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Supramolecular artificial light‐harvesting system with highly efficient host–guest energy transfer pathway provides an ideal platform for optimizing the photochemistry process. The consecutive photo‐induced electron transfer (conPET) process overcomes the energy limitation of visible‐light photocatalysis, but is often compromised by mismatching between the absorption of ground state dye and its radical, weakening the efficiency of photoredox reaction. By encapsulating a conPET photocatalyst rhodamine 6G into metal‐organic cage, the supramolecular approach was undertaken to tackle the intrinsic difficulty of matching the light absorption of photoexcitation between rhodamine 6G and its radical. The highly efficient Förster resonance energy transfer from the photoexcited cage to rhodamine 6G forced by host–guest encapsulation facilitates the conPET process for the single‐wavelength light‐driven activation of aryl halides by stabilizing and accelerating the production and accumulation of the rhodamine 6G radical intermediate. The tunable and flexible nature of the supramolecular host–guest complex renders the cage‐based encapsulation strategy promising for the development of ideal photocatalysts toward the better utilization of solar energy. [ABSTRACT FROM AUTHOR]

Over the past two decades, vibrational resonance has garnered significant interest and evolved into a prominent research field. Classical vibrational resonance examines the response of a nonlinear system excited by two signals: a weak, slowly varying characteristic signal, and a fast-varying auxiliary signal. The characteristic signal operates on a much longer time scale than the auxiliary signal. Through the cooperation of the nonlinear system and these two excitations, the faint input can be substantially amplified, showcasing the constructive role of the fast-varying signal. Since its inception, vibrational resonance has been extensively studied across various disciplines, including physics, mathematics, biology, neuroscience, laser science, chemistry, and engineering. Here, we delve into a detailed discussion of vibrational resonance and the most recent advances, beginning with an introduction to characteristic signals commonly used in its study. Furthermore, we compile numerous nonlinear models where vibrational resonance has been observed to enhance readers' understanding and provide a basis for comparison. Subsequently, we present the metrics used to quantify vibrational resonance, as well as offer a theoretical formulation. This encompasses the method of direct separation of motions, linear and nonlinear vibrational resonance, re-scaled vibrational resonance, ultrasensitive vibrational resonance, and the role of noise in vibrational resonance. Later, we showcase two practical applications of vibrational resonance: one in image processing and the other in fault diagnosis. This presentation offers a comprehensive and versatile overview of vibrational resonance, exploring various facets and highlighting promising avenues for future research in both theory and engineering applications. [ABSTRACT FROM AUTHOR]

In this study, we introduce a distributed algorithm that is specifically designed to address optimization problems featuring a decomposable objective function and equality constraints. To minimize the amount of communication required, we incorporate an event-triggered mechanism that enables information exchange only when variable values exceed predefined thresholds. Importantly, our proposed algorithm possesses a distinctive characteristic where the determination of step size is solely based on the properties of the objective function, regardless of the structure of the communication network. Even in situations where changes occur in the network structure, our algorithm remains valid without necessitating any updates to its step size. Assuming strong convexity and smoothness in local objective functions, along with appropriate event-triggered thresholds, our algorithm achieves a convergence rate that is linear. Several numerical experiments provide evidence supporting the effectiveness and superiority of our proposed approach. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the optimization of cut-blasting methods for deep rock masses under high in situ stress. Several plane fluid–structure interaction (FSI) models were established, and the blasting effects using common cut-blasting methods were analyzed. Considering the damage range of the rock mass and the blast-induced vibration after blasting, the cut-blasting method was selected as suitable for deep rock masses under high in situ stress. Subsequently, the cut-blasting parameters, including blasthole spacing, blasthole diameter, and the distance between the empty hole and the first cut-blasting hole, were optimized through the crack connectedness between the blastholes and the fractal dimension of the damaged rock mass. The results showed that the pentagonal cut-blasting method is more suitable for deep rock masses compared with other methods and the blasthole spacing should be reduced to resist any inhibitory effects from the increasing in situ stress. For in situ nonhydrostatic stress conditions, it is reasonable to choose a wider blasthole spacing in the direction of the major principal stress and a narrower one in the direction of the minor principal stress. Under high in situ stress, the joint optimization of blasthole spacing and blasthole diameter is recommended in order to avoid the poor cutting effect caused by too-narrow spacing. In addition, the formula for calculating the location of empty holes in shallow rock-mass blasting is also applicable to deep rock masses. The partially optimized results were preliminarily verified through comparison with existing field tests. These findings offer a new approach for enhancing the blasting effect on deep rock masses and may provide valuable guidance for the design and construction of cut blasting in deep rock masses. [ABSTRACT FROM AUTHOR]

Flexible pressure sensors are playing an emerging role in artificial intelligence and electronic skin. However, developing a high‐performance, flexible pressure sensor through a reusable and straightforward manufacturing approach still remains a challenge. In this study, a highly sensitive, flexible capacitive pressure sensor based on a fabric‐mould strategy is introduced. Custom square‐conical arrays with Au electrodes can feasibly be fabricated at scale by peeling them off the fabric mould. The fabricated pressure sensor exhibits a high sensitivity of 5.829 kPa−1 (0–0.444 kPa) and a rapid response/recovery time of 160/70 ms. Notably, the sensor has an ultralow detection limit of 0.24 Pa, showing great potential for extremely sensitive pressure detection applications, such as water leakage monitoring. Finite element analysis, grounded on 3D‐scanning reconstruction, reveals that the enhanced sensing performance can be attributed to the contact surface of the square‐conical arrays. Moreover, the pressure sensors can accurately identify human physiological information, as well as the spatial distribution and shape of objects, further highlighting the promise for wearable electronic devices. This work not only offers a new approach for large‐scale fabrication of micro‐structures at low cost but also provides a new insight into the optimization of structures for sensitive pressure sensors. [ABSTRACT FROM AUTHOR]

Accurately detecting human actions in video has many applications, such as video surveillance and somatosensory games. In this paper, we propose a spatial-aware attention module (SAM) and a temporal-aware attention module (TAM) for spatio-temporal action detection in videos. SAM first concatenates the feature maps of consecutive frames on the channel and then uses dilated convolutional layer followed by a sigmoid function to generate a spatial attention map. The resulting attention map contains spatial information from consecutive frames, so it helps the detector focus on salient spatial features to achieve more accurate localization of action instances in consecutive frames. TAM deploys several fully connected layers to generate a temporal attention map. The temporal attention map focuses on the temporal association of each spatial feature; it can capture the temporal association of action instances, thereby improving the detector to track actions. To evaluate the effectiveness of SAM and TAM, we build an efficient and strong anchor-free action detector, cascading spatio-temporal attention network, equipped with a 2D backbone and SAM and TAM modules. Extensive experiments on two benchmarks, JHMDB and UCF101-24, demonstrate the preferable performance of SAM and TAM. [ABSTRACT FROM AUTHOR]

