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Particle packing is widely applied in organic pollutant adsorption, catalytic reaction, biomass combustion, nuclear cooling, and other scenarios. Due to the complexity of the shape, the studies on the void fraction of the cylindrical particles are not as thorough as the spherical particles. This study investigated the influence of the filling rate, material properties and sphericity on the void fraction of cylinders through experiments and simulation. DEM (discrete element method) was validated by the internal structures of the packing obtained by CT (computed tomography). Based on the logarithmic correlation between the void fraction and filling rate, an ingenious framework for predicting the void fraction of cylindrical particles was presented with two intermediate coefficients. By correlating the coefficients with the material property and sphericity, a novel void-fraction prediction model was established with R-squared of 0.996. The mechanism of void fraction under random loose packing for cylinders was eventually found in this study.

Void fraction of cylindrical particles greatly influences heat and mass transfer and resistance characteristics involved in the processes. The effect of the filling rate of cylindrical particles on the void fraction of the random loose packing (RLP) was studied through the experiments. Then, the discrete element method (DEM) was used to reproduce the RLP process of the cylindrical particles, and the effect of the filling rate on the void fraction of the packing was revealed by the internal packing structure. The following conclusions can be drawn: the void fraction increased with the logarithm of the filling rate and did not change after reaching the maximum value; a void fraction prediction model of cylindrical particles, considering filling rate, was established; a larger filling rate would cause the particles to interact to form “bridge” structures, forming larger particle inclination angles and resulting in a larger void fraction of the packing.

Traffic flow prediction plays an important role in intelligent transportation applications, such as traffic control, navigation, path planning, etc., which are closely related to people’s daily life. In the last twenty years, many traffic flow prediction approaches have been proposed. However, some of these approaches use the regression based mechanisms, which cannot achieve accurate short-term traffic flow predication. While, other approaches use the neural network based mechanisms, which cannot work well with limited amount of training data. To this end, a light weight tensor-based traffic flow prediction approach is proposed, which can achieve efficient and accurate short-term traffic flow prediction with continuous traffic flow data in a limited period of time. In the proposed approach, first, a tensor-based traffic flow model is proposed to establish the multi-dimensional relationships for traffic flow values in continuous time intervals. Then, a CANDECOMP/PARAFAC decomposition based algorithm is employed to complete the missing values in the constructed tensor. Finally, the completed tensor can be directly used to achieve efficient and accurate traffic flow prediction. The experiments on the real dataset indicate that the proposed approach outperforms many current approaches on traffic flow prediction with limited amount of traffic flow data.

Community detection in dynamic networks is one of the most challenging tasks in the field of network analysis. In general, networks often evolve smoothly between successive snapshots. Therefore, the community structure detected in each snapshot should not only be of high quality but also reflect the smoothness of the variations compared with the previous snapshot. In this paper, we propose a novel incremental community-detection method named Spiderweb, which detects the community structure in each snapshot by simulating the evolution of spiderwebs. We categorize the evolutionary events of the network into three types, and then address the changed nodes and edges according to three corresponding evolution rules. In this procedure, some nodes are assigned to proper communities. Then, we construct a new subgraph for the unclassified changed nodes, and detect its communities efficiently. Finally, we merge some communities to obtain the resulting community structure. We conduct extensive experiments on both artificial networks and real-world networks to test the proposed method, and the experimental results show the superiority of the proposed method over some state-of-the-art algorithms in terms of both the quality and the temporal smoothness of the detected community structures. The proposed method provides us with a stable and promising solution for the problem of community detection in dynamic networks.

Continuous activity recognition (CAR) plays an important role in human daily indoor activity monitoring and can be widely used in smart home, human-computer interaction and user authentication. Due to the privacy issue and limited coverage of video signals, RF-based CAR has attracted more and more attention in recent years. This paper focuses on three key problems in RF-based CAR: denoising, segmentation and recognition. We present the design and implementation of a contactless and sensorless continuous activity recognition system, namely WiCheck. Our basic idea is to utilize the temporal correlation between two adjacent actions in continuous activity to eliminate the cumulative error in continuous activity segmentation. Firstly, the multi-layer optimized noise elimination method is used to decrease the environment interference. Secondly, a method based on dual-swing window is proposed to reduce the cumulative error of continuous activity segmentation. Finally, WiCheck is implemented in different indoor environments, and 6 continuous activity sequences are designed to evaluate and analyze the influencing factors. The continuous activity recognition accuracy of WiCheck to two actions and three actions can approach 90% and 75%, respectively.

Atmospheric pressure plasma processing (APPP) is proved to be potential in the fabrication of optical elements with high efficiency and near-zero damage. However, high convergence rate in the figuring process is hard to achieve because of the tool influence function (TIF) non-linearity. Directly solved dwell time map by conventional deconvolution methods does not consider the non-linear thermal effect, which leads to significant figuring error. In this paper, the optimization strategy for TIF non-linearity based on the velocity distribution in APPP is presented. The exponential model of TIF with non-linearity is established by trench experiments. A series of simulations are also conducted to analyze the thermal effect of non-linearity on the figuring process, indicating the TIF constantly changes with velocity distribution. Two evaluation parameters, relative balance factor and velocity concentration factor, are proposed to investigate the figuring capacity of calculated velocity distribution. With two evaluation parameters, the optimization strategy of velocity distribution based on TIF selection is proposed to suppress the non-linearity. Verification experiments are carried out to validate the two optimized TIFs. The results show that high convergence is achieved to be 72.41% and 82.81% for root-mean-square value respectively, which proves the feasibility of the proposed optimization strategy.

