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The impact of the coronavirus disease 2019 (COVID-19) pandemic on the etiology of non-COVID-19 viral pneumonia remains to be identified. We investigated the evolution of non-COVID-19 viral pneumonia in hospitalized patients before and after the COVID-19 pandemic.

• N/S-Nb 2 CT x catalyst improves hydrogen storage properties of MgH 2. • The composite can release 4.78 wt% of H 2 within 30 min at 225 °C. • Dehydrogenation activation energy of the composite is 47.44 % reduced than MgH 2. • The energy barrier of hydrogen atom diffusion is reduced by the N/S co-doped. • The composite has the excellent cycling stability within 30 cycles. While MgH 2 has high hydrogen storage capacity, its high dehydrogenation temperature and sluggish de-/hydrogenation rate have hindered practical application. In the present work, a non-metallic element (N, S) co-doped Nb 2 CT x MXene catalyst (N/S-Nb 2 CT x) is employed to improve the hydrogen storage property of MgH 2. The dehydrogenation activation energy of MgH 2 +N/S-Nb 2 CT x composite is reduced to 70.00 kJ mol–1 H 2 , which is much lower than that of MgH 2 +Nb 2 CT x (99.44 kJ mol–1 H 2) and Milled-MgH 2 (133.19 kJ mol–1 H 2). The composite can release about 4.78 wt% of H 2 within 30 min at 225 °C and uptake about 4.00 wt% of H 2 within 80 min even at 30 °C under 30 bar H 2 , which is significantly better than most of the reported MgH 2 +Nb-based-catalyst composites. The mechanism analysis reveals that the stable layered structure of the N/S-Nb 2 CT x catalyst provides enough nucleation sites for MgH 2 /Mg, and the in-situ formed substances (Nb, NbO 2) play the role of elongating Mg–H bond. Besides, the N, S co-doped effectively enhances the ability of multivalent Nb elements to promote the electron transfer between Mg2+ and H–, and it promotes the diffusion of hydrogen through weakening the interaction between Nb and H atoms, thus the de-/hydrogenation kinetics and cyclic stability of MgH 2 is significantly improved. This work not only proves that Nb 2 CT x can effectively enhance its catalytic activity by N and S co-doping, but also provides a MXene-based catalyst design concept for highly efficient hydrogen storage catalysts. [Display omitted] [ABSTRACT FROM AUTHOR]

Magnesium (Mg) matrix composites (Mg-MMCs) with high strength and ductility properties are crucial for the development of lightweight automobiles. In this study, a novel method is proposed for fabricating Mg-MMCs by incorporating nanocopper (Cu) decorated titanium (Ti) particles (Cu@Ti) to reinforce AZ91 alloys. The in-situ generation of the AlCuMg phase at the interface between the Ti particles and the Mg matrix enhances interface integration and promotes the formation of massive twins. The 5.0 wt% Cu@Ti/AZ91 composite exhibits notable mechanical properties, with a yield strength of 238 MPa, ultimate tensile strength of 368 MPa, elongation of 12%, and modulus of elasticity of 46 GPa. These values represent increases of 8.9%, 5.3%, 50.0%, and 2.0%, respectively, compared to those of AZ91 alloys. The strengthening mechanism is mainly attributed to grain refinement strengthening, thermal expansion coefficient mismatch strengthening, Orowan strengthening, and load transfer strengthening. The plasticity improvement benefits from the optimization of the interface structure, grain refinement and twin formation.

For magnesium (Mg) matrix composites (MMCs), trade-off between strength and plasticity has long been an issue of puzzle. In this work, hot-press sintering and hot extrusion are used to prepare Ti particles (Tip) reinforced AZ31 (Tip/AZ31) composites. The strength, plasticity, and wear resistance of Tip/AZ31 composites are improved simultaneously. Ti particles refine the grains of composites and accelerate the precipitation of Mg17Al12particles in Mg matrix. The best tensile properties and wear resistance are achieved in 6 wt%Tip/AZ31 composite, with ultimate tensile strength of 290 MPa, elongation of 15.5 %, and wear rate of 4.343 × 10−3 mm3/m, respectively. Especially, the wear rate of 6 wt%Tip/AZ31 is reduced by 54.6 % compared to the matrix alloy. The underlying strengthening mechanisms, toughness mechanisms, and wear mechanisms of Tip/AZ31 composites were discussed in detail.

The on-board damage detection methods are recently applied to the structural health monitoring (SHM) for railway bridge, and with more economical and efficient than the traditional methods. However, to improve the calculation efficiency and avoid the detection sensitivity of the on-board methods decreasing, most researchers always leave out the track structure in simulation models, while it is not consistent with the complex actual situation. To realize the accurate detection, a novel on-board damage detection method for heavy-haul railway bridge using bogie accelerations is put forward, which is availably implemented for both of damage localization and damage quantification. A relatively complete model considering train–track–bridge interaction is established, and a model simplification method of railway bridge is proposed based on the finite element shape function to improve calculation efficiency further. The sensitivity of the bogie vertical accelerations to damage is analyzed to construct the sensitivity equation of coupling system. By iteratively solving the sensitivity equation and modifying the numerical model, the bridge damage can be identified. For an exhaustive evaluation of the feasibility of the proposed method, different damage scenarios are taken into account. The results demonstrate that the proposed method has a better performance in localizing and quantifying damage than the traditional method. Moreover, the influences of operational parameters such as track irregularity and vehicle speed on the validity and robustness of method are investigated. It is found that the rougher track irregularity and the higher vehicle speed seem to be more in favor of damage identification.

