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Parkinson’s disease (PD) is a neurodegenerative disorder that severely affects the motor system of patients. Early PD detection will greatly improve the quality of lives. However, existing automatic PD detection systems either rely on customized sensors or require users to perform special activities, using machine learning models whose prediction process is not understandable by medical professionals. In this article, we develop a non-disruptive PD detection system on smartphones based on interpretable prediction models. We design an application named PDGes to passively collect touchscreen and Inertial Measurement Unit data of users’ tapping and swiping actions on smartphones. Meaningful features that reflect finger dexterity , tremor , stiffness , and hand movement are extracted to build the prediction model. To better comprehend the decisions made by the model, we conduct a systematic analysis of feature importance to help validate the conformity of the model with clinical PD diagnosis. We collected data from 108 volunteers to evaluate the performance of PDGes . The experiment results show that PDGes achieves a detection accuracy of more than 94.5% on different smartphones.

Atopic dermatitis (AD) is a chronic, inflammatory skin disease. The mechanism was complex. Genetic mutations of Toll-like receptor (TLR) may be associated with AD, yet still unclear. We aim to provide specific evidence of the association of TLR2, TLR9 gene polymorphisms with AD. Publications were selected according to the criteria. Newcastle-Ottawa Scale was applied to evaluate the quality. The value of ORs and 95%CIs were applied to measure the associations. According to the heterogeneity, the effects model of fixed or random was selected in data combination. For TLR2 gene rs5743708 polymorphism, under allele and recessive contrasts, the pooled data showed a significant correlation, which was A vs a, OR = 0.51 (95%CI: 0.30, 0.86); AA vs Aa + aa, OR = 0.54 (95%CI: 0.33, 0.88). For TLR2 gene rs4696480 polymorphism, under allele, homozygous, heterozygous, and dominant contrasts, the pooled data showed a significant correlation, which was A vs a, OR = 0.79 (95%CI: 0.64, 0.97), AA vs aa, OR = 0.65 (95%CI: 0.43, 0.97), Aa vs aa, OR = 0.68 (95%CI: 0.48, 0.97), AA + Aa vs aa, OR = 0.67 (95%CI: 0.49, 0.93). There are significant associations of TLR2 gene rs5743708, rs4696480 polymorphisms with atopic dermatitis, while no associations are found in TLR9 gene rs5743836, rs187084 polymorphisms.

Dupilumab is approved for multiple type 2 inflammatory diseases. In the treatment procedure, the changes of IgE levels need further analysis. We evaluated the changes of IgE levels through meta-analysis, aiming to provide a more comprehensive result.Databases were searched to select eligible publications. After being included, study quality was assessed. The standardized mean difference (SMD) was used as an evaluation.Seven studies were included. At week 4, the level of IgE did not decrease significantly, with SMD = -0.12 (95%CI: -0.31, 0.07) (Levels of IgE can be significantly decreased in patients with dupilumab treatment. In AD patients, the efficacy was related to total dose; for patients with high IgE levels, efficacy may be better with the dose increased.

Verifiable databases (VDB) enables the data owner to outsource a huge unencrypted database to the powerful but untrusted cloud such that any client could later retrieve the database and check whether the cloud returns valid records or not. To the best of our knowledge, there is no prior work considering privacy. Besides, they assume that the data owner and the client are fully trusted while they may be semi-honest in the real world. To address these problems, we propose a new primitive called privacy-preserving publicly verifiable database (PPVDB), which not only guarantees the integrity of the query result but also leaks no information. At the end of this protocol, the client can check whether the cloud returns a valid result and learns the query result but nothing else about the database. Besides, the cloud learns nothing about the database and the query, and the data owner does not know which item that the client has queried. Motivated by the comparison among some strawman solutions, we incorporate verifiable computation for the polynomial with oblivious pseudorandom function to construct a PPVDB scheme, which is the first VDB scheme providing stronger security against the malicious cloud and the semi-honest client and data owner.

