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Abstract: 3Y-TZP/Al2O3 composites were prepared by hot-pressed sintering at 1450°C for 1h under 30MPa in vacuum, and then the fine-grained composite sintered bodies were deformed by superplastic compression at 1500°C. Quantitative texture analysis to the hot-pressed and deformed composites was accomplished via XRD and X-ray pole figure measurements. Highly oriented and textured microstructure was generated by superplastic deformation. The maximum degree of texture was up to 7.3 times random. The microstructure observation based on SEM and TEM was adopted to explain the development and mechanism of texture formation. The results indicated that Al2O3 matrix with fine platelike grains was formed in deformed materials, while the shape of ZrO2 grains did not change obviously. The predominant mechanism for deformation and texture development was grain-boundary sliding and grain rotation, accompanying with anisotropic grain growth. Meanwhile, the intragranular dislocation motion played an important role in the formation of texture. [Copyright &y& Elsevier]

ZrO2/Ni nanocomposite was produced via pulse electrodeposition using a nickel sulfmate bath. The effects of main factors including pH value, temperature T, current density D k and ZrO2 content ρ on the electrodeposit were dealt with by the Taguchi method. Experimental results show that the current density and ZrO2 content affect the electrodepositing process significantly. Nanocomposite with an average grain size of about 50 nm and ZrO2 content of up to 0.4 wt% was produced under the optimal condition. The Young’s modulus of the achieved composite is similar to that of polycrystalline Ni. The microhardness is much higher than that of common pure Ni, primarily due to the ultrafine grains of Ni matrix by the Hall-Petch mechanism. The homogeneous dispersion of stiff ZrO2 particles in the Ni matrix acting as dislocation pinning and microcrack pinning also results in the strengthening effect. [ABSTRACT FROM AUTHOR]

Abstract: Superplastic forming and diffusion bonding (SPF/DB) is a well-established process for the manufacture of components almost exclusively from Ti–6Al–4V sheet material. The SPF/DB with gas pressure control for honeycomb structure is investigated. The optimum parameters are as follows: bonding temperature, T =1203K; bonding pressure, P =10MPa; bonding time, t =30min. The effects of microstructure were carried out with the bonded samples. The microstructure shows an excellent bonding at the interfaces. The optimum parameters for the SPF/DB process are as follows: forming temperature, T =1203K; forming pressure, P =0.6MPa; forming time, t =60min. The distribution of thickness after SPF/DB was investigated. [Copyright &y& Elsevier]

Abstract: Tape casting and hot-press sintering are used to fabricate an Al2O3/3Y-TZP laminated composite. The as-prepared material is deep drawn at high temperature to research its superplastic formability. It is found that the microstructure of the material sintered at 1550°C is fine and no significant residual porosity was detected from SEM observations at the interfaces between the two types of layers. The superplastic forming experiment shows that, when the strain rate is constant, temperature has a great influence on the superplasticity of the Al2O3/3Y-TZP laminated composite. A hat-like part with the greatest deform height is obtained at 1500°C. The processing will be less effective at higher or lower temperature. [Copyright &y& Elsevier]

Abstract: In order to investigate the superplasticity of ceramic/ceramic laminated composite under tensile stress, the superplastic deep-drawing process was simulated by FEM. The results shown that, the strain and stress conditions of laminated composite, made by ceramic with different superplastic formability, are better than that of monolithic ceramic. Consequently, the material may exhibit high superplasticity. To testify this, some experiments were carried out. Tape casting and hot-press sintering are used to fabricate Al2O3/3Y-TZP laminated composite. As-received material is deep-drawing at high temperature to research its superplasticity. The results shown that, when suitable strain rate and forming temperature were used, the as-received material has excellent superplasticity. [Copyright &y& Elsevier]

The synthesis, superplastic deep drawing and cavitation behavior of a fine-grained alumina–zirconia ceramic composite have been investigated. The results show that dense Al2O3/ZrO2 samples with average grain diameter of 230 nm can be elongated to a dome height of at least 12 mm at the punch rate of 0.6 mm·min-1 at 1400 °C. Deformed microstructure of the material indicates that not only the nucleation and growth of internal cavities are effectively suppressed but also the intragranular dislocation structures and sub-boundaries are observed around the nano-particles in alumina grains, which proves that intragranular dislocation creep is playing an important role in deformation. While the research on the deep drawing of the materials with the initial average grain size of 450 nm conforms that a plasticity controlled cavity growth process takes place during deformation. [Copyright &y& Elsevier]

The morphology of additives has strong effects on the tribological performance of lubricant. In this work, molybdenum disulfide (MoS 2) nanowires (NWs) prepared by electrospinning method are used as an additive in perfluoropolyether (PFPE) base oil for the first time. The influence of MoS 2 NWs on the tribological properties of PFPE oil is evaluated using a four-ball tester. The results show that PFPE oil containing 1.0 wt% MoS 2 NWs exhibits significant improvements in reducing friction and anti-wear properties with the minimal friction coefficient (0.11) and wear scar diameter (452 μm) under high vacuum due to the unique NW morphology and good dispersion of MoS 2 NWs in PFPE. • First report of tribological properties of MoS 2 nanowire (NW) additives. • MoS 2 NW–PFPE blend exhibits superior tribological properties. • Significantly improved anti-friction and anti-wear. [ABSTRACT FROM AUTHOR]

Liposarcoma (LPS) is the second most common kind of soft tissue sarcoma, and a heterogeneous malignant tumor derived from adipose tissue. Up to now, the prognostic value of BAG1 or BAG2 in LPS has not been defined yet. Expression profiling data of LPS patients were collected from TCGA and GEO database. Survival curves were plotted to verify the outcome differences of patients based on BAG1 or BAG2 expression. Univariate and multivariate Cox regression models were used to analyze the prognostic ability of BAG1 or BAG2. Chaperone's regulators BAG1 and BAG2 were identified as prognostic biomarkers for LPS patients, which exhibited distinct expression patterns and survival outcome prediction performances. Patients with high BAG2 expression and/or low BAG1 expression had worse prognosis. Enrichment analysis showed that BAG1 was involved in negative regulation of TGF-β signaling. Low expression of BAG1 was associated with high abundance of regulatory T cells (Tregs). The 2-gene signature model further confirmed the improved risk assessment performance of BAG1 and BAG2: high risk patients displayed poor prognosis. BAG1 and BAG2 are supposed to be potential prognostic biomarkers for LPS and have impacts on liposarcomagenesis and immune infiltration in distinctive manners, which may function as potential therapy targets (BAG1 agonists/BAG2 inhibitors) for LPS. [ABSTRACT FROM AUTHOR]