Introduction:Malignant hypertension (mHTN) is a hypertensive emergency. Thrombotic microangiopathy (TMA) is a widespread complication of mHTN. Few studies have evaluated whether glomerular hematuria provides prognostic information for renal dysfunction in patients with mHTN-associated TMA. Methods:This observational cohort study included 292 patients with mHTN-associated TMA based on renal biopsy. Propensity-score matching (PSM) analysis was conducted to adjust for clinical characteristics in a comparison between with and without glomerular hematuria. Cox regression was employed to identify risk factors for renal prognosis. Results:A total of 70 patients with glomerular hematuria were compared to 222 patients with non-glomerular hematuria. After PSM, 67 pairs of patients with mHTN-associated TMA were matched. Patients with glomerular hematuria exhibited lower serum albumin levels, higher 24-h proteinuria, and a higher prevalence of glomerular sclerosis than those with non-glomerular hematuria. Glomerular hematuria was independently associated with deteriorated renal function compared with non-glomerular hematuria (HR: 0.51; 95% CI: 0.29–0.89, p= 0.019). This association remained significant after PSM (HR: 0.51; 95% CI: 0.28–0.91, p= 0.022). Additionally, glomerular hematuria was independently associated with renal replacement therapy (RRT) (HR: 3.14; 95% CI: 2.06–5.66, p< 0.001). This difference remained significant after PSM comparison (HR: 2.41; 95% CI: 1.34–4.33, p= 0.003). Furthermore, despite intensive blood pressure control, patients with glomerular hematuria experienced a higher incidence of RRT and a poorer recovery in renal function, specifically a 25% reduction of creatinine levels, compared to patients with non-glomerular hematuria. Conclusion:Glomerular hematuria is significantly associated with an increased risk of adverse renal outcomes in patients with mHTN-associated TMA.

The complexity of traffic scenarios, the spatial-temporal feature correlations pose higher challenges for traffic prediction research. Traffic spatial-temporal model is an essential method in this research field, primarily focusing on capturing the spatial-temporal features among nodes and their neighboring nodes. However, existing methods lack comprehensive consideration of directional and hierarchical features among traffic nodes. They are mostly applicable to scenarios with random uniform distribution of nodes, but not suitable for more complex small-scale aggregation distribution scenarios. Therefore, this study proposes the Tree Convolutional Network (TreeCN), a tree-based structure. The data design and model design of TreeCN focus on capturing the directional and hierarchical features among nodes. The directional and hierarchical relationships among nodes are represented by the plane tree matrix and constructed as the spatial tree matrix. The TreeCN, with a full convolution network, performs a bottom-up convolution structure on the tree matrix to complete the task of node feature capturing. In this study, TreeCN is thoroughly compared with statistical, machine learning, and deep learning methods in traffic time series prediction. The experimental results show that TreeCN not only performs well in scenarios with random uniform distribution but also exhibits outstanding effect in more complex small-scale aggregation distribution. Moreover, TreeCN adheres to the design principles of Graph Convolutional Networks (GCN) in capturing the spatial features of traffic nodes and can further capture directional and hierarchical features among them. This is expected to make TreeCN a new method to handle complex traffic scenarios and improve prediction accuracy.

The unstable interface between lithium metal anodes and carbonate-based electrolytes is a key challenge limiting the cycling lifespan of high-energy lithium metal batteries. Here, a resilient artificial solid electrolyte interphase (RASEI) was designed by regulating poly(hexafluorobutyl acrylate) (PHFBA) matrix with the benzene-containing bisphenol A ethoxylate dimethacrylate (BAED) crosslinker to address this issue. The rigid BAED molecule can finely tune the flexible PHFBA matrix, enabling superior resilience from 600% elongation to 90% compression with a high Young’s modulus of over 2 MPa. RASEI with these characteristics can accommodate large volume changes of lithium metal and ensure the intimate contact between the lithium metal and the RASEI during battery operation. Consequently, it facilitated homogeneous lithium deposition while mitigating parasitic side reactions. Thanks to the tough and resilient nature of the fluorinated RASEI, the long-term cycling of Li∣∣Li symmetric cells can be achieved for over 500 h at 1 mA cm−2and 1 mAh cm−2. The following post-mortem of cycled Li metal reveals that Li dendrite growth is effectively inhibited. Furthermore, the NCM811 pouch cell with a high cathode loading of 20 mg cm−2exhibits a capacity retention of over 85% after 200 cycles at 1 C.

Understanding the pharmacokinetic profiles of nanomaterials in living organisms is essential for their application in disease treatment. Bipyramidal DNA frameworks (BDFs) are a type of DNA nanomaterial that have shown prospects in the fields of molecular imaging and therapy. To serve as a reference for disease-related studies involving the BDF, we constructed a 68Ga-BDF and employed positron emission tomography (PET) imaging to establish its pharmacokinetic model in healthy mice. Our investigation revealed that the BDF was primarily eliminated from the body viathe urinary system. Ureteral obstruction could significantly alter the metabolism of the urinary system. By utilizing the established pharmacokinetic model, we sensitively observed distinct imaging indicators in unilateral ureteral obstruction and acute kidney injury (a complication of ureteral obstruction) mouse models. Furthermore, we observed that the BDF showed therapeutic effects in an AKI model. We believe that the established pharmacokinetic model and unique renal excretion characteristics of the BDF will provide researchers with more information for studying kidney diseases.

The determination of the time of an injury has been a major problem in forensic science due to the lack of objective, reliable and portable methods. In this study, a subcutaneous hemorrhage model in rats was established over six days, and attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy coupled with chemometrics was used to determine the time since injury. Initial principal component analysis (PCA) showed variance among hematoma sites. Subsequently, spectral data were acquired to establish a dependable partial least square (PLS) regression model with predictive abilities. The root mean square error of cross-validation (RMSECV) and the root mean square error of prediction (RMSEP) values produced by a genetic algorithm (GA) were 0.64 d (R2= 0.88) and 0.57 d (R2= 0.90), respectively. Few variables were involved in the model, and significantly better results were obtained in comparison to the conventional full-spectrum PLS model. In combination with the results of variable importance in projection (VIP) scores, all components, including proteins, nucleic acids and phospholipids, provided inferences regarding the samples at different time points; additionally, amide I and II bands represented the secondary structure of proteins and provided the largest contribution. Based on our preliminary study, the combination of swift and nondamaging ATR-FTIR spectroscopy with chemometrics could prove to be an advantageous approach for gauging the age of an injury in the forensic field.