BackgroundIncreasing numbers of studies demonstrated that picosecond lasers (Picos) were effective and safe for melasma. However, A limited number of randomized controlled trials (RCTs) regarding Picos contribute to a modest level of evidence. Topical hydroquinone (HQ) remains to be the first-line therapy.ObjectiveTo compare the efficacy and safety of non-fractional picosecond Nd:YAG laser (PSNYL), non-fractional picosecond alexandrite laser (PSAL), and 2% HQ cream in the treatment of melasma.MethodSixty melasma patients with Fitzpatrick skin types (FST) III-IV were randomly assigned to the PSNY, PSAL, and HQ groups at a 1:1:1 ratio. Patients in PSNYL and PSAL groups received 3 laser sessions at 4-week intervals. The 2% HQ cream was applied twice daily for 12 weeks in patients of the HQ group. The primary outcome, the melasma area and severity index (MASI) score, was evaluated at weeks 0, 4, 8, 12, 16, 20, and 24. The patient assessment score by quartile rating scale was rated at weeks 12, 16, 20, and 24.ResultsFifty-nine (98.3%) subjects were included in the analysis. Each group showed significant change from baseline in MASI scores from week 4 to week 24. The MASI score in the PSNYL group showed the greatest reduction compared to the PSAL group (p = 0.016) and HQ group (p = 0.018). The PSAL group demonstrated comparable MASI improvement as the HQ group (p = 0.998). The PSNYL group had the highest patient assessment score, followed by the PSAL group and then the HQ group, although only the differences between PSNYL and HQ groups at weeks 12 and 16 were significant. Four patients (6.8%) experienced recurrence. Other unanticipated events were transient and subsided after 1 week to 6 months.ConclusionThe efficacy of non-fractional PSNYL was superior to that of non-fractional PSAL, which was not inferior to 2% HQ, thus non-fractional Picos providing an alternative for melasma patients with FSTs III-IV. The safety profiles of PSNYL, PSAL, and 2% HQ cream were similar.Clinical Trial Registrationhttps://www.chictr.org.cn/showprojen.aspx?proj=130994, ChiCTR2100050089.

Reprogramming the tumor immunosuppressive microenvironment is a promising strategy for improving tumor immunotherapy efficacy. The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 system can be used to knockdown tumor immunosuppression-related genes. Therefore, here, a self-driven multifunctional delivery vector is constructed to efficiently deliver the CRISPR-Cas9 nanosystem for indoleamine 2,3-dioxygenase-1 (IDO1) knockdown in order to amplify immunogenic cell death (ICD) and then reverse tumor immunosuppression. Lactobacillus rhamnosus GG (LGG) is a self-driven safety probiotic that can penetrate the hypoxia tumor center, allowing efficient delivery of the CRISPR/Cas9 system to the tumor region. While LGG efficiently colonizes the tumor area, it also stimulates the organism to activate the immune system. The CRISPR/Cas9 nanosystem can generate abundant reactive oxygen species (ROS) under the ultrasound irradiation, resulting in ICD, while the produced ROS can induce endosomal/lysosomal rupture and then releasing Cas9/sgRNA to knock down the IDO1 gene to lift immunosuppression. The system generates immune responses that effectively attack tumor cells in mice, contributing to the inhibition of tumor re-challenge in vivo. In addition, this strategy provides an immunological memory effect which offers protection against lung metastasis.

As an emerging and promising technology, Time Sensitive Networking (TSN) can be widely used in many real-time systems such as Industrial Internet of Things (IIoT) and Cyber Physical System (CPS). TSN, while ensuring the bounded latency and jitter, exhibits the disadvantage of not being able to efficiently use the bandwidth resources in the guard band. In this paper, we propose an algorithm family named Packet-size Aware Shaping (PAS), which is inspired by abstracting the problem of utilizing the guard band to a classic Precedence-Constrained Knapsack Problem (PCKP). PAS works with the existing TSN standards, having achieved the goal of guaranteeing the end-to-end latency for scheduled time-sensitive applications while fully utilizing the available bandwidth in the guard band for others. Furthermore, we have proposed and implemented several hardware designs for both the current standard TSN scheduler and the programmable one. The simulation results show that the PAS family can achieve satisfying performance in maximizing the resource utilization in the guard band. The synthesis results on Xilinx Vivado show that our proposed Multi-group Push-In-First-Out (MPIFO) scheduler can achieve 100 Mpps scheduling rate for 1024 scheduling items, which is fast enough to support the high-speed TSN.