With the widespread attention and research of distributed photovoltaic (PV) systems, the fault detection and diagnosis problems of distributed PV systems has become increasingly prominent. To this end, a distributed PV array fault diagnosis method based on fine-tuning Naive Bayes model for the fault conditions of PV array such as open-circuit, short-circuit, shading, abnormal degradation, and abnormal bypass diode is proposed. First, in view of the problem of less distributed PV fault data, a fine-tuning Naive Bayes model (FTNB) is proposed to improve the diagnosis accuracy. Second, the failure sample set is used to train the model. Then, the maximum power point data of the PV inverter and the meteorological data are collected for fault diagnosis. Finally, the effectiveness and accuracy of the proposed method are verified by the analysis of simulation. In addition, this method requires only a small number of fault sample sets and no additional measurement equipment is required, which is suitable for real-time monitoring of distributed PV systems. [ABSTRACT FROM AUTHOR]

Micro-filters fabricated using integration methods is now the trend for multichannel filters in imaging spectrum systems. Traditional multichannel bandpass filters are mainly fabricated separately by multilayered thin films and then glued together. This approach involves the complexity of precision cutting, dicing, and adhesive bonding; therefore, the possibility of miniaturization is quite limited. In this work, a dual channel bandpass thin film filter for the mid-infrared was fabricated by using the lift-off process. The structure of a 4-cavity Fabray–Perot (F-P) type filter was designed and optimized. The bandpass filter over the range 3.55–3.75 µm with full width at half maximum (FWHM) of 274 nm and the bandpass filter over the range 4.85–4.95 µm with FWHM of 246 nm were obtained with a 4.5 µm joint width. The average transmittance of the filters is more than 83.5% and optical density value of the cutoff is 3. The thickness of 3.55–3.75 µm bandpass filter was measured and the thickness error was analyzed. The results show that the thickness error, especially the thickness error of spacer layers, induces the degradations of peak transmission and bandwidth. This kind of mid-infrared filter has important application in space remote sensing, military, and civil fields. [ABSTRACT FROM AUTHOR]

Energy storage has attracted more and more attention for its advantages in ensuring system safety and improving renewable generation integration. In the context of China's electricity market restructuring, the economic analysis, including the cost and benefit analysis, of the energy storage with multi-applications is urgent for the market policy design in China. This paper uses an income statement based on the energy storage cost–benefit model to analyze the economic benefits of energy storage under multi-application scenarios (capacity, energy, and frequency regulation markets) in China's future electricity market. The results show that the economic benefits of energy storage can be improved by joining in the capacity market (if it exists in the future) and increasing participation in the frequency regulation market. Nevertheless, the benefits under multi-application scenarios can hardly guarantee the cost recovery of energy storage under the current market mechanism or at the current price levels. Moreover, the economic benefits under different subsidy policies are studied, and the results show that energy storage can recover the cost with appropriate subsidy policies (the subsidy of 0.071 USD/kWh for pumped storage power stations is sufficient while the subsidy of 0.142 USD/kWh is required for electrochemical power stations). Finally, the sensitivity analysis of an energy storage power station to different price levels is carried out considering the difference in electricity price between China and the United States. [ABSTRACT FROM AUTHOR]

China's government launched a policy in October 2017 to permit the distributed generators to peer-to-peer trade their electricity generation on the market. Several clauses in the policy document are, however, unclear and ambiguous. This work identifies three vital but not clearly detailed issues in the policy document: (1) participation eligibility, (2) the grid fee calculation method, and (3) subsidy rates. Then, we carry out a comprehensive analysis of the economic impacts of the trade policy based on a case study of an eastern city in China. Sensitivity analyses on the impacts of the subsidy rates, transmission and distribution prices (TDPs), and end-user regulated prices are conducted. The results show that the trading policy will benefit the photovoltaic (PV) generators with more revenue by 6–11%, reduce the cost for end-users by 6–12%, and decrease the revenue of the power grid company by 32–55%. [ABSTRACT FROM AUTHOR]

They performed an interesting meta-analysis on observational studies to investigate the degree of pain reduction and functional outcome after extracorporeal shockwave therapy (ESWT) for knee osteoarthritis. Besides, nine studies included in this meta-analysis provided sufficient data to perform a subgroup analysis by type of ESWT (focus or radial) and including the missed study can further help to perform the necessary analysis. [Extracted from the article]

The statistical data of different kinds of behaviors of pigs can reflect their health status. However, the traditional behavior statistics of pigs were obtained and then recorded from the videos through human eyes. In order to reduce labor and time consumption, this paper proposed a pig behavior recognition network with a spatiotemporal convolutional network based on the SlowFast network architecture for behavior classification of five categories. Firstly, a pig behavior recognition video dataset (PBVD-5) was built by cutting short clips from 3-month non-stop shooting videos, which was composed of five categories of pig's behavior: feeding, lying, motoring, scratching and mounting. Subsequently, a SlowFast network based spatiotemporal convolutional network for the pig's multi-behavior recognition (PMB-SCN) was proposed. The results of the networks with variant architectures of the PMB-SCN were implemented and the optimal architecture was compared with the state-of-the-art single stream 3D convolutional network in our dataset. Our 3D pig behavior recognition network showed a top-1 accuracy of 97.63% and a views accuracy of 96.35% on the test set of PBVD and a top-1 accuracy of 91.87% and a views accuracy of 84.47% on a new test set collected from a completely different pigsty. The experimental results showed that this network provided remarkable ability of generalization and possibility for the subsequent pig detection and behavior recognition simultaneously. [ABSTRACT FROM AUTHOR]