Traditional conventional air conditioners (CACs) are not applicable to nearly zero energy buildings (NZEBs), especially for residential buildings in regions with a humid climate in China. On the one hand, indoor thermal environment can be significantly affected in buildings by adopting insulations with higher thermal resistance and air tightness. On the other hand, CACs may not be able to meet the energy requirement of NZEBs when dehumidification is in high demand. Therefore, in this paper, a novel hybrid system, which featured solar panel, a multi-evaporator and multi-condenser heat pump, and a desiccant wheel, i.e., the SHDW system was proposed. The evaporator is for pre-cooling, and the desiccant wheel (DW) for handling the whole moisture load. The regeneration air of DW is heated by heat recovery condenser and the solar panel. By varying the evaporation temperature of HP, the energy performance was evaluated, and compared with that of a typical CAC, for controlling indoor temperature and humidity of a residential NZEB, using TRNSYS. The simulations were conducted for Shanghai (in a humid climate) in summer (July and August) and the transition seasons (June and September). The results showed that, first, the optimized evaporation temperature of the system is determined to be 12 °C and 9 °C, respectively, on a typical day both in summer and the transition seasons. Second, the daily coefficient of performances are 3.4 and 2.4 in summer and in transition seasons, respectively. Third, compared to either the temperature or humidity control mode of the CAC, the proposed SHDW system showed better promise for achieving indoor thermal comfort for residential NZEBs, especially in transition seasons. In a typical weekend, the daily energy consumption of the proposed SHDW system is 9.0% and 12.3% lower than that of the CAC with humidity control mode, respectively, in summer and the transition seasons.

Wireless sensor networks have played an important role in many applications, where sensors in the network can automatically collect and transmit information in an environment without much human maintenance. To enhance the adaptability of sensors, people produce mobile wireless sensors through fixing wireless sensors on mobile vehicles or robots. The same as static wireless sensors, since the energy of mobile wireless sensors is still supplied by the battery, their energy management has a great impact on their lifetime. Different with static wireless sensors, the mobility of mobile wireless sensors gives us a new perspective to achieve the efficient energy management. In this paper, a decentralized self-adaptive approach is proposed for mobile wireless sensors, which enables sensors in a mobile wireless sensor network to adapt their locations according to the information transmission regularity in the network so as to reduce their energy consumption for the information transmission. The experimental results indicate that after employed the proposed approach to adapt locations, the energy consumption for the information transmission of sensors in a mobile wireless sensor network can be greatly reduced and their lifetime is extended.

The optimal path planning is one of the hot spots in the research of intelligence transportation and geographic information systems. There are many productions and applications in path planning and navigation, however due to the complexity of urban road networks, the difficulty of the traffic prediction increases. The optimal path means not only the shortest distance in geography, but also the shortest time, the lowest cost, the maximum road capacity, etc. In fast-paced modern cities, people tend to reach the destination with the shortest time. The corresponding paths are considered as the optimal paths. However, due to the high data sensing speed of GPS devices, it is different to collect or describe real traffic flows. To address this problem, we propose an innovative path planning method in this paper. Specially, we first introduce a crossroad link analysis algorithm to calculate the real-time traffic conditions of crossroads (i.e. the $CrossRank$ values). Then, we adopt a $CrossRank$ value based $A$ - $Star$ for the path planning by considering the real-time traffic conditions. To avoid the high volume update of $CrossRank$ values, a $R$ - $Tree$ structure is proposed to dynamically update local $CrossRank$ values from the multi-level subareas. In the optimization process, to achieve desired navigation results, we establish the traffic congestion coefficient to reflect different traffic congestion conditions. To verify the effectiveness of the proposed method, we use the actual traffic data of Beijing. The experimental results show that our method is able to generate the appropriate path plan in the peak and low dynamic traffic conditions as compared to online applications.

Bonnet polishing has been widely used in structured surface generation, form correction and surface finishing. The inflated flexible tool is able to match the local surface to realize surface finishing. However, after surface finishing, the polishing induced form change is still not clear, especially for complex freeform surfaces with millimeter-level spatial periods. This paper presents a simulation and experimental study on form-preserving capability of bonnet polishing. The concept of form-preserving capability is discussed firstly. Subsequently, the relative surface speed and contact condition on ripple structures are calculated and analyzed. The results demonstrate that the contact condition of bonnet tool on structured surfaces has the main influence on form-preserving capability. Then, the influence of various factors on contact pressure difference is investigated. Compared with experimental results, the linear correlation between form change and the contact pressure difference is obtained, indicating that form-preserving capability can be strengthened by reducing contact pressure difference. Under optimal conditions, the form change can be controlled less than 20 nm, which proves the superior form-preserving capability of bonnet polishing.

Mechanofluorochromic properties of powder crystals and single crystals of photoacid-spiropyran (PASP) and tetraphenylethene-decorated Photoacid-spiropyran (PASPTPE) under ambient pressure grinding ...

Based on the pure chemical etching, atmospheric plasma processing techniques have been developed for fused silica optics fabrication, in order to achieve deterministic high rate material removal, small tool spot and no mechanical load applied. However, the surface smoothness tends to be deteriorated after etching process. Comprehensive characterization of surface topography after atmospheric plasma processing is necessary in order to understand the opacification phenomenon and etching mechanism. In this paper, a capacitively coupled atmospheric pressure plasma processing (CCAPPP) system and experimental setup are firstly presented. Chemical composition, surface topography, cross-section topography as well as quantitative surface roughness are respectively characterized and analyzed in detail. The results show that the topography difference between the transparent and the opaque area was not caused by chemical composition. The main differences in the microscopic topography were the size and density of etched cellular microstructures. The opacification phenomenon mainly resulted from the excessive roughening on the processed surface topography, causing visible light to be diffusely reflected.

