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Low-cost and low-barrier antibiotic stewardship strategies are urgently needed to deal with the widespread problem of antibiotic resistance. Social norm feedback could be a promising strategy. In this mixed-methods systematic review (PROSPERO: CRD42022361039), we aimed to identify the key behaviour change techniques used in social norm feedback for antibiotic stewardship and assess their effectiveness in reducing antibiotic prescribing. We searched PubMed, Embase, Web of Science, and Scopus for peer-reviewed studies published between Jan 1, 2000, and Jan 20, 2022. 3547 studies were screened, of which 23 studies reporting the effects of social norm feedback interventions on antibiotic prescribing met the inclusion criteria. 19 behaviour change techniques were tested in the included studies. The meta-analyses showed that social norm feedback is an effective strategy for reducing antibiotic prescribing, with an overall rate difference of 4% (p0·0001). The behaviour change technique with the highest effective ratio (ER=13) was information about health consequences, followed by instruction on how to perform the behaviour (ER=9) and adding objects to the environment (ER=9). Social norm feedback is a promising strategy to reduce antibiotic prescribing, and can be incorporated into the clinical decision-making support system.

Whether the exact amount of training data is enough for a specific task is an important question in machine learning, since it is always very expensive to label many data while insufficient data lead to underfitting. In this paper, the topic that what is the least amount of training data for a model is discussed from the perspective of sampling theorem. If the target function of supervised learning is taken as a multi-dimensional signal and the labeled data as samples, the training process can be regarded as the process of signal recovery. The main result is that the least amount of training data for a bandlimited task signal corresponds to a sampling rate which is larger than the Nyquist rate. Some numerical experiments are carried out to show the comparison between the learning process and the signal recovery, which demonstrates our result. Based on the equivalence between supervised learning and signal recovery, some spectral methods can be used to reveal underlying mechanisms of various supervised learning models, especially those “black-box” neural networks.

The radiation shielding simulation model of coated fabric (flexible composite) was established for the first time by SuperMC nuclear simulation software to help solve the problems of small volume, complex structure, and difficult design of flexible shielding materials, and the γ-ray shielding performance was calculated. Bismuth/polyurethane coated fabric was prepared by a coating method, and its scanning electron microscope, γ-ray shielding performance and mechanical properties were tested. The results show that the simulation accuracy was improved due to the one-to-one correspondence between the structural parameters and performance parameters of the simulation model and the actual samples. The simulation value was in good agreement with the measured value. The shielding performance and mechanical properties of fabric composites were improved after coating. Increasing the content of bismuth and coating thickness can improve the shielding performance of the coated fabric. However, when the content of bismuth was too large, or the coating was too thick, the mechanical properties were relatively decreased. The deposition of ray energy in the material was analyzed by the visual analysis method, and the influence mechanism of process parameters on shielding performance was further revealed, which provided a new theoretical reference for the design of flexible shielding materials. A shielding material design and performance prediction method based on SuperMC is proposed, which can be used for personalized customization design and performance prediction and evaluation before use. It has practical guiding significance for producing and manufacturing flexible fabric shielding materials for protective clothing and equipment.