In smart grid, serious packet loss often occurs in the process of information interaction between the Utilities and customers, which results in supply-demand deviation and further increases the cost of the Utilities. In order to improve the information transmission performance of communication networks, the Utilities purchase relay service from telecom operator to help data aggregator units (DAU) transfer information to gateway (GW), so as to improve communication quality and reduce the cost of the Utilities. Second, in order to solve the problem of telecom operators’ energy reduction and reduce the cost of purchasing energy, we utilize energy supply point (ESP) to collect the surplus energy of retail customers for energy supply, and telecom operator pays a certain amount of remuneration to ESP in exchange for ESP to continuously supply energy to telecom operator. Then, we establish a three-stage game method and system model between the Utilities, telecom operator and ESP, and propose the relay power allocation and energy transaction pricing strategy. Due to the real-time change of energy demand, we consider two situations of energy oversupply and conservative supply, and use the backward induction method and iterative algorithm to obtain the equilibrium solution of the Stackelberg game, including the unit energy price of ESP, total power of telecom operator, the proportion of transmission power allocated to the relay service, and payment scheme of the Utilities. Simulation results show that the proposed algorithm can quickly and accurately converge to the optimal solution of the problem, and the method can improve the stability of demand-side regulation, reduce the cost of the Utilities and increase the profit of telecom operator.

Thermoelectric technology can be utilized to directly convert waste heat into electricity, aiming at energy harvesting in an environmentally friendly manner. As a promising p-type thermoelectric material, CuInTe2possesses a high inherent lattice thermal conductivity, which limits the practical implementation in the field of thermoelectricity. Herein, through the combination of vacuum melting and annealing along with hot-pressure sintering techniques, we demonstrated that CuIn0.95Ag0.05Te2thermoelectric materials with trace Ag doping can exhibit a notably high Seebeck coefficient of 614 μV/K, arising from the high density-of-states effective mass and reduced carrier concentration. Owing to the diminished lattice thermal conductivity derived from Umklapp scattering induced by point defects and dislocation, stemming from the trace Ag doping at In sites rather than Cu sites, CuIn0.95Ag0.05Te2exhibited a maximum figure of merit (ZT) of 1.38 at 823 K, an 18% enhancement over pristine CuInTe2, leading to a maximum average ZTof 0.67 across temperatures ranging from 303 to 823 K. In essence, our work underscores the efficacy of doping engineering and point defects in tailoring the thermoelectric performance of CuInTe2-based materials. This study not only contributes to advancing the fundamental understanding of thermoelectric enhancement but also lays out a practical pathway toward the realization of high-performance CuInTe2-based thermoelectric materials.

Aqueous zinc-ion batteries (AZIBs) are receiving widespread attention due to their abundant resources, low material cost, and high safety. However, the susceptibility of Zn metal anodes to corrosion and hydrogen evolution limits their further practical applications. Replacing Zn metal with intercalation-type anode material and constructing rocking-chair-type batteries could be an effective way to significantly prolong the cycle life of AZIBs. Herein, we present copper selenide with different crystal phase structures through a facile redox reaction as an anode for AZIBs. By comparing and analyzing different copper selenide phases, it is found that the cubic Cu2–xSe shows superior structural stability and highly reversible Zn2+storage. Theoretical calculation results further demonstrate that the cubic Cu2–xSe possesses an increased electrical conductivity, higher Zn2+adsorption energy, and reduced diffusion barrier, thereby promoting the storage reversibility and (de)intercalation kinetics of the Zn2+ion. Thus, the Cu2–xSe anode delivers a long-term service life of over 15 000 cycles and impressive cumulative capacity. Furthermore, the full-cells assembled with the MnO2/CNT cathode operate stably for over 1500 cycles at 6 mA cm–2at a negative/positive (N/P) capacity ratio of ∼1.53. This work provides a more ideal Zn-metal-free anode, which helps to push the practical applications of AZIBs.

Flight dynamics modeling for the Mars helicopter faces great challenges. Aerodynamic modeling of coaxial rotor with high confidence and high computational efficiency is a major difficulty for the field. This paper builds an aerodynamic model of coaxial rotor in the extremely thin Martian atmosphere using the viscous vortex particle method. The aerodynamic forces and flow characteristics of rigid coaxial rotor are computed and analyzed. Meanwhile, a high fidelity aerodynamic surrogate model is built to improve the computational efficiency of the flight dynamics model. Results in this paper reveal that rigid coaxial rotor can bring the Mars helicopter sufficient controllability but result in obvious instability and control couplings in forward flight. This highlights the great differences in flight dynamics characteristics compared with conventional helicopters on Earth.

Volatile organic compounds (VOCs) harm the environment and human health and have been of wide concern and purified efficiently by catalytic oxidation. Spinel oxides, mainly composed of transition metal elements with low price and extensive sources, have been widely investigated as efficient and stable catalysts for VOCs oxidation due to their adjustable element composition, flexible structure, and high thermal/chemical stability. However, it is necessary to dissect the design of the spinel in a targeted way to satisfy the removal of different types of VOCs. This article systematically summarizes the recent advances regarding the application of spinel oxides for VOCs catalytic oxidation. Specifically, the design strategies of spinel oxides were first introduced to clarify their effect on the structure and properties of the catalyst. Then the reaction mechanism and degradation pathway of different kinds of VOCs on the spinel oxides were in detail summarized, and the characteristic requirements of the spinel oxides for various VOCs purification were analyzed. Furthermore, the practice applications were also discussed. Finally, the prospects were proposed to guide the rational design of spinel-based catalysts for VOCs purification and intensify the understanding of reaction mechanisms.

