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The hysteretic damping tuned mass damper (HD-TMD), which exhibits linear damping force, has been achieved by variable friction devices. Such devices own the advantages of stable mitigation capacity and easy maintenance compared to viscous damping devices. Previous studies have mainly concentrated on the vibration mitigation effect of the HD-TMD system without explicit consideration of structural acceleration control. In this context, seismic optimizations of HD-TMD for structural acceleration control were presented, and the effective damping of HD-TMD was investigated. H∞ optimizations of the HD-TMD were considered for undamped and lightly damped structures with fixed-point theory, where the closed-form solutions of optimal and improved parameters were derived. Parametric analysis for the dynamic amplification factors (DAFs) of structural acceleration revealed that the closed-form solutions effectively tuned the DAF into double peaks and reduced the maximum response overall frequency. H2 optimizations were conducted with residue theory for the optimization of the undamped structure, and the optimal parameters of HD-TMD subjected to stochastic ground excitation were obtained by numerical searching and curve-fitting techniques. Effective damping of the HD-TMD was consequently examined using the stochastic stationary process in which the damping effect additionally provided to the structure was measured. The effectiveness of the proposed optimal solutions for the HD-TMD in the form of an available engineering variable friction device was thereby corroborated by twenty sets of seismic ground motions. Spectrum's results indicated that the proposed optimal parameters greatly improved the absolute structural acceleration response and provided excellent seismic mitigation capacity for structural displacement response. The response of the equivalent SDOF demonstrated almost the same trend of absolute structural acceleration reduction, which revealed the successful application of effective damping of HD-TMD for designers. Detailed analysis of the earthquake record indicated the functionality and effectiveness of the proposed methods of HD-TMD with the average absolute structural acceleration reduction ratio of 65.86% and 42.66% for maximum reduction and standard deviation reduction, respectively. [ABSTRACT FROM AUTHOR]

The principal difference between hydroponics and other substrate cultivation methods is the flowing liquid hydroponic cultivation substrate. Our previous studies have revealed that a suitable flowing environment of nutrient solution promoted root development and plant growth, while an excess flow environment was unfavorable for plants. To explain the thigmomorphogenetic response of excess flow-induced metabolic changes, six groups of lettuce (Lactuca sativa L.), including two flow conditions and three time periods, were grown. Compared with the plants without flow, the plants with flow showed decreased root fresh weight, total root length, root surface area, and root volume but increased average root diameter and root density. The roots with flow had more upregulated metabolites than those without flow, suggesting that the flow may trigger metabolic synthesis and activity. Seventy-nine common differential metabolites among six groups were screened, and enrichment analysis showed the most significant enrichment in the arginine biosynthesis pathway. Arginine was present in all the groups and exhibited greater concentrations in roots with flow than without flow. It can be speculated from the results that a high-flowing environment of nutrient solution promotes arginine synthesis, resulting in changes in root morphology. The findings provide insights on root thigmomorphogenesis affected by its growing conditions and help understand how plants respond to environmental mechanical forces. [ABSTRACT FROM AUTHOR]

We present a Zeeman–Doppler imaging study of two weak-line T Tauri stars TAP 4 and TAP 40, based on the high-resolution spectropolarimetric observations with ESPaDOnS at the Canada–France–Hawaii Telescope in November 2013, in the framework of the Magnetic Topologies of Young Stars and Survival of close-in giant Exoplanets large programme. We apply two Zeeman–Doppler imaging codes to the Stokes I and V profiles to reconstruct their brightness and large-scale magnetic field images. The results given by the two imaging codes are in good agreement with each other. TAP 4 shows a large polar cool spot and several intermediate-latitude warm spots on its surface, whereas TAP 40 exhibits very weak variations in its Stokes I profiles, suggesting a mostly unspotted photosphere. We detect Zeeman signatures in the Stokes V profiles of both stars. The reconstructed magnetic maps reveal dominantly toroidal fields, which enclose about 60 per cent of the total magnetic energy for both TAP 4 and TAP 40. Both stars show prominent circular ring features of the azimuthal magnetic field. We derive a solar-like surface differential rotation on TAP 4 from the tomographic modelling. The brightness image of TAP 4 is used to predict the radial velocity (RV) jitters induced by its activity. After filtering out the activity jitter, the rms of its RVs is reduced from 1.7 to 0.2 km s−1, but we do not detect any periodic signals in the filtered RVs of TAP 4, implying that it is unlikely to host a close-in exoplanet more massive than ∼3.5 M Jup at 0.1 au. [ABSTRACT FROM AUTHOR]

Polymer dielectrics with high energy density are of urgent demand in electric and electronic devices, but the tradeoff between dielectric constant and breakdown strength is still unsolved. Herein, the synthesis and molar mass control of three alternating [1.1.1]propellane‐(meth)acrylate copolymers, denoted as P‐MA, P‐MMA, and P‐EA, respectively, are reported. These copolymers exhibit high thermal stability and are semi‐crystalline with varied glass transition temperatures and melting temperatures. The rigid bicyclo[1.1.1]pentane units in the polymer backbone promote the orientational polarization of the polar ester groups, thus enhancing the dielectric constants of these polymers, which are 4.50 for P‐EA, 4.55 for P‐MA, and 5.11 for P‐MMA at 10 Hz and room temperature, respectively. Moreover, the high breakdown strength is ensured by the non‐conjugated nature of bicyclo[1.1.1]pentane unit. As a result, these copolymers show extraordinary energy storage performance; P‐MA exhibits a discharge energy density of 9.73 J cm–3 at 750 MV m–1 and ambient temperature. This work provides a new type of promising candidates as polymer dielectrics for film capacitors, and offers an efficient strategy to improve the dielectric and energy storage properties by introducing rigid non‐conjugated bicyclo[1.1.1]pentane unit into the polymer backbone. [ABSTRACT FROM AUTHOR]

The hysteretic damping tuned mass damper (HD-TMD) is composed of a spring element, a hysteretic damping (HD) element, and a mass. The HD force is proportional to the displacement of the tuned mass damper (TMD). Recently, the application of HD-TMD has emerged, but its optimal design is still lacking. To fill this academic gap, numerical solutions for optimal parameters of HD-TMD subjected to white-noise excitation were obtained based on the H2 optimization criterion. Performance balance optimization with a weighting factor was carried out to improve the response of a structure with the HD-TMD system. A set of earthquake records and harmonic excitations were conducted to prove the effectiveness of the optimal numerical solutions and the performance balance design. It was found that the performance of the HD-TMD is slightly better than that of the traditional optimized TMD. As a real TMD application of HD-TMD, the variable friction pendulum TMD (VFP-TMD) was selected to experience earthquakes with the proposed optimal methods. Results showed that the optimal solutions provided the best performance but raised the problem of difficulty in maintaining linearity with a large displacement. Nevertheless, the performance balance design helped reduce this defect and provided impressive seismic mitigation capacity. Compared with the optimal numerical solution results, the performance balance design demonstrated 2.847% of loss in the maximum structural displacement reduction rate and 3.709% of loss in the root mean square reduction rate during the earthquake-excited period, respectively. [ABSTRACT FROM AUTHOR]

The rapid development of the aviation industry has put forward higher and higher requirements for material properties, and the research on smart material structure has also received widespread attention. Smart materials (e.g., piezoelectric materials, shape memory materials, and giant magnetostrictive materials) have unique physical properties and excellent integration properties, and they perform well as sensors or actuators in the aviation industry, providing a solid material foundation for various intelligent applications in the aviation industry. As a popular smart material, piezoelectric materials have a large number of application research in structural health monitoring, energy harvest, vibration and noise control, damage control, and other fields. As a unique material with deformation ability, shape memory materials have their own outstanding performance in the field of shape control, low-shock release, vibration control, and impact absorption. At the same time, as a material to assist other structures, it also has important applications in the fields of sealing connection and structural self-healing. Giant magnetostrictive material is a representative advanced material, which has unique application advantages in guided wave monitoring, vibration control, energy harvest, and other directions. In addition, giant magnetostrictive materials themselves have high-resolution output, and there are many studies in the direction of high-precision actuators. Some smart materials are summarized and discussed in the above application directions, aiming at providing a reference for the initial development of follow-up related research. [ABSTRACT FROM AUTHOR]

