Search

An increasing number of studies examined the potential effects of PM1 (submicronic particulate matter with an aerodynamic diameter ≤ 1 μm) on the risk of respiratory diseases; however, the results have been inconclusive. This study aimed to determine the overall association between PM1 with total and cause-specific respiratory diseases. A systematic review and meta-analysis was conducted with 68 related articles retrieved, and six articles met the full inclusion criteria for the final analysis. For a 10 μg/m3 increase in PM1, the pooled odds ratio (OR) was 1.05 (95% CI 0.98–1.12) for total respiratory diseases, 1.25 (95% CI 1.00–1.56) for asthma, and 1.07 (95% CI 1.04–1.10) for pneumonia with the I2 value of 87%, 70%, and 0%, respectively. Subgroup analyses showed that long-term exposure to PM1 was associated with increased risk of asthma (OR 1.47, 95% CI 1.33–1.63) with an I2 value of 0%, while short-term exposure to PM1 was not associated with asthma (OR 1.07, 95% CI 0.89–1.27) with the I2 value of 0%. Egger’s test showed that publication bias existed (P = 0.041); however, the funnel plot was symmetrical with the inclusion of the moderator. In conclusion, elevated levels of PM1 may increase morbidity in total and cause-specific respiratory diseases in the population.

A plasmon resonance sensor (SPR) based on D-shape photonic crystal fiber (PCF) is proposed to realize the simultaneous measurement of refractive index (RI) and temperature. The upper surface of the D-shape PCF is coated with gold film as a plasmon resonance excitation material for the detection of RI. An air hole near the fiber core is coated with gold film and filled with temperature-sensitive liquid ethanol to detect temperature. Results show that the y-polarized peaks supported only shift with RI variation and is unaffected by the temperature floating. Similarly, the x-polarized peak is only influenced by the change of temperature in the external environment. The proposed sensor achieved wavelength sensitivity of 3940nm/RIU with analyte RI between 1.35 and 1.40, and 1.075nm/°C of temperature ranging from 20°C to 60°C. The proposed liquid-filled D-shape photonic crystal fiber will have potential application in solving the problem of cross-sensitivity of temperature and RI.

More and more studies found that mental health was closely related to interpersonal relationships. But it is a recent topic that utilizing social network analysis (SNA) to qualify individuals’ interpersonal relationships. Therefore, this study aimed to explore the relationships between undergraduates’ class interpersonal relationships and mental health from a perspective of social network analysis. 481 participants (165 males, 316 females) from the first, second and third year of bachelor’s degree completed the Mental Health Scale for College Students (MHS-CS) and the Social Network Questionnaire (SNQ). Data was analyzed in UCINET 6, Mplus 8.0 and IBM SPSS 25.0. The results of latent profile analysis (LPA) showed that undergraduates’ class interpersonal relationships can be classified into three types, which are the common type, the passive type and the active type. And the results of one-way ANOVA showed that the common group had the highest level of mental health than the other two groups (p = 0.001). In conclusion, SNA provides a new way to qualify undergraduates’ class interpersonal relationships. And the findings of the current study suggests that in the class interpersonal communications of undergraduates, only moderate activity and popularity were positively associated with mental health.

The full-spectrum white light-emitting diode (LED) emits light with a broad wavelength range by mixing all lights from multiple LED chips and phosphors. Thus, it has great potentials to be used in healthy lighting, high resolution displays, plant lighting with higher color rendering index close to sunlight and higher color fidelity index. The spectral power distribution (SPD) of light source, representing its light quality, is always dynamically controlled by complex electrical and thermal loadings when the light source operates under usage conditions. Therefore, a dynamic prediction of SPD for the full-spectrum white LED has become a hot but challenging research topic in the high quality lighting design and application. This paper proposes a dynamic SPD prediction method for the full-spectrum white LED by integrating the SPD decomposition approach with the artificial neural network (ANN) based machine learning method. Firstly, the continuous SPDs of a full-spectrum white LED driven by an electrical-thermal loading matrix are discretized by the multi-peak fitting with Gaussian model as the relevant spectral characteristic parameters. Then, the Back Propagation (BP) and Genetic Algorithm-Back Propagation (GA-BP) NNs are proposed to predict the spectral characteristic parameters of LEDs operated under any usage conditions. Finally, the dynamically predicted spectral characteristic parameters are used to reconstruct the SPDs. The results show that: (1) The spectral characteristic parameters obtained by fitting with the Gaussian model can be used to represent the emission lights from multiple chips and phosphors in a full-spectrum white LED; (2) The prediction errors of both BP NN and GA-BP NN can be controlled at low level, that is to say, our proposed method can achieve a highly accurate SPD dynamic prediction for the full-spectrum white LED when it operates under different operation mission profiles.

