activities and high adsorption ability toward oxidation of AA, DA, and UA. The developed biosensors also showed long-term stability and high selectivity for targeted analytes, with satisfactory results on actual samples in human urine. The results indicate that the as-synthesized Co3O4/Fe3O4/mC@g-C3N4 nanostructure exhibits good electrocatalytic activity and potential applications in clinical diagnosis and biosensing.

Background Biomarker-targeted molecular imaging holds promise for early detection of pancreatic cancer. The aim of this study was to design and evaluate a plectin-1 targeted multi-functional nanoparticle probe for pancreatic cancer imaging. Methods 1,2-Distearoyl-sn-glycero-3-phosphoethanolamine-N-amino(polyethylene glycol) (DSPE-PEG-NH2)-modified superparamagnetic iron oxide (Fe3O4) nanoparticles (SPION) were conjugated with plectin-1 antibody and/or Cy7 to create the multi-functional targeted nanoparticle targeted probe (Plectin-SPION-Cy7) or non-targeted probe (SPION-Cy7). Pancreatic carcinoma cell lines expressing plectin-1 were cultured with the targeted or control probes and then were imaged using confocal laser scanning microscopy and magnetic resonance imaging (MRI). Accumulations of the nanoparticles in pancreatic tumor xenografted mice were determined by MRI and fluorescence imaging. Results In vitro optical imaging and MRI showed that the targeted nanoparticles were highly accumulated in MIAPaCa2 and XPA-1 carcinoma cells but not in non-carcinoma MIN6 cells, which was further confirmed by Prussian blue staining. In vivo MRI showed a significant T2 signal reduction. Prussian blue staining further confirmed that the plectin-1 targeted nanoparticles were highly accumulated in the tumor mass but not in normal pancreatic tissues, or in the liver and kidney, and few nanoparticles were observed in the tumors of mice injected with SPION-Cy7. Conclusions Our data demonstrate that plectin-1 targeted fluorescence and MR dual-functional nanoparticle can visualize pancreatic cancer, and it has great potential to be used with various imaging devices for pancreatic cancer detection., Highlights • We designed a plectin-1 targeted dual-modality nanoparticle (Plectin-SPION-Cy7). • The targeted nanoparticles were highly accumulated in carcinoma cells but not in non-carcinoma cells. • Plectin-1 targeted dual-functional nanoparticle has great potential in pancreatic cancer detection. Molecular-based radiographic tests hold the promise to help precisely identifying pancreatic malignant lesions and their precursors at early stages. Previous studies showed that plectin-1 highly expressed in pancreatic ductal adenocarcinoma but not in non-carcinoma tissues. In the current study, we designed a plectin-1 targeted dual-modality nanoparticle (Plectin-SPION-Cy7). In vitro and in vivo data both indicated that plectin-1 targeted nanoparticles were highly accumulated in carcinoma cells/tissues but not in non-carcinoma cells/tissues. These results show that plectin-1 targeted fluorescence and MR dual-functional nanoparticle is useful for pancreatic cancer detection.

A gait feature extraction method based on resampling shape context is proposed in this article. First, the moving target detection is carried out to obtain the target area of the human body. Second, the gait cycle is measured, and the contour points and the lower limb joints are selected as sampling points. Then, the different sampling points is placed in the polar coordinates of the origin, the number of sampling points in different cells is counted as the shape context; Finally, the feature vectors are constructed according to the shape context, and the minimum distance is used for classification and recognition. Simulation experiments based on resampling shape context are tested in CASIA gait Database A and Database B. The experimental results show that the method proposed in this article has a lower computational complexity and higher recognition rate when compared with the original shape context method, which can be used for gait recognition.

Background Low-grade fibromyxoid sarcoma (LGFMS) is a distinctive slow growing soft tissue neoplasm, mostly affecting young individuals with no gender difference. It usually arises in deep soft tissue of the lower limbs and trunk, but few cases of LGFMS located in pelvis have been reported. Case presentation We describe the magnetic resonance imaging(MRI) features of LGFMS located in the anterior pelvic wall of a 21-year-old female and correlate them with clinicopathological features. The tumor was completely resected and there is no recidivism during the follow-up one year. Conclusions We report on the radiological findings of LGFMS with histological correlation. Awareness of the imaging features may be useful for the diagnosis of LGFMS and helpful to distinguish among mimics.

Density functional theory (DFT) calculation and ab initio molecular dynamics (AIMD) are combined to investigate the CrN oxidation mechanism. The surface energy, adsorption configuration and electronic structure of oxygen molecule and atom on the CrN (100) surface are investigated through DFT calculation. AIMD calculation is used to investigate the geometric configuration and electronic structure evolution of O2 molecule adsorption and dissociation process at 1073 K. Results show that the (100) surface has the lowest surface energy. The top site of Cr atom is the most stable adsorption site for oxygen molecules and atoms, and the adsorption energy values are −4.276 eV and −4.975 eV, respectively. Charge density difference results show that both oxygen molecule and atom undergo charge transfer with the Cr atom. The O atom gains electrons while the Cr atom loses electrons. Results of partial density of states show that the Cr O bond is formed due to the hybridization between the O-p and Cr-d orbitals. At 1073 K, AIMD results show that the O2 molecule automatically dissociates into O atoms, and the dissociated O atoms form stable covalent bonds with the surface Cr atom. The hybridization between the O-p and Cr-d orbitals gradually increases, thereby forming stable adsorption.