Under the 1.5 °C and 2.0 °C warming scenarios, few studies have explored the different influences of CO2, temperature, and precipitation on wheat yield in China. Hence, we analyzed the different influences of above factors on wheat yield after analyzing the wheat yield change. Results show that (1) the wheat yield of China would increase under the two warming scenarios. The spring wheat yield of the Northeast Spring Wheat Region (DB_S) and the Northwest Spring Wheat Region (XB_S) would increase more than that in the other two spring wheat-planting subregions. The winter wheat yield of the Southwest Winter Wheat Region (XN_W) and Middle and Lower Yangtze Winter Wheat Region (CJ_W) would increase more significantly compared with that in the other three winter wheat-planting subregions. (2) CO2 fertilization was identified as the main factor leading to a wheat yield increase, with an estimated increase of 12–18% under the 1.5 °C warming scenario and 18–21% under the 2.0 °C warming scenario. (3) Without considering CO2 fertilization, compared with precipitation, temperature dominated the spatial patterns of the wheat yield responses to climate change. Temperature influence on wheat yield was mainly reflected in the amplitudes of yield increase, while precipitation mainly affected the proportion of yield-increasing area. For wheat-planting regions with less precipitation, such as the North Spring Wheat Region (BB_S) and the Huang-Huai Winter Wheat Region (HH_W), the wheat yield increase caused by precipitation was usually more pronounced. Our findings would help inform policy decisions related to wheat production in China to better cope with future climate warming. [ABSTRACT FROM AUTHOR]

Because modernized global navigation satellite systems (GNSSs) carry high-performance atomic clocks onboard, a new problem has arisen regarding whether the clock estimation approach is good enough to reflect the true performance of onboard atomic clocks. This paper proposes a new and novel centimeter-level clock synchronization approach for BDS-3 satellites based on two-way comparisons using inter-satellite link measurements. The proposed approach estimates satellite clock offsets by adjusting satellite clock offsets obtained from inter-satellite ranging measurements, and measurement noise is greatly reduced. The noise level of clock offsets estimated by the new approach is 0.7 cm, which is 41% of that of clock offsets estimated by ISL direct two-way comparisons. Compared to the ODTS approach, the new approach efficiently eliminates orbit errors in clock offsets. On this basis, the paper presents a space-borne timescale (SPBT) using high-performance atomic clocks onboard BDS-3 satellites. The frequency stability of the SPBT is 8.6E-16 at a 1-day interval; this result is superior to ground GNSS timescales such as BDT. Based on the SPBT, this paper evaluates the performance of the BDS-3 onboard atomic clock. The 2-h and 24-h prediction uncertainties for the BDS-3 PHM are 0.04 and 0.12 m, and the frequency stabilities are 1.6e-14 and 3.4e-15 at 10,000-s and 1-day intervals, respectively. The 2-h and 24-h prediction uncertainties of the BDS-3 RAFSs are 0.05 and 0.37 m, and the frequency stabilities are 1.9E-14 and 8.1E-15 at 10,000-s and 1-day intervals. This study contributes to autonomous navigation and signal-in-space accuracy improvements for GNSSs. [ABSTRACT FROM AUTHOR]

The Global Navigation Satellite Systems (GNSSs) apply conventional relativistic corrections to correct apparent clock offsets. However, with the continuous improvements made to time synchronization approaches and onboard atomic clocks, this model has obviously limits the accuracy improvements of BDS-3 intersatellite time synchronization, and also limited the apparent performance of BDS-3 onboard atomic clocks. This study demonstrates that the amplitude of GNSS conventional relativistic periodic errors can reach 0.08 ns for BDS-3 MEO and IGSO satellites within a day, and 0.40 ns within a month. The frequency stability of the errors' signal can reach 1.33E-14 (approximately10000 s) and 1.78E-15 (approximately1 day), and the absolute influences on the predicted clock offset accuracy can reach 0.05 ns (1 h), 1.08 ns (1 day). Notably, the above signals caused by the model errors are found in the results of current high-accuracy intersatellite time synchronization based on BDS-3 intersatellite links (ISLs). After adopting a higher-accuracy relativistic correction model, the frequency instability of BDS-3 intersatellite clock offsets is obviously reduced, and the RMS of 24 h fitting residual can be reduced by approximately 60% from 0.12 ns to 0.05 ns. The average 2 h 95% predicted error decreases by approximately 17% from 0.38 ns to 0.32 ns. These results indicate that this high-accuracy relativistic correction model can improve both the BDS-3 satellites' time synchronization accuracy and the BDS-3 apparent clock offset prediction capability. This study, thus contributes to time synchronization research and signal-in-space accuracy improvements for BDS-3. [ABSTRACT FROM AUTHOR]

With the increasing penetration of distributed photovoltaic generation (DPVG) in the rural distribution network, some problems such as abandoning solar energy and increasing voltage fluctuation have become more and more prominent. In order to promote local or nearby power consumption of the photovoltaic (PV) generation in the distribution network, the profit strategy is given with an optimal electricity price based on blockchain technology (BCT) by considering the topology, the load fluctuation of the distribution network and the reputation value of agricultural park consumers. The electricity price in the blockchain (BC) transaction is used as an intermediate variable to establish the revenue model for the PV generation, the agricultural park consumers and the distribution network. The power trading mechanism of the PV generation is constructed in the decentralized management agency of the BC. The maximum overall comprehensive income of the PV generation and the park consumers is used as the objective function, and the Stackelberg game theory is applied to prove the existence of the optimal game strategy in the transaction. The local power consumption method of the PV generation is simulated with the optimal electricity price in the IEEE 33‐node distribution network. The problem of abandoning solar energy is effectively relieved within an appropriate voltage limitation, and the comprehensive benefit of the PV generation and the park consumers is raised in the distribution network. [ABSTRACT FROM AUTHOR]

In the self-breakdown experiment, it is demonstrated that the breakdown stability of 15% SF6/N2 was higher than that of pure SF6 and N2 in the non-uniform field under negative impulse voltages. In this paper, the stable breakdown phenomenon of the gas mixture is studied at the nanosecond scale. The corona process and streamer process of these three gases are investigated by using a high-speed framing camera. The stabilized corona and the abnormal streamer phenomena observed in the gas mixture discharge have a relation to the stable breakdown phenomenon. The stabilized corona is supposed to be the main reason that obstructs the development of negative steamer and stabilizes the supply of photons to the anode. Furthermore, the captured images of the streamer process in the gas mixture show that there is a negative ion sheath between the electrodes. The sheath keeps the corona stabilized near the cathode tip. In addition, photons emitted by the stabilized corona can ionize neutral particles near the anode. The generated photoelectrons and positive ions accumulate near the anode surface. The positive streamer occurs once the accumulation number reaches a certain value. In addition, the photon emission intensity and stability also have an influence on the stability of the positive streamer. [ABSTRACT FROM AUTHOR]