Domain adaptation is proposed to improve the recognition performance of the domain shift or the dataset bias. The domain shift is a very common problem, which is caused by diverse factors, such as data capturing angles, illumination, and image quality existing in the natural scene image understanding. Since the domain shift leads to the feature distribution discrepancy, some solutions have been proposed to alleviate the distribution discrepancy by mapping feature spaces between source and target domains, so as to ensure the transferable features can be learned by the deep networks during the end-to-end training for the classification tasks. However, it is still a big challenge to address the domain shift when the distribution spaces are not clearly separated. Inspired by the adversarial idea, we propose a novel unified deep neural network architecture named the unsupervised domain adversarial adaptation deep neural network. It addresses the domain adaptation problem by learning domain-invariant features through mitigating the feature discriminative ability in the domain classification task alternatively by alleviating the feature distribution discrepancy in the main classification task. Therefore, in our proposed unified deep network, we integrate two main modules. One is an auxiliary task module for the domain classifier, which is trained to make sure the learned features are domain-invariant under the adversarial optimization strategy by minimizing the domain discriminative ability. The other is the module at task-specific layers to enhance the learning of the transferable features with the less distribution discrepancy by adding multiple maximum mean discrepancy constraints to map the features to reproducing kernel Hilbert spaces. The experimental results show that the features learned by our proposed unified deep neural network perform better than the features learned by previous cross-domain neural networks on classification tasks. Our proposed approach achieves the state-of-the-art performance on three cross-domain datasets: Office-31 (different capturing angles, illumination, and image quality), Office-Caltech (modified from Office-31) and a combined cross-domain digit dataset, including MNIST, USPS and SVHN (different style digits in each dataset).

As an innovative optical processing technology based on the chemical reaction, inductively coupled atmospheric pressure plasma processing (IC-APPP) technology has the advantages of high processing efficiency, non-mechanical damage and low cost. Inductively coupled plasma jet (ICP) can be characterized by the high temperature and enthalpy, which is the prerequisite of high material removal rate in optical processing. Thermal analysis is critical to characterize the IC-APPP of optics. Based on the energy balance theory in the low-temperature plasma processing, the heat transfer process of substrate was analyzed and boundary conditions in the model were proposed. The gas temperature of the impinging jet was obtained by the simulation of plasma jet characteristics using finite element analysis, which acts as the input to the heat transfer model of IC-APPP process. Experiments were carried out to validate the accuracy of model and thermal effect on the removal rate was analyzed for IC-APPP. Results suggest that there exist varying degrees of nonlinearity with different temperature ranges in the IC-APPP.

Inductively coupled atmospheric pressure plasma processing (IC-APPP) is a novel polishing technique for silica-based optics to quickly mitigate the surface or subsurface damage due to its high efficiency and low cost. However, theoretically uniform removal of materials is difficult to achieve because of complex thermal effect. In this paper, numerical modelling and experimental study of global temperature field in IC-APPP is presented. First, a transient heat transfer model is established using finite element analysis to study the characteristics of temperature field distribution during the process. Then, the effects of substrate geometry and processing parameters are systematically analyzed. Finally, conformal polishing experiments are carried out to illustrate the correlation between the effectiveness of uniform removal and the temperature field. The surface shape can be maintained well with optimal processing parameters in IC-APPP.

In this paper, a low loss jammed-array wideband sawtooth (JAWS) filter is built based on a finite reflection virtually imaged array (FRVIA) which has a lower reflectivity of the exit surface compared to a virtually imaged phased array (VIPA). This filter can be used as an edge filter to interrogate the fiber Bragg grating (FBG) sensors. A fast FBG sensing system is set up to detect the strain wave of iron pipe to demonstrate the use of this interrogator. The result shows that the JAWS based interrogation system has advantages of high speed, low loss and high sensitivity.

This paper addresses the issue of the wireless mobile robot deployment for the ad hoc network establishment in disaster environments, which aims to maximize the important locations covered by the established ad hoc network so as to improve the performance of task allocation. In many disaster environments, the number of wireless mobile robots usually is much less than the number of important locations in the environment so that maximizing the important locations covered by the established ad hoc network is the primary objective of wireless mobile robot deployment approaches. To maximize the coverage of important locations, most of the current approaches were developed based on greedy algorithms. Due to the myopia of greedy algorithms, these approaches can only maximize the coverage of important locations of each wireless mobile robot rather than the whole network. To this end, two mathematical programming-based wireless mobile robot deployment approaches are proposed for ad hoc network establishment in disaster environments. The proposed approach can create suitable deployment locations for all wireless mobile robots in a disaster environment. The experimental results demonstrate that ad hoc networks established by the proposed approaches can cover more important locations in a disaster environment than those established by greedy algorithm-based approaches.

A physical-based constitutive model was developed to model the viscoplastic flow behavior and microstructure evolution of AZ80 magnesium alloy during the hot working process. The competing deformation mechanisms, including work hardening, dynamic recovery, and dynamic recrystallization, in an isothermal compression environment were considered in the model. The internal state variables, including the normalized dislocation density and recrystallized volume fraction, were incorporated into the model to articulate the microstructure evolution during hot deformation. The kinetic condition critical for dynamic recrystallization, considering the effects of the deformation temperature and strain rate, was obtained by employing both the Poliak-Jonas criterion and Zener-Hollomon parameter. Microstructure observations indicate that the recrystallized volume fraction increases with decreasing Z parameter at constant strain, which is consistent with the predicted kinetics model. Based on the developed model, a good correlation was also obtained between the predicted and experimental flow stress. The results indicate a good predictability of the model in describing the hot deformation behavior and microstructure evolution of AZ80 magnesium alloy.

Stimuli-responsive fluorescent materials which can change their optical signal outputs upon changes in ambient physical or chemical parameters exhibit great application potential for comprehensive environmental monitoring. In this article, a new aggregation-induced emission fluorescent switch, 1',3′,3′-trimethyl-5′-(4-(1,2,2-triphenylvinyl)phenyl)spiro[chromene-2,2′-indoline]-6-carbonitrile (TPE-Sp-CN), was synthesized and applied in the quantitative detection of three parameters, namely pH value, sulfite anion and hydrostatic pressure, with different molecular states. According to the analysis of the optical spectra, TPE-Sp-CN can distinguish water pH values from 0 to 4, the detection limit of sulfite anion is 1.04 ppm, and the pressure sensing range is 1 atm to 6 GPa with the sensing sensitivity of a 9.876 nm GPa−1 shift in the PL spectrum. Furthermore, TPE-Sp-CN can quantitatively sense all three parameters with good linear relationships, which is rarely reported. Also, it is promising to use TPE-Sp-CN as an indicator to monitor the environment or disasters that are related to the above parameters, such as harmful geological activities.

