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The type of feedstock and pyrolysis temperature are the main reasons affecting the properties of the resulting biochar. Therefore, this paper investigates the effects of different feedstocks (peanut shell, corn straw and soybean straw) and different pyrolysis temperatures (300, 450 and 600 ℃) on the structural morphology and elemental composition of the resulting biochar. The optimum pyrolysis temperature of 600 ℃ was selected based on the comparison of the adsorption of NFX (norfloxacin) by the biochar prepared at different temperatures. Characterization of biochar materials using x-ray diffractometer, fourier transform infrared spectrometer and scanning electron microscope to study the changes in the physicochemical and structural properties of biochar. The results showed that the pH, surface area and ash content of biochar are increased with increasing temperature. The results of isothermal adsorption and adsorption kinetics experiments showed that the adsorption processes of the three biochar species on NFX were consistent with the Langmuir model and Pseudo-second order kinetic model. The adsorption process occurred in the surface layer of the biochar and was dominated by chemisorption. The inhibition of the adsorption of NFX was more obvious with the higher valence state of cations and the higher ion concentration. The adsorption mechanism of biochar on NFX includes pore filling, hydrogen bonding and electrostatic interactions.

The enhanced NLO properties of tetra (C60)–LaPc are mainly attributed to a combination of different NLO performances of C60 and LaPc, but also to the contribution of the PET/ET process in a D–π–A molecular system.

The construction of molecules with effective photoinduced intramolecular electron transfer (PET) and energy transfer (ET) processes is critical for the enhancement of the nonlinear optical (NLO) properties. A novel D-π-A type compound, namely tetra (C

The ocean occupies 70% of the world's surface area, and extreme changes in sea level can have an even greater impact on humans. Therefore, it is necessary to make an accurate advance prediction of extreme sea level. In this paper, a model with robustness, high accuracy and universal applicability has been constructed based on Nonlinear Auto-Regressive Exogenous (NARX) Neural Network. The data-set collected from several observation stations are selected as the input factors. Moreover, a neuron pruning strategy based on sensitivity analysis is also introduced. Because of this strategy, the model structure can be adjusted accordingly. Meanwhile, a modular prediction method is introduced based on the tide harmonic analysis data so as to make the model prediction results more accurate. At last, a hybrid extreme sea level prediction model, Pruned Modular (PM)-NARX, is constructed. In this paper, the model is trained by using historical data and used for extreme sea level prediction along the southern America in 2020. The simulations on MATLAB show that the correlation between the predicted data and the observed data is stable above 0.99 at 12h in advance. The prediction speed, accuracy, and stability are higher than those of conventional models. In addition, two sets of follow-up tests show that the prediction accuracy of the model can still maintain a high level. It can even be applied to other time-series prediction problems beyond extreme sea level prediction as well.

ACS applied materials & interfaces 14(37), 42531 - 42540 (2022). doi:10.1021/acsami.2c12590, In energy storage and transportation systems, polymer dielectrics are widely applied in smart grids, electric vehicles, and power conditioning owing to their incomparable power density and high reliability. However, the dielectric constant (ε) and breakdown strength (Eb) normally cannot be increased simultaneously, which results in insufficient discharged energy density especially at high temperatures. In this work, enhanced Eb and high energy density are archived in multilayer polymer nanocomposites by introducing cross-linked dielectric transition layers. Specifically, the sandwiched composite achieves a huge discharge energy density of 4.64 J cm$^{–3}$ with a charged–discharged efficiency of 84% at 150 °C and 500 MV m$^{–1}$. The formation of cross-linked dielectric transition layers between layers of the multilayer nanocomposite could effectively restrain the growth of the electrical tree and greatly increase the Eb. This work presents a strategy for designing high-performance multilayered dielectric polymer nanocomposites by introducing cross-linked dielectric transition layers to reduce the loss from interlayer interfaces., Published by Soc., Washington, DC

The northern Gulf of Mexico coast is affected by the North Atlantic hurricane season, which brings serious economic losses to the southern U.S. every year; therefore, it is necessary to make an accurate advance prediction of storm surge level. In this paper, a prediction model has been constructed based on Nonlinear Auto-Regressive Exogenous (NARX) Neural Network. Five types of data are selected as the input factors of the model. A neuron pruning strategy based on sensitivity analysis is introduced. Moreover, a modular prediction method is introduced based on the tide harmonic analysis so as to make the prediction results more accurate. At last, a complete storm surge level prediction model, Pruned Modular (PM)-NARX, is constructed. In this paper, the model is trained by using historical data and used for storm surge level prediction along the northern Gulf of Mexico coast in 2020. The simulation test results show that the correlation coefficient is stable above 0.99 at 12 h in advance within one minute. The prediction speed, accuracy, and stability are higher than those of conventional models. The above can prove that the PM-NARX can effectively provide early warning before the storm surge to avoid property damage and human casualties.