Tartary buckwheat (Fagopyrum tataricum) is rich in polysaccharides that can be utilized by the gut microbiota (GM) and provide several health benefits. However, the mechanisms underlying the action of these polysaccharides remain unclear to date. In this study, Tartary buckwheat polysaccharides (TBP) were purified, and five fractions were obtained. The composition of these fractions was determined using ion chromatography. Different TBP components were investigated regarding their probiotic effect on three species of Bifidobacteria and Lactobacillus rhamnosus. In addition, the effect of TBP on GM and short‐chain fatty acids (SCFAs) was evaluated. Results showed that the probiotic effect of TBP fraction was dependent on their composition. The polysaccharides present in different fractions had specific probiotic effects. TBP‐1.0, mainly composed of fucose, glucose, and d‐galactose, exhibited the strongest proliferation effect on L. rhamnosus, while TBP‐W, rich in glucose, d‐galactose, and fructose, had the best promoting effect on Bifidobacterium longum and Bifidobacterium adolescentis growth. Furthermore, TBP‐0.2, composed of d‐galacturonic acid, d‐galactose, xylose, and arabinose, exhibited its highest impact on Bifidobacterium breve growth. The composition of GM was significantly altered by adding TBP during fecal fermentation, with an increased relative abundance of Lactococcus, Phascolarctobacterium, Bacteroidetes, and Shigella. Simultaneously, the level of SCFA was also significantly increased by TBP. Our findings indicate that Tartary buckwheat can provide specific dietary polysaccharide sources to modulate and maintain GM diversity. They provide a basis for Tartary buckwheat commercial utilization for GM modulation. [ABSTRACT FROM AUTHOR]

Massive residential power consumption information provides data support for the mining and analysis of load patterns. This article proposes a complete framework for load pattern identification, which mainly includes the clustering module and the classification module. Considering that the high-dimensional load profiling dataset will bring a heavy computational burden, multiple dimensional scaling is introduced in the process of data preprocessing. Then, an innovative mixture model based on regular vine copula mixture model (RVMM) is adopted for clustering typical load patterns. Finally, a random forest (RF) classifier constructed with certain load characteristic indexes and RVMM clustering results is employed as a supervised classification model to predict the categories of subsequent new customers, and the accuracy is calculated by the 10-fold cross-validation. It is demonstrated in the case study that the proposed RVMM algorithm exhibits better performance in the clustering validity evaluation. Besides, higher accuracy is achieved by the RF classifier. [ABSTRACT FROM AUTHOR]

Economic scheduling is an important solution to improve the operational efficiency of integrated energy system (IES). Active power is the majority being considered in economic scheduling, ignoring the influence of var-voltage effect on scheduling. In this article, an agent-based var-voltage control (VVC) capability is developed, and integrated in the economic scheduling modeling of IES. First, we build the VVC agent model based on the Markov decision process, and the economic scheduling model of IES is built with the decision function of the VVC agent as a constraint. Then, because the decision function is highly nonconvex and nonlinear, a deep learning enabled surrogate model is proposed to solve the scheduling problem. In the surrogate model, we train a pooling multilayer perception (P-MLP) to fit the mapping relationship between scheduling and maximum voltage deviation under VVC. And the trained P-MLP is used to surrogate the decision function constraint. After surrogating, the scheduling problem is transformed into a mixed integer programming problem, which can be solved directly by calling the solver. Finally, the effectiveness and accuracy of the proposed method are tested by cases. The results show that the scheduling integrated with the VVC capability model can strictly meet safety constraints and reduce the operation cost of IES as well. [ABSTRACT FROM AUTHOR]

The manipulation of surface plasmon polaritons plays a pivotal role in plasmonic science and technology, however, the modulation efficiency of the traditional method suffers from the weak light-matter interaction. Herein, we propose a new method to overcome this obstacle by directly controlling the couple of photon and electron. In this paper, a hybrid graphene-dielectric- interdigital electrode structure is numerically and experimentally investigated. The plasmon is excited due to the confined carrier which is regulated by the potential wells. The frequency of plasmon can be tuned over a range of ~ 33 cm−1, and the obtained maximum extinction ratio is 8% via changing the confined area and the density of carrier. These findings may open up a new path to design the high efficiency all-optical modulator because the electrons can also be driven optically. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the vibration of space robot will reduce the dynamic accuracy of robot, a method of vibration suppression of space robot through trajectory planning is proposed. First, the joint was simplified to a linear torsion spring, and the flexible rod was modelled using the finite element method, resulting in a flexible motion model of the robot. Then, a rigid-soft coupled dynamic model that combined the flexible motion model with the Lagrange method was established. Using the dynamic model, the factors influencing the vibration behaviour of space robots were analysed. Finally, the space robot was subjected to vibration suppression through trajectory planning. As verified by experimental analysis, different trajectories and loads affect the excitation force and inherent characteristics of the robot. In the design process, it is necessary to consider the relationship between the excitation force and natural frequency. The trajectory planning method has apparent effects on vibration suppression. The vibration amplitude was significantly reduced, which can improve the positioning accuracy and work efficiency of the robot. [ABSTRACT FROM AUTHOR]

We apply the variational autoencoder (VAE) to the LAMOST-K2 low-resolution spectra to detect the magnetic activity of the stars in the K2 field. After the training on the spectra of the selected inactive stars, the VAE model can efficiently generate the synthetic reference templates needed by the spectral subtraction procedure, without knowing any stellar parameters. Then, we detect the peculiar spectral features, such as chromospheric emissions, strong nebular emissions, and lithium absorptions, in our sample. We measure the emissions of the chromospheric activity indicators, Hα and Ca  ii infrared triplet (IRT) lines, to quantify the stellar magnetic activity. The excess emissions of Hα and Ca  ii IRT lines of the active stars are correlated well to the rotational periods and the amplitudes of light curves derived from the K2 photometry. We degrade the LAMOST spectra to simulate the slitless spectra of the China Space Station Telescope (CSST) and apply the VAE to the simulated data. For cool active stars, we reveal a good agreement between the equivalent widths of Hα line derived from the spectra with two resolutions. The result indicates the ability of identifying the magnetically active stars in the future CSST survey, which will deliver an unprecedented large data base of low-resolution spectra as well as simultaneous multiband photometry of stars. [ABSTRACT FROM AUTHOR]

Cronobacter spp. is an important foodborne pathogen that can cause life‐threatening diseases in infants and immunocompromised adults. The present study was carried out to understand the prevalence and characterization of Cronobacter spp. in dried edible mushrooms in Jiangsu province, China. Cronobacter isolates were identified and genotyped by multilocus sequence typing (MLST); the antimicrobial susceptibility of Cronobacter strains was determined by the disk diffusion method; the biofilm formation ability of Cronobacter spp. was assessed using the microtiter plate method. The overall prevalence of Cronobacter spp. in dried edible mushrooms was 14.8%, with the highest contamination rate of after 37.2% found in Auricularia auricular. The Cronobacter isolates were identified as C. sakazakii (n = 26), C. malonaticus (n = 2), C. dublinensis (n = 2) and C. turicensis (n = 1). The MLST scheme produced 20 sequence types (STs), two of which were newly identified. ST148 was the most prevalent ST (n = 5), followed by ST4 (n = 3), ST17 (n = 3), ST64 (n = 3), and ST540 (n = 2). One (3.2%) and 15 (48.4%) Cronobacter isolates were resistant to tetracycline and meropenem, respectively. In contrast, all of the tested isolates were susceptible to the remaining 14 antibiotics. Moreover, 20 (64.5%) Cronobacter isolates showed weak ability to produce biofilm, but no isolates showed strong or moderate biofilm‐forming ability. Practical Application: Our findings revealed a high genetic diversity of Cronobacter spp. in dried edible mushrooms and provided new epidemiological evidence for the widespread existence of Cronobacter spp. in such products. The presence of Cronobacter spp. in dried edible mushrooms may pose potential risks to human health and enhancing the hygiene of such products are necessary to ensure food safety. [ABSTRACT FROM AUTHOR]