Previous multi-turn dialogue approaches based on global Knowledge Graphs (KGs) still suffer from generic, uncontrollable, and incoherent responses generation. Most of them neither consider the local topic-level semantic information of KGs nor effectively merge the information of long dialogue contexts and KGs into the dialogue generation. To tackle these issues, we propose a Topic-level Knowledge-aware Dialogue Generation model to capture context-aware topic-level knowledge information. Our method thus accounts for topic-coherence, fluency, and diversity of generated responses. Specifically, we first decompose the given KG into a set of topic-level sub-graphs, with each sub-graph capturing a semantic component of the input KG. Furthermore, we design a Topic-level Sub-graphs Attention Network to calculate the comprehensive representation of both sub-graphs and previous turns of dialogue utterances, which then decoded with the current turn into a response. By using sub-graphs, our model is able to attend to different topical components of the KG and enhance the topic-coherence. We perform extensive experiments on two datasets of DuRecDial and KdConv to demonstrate the effectiveness of our model. The experimental results demonstrate that our model outperforms existing strong baselines.

Density functional theory (DFT) and ab initio molecular dynamics (AIMD) calculations are combined to study the α-Ti oxidation mechanism on atomic scale. The most and second stable adsorption site for O atoms on the surface layer is FCC and HCP site, respectively. The most stable adsorption site of subsurface layer is octahedral site. O atoms all gain electrons from adsorbed Ti atoms and the Ti–O bonds are mainly formed by the hybridization between O-p and Ti-d orbitals. At both 303 K and 873 K, AIMD results show that O2 molecule gradually dissociate into O atoms on α-Ti (0001) surface and then adsorb on the surface. The increase of temperature accelerates the dissociation rate of O2 molecule. During the formation of Ti–O bond, O and Ti atom gain and lose electrons, respectively. The partial density of states evolution results show that the Ti–O bond is formed by the gradually strengthened hybridization between O-p and Ti-d orbitals. At 303 K, α-Ti (0001) surface can form a dense oxide film. But a discontinuous and loose oxide film is formed at 873 K and O atoms can penetrate into the octahedral and tetrahedral sites of the subsurface layer.

Ti2AlC oxidation mechanism was investigated by density functional theory (DFT) and ab initio molecular dynamics (AIMD). DFT results showed that the most stable adsorption site was HCP hollow sites, followed by FCC. O atom gained electrons, while Al atom lost electrons through the hybridisation of O-p and Al-s/p orbitals. AIMD results show that O2 molecule gradually dissociated into O atoms at 1273 K and formed Al-Ti mixed oxide film. The hybridisation between O-p and Al-s/p orbitals formed Al-O bond, while the hybridisation of O-p and Ti-d orbitals formed Ti-O bond.

Camelid single-domain antibodies (sdAbs, VHHs, or Nanobodies®) are types of antibody fragments that are composed of the heavy-chain variable domain only. These VHHs possess unique structural and functional features, as they are small in size and exhibit thermal stability and high solubility. Compared to conventional antibodies, VHHs can be manufactured in microorganisms to significantly save on cost, labor, and time since VHHs lack the Fc domain with its N-linked oligosaccharide. Until now, VHHs have been expressed in several kinds of production systems, ranging from prokaryotic cells, yeasts, fungi, insect cells, and mammalian cell lines, to plants. In this review, we focus on the recent production of VHHs, introduce different platforms, and summarize the current state of this area and its future trends. Finally, the first potential VHH product, produced in Pichia pastoris, will probably be available on the market in 2018; thus, it is of great importance to give this antibody fragment timely attention. This is the first review concerning the production of VHHs in laboratory settings.

Designing heteroatom doped metal oxides and modifying them with carbonaceous materials can grant metal oxides with good Li + storage performance because of the improved structure stability and enhanced electric conductivity. Herein, monodispersed Cr-doped SnO 2 quantum dots fixed by graphene nanosheets and carbon layers (C/Cr-SnO 2 /G) were successfully assembled, which showed excellent cyclic stability, high reversible capacity and remarkable rate capability for Li + storage. According to the characteristics results, 3.8 wt% Cr were uniformly incorporated into SnO 2 lattice in form of Cr 3 + , resulting the decrease of SnO 2 diameters. The C/Cr-SnO 2 /G electrodes displayed an excellent reversible capacity of 672 mA h g − 1 after 200 cycles at 100 mA g − 1 without apparent capacity fading throughout the test, and still retained a stable specific capacity of 296 mA h g − 1 even at 5 A g − 1 . The enhanced electrochemical performances of C/Cr-SnO 2 /G can be related to incorporation of Cr into lattice of SnO 2 and the double structure protections by graphene nanosheets and carbon layers, which can easily obtain quantum dots structure, increase the conductivity, and keep the structure stability.

In this work, we fabricated high-strength Ti2AlNb sheets by hot packed rolling the spark-plasma-sintered pre-alloyed powders at the B2 + O phase field. We rolled the sheets with three different schemes, namely, sheet A (thickness reductions of 42% + 42%), sheet B (30% + 30% + 30%), and sheet C (30% + 21% + 21% + 21%). Results showed that the spheroidizing of the O phase occurred during the multiple rolling processes, and sheet C consisted of only spherical O phases. The mechanical property tests showed that Ti2AlNb sheets with tensile strengths higher than 1400 MPa could be obtained without any post heat treatment. Both micro-sized O and nano-sized O phases contributed to the excellent mechanical properties of the sheets. The multiple rolling processes resulted in slight decreases in tensile strength but an increase in ductility. All sheets showed brittle fracture mode with reduction of area smaller than 5%.