Simple Summary Natural killer (NK) cell-based cancer therapies have substantially reshaped modern strategies for clinical cancer treatment and have improved outcomes for countless patients, notably in hematologic malignancies. Unfortunately, its efficacy is limited against solid tumors due to poor infiltration and persistence in the tumor microenvironment. In this study, we show that peripheral blood mononuclear cell-derived NK cell cytotoxicity and persistence can be greatly enhanced to provide highly potent and durable anti-tumor activity through expansion in a feeder cell free-expansion system. Importantly, we show expanded-NK efficacy against three distinct forms of ovarian cancer in mouse models (i.e., solid tumors, abdominal metastatic tumors, and ascites). Abstract Natural killer (NK) cells have shown great therapeutic potential against a wide range of cancers due to their pan-specific target recognition. Numerous reports indicate that NK cell immunotherapy is an effective therapeutic approach for treating hematological malignancies, but shows limited effects against solid tumors. In this study, several models of ovarian cancer (OC) were used to test the anti-cancer effects of NK cells derived from human peripheral blood mononuclear cells and expanded using a feeder cell-free expansion system (eNKs). The results show that eNKs exhibit potent inhibitory activity on tumor growth in different ovarian cancer xenograft mice (i.e., solid tumors, abdominal metastatic tumors, and ascites), importantly, in a dose-dependent manner. Moreover, adoptive transfer of eNKs resulted in significant reduction in ascites formation in OC peritoneal tumor models, and especially in reducing intraperitoneal ascites. We found that eNKs could migrate to the tumor site, retain their activity, and proliferate to maintain high cell counts in cutaneous xenograft mice. In addition, when increased the infusion with a high dose of 12 × 107 cells/mouse, Graft-versus-host disease could be induced by eNK. These data show that eNK cell immunotherapy could be a promising treatment strategy for ovarian cancers, including solid tumors and ascites.

The transformation of old and new kinetic energy emphasizes that Chinese universities should actively set up and develop a number of new engineering majors on the one hand, and promote the reform and innovation of existing engineering majors on the other hand. The transformation of new and old kinetic energy is essentially the innovation and transformation of talent training mode. Software engineering is a course offered by most colleges and universities. However, each school's talent training program, specific implementation process and final training effect are different. Starting from the teaching practice of software engineering education, based on the analysis of international software engineering professional norms and teaching practice, this paper gives the curriculum system of software engineering major in engineering colleges, focuses on setting up the teaching concept of software engineering and cultivating the ability of software system construction, and discusses the innovative setting scheme of software engineering courses in detail, which can provide reference for international and domestic software engineering teaching plan designers.

Background The association between ozone and ischemic stroke has been widely reported; however, the association among patients with type 2 diabetes (T2D) has remained largely unknown. Methods The time series data of daily morbidity and concentrations of ozone from 2014 to 2018 were collected in Beijing, China. A time-stratified case-crossover study combined with a distributed lag nonlinear model was used to estimate the ozone effect on stroke morbidity among T2D patients. Based on principal diagnosis, ischemic stroke cases were identified according to the International Classification of Diseases (I63), and a history of T2D was coded as E12. Results A total of 149,757 hospital admissions for ischemic stroke among T2D patients were recorded in Beijing. Approximately U-shaped exposure-response curves were observed for ozone and ischemic stroke morbidity among T2D patients. With a reference at 54.91 μg/m3, extreme-low (5th: 9.59 μg/m3) ozone was significantly associated with a decreased risk for ischemic stroke [RR = 0.88, 95% confidence interval (CI): 0.80–0.98]. Subgroup analysis showed that extremely low-ozone (5th) level only had a significant protective effect in males and elderly population, with a RR value of 0.86 (95% CI: 0.76–0.97) and 0.85 (95% CI: 0.75–0.96), respectively. Extreme-high ozone (99th: 157.06 μg/m3) was significantly associated with an increased risk for ischemic stroke (RR = 1.33, 95% CI: 1.12–1.57). The effect size was 1.34 (95% CI: 1.10–1.63) for males and 1.32 (95% CI: 1.07–1.63) for females, and the difference was not significant (Z = -0.29, P = 0.77). The effect size in younger adults was significantly higher than that in participants aged ≥65 years [1.52 (95% CI: 1.21–1.91) vs. 1.22 (95% CI: 1.01–1.47), Z = -1.62, P Conclusions U-shaped associations were observed between ozone and ischemic stroke morbidity in T2D patients. Men and elderly population are vulnerable to low-ozone level, and the younger adults are more susceptible to extremely high-ozone level than the elderly.

Background: Scientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. Methods: A two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM2.5 and PM10 were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. Results: A total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM2.5 corresponded to 1.91% (95% CI: 1.33–2.49%), 2.16% (95% CI: 1.08–3.25%), and 1.92% (95% CI: 1.46–2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0–8 days, lag 8 days, and lag 8 days. The effect size of PM2.5 was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P

Social media networks have shown rapid growth in the past, and massive social data are generated which can reveal behavior or emotion propensities of users. Numerous social researchers leverage machine learning technology to build social media analytic models which can detect the abnormal behaviors or mental illnesses from the social media data effectively. Although the researchers only public the prediction interfaces of the machine learning models, in general, these interfaces may leak information about the individual data records on which the models were trained. Knowing a certain user’s social media record was used to train a model can breach user privacy. In this paper, we present SocInf and focus on the fundamental problem known as membership inference. The key idea of SocInf is to construct a mimic model which has a similar prediction behavior with the public model, and then we can disclose the prediction differences between the training and testing data set by abusing the mimic model. With elaborated analytics on the predictions of the mimic model, SocInf can thus infer whether a given record is in the victim model’s training set or not. We empirically evaluate the attack performance of SocInf on machine learning models trained by Xgboost, logistics, and online cloud platform. Using the realistic data, the experiment results show that SocInf can achieve an inference accuracy and precision of 73% and 84%, respectively, in average, and of 83% and 91% at best.