Temporal action detection, aiming to determine the fragment and category of a human action simultaneously from continuous data stream, is still a challenge issue in the field of human–robot interaction, somatosensory game and security monitoring. In this paper, we present a novel one-stage skeleton-based TAD method, Action-CenterNet(ACNet) with a simple anchor-free and fully convolutional encoder-decoder pipeline. Our approach encodes skeleton position and motion data sequence from multiple persons into multi-channel skeleton images which are subsequently preprocessed by view invariant transform and translation-scale invariant. ACNet models each action fragment as a center point along the time dimension and generates a keypoint heatmap to locate and classify action fragments. To ensure the accurate temporal coordinates, the discretization error caused by the output stride of network is also learned. Compared with two-stage methods, ACNet is end-to-end differential and flexible. ACNet is also an anchor-free method avoiding the drawbacks of anchor boxes used in anchor-based TAD methods. Experimental results on PKU-MMD dataset, NTU RGB-D dataset and HITvs dataset reveal the excellent performance of our approach. [ABSTRACT FROM AUTHOR]

Purpose. This study aimed to investigate nurses' perceptions of spirituality and spiritual care and perceived professional benefits in China and reveal the relationship between them. Design and Methods. In this study, 372 nurses (response rate: 93.47%) from a number of hospitals across China were surveyed using convenience sampling. The data were collected through online questionnaires, including a sociodemographic characteristics form, the Chinese version of the Spiritual Care-Giving Scale (C-SCGS), and the Nurses' Perceived Professional Benefits Questionnaire (NPPBQ). Findings. The total score of the NPPBQ was 136.88 ± 20.13. A statistically significant relationship was found between the total score and subscale score of the C-SCGS and the total score and subscale score of the NPPBQ (R = 0.217–0.475, P < 0.01). Practice Implications. Nursing managers and educators should pay attention to improving nurses' perceptions of spirituality and spiritual care in order to help nurses gain more perceived professional benefits. [ABSTRACT FROM AUTHOR]

Frequent emergencies highlight the importance of corporate resilience, and relationship governance behaviors have received much attention for improving firms' resilience. This study uses structural equation modeling to test hypotheses based on trust theory and synergy theory. It investigates the impact of the behavioral operations management approach of collaborative action on manufacturers' resilience in Chinese manufacturing firms during the COVID-19 pandemic. Environmental uncertainty is used as a moderating variable to explore its role between the trust relationship with suppliers and collaborative action, which are two types of relationship management behaviors. The results show that collaborative action positively affects each of the three stages of manufacturer resilience. Moreover, collaborative action mediates between the trust relationship with suppliers and the different dimensions of manufacturer resilience. Environmental uncertainty does not moderate the facilitative effect of the trust relationship with suppliers on collaborative action. This study examines the relational governance behavior of firms in the context of a particular Chinese culture to build a bridge between relational governance behavioral science and firm resilience management. This study tries to provide inspiration for managers to improve the risk management ability of manufacturing enterprises by using relationship management theory and behavioral science. [ABSTRACT FROM AUTHOR]

When the load and speed of rotating machinery change, the vibration signal of rolling bearing presents an obvious nonstationary characteristic. Stochastic resonance (SR) mainly is convenient to analyze the stationary feature of vibration signals with high signal-to-noise ratio. However, it is difficult for SR to extract the nonstationary feature of rolling bearings under strong noise background. For one thing, the frequency change of nonstationary signals makes the occurrence of SR very difficult. For another, the features of rolling bearings are large parameters and further prevent the SR method from performing well. Therefore, combined with order analysis (OA), adaptive frequency-shift SR is presented in this paper. To solve the problem of frequency change, OA is used to convert the nonstationary feature into stationary feature, which resamples the nonstationary signal in the time domain to stationary signal in the angular domain. To solve the other problem, the frequency-shift method based on Fourier transform is adopted to move the fault feature frequency to low frequency, and thus SR is more likely to occur under small parameter conditions. The simulated and experimental results indicate that not only the amplitude of fault feature but also the signal-to-noise ratio is significantly improved. These demonstrate that the fault features of rolling bearing in variable speed conditions are extracted successfully. [ABSTRACT FROM AUTHOR]

As an emerging technology, desalination by pervaporation (PV) has excellent potential in freshwater supply from saline waters. However, the investigation of stable membrane materials needs still to address separation issues such as fouling in desalination applications. Ceramic membranes, especially hybrid‐silica membranes, possess the required properties for pervaporation desalination and remain potentially tolerant to various saline waters which conventional membranes cannot withstand. Herein, we report the preparation of a thin, short‐chain BTESM hybrid‐silica membrane on cheap macroporous alumina supports for desalination applications through pervaporation. The fabricated membrane delivered water flux of 9.1 kg m−2 h−1 and 6.7 kg m−2 h−1 at 60 °C for simulated and real based sampled seawater, respectively, with a high rejection of >99.5 %. The fabricated membrane delivers excellent separation for various salt ranges and different salt solutions, including KCl, MgCl2, and CaCl2. Further, the PV performance of fabricated membranes implies that hybrid silica based membranes can be potential candidates for commercial desalination markets. [ABSTRACT FROM AUTHOR]

Objective: To explore the potential clinical effects of renin-angiotensin system blocker (RASB, angiotensin II receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACEIs)) in patients from the Parkinson's Progress Marker Initiative (PPMI) study database.Methods: One hundred and seven untreated, newly diagnosed PD patients with hypertension, from the PPMI were included. We measured cognitive performance, biomarkers in CSF, and magnetic resonance imaging (MRI) during the five follow-up years for patients exposed or not to renal-angiotensin system blockers. Sixteen PD patients with hypertension underwent [18F]florbetaben positron emission tomography (PET) scanning. SUVRs of region of interest (ROI) were calculated and compared within different groups.Result: Treatment with ARBs but not ACEIs improved global cognitive function evaluated by MoCA score in PD patients with hypertension compared to other hypertensive medicines up to 5 years follow up. Specifically, ARBs improved visuospatial, memory, executive abilities, processing speed attention test scores in PD. There was no significant impact of ARBs on α-syn, tau, Aβ in CSF. RASBs reduced [18F] florbetaben uptake in cortex and subcortex nuclei in the brain.Conclusions: These results show potential protective effect with ARBs in cognitive impairment of parkinson's disease with hypertension. [ABSTRACT FROM AUTHOR]

In this paper, a transmission line with five spiral-wires in parallel was designed. The transit time and the characteristic impedance of the transmission line are 200 ns and 14 Ω, respectively. Its slow wave coefficient is close to 13. The insulating medium of the transmission line is glycerin. In order to investigate the breakdown strength of glycerin under a hundred-nanosecond pulse, simulations and experiments are conducted. The results indicate that the breakdown strength of glycerin under hundred nanoseconds reached 653 kV/cm, which is a 400 kV/cm increase compared with that under a microsecond pulse. However, under hundred nanoseconds, the breakdown strength of glycerin in transmission is unaffected by pressure within 1 MPa, and pressure is conducive to the insulation recovery of glycerin. [ABSTRACT FROM AUTHOR]