The dispersion characteristics of fuel particles in the dense phase zone in circulating fluidized bed (CFB) boilers have an important influence on bed temperature distribution and pollutant emissions. However, previous research in literature was mostly on small-scale apparatus, whose results could not be applied directly to large-scale CFB with multiple dispersion sources. To help solve this problem, we proposed a novel method to estimate the lateral dispersion coefficient (Dx) of fuel particles under partial coal cut-off condition in a 350 MW supercritical CFB boiler based on combustion and dispersion models. Meanwhile, we carried out experiments to obtain the Dxin the range of 0.1218–0.1406 m2/s. Numerical simulations were performed and the influence of operating conditions and furnace structure on fuel dispersion characteristics was investigated, the simulation value of Dxwas validated against experimental data. Results revealed that the distribution of bed temperature caused by the fuel dispersion was mainly formed by char combustion. Because of the presence of intermediate water-cooled partition wall, the mixing and dispersion of fuel and bed material particles between the left and right sides of the furnace were hindered, increasing the non-uniformity of the bed temperature near furnace front wall.

For magnesium matrix composites (MMCs), it is crucial to enhance their strength while maintaining plasticity. In this work, Ti particle (TiP) reinforced VW94 composites (TiP/VW94 composites) with varying amounts of Ti particles were prepared using a semi-solid stirring-assisted ultrasonic vibration method followed by homogenizing treatment. Microstructural analysis revealed that the addition of Ti particles resulted in grain refinement and facilitated the formation of lamellar long period stacking ordered structure (LPSO) during homogenizing treatment due to the increasing dislocation density. In addition, the jagged interfacial product of MnTi phase was generated at the interface between Ti particles and Mg matrix, and a strong interfacial bonding was formed at the Mg/Ti interface. The tensile test results show that the strength and elongation of TiP/VW94 composites all improved than VW94 matrix alloy and the 5%TiP/VW94 composite presents the best tensile properties with yield strength (YS), ultimate tensile strength (UTS), and elongation of 173 MPa, 256 MPa and 5.9%, respectively. The improved tensile properties of TiP/VW94 composites can be attributed to grain refinement, load transfer, dispersion strengthening, dislocation strengthening, and an increase in lamellar LPSO.

Wheel polygonal wear aggravates the dynamic responses of vehicle-track coupling systems, especially for the wheel-rail interaction force and rail vibration acceleration, which will influence train operation safety. Previous studies about wheel polygonal wear mostly focused on high-speed trains, while freight trains and track systems are rarely involved. This paper presents a comprehensive investigation of the wheel polygonization effect on the dynamic responses of vehicle-track coupling systems, involving a high-speed train, a heavy haul freight train, ballasted tracks, and slab ballastless tracks. With the combined excitation of track irregularity and wheel polygons of different orders and wave depths, the simulation results are analyzed in the time domain and frequency domain, and this indicates that the rail accelerations and wheel/rail forces of slab tracks induced by over-15th order polygonal wear are more intense than those of ballasted tracks as high-speed trains pass at speeds of 300 km/h and above, and the responses of freight trains are more severe than those of passenger trains on ballasted tracks. For the vehicle system of freight wagons, wheel polygonization has a more obvious effect on the wheelset than the car-body and bogie frame. Moreover, rail vertical acceleration is more sensitive to the various types of wheel polygonal defect in different track structures, and this can serve as a vital indicator of polygonal wear.

Online ride-hailing is gradually becoming one of the indispensable travel modes for people. Online ride-hailing platforms receive tens of thousands of taxi travel orders every day. However, some orders are canceled by the user after the driver answers. User cancellation of orders will disrupt the regular operation of the taxi platform, reduce the efficiency and income of drivers on the online ride-hailing platform, and affect the ride experience of other users. To capture the relationship between the cancellation probability of online taxi orders and users, we first analyze the factors that affect users’ cancellation of online taxi orders. We find that the cancellation probability of online ride-hailing orders is highly correlated with the travel time of the online taxi, the distance between vehicle and passengers, road congestion conditions, and alternative transportation resources around the passengers. Second, a deep residual network-based ride-hailing order cancellation probability prediction model (DeepOCP) is designed to predict the probability of a user canceling an answered online-hailing order. Finally, the Didi Chengdu Express public data set is used to test the model’s effectiveness. This paper is the first study to use a deep-learning model to predict the cancellation probability of online ride-hailing orders.

Exploring the nonlinearity of commute-time utility is useful in predicting urban travel demand. However, existing studies assume that commute utility decreases linearly with commute time. This ignores the influence of commuters’ ideal preferences and tolerance thresholds on commute utility. To reveal the nonlinear variation of commute utility with commute time and its influence on the choice of commute mode, the ideal commute time (ICT) and the tolerance threshold for commute time (TTCT) were introduced. Three-piecewise linear utility models (Models 2, 3, 4) were constructed and compared with the linear utility multinomial logit model (Model 1). The results of empirical study showed that: (a) the goodness of fit of these three modified models is higher than that of Model 1, indicating that the fitting effect of the commute-time utility model can be improved with either or both the ICT and TTCT; (b) there is a nonlinear relationship between the commute utility and the commute time. The commute-time utility decreases slowly before ICT, declines steadily between the ICT and the TTCT, and falls significantly after TTCT; and (c) when the commute time exceeds the TTCT, the perceived utility of commuters traveling by walking or cycling decreases significantly, and there are few changes in the perceived utility of commuters by car, which increases the probability that commuters who use active modes will transfer to commuting by car. The research results have implications for improving the prediction capacity of commute mode choice model and could guide commuters to switch to more sustainable commute modes.

Titanium (Ti) particles reinforced AZ91 matrix composite (Tip/AZ91) was prepared by powder metallurgy method. In the present work, we investigated the hot deformation behavior of Tip/AZ91 composite by isothermal compression tests at a range of temperature from 250 °C to 400 °C and strain rates from 0.001 s−1to 1 s−1. Microstructure observations revealed that Ti particles were distributed uniformly in the composite, with the presence of a diffusion layer containing Mg, Ti, and Al elements between the Ti particles and the magnesium (Mg) matrix. The strain-compensated Arrhenius constitutive model was constructed, and the accuracy was evaluated by error analysis. The stress index exponent (n) was calculated as 4.98, indicating that the dislocation climb mechanism dominates the thermal deformation of Tip/AZ91 composite. Moreover, the calculated activation energy (Q) of 153.7 kJ/mol was observed to be lower than that of the pure AZ91 alloy, which can be attributed to the presence of a particle deformation zone (PDZ). Further microstructure analysis indicated that the continuous dynamic recrystallization mechanism (CDRX) occurred. As the recrystallized grains grow, the texture changes from a bimodal texture to a typical unimodal texture, resulting in a recrystallized <0001>//normal direction texture. In addition, the particle stimulated nucleation (PSN) phenomenon was observed around Ti particles at low Zener-Hollomon parameter (lnZ = 20.73) condition.