• The nonlinear behavior of the PTMD with different damping is fully described. • Damping nonlinearity and stiffness nonlinearity of structure-PTMDs system are illustrated. • The attenuation characteristics of the PTMDs are obtained with closed-form expressions. • Nonlinear performance oriented optimization is based on amplitude robustness. • The optimization achieves an enlarged damping dissipation capacity of PTMD with HD. The inherent nonlinearity of the pendulum motion becomes increasingly pronounced as excitation amplitudes rise, leading to the uncertainty of vibration and the loss of predictive accuracy owing to the linear assumption. To address this concern, this study introduces the pendulum tuned mass damper (PTMD) with hysteretic damping (HD) to realize the nonlinear performance oriented optimal seismic design. The primary contribution of this study is introducing the nonlinear performance of the PTMD with HD, thereby proposing amplitude robustness optimization based on nonlinear dynamic performance. Theoretical configurations of PTMD that facilitate different types of damping, including viscous damping (VD), constant damping, and hysteretic damping (HD), are compared. The Krylov–Bogoliubov (K–B) method is originally adopted to analyze the nonlinear effect of the PTMDs in the case of forced oscillation and free vibration. The nonlinear frequency response functions (FRFs) of the structure-PTMD system are derived, and the coupled systems are evaluated. The presence of stiffness softening, the persistence of stable solutions, and the occurrence of unstable frequency response loops demonstrate the inherent nonlinearity and sensitivity of control effectiveness. Attenuation characteristics of the PTMDs are obtained to determine the damping dissipation properties with accuracy compared with the dynamic solutions. Prue HD shows a similar dynamic interaction with an exponential decay in damping dissipation as the VD, which exhibits the linear damping performance for the coupled control system. A nonlinear performance oriented optimal seismic design based on the amplitude robustness index is proposed to consider the amplitude uncertainty impact on the structure-PTMD system. A case study is assessed based on the 20-story benchmark structure to investigate the functionality of the proposed optimization for the PTMD with HD. The results confirm the effectiveness of optimization from the perspective of FRFs, where the optimal PTMD with HD exhibited an FRF with a lower peak in structural amplitude compared to the optimal PTMD with VD. Seismic validations of the spectral analysis and specific earthquake evaluations verify the applicability of the proposed optimization for PTMD with HD, enabling an enlarged damping dissipation capacity as earthquake excitation increases to provide better structural protection. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Gene expression programs are intimately linked to the interplay of active cis regulatory elements mediated by chromatin contacts and associated RNAs. Genome-wide association studies (GWAS) have identified many variants in these regulatory elements that can contribute to phenotypic diversity. However, the functional interpretation of these variants remains nontrivial due to the lack of chromatin contact information or limited contact resolution. Furthermore, the distribution and role of chromatin-associated RNAs in gene expression and chromatin conformation remain poorly understood. To address this, we first present a comprehensive interaction map of nuclear dynamics of 3D chromatin-chromatin interactions (H3K27ac BL-HiChIP) and RNA-chromatin interactions (GRID-seq) to reveal genomic variants that contribute to complex skeletal muscle traits. Results: In a genome-wide scan, we provide systematic fine mapping and gene prioritization from GWAS leading signals that underlie phenotypic variability of growth rate, meat quality, and carcass performance. A set of candidate functional variants and 54 target genes previously not detected were identified, with 71% of these candidate functional variants choosing to skip over their nearest gene to regulate the target gene in a long-range manner. The effects of three functional variants regulating KLF6 (related to days to 100 kg), MXRA8 (related to lean meat percentage), and TAF11 (related to loin muscle depth) were observed in two pig populations. Moreover, we find that this multi-omics interaction map consists of functional communities that are enriched in specific biological functions, and GWAS target genes can serve as core genes for exploring peripheral trait-relevant genes. Conclusions: Our results provide a valuable resource of candidate functional variants for complex skeletal muscle-related traits and establish an integrated approach to complement existing 3D genomics by exploiting RNA-chromatin and chromatin-chromatin interactions for future association studies. [ABSTRACT FROM AUTHOR]

The manipulation of surface plasmon polaritons plays a pivotal role in plasmonic science and technology, however, the modulation efficiency of the traditional method suffers from the weak light-matter interaction. Herein, we propose a new method to overcome this obstacle by directly controlling the couple of photon and electron. In this paper, a hybrid graphene-dielectric- interdigital electrode structure is numerically and experimentally investigated. The plasmon is excited due to the confined carrier which is regulated by the potential wells. The frequency of plasmon can be tuned over a range of ~ 33 cm−1, and the obtained maximum extinction ratio is 8% via changing the confined area and the density of carrier. These findings may open up a new path to design the high efficiency all-optical modulator because the electrons can also be driven optically. [ABSTRACT FROM AUTHOR]

The emergence of prosumers in the distribution networks provides the proactive local management of distributed energy resources (DERs) and distributed energy trading. A bilevel framework of prosumers is proposed, enabling the joint optimization of the internal scheduling and external peer-to-peer (P2P) trading. Interactive benefit is defined as the marginal response cost. On the lower prosumer scheduling level, instead of concurrent scheduling process considering merely internal DERs’ response, interactive benefits of the DERs and the P2P trading are both taken into consideration while solving prosumers’ scheduling problem. Subsequently, a cooperative interaction method using the interactive benefit prioritization principle is proposed for the joint optimization problem in prosumer, considering both internal and external strategies. On the upper P2P trading level, an iterative bilateral negotiation algorithm is proposed, integrated with network charges. The proposed algorithm enables trading peers to reach an agreement, without the intervention of DSO. As a means to attribute the costs incurred by P2P trades to prosumers, the network charges include the congestion and loss costs, and the maintenance and modernization costs. Finally, the proposed method is implemented and benchmarked on a test case using the IEEE 33 bus system. The effectiveness of the method is verified in terms of promoting the consumption of DERs and prosumers’ benefits. Also, it is verified that the appropriate network charges may facilitate both the P2P trades and the secure operation. [ABSTRACT FROM AUTHOR]