To analyze the impacts of composition-associated factors of high-viscosity asphalt mixtures and thermal aging on the cohesion and adhesion characteristics of high viscosity–modified asphalt (HVMA), neat asphalts (NAs), high-viscosity additives, and aggregates were selected, and several HVMAs were first prepared. Then, the prepared HVMAs were subject to contact angle testing, and their cohesion and adhesion behaviors and influencing factors were explored by multifactor orthogonal testing coupled with the surface free energy (SFE) concept. Further, the variations and influencing factors of cohesion and adhesion properties of relevant HVMAs under aging were analyzed in comparison with styrene-butadiene-styrene (SBS)-modified asphalts (SBSMAs) and NAs. Lastly, under aging, the change behaviors of microscopic phases of HVMAs were contrastively investigated using atomic force microscopy (AFM) testing, and the relationship between the microscopic phases and the cohesion and adhesion properties was illustrated. Results showed that NA type, high-viscosity additive dosage and type, and aggregate type notably influenced the cohesion and adhesion of HVMAs, and the high-viscosity additive dosage influenced their cohesion the most. Aging weakened the cohesion and adhesion of asphalts, and the HVMAs possessed the superior cohesion and adhesion at each aging period. Under aging, the NA type, aggregate type, and aging level remarkably affected the cohesion and adhesion of HVMAs, among which the NA type affected their cohesion most prominently. Besides, the aggregate type was the most influential variable on the adhesion of HVMAs whether the HVMAs were aged or not. AFM testing demonstrated that aging reduced the component of microscopic phase structures of HVMAs and the amount of their bee structures, and diminished the surface roughness Ra of asphalt binders; in contrast, aging did not alter the component of microstructural morphology of SBSMAs and NAs. The cohesion and adhesion indexes of HVMAs under aging obeyed the high Pearson correlation and the moderate linear correlation with the Ra index. [ABSTRACT FROM AUTHOR]

Satellite clock offsets are the critical parameters for The Global Navigation Satellite Systems (GNSSs) to provide position and timing (PNT) service. Unlike other GNSSs, BDS-3 uses the two-way superimposition strategy to measure satellite clock offsets. However, affected by some deficiencies of the two-way superimposition strategy, the accuracy of BDS-3 clock offsets parameters is 1.29 ns (RMS), which is the main bottleneck for BDS-3 to improve its space signal accuracy. After analyzing problems in the clock offsets measurement process of BDS-3, the paper proposes a new strategy to real-time estimate high-accuracy satellite clock offsets. The clock offsets estimated by the new strategy show a good consistency with GBM clock offsets. The averaged STD of their differences in MEO is 0.14 ns, and the clock offsets estimated by the new strategy present less fluctuation in the 1-day fitting residuals. Applying the new clock offsets to prediction, BDS-3 can reduce its clock offsets errors from 1.05 ns to 0.29 ns (RMS), about 72%. The above results indicate that the new clock offsets estimated strategy can improve the accuracy of clock offsets parameters of BDS-3 effectively. [ABSTRACT FROM AUTHOR]

Interface properties between asphalt and aggregate intimately affect the service performance and long-term durability of asphalt pavement. This study seeks to explore the interfacial adhesion features of high-viscosity asphalt (HVA)-aggregate under water conditioning to provide the understanding for the moisture damage of HVA-aggregate interface and asphalt pavement. To this end, the HVA was initially suffered from different durations of water conditioning, and atomic force microscopy (AFM) test was employed to gather the microscopic phase structure and adhesion force of water-conditioned HVA and aggregate, to analyze the adhesion variations of HVA-aggregate interface. Further, molecular dynamics method was used to simulate the changing process and influencing mechanism of adhesion effect at the HVA-aggregate interface under water immersion. The findings indicated that with the increasing water immersion, Catana phase of HVAs vanished, and concave and convex structures appeared on the surface, along with pit groove dispersion phase structures. Longer immersion time resulted in augmented surface roughness of HVA and a more dispersed height distribution in the area domain, most notably during the initial stages of water immersion. Aging increased sensitivity to immersion duration in terms of surface roughness, mechanical properties and adhesion ability of HVAs. Water immersion had a diminishing effect on the mechanical properties of HVA at different aging degrees, although it increased the micro-mechanical modulus of HVAs and impaired the interface adhesion with aggregates. Under water immersion, the phase structure and mechanical properties of HVAs and the interface adhesion indexes all distinguished a prominent negative Pearson correlation (correlation coefficient |R| > 0.7000), and these factors were critical for HVA-aggregate interface adhesion, as alterations in surface phase structure and micro-mechanical traits of HVAs triggered variations in the HVA-aggregate interface adhesion. In addition, water content in the interface layer, simulation temperature and mineral anisotropy significantly affected the interfacial adhesion of HVA and aggregate in water environment. The introduction of water and the rise of temperature considerably weakened the interfacial adhesion effect of asphalt-aggregate system, and the interface adhesion failure occurred once the water layer thickness surpassed 5 Å. Comparatively, the HVA-calcite system demonstrated better interfacial adhesion competence than the HVA-α-quartz system, and the HVA-calcite {1 0 4} system showed the optimal interfacial adhesion. [Display omitted] • Water erosion altered surface phase morphology and micro structure of HVA. • Longer immersion duration resulted in faded adhesive force of HVA. • Thermal aging enhanced the susceptibility of micro-properties of HVA to immersion time. • Interfacial adhesion failure occurred when the water layer surpassed 5 Å. [ABSTRACT FROM AUTHOR]

Text-based video segmentation aims to segment an actor in video sequences by specifying the actor and its performing action with a textual query. Previous methods fail to explicitly align the video content with the textual query in a fine-grained manner according to the actor and its action, due to the problem of semantic asymmetry. The semantic asymmetry implies that two modalities contain different amounts of semantic information during the multi-modal fusion process. To alleviate this problem, we propose a novel actor and action modular network that individually localizes the actor and its action in two separate modules. Specifically, we first learn the actor-/action-related content from the video and textual query, and then match them in a symmetrical manner to localize the target tube. The target tube contains the desired actor and action which is then fed into a fully convolutional network to predict segmentation masks of the actor. Our method also establishes the association of objects cross multiple frames with the proposed temporal proposal aggregation mechanism. This enables our method to segment the video effectively and keep the temporal consistency of predictions. The whole model is allowed for joint learning of the actor-action matching and segmentation, as well as achieves the state-of-the-art performance for both single-frame segmentation and full video segmentation on A2D Sentences and J-HMDB Sentences datasets. [ABSTRACT FROM AUTHOR]

A hybrid methodology for the synthesis of nonuniformly spaced and excited linear arrays is proposed. At first, a modified genetic algorithm (GA) named linear-constraint genetic algorithm (LCGA) is discussed in this article to adapt to generalized linear-constraint optimization problems. Then, by nesting the technique of convex programming (CP) into LCGA, a hybrid optimization implementation is developed to jointly optimize the position and excitation variables. Due to the linear-constraint character of LCGA, array layouts can be exactly constrained with element spacings and the aperture size. A set of representative numerical experiments shows the effectiveness of this method to obtain very high-quality solutions. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new travel time estimation framework based on transformer and convolution neural networks (CNN) to improve the accuracy of travel time estimation. We design a traffic information fusion component, which fuses the GPS trajectory, real road network, and external attributes, to fully consider the influence of road network topological characteristics as well as the traffic temporal characteristics on travel time estimation. Moreover, we provide a multiview CNN transformer component to capture the spatial information of each trajectory point at multiple regional scales. Extensive experiments on Chengdu and Beijing datasets show that the mean absolute percent error (MAPE) of our MCT-TTE is 11.25% and 11.78%, which is competitive with the state-of-the-arts baselines. [ABSTRACT FROM AUTHOR]