Recent years have witnessed a rapid development of sources for intense terahertz (THz) pulses and an increasing number of their applications. The advent of laser pulses with intensities in excess of $10^{18}$ W/cm2 offers an immense opportunity for generating extremely energetic THz pulses from laser-produced plasmas. This paper will review recent progress in the study of THz radiation generated from relativistically intense laser–plasma interactions, mainly focusing on the underlying THz generation models under different laser and plasma parameters, albeit still not yet fully explored. Various THz generation scenarios are discussed associated with laser-excited waves in plasmas, the transport and emission of laser-accelerated electrons, and structured targets.

The illuminance index has been widely used in the field of photometry, although the luminance contains more information on not only light intensity but also light direction. In this study, we clarify which photometric index is more competent to describe the influence of lighting environment on human eye. In this study, we propose a novel methodology to investigate the photo-biological effect of the lighting environment by human factor experiment. With the human factor experiments performed on 20 participants, we compare the variations of ocular responses during the Landolt-rings-counting visual task in lighting environments with similar illuminance while distinct luminance changes. With the same Correlated Color Temperature (CCT) and Spectral Power Distribution (SPD), optical performances with similar illuminance values present quite different influences on ocular responses, and the response variations are found to vary with luminance values. It is implied that the regularity of luminance influence on the ocular responses to lighting environment is likely to be dependent on luminance value instead of illuminance, and the photometric index luminance seems more appropriate to be used to assess the lighting quality in standards.

As a typical safety-critical cyber-physical system, the brake-by-wire system, which provides improved control and enhanced performance, shows promise as an automotive braking scheme. In addition, the BBW system can be incorporated into all types of vehicles, including conventional vehicle with an internal combustion engine, electrified vehicles, and intelligent vehicles. However, the high cost and complexity of existing BBW systems limit their usage. In this paper, we consider a novel BBW system that we have developed, which has the advantages of having a simple structure and low cost. To enhance control accuracy of hydraulic pressure modulation and reduce noise, two pressure modulation methods, namely, the hydraulic pump based pressure modulation (HPBPM) and the close-loop pressure-difference-limiting (CLPDL) modulation, were proposed. So as to demonstrate the performance of the proposed approach, hardware-in-the-loop (HiL) experiments were conducted. The experimental results indicated that the proposed BBW system, which incorporates the CLPDL control method, appears to be a promising system in terms of overall performance, including control performance, noise reduction, and system simplification. Accepted version

As the penetration of renewable energy increases a lot, the needs for novel grid topology and control strategy attracts researches. The breakthrough of power electronics makes the power transformation between multiple voltage levels or different current forms easier and cost lower. As for typical commercial building with on-site generation, this paper proposed a novel optimization method for power flow assigned to parallel- connected converters between two voltage levels for DC distribution. By the utilization of Lagrange Multiplier Method, the energy management system for those converters are corrected. In addition, several popular energy efficiency definitions are compared and analysed for choosing the most accurate one to carry on system evaluation. By combining normalized value of economic and efficiency index, the weighting factor based metric is used to compare the conventional AC distribution and DC distribution. Based on the time sequential simulation, the results show that under such novel optimization strategy, the energy efficiency is increased by 3.83% while the grid electricity saving is about 75.53 MWh accounting for 5% of the total annual load consumption.

Background: The association between gaseous pollutants and cerebrovascular morbidity has been widely studied; however, the association in patients with type 2 diabetes has remained unknown in developing countries.Methods: A time-stratified case-crossover design combined with a distributed lag nonlinear model was adopted to estimate the short-term effects of gaseous pollutants (nitrogen dioxide [NO2], sulfur dioxide [SO2], ozone [O3], and carbon monoxide [CO]) on cerebrovascular cases among patients with type 2 diabetes in Beijing. In addition, our study explored the variability across sex and age groups.Results: A total of 223,216 (male 57.6% and elderly 61.7%) cerebrovascular cases were reported from 2014 to 2018. The cumulative exposure-response curves were U-shaped for NO2, J-shaped for SO2, and V-shaped for O3 and CO. Extreme low-O3, low-CO and high-CO increased the risk of cerebrovascular morbidity, with the maximum relative risk (RR) of 1.14 (95% CI: 1.01-1.28) (1st vs median), 1.02 (95% CI: 1.01-1.03) (1st vs median) and 1.25 (95% CI: 1.09-1.45) (99th vs median), respectively, appearing at lag0-13. Elderly individuals aged over 65 years were susceptible to extremely low-O3 (maximum RR: 1.27, 95% CI: 1.08-1.48). Men and elderly individuals were more susceptible to extremely high-CO, and the maximum RR was 10% [1.31 (1.11-1.54) vs. 1.19 (1.00, 1.41)] and 26% higher [1.41(1.17-1.69) vs. 1.12 (0.97, 1.30)] than women and adults, respectively. Conclusions: NO2, SO2, O3 and CO presented nonlinear and lagged effects on cerebrovascular disease among patients with type 2 diabetes, which may vary by sex and age. Our study added to the limited evidence for the risk of cerebrovascular disease due to gaseous pollutants among patients with comorbid type 2 diabetes.

Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of the water distribution process. Especially for the watershed including irrigation area with multiple water sources and water users, it is complicated that the joint risk among available water from each water source and multi-uncertainties under water resource allocation among multiple water users. In this research, an approach is developed that a copula-based interval multi-stage fuzzy stochastic programming (CIMFSP) model. This research aims at figuring out the planning of a case study for water-resources management. In the multi-sources water supply subsystem, the copula function is introduced to tackle the interaction of water availability between two water sources (i.e., A &B). Joint risk was set 0.05, 0.10, 0.15 to reflect the shortage risk of total available water at diverse levels. An interval parameter multi-stage fuzzy stochastic programming (IMFSP) model is developed for water resource distribution in a multi-users water-demand subsystem. Through this model, uncertainties presented as interval numbers and probability distributions, as well as fuzzy sets, were handled. The dynamics of the entire water resource system can be reflected by multi-stage discrete trees. A series of solutions can be generated under multiple scenarios (i.e., joint risk and α-cut levels). The modeling results will produce a series of alternatives under a battery of scenarios and help the decision-makers get an insight into the tradeoff between the system economic benefit and financial penalties under the corresponding risk level. This approach is valuable for improving the feasibility of optimal results in the watershed with irrigation region water resource management.

To compare image quality and lesion diagnosis between reduced-dose abdominopelvic unenhanced computed tomography (CT) using deep learning (DL) post-processing and standard-dose CT using iterative reconstruction (IR).Totally 251 patients underwent two consecutive abdominopelvic unenhanced CT scans of the same range, including standard and reduced doses, respectively. In group A, standard-dose data were reconstructed by (blend 30 %) IR. In group B, reduced-dose data were reconstructed by filtered back projection reconstruction to obtain group B1 images, and post-processed using the DL algorithm (NeuAI denosing, Neusoft medical, Shenyang, China) with 50 % and 100 % weights to obtain group B2 and B3 images, respectively. Then, CT values of the liver, the second lumbar vertebral centrum, the erector spinae and abdominal subcutaneous fat were measured. CT values, noise levels, signal-to-noise ratios (SNRs), contrast-to-noise ratios (CNRs), radiation doses and subjective scores of image quality were compared. Subjective evaluations of low-density liver lesions were compared by diagnostic results from enhanced CT or Magnetic Resonance Imaging.Groups B3 and B1 showed the lowest and highest noise levels, respectively (P 0.001). The SNR and CNR in group B3 were highest (P 0.001). The radiation dose in group B was reduced by 71.5 % on average compared to group A. Subjective scores in groups A and B2 were highest (P 0.001). Diagnostic sensitivity and confidence for liver metastases in groups A and B2 were highest (P 0.001).Reduced-dose abdominopelvic unenhanced CT combined with DL post-processing could ensure image quality and satisfy diagnostic needs.

Intense terahertz (THz) electromagnetic fields have been utilized to reveal a variety of extremely nonlinear optical effects in many materials through nonperturbative driving of elementary and collective excitations. However, such nonlinear photoresponses have not yet been obeserved in light-emitting diodes (LEDs), let alone employing them as fast, cost-effective, compact, and room-temperature-operating THz detectors and cameras. Here, we report ubiquitously available LEDs exhibiting photovoltaic signals of ~0.8 V and ~2 ns response time with signal-to-noise ratios of ~1300 when being illuminated by THz field strengths ~240 kV/cm. We also demonstrated THz-LED detectors and camera prototypes. These unorthodox THz detectors exhibited high responsivities (>1 kV/W) with response time four orders of magnitude shorter than those of pyroelectric detectors. The mechanism was attributed to THz-field-induced impact ionization and Schottky contact. These findings not only help deepen our understanding of strong THz field-matter interactions but also contribute to the applications of strong-field THz diagnosis. Interest in the exploration of non-perturbative nonlinear optical phenomena driven by intense terahertz fields has seen a leap forwards with the recent development in femtosecond laser-based table-top sources for strong THz radiation. The authors present intense THz-field-induced effects in ubiquitously available LEDs illuminated by strong THz pulses, paving the way to their use in detecting and imaging intense THz radiation.

Extreme terahertz (THz) science and technologies, the next disruptive frontier in nonlinear optics, provide multifaceted capabilities for exploring strong light-matter interactions in a variety of physical systems. However, current techniques involve the need for an extremely high-field free space THz source that is difficult to generate and has limited investigations to a rather weak and linear regime of light-matter interactions. Therefore, new approaches are being sought for the tight confinement of THz waves that can induce nonlinear effects. Here, a nonlinear “tera-nano” metasurface is demonstrated exhibiting extremely large THz nonlinearity and sensitive self-modulation of resonances at moderate incident THz field strengths. A record deep-subwavelength (≈λ/33 000) confinement of strongly enhanced (≈3200) THz field in a nano-gap (15 nm) exhibits remarkable THz field-tailored nonlinearity. Further, ultrafast injection of photocarriers reveals a competition between nonlinear THz field-induced intervalley scattering and optically driven interband excitations. The results on “tera-nano” metasurfaces enable a novel platform to realize enhanced nonlinear nano/micro composites for field-sensitive extreme THz nonlinear applications without the need for intense THz light sources. Ministry of Education (MOE) This work was supported by the National Natural Science Foundation of China (61905007, 11827807), the National Key R&D Program of China (2019YFB2203102), and the Open Project Program of Wuhan National Laboratory for Optoelectronics No. 2018WNLOKF001, and the Open Fund of Guangdong Provincial Key Laboratory of Information Photonics Technology (Guangdong University of Technology, No. GKPT20). M.M. and R.S. acknowledge research funding support from the Ministry of Education, Singapore (AcRF Tier 1, Grant RG191/17, MOE2017-T2-1-110, and MOE2016-T3-1-006(S)).