To provide evidence of the association between CLTA-4 gene polymorphisms and alopecia areata (AA).PubMed, EMBASE, Web of Science, Cochrane, Wanfang, and CNKI databases were searched until 30 April 2021. The selection was completed according to the inclusion and exclusion criteria. The study quality assessment was based on Newcastle-Ottawa Scale. The assessment of the association was measured by ORs and 95%CIs.Nine studies, containing 2858 AA cases and 5444 disease-free control subjects were included. For rs231775 polymorphism, no significant association with AA was found, which was AA significant correlation between CTLA-4 rs231726 polymorphism and AA susceptibility was found, but no significant association of CTLA-4 gene rs231775 and rs3087243 polymorphisms and AA susceptibility was found.

Breast cancer is a highly heterogeneous disease lacking prognostic markers. Tumor-associated macrophages (TAMs) in the tumor microenvironment are associated with distant metastasis as well as poorer outcomes in breast cancer. Therefore, monitoring TAMs may guide prognostic assessment. This study explores an imaging modality based on a two-step click chemistry procedure for detecting TAMs in breast cancer. Mannose-targeted liposomes (MAN-lipo-AAG) and non-targeted liposomes (lipo-AAG) encapsulating Ac4GalNAz were prepared and comprehensively characterized. The sizes of the prepared MAN-lipo-AAG and lipo-AAG were 126 ± 0.22 and 93 ± 0.23 nm, respectively. In vitro studies demonstrated higher uptake of MAN-lipo-AAG than lipo-AAG by RAW264.7 cells. Moreover, flow cytometry and confocal microscopy confirmed that bright, homogeneous fluorescence labeling was present on RAW264.7 cell membranes in the MAN-lipo-AAG group. Furthermore, in vivo analysis indicated that MAN-lipo-AAG, compared with lipo-AAG, had higher accumulation in a 4T1 xenograft model and higher uptake by mannose-overexpressing TAMs. This study describes a promising approach for specific and non-invasive TAM-targeted imaging via metabolic glycoengineering.

The progression of agricultural production, ever-increasing industrialization, population boom, and more water-concentrated lifestyles has placed a severe burden on Yellow River Basin’s existing water resources, particularly in the current century. In the context of resource and environmental constraints, improving the green efficiency of agricultural water use (AWGE) is an important measure for alleviating the shortage of water resources as well as meeting the intrinsic requirement to promote the green transformation and upgrading of agriculture. This study used the Super Slack-Based Measure (Super-SBM) to measure the AWGE of 87 regions in the Yellow River Basin from 2000 to 2019. Based on spatial and temporal perspectives, it applied Exploratory Spatial Data Analysis (ESDA) to explore the dynamic evolution and regional differences in AWGE. Then, this study used a spatial econometric model to analyze the main factors that influence AWGE in the Yellow River Basin. The results show that, firstly, the AWGE of the Yellow River Basin shows a steady upward trend from 2000 to 2019, but the differences among regions were obvious. Secondly, the AWGE showed an obvious spatial autocorrelation in the Yellow River Basin and showed significant high–high and low–low agglomeration characteristics. Thirdly, rural per capita disposable income and effective irrigation have a positive influence on AWGE, while rural labor transfer, the input intensity of agricultural machinery and water structure have a negative influence. The spatial econometric model regression results show that the influence factors of AWGE in the Yellow River Basin showed significant spatial spillover effects and spatial heterogeneity in their effect. Finally, when improving AWGE in the Yellow River Basin, plans should be formulated according to local conditions. The results of this study can provide new ideas on the study of AWGE in the Yellow River Basin and provide references for the formulation of regional agricultural water resource utilization policies as well.

Heaving motion of ocean wave is a promising renewable energy source but challenging to capture with consistent conversion efficiencies. Main issue of the varying energy extraction efficiency of wave energy converters (WEC’s) is primarily caused by the variation of incident wave frequency and amplitude. Traditional design of the WEC has to account for the extreme sea conditions, leaving the WEC to work at suboptimal regions for most of the time. Due to the loss characteristics of the fluid power components, the performance and efficiency drop rapidly when moved away from the optimal working condition. In order to improve the efficiency of WEC, the buoy needs to operate at maximum amplitude most of the time. To do so, a new buoy structure based on actively controlled fluid-air ratio is proposed. Contrast to the traditional buoy for WEC’s, which has fixed density and weight, the proposed structure is capable of weight manipulation, resulting adjustable system natural frequency. MATLAB/Simulink simulation analysis is carried out to verify the feasibility of adjusting the gas-liquid ratio inside the buoy with a water hydraulic system. To resonate with the unknown incident wave, maximum power point tracking (MPPT) algorithm is proposed to control the buoy mass with trial steps for maximizing the resonating amplitude of the buoy. Initial simulation results have shown that the proposed system is capable of adjusting the natural frequency and the MPPT algorithm can increase the amplitude of the buoy motion.