In sports, the essence of a complete technical action is a complete information structure pattern and the athlete's judgment of the action is actually the identification of the movement information structure pattern. Action recognition refers to the ability of the human brain to distinguish a perceived action from other actions and obtain predictive response information when it identifies and confirms it according to the constantly changing motion information on the field. Action recognition mainly includes two aspects: one is to obtain the required action information based on visual observation and the other is to judge the action based on the obtained action information, but the neuropsychological mechanism of this process is still unknown. In this paper, a new key frame extraction method based on the clustering algorithm and multifeature fusion is proposed for sports videos with complex content, many scenes, and rich actions. First, a variety of features are fused, and then, similarity measurement can be used to describe videos with complex content more completely and comprehensively; second, a clustering algorithm is used to cluster sports video sequences according to scenes, eliminating the need for shots in the case of many scenes. It is difficult and complicated to detect segmentation; third, extracting key frames according to the minimum motion standard can more accurately represent the video content with rich actions. At the same time, the clustering algorithm used in this paper is improved to enhance the offline computing efficiency of the key frame extraction system. Based on the analysis of the advantages and disadvantages of the classical convolutional neural network and recurrent neural network algorithms in deep learning, this paper proposes an improved convolutional network and optimization based on the recognition and analysis of human actions under complex scenes, complex actions, and fast motion compared to post-neural network and hybrid neural network algorithm. Experiments show that the algorithm achieves similar human observation of athletes' training execution and completion. Compared with other algorithms, it has been verified that it has very high learning rate and accuracy for the athlete's action recognition. [ABSTRACT FROM AUTHOR]

Isomorphous substitution of heteroatoms is an effective platform for finely tuning the pore chemistry, pore structure, and surface properties of the zeolite framework as catalysts or separation membranes. A continuous and compact isomorphously substituted tungsten (W)‐MFI membrane was firstly developed on coarse α‐Al2O3 tube dip‐coated with W‐MFI seeds using hydrothermal secondary growth and pretreated synthesis solution. The synthesized W‐MFI membrane is found to be ethanol permselective having a pervaporation based separation factor and flux of 69 and 2.50 kg/m2 h, respectively while exhibiting the highest separation index of 170 kg/m2 h for the separation of 5 wt% ethanol‐water mixture among the reported heteroatoms substituted and α‐Al2O3 supported tubular MFI membranes. The isomorphous substitution of W improves the hydrophobicity and also plays a significant role for the enhanced separation performance. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method for dynamic label assignment in temporal action detection (TAD) called Optimal Action Segment Assignment (OASA). The OASA method converts label assignment into an optimal transportation problem by computing the cost matrix between predicted temporal action segments and groundtruths. The unit transportation cost between a predicted temporal segment and a groundtruth pair is defined as the weighted summation of action classification loss and temporal localization loss. Additionally, we deploy Adaptive Estimation of Candidate Segment Number (AE-CSN) to adaptively determine the number of positive samples for each groundtruth. After formulation, the label assignment problem is converted to find a global optimal assignment plan by minimizing the cost. Therefore, OASA eliminates the need for manually designed prior parameters, which exist in fixed label assignment methods, and improves the generalization of the algorithm between different datasets. To evaluate OASA, we also introduce a simple anchor-free temporal action detector called ActionMixer. It consists of two components: Temporal Mixer and Channel Mixer. The Temporal Mixer employs depth-wise convolution layers with large kernels to capture temporal information, while the Channel Mixer mixes and extracts features across the channel dimension. Extensive experiments conducted on the THUMOS-14, ActivityNet-1.3, and EPIC-Kitchens-100 datasets show that ActionMixer equipped with OASA achieves state-of-the-art performance, surpassing other advanced temporal action detection methods. • Optimal Action Segment Assignment is proposed for Temporal Action Detection. • Optimal Action Segment Assignment removes the temporal prior. • ActionMixer is proposed to evaluate Optimal Action Segment Assignment. • ActionMixer achieves state-of-the-art performance on the popular benchmarks. [ABSTRACT FROM AUTHOR]

Stochastic resonance (SR) and self-induced stochastic resonance (SISR) are two kinds of important dynamical phenomena in the nonlinear system. SR occurs at the frequency of the characteristic signal. However, SISR can occur at a frequency that is included in the excitation. In present, there are volumes of literatures focusing on extracting the bearing fault characteristics from the vibration signal by SR method. However, the occurrence of SISR may result in the fault features misjudgment in SR processing. Through experimental verifications, we find that the interference of SISR is illustrated strongly in the fault characteristics identification. More importantly, the transition from SISR to SR corresponds to the evolution process of bearing state from normal to damage. Therefore, this evolutionary process can not only judge the state of bearing, but also describe the severity of bearing failure. The result is verified by processing the signals of bearing fault with different severity in noise background. They are the most important findings in this work. [ABSTRACT FROM AUTHOR]

In previous research works, logical stochastic resonance (LSR) was reported to frequently occur in an asymmetric bistable system, where the bias parameter is the key factor to make the LSR appear. In this work, we investigate the effect of different anharmonic periodic signals on the pitchfork and saddle-node bifurcations in a symmetric bistable system. We focus on the relationship between the static bifurcation and LSR. We use both numerical and circuit simulations to analyze some interesting phenomena. Like the bias parameter, some anharmonic periodic signals also break the symmetry of the symmetric bistable system and lead to the saddle-node bifurcation. The anharmonic periodic signal with a constant term in its expanded Fourier series induces a reliable LSR in the symmetric bistable system. The key factor of LSR is the saddle-node bifurcation which implies the asymmetry of the system. Here, we replace the bias parameter by choosing an anharmonic periodic signal and make the LSR occur in a different way. [ABSTRACT FROM AUTHOR]

In the traditional heap leaching of rare earth minerals, the top of the rare earth pile is covered with leaching liquid. This creates trouble for vegetation restoration carried out timely on the top of the pile. In order to solve this trouble, a novel pile structure into which leaching liquid is laterally injected is proposed for heap leaching of rare earth. In this study, a laboratory test is carried out to study the formation and distribution of preferential flow paths for the rare earth pile under a horizontal liquid injection condition. Furthermore, numerical simulations based on a dual-permeability model are conducted to investigate the influence of the preferential flow paths on the seepage characteristics in the rare earth pile. The results show that, under the horizontal liquid injection condition, the fine particles of the rare earth move away from the liquid injection end and also toward the lower part of the pile. The migration of the fine particles results in the formation and connection of macropore, thereby generating preferential flow paths in the rare earth pile. The preferential flow paths are mainly distributed in the lower part of the pile near the liquid injection end. This causes the fluid in the lower part of the pile to seep faster significantly than that in the upper part. Within the region where the preferential flow paths develop, the seepage in the early stage of the horizontal liquid injection is dominated by preferential flow. The preferential flow is more significant at the locations farther away from the liquid injection end. [ABSTRACT FROM AUTHOR]