Recently, demand-side resources (DSRs) have proceeded to participate in frequency control of the power systems. Compared with traditional generation-side resources, DSRs have unique intermittent characteristics. Taking aggregation of air conditions as an example, they must take a break after providing power support for a period of time considering the user comfort. This behavior, known as the intermittent characteristic, obviously affects the stability of the power systems. Therefore, this paper designs a corresponding controller for DSRs based on the intermittent control method. The designed controller is incorporated into the traditional load frequency control (LFC) system. The time delay is also considered. A rigorous stability proof and the robust H ∞ performance analysis is presented for the new LFC system. Then, the sufficient robust frequency stabilization result is presented in terms of linear matrix inequalities (LMIs). Finally, a two-area power system is provided to illustrate the obtained results. The results show that the designed intermittent controller can mitigate the impact of intermittent characteristics of DSRs. [ABSTRACT FROM AUTHOR]

The detection of pig behavior helps detect abnormal conditions such as diseases and dangerous movements in a timely and effective manner, which plays an important role in ensuring the health and well-being of pigs. Monitoring pig behavior by staff is time consuming, subjective, and impractical. Therefore, there is an urgent need to implement methods for identifying pig behavior automatically. In recent years, deep learning has been gradually applied to the study of pig behavior recognition. Existing studies judge the behavior of the pig only based on the posture of the pig in a still image frame, without considering the motion information of the behavior. However, optical flow can well reflect the motion information. Thus, this study took image frames and optical flow from videos as two-stream input objects to fully extract the temporal and spatial behavioral characteristics. Two-stream convolutional network models based on deep learning were proposed, including inflated 3D convnet (I3D) and temporal segment networks (TSN) whose feature extraction network is Residual Network (ResNet) or the Inception architecture (e.g., Inception with Batch Normalization (BN-Inception), InceptionV3, InceptionV4, or InceptionResNetV2) to achieve pig behavior recognition. A standard pig video behavior dataset that included 1000 videos of feeding, lying, walking, scratching and mounting from five kinds of different behavioral actions of pigs under natural conditions was created. The dataset was used to train and test the proposed models, and a series of comparative experiments were conducted. The experimental results showed that the TSN model whose feature extraction network was ResNet101 was able to recognize pig feeding, lying, walking, scratching, and mounting behaviors with a higher average of 98.99%, and the average recognition time of each video was 0.3163 s. The TSN model (ResNet101) is superior to the other models in solving the task of pig behavior recognition. [ABSTRACT FROM AUTHOR]

Multi-element CrTaNbMoV nitride films are prepared using direct current magnetron sputtering CrTaNbMoV mosaic alloy target at various N 2 /(Ar + N 2) flow ratios (R N). The influence of R N on the composition, structure, mechanical properties and wear behavior of the films deposited at R N = 0%, 10%, 20%, 30% and 40% are investigated. The alloy CrTaNbMoV film exhibits a simple BCC structure, while a nanocrystalline BCC structure of metals and metal nitrides is observed in the nitride films deposited at R N = 10%. With further increasing R N from 20% to 40%, the structure evolves from BCC to FCC. The nitride film deposited at R N = 20% exhibits the highest hardness and adhesive critical load (Lc), which are 21.6 GPa and 331 mN, respectively. The wear rate of film deposited at R N = 20% is decreased six times than the alloy film (R N = 0%), indicated an excellent wear resistance. Image 1 • CrTaNbMoV nitride films were deposited by sputtering mosaic alloy target. • The structure of nitride films was evolved from BCC to FCC with increasing R N [N 2 /(N 2 +Ar)]. • Maximum hardness and adhesive load of nitride film reached 21.6 GPa and 331 mN, respectively. • CrTaNbMoV nitride films exhibited superior wear resistance. [ABSTRACT FROM AUTHOR]

Abstract: Vanadium sesquioxide (V2O3) nanopowder was successfully prepared through thermal decomposition of the oxalate. Techniques of X-ray diffraction (XRD), transmission electron microscopy (TEM), electron diffraction (ED), and X-ray photoelectron spectroscopy (XPS) have been used to characterize structure, morphology, and composition. The as-obtained samples are well dispersed and display sphere-like morphology with diameters of 25–50 nm. [Copyright &y& Elsevier]

For both pigs in commercial farms and biological experimental pigs at breeding bases, mounting behaviour is likely to cause damage such as epidermal wounds, lameness and fractures, and will no doubt reduce animal welfare. The purpose of this paper is to develop an efficient learning algorithm that is able to detect the mounting behaviour of pigs based on the data characteristics of visible light images. Four minipigs were selected as experimental subjects and were monitored for a week by a camera that overlooked the pen. The acquired videos were analysed and the frames containing mounting behaviour were intercepted as positive samples of the dataset, and the images with inter-pig adhesion and separated pigs were taken as negative samples. Pig segmentation network based on Mask Region-Convolutional Neural Networks (Mask R-CNN) was applied to extract individual pigs in the frames. The region of interest (RoI) parameters and mask coordinates of each pig, from which eigenvectors were extracted, could be obtained. Subsequently, the eigenvectors were classified with a kernel extreme learning machine (KELM) to determine whether mounting behaviour has occurred. The pig segmentation presented considerable accuracy and mean pixel accuracy (MPA) with 94.92% and 0.8383 respectively. The presented method showed high accuracy, sensitivity, specificity and Matthews correlation coefficient with 91.47%, 95.2%, 88.34% and 0.8324 respectively. This method can be an efficient way of solving the problem of segmentation difficulty caused by partial occlusion and adhesion of pig bodies, even if the pig body colour was similar to the background, in recognition of mounting behaviour. [ABSTRACT FROM AUTHOR]

Traditional virtual power plants (VPPs) with fixed resource composition and coordination strategies struggle to cost-effectively exploit the flexibility of large-scale resources for adapting variable regulation requirements and resources characteristics. To this end, this paper proposes a dynamic aggregation mechanism to flexibly select and coordinate individual resources for forming aggregators according to grids regulation requirements and resource characteristics. The proposed mechanism is operated through a two-stage dynamic aggregation model comprising resource selection and coordination. Considering the two-stage dynamic aggregation model is a combinational optimization problem with high computational complexity, the submodular optimization method is utilized to swiftly address this problem. First, the complementarity and submodularity of the dynamic aggregation process are formulated to elaborate how the aggregation regulation characteristics (ARCs) evolve with flexible resource composition and coordination. Next, a submodularity-based algorithm is developed to promptly solve dynamic aggregation model under three scenarios, where aggregation operators focus on the resources quantity, quality, and cost-effectiveness, respectively. The polynomial computational complexity of the proposed algorithm has also been evaluated. Simulations using the IEEE 39-bus (New England) system consists of 10,000 flexible resources were executed to assess the submodularity approach. The proposed algorithm demonstrates superior computing speed and better performance guaranteed results (90%, 97%, 90% in three scenarios) compared to other methods—making it more suitable for implementation in practice. • The complementarity and submodularity of dynamic aggregation process are revealed and proved. • A two-stage dynamic aggregation model consists of resources selection and coordination is established. • A dynamic aggregation algorithm is proposed to deal with different aggregation scenarios. • The approximate guarantees and polynomial computational complexity of algorithm are proved. [ABSTRACT FROM AUTHOR]