Accompanied with the energy crisis and global warming, the concept of Energy Internet (EI) emerges, which aims to make full use of renewable energy. Among many possible structures, a particularly interesting EI structure has multiple microgrids interconnected by energy routers. In order to ensure that energy routers can control and transmit energy efficiently and reliably among microgrids, information technology plays an important role. Focusing on the information layer of the considered EI structure, a novel edge-cloud coordination architecture is proposed in this paper. A task allocation strategy is developed to improve the reliability and efficiency of the information layer. In order to reduce the information delay as well as ensuring the reliability of information transmission, a joint optimization problem is formulated and solved by particle swarm optimization algorithm. The effectiveness of the proposed method are demonstrated by simulations.

This paper presents a vision system for the tracking of the shot and the measure of the thrown distance in a shot put competition. The pan-tilt-zoom (PTZ) camera is used to capture images of the shot and track the shot to the landing position, and the lidar is used to measure the thrown distance once the landing position is determined. A new algorithm based on Hough gradient is developed in order to detect object quickly. The algorithm is further accelerated through GPU parallel computing and implemented on NVIDIA TX2. The control of the system is realized with an onboard arm processor. The system is able to handle video steam of 75 frame per second (FPS), where the image resolution is $640 \times 480$ pixels.

We successfully realized the generation of 1.4 mJ high energy terahertz pulses based on tilted pulse front technique in large-size lithium niobate crystals, and verified the nonlinear applications in semiconductors.

Arbitrary manipulation of broadband terahertz waves with flexible polarization shaping at the source has great potential in expanding numerous applications, such as imaging, information encryption, and all-optical coherent control of terahertz nonlinear phenomena. Topological insulators featuring unique spin-momentum–locked surface state have already exhibited very promising prospects in terahertz emission, detection, and modulation, which may lay a foundation for future on-chip topological insulator-based terahertz systems. However, polarization-shaped terahertz emitters based on topological insulators with an arbitrarily manipulated temporal evolution of the amplitude and the electric-field vector direction have not yet been explored. We systematically investigated the terahertz radiation from topological insulator Bi2Te3 nanofilms driven by femtosecond laser pulses and successfully realized the generation of efficient chiral terahertz waves with controllable chirality, ellipticity, and principal axis. The convenient engineering of the chiral terahertz waves was interpreted by a photogalvanic effect (PGE)-induced photocurrent, while the linearly polarized terahertz waves originated from linear PGE-induced shift currents. Our work not only provides further understanding of femtosecond coherent control of ultrafast spin currents but also describes an effective way to generate spin-polarized terahertz waves at the source.

With the wide application of wireless sensor networks in various fields, the security issues in wireless sensor networks have become increasingly important. The security threats of privacy information such as identity, routing, and communication relationship of nodes in the network have become the main bottlenecks for large application and deployment. In this paper, an anonymous communication scheme with enhanced anonymity and less overhead is designed for the characteristics of wireless sensor networks by using bilinear problem, which aims to prevent attackers accessing to the privacy information by attacking the network. The scheme not only provides anonymous session key, anonymous authentication and anonymous data transmission, but also provides privacy protection for transmission data and effectively resists active attacks and passive attacks. The theoretical computation shows that our scheme reduces the time delay by 39% and the communication cost by 20% compared with the classical anonymous communication scheme in [6], [8] and [9].

Introduction Autism spectrum disorder (ASD) is a complex and prevalent neurodevelopmental disorder characterized by deficits in social communication and social interaction as well as repetitive behaviors. Alterations in function connectivity are widely recognized in recent electroencephalogram (EEG) studies. However, most studies have not reached consistent conclusions, which could be due to the developmental nature and the heterogeneity of ASD. Methods Here, EEG coherence analysis was used in a cohort of children with ASD (n = 13) and matched typically developing controls (TD, n = 15) to examine the functional connectivity characteristics in long‐distance and short‐distance electrode pairs. Subsequently, we explore the association between the connectivity strength of coherence and symptom severity in children with ASD. Results Compared with TD group, individuals with ASD showed increased coherence in short‐distance electrode pairs in the right temporal–parietal region (delta, alpha, beta bands), left temporal–parietal region (all frequency bands), occipital region (theta, alpha, beta bands), right central–parietal region (delta, alpha, beta bands), and the prefrontal region (only beta band). In the long‐distance coherence analysis, the ASD group showed increased coherence in bilateral frontal region, temporal region, parietal region, and frontal–occipital region in alpha and beta bands. The strength of such connections was associated with symptom severity. Discussion Our study indicates that abnormal connectivity patterns in neuroelectrophysiology may be of critical importance to acknowledge the underlying brain mechanism., Alterations in function connectivity are widely recognized in recent electroencephalogram (EEG) studies. Our study indicates that discovery of atypical brain coherence in ASD young children may be of a critical importance to acknowledge the underlying brain mechanism.