Network Calculus is an established analytical framework which can provide deterministic estimates of latency and buffer requirements for feed-forward packet-switched communication networks. Researchers find it useful in analyzing network performance in real-time systems. As there are several Network Calculus tools and software packages for estimating network performance, it is important to select suitable Network Calculus tools for network analysis problems. This article introduces twelve established tools for Network Calculus analysis and compares their advantages and disadvantages in terms of their applicability for various systems and analysis needs. We also provide recommendations for users to select the suitable tools for research. Five public tools, namely DiscoDNC, RTC Toolbox, Deborah, CyNC, and nc-tandem-tight, are chosen to analyze end-to-end delay in a series of tandem networks for their performance demonstration. Simulations of the same tandem networks are implemented to compare with the analytical results achieved by the Network Calculus tools. To our best knowledge, this is the first comprehensive study that compares existing tools of Network Calculus analysis for real-time system network infrastructure. Our aim is to provide quick guidance to research communities for selecting suitable tools to analyze delay performance of networks.

We investigate the phase behaviours of Pluronic L62 in aqueous solution in the presence of aerosol-OT (AOT) molecules by small angle neutron scattering (SANS). The presence of AOT significantly changes the micellization phenomenon of L62 micelles in aqueous solution, including their critical micelle temperature (CMT), global size, and asphericity. The origin of these observations is attributed to the complexation between the neutral L62 surfactants and the ionic AOT molecules, which additionally provides charge to the mixed micelles: we analyse the data and extract meaningful information using the Ornstein–Zernike integral formalism. As a result, we observe that the co-micellization of L62 and AOT is very stable across a wide temperature range.

Network function virtualization (NFV), has been widely adopted in existing networks since it brings lower capital expenditure and operating expense, as well as flexible and elastic deployment. Based on NFV, dynamic Service function chain (SFC) provides more comprehensive and thorough traffic steering over a series of middleboxes, e.g., DPI, and IDS. Nevertheless, dynamic SFC involves internal state migration in middleboxes, making it hard to allocate SFC requests. We propose a reconfigurable SFC scheduling approach with consideration on resource constraints and race of the state migration to collaborate the execution of the SFC reconfiguration, in the reasonable fashion based on a heuristic algorithm. The evaluation is conducted through discrete event simulation to validate the efficiency of our reconfigurable SFC scheduling, and the results demonstrate that the proposed method outperforms First Come First Serve scheduling and random scheduling.

A hierarchical composite of Sb2S3 nanorods grown on zinc oxide (ZnO) nanofiber was prepared, and the formation of comb-shaped Sb2S3 nanorod arrays on the ZnO nanofibers was confirmed. It was found that the size of the diameter and the density of the nanorods are regulatable by changing the concentration of polyvinyl pyrrolidone as an additive for the growth of Sb2S3 nanorod on ZnO nanofiber. The obtained Sb2S3 nanorod arrays were applied as a light absorber for thin-film solar cells composed of glass-fluorine-doped tin oxide/compact ZnO/ZnO nanofibers−ZnS/Sb2S3 nanorod arrays/poly(3-hexylthiophene-2,5-diyl)/MoOx/Ag. The rectification ratio and photocurrent generation efficiency of the comb-shaped Sb2S3 nanorod arrays were improved as compared with the heterojunction of randomly stacked Sb2S3 nanorods. Smaller series resistance ( Rs) of 8.13 Ω cm−2 and an ideality factor ( n) of 2.84 with the comb-shaped Sb2S3 nanorod arrays than those of the randomly stacked ones of Rs = 15.01 Ω cm−2 and n = 3.83 also indicated superior charge extraction property and suppressed recombination of the comb-shaped Sb2S3 nanorod arrays at the interface.