Constipation commonly occurs during childhood, and more than 95% of cases are classified as functional constipation. If not effectively treated, 20% of patients with childhood constipation can continue to exhibit symptoms into adulthood, which seriously affects their mental health and quality of life. The main feature of acupuncture or acupoint stimulation, a special branch of traditional Chinese medicine, is the selection of different acupoints for different diseases, and many worthy guidelines have been established for matching acupoints. The back-shu and front-mu point combination adheres to an important acupoint compatibility law that has been used since its proposal 2,500 years ago but has not yet been verified by the modern evidence-based experiments. This study focused on the back-shu and front-mu point combination using the Dachangshu (BL25) and Tianshu (ST25) points as examples to explore possible research methods for network acupoint-based stimulation based on existing evidence and to elucidate the mechanisms induced by BL25 and ST25 in the treatment of functional constipation in children (FCC). The study found that BL25 and ST25 have 20 common targets, namely, AQP8, DRD2, VIP, TAC1, IL6R, TNF, FOS, KIT, CHAT, HTR3A, GAS8, SOD3, TRPV1, MPO, CALCA, IL1B, P2RX7, NPY2R, IL10RA, and TPH1, and these targets may provide a strategy for the combined usage of BL25 and ST25. In addition, BL25 and ST25 can affect FCC treatment through inflammation-relatedTh17-cell differentiation, the NF-kappa B signaling pathway, and the Toll-like receptor signaling pathway. Adipocytokines or leptin may also comprise the mechanism through which BL25 and ST25 regulate FCC. In addition, BL25 and ST25 regulate FCC through 13 core targets, namely, NFKBIA, RELA, TNF, IKBKB, IRAK1, TLR4, MYD88, TNFRSF1A, IL1R1, TLR2, IL1B, TRAF6, and TNFRSF1B. In short, this study provides new ideas and methods for studying the mechanism of acupuncture points.

Self-assembly of colloidal particles enables the versatile fabrication of highly ordered structures and materials for optical, sensing, and other applications. Nevertheless, many traditional assembly processes are inefficient, because there exists an inevitable contradiction between time efficiency and crystalline quality. In this work, we introduce an ultrafast, robust, and scalable approach of imbibition-induced assembly. We assume that the instantaneous solvent imbibition induced by the nanoporous media could direct ultrafast self-assembly of colloidal particles into ordered structures.Self-assembly of colloidal particles from a droplet on a nanoporous substrate was firstly observed and investigated. A phase diagram of the thickness of the colloidal crystal as a function of the printing speed and the particle volume fraction was presented through systematic experiments.The nanoporous substrate can induce strong capillary flow that will directthe rapid self-assemblyof particles intocolloidalcrystals. The imbibition-induced assembly was spatially and temporally combined with the meniscus-guided printing approach, and the printing speed can be improved by two orders of magnitude than the traditional evaporative assembly methods. We finally demonstrate an effective and ultrafast approach for assembling colloidal particles into photonic crystals with controllable sizes and shapes on the macroscale.

The inverse design method of aerodynamic configuration is hard to give a reasonable pressure distribution, and strongly rely on experience of designers. The method has been difficult to adapt to the needs of modern aircraft design. Aiming at the shortcoming of the method, an efficient and robust aerodynamic configuration inverse design method is developed, employing knowledge of machine learning methods and optimization methods. The present method establishes the mapping between the high dimensional data obtained from aerodynamic shape and pressure distribution and the variables in the latent space. Then, the global optimization is carried out in the latent space by using the genetic algorithm. The optimum pressure distribution and the corresponding shape can be obtained. Through the the GTM model with high precision, there is not necessary for the flow solver in the whole iterative process, thus the design efficiency can be enhanced. Besides, by taking the advantage of optimization method, the target pressure distribution can be given in a very flexible way, and does not need to be physically meaningful. This feature can reduce reliance on the design experience. Airfoils in low speed and transonic flow and a three-dimensional laminar nacelle design cases are carried out. It is shown that the method robustly and efficiently converges to the target pressure, and has good engineering application potential.

Aiming at poor noise reduction performance of light and thin fiber aggregate materials, the polyurethane/ferroferric oxide/activated carbon fiber felt coated flexible composite materials were prepared by coating composite method. The effects of composite structure, ferroferric oxide particle content (10–25%), and coating thickness (0.25–1 mm) on the composites' sound absorption and sound insulation properties were systematically studied. The results show that with the increase of coating thickness and ferroferric oxide particle content, the sound absorption curve of the composite obviously moves to low frequency, and the resonance frequency decreases. When the particle content increased from 0% to 20%, the resonance frequency shifted 967 Hz. When the ferroferric oxide content is 25%, the maximum sound absorption coefficient and maximum transmission loss of the composite are 3.5 times and 25 times of that of the fiber felt, respectively. When the polyurethane/ferroferric oxide film thickness is only 0.1 mm, the maximum sound absorption coefficient and the average sound absorption coefficient of the composite are 3.5 times and 2.3 times of those of activated carbon fiber felt, respectively. Compared with single fiber felt, the composite material has better sound absorption, sound insulation, and mechanical properties while maintaining the thin and soft characteristics of the fiber felt.