In recent years, the idea of green aviation and environmental protection has received increasing attention from the aviation industry. Hydrogen energy has an important role in the transition to low-carbon energy systems. To address that, this article conducts the technoeconomic analysis for the hydrogen energy system, photovoltaic energy, battery storage system, electric auxiliary power unit (APU) of aircraft, and electric vehicles (EVs) into the electrified airport energy system. Specifically, the model quantifies aircraft electrical load based on passenger’ travel behavior, establishes a corresponding APU load characteristic model, and establishes an EV charging load profile based on the flight schedule and sequencing algorithm. A mixed-integer linear programming optimization method based on life cycle theory was proposed to minimize the total costs of hydrogen-integrated energy systems for airports (HIES). However, the resilience advantages of hydrogen energy concerning power failure are little explored in existing academic research. Thus, a resilience assessment method and improvement measure were proposed for HIES. Case studies have been conducted under different optimal hydrogen energy integration configurations and disaster times with resilience assessment by considering periods when the power supply capacity of the grid is insufficient. The results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Morus spp. leaves (MSLs) show various beneficial effects in the treatment of metabolic-related diseases, which have created a growing interest in MSL development as dietary supplements and functional foods. The illustration of chemical compositions and screening of high-quality MSL resources are therefore necessary for further application. This study developed a new UHPLC-ESI-QTOF-MS/MS strategy of in-source collision-induced dissociation (IS-CID) and target collision-cell CID (TCC-CID) to quickly capture analogues with consistent skeleton, and combined global natural product social molecular networking (GNPS) to efficiently annotate bioactive phytochemicals in MSLs. For the results, 49 bioactive ingredients, including quercetin-type flavonoids, kaempferol-type flavonoids, chlorogenic acid isomers, 1-deoxynojirimycin, γ-aminobutyric acid, amino acids, and unsaturated fatty acids, were systematically identified in MSLs for the first time. Quantification for the typical components was simultaneously carried out in MSLs of 90 Morus resources collected from different locations. Partial least squares discriminant analysis (PLS-DA) indicated that quercetin-3-O-(6″-O-malonyl)-glucoside, rutin, kaempferol-3-O-(6″-O-malonyl)-glucoside, kaempferol-3-O-rutinoside, and chlorogenic acid showed high variable importance in the project (VIP > 1) that were significant constituents for the differences between MSL species. Then, high-quality MSLs were comprehensively screened in multiple Morus cultivars based on the criteria importance through intercriteria correlation (CRITIC) method. This study presented an efficient strategy to annotate bioactive compounds, revealed the difference of bioactive components in MSLs, and provided important information for the high-value production of Morus cultivars in food and supplement fields. [ABSTRACT FROM AUTHOR]

An anionic 2D→3D interpenetration metal–organic framework containing [NH 4 ] + ions by the simple solvothermal reaction were obtained, denoted as Cu-Zn-MOF. Systematic studies revealed that Cu-Zn-MOF was an efficient ion exchanger material for the selective capture of Sr2+ ions. [Display omitted] • A 2D → 3D interpenetration metal–organic framework (Cu-Zn-MOF) was synthesized by one-step solvothermal method. • Cu-Zn-MOF exhibited high adsorption capacity (q m = 209.8 mg/g), excellent selectivity and fast kinetics towards Sr2+. • The adsorption mechanisms include ion exchange and coordination adsorption. Rapid removal of radioactive strontium from solutions is of great significance for ecosystem conservation. Herein, a new Cu-Zn-MOF namely, [NH 4 ] 3 [(Cu 3 Zn 2 (FDA) 6 (H 2 O) 8 Cl·3H 2 O] (Cu-Zn-MOF ; H 2 FDA = 2,5-furandicarboxylic acid) is designed for the efficient adsorption of radioactive Sr2+ by ion exchange. The newly designed Cu-Zn-MOF possessed an anionic 2D → 3D interpenetration framework based trinuclear centers which are charge-balanced by amino cations. Kinetic studies showed that Cu-Zn-MOF rapidly removed Sr2+ (96.7 % in 4 h), and the kinetic data fitted well with the pseudo-second-order model. The adsorption isotherms were well described by Langmuir model and Cu-Zn-MOF exhibited high adsorption capacity (220.7 mg/g at 298 K), out-performing many state of the art adsorbents. More importantly, Cu-Zn-MOF exhibited intriguingly high selectivity for Sr2+ in solutions containing coexisting ions with good reusability. The findings of this study can provide key and useful information for the adsorptive removal of Sr2+ and other similar radioactive material with minimal processing and cost. [ABSTRACT FROM AUTHOR]

Flexible high-rise buildings are extremely vulnerable to wind, especially when synchronously subjected to alongwind and crosswind forces. In this scenario, acceleration-sensitive targets (such as delicate instruments) are at risk of damage. Moreover, occupant comfort and structural safety may be degraded due to excessive bi-directional vibrations. To resolve this problem, a bi-directional rail variable friction pendulum-tuned mass damper (BRVFP-TMD) is used to achieve optimal bi-directional wind-induced vibration control. The modeling of the BRVFP-TMD for bi-directional high-rise buildings under bi-directional winds was performed. Further, the physical interaction forces of the BRVFP-TMD with a multi-degree-of-freedom structure and the governing equations for the modal structure with the BRVFP-TMD were derived, with experimental results confirming the effectiveness of the linear variable friction force. For the BRVFP-TMD with a lightly damped structure, acceleration optimizations were conducted to obtain closed-form solutions for optimal parameters. However, the deployment position of the tuned mass damper (TMD) was found to degrade the optimal control performance significantly. Therefore, for the convenience of engineers, improved optimal solutions were obtained by considering the actual deployment position of the TMD and the influence of inherent structural damping. The stochastic linearization method was used to evaluate the effect of linear hysteretic damping (HD) with equivalent viscous damping (VD) in the field of random theory. Accordingly, a closed-form expression for the VD ratio was proposed to represent HD. Numerical verifications of a Chinese landmark (Canton Tower) subjected to bi-directional winds were assessed through time history and frequency decomposition analyses. The results verified the effectiveness, correctness, and necessity of the BRVFP-TMD; the improved optimal solutions were also confirmed. Compared with the closed-form solution, which neglects the deployment position of the TMD, and the classic TMD, the improved optimal solutions of the BRVFP-TMD demonstrated superior performance in mitigating both structural displacement and acceleration. The vibration reduction ratios achieved were 44.55% for the displacement at the top of the mast and 46.69% for the acceleration at the top of the main tower. • The constitutive relation of BRVFP-TMD equipped with MDOF structure is provided. • Closed-form solutions for optimal acceleration control of BRVFP-TMD are obtained. • Improved optimal solutions of BRVFP-TMD considering deploy position are acquired. • SLM is verified by MCS to illustrate the connection between VD and HD. • Closed-form expression of equivalent VD ratio to represent HD ratio is obtained. [ABSTRACT FROM AUTHOR]

• A new two-dimensional anionic metal-organic framework (K-Zn-MOF) was synthesized by one-step solvothermal method. • K-Zn-MOF exhibited high adsorption capacity towards Sr2+ (q m = 878.3 mg/g). • K-Zn-MOF exhibited ultrafast kinetics for Sr2+ with 95.39% at an equilibrium time of 60 min. • The adsorption mechanisms include ion exchange and coordination adsorption. Efficient removal of radioactive 90Sr from solutions is of vital importance due to its radioactive nature and high mobility. Herein, a 2D anionic metal-organic framework (MOF) [Me 2 NH 2 ][KZn(pydc) 2 (H 2 O) 2 ]∙H 2 O (K-Zn-MOF; pydc = 2,6-pyridinedicarboxylic acid) was synthesized and characterized. The prepared K-Zn-MOF was in turn applied for the removal of Sr2+ ions and various experimental conditions including contact time, initial concentration, and temperatures were optimized. Experimental findings revealed that the adsorption of Sr2+ on K-Zn-MOF reached equilibrium within 60 min at room temperature with R e = 95.39%. K-Zn-MOF exhibited ultra-high adsorption capacity (878.3 mg g−1), remarkable affinity (K d = 5.8 × 105 mL g−1) in solutions and super-high selectivity in the presence of interfering coexisting ions (Na+, K+, Mg2+, and Ca2+). Mechanistic investigation suggested that free exchangeable [Me 2 NH 2 ]+ ions and strong interactions between uncoordinated oxygens from COO− groups with target ions significantly contributed to the rapid adsorption of Sr2+ ions. A 2-D anionic layer structure containing [Me 2 NH 2 ] + ions by the simple solvothermal reaction were obtained, denoted as K-Zn-MOF. Systematic studies revealed that K-Zn-MOF was an efficient ion exchanger material for the selective capture of Sr2+ ions. [Display omitted] [ABSTRACT FROM AUTHOR]