The infinite projected entangled simplex state (iPESS), a type of tensor network (TN) state, has been used successfully for simulating and characterizing {\it non-chiral} spin liquids on the kagome lattice. Here, we demonstrate that iPESS also provides a faithful representation of a {\it chiral} spin liquid (CSL) on the same lattice, namely the ground state of the spin-$1/2$ kagome Heisenberg antiferromagnet with a scalar chirality. By classifying local tensors according to SU$(2)$ and point group symmetries, we construct a chiral ansatz breaking reflection $P$ and time reversal $T$ symmetries while preserving $PT$. The variational TN states are shown to host, for bond dimension $D\ge 8$, a chiral gapless entanglement spectrum following SU$(2)_1$ conformal field theory. The correlation function shows a small weight long-range tail complying with the prediction of the TN bulk-edge correspondence. %{\color{red}With more constraints included, the chiral ansatz is reduced to a non-chiral one which preserves full point group symmetries due to an emergent {\it tensor conservation law} and is of relevance to the ground state at the Heisenberg point. Lastly, by simulations in the complete ansatz family we discuss the transition from the non-chiral spin liquid to the CSL induced by the scalar chirality term.} We identify a non-chiral manifold spanned by only a subset of symmetric tensors where a new emergent {\it tensor conservation law} is realized. This allows us to both probe the stability of the non-chiral spin liquid and discuss its transition to CSL induced by a scalar chirality term.

Quenching a quantum system involves three basic ingredients: the initial phase, the postquench target phase, and quantum dynamics, which may carry the information of the former two. Here we propose a dynamical theory, based on an interaction quench, to characterize both the equilibrium symmetry-breaking order and topological phases by nonequilibrium correlated quantum dynamics. We illustrate the theory with the Haldane-Hubbard model, which is quenched from an initial correlated magnetic phase to a topologically nontrivial regime. We show that the quench dynamics exhibit profound universal behaviors on the so-called band-inversion surfaces (BISs), from which both the topological phase in the weakly interacting regime and the correlated magnetic phase in the strongly interacting regime can be extracted. In particular, the topology is characterized by dynamical topological patterns emerging on BISs, which are robust against interaction-induced dephasing and heating; the symmetry-breaking order can be read out from a universal dynamical scaling behavior, which is valid beyond the mean-field theory. This work uncovers the first paradigm of nonequilibrium characterization of equilibrium symmetry-breaking and topological phases.

The critical phases, being delocalized but non-ergodic, are fundamental phases which are different from both the many-body localization and ergodic extended quantum phases, and have so far not been realized in experiment. Here we propose to realize such critical phases with and without interaction based on a topological optical Raman lattice scheme, which possesses one-dimensional spin-orbit coupling and an incommensurate Zeeman potential. We demonstrate the existence of both the noninteracting and many-body critical phases, which can coexist with the topological phase, and show that the critical-localization transition coincides with the topological phase boundary in noninteracting regime. The dynamical detection of the critical phases is proposed and studied in detail. Finally, we demonstrate how the proposed critical phases can be achieved based on the current cold atom experiments. This work paves the way to observe the novel critical phases., Comment: 5 pages (4 figures) + Supplementary Material (6 figures). Discussions are updated

Web service classification has become an urgent demand on service-oriented applications. Most existing classification algorithms mainly rely on the original service descriptions. That leads to low classification accuracy, since it cannot fully reflect the semantic feature specific to a service category. To solve the issue, this article proposes a novel approach for web service classification, including service topic feature extraction, service functionality augmentation, and service classification model learning. The characteristic is that the original service descriptions can be semantically augmented, which is fed to deriving a service classifier via labeled probabilistic topic model. A benefit from this approach is that it can be applied to an online service management platform, where it assists service providers to facilitate the registration process. Extensive experiments have been conducted on a large-scale real-world data set crawled from ProgrammableWeb. The results demonstrate that it outperforms state-of-the-art methods in terms of service classification accuracy and convergence speed.