In disasters, many stationary tasks, such as saving survivors in debris, extinguishing fire of buildings, and so on, need first responders to complete on site. In such circumstances, wireless mobile robots are usually employed to search for tasks and establish ad hoc networks to assist first responders. Due to the unknown and complexity of environments and limited capabilities of wireless mobile robots, searching and establishing ad hoc networks in disaster environments is a challenging issue in both theory and practice. To this end, a task-based wireless mobile robot deployment approach is proposed in this article. The proposed approach consists of a search process and a deployment process. The search process can guide wireless mobile robots to efficiently find tasks in unknown and complex environments. The deployment process can find suitable deployment locations for wireless mobile robots to establish ad hoc networks. The established ad hoc networks can ensure the communication of wireless mobile robots in the network and can cover the maximum number of task locations and the maximum areas in a disaster environment. Experimental results demonstrate that based on the proposed approach, wireless mobile robots have better performance in terms of search and ad hoc network establishment in disaster environments.

Recently, increasing demands on automatic soldering of flexible printed circuit boards (PCBs) have been reflected in the fast expanding computer, communication, and consumer electronics manufacturing. However, the deformation of flexible PCBs results in the changing shape and hence the varying position of solder pads on flexible PCBs under applied forces, which opens up challenges for robotic soldering of flexible PCBs. This paper presents a vision-based control scheme for robotic soldering of flexible PCBs. The proposed controller enables the robot to automatically contact, then actively deform the flexible PCB into a desired configuration, such that the well-deformed PCB can be soldered in an automatic soldering machine. Both operations of contacting and active deformation are smoothly integrated into a single continuous controller and automatically transited by assessing the physical contact online. Neural-network techniques are employed to approximate the unknown deformation model and the uncalibrated camera model. The dynamic stability of the closed-loop system is rigorously proved with Lyapunov methods, and experimental results are presented to illustrate the performance of the proposed controller.

The data abuse issue has risen along with the widespread development of the deep learning inference service (DLIS). Specifically, mobile users worry about their input data being labeled to secretly train new deep learning models that are unrelated to the DLIS they subscribe to. This unique issue, unlike the privacy problem, is about the rights of data owners in the context of deep learning. However, preventing data abuse is demanding when considering the usability and generality in the mobile scenario. In this work, we propose, to our best knowledge, the first data abuse prevention mechanism called DAPter. DAPter is a user-side DLIS-input converter, which removes unnecessary information with respect to the targeted DLIS. The converted input data by DAPter maintains good inference accuracy and is difficult to be labeled manually or automatically for the new model training. DAPter’s conversion is empowered by our lightweight generative model trained with a novel loss function to minimize abusable information in the input data. Furthermore, adapting DAPter requires no change in the existing DLIS backend and models. We conduct comprehensive experiments with our DAPter prototype on mobile devices and demonstrate that DAPter can substantially raise the bar of the data abuse difficulty with little impact on the service quality and overhead.

Biogas fermentation rate is largely affected by environment temperature, causing a much more difficult production of biogas digesters in cold winter, for most regions in China. Combining the abundant solar energy resources and biomass dry anaerobic fermentation together, solar thermal energy can guarantee the production of biogas in winter. With this method, the prediction of the appropriate fermentation temperature is required. In this study, the effect of temperature on biogas fermentation was studied. To predict the fermentation temperature, a heat transfer model of biogas fermentation based on a project in city Xuzhou, which assisted with a simple solar greenhouse, was established according to the heat transfer theory. The maximum difference between the measured and calculated fermentation temperature was 2%. The effect of biogas fermentation assisted by simple solar greenhouse in typical city of different climate zones, including severe cold region, cold region and hot summer and cold winter region, was studied with the combination of heat transfer model and temperature-based biogas production rates prediction model. The results showed that, the gas production rate of biogas fermentation increases with the increase of temperature in a certain range. Assisted by simple solar greenhouse, the biogas digester temperature is increased by 6~8°C compared with the previous one, ensuring a better daily gas production rate of 0.5~0.7m3/m3 in winter.

The construction projects in Pakistan have inherent problems of erroneous planning and schedule development. This dilemma has led to the failure of the majority of construction projects in Pakistan. Earlier researches have tried to curtail the increasing spectrum of inaccurate planning and schedule development. But not many research studies have shed light on the major factor of 2D CAD drawings interpretation problems, which are playing a key role in defective planning and scheduling. Moreover, the role of BIM, i.e., Building Information Modeling with respect to efficient planning, has not been also discussed in detail. This study has concluded a positive impact of BIM on effective planning and scheduling in the construction industry of Pakistan. About 210 responses were obtained from experienced construction professionals of Pakistan and tested via regression analysis in order to validate this argument. It has been analyzed that 2D CAD drawings are now getting primitive and 3D technology BIM is taking its place. BIM is an efficient tool for planning and scheduling. With the start of CPEC and Multi-Billion Dollar investment on infrastructure, construction industry of Pakistan needs to uplift its existing standard in order to meet with international requirements. For this purpose, BIM has been recommended. It will not only assist in attaining flawless planning but will also increase the success rate of CPEC projects in Pakistan.

With the development of 5G, device-to-device (D2D) and other technologies have emerged one after another, making the communication services faster and wider in coverage. Aiming at the problem of high computational complexity of traditional resource allocation algorithms, by studying the D2D communication network model and the spatial location relationship of users, ignoring parameters that have little impact on the calculation, a D2D resource scheduling algorithm based on location relationship is proposed and optimized system performance. Simulation results show that, compared with traditional algorithms, the proposed resource scheduling algorithm has greatly reduced algorithm complexity, and has good data transfer rate and high system capacity.