Background and Objective: Methylphenidate (MPH) and atomoxetine (ATX) are the most common medications used to treat attention-deficit hyperactivity disorder (ADHD) in China; however, despite this, there is still a paucity of studies comparing their efficacy and safety, particularly for different characteristics. To address the lack of research, a real-world prospective cohort study was conducted to examine these properties of MPH and ATX, and to analyze correlations associated with age, sex, and different ADHD presentation. Methods: Children with ADHD meeting the eligibility criteria were recruited from January 2016 to July 2021. Study participants were treated with either MPH or ATX prescribed in the real-world setting, and were followed up for 26 weeks. Clinical efficacy response and adverse events (AEs) were recorded and measured. Subgroup analysis was performed to examine the efficacy response and AEs associated with age, sex, and different ADHD presentation. Results: A total of 1050 children were recruited and 29 children were lost to follow-up. Of the 1021 children remaining, 533 were treated with MPH and 488 were treated with ATX. No significant differences were found in intelligence quotient, age, sex, or ADHD presentation between the MPH- and ATX-treated groups (p > 0.05). The response rates were 84.6% in the MPH-treated group and 63.3% in the ATX-treated group. Subgroup analysis of response rate demonstrated that the treatment effect of MPH over ATX was consistent across subgroups except in the girls (odds ratio [OR] 2.09, 95% confidence interval [CI] 0.97–4.7) and the hyperactive/impulsive presentation group (OR 2.88, 95% CI 0.77–12.76). A total of 47.8% of children experienced AEs during MPH treatment, significantly lower than the rate of 56.8% during ATX treatment (p < 0.05). The incidence of AEs in the MPH-treated group was higher in young children (<8 years: 56.8%; 8–10 years: 47.2%) and lower in children over 10 years of age (29.0%). Conclusions: Overall, MPH was more effective and better tolerated than ATX. The incidence of AEs in children treated with MPH varied with age, and was higher in young children and lower in children over 10 years of age. [ABSTRACT FROM AUTHOR]

The present study investigated high-aspect ratio micro-hole array parts which were made by ZrO2 micro-powder with different particle sizes and micro-powder injection molding technology. It analysed the influence of particle sizes on feedstock, debinding and sintering of ceramic nozzles with multi-micro-holes. The forming quality of ceramic nozzles with multi-micro-holes was discussed in this paper. The results show that the two mixed ZrO2 feedstocks have fine uniformity. The average deviation of the feedstock made with 200 nm powder was −2%, and the average deviation of the feedstock made with 100 nm powder was −7.1%. The sample showed certain sintering characteristics which provided better strength (11.10 MPa) to parts after debinding. The linear shrinkage and the density of the two powder samples at different sintering temperatures increased as the sintering temperature increased. If the temperature continued to increase, the linear shrinkage and the density decreased. The highest hardness and flexural strength values of the ZrO2 sample with 200 nm powder used were: 1265.5 HV and 453.4 MPa, and the crystalline particle size was 0.36 μm. The highest hardness and flexural strength values of the ZrO2 sample with 100 nm powder used were: 1425.8 HV and 503.6 MPa, and the crystalline particle size was 0.18 μm. The ceramic nozzles with multi-micro holes shrunk to nearly the same axial, radial and circumferential directions during sintering. After sintering, the roundness of ceramic micro-hole met the user requirements, and the circular hole had a high parallelism in the axial direction. The micropore diameter was 450 ± 5 μm, and it was possible to control the dimensional accuracy within 1.5% after sintering. The study presented a superior application prospect for high-aspect ratio micro hole array parts in aerospace, electronics and biomedicine. [ABSTRACT FROM AUTHOR]

In this paper, one kind of new composite material formed with Nb and SiC was prepared by hot pressing sintering. The influence of the addition of SiC particles on the mechanical properties at room and high temperature was analyzed. The composite material consists of three phases: Nb2C, Nb3Si, and Nb solid solution (Nbss). The fraction of SiC particles added in the Nb matrix was 3%, 5%, and 7%, respectively. Flexural strength, Vickers hardness, and compressive strength at room temperature were improved with the increasing of SiC content. Among them, compressive strength and fracture toughness were higher than those of Nb/Nb5Si3 composites. The compressive strength at high temperature of the new composites was higher than that of Nb-Si alloys, which improved with the increasing of SiC content. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Self-lubricating film was designed on Si wafer via thiol-ene "click" reaction. • Thicker molecules packing density of MACEs was obtained via heating than UV. • SAM H possessed lower friction coefficient and longer tribological durability. Abstract Self-assembled monolayer (SAM) of multiply-alkylated cyclopentenes (MACEs), homologue of the famous hydrocarbon mobile lubricant multiply alkylated cyclopentanes (MACs), was fabricated as self-lubricating film on the surface of the thiol-functionalized silicon wafer (HS-Si) via facile thiol-ene "click" reaction, induced with UV-light or heating. The surface property analysis, including static contact angle and surface roughness, indicated the successful self-assembly. The microtribological tests of the different samples on a UMT-1 tribometer (CETR) in a ball-on-plate contact configuration showed that the SAMs possessed excellent self-lubricating property, in which the SAM H obtained via the heating-induced thiol-ene "click" reaction had the lower friction coefficient and longer tribological durability than the SAM UV one prepared under UV-irradiation. The proposed self-lubricating strategy is expected to be used in the lubrication of micro-/nano-electromechanical systems (MEMSs/NEMSs). [ABSTRACT FROM AUTHOR]