The impact of wind speed on PV power generation is influenced by the monsoon and the complex topography and environmental factors found in mountainous areas. This complexity can reduce the correlation between PV power and irradiance. To better understand the impact of wind speed, we conducted an analysis in various topographical regions of the Hengduan Mountain in China. Our findings show that high wind speeds can enhance PV utilization, particularly in plateau and hill regions. This is due to the blocking and lifting effect of the north-south oriented mountains on the east-west wind, as well as the channeling effect on the north-south wind. To improve the efficiency of utilizing solar energy, it is important to consider the spatial distribution of wind speed when developing PV. Correlation analysis of multi-factors on a spatial and temporal scale can also offer insight. Furthermore, planning the layout of PV systems with meteorological resources in mind can enhance PV utilization in complex mountainous terrain. [ABSTRACT FROM AUTHOR]

• Pendulum tuned mass damper (PTMD) with geometric nonlinear dampers (GND) is proposed. • Nonlinear behavior of the PTMD with GND characterized by the "unavailable" points. • The stochastic linearization method is adopted to simplify the nonlinear model. • Closed-form solution and optimal design procedure are built for the PTMD with GND. • The optimal design provides significant reduction by the dynamic damping mechanism. In engineering applications, the geometric nonlinear (GN) arrangement of pendulum-tuned mass dampers (PTMDs) may induce the damping force to deviate from its intended state. Therefore, this study extends the scope of the structural control strategy by introducing a pendulum-tuned mass damper considering geometric nonlinear dampers (GND). Specifically, the damper developed in this study, termed PTMD with GND, is an inconspicuous pendulum-type tuned mass damper with different GN settings in the initial state. A nonlinear mathematical model of the PTMD with GND is developed, identifying its significant nonlinear characteristics, particularly the "unavailable" locations. The stochastic linearization method (SLM) is adopted to simplify the nonlinear model using the Kanai-Tajimi modified spectrum. The SLM agrees well with the numerical results obtained using the Monte Carlo simulation method. Furthermore, the control strategy of PTMD with GND is proposed with the consideration of filtered random excitation. Several numerical cases have been conducted to investigate the availability of PTMD with GND and the proposed optimal design strategy under 178 real seismic excitations. The results show that the PTMD with GND is nearly as effective as the ideal transitional TMD in mitigating the seismic response of the primary structure and more effective than the inverted rough linear adjustment. It can be concluded that the proposed optimal design strategy for the PTMDs with GND efficiently suppressed the structural vibration through multiple performance indices and used the nonlinearity of the damping mechanism of the GND to provide a sufficient damping energy dissipation effect adaptively. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • Changes in the key flavor substances were elucidated during broad bean fermentation. • The core microorganisms during the fermentation process were identified. • The pathways and mechanisms for forming the key flavor substances were established. Pixian Douban (PXDB) is a popular Chinese condiment for its distinctive flavor. Broad bean fermentation (Meju) is the most important process in the formation of flavor substances. Key flavors were analyzed qualitatively and quantitatively, and metagenomic technology was applied to study the microbial diversity during broad bean fermentation. In addition, the main metabolic pathways of key flavors were explored. Results indicated that Staphylococcus_gallinarum was the main microorganism in the microbial community, accounting for 39.13%, followed by Lactobacillus_agilis , accounting for 13.76%. Aspergillus_flavus was the fungus with the highest species abundance, accounting for 3.02%. The KEGG Pathway enrichment analysis showed that carbohydrate metabolism and amino acid metabolism were the main metabolic pathways. Glycoside hydrolase and glycosyltransferase genes were the most abundant, accounting for more than 70% of the total number of active enzyme genes. A total of 113 enzymes related to key flavors and 39 microorganisms corresponding to enzymes were annotated. And Staphylococcus_gallinarum, Lactobacillus_agilis, Weissella_confusa, Pediococcus_acidilactici, Staphylococcus_kloosii, Aspergillus_oryzae, and Aspergillus_flavus played a key role in the metabolic pathway. This study reveals the formation mechanism of key flavors in fermented broad bean, it is important for guiding the industrial production of PXDB and improving product quality. [ABSTRACT FROM AUTHOR]

With the increasing market penetration of electric vehicles (EVs), the charging behavior and driving characteristics of EVs have an increasing impact on the operation of power grids and traffic networks. Existing research on EV routing planning and charging navigation strategies mainly focuses on vehicle-road-network interactions, but the vehicle-to-vehicle interaction has rarely been considered, particularly in studying simultaneous charging requests. To investigate the interaction of multiple vehicles in routing planning and charging, a routing optimization of EVs for charging with an event-driven pricing strategy is proposed. The urban area of a city is taken as a case for numerical simulation, which demonstrates that the proposed strategy can not only alleviate the long-time queuing for EV fast charging but also improve the utilization rate of charging infrastructures. Note to Practitioners—This article was inspired by the concerns of difficulties for electric vehicle (EV)’s fast charging and the imbalance of the utilization rate of charging facilities. Existing route optimization and charging navigation research are mainly applicable to static traffic networks, which cannot dynamically adjust driving routes and charging strategies with real-time traffic information. Besides, the mutual impact between vehicles is rarely considered in these works in routing planning. To resolve the shortcomings of existing models, a receding-horizon-based strategy that can be applied to dynamic traffic networks is proposed. In this article, various factors that the user is concerned about within the course of driving are converted into driving costs, through which each road section of traffic networks is assigned the corresponding values. Combined with the graph theory analysis method, the mathematical form of the dynamic traffic network is presented. Then, the article carefully plans and adjusts EV driving routes and charging strategies. Numerical results demonstrate that the proposed method can significantly increase the adoption of EV fast charging while alleviating unreasonable distributions of regional charging demand. [ABSTRACT FROM AUTHOR]

Sterol regulatory element binding protein (SREBP) cleavage-activating protein (SCAP) is a widely expressed membrane glycoprotein that acts as an important modulator of lipid metabolism and inflammatory stress. N-glycosylation of SCAP has been suggested to modulate cancer development, but its role in nonalcoholic steatohepatitis (NASH) is poorly understood. In this study, the N-glycosylation of SCAP was analyzed by using sequential trypsin proteolysis and glycosidase treatment. The liver cell lines expressing wild-type and N-glycosylation sites mutated SCAP were constructed to investigate the N-glycosylation role of SCAP in regulating inflammation and lipid accumulation as well as the underlying mechanisms. The hepatic SCAP protein levels were significantly increased in C57BL/6J mice fed with Western diet and sugar water (WD + SW) and diabetic db/db mice, which exhibited typical liver steatosis and inflammation accompanied with hyperglycemia. In vitro, the enhanced N-glycosylation by high glucose increased the protein stability of SCAP and hence increased its total protein levels, whereas the ablation of N-glycosylation significantly decreased SCAP protein stability and alleviated lipid accumulation and inflammation in hepatic cell lines. Mechanistically, SCAP N-glycosylation increased not only the SREBP-1-mediated acetyl-CoA synthetase 2 (ACSS2) transcription but also the AMPK-mediated S659 phosphorylation of ACCS2 protein, causing the enhanced ACSS2 levels in nucleus and hence increasing the histone H3K27 acetylation (H3K27ac), which is a key epigenetic modification associated with NASH. Modulating ACSS2 expression or its location in the nuclear abolished the effects of SCAP N-glycosylation on H3K27ac and lipid accumulation and inflammation. In conclusion, SCAP N-glycosylation aggravates inflammation and lipid accumulation through enhancing ACSS2-mediated H3K27ac in hepatocytes. NEW & NOTEWORTHY:N-glycosylation of SCAP exacerbates inflammation and lipid accumulation in hepatocytes through ACSS2-mediated H3K27ac. Our data suggest that SCAP N-glycosylation plays a key role in regulating histone H3K27 acetylation and targeting SCAP N-glycosylation may be a new strategy for treating nonalcoholic steatohepatitis (NASH). [ABSTRACT FROM AUTHOR]