Time-Sensitive Networking (TSN) is designed for real-time applications, usually pertaining to a set of Time-Triggered (TT) data flows. TT traffic generally requires low packet loss and guaranteed upper bounds on end-to-end delay. To guarantee the end-to-end delay bounds, TSN uses Time-Aware Shaper (TAS) to provide deterministic service to TT flows. Each frame of TT traffic is scheduled a specific time slot at each switch for its transmission. Several factors may influence frame transmissions, which then impact the scheduling in the whole network. These factors may cause frames sent in wrong time slots, namely misbehaviors. To mitigate the occurrence of misbehaviors, we need to find proper scheduling for the whole network. In our research, we use a reinforcement-learning model, which is called Deep Deterministic Policy Gradient (DDPG), to find the suitable scheduling. DDPG is used to model the uncertainty caused by the transmission-influencing factors such as time-synchronization errors. Compared with the state of the art, our approach using DDPG significantly decreases the number of misbehaviors in TSN scenarios studied and improves the delay performance of the network.

Bursts of 16 femtosecond laser pulses are generated in a fourfold Michelson interferometer with a tunable delay and envelope. Solutions are given to solve the “forward problem” (bursts from a given parameter set) and “inverse problem” (obtain parameter set from a given burst). Three types of bursts are generated experimentally with envelopes suitable for applications in laser materials processing and the generation of terahertz radiation.

AFDX (Avionics Full Duplex Switched Ethernet) is developed to support mission-critical communications while providing deterministic Quality of Service (QoS) across cyber-physical avionics systems. Currently, AFDX utilizes FP/FIFO QoS mechanisms to guarantee its real-time performance. To analyze the real-time performance of avionic systems in their design processes, existing work analyzes the deterministic delay bound of AFDX using NC (Network Calculus). However, existing analytical work is based on an unrealistic assumption leading to assumed worst cases that may not be achievable in reality. In this paper, we present a family of algorithms that can search for realistic worst-case delay scenarios in both preemptive and non-preemptive situations. Then we integrate the proposed algorithms with NC and apply our approach to analyzing tandem AFDX networks. Our reality-conforming approach yields tighter delay bound estimations than the state of the art. When there are 100 virtual links in AFDX networks, our method can provide delay bounds more than 25% tighter than those calculated by the state of the art in our evaluation. Moreover, when using our reality-conforming method in the design process, it leads to 27.2% increase in the number of virtual links accommodated by the network in the tandem scenario.

In network function virtualization (NFV), network functions (NFs) are chained as a service function chain (SFC) to enhance NF management with high flexibility. Recent solutions indicate that the processing performance of SFCs can be significantly improved by offloading NFs to programmable switches. However, such offloading requires a deep understanding of NF properties to achieve the maximum SFC performance, which brings non-trivial burdens to network administrators. In this paper, we propose LightNF, a novel system that simplifies NF offloading in programmable networks. LightNF automatically dissects comprehensive NF properties (e.g., NF performance behaviors) via code analysis and performance profiling while eliminating manual efforts. It then leverages the analyzed NF properties in its SFC placement so as to produce the performance-optimal offloading. We have implemented a LightNF prototype. Our experiments show that LightNF outperforms state-of-the-art solutions with an orders-of-magnitude reduction in per-packet processing latency and 9.5× improvement in SFC throughput.

Current Industrial Internet faces serious threats where attackers propagate malicious flows, resulting in communication failures in the Industrial Internet. In this work, we propose a practical and novel method to detect malicious traffic attack in real time with high accuracy. Our primary idea is to capture network flow, extract adequate network flow features, construct a long short-term memory (LSTM) based deep learning model, and identify the property of the corresponding network flow. Whether the network suffers attack or not is then determined according to the detection results. The corresponding prototype is also implemented in the Industrial Internet which is equipped with Software Defined Networking (SDN). Experimental results validate that the proposed method is effective in defending against malicious traffic attack in real-world network.

Hybrid renewable energy system (HRES) is a promising way to promote the supply stability of renewable energy and reduce carbon emission. This paper focuses on designing a novel HRES with equipment type consideration. Multiple types of equipment can improve the flexibility and reliability of the HRES, meanwhile more types means higher investment and maintenance cost. The optimization of such system involves a large number of discrete variables and complex performance equations. To deal with this problem, A two-step approach is proposed in this study. The minimum total annual cost and minimum equipment types are set as the optimization goals. A group of Pareto sets are generated after optimization process. These results can help engineers evaluate the impact of multiple factors and assist them in decision-making.

An adaptive dynamic programming value iteration algorithm is designed to solve nonlinear continuous-time nonzero-sum games in this paper. Since existing studies were developed on policy iteration, the initial condition of control policy requires to be admissible and thus the application has been limited. The proposed algorithm can be started with a more relaxed condition compared with policy iteration based methods, which relaxes the initial condition of the existing works. A simulation example is displayed to show the effectiveness.