Background Climate warming not only affects humans, megafauna and other flora but also the world’s microbial organisms. However, the relationship between ambient temperature and antimicrobial resistance (AMR) of important clinical bacteria is still unclear; therefore, we explored the association between ambient temperature and AMR in China.Methods Six bacteria-antibacterial combination, identified by the World Health Organization as high priority, were collected from the China Antimicrobial Resistance Surveillance System (CARSS) database for 30 provinces from 2014 to 2020. Meteorological factor, socioeconomic and health care factors were obtained from the China Statistical Yearbook. A revised Difference-in-Difference (DID) approach was applied to quantitatively assess the association between ambient temperature and AMR, and exploring the modified effects of socioeconomic and health care factors.Results Ambient temperature had a significant protective effect on Methicillin-Resistant Staphylococcus Aureus (MRSA) (Relative risk (RR) = 0.959, p = 0.042) and Vancomycin Resistant Enterococcus Faecium (VRefm) (RR = 0.798, p Penicillin Resistant Streptococcus Pneumoniae (PRSP) (RR = 1.556, p Conclusions Ambient temperature was significantly associated with AMR, having varied effects for different bacteria-antibacterial combination. Some certain socioeconomic and health care factors will influence the association between temperature and antimicrobial resistance, thereby increasing the risk of bacterial resistance. The effect of temperature on antimicrobial resistance, and interactions with socioeconomic and hospitalization rate should be seriously considered in antimicrobial stewardship within a changing climate.

Node classification is a substantial problem in graph-based fraud detection. Many existing works adopt Graph Neural Networks (GNNs) to enhance fraud detectors. While promising, currently most GNN-based fraud detectors fail to generalize to the low homophily setting. Besides, label utilization has been proved to be significant factor for node classification problem. But we find they are less effective in fraud detection tasks due to the low homophily in graphs. In this work, we propose GAGA, a novel Group AGgregation enhanced TrAnsformer, to tackle the above challenges. Specifically, the group aggregation provides a portable method to cope with the low homophily issue. Such an aggregation explicitly integrates the label information to generate distinguishable neighborhood information. Along with group aggregation, an attempt towards end-to-end trainable group encoding is proposed which augments the original feature space with the class labels. Meanwhile, we devise two additional learnable encodings to recognize the structural and relational context. Then, we combine the group aggregation and the learnable encodings into a Transformer encoder to capture the semantic information. Experimental results clearly show that GAGA outperforms other competitive graph-based fraud detectors by up to 24.39% on two trending public datasets and a real-world industrial dataset from Anonymous. Even more, the group aggregation is demonstrated to outperform other label utilization methods (e.g., C&S, BoT/UniMP) in the low homophily setting., Accepted to The ACM Webconf 2023

In this paper, a contactless nonlinear acoustic method is developed for the evaluation of stress states in anisotropic metallic plates by a combination of electromagnetic acoustic resonance (EMAR) technique and higher harmonic generation. Electromagnetic transducers (EMATs) designed and applied for exciting and receiving ultrasonic signals can maintain the coupling condition consistently on the measure of higher harmonics generated. EMAR provides a sufficient magnitude of signals for higher harmonics generated. In addition, the conventional EMAR technique based on the measurement of shear-wave velocity and attenuation within a certain frequency range is also carried out in the specimens. The effect of stress on the higher harmonic generation is explored and discussed. It is found that nonlinear parameters measured by the nonlinear EMAR method change significantly versus the increase of external tension stress loadings, whereas the variations of linear acoustic parameters measured are negligible. In addition, the obtained results clearly indicate that the variation of the measured acoustic nonlinear parameters versus external stresses is direction-depended in anisotropic materials. The contactless nonlinear acoustic technique combines the feature of EMAR with the merit of higher harmonic generation, providing an effective means for stress evaluation in weakly anisotropic materials with improved reliability and sensitivity over linear ones.