The spectroscopic properties of 3-(benzo[d]-thiazol-2-yl)-2-hydroxy-5-methoxy benzaldehyde molecule were investigated [J. Phys. Chem. A 2019, 123, 10246–10253]. The result shows that the excited-state intramolecular proton transfer (ESIPT) was driven toward the N center over the O center. In this research, the density functional theory and time-dependent density functional theory method were used to calculate molecule structures. Through our calculations, the ESIPT process toward N atom is proved to be feasible. Moreover, the emission peak we obtained of ESIPT process from the OH proton to aldehyde O atom is located at 564 nm, which is attributed to 500 nm in previous research. From the potential energy curves, the 0.35 kcal/mol energy barrier indicates the ESIPT process could occur when excited to S1 state from the OH proton to aldehyde O atom. In addition, the frontier molecular orbitals analysis and IR spectrum were also calculated. Finally, we revise the direction of BTHMB molecule, the two directions of ESIPT are both feasible when excited to S1 state.

Antifreezing gels are promising in diverse engineering applications such as structural soft matters, sensors, and wearable devices. However, the capability of fast self-healing and reversible adhesiveness still remain a huge challenge for gels at extreme temperatures. Here, we proposed a solvent-involved cross-linking system composed of polyacrylic acid, polyvinyl alcohol, borax, ethylene glycol, and water, capable of antifreezing below -90 °C. It was not only antifreezing, anticrystalline, and abundant in dynamic bonds but also highly transparent, stretchable (over 800%), and conductive over the scope of temperature from -60 to 60 °C. Moreover, this gel could self-heal within 1 min and repeatedly adhere to multiple substrates including glass, metal, and rubber with an adhesive strength greater than 18 kPa. These key functions of the gel could be mostly preserved after 5 days of storage at 70% relative humidity. It is anticipated that our research opens a new scope for high-performance extreme environment-tolerant adhesives or wearable devices.

The facial expression is diverse and various among persons due to the impact of the psychology factor. Whilst the facial action is comparatively steady because of the fixedness of the anatomic structure. Therefore, to improve performance of the action unit recognition will facilitate the facial expression recognition and provide profound basis for the mental state analysis, etc. However, it still a challenge job and recognition accuracy rate is limited, because the muscle movements around the face are tiny and the facial actions are not obvious accordingly. Taking account of the moving of muscles impact each other when person express their emotion, we propose to make full use of co-occurrence relationship among action units (AUs) in this paper. Considering the dynamic characteristic of AUs as well, we adopt the 3D Convolutional Neural Network(3DCNN) as base framework and proposed to recognize multiple action units around brows, nose and mouth specially contributing in the emotion expression with putting their co-occurrence relationships as constrain. The experiments have been conducted on a typical public dataset CASME and its variant CASME2 dataset. The experiment results show that our proposed AU co-occurrence constraint 3DCNN based AU recognition approach outperforms current approaches and demonstrate the effectiveness of taking use of AUs relationship in AU recognition.

State intervention in land supply can be a powerful tool in shaping real estate investment. Yet, few studies have examined the effect of central state intervention on land supply at the municipal level and the impact of land supply on real estate investment with respect to different tiers of prefecture-level cities in China. Varying central&ndash, local dynamics of land supply in different tiers of cities, and the often taken-for-granted relationship between land supply and real estate investment, warrant further investigation. This study aims to fill these gaps. It is found that the multi-purposed central land policy and the varying land leasing strategies adopted by different tiers of cities contribute to the varying land supply trajectories, calling for more nuanced and better-tailored central land policies that focus on the socioeconomic conditions of cities. The general significant and positive correlation between land supply and real estate investment, revealed by a panel regression analysis incorporating 280 prefecture-level Chinese cities, suggests that land supply control can function as a critical tool in governing real estate investment in China, which also sheds light on the governance and promotion of sustainable real estate markets in other parts of the world. This study also reveals a higher possibility of land speculation in first- and second-tier cities than that of low-tier cities. The nuanced correlations between land supply and real estate investment and the varying land development strategies employed in different tiers of Chinese cities imply that the effectiveness of land supply intervention in shaping healthy real estate investment may depend on local contingencies, calling for meticulous and tailored governance on land supply and real estate investment behaviors.

Based on the conceptual framework of neoliberal and post-neoliberal governance, this study explores the changing financial governance under the real estate boom-bust cycle in Ordos City, China. It finds that Ordos City’s neoliberal financial governance, featuring excessive deregulation, active public–private partnerships, market-friendly and growth-chasing institutional restructuring, land financialization, and enthusiastic state investment, has significantly contributed to the city’s real estate boom and overbuilding. In Ordos City’s post-bubble period, although preferential financial policies and deregulation persist, neoliberal financial governance has been largely curbed through reinforced governance and enhanced welfare and redistributive policy efforts such as the Housing Exchange Program. This article reiterates the essence of China’s neoliberal governance and verifies the existence of neoliberal governance in Ordos City. It also showcases the resilience of neoliberal local governing strategies in China. Nevertheless, the post-neoliberal endeavors in Ordos City, characterized by reinforced welfare and redistributive measures, and timely and effective state intervention via rigorous governance and enhanced public ownership of real estate assets for redistribution, add critical insights to the global intellectual and practical quests for post-neoliberal possibilities. Finally, this study calls for combined efforts of sustainable development policy initiatives, effective policy implementation, rigorous governance, and a mindset of sustainability for all to combat neoliberalism.

GEneral Matrix Multiply (GEMM) is the most fundamental computational kernel routine in the BLAS library. To achieve high performance, in-memory data must be prefetched into fast on-chip caches before they are used. Two techniques, software prefetching and data packing, have been used to effectively exploit the capability of on-chip least recent used (LRU) caches, which are popular in traditional high-performance processors used in high-end servers and supercomputers. However, the market has recently witnessed a new diversity in processor design, resulting in high-performance processors equipped with shared caches with non-LRU replacement policies. This poses a challenge to the development of high-performance GEMM in a multithreaded context. As several threads try to load data into a shared cache simultaneously, interthread cache conflicts will increase significantly. We present a Shared Cache Partitioning (SCP) method to eliminate interthread cache conflicts in the GEMM routines, by partitioning a shared cache into physically disjoint sets and assigning different sets to different threads. We have implemented SCP in the OpenBLAS library and evaluated it on Phytium 2000+, a 64-core AArch64 processor with private LRU L1 caches and shared pseudo-random L2 caches (per four-core cluster). Our evaluation shows that SCP has effectively reduced the conflict misses in both L1 and L2 caches in a highly optimized GEMM implementation, resulting in an improvement of its performance by 2.75% to 6.91%.