[Display omitted] • The PP/EPR/PE exhibited superior modifying effects and followed by HIPP and FRPP. • Copolymerizing with EPR could improve partial properties of waste PP modified asphalt. • Waste HIPP modified asphalt showed best creep recovery property and storage stability. • Waste FRPP could establish crosslink structure within virgin asphalt binder. Using end-of-life polypropylene (PP) as additive to modify base asphalt has received rapid-growing attention. However, the low flexibility of waste PP results in undesired low-temperature property so as to limit its application. Accordingly, three waste PP matrix copolymers were analyzed in this study, including laboratory-made PP, ethylene-propylene-rubber (EPR) and polyethylene (PE) copolymer, commercial highimpact PP (HIPP) and fiber reinforced PP (FRPP). Moreover, their modifying effects were measured with respect to creep recovery, force-ductility curve, fatigue resistance and storage stability. The fluorescence micrograph (FM) was also analyzed to reveal the modification mechanism. Analytic hierarchy process (AHP) was employed to determine the optimum waste PP matrix composite and concentration. Test results showed that mingling waste PP with rubber, elastomer or fiber was attributed to enhance the toughness of corresponding modified asphalt at low temperature. Considering the overall properties of modified asphalts, the PP/EPR/PE a top priority and followed by HIPP and FRPP. [ABSTRACT FROM AUTHOR]

The hot deformation behavior and pulse current assisted diffusion bonding (PCDB) behavior of sintered γ-TiAl based alloy with near gamma microstructure were investigated for fabricating honeycomb structure via isothermal forging - PCDB route. Honeycomb core structures were fabricated via isothermal forging at 1150–1250 °C with a nominal strain rate of 10 −3 s −1 based on the hot deformation behavior of the sintered alloy. Additionally, the mechanical property and structural morphology demonstrated that the best forging parameter was forging at 1200 °C with a nominal strain rate of 10 −3 s −1 . Subsequently, the effects of bonding temperature, holding time, and bonding pressure on the microstructure evolution, plastic strain, and shear strength of the PCDB joints were investigated. The plastic strain and shear strength of the PCDB joints increased with increasing bonding temperature, time and stress, additionally, the fracture mode transformed from interfacial sliding fracture into substrate fracture with the optimization of bonding parameters. Furthermore, a sound metallurgical bonding joint with smaller plastic strain and shear strength as high as 92% of the base material was achieved at 1100 °C with a holding time of 20 min and a pressure of 25 MPa, showing priority compared to traditional hot pressing diffusion bonding process. [ABSTRACT FROM AUTHOR]

We have developed and characterized a plasmon-excitation scattering-type near-field scanning optical microscope with sharpened single carbon nanotube probe. The developed microscope can optically capture differences in the refractive index of single-nanometer surface structures. Statistical analysis enabled us to estimate the precision of the optical length measurement to 1.8 nm. [ABSTRACT FROM AUTHOR]

We deposit hydrogenated amorphous carbon (a-C:H) films by magnetron sputtering of graphite in an Ar + C 2 H 2 mixture at various bias voltages. The mechanical properties, Raman spectra, and high-vacuum frictional behaviors of the a-C:H films indicate that the films deposited at bias 0, –50, and −100 V are polymer-like carbon (PLC) films and the film deposited at −150 V is a diamond-like carbon (DLC) film. The lifetimes of superlubricity, with friction coefficient ∼0.002, of the PLC films in high-vacuum increase from 10000 to 28000 cycles with increasing bias, although the film thicknesses decrease. The DLC film's wear-life is ∼600 cycles. The enhanced wear-resistance in PLC films is attributed to improvement of the crosslinking degree of the PLC network and the film compactness. [ABSTRACT FROM AUTHOR]

Recycled aggregate concrete (RAC) is an eco-friendly material that is increasingly being used in new constructions. Nowadays, the application of RAC is mainly limited by lower mechanical properties and durability performance. This paper outlines the mechanical properties (i.e., compressive strength, splitting tensile strength, and flexural strength), pore structure, and water absorption of RAC with supplementary cementitious materials (SCMs). In addition, to improve the properties and more sustainability of RAC, utilization of SCMs such as fly ash (FA), granulated blast furnace slag (GBFS), silica fume(SF), and metakaolin(MK) were used as cement replacement materials. Thirty-two mixtures were designed with five volume ratios of recycled concrete aggregates (RCA) replacing natural aggregate and containing FA, GBFS, SF, and MK contents as cement replacement (by weight), respectively. The results show that up to 20% FA or 20% SF in binary blends, or 15% SF in ternary blends, the RAC had higher compressive and splitting tensile strength and, thereafter, a gradual reduction in strength with an increase in FA or SF. MK significantly increasingly improved the strengths of RAC with binary or ternary blends, with the rise in the replacement ratio of MK. By characterization of the mineral composition and its relative weight, and the pore structure of RAC with SCMs, the critical influential factors on mechanical properties and water absorption of RAC with binary or ternary blends were the pozzolanic action and filling action of SCMs; however, those of RAC with quaternary or multi- blends was the filling action. It was also found that the water absorptions of RAC with SCMs were positive relative to the total intrusion volume and porosity. A regression model of predicted compressive strength was established. [ABSTRACT FROM AUTHOR]

Liposarcoma (LPS) is one of the most common subtypes of sarcoma with a high recurrence rate. CENPF is a regulator of cell cycle, differential expression of which has been shown to be related with various cancers. However, the prognostic value of CENPF in LPS has not been deciphered yet. Using data from TCGA and GEO datasets, the expression difference of CENPF and its effects on the prognosis or immune infiltration of LPS patients were analyzed. As results show, CENPF was significantly upregulated in LPS compared to normal tissues. Survival curves illustrated that high CENPF expression was significantly associated with adverse prognosis. Univariate and multivariate analysis suggested that CENPF expression could be an independent risk factor for LPS. CENPF was closely related to chromosome segregation, microtubule binding and cell cycle. Immune infiltration analysis elucidated a negative correlation between CENPF expression and immune score. In conclusion, CENPF not only could be considered as a potential prognostic biomarker but also a potential malignant indicator of immune infiltration-related survival for LPS. The elevated expression of CENPF reveals an unfavorable prognostic outcome and worse immune score. Thus, therapeutically targeting CENPF combined with immunotherapy might be an attractive strategy for the treatment of LPS. [ABSTRACT FROM AUTHOR]