Background: Starch is one of the most important renewable polysaccharides in nature for production of bio-ethanol. The starch saccharification step facilitates the depolymerization of starch to yield glucose for biofuels production. The filamentous fungus Aspergillus niger (A. niger) is the most used microbial cell factory for production of the commercial glucoamylase. However, the role of each component in glucoamylases cocktail of A. niger O1 for starch saccharification remains unclear except glucoamylase. Results: In this study, we identified the key enzymes contributing to the starch saccharification process are glucoamylase, α-amylase and acid α-amylase out of 29 glycoside hydrolases from the 6-day fermentation products of A. niger O1. Through the synergistic study of the multienzymes for the starch saccharification in vitro, we found that increasing the amount of α-amylase by 5-10 times enhanced the efficiency of starch saccharification by 14.2-23.2%. Overexpression of acid α-amylase in strain O1 in vivo increased the total glucoamylase activity of O1 cultures by 15.0%. Conclusions: Our study clarifies the synergistic effects among the components of glucoamylases cocktail, and provides an effective approach to optimize the profile of saccharifying enzymes of strain O1 for improving the total glucoamylase activity. [ABSTRACT FROM AUTHOR]

Light‐driven nanomotors have attracted much attention due to their potential applications. The movement of conventional nanomotors typically occurs in the solution phase, which limits their application fields. Utilizing visible light to drive nanomotors at the solid–liquid interface represents a grand challenge due to the large friction force between the nanomotor and the solid surface. Based on the attractive plasmon resonance of Au nanocrystals, for the first time, plasmon‐enhanced Au nanocrystal‐based nanomotors moving at the silicon–aqueous solution interface have been developed. Such nanomotors move with a clear trace engraved on the Si surface, representing an excellent and exceptional self‐traced nanomotor system. In addition, the nanomotor trace on the Si surface also provides a unique and promising approach to the fabrication of nanoscale Si patterns, which is central to many applications, including microelectronics, sensing, information storage, and optoelectronics. [ABSTRACT FROM AUTHOR]

Light‐driven nanomotors have attracted much attention due to their potential applications. The movement of conventional nanomotors typically occurs in the solution phase, which limits their application fields. Utilizing visible light to drive nanomotors at the solid–liquid interface represents a grand challenge due to the large friction force between the nanomotor and the solid surface. Based on the attractive plasmon resonance of Au nanocrystals, for the first time, plasmon‐enhanced Au nanocrystal‐based nanomotors moving at the silicon–aqueous solution interface have been developed. Such nanomotors move with a clear trace engraved on the Si surface, representing an excellent and exceptional self‐traced nanomotor system. In addition, the nanomotor trace on the Si surface also provides a unique and promising approach to the fabrication of nanoscale Si patterns, which is central to many applications, including microelectronics, sensing, information storage, and optoelectronics. [ABSTRACT FROM AUTHOR]

Enzymes and cell factories play essential roles in industrial biotechnology for the production of chemicals and fuels. The properties of natural enzymes and cells often cannot meet the requirements of different industrial processes in terms of cost-effectiveness and high durability. To rapidly improve their properties and performances, laboratory evolution equipped with high-throughput screening methods and facilities is commonly used to tailor the desired properties of enzymes and cell factories, addressing the challenges of achieving high titer and the yield of the target products at high/low temperatures or extreme pH, in unnatural environments or in the presence of unconventional media. Droplet microfluidic screening (DMFS) systems have demonstrated great potential for exploring vast genetic diversity in a high-throughput manner (>106/h) for laboratory evolution and have been increasingly used in recent years, contributing to the identification of extraordinary mutants. This review highlights the recent advances in concepts and methods of DMFS for library screening, including the key factors in droplet generation and manipulation, signal sources for sensitive detection and sorting, and a comprehensive summary of success stories of DMFS implementation for engineering enzymes and cell factories during the past decade. [ABSTRACT FROM AUTHOR]

Tunnel blast-induced vibration probably causes damage to the rock mass surrounding the tunnel surface and also to the rock mass of the slope at the tunnel entrance. It is important to simultaneously monitor the vibration on the tunnel surface and on the tunnel entrance slope face, especially when the blasting work face is close to tunnel entrance. During blasting excavation of the traffic tunnel at Baihetan hydropower station, vibration monitors were installed both on the tunnel surface and on the tunnel entrance slope face. Based on the monitoring data, a comparative study is conducted on the peak particle velocity (PPV) and frequency characteristics of the vibrations at these two locations. A three-dimensional FEM simulation of the tunnel blast is then performed to verify the field test results. The field monitoring and the numerical simulation show that there is significant difference between the vibration on the tunnel surface and that on the tunnel entrance slope face. The vibration on the tunnel surface has greater PPV and faster attenuation, while the tunnel entrance slope face has higher frequency and faster reduction rate in the center frequency. These differences are attributed to the different wave types and wave propagation paths. The tunnel surface is mainly surface waves transmitted through the damaged rock mass around the tunnel profile, while the tunnel entrance slope face originates mainly from the body waves transmitted via the undamaged rock mass inside the mountain. The comparisons of the monitored vibrations with the velocity limits specified in the Chinese standard show that the most dangerous vibration that may exceed the limit occurs on the tunnel surface. Therefore, the maximum charge weight used in the tunnel blast is determined by the vibration on the tunnel surface. Under different control standards, the allowable maximum charge weight per delay is further discussed. [ABSTRACT FROM AUTHOR]

At present, the rationality and applicability of various high-temperature performance evaluation indexes for polymer-modified asphalts have not been comprehensively explored. This study aimed to fully explore their rationality and applicability. For this purpose, five asphalt binders including four representative polymer-modified asphalts and one neat asphalt (NA) were chosen, and many of their high-temperature performance indexes were first obtained by using a series of tests. Then the five corresponding asphalt mixtures were fabricated and their high-temperature performance indexes were also obtained by performing a wheel tracking test. On this basis, the high-temperature potential of asphalt binders was evaluated using the obtained indexes, and the correlation between the indexes of asphalt binders and their mixtures was analyzed via data processing software. Results show that the rankings of high-temperature performance of these five asphalt binders are not exactly consistent when all the high-temperature performance indexes—including penetration (P) at 25°C, penetration index (PI), equivalent softening point (T800), softening point (SP), dynamic viscosity (DV) at 60°C, rutting factor (G*/sinδ), improved rutting factor [G*/(sinδ)9] , Shenoy's nonrecoverable compliance (JShenoy), critical temperature of rutting factor (TG*/sinδ), nonrecoverable creep compliance (Jnr), creep modulus (GV), zero shear viscosity (ZSV), and generalized dynamic shear modulus (GDSM)—are utilized for evaluation. However, all the indexes can distinguish the polymer-modified asphalts from NA well. Among these indexes, the evaluation results of Jnr at different temperatures are consistent at the same stress level (0.1 or 3.2 kPa), and all the correlation coefficients between the Jnr and dynamic stability (DS) of asphalt mixtures exceed 0.9; thus, the Jnr is recommended as the dominant evaluation index. The G*/sinδ , TG*/sinδ , and GV correlate weakly with the DS, and the ZSV performs poor repeatability in the test; thus, their rationality needs to be further verified using more asphalt samples. [ABSTRACT FROM AUTHOR]