Clinical diagnostic assays that monitor redox enzyme activity are widely used in small, low-cost readout devices for point-of-care monitoring (e.g., a glucometer); however, monitoring non-redox enzymes in real-time using compact electronic devices remains a challenge. We address this problem by using a highly scalable nanogap sensor array to observe electrochemical signals generated by a model non-redox enzyme system, the DNA polymerase-catalyzed incorporation of four modified, redox-tagged nucleotides. Using deoxynucleoside triphosphates (dNTPs) tagged with para-aminophenyl monophosphate (pAPP) to form pAP-deoxyribonucleoside tetra-phosphates (AP-dN4Ps), incorporation of the nucleotide analogs by DNA polymerase results in the release of redox inactive pAP-triphosphates (pAPP3) that are converted to redox active small molecules para-aminophenol (pAP) in the presence of phosphatase. In this work, cyclic enzymatic reactions that generated many copies of pAP at each base incorporation site of a DNA template ...

This paper addresses the problem of multi-objective coalition formation for task allocation. In disaster rescue, due to the dynamics of environments, heterogeneity and complexity of tasks as well as limited available agents, it is hard for the single-objective and single (task)-to-single (agent) task allocation approaches to handle task allocation in such circumstances. To this end, two multi-objective coalition formation for task allocation models are proposed for disaster rescues in this paper. First, through coalition formation, the proposed models enable agents to cooperatively perform complex tasks that cannot be completed by single agent. In addition, through adjusting the weights of multiple task allocation objectives, the proposed models can employ the linear programming to generate more adaptive task allocation plans, which can satisfy different task allocation requirements in disaster rescue. Finally, through employing the multi-stage task allocation mechanism of the dynamic programming, the proposed models can handle the dynamics of tasks and agents in disaster environments. Experimental results indicate that the proposed models have good performance on coalition formation for task allocation in disaster environments, which can generate suitable task allocation plans according to various objectives of task allocation.

The properties of a traditional inductively coupled plasma (ICP) jet, such as temperature and velocity, cannot satisfy the engineering application requirements in optical fabrication. Therefore, a conical nozzle was proposed to obtain a low-temperature jet with high stiffness and meet the requirements. Furthermore, the effects of the nozzle geometry on the plasma jet properties were analyzed. First, a numerical model was developed for ICP discharged from the nozzle into the ambient air. Second, the model was validated by comparing the computed temperature with three sets of experiments. A good agreement was obtained between the computed results and the experimental values, and the accuracy of the model was demonstrated. Subsequently, the properties of an argon plasma jet discharging from the nozzle into the air were examined by using the developed model. The effects of entrainment of cold air on the jet properties were also analyzed. The results indicated that the jet properties are considerably affected by entrainment of the air. Finally, the effects of nozzle geometry, such as length of the convergent section and the nozzle exit radius, on the jet properties were analyzed using single-factor simulations. An orthogonal study was then conducted for further optimization of the nozzle structure.

Fluorescent molecular switches have great application potential in sensing and data storage. Materials that exhibit fluorescence switching properties both in solution and in solid state cannot be easily synthesized because of the contrasting ACQ and AIE effects. Herein, a dyad of pyrene-decorated spiropyran was designed via single bond linkage, and the material exhibited solvent polarity-correlated blue to green emission in solution and blue emission in solid state, although neither pyrene nor spiropyran emit in the visible light region. Acidic conditions could trigger the isomerization of spiropyran moiety to the protonated merocyanine (MCH) form accompanied by the disappearance of emission in solution. Crystalline Py–MCH exhibited red/dark “on/off” fluorescent switch upon grinding. Moreover, acid sensing and reversible fluorescent display were demonstrated based on Py–Sp-doped polymer nanofibers and films utilizing stimuli-responsive emission switching property.

Non-invasive fluorescent molecular switch is very challenging to achieve in solid state. Here, a new multi-stimulus-responsive fluorescent molecular switch of SPPATPE was prepared by linking spiropyran-photoacid (SPPA) with tetraphenylethene (TPE). The isomerization of SPPATPE can be triggered with either visible light/dark or acid/base in solution. Both ring-closed form (RCF) and ring-open form (ROF) of SPPATPE exhibit aggregation-induced emission (AIE). The RCF SPPATPE aggregates give out a cyan emission, which is assigned as the local excited emission of TPE moiety, while ROF SPPATPE have two forms of aggregation states, which give out two red emissions from intramolecular charge transfer. By selecting a suitable polymer of polyvinyl pyrrolidone (PVP) as the matrix, which gives the molecules a moderate alkaline environment, SPPATPE can exhibit non-invasive light/heat responsive emission switch in the polymer thin film with both good waterproofness and good processibility, which makes this kind of hybrid material potentially applicable in photo sensing, rewritable display, etc.

In this work, we use density functional theory and time dependent density functional theory to explore the ESIPT and TICT process of 6-(1H-Benzoimidazol-2-yl)-2,3-dimethoxy-phenol (BIDOP) in cyclohexane (CHX) and tetrahydrofuran (THF) solvent, respectively. It reveals that ESIPT process of BIDOP can occur in both CHX and THF solvent at the first excited state with similar reaction barrier. Remarkably, compared to barrierless from keto (K*) to TICT state of BIDOP in THF solvent, the reaction barrier between K* and TICT state is up to 20.28 kcal/mol for in CHX that TICT process is inhibited in CHX solvent. The absence of nonradiative decay TICT state of BIDOP in CHX solvent induces higher fluorescence in CHX compared to in THF solvent. These findings indicate that CHX solvent can effectively enhance fluorescence of BIDOP. Our study highlights a convenient approach for enhancing fluorescence and is significant for photophysics and photobiology field.