Pursuing ever-smaller feature size in laser-based lithography is a research topic of vital importance to keep this technique competitive with other micro-/nano-fabrication methods. Features smaller than the diffraction-limited spot size can be obtained by "thresholding", which utilizes the deterministic nature of damage threshold with ultrashort laser pulses and is achieved by precisely tuning pulse energies so that only the central portion of the focal spot produces permanent modification. In this paper, we examine the formulation commonly used to describe thresholding and show that the relationship between feature size (r) and laser fluence (F) is invariant with respect to the nature of laser absorption. Verified by our experiments performed on metal, semiconductor, and dielectric samples, such invariance is used to predict the smallest feature size that can be achieved for different materials in a real-world system.

Objective. To evaluate the efficacy and safety of Qingpeng ointment for the treatment of subacute and chronic eczema. Method. Randomized controlled trials (RCTs) on Qingpeng ointment for subacute and chronic eczema were searched on PubMed, the Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database, and Chinese Science and Technology Periodical Journal from their inception to 30 November 2020. Quality assessment and data analysis were performed by Review Manager 5.3. Results. A total of 26 RCTs were included. Qingpeng ointment could significantly improve the total efficacy rate (TER) ( RR = 2.60 , 95% CI: 2.11 to 3.21, P < 0.00001 ), reduce the total symptom score (TSS) ( SMD = − 2.35 , 95% CI: -3.74 to -0.97, P = 0.0009 ), and decrease visual analogue scale (VAS) for pruritus ( MD = − 3.86 , 95% CI: -4.41 to -3.31, P < 0.00001 ) compared with the placebo. The TER of Qingpeng ointment was similar to that of topical corticosteroid (TCS) ( RR = 0.96 , 95% CI: 0.88 to 1.03, P = 0.25 ), and the TSSs between Qingpeng ointment and medium or low potency TCS were not significantly different ( SMD = − 0.05 , 95% CI: -0.22 to 0.12, P = 0.54 ). However, Qingpeng ointment was not superior to TCS in reducing VAS score ( SMD = 0.48 , 95% CI: 0.00 to 0.96, P = 0.05 ). In addition, Qingpeng ointment combined with TCS performed better than TCS alone in all three outcomes. For safety, nothing but skin irritative reactions occurred in the Qingpeng ointment group, and its incidence of skin irritative reactions was similar to those of the placebo ( RR = 1.47 , 95% CI: 0.61 to 3.55, P = 0.40 ) and TCS ( RR = 1.82 , 95% CI: 0.79 to 4.22, P = 0.16 ). The combined therapy did not increase the risk of skin irritative reactions ( RR = 0.69 , 95% CI: 0.27 to 1.78, P = 0.44 ). Conclusion. Qingpeng ointment is an effective and safe treatment for subacute and chronic eczema. It is also an add-on treatment to TCS for eczema. However, due to the suboptimal quality of the included studies, more large-sample and high-quality RCTs are needed to improve the evidence quality.

The value iteration mechanism is introduced to design the constrained optimal tracking controller for continuous-time nonlinear system in this paper. Unlike most studies were developed by policy iteration, the proposed VI algorithm is designed to be started with arbitrary semi-definite positive function, and thus no restriction is in the initial condition. The iterative property of the proposed algorithm is discussed and the optimality of the iterated results are obtained. To verify the effectiveness, a nonlinear case is simulated.

The development of the state-of-the-art global geopotential model (GGM) broadens its applications in ocean science, which emphasizes the importance for model assessment. We validate the recently released high-degree GGMs over the South China Sea using geodetic observations and synthetic/ocean reanalysis data. The assessment against a recently conducted high resolution (~ 3 km) airborne gravimetric survey over the Paracel Islands shows that XGM2019e_2159 has the highest accuracy (~ 3.1 mGal). However, the comparison with airborne/shipborne data hardly discriminate the qualities of other GGMs that have or truncated to same degree and order. Whereas, the validation results of GGMs against synthetic/ocean data are not identical. XGM2019e_2159/XGM2019 has the best quality, and the accuracy of associated mean dynamic topography (MDT) is 2.5 cm, and this value changes to 7.1 cm/s (6.8 cm/s) when the zonal (meridian) geostrophic currents are assessed. In contrast, the assessments of other GGMs show that they have deteriorated accuracies compared to XGM2019e_2159/XGM2019; in particular, the widely used EGM2008 has the worst performance, and the accuracies of associated MDT and zonal (meridian) currents are reduced by 3.9 cm and 4.0 cm/s (5.5 cm/s), respectively, compared to results derived from XGM2019e_2159/XGM2019. These results suggest that the choice of GGM in oceanographic research is crucial, especially in coastal zones and regions that only fill-in data were used for GGM development. Moreover, the existing synthetic/ocean data may be served as an additional data source for global/regional gravity field assessment, which is especially useful in regions that lack of control data.