Bolts are utilised extensively in machinery and often bear large loads. Reliable connection of bolts is related to the effective functioning of machinery. Therefore, it is of utmost importance to detect bolt looseness in time. However, the identification of bolt looseness is typically challenging due to the strong background noise. Compared with Gaussian white noise, only few researches were conducted on Poisson white noise. To detect the looseness of the bolt in the presence of strong Poisson white noise, we propose a novel method based on sub-harmonic resonance, time-domain averaging and adaptive stochastic resonance. The disadvantages of damaging characteristic frequencies that exist in a majority of approaches are overcome. In addition, the looseness is assessed by the quality factor derived from physical science. To verify the efficacy of the method, we propose numerical simulations and experimental validations. The results demonstrate that the proposed method has effectively detected bolt looseness under strong Poisson white noise. The detection of bolt looseness might benefit greatly by adopting the suggested approach. [ABSTRACT FROM AUTHOR]

Recently, the development of pillar-layered metal-organic frameworks (MOFs) is receiving more and more attention because of their pore surface chemistry tunability and designability. In this work, we firstly synthesized various sizes of high-quality Ni-LAP [Ni 2 (L-asp) 2 (pz)] (L-asp = l -aspartic acid, pz = pyrazine) crystals key for secondary growth by manipulating the crystal thermal dynamics and kinetics of Ni-LAP synthesis solution simply through choosing the Ni(OAc) 2 as metal source and pretreatment at 40 °C, followed by the fabrication of defect-free Ni-LAP membranes as a model in a short time of 4 h using the linker salt method. It is found the pretreatment of Ni(OAc) 2 precursor solution at 40 °C with continuous stirring for 6 h can effectively promote deprotonation to form 250 nm crystals. The linker salt method enables a greener and more rapid synthesis of Ni-LAP membranes, with continuous and compact Ni-LAP membranes, where soluble metal precursors and organic linking salts provide the synthesis solution a higher degree of supersaturation, both of which play an important role in the rapid preparation of Ni-LAP membranes. The preparation parameters of the Ni-LAP membranes were investigated in detail, and the results from the Ni-LAP membrane gas separation performance showed that the preferential (111) orientation membrane (M9) exhibited the best H 2 /CO 2 separation performance with separation factor of 23.8 and H 2 permeance of 2.11 × 10−7 mol m−2 s−1 Pa−1 compared to the preferential (002) orientations (M3), which may attributed to the preferential (111) orientation being at an angle to the optimal a-axis aperture perpendicular to the support thereby reducing the mass transfer resistance. Furthermore, the generation of corrosive nitric acid during the preparation process can be greatly reduced and replaced by eco-friendly potassium nitrate. The superiority of the pore structure and the remarkable stability of these MOF membranes show the potential for H 2 purification. Moreover, our preparation route demonstrates the universality of preparing other isomorphs, such as Ni-LAB and Co-LAP membranes. A rapid synthesis strategy through linker salt method was proposed for preparing pillar-layered [Ni 2 (L-asp) 2 (pz)] (Ni-LAP) membranes with good H 2 /CO 2 perm-selectivity as a model system by manipulating the crystal thermal dynamics and kinetics of Ni-LAP to obtain uniform near-nanocrystal seeds, followed by secondary growth using L-asp salt (KHL-asp) in a short time of 4 h, offering a highly effective and universal platform to develop novel MOFs membrane. [Display omitted] • Various sizes of high-quality Ni-LAP crystals were successfully prepared. • Dense tubular Ni-LAP membranes were fabricated by linker salt method. • The soluble Ni(NO 3) 2 ·6H 2 O and organic linker salt KHL-asp played important roles in the preparation of Ni-LAP membrane. • Ni-LAP membrane with preferential (111) orientation shows higher H 2 selectivity and permeance. [ABSTRACT FROM AUTHOR]

This study investigates the propagation and attenuation characteristics of shock waves produced by drilling and blasting. The focus is on a novel method for calculating the attenuation of the shock wave pressure. Based on the propagation of shock waves in a rod with a variable section and a Maxwell model for rock, theoretical solutions for the attenuation of the blast-induced shock wave pressure were derived and the main factors influencing the attenuation speed were analyzed. The attenuation law of shock waves for siltstone, limestone, and granite, with common borehole diameters of 76–150 mm and initial shock pressures of 1–6 GPa, was analyzed through numerical simulations. The results show that the shock wave falls off as the square root of the relative distance. The attenuation speed of the shock wave is mainly related to the borehole size, rock properties, and shock wave intensity. The attenuation speed increases with increasing initial shock pressure on the borehole wall, but decreases with increasing borehole radius. Compared with soft rock, the shock wave pressure attenuates faster in hard rock. Combining theoretical analysis and numerical simulations, an exponential attenuation coefficient was introduced to the attenuation formula. Statistical analysis shows that the exponential attenuation coefficient is linearly proportional to the initial shock pressure. Furthermore, a new method for calculating the attenuation of shock wave pressure was proposed, reflecting the comprehensive influence of rock characteristics and shock wave intensity. The new method is an improvement over existing methods, which only consider the effect of rock properties on shock wave attenuation. The reliability of the new method was verified against the results of field tests. The findings provide a theoretical basis for the optimization of blasting parameters and assessments of blast-resistance for structures. [ABSTRACT FROM AUTHOR]

Background. To investigate the effects of phenylethanoid glycosides (PhGs) extracted from Herba Cistanches on the behavioral and cognition capacity of the APP/PSI transgenic mice with Alzheimer's disease (AD). Methods. AD mice were randomly divided into the control group, model group, donepezil group, PhG groups, and verbascose group, respectively. Three weeks later, the animals were subject to behavioral and cognition evaluation by the nesting test, Morris water maze test, and step-down test. Results. The cognition capacity in these groups showed a significant increase compared with that in the model group. The step-down test indicated that the errors induced by the memory decrease in the PhG groups and verbascose group showed a significant decrease compared with those in the model group (P < 0.05). Conclusions. PhGs attenuated the cognitive dysfunction features of the APP/PSI transgenic gene. Besides, PhGs were the active components for the anti-AD activity of H. Cistanches. [ABSTRACT FROM AUTHOR]

Nitrogen fixation is an essential process for sustaining life. Tremendous efforts have been made on the photodriven fixation of nitrogen into ammonia. However, the disproportionation of dinitrogen to ammonia and nitrate under ambient conditions has remained a grand challenge. In this work, the photodriven disproportionation of nitrogen is realized in water under visible light and ambient conditions using Fe‐doped TiO2 microspheres. The oxygen vacancies associated with the Fe dopants activate chemisorbed N2 molecules, which can then be fixed into NH3 with H2O2 as the oxidation product. The generated H2O2 thereafter oxidizes NH3 into nitrate. This disproportionation reaction can be turned to the reductive one by loading plasmonic Au nanoparticles in the doped TiO2 microspheres. The generated H2O2 can be effectively decomposed by the Au nanoparticles, resulting in the transformation of the disproportionation reaction to the completely reductive nitrogen photofixation. [ABSTRACT FROM AUTHOR]