This paper first proposes a fractional prospect theory-based method for modeling the bidding strategy of a power retail company in the uniform pricing electricity market under price uncertainty. Different from the traditional methods which assume that the retail company always bids completely rationally to maximize its individual payoffs, this paper introduces the prospect theory (PT) into the bidding model to reflect the impacts of psychological factors and subjective perceptions. To address the partial uncertainties brought by the continuous probability distribution in the value function, this paper modifies the classical PT into the fractional prospect theory (FPT) and builds up the FPT-based bidding strategy model under 1-segment and 3-segment bidding rules. The simulation results show that the proposed method can effectively model the psychological factors in the bidding strategy of a power retail company in the uniform pricing electricity market under price uncertainty, which can help to further study the competition and equilibrium of the uniform pricing market considering the psychological factors of the participants. [ABSTRACT FROM AUTHOR]

Tetrahedral amorphous carbon (ta-C) films with bias-regulated (namely from −50 V to −200 V) Ti interlayers were prepared on AISI 440C stainless steel substrates, followed by systematic investigation on the microstructure, mechanical, and adhesion properties of such films. In addition, molecular dynamics simulation has been employed to study the formation of Ti films deposited with different incident energy, which was found to be influenced by the bias voltage significantly. The experimental results demonstrated that varying bias voltage on the Ti interlayer exerted minor influence on the sp3C fraction and mechanical properties of ta-C films. Molecular dynamics simulations showed further support for the experimental results. The Ti interlayer exhibited the amorphous-like microstructure, and increasing Ti-atom incident energy resulted in increasing Ti/Fe interlayer thickness and a firstly rising and then descending Fe/Ti interfacial bonding strength. The adhesive failure mode can be divided into buckling crack and interfacial spallation, which was primarily attributed to the tensile-to-compressive transformation of the Ti-interlayer internal stress. Optimised adhesion property of ta-C films can be achieved with a Ti-interlayer bias voltage of ∼ -100 V. • The effects of interlayer bias voltage on the mechanical properties was studied. • The highest adhesion strength was obtained with voltage bias of −100 V in the Ti interlayer. • MD simulations to clarify the relationship between the adhesion and the Ti ions incident energy. [ABSTRACT FROM AUTHOR]

We investigate an open question in the study of the curse of dimensionality: Is it possible to find the single nearest neighbor of a query in high dimensions? Using the notion of (in)distinguishability to examine whether the feature map of a kernel is able to distinguish two distinct points in high dimensions, we analyze this ability of a metric-based Lipschitz continuous kernel as well as that of the recently introduced Isolation Kernel. Between the two kernels, we show that only Isolation Kernel has distinguishability and it performs consistently well in four tasks: indexed search for exact nearest neighbor search, anomaly detection using kernel density estimation, t-SNE visualization and SVM classification in both low and high dimensions, compared with distance, Gaussian and three other existing kernels. [ABSTRACT FROM AUTHOR]

To sustain energy supply capability and mitigate vulnerability to operational failures, enhancing resilience in multi-energy systems (MES) becomes imperative in the face of deliberate attacks and natural disruptions. In this paper, a resilience enhancement optimization model (REOM) is proposed, incorporating various enhancement measures such as adding backup, strengthening physical protection, and constructing new lines. The objective is to minimize the betweenness centrality loss of the MES after being attacked or disrupted, where the betweenness centrality is improved by integrating the power output of energy supply equipment as weighted factors. To accelerate the calculation of shortest paths in large-scale MES, an approximate algorithm for shortest paths is proposed to extract necessary information of shortest paths, through selecting landmarks and converting the target path into the summation of different segments with the landmarks. Then, the REOM is transformed into a bi-level problem while the lower-level one is linearized into a mixed-integer linear programming (MILP) problem, and a genetic algorithm-MILP (GA-MILP) is employed to solve it. Assessing the optimal resilience enhancement plan, a comparison is made with the results obtained under two different attack strategies in the remaining two scenarios through three validation indicators: network fragmentation, decline in energy transfer efficiency, and load loss rate. Through simulations on both a 67-bus power-gas system and a virtual European power-gas system, it was observed that the weighted betweenness centrality loss decreased by 45.37% and 14.95%, respectively, compared to scenarios without the incorporation of the optimal resilience enhancement plan, effectively reinforcing system robustness. [Display omitted] • A complex network theory-based resilience enhancement optimization model (REOM) is established for multi-energy system. • An approximate algorithm for shortest paths (AA-SPC) is proposed to extract shortest-path information efficiently. • A self-built virtual 1310-bus European power-gas system is applied for REOM. • A genetic algorithm-mixed-integer linear programming (GA-MILP) is proposed to solve the REOM. [ABSTRACT FROM AUTHOR]

The application of brick–concrete recycled aggregates can alleviate the problem of increasing construction waste and increasing scarcity of natural aggregates. The different moisture condition of coarse aggregates can significantly affect the performance of brick–concrete recycled aggregate concrete. In this paper, the additional water quantity of dry and air-dried brick–concrete recycled coarse aggregate concrete was determined. Additionally, the fluidity, rheological parameters, autogenous shrinkage, strength and chloride ion penetration resistance were tested, and compared with saturated surface dry recycled brick–concrete coarse aggregate concrete and natural aggregate concrete. The results showed that the slump of concrete was increased, whereas the plastic viscosity, static and dynamic yield stress were decreased by adding additional water or using saturated surface dry coarse aggregate. Compared with the dry and saturated surface dry state, the air-dried recycled coarse aggregate concrete has the smallest 28 days autogenous shrinkage value, higher compressive strength and splitting tensile strength, and less adverse effects on chloride permeability. It is most beneficial to the performance and economy of concrete to adopt the air-dried state when the brick–concrete recycled coarse aggregate is applied in engineering. [ABSTRACT FROM AUTHOR]