In this paper, sodium oleyl sulphate (SOS) was successfully synthesised by reacting octyl alcohol (OA) with gaseous sulphur trioxide (SO3) as a sulphating reagent in a falling film reactor. The structure was determined by Fourier transform infrared (FTIR) and proton nuclear magnetic resonance (1HNMR) spectroscopy. The dynamic adsorption and aggregation behaviour of SOS was systematically investigated to reveal the relationship between the structure and properties of SOS. The physicochemical properties of SOS were determined by measuring the equilibrium surface tension, dynamic surface tension and dynamic contact angle, respectively. A laser particle size analyser and a transmission electron microscope (TEM) were used to analyse the aggregation behaviour of SOS. Compared to sodium dodecyl sulphate (SDS) and sodium n-octadecyl sulphate (C18H37OSO3Na), which have a similar structure to SOS, the increase in hydrophobic chain size and tighter molecular packing enabled by the polar head conformation caused a decrease in CMC and an increase in surface activity. The efficiency of the surface activity was controlled by a mixed diffusion kinetic adsorption mechanism. Moreover, SOS in aqueous solution showed efficient wettability on the surface of the low-energy paraffin film at concentration above the CMC. In addition, SOS molecules can spontaneously form spheroidal aggregates with increasing concentration, and the size of the aggregates increased with the concentration.

The dynamic structural responses are sensitive to the time-frequency content of seismic waves, and seismic input motions in time-history analysis are usually required to be compatible with design response spectra according to nuclear codes. In order to generate spectra-compatible input motions while maintaining the intrinsic non-stationarity of seismic waves, an improved time-domain approach is proposed in this paper. To maintain the nonstationary characteristics of the given seismic waves, a new time-frequency envelope function is constructed using the Hilbert amplitude spectrum. Based on the intrinsic mode functions (IMFs) obtained from given seismic waves through variational mode decomposition, a new corrective time history is constructed to locally modify the given seismic waves. The proposed corrective time history and time-frequency envelope function are unique for each earthquake records as they are extracted from the given seismic waves. In addition, a dimension reduction iterative technique is presented herein to simultaneously superimpose corrective time histories of all the damping ratios at a specific frequency in the time domain according to optimal weights, which are found by the genetic algorithm (GA). Examples are presented to show the capability of the proposed approach in generating spectra-compatible time histories, especially in maintaining the nonstationary characteristics of seismic records. And numerical results reveal that the modified time histories generated by the proposed method can obtain similar dynamic behaviors of AP1000 nuclear power plant with the natural seismic records. Thus, the proposed method can be efficiently used in the design practices.

Activity prediction aims to predict what activities will occur in the future. In smart homes, to facilitate the daily living of the residents, automated or assistive services are provided. To provide these services, the ability of activity prediction is necessary. When we make a prediction, most of the existing works focus on predicting information about the next activity. However, in a smart home environment, compared with just predicting information about the next activity, another type of activity prediction problem has more practical value: predicting what activities will occur in the coming time period of a certain length. The necessity of this type of prediction is due to the purpose of the smart homes and the character of the activities. Many activities in smart homes need preparation time before being performed. Through this type of prediction, activities could be predicted sufficient time before being performed, and there will be adequate time for the smart home system to prepare corresponding automated or assistive services. As more than one activity could occur within the time period in which the prediction is made, this problem is a multilabel classification problem. In this article, we first give a formulation of the problem. Then, we propose a deep learning model to address it. The proposed model consists of the convolutional part, the long short-term memory layer, and the multilabel output layer. Experiments on real-world datasets show the effectiveness of our model.

The thermal conductivity of superlattices is strongly reduced as compared to that of the parent materials due to phonon-scattering and thermal boundary resistances at the superlattice period interfaces. Herein, homogenous superlattices consisting of homogenous structural CeδCa1−δTiO3and CaTi1−δCeδO3alternate layers were obtained through a variable-valence Ce doping, providing multi-quantum well interfaces between the alternate layers due to Ce-substitution at Ca and Ti sites, respectively. This material comprising these homogenous superlattices displayed a significantly reduced lattice thermal conductivity of 1.82 W m−1K−1and a record high zTvalue of 0.405 at 1031 K in CaTiO3-based thermoelectric materials. This strategy of synthesizing homogeneous superlattices provides a cost advantage over heterogeneous superlattices prepared by the molecular beam epitaxy method and paves a route for preparing bulk superlattices with unique thermoelectric properties rooting in the quantum domain limiting effect.

The ageing behavior of as-extruded TiP/VW94 composites was investigated. The peak hardness of the composites increases compared to the matrix alloy and the 5%TiP/VW94 composite presents the highest peak hardness of 148.7 HV after aging for about 50 h. However, the hardness increments first decrease and then slightly increase with increasing Ti particle content due to the introduction of high-density dislocations by Ti particles.

The surface defect detection of T-beam of highway bridge in the traditional quality control process is mainly based on naked eye observation. The detection results are too dependent on personal experience and require a significant amount of work. This paper applies the convolutional neural network constructed by differentiable neural architecture search method to the automatic detection of surface defect on T-beams. And a reduction cell of the modified network is designed to search for the normal cell to improve the search efficiency. The results show that the search efficiency of the network is improved and the search time is reduced by about 31%.