The nanostructured Cu coatings were electrodeposited with different vibration, such as vibration-free, agitation and ultrasonic.Ultrasonic could help to refine grains and optimize the comprehensive performance of the coating. The effect of vibration on the thermal stability of pure Cu coatings was investigated with the coatings annealing at 450 °C, 500 °C and 550 °C. Both agitation and ultrasonic can suppress the nanograins coarsening and the effect of ultrasonic was more excellent. Ultrasonic can not only increase the content of nanotwins and triple junctions but also induce the relaxation of GBs. Therefore, the ultrasonic deposited nanograins in the low-energy state exhibit superior thermal stability. The mechanisms of the thermal stability in the electrodeposited coatings were studied from thermodynamics and dynamics. By comparing dislocation density, stacking faults energy and grain boundaries energy, it was proved that the driving force of grain growth in the ultrasonic deposited coating was lowest. Both the methods of isothermal measurements and Kissinger showed that the ultrasonic could increase the activation energy of grain growth to inhibit grain boundary mobility.

The electric resistance heating technology was introduced into the solution heating, forming-quenching with cold die integrated process for improving the dimensional accuracy of the 5A90 Al–Li alloy U-shaped parts. In order to evaluate the effect of current density on the forming quality of U-shaped parts, the springback and mechanical properties of formed parts were analyzed. The dimensional accuracy of formed parts increased with the current density. The U-shaped part with the minimum springback angle (0.43°) was obtained under the current density of 12.76 A/mm2. The increase in hardness of the typical positions of U-shaped parts was mainly due to the spherical δ′ phase with the proper matching of volume fraction and size. The hardness of the bottom fillet increased from 82.4 HV to 113.53 HV after ageing at 160 °C for 10 h. A mechanistic model referring to grain boundaries, dislocation accumulation, solid solution and precipitation was established to describe the hardening mechanisms. The δ′ phase not only contributed to the precipitation hardening mechanism but also affected the solid solution hardening by changing the concentration of solute atoms. The precipitate hardening caused by δ' phase with the perfect antiphase boundaries was the dominant mechanism, which afforded 35.6 HV with the volume fraction of 31.51% in the peak-aged sample.

TixVNbMoTa refractory high-entropy alloys (RHEAs) were fabricated by mechanical alloying (MA) and spark plasma sintering (SPS) based on classic VNbMoTaW RHEA. The effect of Ti content on the microstructures and mechanical properties of the TixVNbMoTa RHEAs were systematically investigated. The results showed that the milling powders with more Ti content were agglomerated severely in the early stage of the MA process, leading to the extension of mechanical alloying time. The mechanically alloyed powders in all groups exhibited single body-centered-cubic (BCC) phase after the MA process. The sintered alloys were consisted of ultra-fine matrix and precipitation phase. The grain sizes of the matrix and precipitation phases, as well as the volume fraction of the precipitation phases were increased with the increase of Ti content. The MA and SPS processes and the replacement of Ti not only greatly reduce the densities, but also significantly improved the ductility, strength and specific strength of the alloys. The yield strengths were decreased first and then increased with the increase of Ti content in the TixVNbMoTa RHEAs, which is mainly attributed to the weakened effect of grain boundary strengthening, and the enhanced effect of the substitution solid solution strengthening and the interstitial solid solution strengthening. The rapidly increased sizes and volume fractions of the precipitated phases in Ti1.5 and Ti2 destroyed the continuity of matrix and the coordination of deformation, resulting in the decrease of ductility.

Porous h-MoO3@C nanofibers with a large specific surface area of 400.2 m2 g−1 were successfully synthesized with hot HNO3 oxidizing MoO2@C nanofibers without obvious damage to carbon shells. As anodes for lithium ion batteries (LIBs), the porous h-MoO3@C nanofibers electrodes show a reversible capacity of 302.9 mA h g−1 at 2 A g−1 after 500 cycles. As anodes for sodium ion batteries (SIBs), they also can deliver a good rate capacity and hold 108.9 mA h g−1 at 2 A g−1 after 500 cycles, even can have 91 mA h g−1 at 5 A g−1 after 1200 cycles. The excellent electrochemical performances of the porous h-MoO3@C nanofibers are attributed to the unique structure which not only can maintain the structure stability but also provide enough active sites for Li+/Na+. At the same time, the tunnel structure of h-MoO3 can lead to separate electron–hole and offer a great deal of special positions for cation (Li+/Na+) insertion/extraction. The present method may be helpful for the synthesis of transition metal oxides (TMOs)-carbon composites with high valence metal atoms in the field of batteries and catalysts.

Timely and reliable sensing and actuation control are essential in networked control. This depends on not only the precision/quality of the sensors and actuators used but also on how well the communications links between the field instruments and the controller have been designed. Wireless networking offers simple deployment, reconfigurability, scalability, and reduced operational expenditure, and is easier to upgrade than wired solutions. However, the adoption of wireless networking has been slow in industrial process control due to the stochastic and less than 100 % reliable nature of wireless communications and lack of a model to evaluate the effects of such communications imperfections on the overall control performance. In this paper, we study how control performance is affected by wireless link quality, which in turn is adversely affected by severe propagation loss in harsh industrial environments, co-channel interference, and unintended interference from other devices. We select the Tennessee Eastman Challenge Model (TE) for our study. A decentralized process control system, first proposed by N. Ricker, is adopted that employs 41 sensors and 12 actuators to manage the production process in the TE plant. We consider the scenario where wireless links are used to periodically transmit essential sensor measurement data, such as pressure, temperature and chemical composition to the controller as well as control commands to manipulate the actuators according to predetermined setpoints. We consider two models for packet loss in the wireless links, namely, an independent and identically distributed (IID) packet loss model and the two-state Gilbert-Elliot (GE) channel model. While the former is a random loss model, the latter can model bursty losses. With each channel model, the performance of the simulated decentralized controller using wireless links is compared with the one using wired links providing instant and 100 % reliable communications. The sensitivity of the controller to the burstiness of packet loss is also characterized in different process stages. The performance results indicate that wireless links with redundant bandwidth reservation can meet the requirements of the TE process model under normal operational conditions. When disturbances are introduced in the TE plant model, wireless packet loss during transitions between process stages need further protection in severely impaired links. Techniques such as retransmission scheduling, multipath routing and enhanced physical layer design are discussed and the latest industrial wireless protocols are compared.