COVID-19 has caused a huge impact on people’s daily life and has made great damage on national economy. All the epidemic situation not only require the improvement of medical science, but also the corresponding auxiliary research field, e.g. the improve of protective clothing for medical use (MUPC). Developing a new kind of MUPC with portable cooling devices to improve medical workers’ thermal comfort and protection performance of MUPC is imminent. In this paper, an integrated MUPC with a portable vortex tube cooling device was studied with experimental method. In a phytotron, a manikin wearing the MUPC was experimentally studied in terms of the influence of environment temperature and cool air supply conditions. On the basis of experiments, the MUPC inside air temperature and relative humidity, skin temperature of human body was studied with simulation method. Overall thermal sensation vote (TSV) and local TSV of human body were calculated, based on simulation results, to evaluate human thermal sensation. The results showed that, first, 50 L/min cool air flowrate with 18–20 °C supply temperature can create a good MUPC inside thermal sensation environment, for both head supply and body supply conditions. Both body supply condition and head supply condition cannot create a uniform MUPC inside thermal sensation environment. Second, MUPC inside air relative humidity is around or lower than 60% for most body parts, except for air supply position and body parts that air is difficult to reach. Thirdly, with cool air supplied into MUPC, a micro-positive pressure environment can be obtained, and the protection performance of MUPC can be improved.

Adsorption desalination is an emerging method to address the shortage of fresh water. To achieve its energy-saving potentials, a renewable low-temperature heat source is the key. This paper focuses on the area optimization of solar collectors in combined solar heating systems that supply heat for adsorption desalination, aiming at achieving the maximum economic benefits during the lifespan of a project. The optimum tilt angle was discussed and the corresponding daily radiation data were calculated with HDKR (Hay, Davies, Klucher, Reindl) model. The area optimization function was proposed with the unit costs of fresh water as the optimization objective. A reference area calculated according to annual solar radiation was employed to describe the optimization results. Then the influences of the price of auxiliary energy sources, the performance ratio of adsorption desalination, and the heat loss of solar heating on the optimization results were studied with an actual adsorption desalination project in Tianjin. It has been found that the optimal area is positively associated with the auxiliary energy price, however approximately inversely proportional to the performance ratio of desalination and the energy efficiency of solar heating. The unit costs of producing fresh water can be reduced up to 20% after collector area optimization when the auxiliary energy is expensive. Besides, the overall costs of utilizing solar heating to supply heat for adsorption desalination is around 0.03–0.04 CNY/MJ which is lower than conventional energy sources. We also tested the optimization results with an altered precision of radiation data and different meteorological conditions. Findings in this paper proved the advantages of incorporating solar heating in adsorption desalination and provided instructions for designing solar adsorption desalination projects.

Highly stretchable and highly resilient polymer-clay nanocomposite hydrogels were synthesized by in situ polymerization of acrylamide in the presence of pristine montmorillonite (MMT) or chitosan-treated MMT nanoplatelets at an elevated temperature. Both nanocomposite hydrogels can be stretched to a strain of no less than 1290%. The treatment of clay with chitosan improves the tensile strength, elongation at break, and energy at break of the nanocomposite hydrogel by 237%, 102%, and 389%, respectively, due to the strong chitosan-MMT electrostatic interaction and the grafting of polyacrylamide onto chitosan chains. Both hydrogels display excellent resilience with low hysteresis; with a maximum tensile strain of 50%, ultralow hysteresis is found, while, with a maximum strain of 500%, both hydrogels fully recover their original state in just 1 min. The superb resilience of the nanocomposite hydrogels is attributed to the strong interactions within the hydrogels brought by chain branching, multiple hydrogen bonding, covalent bonding, and/or electrostatic force. The hydrogels can be fabricated into different shapes and forms, including microfibers spun using pressurized gyration, which may find a variety of potential applications in particular in healthcare.

A time-domain method for calculating the defect states of scalar waves in two-dimensional (2D) periodic structures is proposed. In the time-stepping process of the proposed method, the column vector containing the spatially sampled field values is updated by multiplying it with an iteration matrix, which is written in a matrix-exponential form. The matrix-exponential is first computed by using the Suzuki's decomposition based technique of the fourth order, in which the FloquetBloch boundary conditions are incorporated. The obtained iteration matrix is then squared to enlarge the time-step that can be used in the time-stepping process (namely, the squaring technique), and the small nonzero elements in the iteration matrix is finally pruned to improve the sparse structure of the matrix (namely, the pruning technique). The numerical examples of the super-cell calculations for 2D defect-containing phononic crystal structures show that, the fourth order decomposition based technique for the matrix-exponential computation is much more efficient than the frequently used precise integration technique (PIT) if the PIT is of an order greater than 2. Although it is not unconditionally stable, the proposed time-domain method is particularly efficient for the super-cell calculations of the defect states in a 2D periodic structure containing a defect with a wave speed much higher than those of the background materials. For this kind of defect-containing structures, the time-stepping process can run stably for a sufficiently large number of the time-steps with a time-step much larger than the CourantFriedrichsLewy (CFL) upper limit, and consequently the overall efficiency of the proposed time-domain method can be significantly higher than that of the conventional finite-difference time-domain (FDTD) method. Some physical interpretations on the properties of the band structures and the defect states of the calculated periodic structures are also presented.

A comparative assessment of external and internal insulation for an intermittent air-conditioned bedroom was performed numerically. A bedroom in Shanghai was used for the numerical calculations and two operation modes were assumed. The energy for the on-periods and the thermal comfort index during the off-periods were used to evaluate the exterior walls insulation configurations. The study shows that, the energy used for heating was significantly reduced by adding insulation layers on the surfaces of the exterior walls. The energy used for cooling was also decreased with the increasing insulation layers even though the exterior walls insulation seems have little impact on the amount of energy decreased. The external insulation configuration gave better thermal performance compared to internal insulation configuration, when measured by both the annual cooling and heating energy requirements. Using the thermal comfort index as criterion, for a given total thickness of insulation layer, the better performance was obtained when placing the insulation layers at the outdoor surface.