The rapid development of Virtual Reality technology and the video sharing market of VOD (video-on-demand) stream nowadays makes online 360-degree video a new form of internet media. In the past few years, many 360-degree video delivery schemes are proposed. Yet, high fps requires a very high network band, otherwise will suffer from significant video quality drop. In this paper, we are focusing on using salient object detection and frame motion state detection for quality adjustment to reset 360-degree image quality of salient foreground and unimportant background. The system predicts the salient portion of video and then separate one frame in to foreground frame and back ground frame. Then by combining MS SSIM (Modified Structural Similarity of Images) algorithm, it also detects important frames and estimate the motion state of each view. The following procedure includes methods which lower the quality of dynamic background view and meanwhile maintain the high quality of foreground. This stage separates a 360-degree video into two videos with a much smaller file size of the background video. The core contribution of the scheme is that it is able to detect salient foreground and less noticed dynamic background of VR graphics. As a result in the transmission of the VR graphics, the network can execute a parallel transmission of a foreground and a economized background, costing less network resources.The results prove that this proposed scheme can effectively reduce global transmission bandwidth of the network with a wide adaptation of all genres of 360-degree videos.

Traditional text document clustering methods represent documents with uncontextualized word embeddings and vector space model, which neglect the polysemy and the semantic relation between words. This paper presents a novel text document clustering method to deal with these problems. Firstly, pre-trained language representation model Bidirectional Encoder Representations from Transformers (BERT) is utilized to generate sentence embeddings. Then, two sentence-level weighting schemes based on named entity are designed to enhance the performance. Finally, the k-means clustering algorithm is applied to find groups of similar documents. Experimental results on four datasets indicate that the proposed weighted method achieves higher accuracy than unweighted average method. Friedman tests conducted separately with F1 score and Adjusted Rand Index (ARI) values both validate better overall performance of our proposed method.

The curvature regularities have received growing attention with the advantage of providing strong priors in the continuity of edges in image processing applications. However, owing to the non-convex and non-smooth properties of the high-order regularizer, the numerical solution becomes challenging in real-time tasks. In this paper, we propose a novel curvature regularity, the total curvature (TC), by minimizing the normal curvatures along different directions. We estimate the normal curvatures discretely in the local neighborhood according to differential geometry theory. The resulting curvature regularity can be regarded as a re-weighted total variation (TV) minimization problem, which can be efficiently solved by the alternating direction method of multipliers (ADMM) based algorithm. By comparing with TV and Euler's elastica energy, we demonstrate the effectiveness and superiority of the total curvature regularity for various image processing applications.

Using a Dazzler system and tilting a compressor grating, we provide an effective way of using the laser group delay dispersion to continuously steer the electron beam accelerated by an asymmetric laser wakefield. The deviation angle of the electron beam was the same as that of the angularly chirped laser pulse from its initial optical axis, which is determined by the laser pulse-front-tilt (PFT). This method can be utilized to continuously control over the pointing direction of electron bunches to the requisite trajectories, especially for practical applications in highly sensitive alignment devices such as electron-positron colliders or undulators. Additionally, we investigate the effect of PFT on the properties of the electron beam.

The concept of net zero energy building has attracted many attentions and controversies since it was put forward. Many scholars have analyzed its configuration, technology, modeling approach and feasibility of application. However, there are still few studies focus on the application of net zero buildings considering future energy development. Based on the current energy situation and the development trend of energy technology, this paper analyzed the technical feasibility of net zero energy building in the hot summer and warm winter climate zone in China through case studies of two demo projects. Simulation and real-site measurement are used to obtain energy consumption data of the case buildings. The results show that the realization of net zero energy building should not only depend on the traditional energy-saving technologies, but should also depend on the transformation of the energy system and the combination of information technologies. The achievement of net zero energy building should not be conducted in an individual building, but should be conducted in scale of a whole urban energy system. In summary, net zero energy buildings are one of opportunities for the construction industry to undertake country-wide energy revolution and further integration with information technology.

Future information technologies for low-dissipation quantum computation, high-speed storage, and on-chip communication applications require the development of atomically thin, ultracompact, and ultrafast spintronic devices in which information is encoded, stored, and processed using electron spin. Exploring low-dimensional magnetic materials, designing novel heterostructures, and generating and controlling ultrafast electron spin in two-dimensional (2D) magnetism at room temperature, preferably in the unprecedented terahertz (THz) regime, is in high demand. Using THz emission spectroscopy driven by femtosecond laser pulses, we successfully realized optical THz spin current bursts at room temperature in 2D van der Waals ferromagnetic Fe3 GeTe2 (FGT) integrated with Bi2 Te3 as a topological insulator. The symmetry of the THz radiation was effectively controlled by the optical pumping incidence and external magnetic field directions, indicating that the THz generation mechanism is the inverse Edelstein effect contributed spin-to-charge conversion. Thickness-, temperature-, and structure-dependent nontrivial THz transients revealed that topology-enhanced interlayer exchange coupling increases the FGT Curie temperature to room temperature, which provides an effective approach for engineering THz spin current pulses. These results contribute to the goal of all-optical generation, manipulation, and detection of ultrafast THz spin currents in room-temperature 2D magnetism, accelerating the development of atomically thin high-speed spintronic devices. This article is protected by copyright. All rights reserved.