Iron-based catalysts for oxygen reduction reaction (ORR) have attracted considerable attention as one of the most promising candidates owing to their low cost and high catalytic activity. Herein, sandwich-like Fe, N-graphene composites catalysts were rationally designed and synthesized by a two-step procedure using graphene oxide and pyrrole as chemicals. The layered graphene oxide @ polypyrrole precursor was synthesized by in-situ polymerization of pyrrole with GO/FeCl 3 complexes served as both template and oxidant. The resulted Fe N C catalysts obtained from above precursors annealed at 825 °C with sandwich-like structure of Fe species between graphene and carbon coating as the electrocatalysts for ORR showed that, comparable to the commercial Pt/C catalyst, positive onset potential (−0.08 V vs Ag/AgCl), high ORR limiting current density (5.87 mA cm −2 at −0.6 V), favoured an apparent 4-electron transfer pathway, outstanding stability, excellent methanol tolerance. Those excellent properties of rational designed Fe N C catalysts can be attributed to the suitable feeding order of chemicals to keep the advantages of graphene with high specific surface area and provide more effective surface active sites, and protection for active sites by carbon layers from polypyrrole.

Industrial Internet of Things (IIoT) applications, featured with data-centric innovations, are leveraging the observability, control, and analytics, as well as the safety of industrial operations. In IIoT deployments, wireless links are increasingly used in improving the operational connectivity for industrial data services, such as collecting massive process data, communicating with industrial robots, and tracking machines/parts/products on the factory floor and beyond. The wireless system design for IIoT applications is inherently a joint effort between operational technology (OT) engineers, information technology (IT) system architects, and wireless network planners. In this paper, we propose a new reference framework for the wireless system design in IIoT use cases. The framework presents a generic design process and identifies the key questions and tools of individual procedures. Specifically, we extract impact factors from distinct domains including industrial operations and environments, data service dynamics, and the IT infrastructure. We then map these factors into function clusters and discuss their respective impact on performance metrics and resource utilization strategies. Finally, discussions take place in four exemplary IIoT applications where we use the framework to identify the wireless network issues and deployment features in the continuous process monitoring, discrete system control, mobile applications, and spectrum harmonization, respectively. The goals of this work are twofold: 1) to assist OT engineers to better recognize wireless communication demands and challenges in their plants, 2) to help industrial IT specialists to come up with operative and efficient end-to-end wireless solutions to meet demanding needs in factory environments.

A fourth industrial revolution, occurring in global manufacturing, provides a vision of future manufacturing systems that incorporate highly dynamic physical systems, robust and responsive communications systems, and computing paradigms to maximize efficiency, enable mobility, and realize the promises of the digital factory. Wireless technology is a key enabler of that vision. A comprehensive graphical model is developed for a generic wireless factory work cell which employs the Systems Modeling Language (SysML), a standardized and semantically rich modeling language, to link the physical and network domains in such a cyber-physical system (CPS). The proposed model identifies the structural primitives, interfaces, and behaviors of the highly connected factory work cell in which wireless technology is used for significant data flows involved in control algorithms. The model includes the parametric definitions to encapsulate information loss, delay, and mutation associated with the wireless network, and it identifies pertinent wireless information flows.

Cyber-physical systems are systems governed by the laws of physics that are tightly controlled by computer-based algorithms and network-based sensing and actuation. Wireless communication technology is envisioned to play a primary role in conducting the information flows within such systems. A practical industrial wireless use case involving a robot manipulator control system, an integrated wireless force-torque sensor, and a remote vision-based observer is constructed and the performance of the cyber-physical system is examined. By using readings from the remote observer, an estimation system is developed using machine learning regression techniques. We demonstrate the practicality of combining statistical analysis with machine learning to indirectly estimate signal-to-interference of the wireless communication link using measurements from the remote observer. Results from the statistical analysis and the performance of the machine learning system are presented.

A work cell is an essential industrial environment for testing wireless communication techniques in factory automation processes. A new testbed was recently designed and developed to facilitate such studies in work cells by replicating various data flows in an emulated production environment. In this paper, the testbed’s baseline design is presented which characterizes deterministic and reliable communication needs between work cell components in a typical machine tending application. Special design issues are discussed regarding safety measures in collaborative robotic operations and network synchronization among distributed machines. Measurement plans in the hardwired baseline are also introduced along with further wireless extensions. The testbed can serve as a representative cyber-physical system (CPS) model to verify industrial wireless techniques in support of mission-critical data transmissions.

Recent years have brought significantly increased interest in integrating wireless communication capability within factory automation systems. Such integration motivates the study of interactions among the physical layout of factory workcells, wireless communication among workcells, and improving the overall factory system performance. In this paper, we develop methods for modeling and simulating these interactions, and implement these methods into the experimental study of complex design spaces for factory automation systems. The proposed methodology for modeling, simulation, and design space exploration can be used to gain insight into approaches for improving the configuration (e.g., physical layout or wireless protocol settings) of existing factory systems, and for understanding trade-offs in the design of new systems.