Due to the increasing realisation of improving the utility of energy and reducing pollutant emissions, the electric vehicle has been a hot topic in electrical engineering courses. However, it is the scale evolution of electric vehicles that is the basis for investigating their impacts on the power grid. This paper presents the main steps of designing an educational tool based on system dynamic approach to understanding the electric vehicles evolution and arouses their interests in the course named Electric Vehicle and Smart Grid. This tool is a work done by a team of students based on theory and survey, calculating the size of electric vehicles. The effectiveness of this tool is verified by the case studies in this paper, including the scale evolution, analysing the influence factors and stimulating students' interests. In addition, this tool has been used in teaching to demonstrate the scale evolution intuitively, thus achieving better teaching. [ABSTRACT FROM AUTHOR]

The self-calibrating sensor based on Tb/Eu-MOF-6 exhibits visual colorimetric sensing for anthrax biomarker: fluorescent color changes from yellow to red after adding DPA. [Display omitted] Bacillus anthracis is toxic bacterial spore that cause human anthrax infections. Therefore, rapid and sensitive detection of Bacillus anthracis or its main biomarker 2, 6-pyridine dicarboxylic acid (DPA) is of great significance. Herein, a series of lanthanide–organic frameworks (Tb/Eu-MOF - 1 – 6) were synthesized by the solvothermal reactions of 2,2′-bipyridine-6,6′-dicarboxylic acid (H 2 BPDC) with Eu3+ and Tb3+. Among these samples, Tb/Eu-MOF-6 exhibited selective detection of DPA with self-calibrating and colorimetric fluorescence determination. The sensitivity of Tb/Eu-MOF-6 revealed a linear response of ln (I N) = -10.896C DPA + 0.14366 with a limit of detection with 4.51 μM. The emission color of Tb/Eu-MOF-6 observed with the naked eye, turned yellow to red after introducing appropriate concentration of DPA. The energy-transfer behavior between BPDC2- Tb3+, and Eu3+ was systematically studied, which primarily controlled the sensitivity of detection. With the combined merits of self-calibrating, rapid and naked-eye recognition of DPA, Tb/Eu-MOF-6 can be counted as a promising contender for anthrax biomarker detection. [ABSTRACT FROM AUTHOR]

• A multi-objective investment evaluation method is proposed with a dynamic mapping evolution model based on system dynamics. • Four aspects of power system development goal are analyzed with four sub-model, and each sub-model can be evaluated by its normalized weight index. • The proposed evaluation method can adapt the characteristics of low-carbon power system and can give policy support. The energy transition development path towards low carbon power systems requires considered investments for system design. A multi-objective investment evaluation method for power system evolution towards low-carbon is established based on multiple development goals including energy security, ecological protection, economic development and technology advancement. The four aspects are modeled based on system dynamics and provide collaborative quantitative evaluation for power system evaluation. Different evolution paths are simulated and analyzed with different policy scenarios, which verify the effectiveness of the proposed model. The results of several indices show that with strong enough policies, it is expected to achieve the CO 2 peak around 2030. And accelerating the construction of electricity market reform can provide greater investment space. The ecological protection index has the largest weight in the multi-objective investment, requiring power system to deepen the low-carbon transition. [ABSTRACT FROM AUTHOR]

With rapid development of the electric vehicle (EV) industry, charging infrastructures are built fast. However, the unreasonable deployments with increasing EVs contribute to a long queuing time for charging demand of EVs, especially in the peak hours. How to navigate a specific EV to economically satisfy its charging demand, while relieve the traffic burden, is an urgent problem. To address that, a price incentive-based charging navigation strategy for EVs is proposed. Unlike previous charging navigation studies that mainly focus on the EVs-transportation-power systems modeling, it considers the spatial-temporal influence of EVs’ charging decision, especially the simultaneous charging requests. Specifically, the charging navigation framework with the collaborative working mode of EV-charging station-information exchange center-intelligent transportation system is established first. Following this, spatiotemporal distribution of the charging demand is obtained through the origin–destination analysis. After this, an event-driven dynamic queue model is constructed. It contributes to the modeling of the charging strategy, together with the proposed reservation opportunity cost mechanism. Finally, the simulation results indicate that the presented charging navigation strategy can not only reduce the EV's charging cost but also improve the utilization rate of charging facilities, which verify its effectiveness. [ABSTRACT FROM AUTHOR]

An improved explicit estimation algorithm is proposed for reliability estimation of the distribution network. Firstly, hierarchical clustering is used to identify and cluster typical feeders based on the topology structure. Secondly, the explicit formula of reliability index under each typical feeder topology is derived by regression analysis, to establish the model for network reliability estimation. Numerical simulations show the suitability of the proposed method in obtaining accurate reliability index for diversified network topology. [ABSTRACT FROM AUTHOR]

The objectives of this study were to develop and optimize ultrasound-assisted extraction (UAE) for shikonin from Arnebia euchroma using response surface methodology (RSM) and to evaluate the antimicrobial activity of shikonin. The maximum yield of shikonin was 1.26% under the optimal extraction conditions (ultrasound power, 93 W; time, 87 min; temperature, 39°C; and liquid-solid ratio, 11 : 1). Shikonin showed inhibitory activity against standard strains and clinical isolates to varying extents (MICs ranging from 128 to 1024 μg/mL, MBCs ranging from 256 to 2048 μg/mL), and it was more effective for Gram-positive bacteria as indicated by lower MIC and MBC values. Time-kill curves revealed that antibacterial activity of shikonin exhibited a dose-response relationship. In summary, via this study, we identified ultrasound-assisted RSM as the optimal extraction method for shikonin, which is a potential material for the treatment of bacterial infections. [ABSTRACT FROM AUTHOR]

Summary: With the increasing access of distributed generation (DG), the investment decision of distribution network (DN) has become a large‐scale portfolio optimization problem with various reconstruction strategies, which reduces the applicability of the traditional investment decision optimization model. Therefore, aiming at reliability of DN, a novel deep belief networks (DBN)‐based correlation constraint‐integrated investment decision model is proposed in this paper. With the DBN‐based correlation constraint replacing the nonlinear and nonconvex constraints in the traditional model, a new investment decision model is established aiming at maximizing the reliability index and minimizing the total investment cost. In this way, the effects of different reconstruction strategies can be analysed, from which the optimal investment reconstruction plans are identified. Finally, an example of a regional distribution network in a city is provided to verify the rapidity, feasibility, and effectiveness of the investment decision model. [ABSTRACT FROM AUTHOR]

We present new Doppler images of both components of the double-lined binary σ2 CrB, based on the high-resolution spectroscopic data collected during 11 nights in 2015 March–April. The observed spectra form two independent data sets with sufficient phase coverage. We apply the least-squares deconvolution to all observed spectra to obtain high signal-to-noise mean profiles, from which we derive the Doppler images of both components of σ2 CrB simultaneously. The surfaces of both F9 and G0 components are dominated by pronounced polar spots. The F9 component exhibits a weak spot at latitude 30° and its mid-to-low latitudes are relatively featureless. The G0 star shows an extended spot structure at latitude 30°, and its surface spot coverage is larger than that of the F9 star, which suggests a higher level of magnetic activity. With the cross-correlation method, we derive a solar-like surface differential rotation on the G0 star of σ2 CrB for the first time, and the surface shear rate is ΔΩ = 0.180 ± 0.004 rad days−1 and α = ΔΩ/Ωeq = 0.032 ± 0.001. We do not obtain a clear surface shear law for the F9 star due to the lack of mid-to-low latitude features, but detect a systematic longitude shift of high-latitude spots, which indicates a slower rotation with respect to the corotating frame. [ABSTRACT FROM AUTHOR]