Nitrogen fixation is an essential process for sustaining life. Tremendous efforts have been made on the photodriven fixation of nitrogen into ammonia. However, the disproportionation of dinitrogen to ammonia and nitrate under ambient conditions has remained a grand challenge. In this work, the photodriven disproportionation of nitrogen is realized in water under visible light and ambient conditions using Fe‐doped TiO2 microspheres. The oxygen vacancies associated with the Fe dopants activate chemisorbed N2 molecules, which can then be fixed into NH3 with H2O2 as the oxidation product. The generated H2O2 thereafter oxidizes NH3 into nitrate. This disproportionation reaction can be turned to the reductive one by loading plasmonic Au nanoparticles in the doped TiO2 microspheres. The generated H2O2 can be effectively decomposed by the Au nanoparticles, resulting in the transformation of the disproportionation reaction to the completely reductive nitrogen photofixation. [ABSTRACT FROM AUTHOR]

By combining convex programming (CP) and particle swarm optimization (PSO), a hybrid method for the synthesis of excitations and locations of nonuniformly spaced linear subarrays to minimize the subarray number is proposed and discussed in this article. The synthesis problem herein is formulated as a CP problem by minimizing the $l_{1}$ -norm with respect to the excitation variables, and the PSO procedure is carried out as far as location variables are concerned. Through collaborations like this, we can finally get the optimal solution in a global sense. A set of representative numerical experiments shows the effectiveness of this method with quite a number of subarrays saved when compared with the uniformly spaced layouts. [ABSTRACT FROM AUTHOR]

Stochastic resonance is significant for signal detection. In this paper, a method to improve the stochastic resonance performance in a bistable system excited by bounded noise is studied. Specifically, we add a high-frequency signal to the system as an auxiliary excitation to induce vibrational resonance and focus on the influence of the auxiliary excitation waveform on the improvement effect. We investigate the stochastic resonance performance improved by a fast excitation in different waveforms through numerical simulations. The results show that, the improvement effect of the stochastic resonance depends on the waveform of the fast excitation closely. The symmetry property and constant component of the fast excitation are two key factors. Further, we accomplish the circuit simulation by constructing a circuit to generate bounded noise and the circuit of the bistable system. [ABSTRACT FROM AUTHOR]

Disruptive behavior by passengers delayed at airport terminals not only affects personal safety but also reduces civil aviation efficiency and passenger satisfaction. This study investigated the causal mechanisms of disruptive behavior by delayed passengers in three aspects: environmental, managerial, and personal. Data on flight delays at Shenzhen Airport in 2018 were collected and analyzed. The main factors leading to disruptive behavior by delayed passengers were identified, and an early warning model for disturbances was developed using multiple logistic regression and a back-propagation(BP) neural network. The results indicated that the proposed model and method were feasible. Compared to the logistic regression model, the BP neural network model had advantages in predicting disturbances by delayed passengers, showing higher prediction accuracy. The BP network weight analysis method was used to obtain the influence weight of each factor on behavior change of delayed passengers. The influence weight of different factors was obtained, providing an assistant decision-making method to address disruption from flight-delayed passengers. [ABSTRACT FROM AUTHOR]

Cybersecurity comprised all the technologies and practices that protect data as well as computer and network systems. In this article, we develop four course modules on critical cybersecurity topics that can be adopted in college-level cybersecurity courses in which these topics are covered. Our goal for developing these course modules with the hands-on labs is to increase students' understanding and hands-on experiences on these critical topics that support cyber skills development for college students. The hands-on labs are designed to enhance students' engagement and provide them hands-on experiences with real-world cyber activities to augment their cyber education of both foundational and advanced skills. We also conduct research surveys on the most-recent significant research in these critical cybersecurity fields. These cybersecurity course modules with the labs are also designed to help college/university professors enhance and update their cybersecurity course content, activities, hands-on lab exercises, and pedagogical methods, as well as emphasize the cyber skills to meet today's pressing cybersecurity education needs for college students. Our proposed cybersecurity modules with hands-on labs will also help building the nation's cybersecurity workforce. [ABSTRACT FROM AUTHOR]

The laser technique based sensors and actuators can provide many superior properties as noncontact, high sensitivity, remote operation, and reliable performance in contrast to other mechanical and electrical techniques. In this paper, we design and fabricate a high‐precision 360° laser receiver for leveling, especially for agricultural and construction field. The laser receiver is primarily composed of photoelectrical conversion module, electrical signal processing module, and display panel module. Based on the centroid method, the detection error of the laser receiver with respect to laser source and silicon photocell array, is analyzed and simulated. The design and fabrication process are described in detail, including the overall structure and electrical circuits. Furthermore, this fabricated laser receiver is demonstrated to be high precision through several static and dynamic tests in the distance of 10 and 50 m. Besides, this fabricated laser possesses wireless transmission function, which provides much convenient for users in remote operation. [ABSTRACT FROM AUTHOR]

In magnetic prospecting, the total field anomaly formula that represents the projection of the magnetic anomaly vector on the geomagnetic field is widely used because it simplifies the calculation of forward modelling and inversion of magnetic data. However, the projection anomaly yields errors relative to the true observed magnetic anomaly, especially for high-amplitude magnetic anomalies such as in iron orebody and unexploded ordnance prospecting. In this study, we analyse the difference between the projection anomaly and observed modulus difference anomaly with physical parameters, and propose to directly invert for the modulus difference anomaly by constructing a nonlinear matrix equation between the model corrections and data corrections. The inversion is then implemented using a preconditioned conjugate gradient algorithm. Synthetic and field magnetic data were used to test the inversion method. Comparison of the two types of total field anomalies shows that the error of the projection anomaly increased with increasing total-field magnetic anomaly. When the total-field magnetic anomaly was < 5,000 nT, the difference between the projection anomaly and modulus difference anomaly results can be ignored. For high-amplitude magnetic anomalies, the modulus difference anomaly inversion produced more accurate representations of both the shape and location of the magnetic sources. [ABSTRACT FROM AUTHOR]

We investigate the effects on the pitchfork bifurcation and the vibrational resonance of an overdamped bistable system subjected to both a slow harmonic excitation and a fast periodic excitation with different waveforms. We use numerical simulations along with theoretical explanations to analyze some interesting phenomena. The bifurcation configuration depends closely on the form of the fast excitation. As a result, we have found that the key factor to influence the bifurcation configuration is the symmetry property of the fast excitation. Further, due to the relationship of the vibrational resonance with the pitchfork bifurcation, the vibrational resonance also depends closely on the form of the fast periodic excitation. Moreover, for anharmonic fast excitations, if it is asymmetric, the vibrational resonance usually depends closely on the initial conditions. [ABSTRACT FROM AUTHOR]