Advanced driver assistance and automated driving systems rely on risk estimation modules to predict and avoid dangerous situations. Current methods use expensive sensor setups and complex processing pipeline, limiting their availability and robustness. To address these issues, we introduce a novel deep learning based action recognition framework for classifying dangerous lane change behavior in short video clips captured by a monocular camera. We designed a deep spatiotemporal classification network that uses pre-trained state-of-the-art instance segmentation network Mask R-CNN as its spatial feature extractor for this task. The Long-Short Term Memory (LSTM) and shallower final classification layers of the proposed method were trained on a semi-naturalistic lane change dataset with annotated risk labels. A comprehensive comparison of state-of-the-art feature extractors was carried out to find the best network layout and training strategy. The best result, with a 0.937 AUC score, was obtained with the proposed network. Our code and trained models are available open-source., Comment: 8 pages, 3 figures, 1 table. The code is open-source

A three dimensional (3D) nanostructured composite based on the self-assembly of MoS

The hot deformation behaviors of an ultrafine-grained MoNbTaTiV refractory high entropy alloy (RHEA) fabricated by powder metallurgy (P/M) were investigated using isothermal compression tests in the deformation temperature range of 1100 °C ~ 1300 °C and the strain rate range of 0.0005 s−1–0.5 s−1. Electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM) techniques were used to analyze the effect of the deformation temperatures and the strain rates on the flow stress behaviors and microstructural evolution during hot deformation. The results showed that the flow stresses exhibit typical dynamic recrystallization (DRX) characteristics, but show work hardening characteristics at 1100 °C and 0.5 s−1 deformation conditions and at 1200 °C and 0.5 s−1 deformation conditions. With increasing deformation temperature and decreasing strain rate, the maximum compressive stresses were dramatically decreased, and the average grain sizes also slowly increased. The limited growth of grains was due to the sluggish diffusion effect of high entropy alloys (HEAs) and the pinning effect of the ultrafine precipitated phases. The dominant DRX process gradually changed from discontinuous dynamic recrystallization (DDRX) to continuous dynamic recrystallization (CDRX) with increasing deformation temperature and decreasing strain rate. Both of these DRX processes were promoted by the ultrafine precipitated phases. The dominant deformation mechanism at low deformation temperature and high strain rate was grain deformation. Grain boundary gliding became the dominant deformation mechanism at higher deformation temperature and lower strain rate, but it was inhibited to some extent by grain growth and the ultrafine precipitated phases distributed at grain boundaries.

In this work, a novel “spark plasma sintering (SPS) of pre-alloyed powder followed by a hot packed rolling” method is proposed to fabricate the Ti2AlNb sheet. Ti2AlNb sheets with high tensile strength and good ductility are obtained without any post heat treatment. Ti2AlNb compact is first prepared by SPS of the pre-alloyed powders. The compact sintered at 1060 °C consists of only B2 phases with an average grain size of 25.88 μm. No α2 phase forms after rolled at 1030 °C and the B2 grain size increases by increasing the rolling passes because of the fast grain growth of B2 grains. Numerous ultrafine O phases precipitated inside the B2 matrix after cooled in air, and they contribute to the excellent strength and ductility of the sheets. The mechanical property tests showed that the sheets rolled by 2 passes (thickness reduction: 42% + 42%) and 4 passes (30% + 21% + 21% + 21%) had the maximum tensile strength of 1239.03 MPa and the maximum elongation of 9.49%, respectively. All the rolled sheets presented ductile fracture mode with numerous dimples on the fracture surface.

Synovitis, acne, palmoplantar pustulosis, hyperostosis and osteitis syndrome (SAPHO) is a rare syndrome that affects the skin, bones and joints. Diagnosis of SAPHO syndrome is established on clinical appearance and imaging features. The present case report described the imaging features of three cases of SAPHO with sternoclavicular joint arthritis but without skin manifestations using multiple imaging modalities, including computed tomography (CT), magnetic resonance imaging (MRI) and bone scintigraphy. The first case was a 52-year-old male who suffered from progressive sternoclavicular arthritis for 2 years. The second case was a 62-year-old female with arthritis in the larger joints for 5 years, particularly on the right thoracic area. The third case was a 44-year-old male who exhibited a slight bulge accompanied by pain in the upper anterior chest wall for 4 years. All of them lacked cutaneous lesions. CT demonstrated sclerosis and hyperostosis with subchondral erosions in the sternocostoclavicular joints. MRI revealed bone marrow edema that was slightly hypointense on T1-weighted imaging, and hyperintense on T2-weighted imaging. Typical ‘bull head’ signs were observed in bone scintigraphy images. The present case study demonstrated that SAPHO syndrome should be suspected in patients with multifocal osteitis or arthritis affecting the chest wall that lack skin manifestations. Multimodal imaging modalities in combination are helpful for SAPHO diagnosis.

In this paper, two carbon nanotube (CNT) nanofillers, namely the multi-walled carbon nanotubes (MWCNTs) and the carboxyl-modified MWCNTs (cMWCNTs), were introduced into the polydimethylsiloxane (PDMS) matrix respectively, in order to produce the PDMS composites with reinforced anti-biofouling properties. The anti-biofouling capacity of the silicone-based coatings, including the unfilled PDMS (P0), the MWCNTs-filled PDMS (PM) and the cMWCNTs-filled PDMS (PC), was examined via the field assays conducted in Weihai, China. The effect of different silicone-based coatings on the dynamic variations of the pioneer microbial-community diversity was analyzed using the single-strand conformation polymorphism (SSCP) technique. The PM and PC surfaces have exhibited excellent anti-biofouling properties in contrast to that of the PDMS surface, with extremely low attachment of the early colonizers, such as juvenile invertebrates, seaweeds and algae sporelings. The PM and PC surfaces can effectively prevent biofouling for more than 12 weeks. These combined results suggest that the incorporation of MWCNTs or cMWCNTs into the PDMS matrix can dramatically reinforce its anti-biofouling properties. The SSCP analysis reveals that compared with the PDMS surfaces, the PM and PC surfaces have strong modulating effect on the pioneer prokaryotic and eukaryotic communities, particularly on the colonization of pioneer eukaryotic microbes. The significantly reduced pioneer eukaryotic-community diversity may contribute to the weakening of the subsequent colonization of macrofoulers.