Renewable energy has the characteristics of low carbon and environmental protection compared to traditional water and thermal power, but it also has the intermittency and uncertainty that traditional water and thermal power does not have. These characteristics make the inertia of the power system increase, which greatly affects the frequency stability of the grid. To solve such problems, the participation of demand-side resources (DSRs) in the dispatch of power systems has become a viable solution.However, unlike generation-side resources, DSRs have their own unique characteristics. In this paper, by taking into account a load frequency control system (LFC) with intermittent demand-side resources, the robust H∞ load frequency control problem are discussed in detail.A robust controller to coordinate the load side with the resource side is introduced. A critical stability criterion and robust performance evaluation of the new LFC system was carried out. Finally, simulation results based on the new LFC system are provided to demonstrate that the proposed control strategy can effectively improve the stability and robustness of the grid under large disturbances, thus allowing the grid frequency to return to the reference value. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is an early-onset neurodevelopmental disorder in which genetics play a major role. Molecular diagnosis may lead to a more accurate prognosis, improved clinical management, and potential treatment of the condition. Both copy number variations (CNVs) and single nucleotide variations (SNVs) have been reported to contribute to the genetic etiology of ASD. The effectiveness and validity of clinical targeted panel sequencing (CTPS) designed to analyze both CNVs and SNVs can be evaluated in different ASD cohorts. CTPS was performed on 573 patients with the diagnosis of ASD. Medical records of positive CTPS cases were further reviewed and analyzed. Additional medical examinations were performed for a group of selective cases. Positive molecular findings were confirmed by orthogonal methods. The overall positive rate was 19.16% (109/569) in our cohort. About 13.89% (79/569) and 4.40% (25/569) of cases had SNVs only and CNVs only findings, respectively, while 0.9% (5/569) of cases had both SNV and CNV findings. For cases with SNVs findings, the SHANK3 gene has the greatest number of reportable variants, followed by gene MYT1L. Patients with MYT1L variants share common and specific clinical characteristics. We found a child with compound heterozygous SLC26A4 variants had an enlarged vestibular aqueduct syndrome and autistic phenotype. Our results showed that CTPS is an effective molecular diagnostic tool for ASD. Thorough clinical and genetic evaluation of ASD can lead to more accurate diagnosis and better management of the condition. [ABSTRACT FROM AUTHOR]

Cooling water shortage, frequently attributed to drought and heat waves, poses a significant threat to the operations of thermoelectric power plants and further poses a challenge for the entire power system and environmental stakeholders. Recognizing the critical nexus between power generation and cooling water availability and the potential ability of power generations to adjust generation schedules during cooling water shortages, this paper introduces a security-constrained unit commitment and economic dispatch model considering water-energy nexus. In specific, the model is augmented with a unit-level cooling water requirement (CWR) model and multi-level cooling water availability (CWA) constraints. The unit-level CWR model quantifies the cooling water withdrawal per MWh of power generation, taking into account factors such as thermoelectric generation technologies, cooling system technologies, and environmental parameters. The multi-level CWA constraints incorporate pump-level, plant-level, watershed-level, and forced minimum power constraints, utilizing data derived from actual-based cooling water shortage scenarios. Using a simulation case study in Illinois, United States, this research examines the reliability, economic, and environmental implications of cooling water shortages on power system operations. The results show that Illinois may experience 10–15% daily load curtailment and severe congestion between certain regions from the east to central during cooling water shortages, while once-through and wet-tower units experience a 52% and 17% reduction in power generation. Overall cooling water withdrawal decreases by 24–38% as severity intensifies. © 2017 Elsevier Inc. All rights reserved. • Unit-level cooling water requirement are modeled considering fuel and cooling types. • Add multi-level cooling water availability constraints to power system operation. • Illinois may experience 10–15% daily load curtailment during cooling water shortage. • Power generation from once-through units drops by 52% in the most severe scenario. • Cooling water withdrawal decreases by 24–38% in drought and heat wave scenarios. [ABSTRACT FROM AUTHOR]

Wind power forecast (WPF) plays a crucial role in the reliable and safe operation of power systems. Existing wind power prediction methods mainly focus on the overall trend information, often neglecting the performance of some typical intervals that can significantly impact the reserve requirements of power system, e.g. , unexpected ramp-up and ramp-down, local peak interval (LPI), and so on. Therefore, the primary focus of this paper is to explore techniques for enhancing the accuracy of wind power during the LPI. Considering that the points during the LPI are influenced by dynamic ramp characteristics, with the steepness and magnitude of ramps influencing the range of LPI, this paper proposes a novel focused-LPI model by incorporating dynamic ramp considerations. Specifically, beyond the tradition forecasting model, the proposed model encodes the information of ramp occurrence in wind power data based on a positional encoder; subsequently, the proposed model not only outputs standard predictions within a prediction range but also identifies the presence of ramps within these predictions. In addition, this paper employs a dynamically weighted loss function to optimize the proposed multi-task model. The proposed model is applied for various network architectures, and the results confirm that the proposed model is widely suitable for various basis network architectures. Specifically, the R-squared (R2) of the proposed model for the overall trend can exist a little error compared to the initial basic network architectures; the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Relative Error (MRE) of the proposed model for predicting the LPI points can outperform the initial basis network architecture by average enhancements of 7.10%, 2.66%, and 3.46%, respectively. In addition, compared to existing state-of-the-art (SoTA) models in the LPI points, the proposed model obtains improved performance with 14.43% for MAE and 11.19% for RMSE, respectively, presenting its substantial performance enhancement. • Multi-tasks wind power forecast model enhances the accuracy of local peak interval. • Dynamic weighted loss function with learnable parameter balance the multi-tasks model. • Accuracy of local peak interval is improved by an average of 12.8% than SoTA models. • The proposed model outperforms the initial basis network architecture by 4.4%. [ABSTRACT FROM AUTHOR]