In electrical transmission grids, the redundant communication paths nondisjointly overlapping at links can be established between certain substations and the control center to guarantee reliable packet delivery under link failures. However, the generation of nondisjoint paths with multiplicative and concave constraints is with the NP-complete complexity and the failovers can lead to out-of-order packets. This paper presents an OpenFlow-based nondisjoint path aggregation mechanism to heuristically compute the constrained nondisjoint paths in a centralized fashion and reorganize the out-of-order packets at edge switches. The solution is evaluated through simulations of the IEEE 30-bus network scenario under 2% link failure rate and the result confirms its effectiveness: the packet delivery success rate is significantly improved in comparison with the current nondisjoint and disjoint path algorithms. TCP throughput is improved by 121.62% with the packet reordering. Also, the memory usage for the packet reordering buffer is reduced by 76.563% compared with the distributed cognitive packet network.

High-quality economic development is an important approach for achieving sustainable economic development, and it is an essential condition for coordinated development between economic systems and ecosystems. This paper starts from five key points, namely, “innovation, coordination, opening-up, sharing and greenness”, to construct an evaluation system for the index of high-quality economic development, using the AHP and EVM methods to measure the level of high-quality economic development of 30 regions in China from 2004 to 2019. It uses the kernel density estimation model (hereinafter referred to briefly as KDE) and clustering method to analyze time evolution trends and spatial variation characteristics. Moreover, the LSE model is adopted to explore and analyze the factors influencing high-quality economic development in different regions. Additionally, the driving forces of China’s high-quality economic development are analyzed by means of path analysis combined with the average value of each index. The results show the following: (1) The high-quality economic development of 30 regions in China (excluding Hong Kong, Macao, Taiwan and Tibet) is spatially clustered, with obviously different development levels, characterized by the eastern region being better developed than the central and western regions. (2) With the passage of time, the polarization of China’s 30 regions has been alleviated, but they are still facing challenging development situations; (3) The factors affecting the high-quality economic development of these 30 regions in China can be divided into four types: three-factors, four-factors-I, four-factors-II and five-factors. Contributing regional factors show different distribution characteristics. The above conclusion provides a reference and scientific basis for the government to formulate policies of high-quality economic development and to solve problems facing coordinated sustainable development among regional societies, their economies and the environment.

Enzymatic browning is a major industrial problem of fresh-cut vegetables and fruits. Bioactive peptides are safe, nutritive and low-cost sources of antioxidant and antimicrobial agents. However, there has been little research on the effect of random peptides on anti-browning of fresh-cut food. For developing more natural and nutritive anti-browning agents, the effect of the enzymatic hydrolysis of random peptides from cod fish skin on polyphenol oxidase (PPO), peroxidase (POD), phenylalanine ammonia-lyase (PAL), total phenolic content, membrane permeability, malondialdehyde (MDA) content and color changes were investigated during fresh-cut potato storage. The results showed that 0.1% (w/w) cod peptides efficiently blocked enzymatic browning by inhibiting PPO, POD and PAL activities, reducing the total phenol accumulation during the entire 8 d storage at 4 °C. Furthermore, the membrane permeability and MDA content increases were delayed in 0.1% cod peptides treatment compared with the control. Oddly, the browning of fresh-cut potato was aggravated in 1.0% cod peptides treatment, which expressed higher POD and PAL activities. Meanwhile, the functional composition of cod peptides was a random component, which total 1765 peptides were identified by LC–MS/MS and the amino acids length of peptides were 4∼57 in the cod peptides. All the results showed that random peptides might be promising candidates as anti-browning agents for fresh-cut potato slices.