Isothermal compression tests were conducted on A100 steel using a Gleeble 1500 thermal simulator at a temperature range of 900–1,200°C and strain rate range of 0.001–3 s−1. Results show that the A100 steel has higher strength than the Aermet 100 steel at high temperatures. Constant values, such as A, α, and n, and activate energy Q were obtained through the regression processing of the stress–strain data curves under different strains. A set of constitutive equations for A100 steel was proposed by using an Arrhenius-type equation. The optimum processing craft ranges for A100 steel based on the analysis of the hot working diagram and deformation mechanism are as follows: temperature range of 1,000–1,100°C and strain rate range of 0.01–0.1 s−1. The average grain size within this working range is 7–22.5 μm.

To obtain alkaline protease producing strain with high-yield, the strain Bacillus subtilis was treated by atmospheric and room temperature plasma (ARTP) mutagenesis. The results showed that the strain had a higher positive mutation rate when the mutagenesis time was 50s. Finally, a high-yield mutant strain A59 was obtained after repeated mutagenesis by ARTP and enzyme activity increased by 23.38% from 6835U/mL to 8433U/mL. Then fermentation conditions of mutant strain were optimized by single-factor method and response surface method, and the optimum fermentation conditions were as follows: 3.6% soybean meal, 5.2% corn meal, 0.9115% Na2HPO4, 0.1593% Mg2+, 0.09% Tween-80 and 5% inoculation volume. Under the conditions of the verification experiment, the enzyme activity of the A59 strain reached 14026 U/mL, which was 2.05 times that of the original strain.

This work reported a label-free electrochemical aptasensor based on bimetallic ZnNi metal–organic framework (MOF) microspheres for highly efficient detection of adenosine (AD). Three ZnNi MOFs with different morphologies were prepared by regulating the molar ratio of Zn2+ to Ni2+ (1:1, 1:2, and 1:3) in the preparation processes. The ZnNi MOF (1:2)-based aptasensor displayed excellent sensing performance toward AD compared with ZnNi MOF (1:1) and ZnNi MOF (1:3)-based ones due to its higher electrochemical activity and stronger binding interaction between the aptamer strands and hierarchically nanostructured hollow microspheres. The proposed aptasensor exhibited a low detection limit of 20.32 fg·mL−1 for AD within a wide linear range from 0.0001 to 100 ng·mL−1. This aptasensor also showed excellent selectivity, acceptable reproducibility, high stability, good regenerability, and favorable applicability for AD detection in human serum. The remarkable biosensing performance was primarily attributed to the strong adsorption interactions of Ni2+ to aptamers, special morphology of materials, and the synergistic effect of Zn2+/Ni2+ in MOF matrixes. The rational construction of bimetallic ZnNi MOFs provided a promising sensing platform for sensitive detection of AD and further, showed great potentials in clinic diagnosis.

Rehmannia glutinosa root contains many compounds with important medicinal properties and nutritional benefits, but only more than 140 compounds have been reported so far. Many other compounds and their accumulation and metabolic networks during its development remain unclear. In order to clarify them, its metabolic profiles at three different developmental stages were analyzed using untargeted LC-MS analysis. Multivariate analysis revealed that 434 metabolites differently accumulated in its different stages, suggesting different change trends. The metabolites having the same trend share common metabolic pathways, the metabolites showing increasing contents during its development have medical and nutritional values, and some mature root-specific metabolites may be better candidates for its quality control; 434 metabolites were mapped onto 111 KEGG pathways including 62 enzymes, whose increasing and decreasing patterns were shown during its development. Some metabolites complicatedly interacted with some enzymes and the top-10 pathways enriched from 111 KEGG pathways in network analysis. These findings extended the dataset of its identified compounds, and revealed that its development and quality were associated with the accumulation of different metabolites. Our work will lay the foundation for the better understanding of its chemical constituents, quality and developmental mechanism.

We have explored a nanocomposite composed of a bimetallic CoNi-zeolitic imidazole framework embedded by MoS2 nanosheets (MoS2@CoNi-ZIF), as a bifunctional electrocatalyst for non-Pt methanol oxidation reaction (MOR) and overall water splitting in an alkaline solution. The series of MoS2@CoNi-ZIF nanocomposites exhibit different catalytic activities. Significantly, the MoS2@CoNi-ZIF nanosheet with a ratio of MoS2:CoNi-ZIF = 3:1 (MoS2@CoNi-ZIF(3-1)) shows the excellent electrocatalytic activity for MOR, affording an oxidation potential at 1.6 V, also with high catalytic current density and durability. Moreover, the MoS2@CoNi-ZIF(3-1) nanocomposite shows a superior electrocatalytic performance toward HER and OER. When the MoS2@CoNi-ZIF(3-1) was applied as the bifunctional catalyst for both the anode and cathode, the voltage applied to a two-electrode cell is 1.55 V to achieve a current density of 10 mA cm−2 for overall water splitting. This work provides a promising electrocatalyst for developing high-performance non-Pt-based clean energy and fuel cells in alkaline solution.