The reaction process of deposition of Iridium coating on Mo (1 1 0) surface by atomic layer deposition (ALD) was studied theoretically by using the density functional theory and periodical slab model. The results indicated that the whole ALD reaction cycle of iridium deposition can be divided into two half-reaction processes, that the half-reaction I was the reaction between iridium precursor (Ir(acac) 3) and oxygen atom on Mo cluster, causing the chemical bond length of Ir–C to stretch and that of Mo–O to shorten, and forming a ring-like skeleton structure of transition state Mo–O–C–Ir, which was approximately a planar structure and presenting a fresh and active surface of (CH 3) 2 *Ir–Mo–Ir(CH 3) 2 *; In the half-reaction II, the oxygen atoms react with -(CH 3) 2 * active group of (CH 3) 2 *Ir–Mo–Ir(CH 3) 2 * surface, causing the chemical bond length of Ir–C to stretch and that of O–O to shorten, forming a ring-like skeleton structure of transition state O–C–Ir–C, which was also approximately a planar structure and presenting a fresh and active O*-Ir-Mo-Ir-O* surface eventually. Furthermore, the by-products of every surface reaction were released in the form of CO 2 and H 2 O. The experiment result shown that the surface of iridium coating deposited by ALD at 300 °C was flat and smooth, and the preferred growth crystal plane was (111). The theoretical conclusion was in good agreement with the experimental results. • Reaction process of Iridium coating on Mo surface by atomic layer deposition was studied. • A whole ALD cycle of iridium coating deposition can be divided into two half-reactions. • The half-reaction I is a reaction between Ir(acac) 3 molecules and oxygen atoms. • The half-reaction II is a reaction between oxygen molecules and active group -Ir(acac) 2 *. • The energy change provides evidence to conform the reaction path analysis. [ABSTRACT FROM AUTHOR]

In the field of industrial applications, reasonable selection of frictional counterparts is pivotal for reducing friction and wear. To interpret the tribological behavior of W-DLC films when interfacing with themselves and 9Cr18 steel, W-DLC coatings of varying W content were applied using sputtering of a WC target in a combined Ar and C 2 H 2 atmosphere. The findings reveal that the sp3 content elevates as the WC target power intensifies, peaking at 52.5 at.% with a WC target power of 2 kW. Beyond this point, a further increase in power results in a decline of sp3 content. When W-DLC coatings of different W content are pitted against a 9Cr18 ball, the W-DLC coating with a composition of 19.4 at.% W content exhibits a notably lower friction coefficient and minimized wear rate. The tribological results for W-DLC coatings interfacing with a W-DLC coated 9Cr18 ball surpass those of an uncoated 9Cr18 ball. Moreover, the wear rates for W-DLC coatings with reduced W content, when tested against the W-DLC coated 9Cr18 ball, reduce by more than twice as compared to their performance against an uncoated 9Cr18 ball. This suggests that the transfer layer effect is subdued when W-DLC coatings interface with a W-DLC counterpart. Here, the surface texture and resilience of the coatings assume a significant role. Coatings with resilience and smoother surfaces exhibit enhanced wear resistance. A reduced difference in hardness between the W-DLC coated disc and the 9Cr18 ball makes it prone to pronounced wear. This highlights the notion that the concurrent application of similar W-DLC coatings on both the disc and ball marginally enhances wear resistance. • Tribological behaviors of W-DLC coatings sliding against different materials were investigated. • The content of sp3 increases first and then decreases with the increase of WC target power. • W(19.4 at%)-DLC coating sliding against 9Cr18 has a low friction coefficient and minimal wear rate. • All W-DLC coatings sliding against W-DLC coated 9Cr18 have a better tribological performance. [ABSTRACT FROM AUTHOR]

Power forecast for each renewable power plant (RPP) in the renewable energy clusters is essential. Though existing graph neural networks (GNN)-based models achieve satisfactory prediction performance by capturing dependencies among distinct RPPs, the static graph structure employed in these models ignores crucial lead-lag correlations among RPPs, resulting from the time difference of the air flow at spatially dispersed RPPs. To address this problem, this paper proposes a novel dynamic graph structure using multiple temporal granularity groups (TGGs) to characterize the lead-lag correlations among RPPs. A granular-based GNN called GGNet is designed to generate an optimal adjacency matrix for the proposed graph structure. Specifically, a two-dimensional convolutional neural network (2D-CNN) is used to quantify the uncertain lead-lag correlations among RPPs; secondly, a gate mechanism is used to calculate a dynamic adjacency matrix; Finally, a graph attention network (GAT) is used to aggregate the information on RPPs based on the well-learned adjacency matrix. Case studies conducted using real-world datasets, with wind power plants and photovoltaic power plants, show our method outperforms state-of-the-art (SoTA) ones with better performance. Compared with the SoTA models, the RMSE N and MAE N of wind power plants for 1–4 h forecast steps decreased on average by 22.925% and 13.18%, respectively; the RMSE N and MAE N of photovoltaic power plants for 1–4 h forecast steps decreased on average by 48.95% and 18.75%, respectively. The results show that the proposed framework can generate improved performance with accuracy and robustness. • Dynamic graph structure can clarify lead-lag power correlation of renewable plants. • A novel model can quantity the lead-lag power correlation of renewable plants. • Memory cell can make the adjacency matrix among renewable plants learnable. • A graph attention network can improve power forecast accuracy of renewable plants. [ABSTRACT FROM AUTHOR]

• Weighted coupling betweenness is proposed to identify critical weak points in PGIS. • An approximate algorithm of shortest-paths calculations (AA-SPC) is proposed. • Six attack strategies and two vulnerability assessment indicators are developed. • A virtual European PGIS is constructed by combining three types of energy hubs. Prompt and precise identification of critical weak points is essential in integrated energy systems (IES) to mitigate system reliability issues and effectively prevent cascading failures. This study proposes methods to identify critical weak points in the power-gas integrated system (PGIS) based on complex network theory for this task. Firstly, we improve the traditional betweenness indices in complex network theory by integrating power output of energy supply equipment as weighted factors to capture diverse types of energy flows, and incorporating the efficiency coefficient to account for energy losses via the PGIS coupling equipment. By integrating these refinements, our approach could further identify some points that are not weak from the viewpoint of topology but are crucial for energy transmission. Secondly, we propose an approximate algorithm for shortest-paths calculations (AA-SPC), which preserves information of total node and some specific topological, and simplifies the calculation of target shortest path, aiming at increasing the efficiency of obtaining path information. Additionally, vulnerability assessment indicators, including system fragmentation and network betweenness loss, measure PGIS vulnerability under different attack strategies. The aforementioned methods are applied to a self-built virtual European PGIS based on the open-source database SciGRID , successfully identifying critical weak points overlooked by traditional betweenness indices. [ABSTRACT FROM AUTHOR]