We present the first Doppler images of the prototypical active binary star RS Canum Venaticorum, derived from high-resolution spectra observed in 2004, 2016 and 2017, using three different telescopes and observing sites. We apply the least-squares deconvolution technique to all observed spectra to obtain high signal-to-noise line profiles, which are used to derive the surface images of the active K-type component. Our images show a complex spot pattern on the K star, distributed widely in longitude. All star-spots revealed by our Doppler images are located below a latitude of about 70°. In accordance with previous light-curve modelling studies, we find no indication of a polar spot on the K star. Using Doppler images derived from two consecutive rotational cycles, we estimate a surface differential rotation rate of ΔΩ = −0.039 ± 0.003 rad d−1 and α = ΔΩ/Ωeq = −0.030 ± 0.002 for the K star. Given the limited phase coverage during those two rotations, the uncertainty of our differential rotation estimate is presumably higher. [ABSTRACT FROM AUTHOR]

This is a study on the relationship between the protective effect of ginsenoside Rg1 on senescent neural stem cells and Wnt-β/catenin signaling pathway. Background. Recent studies have shown that overactivation of the Wnt/β-catenin signaling pathway is closely related to stem cell senescence. Whether Rg1 delays the senescence of NSCs is related to the regulation of this signaling pathway. Methods. The whole brain of Nestin-GFP transgenic newborn rat was extracted, and NSCs were extracted and cultured to P3 generation. The following indicators were detected: (1) NSC culture identification, (2) the effect of LiCl on the proliferation and survival rate of NSCs, (3) the effect of ginsenoside Rg1 on the proliferation and survival of NSCs, (4) the growth of NSCs in each group observed by an optical microscope, (5) the cell cycle of each group detected by flow cytometry, (6) the proliferative ability of each group detected by BrdU, (7) the fluorescence intensity of Nestin and Sox2 of NSCs in each group observed by a fluorescence microscope, (8) the positive rate of senescence staining analyzed by SA-β-Gal staining, (9) the localization of β-catenin in NSCs observed by laser confocal microscopy, and (10) the changes of the Wnt/β-catenin pathway-related proteins in each group detected by Western blotting. Results. LiCl activates the Wnt/β-catenin pathway and promotes mouse neural stem cell senescence. Ginsenoside Rg1 promotes proliferation of neural stem cells and inhibits Wnt/β-catenin pathway activation. Conclusions. LiCl can activate the Wnt/β-catenin signaling pathway of NSCs, and ginsenoside Rg1 can antagonize the senescence of NSCs caused by activation of the Wnt/β-catenin signaling pathway and delay brain aging. [ABSTRACT FROM AUTHOR]

The distribution of urban electricity load is highly uneven in both space and time, posing significant challenges to the problem of distribution network expansion planning (DNEP). An autonomous topology planning method for distribution network expansion is proposed to address that, driven by a learning-based decoupled optimization approach. The planning problem is decoupled from the impact of distribution network operation and used as reinforcement cost prediction for autonomous planning after the generation of topology schemes. First, a reinforcement model of the original distribution network is built that considers the actual distance calculation method of load nodes. Then an effective method for generating historical operation samples is designed, followed by the development of a learning-based reinforcement cost prediction model for the original distribution network based on operation state learning using XGBoost, which enables the prediction of said costs under different scenarios. Utilizing a distribution network topology generating method driven by the adjustable weight minimum spanning tree (AWMST) algorithm, an autonomous topology expansion planning strategy generation method employing the learning-based decoupled optimization approach is established. The feasibility and superior analysis of the proposed method is verified and analyzed on an actual urban distribution network case with simulation scenarios. The results show that the proposed method is faster and more flexible to deal with the distribution network planning problem brought about by rapid load growth in urban distribution networks. • An autonomous distribution network topology planning method is proposed. • A XGBoost learning-based reinforcement cost prediction model is established. • The topology planning scheme could be obtained by an intelligent decoupled optimization algorithm. [ABSTRACT FROM AUTHOR]

Guiding electric vehicles (EVs) in smart energy communities to participate in demand response can significantly benefit users and the load aggregator. However, when the user's travel plans are uncertain, the EV may end up charging before the planned time, leaving the user with an insufficient power supply. This can occur because the control program chooses to charge the EV during periods of low electricity prices to reduce user costs. To address this issue, a new strategy for charging pricing based on service-quality is proposed to help users deal with the uncertainty of travel plans and promote user participation in demand response. In this paper, the proposed charging pricing of EVs consists of three parts. Firstly, the model of charging packages with different service qualities is designed for users. The differences in charging packages are reflected in the percentage of power supply and price within each time slot. Charging packages provide users with at least a certain amount of power in each time slot, allowing them to better cope with the uncertainty of their travel plans. Secondly, a subscription model for charging packages is built to match the user's travel plans. Finally, the pricing model of the charging package is established, representing the master-slave game between the load aggregator and the user. The model is linearized by the KKT condition. The results show that the proposed strategy helps users cope with the uncertainty of their travel plans, reducing charging cost for users by 16.39% while increasing revenue for the load aggregator by 14.8%. • A novel charging package for electric vehicles based on service-quality is proposed. • A pricing model is established as a master-slave game formulation. • The uncertainty of the EV users' travel plan is effectively handled. • The user 's charging cost is reduced by 16.39% in the case. • The revenue of the load aggregator is increased by 14.8% in the case. [ABSTRACT FROM AUTHOR]

• Bi-directional rail variable friction pendulum-tuned mass damper (BRVFP-TMD) was proposed. • Bi-directional traditional friction pendulum systems were improved by geometric nonlinearity. • The impact of bi-direction motion to the bi-directional friction pendulum systems was revealed. • Closed-form solutions for the optimal parameters of BRVFP-TMD were obtained. • Bi-directional loadings were conducted to illustrate the superiority of BRVFP-TMD. The shape of hysteretic loops for a friction pendulum system transforms when excited by bi-directional motion, which exhibits unexpected dynamic behavior compared with unidirectional motion. Therefore, a novel bidirectional rail variable friction pendulum-tuned mass damper (BRVFP-TMD) with two independent rails that satisfied the purpose of bidirectional structural response control and provided a full bidirectional friction force was proposed. The variable friction arrangement was applied to the rails so that the BRVFP-TMD could be accomplished with a linear hysteretic damping property that is contributed by the displacement-dependent variable friction force. Using unidirectional harmonic excitations with attack angle as bi-directional loading, illustrations were created to investigate the control effect of traditional pendulum friction TMDs with a spherical sliding surface. This demonstrated the collapse of hysteretic loops of traditional pendulum friction TMDs and superiority of BRVFP-TMD in terms of mechanism. For the BRVFP-TMD with a lightly damped structure, the optimizations of the fixed-point theory were accessed to obtain the closed-form solutions of the optimal parameters of the BRVFP-TMD. Numerical verifications based on bidirectional motions were conducted to evaluate the performance of the BRVFP-TMD. The bidirectional earthquake results indicated stable and excellent performance of the BRVFP-TMD in terms of either frequency response reduction or friction energy dissipation efficiency. Meanwhile, bidirectional wind-induced vibrations confirmed the correctness of the optimization and the stable robustness of the optimized BRVFP-TMD. [ABSTRACT FROM AUTHOR]