Aqueous zinc–sulfur (Zn–S) batteries are regarded as excellent candidates for energy storage applications due to their low cost, non-toxicity, and high theoretical energy density. However, the low utilization of the traditional thick foil-type Zn anode would severely restrict the overall energy density of Zn–S batteries. Herein, a mechanically and chemically stable powder-Zn/indium (pZn/In) anode with finite Zn loading was designed and constructed for enhancing the cycle stability of aqueous Zn–S batteries. Notably, the bifunctional In protective layer can inhibit the corrosion rate of highly active pZn and homogenize the Zn2+flux during Zn plating/stripping. As a result, the obtained pZn/In anode exhibits a greatly improved cyclability of over 285 h even under a much harsh test condition (10 mA cm−2, 2.5 mA h cm−2, Zn utilization rate: ∼38.5%). Furthermore, when assembled with an S-based cathode at a negative/positive (N/P) capacity ratio ∼2, the full cell delivers a high initial specific capacity of ∼803 mA h g−1and operates stably for over 300 cycles at 2C with a low capacity fading rate of ∼0.17% per cycle.

Ti particles (5 wt%) reinforced AZ91 Mg matrix composites (TiP/AZ91 composites) were prepared by powder metallurgy. As a result, the strength and ductility of TiP/AZ91 composites were improved compared with AZ91 alloy. The ultimate tensile stress (UTS) increased significantly from 163 MPa to 221 MPa, and the elongation increased from 3.5% to 10.9%. The YS and hardness decreased due to the slightly coarser grain size. The microstructural results showed that Ti particles were uniformly dispersed in the Mg matrix and the content of Mg17Al12was reduced, indicating that Ti particles can inhibit the precipitation of the second phase. The interface between Ti particle and Mg matrix showed that the Al3Ti layer was formed at the edge of the Ti particles. EBSD was used to analyze the twins and dislocations at different tensile strains. During the tensile deformation at room temperature, many tensile twins and dislocations formed in the TiP/AZ91 composites. The tensile twins and dislocations could coordinate plastic deformation, thus improving the elongation of the TiP/AZ91 composites.

The combination of nonorthogonal multiple access (NOMA) using power-domain with backscatter communication (BC) is expected to connect large-scale Internet of things (IoT) devices in the future sixth-generation era. This article introduces a BC in a multicell IoT network, where a source in each cell transmits a superimposed signal to its associated IoT devices using NOMA. The backscatter sensor tag (BST) also transmits data to IoT devices by reflecting and modulating the superimposed signal of the source. A new optimization framework is provided that simultaneously optimizes the total power of each source, power allocation coefficient of IoT devices, and RC of BST under imperfect successive interference cancellation decoding. This work aims to maximize the total energy efficiency (EE) of the IoT network subject to the quality of services of each IoT device. The problem is first transformed using the Dinkelbach method and then decoupled into two subproblems. The Karush–Kuhn–Tucker conditions and dual Lagrangian method are employed to obtain efficient solutions. In addition, we also calculate the EE of the conventional NOMA network without BC as a benchmark framework. Simulation results unveil the advantage of our considered NOMA BC network over the conventional NOMA network in terms of system total EE.

The breast plumage color of Guangxi Yao chickens shows obvious sexual dimorphism, with roosters showing black and black with red, and hens displaying partridge and red. Black plumage in roosters is considered a sign of quality, necessitating the purification of plumage color. Here, we developed an effective method based on genetic variations within MC1R and plumage characteristics. We clarified the distribution of 5 single nucleotide polymorphisms (SNP) and 3 haplotypes (H1, H2, and H3) of MC1Rgene, and revealed potential associations between haplotype H1 and black breast plumage in the F2 resource population derived from a backcross between Guangxi Yao and Yellow chickens. Subsequently, using H1/H1 diplotype roosters and hens to construct families (n = 1,244) notably increased the proportion of offspring with black plumage. Further analysis suggested that red plumage in hens may be the putative phenotype of black plumage in roosters, driven by haplotype H1 of the MC1Rgene, as verified by genotype and phenotype analysis. As expected, we found that almost all male offspring of hens with red breast plumage showed black plumage. In short, we established a selection pattern based on the combination of black-plumage roosters and red-plumage hens can significantly purify the sexually dimorphic plumage color and improve the efficiency of breeding programs in Guangxi Yao chickens. Our findings provide a novel technical framework to accelerate the breeding process for plumage trait in poultry.

Phase change cold storage technology can improve the efficiency of energy storage in cold chain logistics. In this paper, a new ternary salt-water eutectic phase change gel was developed. The experimental results show that the content of the optimal gel matrix in the composite is 12 %, and the phase change temperature of the composite is −12.44 °C, with a latent heat of 138.9 J g−1. The gel network is formed by covalent cross-linking and ionic cross-linking, and the brine eutectic solution can be seen to be uniformly encapsulated by the gel network through microscopic magnification. The feasibility of the composite phase change gel for cold chain transportation and cold chain logistics was also demonstrated by application experiments. The component changes during the phase change process were analyzed using thermochemical software, which provides a reference for future analysis of the phase change process of eutectic solutions. In conclusion, the composite phase change gel has obvious thermal permeability and morphological stability and has good performance for further application in cold chain logistics systems.

Osteoarthritis (OA) is a prevalent degenerative joint disease in the elderly, characterized by chondrocyte death and cartilage matrix degradation, influenced by mechanical, biological, and environmental factors. Current treatments focus on surgery, but there is a critical need for effective drug development to advance OA management. In this study, we developed a novel composite material, ALG-BA-8-HQ, composed of alginate (ALG), benzoic acid (BA), and 8-hydroxyquinoline (8-HQ), and subsequently loaded it with compound 1, forming ALG-BA-8-HQ@1. Comprehensive characterization using Fourier-Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), Ultraviolet–Visible Spectroscopy (UV–Vis), and fluorescence spectroscopy confirmed the chemical bonding between ALG, BA, and 8-HQ, revealed the surface morphology and microstructure, and demonstrated excellent fluorescence properties. The application of ALG-BA-8-HQ@1 in OA treatment showed promising results, enhancing chondrocyte proliferation and increasing the anti-inflammatory capacity of chondrocytes, indicating its potential for effective OA therapy.