20-Hydroxyeicosatetraenoic acid (20-HETE), a cytochrome P450 4A (CYP4A) metabolite of arachidonic acid, is one of the primary eicosanoids in most of microcirculatory beds. Studies have indicated that 20-HETE has important functions in the modulation of vascular tone, ion transport, inflammation reaction, and cellular proliferation. Both we and others have demonstrated that 20-HETE plays an important role in acute phase of ischemic stroke. However, little is known about the effect of 20-HETE on recovery phase of stroke. Crosstalk between the cells within the neurovascular unit is increasingly suspected of playing critical roles in stroke recovery. We found that CYP4A is upregulated in astrocytes exposed to oxygen-glucose deprivation (OGD), which increases the production of 20-HETE that promotes endothelial cell proliferation, tube formation and migration. siRNA suppression of CYP4A or 20-HETE inhibitor prevents this effect. In a mouse model of transient focal cerebral ischemia, inhibition of CYP4A reduces peri-infact angiogenesis and worsens neurological deficits 14 days after stroke. We further showed that ischemia injury increases VEGF and HIF-1α expression in cell cultures and ischemic brains, which is negated by a 20-HETE inhibitor-HET0016. Lastly, we showed that JNK signaling pathway is a component of 20-HETE regulated ischemic angiogenesis after stroke. Taken together, we demonstrated a positive influence of 20-HETE in angiogenesis in later stage of stroke. These molecular and in vivo findings also support a previously undescribed mechanism of crosstalk between reactive astrocytes and endothelial cells wherein 20-HETE promotes neurovascular remodeling and functional recovery after ischemic stroke.

This work focused on the microstructure, morphology and thermal stability of a MoNbTaTiV refractory high-entropy alloy synthesized by mechanical alloying. The mechanically alloyed powder with a uniform chemical distribution and an average grain size of less than 15 nm was obtained after 40 h milling process. With a refinement of the grain size and an increase of the lattice strain, the milled powder transformed from large and inhomogeneous to refined and homogeneous. The mechanically alloyed powder exhibited excellent thermal stability at 1200 °C.

A floating nuclear power plant (FNPP) with small modular reactor (SMR) is a combination of a civilian nuclear infrastructure and an offshore installation, which is defined as a floating nuclear facility. The article draws the lessons from studying of the engineer combination like Floating Production Storage and Offloading (FPSO) under the regulation of several government departments. It puts forward recommendations for license application and government regulation as follows in consideration with current license application for nuclear power plant and ship survey. A FNPP shall follow the requirements of construction, fueling and operation for civil nuclear installation combined with ship survey. Application is submitted to nuclear safety regulator for construction permit, while the design drawings shall be submitted to department of ship survey which checks the drawings whether meet the requirements of ship survey, considering some nuclear safety needs. The result of ship survey shall be represented in the safety analysis reports. The construction and important devices manufacturing shall be under the supervision of nuclear installation regulators and ship survey departments. In conclusion, National Nuclear Safety Administration (NNSA) and Maritime Safety Administration of the People’s Republic of China (MSA) shall establish united supervisory system for SMR on sea in China. It is suggested that NNSA is in charge of the overall safety of a FNPP, while MSA is responsible of the ship survey. The operator shall undertake obligation of a FNPP and evaluate the ship cooperating with experienced agency. It is suggested that government departments build the mutual recognition agreement of safety review. It is better to solve the vague questions by coordination.

Industrial wireless is increasingly developing to enhance data dissemination in the Industrial Internet of Things (IIoT) for leveraging the visibility, control, and safety in industrial environments. In this paper we propose a generic framework that enumerates physical and cyber factors in an IIoT use case that may impact the performance of wireless transmissions and challenge the design work. These factors are discussed in a conceptually tiered structure using domain knowledge from operational technology (OT) applications, data services, and information technology (IT) infrastructures. The correlations between intra- and inter-domain factors are also discussed in search of efficient wireless design solutions. Given the diversity and variety of IIoT practices, such a framework that identifies general and specific wireless requirements in individual use cases would be of high practical value to industrial wireless design and implementation.

Background/Aims: Cancer stem cells (CSCs) are largely responsible for tumor relapse and metastatic behavior. Doublecortin-like kinase 1 (DCLK1) was recently reported to be a biomarker for gastrointestinal CSCs and involved in the epithelial-mesenchymal transition (EMT) and tumor progression. B cell-specific Moloney murine leukemia virus insertion site 1 (Bmi-1) is a crucial regulator of CSC self-renewal, malignant transformation and EMT, and a previous study from our group showed that Bmi-1 is upregulated in pancreatic cancer progression and participates in EMT. However, it remains unclear whether DCLK1 is involved in pancreatic cancer or whether DCLK1 is associated with the altered level of Bmi-1 expression. Methods: The correlation of DCLK1 expression and clinical features of pancreatic cancer was analyzed in 210 paraffin-embedded archived pancreatic cancer specimens by immunohistochemical analysis. The biological effects of DCLK1 siRNA on cells were investigated by examining cell proliferation using a cell counting kit and cell colony assays, cell migration by wound healing assay and cell invasion by Transwell invasion assay. We further investigated the effect of therapeutic siRNA targeting DCLK1 on pancreatic cancer cell growth in vivo. Moreover, the molecular mechanism by which DCLK1 upregulates Bmi-1 expression was explored using real-time PCR, western blotting and Co-immunoprecipitation assay. Results: DCLK1 is overexpressed in pancreatic cancer and is related to metastasis and prognosis. Knockdown of DCLK1 markedly suppressed cell growth in vitro and in vivo and also inhibited the migration and invasion of pancreatic cancer cells. Furthermore, we found that DCLK1 silencing could inhibit EMT in cancer cells via downregulation of Bmi-1 and the mesenchymal markers Snail and Vimentin and upregulation of the epithelial marker E-cadherin. Moreover, high DCLK1 expression in human pancreatic cancer samples was associated with a mesenchymal phenotype and increased cell proliferation. Further co-immunoprecipitation indicated that DCLK1 did not interact with Bmi-1 directly. Conclusion: Our data suggest that upregulation of DCLK1 may contribute to pancreatic cancer metastasis and poor prognosis by increasing Bmi-1 expression indirectly. The findings indicate that inhibiting DCLK1 expression might be a novel strategy for pancreatic cancer therapy.