This paper examines the dynamic behaviour of stiffening rings reinforced tubular T-joints with precompression chord by means of experimental studies. An experimental programme involved one test on unstiffened tubular T-joint and three on stiffened configurations is carried out through a high-performance drop hammer machine. A series of disc springs is installed to apply axial compression to the chord. The dynamic response of four tubular T-joints are described and discussed with emphasis on the dimensional parameters of stiffening rings. Based on the experimental results, the key behavioural patterns including the development of impact force, deformation and strain, as well as deformation modes are identified. In general, the presence of stiffening rings significantly improves the impact resistance of tubular T-joints.

Biogas digesters have recently been used as an alternative cooking fuel for some rural families in China. Biogas production by digesters is considerably affected by fermentation temperature. Soar energy can be used to improve the biogas production rates in winter in cold climate zone of China. A thermal balance model is developed to compute the fermentation temperature by ambient temperature and solar radiation for simple sunlight greenhouse assisted biogas project, a series of field experiments on a biogas project in Xuzhou, China was conducted to investigate the thermal performance of biogas digesters and to validate the model, the average temperature rise between the inside and ambient is over 10 °C in winter.

As the heat releas of equipment in metro system has rarely been measured before, the cooling load of equipment stations is often overestimated in the design stage of air conditioning system, which causes the overlarge equipment selection, unit configuration and results in a great waste of energy and economy. In this study, the actual cooling load is analyzed based on onsite measurement in metro systems, including electric control room, communication equipment room, communication power room, signal equipment room, traction network room, traction transformer room, high voltage switch cabinet room, step-down transformer substation and other equipment rooms. The results show that the actual cooling load of high voltage switch cabinet is only 21.21% as design load, for communication equipment room and traction transformer room is 41.51% and 46.43%, respectively. The actual cooling load of all equipment rooms is only 42.33% as design load. The sensible heat ratio of equipment rooms in metro system ranged from 30% to 70% in general. Moreover, it was proved that the piston wind and unbalanced air volume can increase latent cooling load and decrease the sensible heat ratio.

When assessing the environmental impact of a product or system, the life cycle assessment (LCA) is one of the most accepted methods. However, LCA relies heavily on the fundamental data sources, especially for energy related inventory database. The energy related inventory database is the basis of life cycle assessment for a product or system. Due to the great variety and the frequent updates of the energy related inventory database, the effect of temporal variables on life cycle inventory results should be quantified and interpreted in LCA case studies. In this study, a life cycle greenhouse gas (GHG) emissions calculation model for various energy sources is developed, and the life cycle GHG emissions of six types of energy in China in 2003 and 2013 are calculated and compared. There are significant reductions of 10.60–33.40% for different types of energy when using database of 2013 compared to 2003. To fill the temporal gaps, we develop a generic methodology for screening out the key temporal parameters in life cycle inventory analysis of energy upstream. Nine key temporal parameters related to the life cycle GHG emissions of six types of energy are screened out by sensitivity analysis coupled temporal variability analysis. The update interval of these parameters is quantified and suggested to ensure the reliability of analysis results. This methodology can help to reduce the maintenance workload of the database, and to provide a foundation for improving the reliability of life cycle analysis results for a product or system.

The increasing demand for precision optical components invokes the requirement of advanced fabrication techniques with high efficiency. Atmospheric pressure plasma processing (APPP), based on chemical etching, has a high material removal rate and a Gaussian-shaped influence function, which is suitable to generate complex structures and correct form errors. Because of the pure chemical etching, an optically smooth surface cannot be achieved using only APPP. Thus, bonnet polishing (BP) with a flexible membrane tool, also delivering a Gaussian influence-function, is introduced to smooth the surface after APPP. In this paper, the surface texture evolution in the combined process of APPP and BP is studied. The etched texture with increased removal depth of APPP is presented and analyzed. Subsequently, the processed substrates are smoothed by BP. The texture smoothing and the roughness improvement is investigated in detail. The experimental results show that the APPP etched pits coalesce with each other and transform into irregular convex-concave structures, with roughness degraded to about 25 nm arithmetical mean deviation (Ra). The APPP etched texture can be successfully smoothed to 1.5 nm Ra, with 0.2&ndash, 1 &mu, m material removal of BP.

In recent years, communication radar integration research has received extensive attention. The communication radar system based on waveform multiplexed signals has a high degree of integration, and it is one of the hotspots in communication radar integration research direction. In this paper, a communication radar integrated signal of MCPC (Multi-carrier Complementary Phase-coded) based on Costas coding is proposed. By analyzing the ambiguity function of MCPC signal, we can know that the system using this signal has excellent radar detection capability. The subcarriers of the signal are encoded by Costas array, enabling them to carry communication information efficiently. The simulation results show that the communication radar integrated system using this signal has better radar detection and communication capabilities, which can meet the needs of practical applications.

A multi-aperture atmospheric pressure plasma processing (APPP) method was proposed to structure the continuous phase plate (CPP). The APPP system was presented and removal investigation showed the removal function of APPP was of a high repeatability and robustness to the small disturbance of gas flows. A mathematical model for the multi-aperture structuring process was established and the simulation analysis indicated the advantages of the proposed method in terms of balancing the efficiency and accuracy of the process. The experimental results showed that multi-aperture APPP has the ability to structure a 30 mm × 30 mm CPP with the accuracy of 163.4 nm peak to valley (PV) and 31.7 nm root mean square (RMS).

This paper discusses the selective maintenance of industrial robots. Propose a working mode to keep missions uninterrupted and maintain high reliability within a limited time resource. During the execution of multiple missions, each mission selects a reasonable amount of robots to work, and the rest robots are for maintenance with a level or standby. The choice of robot needs to consider time, cost, reliability, and mission requirements. The fundamental constructs and the relevant parameters of this decision-making problem are developed and discussed. A mathematical optimization model is then proposed where the objective is to maximize the reliability of executing the next mission, taking into account both budget and time maintenance constraints. A numerical example is provided to demonstrate this method is reasonable.