BiSbSe1.5Te1.5, a typical multi-layered compound, can be utilized to fabricate p-n junctions with the identical chemical composition by regulating the antisite defects and anion vacancies via defect engineering. However, the thermoelectric performance of n-type BiSbSe1.5Te1.5is limited due to poor electrical transport properties. Entropy engineering is a novel strategy for expanding the space of performance optimization in materials science, including the field of thermoelectric. Herein, we realize a largely enhanced thermoelectric performance for n-type BiSbSe1.5Te1.5by employing entropy engineering. Both mass field fluctuations and stress variations field are introduced simultaneously in the lattice, leading to additional phonon scattering. Moreover, nano-laminate structure, nanoscale interstices and holes are formed in the samples. All of these defects and nanoscale structures are especially efficient on trapping phonons. As a result, the optimizing electrical transport properties while maintaining low thermal conductivity are achieved, showcasing a peak ZTof 0.54 at 475 K and a remarkable average ZTof 0.45 between 300 and 550 K for n-type BiSbSe1.25Te1.75.These findings not only provide a way to enhance the thermoelectric performance of n-type BiSbSe1.5Te1.5but also push forward the promise of the applications in fabricating well-matched p-n junctions using thermoelectric materials with the identical chemical composition.

Fabricating gradient structure (GS) is increasingly adopted in structural engineering materials due to the unique combinations of mechanical properties. In the present work, a gradient ultrafine-grained structure with a change in the grain size up to three orders of magnitude from nano to micrometer is prepared on Mg-2Gd-0.4Zr (wt.%) alloy sheet with coarse grains (CG) by sliding friction treatment (SFT). Compared with homogeneous CG structure, the yield strength of GS + CG + GS is improved from 126 MPa to 243 MPa, acquiring an increase of 93%, and maintains an excellent ductility of 25%, showing an extraordinary strength-plasticity combination among the reported GS-containing Mg alloys. Two-beam condition TEM and EBSD analyses reveal that the refined grain structure and grain orientation modification can promote the activation of multiple dislocation slip systems such as and slipping in the GS area, which improves the coordinate ability of plastic deformation. In addition, GS + CG + GS owns higher strength, ductility and better strain hardening ability than that of the GS + CG sample. This is because the symmetrical sandwich structure can alleviate the strain localization so exhibits a better work hardening effect and resistance for failure. This work sheds light on the deformation behavior of heterostructured material and provides a new strategy to improve the mechanical properties of wrought Mg alloys.

OBJECTIVE--To explore the relationship between serum neuron-specific enolase (NSE) levels and diabetic neuropathy. RESEARCH DESIGN AND METHODS--Type 1 or 2 diabetic and healthy control subjects (n = 568) were randomly [...]

A KVPO4F/reduced graphene oxide (KVPF/rGO) hybrid was prepared through a simple ball milling-freeze drying-thermal reduction method. Due to the small size of KVPF nanoparticles and their homogeneous distribution in the rGO network, the as-fabricated KVPF/rGO cathode shows efficient potassium storage performance.

In this paper, a silica-based D-shaped circular photonic crystal fiber Bragg grating sensor for refractive index sensing is proposed theoretically. D-shaped fiber construction can effectively enhance the coupling effect between the guiding mode and external liquid analyte, which then causes a distinct shift in the typical reflection spectrum as the refractive index of the analyte varies. This design exhibits highly improved sensitivity of 487 nm/RIU in a large refractive index range from 1.30 to 1.40 compared with the previous fiber grating sensors. Study of the dependence of sensing performance on the structure parameters suggests that the resonance peak shifts towards longer wavelengths with the increased air-hole diameter of fiber, while it is almost immobile as the hole spacing and the number of air-hole layers change in a certain range. For the influence of the Bragg grating structure, results show that the resonance peak is not sensitive to the grating length, but linearly increases as the grating period expands. The effects of polishing depth and fiber preparation error on the sensor are also discussed in detail. This high-sensitivity sensor based on a D-shaped photonic crystal fiber and Bragg grating has great potential in biochemical detection, environmental monitoring, and medical sensing.

To achieve the three-dimensional free movement of the slung load, a load-leading hierarchical control strategy has been adopted recently which divides the cooperative multi-lift system into a load layer, a cable layer, and an aircraft layer. But there exists a non-convex optimization problem in the cable layer when computing the force of each cable, and more control difficulties of the aircraft due to the additional disturbances resulting from the load movement. To solve these problems, an application of the social spider optimization (SSO) algorithm and the improved active disturbance rejection controller (IADRC) in hierarchical control of cooperative multi-lift with four unmanned helicopters is proposed in this study. First, the unmanned helicopters as well as the load are modeled. Then the three layers mentioned above are designed, respectively. Specifically, an optimization method combining SSO with the MATLAB/fmincon function is proposed to solve the non-convex problem in the cable layer. And within the unmanned helicopter layer, the fuzzy theory is introduced into the nonlinear error feedback control strategy of the traditional active disturbance rejection controller (ADRC) to realize the control of the unmanned helicopter. At last, some simulations are carried out, and the results indicate that the system has higher calculation efficiency, smaller steady-state error, and better adaptability to trajectory change or load release with the designed hierarchical control strategy.

Background: The transoral endoscopic thyroidectomy vestibular approach (TOETVA) is receiving increased attention, frequently due to growing requirements for cosmetic incisions. Here, we report our initial experience and discuss the safety and efficacy of the innovative surgical working space suspension system for gasless TOETVA. Methods: We retrospectively analyzed 75 consecutive patients for whom gasless TOETVA with our novel working space suspension system was used. This suspension system included self-developed retractors, a sterile bandage, and an anesthesia stand. We also improved some main surgical instruments in gasless TOETVA. Results: The study included 75 patients who successfully underwent thyroidectomy and central neck dissection via gasless TOETVA. The mean operating time was 143.27 ± 34.60 min. The mean number of retrieved lymph nodes was 8.00 ± 5.39. Conversion to open surgery did not occur, nor did patients exhibit serious postoperative complications. Postoperative complications included 4 cases of transient recurrent laryngeal nerve (RLN) palsy, 9 of transient hypoparathyroidism, and 3 of transient mental nerve injury. One patient with subcutaneous fluid after surgery recovered after aspiration. Another patient with submental minor perforation recovered well after suturing. There was no evidence of specific complications related to self-designed retractors. Conclusion: The innovative working space suspension system for gasless TOETVA provided enough and stable working space and optimized the clarity of the surgical field without CO2-related complications.