With distributed generation and battery storage technologies thriving in microgrids, the use of direct current (DC) microgrids in the building sector offers multiple advantages in energy efficiency and power quality compared with alternating current (AC) systems. This study developed a new concept of a loose-coupled bipolar DC building power system. The concept was used to design a real-world office building in Shenzhen, China. A power system model was developed to study the stability and control of the DC power system and to verify DC power quality. The design and modeling of the DC power control system is discussed in detail. The study developed a few common fault scenarios in DC building microgrids that were simulated in the MATLAB-Simulink environment to validate the design of a loose-coupled bipolar DC system. The results indicate that the proposed loose-coupled bipolar DC system schema, when implemented with proper control algorithms, can achieve good fault-tolerant performance with reliable power quality, even during disruptive system events.

A fast quantitative phase imaging technology based on space-domain Kramers-Kronig relations is proposed. By incorporating Kramers-Kronig relations, we acquire distributions on phase via measurements of intensity over the captured spectrum. Only using four low-resolution images, we built a microscope prototype with a half-pitch resolution of 625 nm (final effective imaging performance of 0.5 NA) and a field of view of 3.8 mm2 at a wavelength of 625 nm via a 10×/0.25 NA objective. Correspondingly, the data recording time is 0.16 s, and the space-bandwidth-time product is 243.3 megapixels per second. It is worth noting that the proposed scheme requires neither mechanical scanning nor extra illumination like interferometry. Meanwhile, the reconstruction is non-iterative and object-independent. Our method provides a high-efficiency phase retrieval framework and is promising in biomedicine and dynamic observation.

We present an improvement design of a two-dimensional (2D) angular-resolved proton spectrometer for wide-angle measurement of proton beams from high-intensity laser-solid interactions. By using a 2D selective entrance pinhole array with different periods in orthogonal axes, the angular resolution along one dimension is improved by a factor of 6.7. This improvement provides the accessibility to detect the spatial fine structures of the proton energy spectrum.

Active control of electric powertrains is challenging, due to the fact that backlash and structural flexibility in transmission components can cause severe performance degradation or even instabili...

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented. Simulation-based parameter optimizations are carried out according to the objective functions. Simulation results show that an electric powertrain with intelligent controller can perform its tasks well under sport, eco, and normal driving modes. The vehicle further improves overall performance in vehicle dynamics, ride comfort, and energy efficiency. The results validate the feasibility and effectiveness of the proposed CPS-based optimization framework, and demonstrate its advantages over a baseline benchmark.

The flexibility of the electrified powertrain system elicits a negative effect upon the cooperative control performance between regenerative and hydraulic braking and the active damping control performance. Meanwhile, the connections among sensors, controllers, and actuators are realized via network communication, i.e., controller area network (CAN), that introduces time-varying delays and deteriorates the control performances of the closed-loop control systems. As such, the goal of this paper is to develop a control algorithm to cope with all these challenges. To this end, the models of the stochastic network induced time-varying delays, based on a real in-vehicle network topology and on a flexible electrified powertrain, were firstly built. In order to further enhance the control performances of active damping and cooperative control of regenerative and hydraulic braking, the time-varying delays compensation algorithm for the electrified powertrain active damping during regenerative braking was developed based on a predictive scheme. The augmented system is constructed and the H∞ performance is analyzed. Based on this analysis, the control gains are derived by solving a nonlinear minimization problem. The simulations and hardware-in-loop (HIL) tests were carried out to validate the effectiveness of the developed algorithm. The test results show that the active damping and cooperative control performances are enhanced significantly.

With China’s urbanization rate researches 56.1% in 2015, the limitation of the city scale and retrofitting the existing building became the social consensus. According to incomplete survey, there are 400~600 billion m2 existing buildings in China and only less than 10% can be rated as the energy efficiency building, with considerable interest and activity in green retrofit design and construction. We review briefly the context of existing building retrofit design and construction in China. Next we look at a specific project as an example of a high performance, sustainable retrofit design, the Green E-Park, in the typical old downtown area of Shanghai China. Based on the climate condition, cultural characteristics and old industrial features, the retrofit of Green E-Park improves the quality of the indoor environment, building performance and utilization of the renewable energy source. And most importantly, the retrofit of the Green E-Park is not only limited in the building, but also takes the community retrofit into the consideration which includes a series of community sustainable retrofit planning technology. We also comment on the unique planning and design process, which incorporated passive strategies throughout the building, and has led to high occupant satisfaction and remarkably low retrofit cost. Lastly we present thoughts on how the retrofit philosophy of the Green E-Park can be a guide for sustainable retrofit in different climate regions throughout China and elsewhere

A metallic binary-groove gratings, which can be exploited to absorb light at C-band and sense materials with refractive index (1.0 - 1.2), is proposed and investigated numerically. Both ultra-high absorption (99.937%) and sensitivity (1600 nm/RIU) are achieved.

Community energy planning has attracted wide attention in China as the implementation of China’s low-carbon city policies. Meanwhile the rapid development of energy science and technology has shifted buildings and communities from energy consumers to prosumers, which lead to more difficulties in configuring the energy technology portfolio. This study es-tablishes an optimal decision-making model for community energy planning and develops an online tool called District EnErgy Planning(DEEP). Based on DEEP, the impact of energy price and equipment cost on optimization results, and the corresponding operational strategies are discussed through case study and scenario analysis. The results show that, when natural gas price exceeds 2yuan/m3 the gas-based solutions become economically uncompetitive. The technologies are propitious when equipment prices are reduced by 50%, 50%, 80% for CHP facilities, PV panels and electric battery, respectively.