A minimal Weyl semimetal Many compounds have now been identified as Weyl semimetals, materials with an unusual electronic band structure characterized by the so-called Weyl points. Weyl points always appear in pairs, but the solid-state materials studied so far have at least four. Wang et al. engineered a Weyl semimetallic state with the minimum number of Weyl points (two) in a gas of ultracold atoms trapped in an optical lattice (see the Perspective by Goldman and Yefsah). To do that, the researchers had to create three-dimensional spin-orbit coupling in this system. The relative simplicity of the resulting band structure will make it easier to observe the unusual effects associated with this state. Science , this issue p. 271 ; see also p. 234

Colistin (polymyxin E) is an effective antibiotic for the treatment of most multidrug-resistant Gram-negative bacteria. However, some bacteria, including bacterial spp. belonging to the Enterobacteriaceae family, have an acquired resistance against polymyxins, which is attributed to they possess plasmid-carried resistance genes (mcr-1 and its variants). So, there is an urgent need to develop new therapeutic strategies to target broad spectrum resistant spp. from Enterobacteriaceae family in response to the loss of the protective barrier of last-line antibiotics. Here, we report the adjuvant capacity of nordihydroguaiaretic acid (NDGA) for restoring the antibacterial activity of colistin against MCR-1-positive E. coli ZJ487 in vivo/in vitro.A checkerboard assay, time-killing analysis, isobolograms, growth curves and inducible resistance test showed the effect of NDGA combined with colistin in vitro. TLC was used to detect the inhibitory effect of NDGA on MCR-1. Colony determination and hematoxylin and eosin (HE) staining were used to assess the synergistic effect of NDGA and colistin in mice.Our results showed that NDGA in combination with colistin showed a synergistic bactericidal action without inducing resistance. NDGA directly inhibited MCR-1 activity and resulted in measurable injury to the bacterial cell membrane to recover the antibacterial effect of colistin. Most importantly, NDGA in combination with colistin exhibited an in vivo synergistic effect in murine peritonitis infection models, as evidenced by the survival rate of MCR-1-positive E. coli ZJ487-infected mice which increased from 6.67 to 50.0%.Our study demonstrated that NDGA effectively rescues the efficiency of colistin against MCR-positive E. coli ZJ487 by simultaneously inhibiting both, the MCR activity and the injury to the cell membrane of bacteria.

Topological phase of matter is now a mainstream of research in condensed matter physics, of which the classification, synthesis, and detection of topological states have brought excitements over the recent decade while remain incomplete with ongoing challenges in both theory and experiment. Here we propose to establish a universal dynamical characterization of the topological quantum phases classified by integers, and further propose the high-precision dynamical schemes to detect such states. The framework of {the dynamical classification theory} consists of basic theorems. First, we uncover that classifying a $d$-dimensional ($d$D) gapped topological phase {of generic multibands} can reduce to a ($d-1$)D invariant defined on so-called band inversion surfaces (BISs), rendering a {\it bulk-surface duality} which simplifies the topological characterization. Further, we show in quenching across phase boundary the (pseudo)spin dynamics to exhibit unique topological patterns on BISs, which are attributed to the post-quench bulk topology and manifest a {\it dynamical bulk-surface correspondence}. For this the topological phase is classified by a dynamical topological invariant measured from dynamical spin-texture field on the BISs. Applications to quenching experiments on feasible models are proposed and studied, demonstrating the new experimental strategies to detect topological phases with high feasibility. This work opens a broad new direction to classify and detect topological phases by quantum dynamics., 14+pages, 8 figures. Updates are made according to referee reports

Physical exercise is an efficient therapeutical tool in the management of insulin resistance (IR) and related metabolic diseases. Leptin, the well-known obesity hormone and the absence of which leads to IR, showed controversial effects on IR as research continues. Thus, in this study, a detailed investigation of the effect of leptin on exercise-mediated improvement of insulin sensitivity and its underlying mechanism was carried out. Using a rat model of chronic or acute swimming exercise training, we found that serum leptin increased 1 h after either acute exercise or the last session of chronic exercise, when impaired insulin action was observed in previous reports. However, chronic exercise reducd basal serum leptin levels and promoted insulin sensitivity compared with sedentary controls or rats subjected to one bout of aerobic exercise. Our animal results indicated the potential linkage between leptin and insulin sensitivity, which is further investigated in the skeletal muscle L6 cells. Leptin treatment in L6 cells promoted the basal levels of insulin signaling as well as glucose uptake, while blocking JAK2 signaling with either pharmacological intervention (JAK2 inhibitor AG490) or genetic manipulation (siRNA knockdown) decreased the basal levels of insulin signaling. Furthermore, leptin treatment inhibited insulin-stimulated insulin signaling and glucose uptake, while blocking JAK2 signaling restored leptin-attenuated insulin sensitivity. Taken together, our results demonstrated that reduced serum leptin, at least in part, contributes to exercise-mediated improvement of insulin sensitivity, indicating JAK2 as a potent therapeutical target of insulin resistance.