Metal-organic frameworks (MOFs) derived porous carbons are promising electrode materials in electrochemical energy conversion and storage systems. However, the typical synthetic route of MOFs involving high temperature, organic solvent, massive energy consuming, and laboratory-scale production, hinders the realistic applications of MOFs serving as sacrificial templates for porous carbon. Herein, we demonstrate that highly crystalline MIL-100 (Fe) nanoparticles (MIL: Materials of Institute Lavoisier) can be synthesized in large scale with low cost under mild and green conditions. High-temperature pyrolysis of MIL-100(Fe) under argon atmosphere results in hollow carbon polyhedra (HCPs) featuring high degree of graphitization and hierarchical pore structures. The obtained HCPs are excellent electrode materials for electric double-layer capacitors (EDLCs), and show a specific capacitance of 214 F g−1 at current density 50 mA g−1. Moreover, the HCP-based supercapacitors can endure more than 5000 cycles without significant degradation of capacitance. The unique structure of HCPs, including hollow polyhedral shape, hierarchical micro/mesopore structures, and ultrathin layer of highly graphitized carbon shells, endows the superior performance of HCPs based EDLCs with specific capacitance and high rate capability. Image 1 • Room temperature synthesis of MIL-100(Fe) nanocrystals in a low cost and green fashion. • Pyrolysis of MIL-100(Fe) resulted in hollow carbon polyhedra (HCPs). • HCPs show high degree of graphitization and hierarchical pore structures. • HCPs-based SCs exhibit high specific capacitances and excellent cycling stability. [ABSTRACT FROM AUTHOR]

With the development of distributed energy resources (DERs) and the increasing flexibility in active distribution networks (ADNs), the economic operation of ADN coordinating both generation and demand sides is required to be studied. In this paper, considering the electricity price response of DER, a coordinated operation strategy for ADN is presented based on a bi-level agent framework. The DER agent makes their own response based on the technical operability and economic consideration, while the ADN agent will finally coordinate each participant by using the interactive benefit prioritization (IBP) principle. The simulation results indicate that the proposed strategy cannot only reduce the power imbalance but also improve the economic operation of ADN. Moreover, consumption of renewable energy is ameliorated as well. [ABSTRACT FROM AUTHOR]

Poor swimming performance and low hypoxia tolerance have been suggested as the main reasons for the dramatic decrease in the wild population of Chinese sucker. The present study aimed to investigate the potential for exercise training to enhance swimming performance and hypoxia tolerance in this fish species targeted for stocking enhancement. Fish were exercise trained (force to swim against a flow) once daily, twice daily or not exercise trained for 20 d and then detrained for 10 d (a period of nontraining). Training showed no significant effect on anaerobic swimming performance.. The fish from both training groups showed lower hypoxia tolerance and a lower survival rate under predation. Thus, the present study suggested thatexercise training showed little effect or even a negative effect on physiological function in Chinese sucker, and the forced training might not be the proper protocol to apply for improving the stocking enhancement of Chinese sucker.. [ABSTRACT FROM AUTHOR]

Optimal planning of distributed generation (DG) in distribution networks is key for improving energy utilization efficiency and system operation benefits. Considering the uncertainties and temporal correlations of DG output and load demand, a multi-scenario chance-constrained economic model for DG planning is established in this paper. The model considers the comprehensive benefits of environmental, reliability and other aspects, as well as the active curtailment management of DGs. Thereafter, the model is extended to the coordinated planning of both DGs and tie lines, which is formulated as a multi-objective model. An improved genetic algorithm based solving strategy integrated with game multi-objective decision method is proposed. The feasibility and effectiveness of the proposed models are verified on the IEEE 33-bus distribution system. The impacts of natural resource distribution, confidence level, unit environmental cost and other parameters are investigated as well. The case studies also prove the integration of complementary DG generation could help improve the maximum capacity of DG and indicate the environmental benefit is the vital incentive to introduce DG into the distribution network. [ABSTRACT FROM AUTHOR]

This paper summarizes determinants and mechanisms of house price movements in general situations and special characteristics in China. On the basis of recognizing the periods during which house price changes differently and classifying cities scientifically, the paper examines the factors driving house price in 35 Chinese cities during different periods from 2001 to 2015 using the panel threshold regression model. The results show that the main determinants of house price in Chinese cities have changed after 2009. Availability of financing, land finance and land restriction policy has a sizable impact on house price, meanwhile the investment role of stock market revealed. As to house prices in different kinds of cities that in category 1 and 2 consisting of first-tier cities and several popular second-tier cities are driven by land finance of local governments, land supply and availability of financing after 2009. Moreover, household income has a significant influence on house price of cities in category 3, which are relatively less developed. [ABSTRACT FROM AUTHOR]

The increasing integration of distributed resources, such as distributed generations (DGs), energy storage systems (ESSs), and flexible loads (FLs), has ushered in a new era for the active distribution system (ADS), characterized by more reliable, economical, and low-carbon. Nonetheless, with the increase in number and variety, how to realize self-consistent and self-optimal operation among these distributed resources has become major challenge for ADS. In this paper, a multi-agent deep reinforcement learning (MADRL) based algorithm with strategic goals of the real-time optimal scheduling of ADS is proposed, in which the uncertainty of renewable generations (RDGs), loads and electricity price are considered. The control variables contain the active and reactive power of dispatchable thermal DGs, the reactive power of photovoltaic and wind turbine DGs, the exchange power of ESSs, and the demand response (DR) of FLs. Besides, the region ownership of distributed resources is considered in our MADRL framework to resolve the partitioned optimization problem in large-scale ADS. Finally, the effectiveness and superiority of the proposed algorithm are demonstrated on the 33-node and 152-node active distribution system, including the terms of cost-effective and uncertainty adaptation. • A model-free optimal scheduling method for active distribution system is proposed. • Only the local measurements are required for agents in the Dec-POMDP formulation. • The designed reward function improves the strategy quality and learning efficiency. [ABSTRACT FROM AUTHOR]

Scale evolution pattern recognition of plug-in electric vehicles (PEVs) and charging demand modeling are essential for various involved sectors to promote PEV proliferation and integration into power systems. Considering that the market penetration development of PEVs will drive the evolution of charging demand, an integrated dynamic method based on an agent-based modeling technology is proposed in this paper by combining scale evolution model with charging demand model to jointly detect the possible PEVs evolution patterns and long-term charging demand profiles. Heterogeneous consumers presenting different preferences in making vehicle purchase decisions and the interactions with other consumers via social dynamics are taken into consideration in the scale evolution model. After obtain the scale of PEVs by aggregating individual consumer agents purchase behavior, the driving patterns, charging behavior habits, and charging strategies are systematically incorporated into the charging demand model. Case studies demonstrate the feasibility and effectiveness of the proposed methodology by taking an urban area as an example. Furthermore, the factors that affect the market evolution of PEVs and the charging demand are also simulated and analyzed. [ABSTRACT FROM AUTHOR]

Background: Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been proposed for the side effect predictions. The assumption that similar drugs may induce same side effects is usually employed for modeling, and how to calculate the drug-drug similarity is critical in the side effect predictions. Results: In this paper, we present a novel measure of drug-drug similarity named "linear neighborhood similarity", which is calculated in a drug feature space by exploring linear neighborhood relationship. Then, we transfer the similarity from the feature space into the side effect space, and predict drug side effects by propagating known side effect information through a similarity-based graph. Under a unified frame based on the linear neighborhood similarity, we propose method "LNSM" and its extension "LNSM-SMI" to predict side effects of new drugs, and propose the method "LNSM-MSE" to predict unobserved side effect of approved drugs. Conclusions: We evaluate the performances of LNSM and LNSM-SMI in predicting side effects of new drugs, and evaluate the performances of LNSM-MSE in predicting missing side effects of approved drugs. The results demonstrate that the linear neighborhood similarity can improve the performances of side effect prediction, and the linear neighborhood similarity-based methods can outperform existing side effect prediction methods. More importantly, the proposed methods can predict side effects of new drugs as well as unobserved side effects of approved drugs under a unified frame. [ABSTRACT FROM AUTHOR]

This letter presents a simple temporal-scenario-based economic criterion for planning distributed renewable generation (DRG) in the zone-type distribution network. The advantage of the proposed criterion is that its formulation does not rely on power flow calculations and optimization iterations, thus can quickly indicate the economic feasibility of the DRG unit. A case study has verified its effectiveness, and also indicates that the proposed criterion could calculate the economic attractiveness or resistance for renewable energy investors in this zone. [ABSTRACT FROM AUTHOR]