In this paper, we propose a novel three dimensional metamaterial design with eight-fold rotational symmetry that shows a polarization-insensitive, wide-angle and broadband perfect absorption in the microwave band. By simulation, the polarization-insensitive absorption is over 90% between 26.9 GHz to 32.9 GHz, and the broadband absorption remains a good absorption performance to a wide incident angles for both TE and TM polarizations. The magnetic field distribution are investigated to interpret the physical mechanism of broadband absorption. The broadband absorption is based on overlapping the multiple magnetic resonances at the neighboring frequencies by coupling effects of multiple metallic split-ring resonators (SRRs). Moreover, it is demonstrate that the designed structure can be extended to other frequencies by scale down the size of the unit cell, such as the visible frequencies. The simulated results show that the absorption of the smaller absorber is above 90% in the frequency range from 467 THz to 765 THz(392–642 nm), which include orange to purple light in visible region(400–760nm). The wide-angle and polarization-insensitive stabilities of the smaller absorber is also demonstrated at visible region. The proposed work provides a new design of realization of a polarization-insensitive, wide-angle and broadband absorber ranging different frequency bands, and such a structure has potential application in the fields of solar cell, imaging and detection.

Bragg gratings, because of their favored surface plasmon coupling characteristic, are widely applied in nano-optics. We propose a periodic staggered Bragg gratings structure as a refractive index sensor by the finite element method. The optimized extraordinary optical transmission based on staggered gratings can excite surface plasmon resonance for much larger wavelength. The refractive index can be obtained by detecting the resonant wavelength shift of transmittance peak. This sensor exhibits high sensitivity and favorable linear characteristic in a wide variation interval of refractive index. The simulation results provide a further insight into nano optical sensors.

Terahertz electric field induced nonlinearity on gold nanofilms with different thicknesses are systematically investigated. With increasing the applied terahertz electric field strength, we find that the terahertz transmittance first increases linearly and then saturates, resulting in a field dependent nonlinear behavior.

Vehicular ad-hoc networks (VANET) is the application of MANET in vehicle communication, which is widely used in traffic management, road condition detection, vehicle tracking, traffic safety, current state navigation, and other fields. Research of VANTE has extensive prospect due to the merging of wireless communication and transmission technique. However, mobility characteristics of VANET itself leads to a high rate of packet loss. And the existing routing protocols cannot be well applied to VANET. In this paper, the ant colony algorithm is added to the AODV protocol for optimization and improvement. In the same scenario, we compared the packet loss characteristics and the average throughput of the AODV protocol and new-AODV protocol in VANET. The experiment result shows that the packet loss rate of the latter is lower than the former, and the network has better stability.

Human driver's intervention is still needed before achieving fully autonomous driving, and this poses a great challenge for ensuring safety and smoothness during control transition from automation to human driver. This paper addresses this challenge by proposing a novel predictive haptic takeover control method. First, a new human-machine interaction model considering two phases, namely machine dominance and human dominance, is developed to describe the interactive behaviors between human driver and automation system during takeover. Based on the model built, a novel haptic takeover controller is designed by using model predictive control approach in order to achieve a safe and smooth handover transition. The optimal steering input is derived by considering the expected paths of both human driver and automation system. The takeover controller generates predictive haptic steering torque based on driver's states, guiding and assisting human driver to gradually resume manual control. Simulation is conducted under a typical driving condition with proposed method. Simulation results indicate that the automation-to-human control transfer is completed safely and smoothly with the proposed haptic takeover controller, and meanwhile the vehicle performance and stability are also guaranteed.

Significance Terahertz (THz) radiation, with frequencies spanning from 0.1 to 10 THz, has long been the most underdeveloped frequency band in electromagnetic waves, mainly due to the dearth of available high-power THz sources. Although the last decades have seen a surge of electronic and optical techniques for generating intense THz radiation, all THz sources reported until now have failed to produce above-millijoule (mJ) THz pulses. We present a THz source that enables a THz pulse energy up to tens of mJ, by using an intense laser pulse to irradiate a metal foil., Ultrahigh-power terahertz (THz) radiation sources are essential for many applications, for example, THz-wave-based compact accelerators and THz control over matter. However, to date none of the THz sources reported, whether based upon large-scale accelerators or high-power lasers, have produced THz pulses with energies above the millijoule (mJ) level. Here, we report a substantial increase in THz pulse energy, as high as tens of mJ, generated by a high-intensity, picosecond laser pulse irradiating a metal foil. A further up-scaling of THz energy by a factor of ∼4 is observed when introducing preplasmas at the target-rear side. Experimental measurements and theoretical models identify the dominant THz generation mechanism to be coherent transition radiation, induced by the laser-accelerated energetic electron bunch escaping the target. Observation of THz-field-induced carrier multiplication in high-resistivity silicon is presented as a proof-of-concept application demonstration. Such an extremely high THz energy not only triggers various nonlinear dynamics in matter, but also opens up the research era of relativistic THz optics.

We study the effect of crystal temperature on terahertz generation efficiency and output spectrum by single-shot waveform measurements, and observe enhanced optical-to-terahertz efficiency and broadened spectrum after cryogenically cooling the crystal.

High power laser science and engineering 7, e54 (2019). doi:10.1017/hpl.2019.36, Published by Cambridge Univ. Press, Cambridge