The electrochemical reduction of water to produce molecular hydrogen is a potential strategy for generating clean, renewable energy. However, the development of an efficient and durable catalyst remains a significant challenge. Inspired by nature, we herein describe a three-dimensional, porous hybrid catalyst fabricated by using a biomimetic approach, in which a small amount of ruthenium (Ru) nanoparticles is uniformly dispersed onto a carbonized collagen scaffold. Coordination between Ru nanoparticles and the active sites of collagen promotes the electrochemical formation of molecular hydrogen by altering the electronic state of Ru and regulating the free energy of hydrogen chemisorption. The prepared catalyst exhibits superior activity for hydrogen evolution, with an overpotential and Tafel slope comparable to those of a Pt/C catalyst. This work provides a novel perspective on the fabrication of high-efficiency electrochemical catalysts.

Finding the optimal parameters in laser processing applications can be time-consuming given the large parameter space and various sources of error. This problem is exacerbated by day-to-day variation in laser beam characteristics and a large variety of materials that need to be processed. The ideal laser processing system should be “smart,” meaning that it can sense changes in the environment, make proper adjustment, and predict parameters for new materials. As a step toward this goal, we propose a method to efficiently extract the areas of a large number of laser-induced damages in situ using an automated data acquisition system that can control laser parameters, motorized stage movement, image capturing/processing, and feature extraction. The damage areas are extracted and compared with direct measurements. Damage areas are fed into an artificial neural network (ANN) for prediction. Various ANN structures and training functions are tested to create the optimal ANN for prediction. ANN predictions were found to be capable enough to accurately model and optimize the laser processing parameters that were investigated. With the capability of collecting a large amount of usable data in a short period of time, this acquisition system can be used to train sophisticated ANNs for complicated tasks such as quality control and failure prediction.

Portulaca oleracea is an important and widely distributed medicinal and edible plant that has great economic value in the medical and food industries. We sequenced the complete chloroplast (cp) genome of P. oleracea,whichis156,533 bp in length, including a pair of inverted repeats (IRs) of 25,501 bp separated by a large single copy (LSC) region of 87,436 bp and a small single copy (SSC) region of 18,095 bp. The genome contains 85 protein-coding genes, 37 transfer RNA (tRNA) genes, and 8 ribosomal RNA (rRNA) genes. There are 40 repeat units and 111 simple sequence repeats (SSRs) in the genome. We also carried out complete cp genome comparison with other Caryophyllales species. The size, gene content, and structural organisation of P. oleracea are relatively conserved, but the genes ycf1 and ycf2 have larger introns. The simple sequence repeats (SSR) in the introns of ycf3, ycf1, atpB, rrn23 and ndhH have significant polymorphism. Comparisons of IR boundaries among 8 Caryophyllales species showed co...

We report on the experimental and theoretical study of direct laser writing on dielectrics with reduced feature size by using temporally and spatially separated pulses. Features on the front surface of fused silica within the overlapping area of two laser pulses are obtained by tuning the delay time between the two pulses. The observed dependence of feature position on delays longer than the free-carrier lifetime indicates an ionization pathway initiated by self-trapped excitons. The sensitivity of feature size with the increase of laser intensity is studied by simulating the free-carrier density distribution for different temporal and spatial separation of two laser pulses. It is found that the sensitivity is influenced by the spatial and temporal separation of the two pulses.

The intrusion response system is dedicated to automatically respond to sophisticated network intrusions, which is a sequential decision-making problem for autonomous agents. The current Markov decision process (MDP) or stochastic games based solutions suffer from several weaknesses: (i) The MDP- based approach is unable to explicitly model the opponents; (ii) The Nash equilibrium approach of stochastic games cannot handle the condition with multi equilibria. Existing studies have not considered the cognitive ability of the agent and lack of explicit opponent modeling. Inspired by recursive reasoning, this paper introduces a theory of mind (ToM)-based stochastic game-theoretic approach to reason about the beliefs and behaviors of the attackers. Each agent maintains different order ToM beliefs concerning his opponent with explicit opponent modeling. In order to accurately predict the attacker's action with nested beliefs, we utilize the Bayesian attack graph (BAG) to model multi-step attacks scenarios. In addition, the agent is allowed to learn from new information to adjust his beliefs and learning speed. Simulation results validate that ToM modeling performs well in the intrusion response system than random defense actions. Besides, a defender with first-order ToM beliefs always wins an attacker with zero-order ToM beliefs.