Voice-based human-machine interface has become a prevalent feature for modern intelligent vehicles, especially in navigation and infotainment applications. Automatic Speech Recognition (ASR) converts spoken audio streams to plain texts, but a follow-up Natural Language Processing (NLP) sub-system is needed to understand the contextual meaning from the text and act. For the specific human-vehicle navigation dialogue application, the two major tasks include (1) intent detection — decide whether a sentence is navigation-related, and (2) semantic parsing — retrieve important information (e.g., point-of-interest destinations) from the words. To address these two tasks, this study proposes a Recurrent Neural Network (RNN) architecture, with the consideration of (1) one joint model vs. two separate models, (2) a context window approach vs. sequence-to-sequence translation approach, as well as (3) alternate model hyper-parameter selections. The experiment is conducted with both the benchmark ATIS dataset and the CU-Move in-vehicle dialogue corpus, and the result is compared against related state-of-the-art methods. Overall, the proposed solution on the CU-Move data achieves accuracies of 98.24% for intent detection and 99.60% for semantic parsing, outperforming other related methods.

In this paper, a cluster-based two-phase coordination scheme for cooperative cognitive radio networks is proposed considering both spectrum efficiency and network fairness. Specifically, candidate secondary users SUs are first selected by a partner selection algorithm to enter the two-phase cooperation with primary users PUs. In phase I, the selected SUs cooperate with PUs to acquire a fraction of time slot as a reward. In phase II, all SUs including the unselected ones share the available spectrum resources in local clusters; each of which is managed by a cluster head who participated in the cooperation in phase I. To improve the total network utility of both PUs and SUs, the maximum weighted bipartite matching is adopted in partner selection. To further improve the network performance and communication reliability, network coding is exploited during the spectrum sharing within the cluster. Simulation results demonstrate that, with the proposed cluster-based coordination scheme, not only the PUs' transmission performance is improved, but also SUs achieve spectrum access opportunities. Copyright © 2015John Wiley & Sons, Ltd.

The continuous variations of dissolved oxygen (DO), manganese (Mn), pH, and their effect on manganese removal by different water treatment processes are investigated. The results show that the declined DO concentration and pH value in the bottom of reservoir results in the increasing release of Mn from sediment to source water. Manganese concentration increased from 0.1 to 0.4 mg·L−1 under the condition that DO concentration decreased from 12.0 to 2.0 mg·L−1 in raw water. The different water treatment processes exhibited different efficiency on manganese removal. The processes with recycling of the suspended sludge, low elevation velocity in settling tank and slow filter rate, will benefit the manganese removal. During a high release of manganese in raw water, traditional coagulation-sedimentation and filtration could not completely remove Mn, although granular activated carbon filtration (GAC) had been applied. At that case, preoxidation with chlorine or potassium permanganate (KMnO4) was necessary to address the high manganese concentration.

This paper proposes a novel base station (BS) coordination approach for intercell interference mitigation in the orthogonal frequency-division multiple access based cellular networks. Specifically, we first propose a new performance metric for evaluating end user's quality of experience (QoE), which jointly considers spectrum efficiency, user fairness, and service satisfaction. Interference graph is applied here to capture and analyze the interactions between BSs. Then, a QoE-oriented resource allocation problem is formulated among BSs as a local cooperation game, where BSs are encouraged to cooperate with their peer nodes in the adjacent cells in user scheduling and power allocation. The existence of the joint-strategy Nash equilibrium (NE) has been proved, in which no BS player would unilaterally change its own strategy in user scheduling or power allocation. Furthermore, the NE in the formulated game is proved to lead to the global optimality of the network utility. Accordingly, we design an iterative searching algorithm to obtain the global optimum (i.e., the best NE) with an arbitrarily high probability in a decentralized manner, in which only local information exchange is needed. Theoretical analysis and simulation results both validate the convergence and optimality of the proposed algorithm with fairness improvement.

Voice-based human-machine interfaces are becoming a key feature for next generation intelligent vehicles. For the navigation dialogue systems, it is desired to understand a driver's spoken language in a natural way. This study proposes a two-stage framework, which first converts the audio streams into text sentences through Automatic Speech Recognition (ASR), followed by Natural Language Processing (NLP) to retrieve the navigation-associated information. The NLP stage is based on a Deep Neural Network (DNN) framework, which contains sentence-level sentiment analysis and word/phrase-level context extraction. Experiments are conducted using the CU-Move in-vehicle speech corpus. Results indicate that the DNN architecture is effective for navigation dialog language understanding, whereas the NLP performances are affected by ASR errors. Overall, it is expected that the proposed RNN-based NLP approach, with the corresponding reduced vocabulary designed for navigation-oriented tasks, will benefit the development of advanced intelligent vehicle human-machine interfaces.

Human health risks associated with drinking water chlorination disinfection have been identified, and the development of new disinfecting methods to minimize the risks with less energy and chemicals is the direction of water treatment industry. In this study, an electrochemical system was investigated for drinking water treatment in an undivided electrochemical reactor using Ti/RuO2–IrO2 anode and graphite felt cathode. The reactor configuration was designed in such a way that the angle of the electrodes was adjustable between 0° and 90°. It was found that the laboratory reactor (660 × 620 mm size) with electrodes positioned between 30° and 65° provided satisfactory results at a treatment capacity of 250 L/h water. A pilot plant test was conducted for treatment of Yellow River water using four laboratory-scale reactors in parallel, and the electrochemical treatment was compared with chemical disinfection using sodium hypochlorite, ozone, and potassium permanganate in the pilot plant facility. The ...