We examine the Chern Kondo insulator proposed in a square optical lattice with staggered flux induced by $s$-$p$ orbital hybridization by revisiting its realization and taking into account the magnetic effects for the Kondo phases. The Ruderman-Kittel-Kasuya-Yoshida interaction is analyzed at the weak $s$-$p$ hybridization regime, with the anisotropic magnetic effects being discussed. Furthermore, the paramagnetic and magnetic phases coexisting with Kondo couplings are systematically investigated through the slave-boson theory, for which the rich phases are obtained, including the antiferromagnetic, collinear antiferromagnetic Kondo insulator, and Kondo metal phases. The magnetic orders are shown to enhance the effective Kondo hybridization compared with the case without taking into account magnetic effects, and exhibit different influences on the bulk topology. In particular, the antiferromagnetic order always enhances the topological phase by increasing bulk gap of the Chern Kondo phases. The results show the rich topological and magnetic effects obtained in the present Chern Kondo lattice model. We also investigate how to identify the topology and strong correlation effects through measuring the Hall conductance and double occupancy, which are achievable in ultracold atom experiments., Comment: 22 pages, 10 figures; The title is corrected! (OMG!)

Observation of topological phases beyond two-dimension (2D) has been an open challenge for ultracold atoms. Here, we realize for the first time a 3D spin-orbit coupled nodal-line semimetal in an optical lattice and observe the bulk line nodes with ultracold fermions. The realized topological semimetal exhibits an emergent magnetic group symmetry. This allows to detect the nodal lines by effectively reconstructing the 3D topological band from a series of measurements of integrated spin textures, which precisely render spin textures on the parameter-tuned magnetic-group-symmetric planes. The detection technique can be generally applied to explore 3D topological states of similar symmetries. Furthermore, we observe the band inversion lines from topological quench dynamics, which are bulk counterparts of Fermi arc states and connect the Dirac points, reconfirming the realized topological band. Our results demonstrate the first approach to effectively observe 3D band topology, and open the way to probe exotic topological physics for ultracold atoms in high dimensions., 6 pages, 4 figures, supplementary information

QoS-aware Web service composition has recently become one of the most challenging research issues. Although much work has been investigated to solve the problem, they mainly focus on certain QoS of Web services, while QoS with uncertainty exposes the most important characteristic in a real and highly dynamic environment on the Internet. In this paper, with the consideration of uncertain service QoS, we model the issue of Web service composition with QoS uncertainty that is translated into a multi-objective optimization problem via uncertain interval number, which can be solved by our proposed approach via an non-deterministic multi-objective evolutionary algorithm using the strategy of decomposition. Large-scale empirical experiments have been conducted on our simulated datasets. The experimental results demonstrate that our proposed approach can effectively and efficiently find an optimum composite service solution set with satisfactory convergence.

Vacuum technology is extensively used in space science, nuclear energy, surface science, materials science, electric vacuum industry, microelectronics, semiconductor, metallurgy, and so on. More and more fields need ultra high vacuum (UHV) or extreme high vacuum (XHV) for scientific research and production. Both the rigorous vacuum processing technics and highly developed sophisticated vacuum technology are the necessities for the acquisition and conservation of UHV or XHV ambience. In this paper, a vacuum decline was analyzed and the UHV system was recovered. Using the residual gas analyzer to measure the partial pressure of residual gas and identify the type of gas, the outgassing source was found out by comparing the measure results. The UHV system was recovered back to 10 -9 Pa through treatment. The residual gas analyzing method can effectively identify the type of gas about outgassing, narrow the scope of outgassing subassembly, shorten the vacuum system recovery time, and improve work efficiency. The method of determining the outgassing source by residual gas analyzer can be applied in the fields of UHV and XHV, and it has a certain reference significance for further improving the system vacuum degree.