In order to investigate the application of 3D base-seismic isolation system in nuclear power plants (NPPs), comprehensive analysis of constitution and design theory for 3-dimensional combined isolation bearing (3D-CIB) was presented and derived. Four different vertical stiffness of 3D-CIB was designed to isolate the nuclear island (NI) building. This paper aimed at investigating the isolation effectiveness of 3D-CIB through modal analysis and dynamic time-history analysis. Numerical results in terms of dynamic response of 3D-CIB, relative displacement response, acceleration and floor response spectra (FRS) of the superstructure were compared to validate the reliability of 3D-CIB in mitigating seismic response. The results showed that 3D-CIB can significantly attenuate the horizontal acceleration response, and a fair amount of the vertical acceleration response reduction of the upper structure was still observed. 3D-CIB plays a significant role in reducing the horizontal and vertical FRS, the vertical FRS basically do not vary with the floor height. The smaller the vertical stiffness of 3D-CIB is, the better the vertical isolation effectiveness is, whereas, it will increase the displacement and the rocking effect of superstructure. Although the advantage of 3D-CIB is that the vertical stiffness can be flexibly adjusted, it should be designed by properly accounting for the balance between the isolation effectiveness and displacement control including rocking effect. The results of this study can provide the technical basis and guidance for the application of 3D-CIB to engineering structure.

[Display omitted] • The top-down method was used to fabricate the TiNi 1+ x Sn half-Heusler alloy. • A large number of incoherent interfaces of HH/FH were generated. • The electrical conductivity was enhanced by the incoherent interfaces. • A relatively high ZT of 0.41 at 723 K was achieved for the synthesized TiNi 1.05 Sn. The top-down method was used to fabricate the TiNi 1+ x Sn half-Heusler alloy. Several knotty problems have been solved using the top-down method, including the generation of impurity phases, the visible discrepancy in the grain size of the TiNi 2 Sn second phase, and irregular variations in the Seebeck coefficient (S), electrical conductivity (σ), and thermal conductivity (κ) with increasing Ni content. The generation of a large number of incoherent interfaces between the half-Heusler (HH) and full-Heusler (FH) phases fabricated by the top-down method drastically improved σ and retained κ and S , thereby leading to an enhancement in the dimensionless figure of merit (ZT) by ∼19 % for the TiNi 1.05 Sn sample as compared to the ZT of the samples prepared by the conventional method. [ABSTRACT FROM AUTHOR]

Unmanned helicopters are widely used in military and civil fields. One of the most important applications is flying with an underslung load, but the pendulum-like behavior of the load can cause damage or even forced landing to the helicopter. To solve this problem, a control strategy to stabilize the helicopter/load system based on active disturbance rejection control (ADRC) and improved sliding mode control (ISMC) algorithms is proposed in this paper. First, the helicopter/load system is modelled using Newton-Euler equations according to the multi-body dynamics theory. Then a manipulation strategy which can reduce the swing angle of the load and an overall control strategy for the helicopter/load system are presented. Specifically, ADRC is applied to attitude control due to its ability to regard the pendulum-like behavior as the internal uncertainties of the system, meanwhile ISMC to position control. Within ISMC, two sliding surfaces with adjustable weights are constructed by employing the position of the helicopter as well as the swing angle of the load. In addition, a real-time beetle antennae search algorithm is designed to online modify the weights by taking the minimum error at current time as the optimization objective. Besides, the radial basis function neural network is introduced to approach the uncertainty coefficients considering the system’s complexity. At last, relevant simulations are carried out and the results indicate that the system is capable of not only controlling the attitude and position of the helicopter precisely but also stabilizing the underslung load rapidly with ADRC and ISMC.

The effect of hydrophilic chain of surfactants fatty alcohol polyoxyethylene ether sodium sulphates (AEnS, n = 2, 3, 7) on surface properties and wetting properties was investigated by the measurement of equilibrium surface tension, dynamic surface tension and dynamic contact angle. The fatty alcohol polyoxyethylene ether sodium sulphates with different head group sizes were used. From the results of equilibrium surface tension measurements, we could obtain the critical micellisation concentration, adsorption efficiency, maximum surface excess concentration and Langmuir equilibrium adsorption constant at air/liquid interface. The dynamic surface tension results showed that the adsorption of aqueous solutions at the air/liquid interface follows a mixed-diffusion kinetic adsorption mechanism. In conclusion, for both studied surfactant, the longer the oxyethylene chains, the higher the maximum rate of surface tension reduction, the higher the diffusivity and wetting properties in terms of contact angle.

Quad tilt-rotor(QTR) UAV is a nonlinear time-varying system in full flight mode. It is difficult and inaccurate to model the nonlinear time-varying system, which cannot fully reflect the problem of controlling input and system response output in the full flight mode. In order to solve the above problems, a novel neural network model was adopt to identify the nonlinear time-varying system of quad tilt-rotor in full flight mode. An adaptive learning rate algorithm based on foraging strategy is proposed based on the global error BP neural network. Corresponding to the nonlinear time-varying system, BP neural network is set as the time-invariant system structure with constant network structure and continuously changing weights at multiple times, and the nonlinear input-output relationship under the time-varying system is jointly described by fitting the network at all times. The extended Kalman filtering algorithm is used to track the network connection weights by modifying the network weights at the current moment with the input and output data at the next moment. The final identification result shows that the smaller mean square error of both only transition process and full flight mode, shows that using this optimization algorithm can well describe the input and output characteristics of the nonlinear time-varying systems. When the same network structure is adopted, no matter for transition mode or full mode, the BP optimization algorithm based on foraging strategy is better than the global BP algorithm for system identification of the full mode quad tilt-rotor. Therefore, when the BP neural network based on foraging strategy is adopted, the same network structure can be adopted to systematically identify the full mode of quad tilt-rotor by changing the weight.