We analyze the formation of maximally entangled Rydberg atom pairs subjected to Landau-Zener sweeps of the atom-light detuning. Though the populations reach a steady value at longer times, the phases evolve continuously, leading to periodic oscillations in the entanglement entropy. The local unitary equivalence between the obtained maximally entangled states and the Bell states is verified by computing the polynomial invariants. Finally, we study the effect of spontaneous emission from the Rydberg state of rubidium atoms on the correlation dynamics and show that the oscillatory dynamics persists for high-lying Rydberg states. Our study may offer novel ways to generate maximally entangled states, quantum gates and exotic quantum matter in arrays of Rydberg atoms through Landau Zener sweeps., 7 pages, 7 figures and 1 table

After evaporation of a sessile colloidal droplet, the coffee stain always emerges with disordered structures. This may be unfavorable for many applications, such as droplet-based printing. Therefore, to realize uniform and ordered patterns is becoming an urgent task. In this work, we realize ultrafast fabrication of uniform colloidal crystals by suppressing the coffee ring effect in flash evaporation of a droplet. The low-pressure environment can tremendously improve the evaporation rate, which will accelerate the colloidal particles to be captured by the gas-liquid interface and self-assemble into ordered structures instantaneously. With the control of the pressure and concentration, the uniform and ordered patterns can be realized in several seconds. The colloidal photonic crystals with diverse structural colors can be easily and rapidly obtained by adjusting the particle sizes. We think this work may have instructive significance in the rapid fabrication of high-quality and high-performance printed electronics.

In this paper, bismuth oxide (Bi2O3) as the main functional powder, lead (Pb) and tantalum (Ta) as the metal additives, epoxy resin as the matrix and polyester–cotton blended woven fabric as the substrate, Bi2O3 coating nuclear radiation protection composite, Bi2O3/Pb coating nuclear radiation protection composite, and Bi2O3/Ta coating nuclear radiation protection composite with different process parameters were prepared. The cross-section scanning analysis and the influence factor analysis of γ-ray protection performance were carried out, and the mechanical properties of the composites were discussed. The results show that an increase in Bi2O3 content (mass fraction) and an increase in coating thickness can improve the shielding rate of the composite materials to γ-rays. When the thickness of the coating is 1.6 mm and the content of Bi2O3 is 50%, the shielding rate of the composite to γ-rays (at 59.5 keV) reaches 46.1%. The shielding rate of the composite can be increased by adding appropriate metal additives, and the effect of adding Ta is better than that of Pb. The shielding rate of the composite to γ-rays (59.5 keV) can be increased from 28.4% to 31.5% by adding 5% Ta. An increase in Bi2O3 content (mass fraction) and an increase in the coating thickness can aggravate the agglomeration of functional particles in the material. The addition of metal additives can reduce agglomeration to a certain extent. Bi2O3 content, coating thickness, and metal additives all have an effect on the mechanical properties of the composite. If the coating is too thick or the functional particle content is too high, the tensile strength and elongation at break of the composite will be reduced.

The use of acoustic nonlinear response can be an effective method for the early-stage damage evaluation of materials. However, it is challenging to assess the thermal damage in highly attenuating materials, such as polymethyl methacrylates, by the measure of generated second harmonics with a double fundamental frequency of primary waves. Quasi-static component (QSC) generated by ultrasonic wave propagation in damaged structures, which combines the high sensitivity of acoustic nonlinearity and low attenuative effect, has a great potential for early-stage damage evaluation in highly attenuating materials. In this paper, an experimental approach for directly detecting the QSC pulse of an ultrasonic wave tone burst is proposed. While a high-frequency longitudinal wave transducer is used for exciting the primary ultrasonic wave tone burst, the co-propagating QSC pulse is captured using a low-frequency ultrasonic transducer. The phase-reversal technique is employed to enhance the signal-to-noise ratio of QSCs and to counteract the signals of primary longitudinal waves. Amplitude variations of QSCs under different thermal loadings are clearly illustrated in a repeatable manner, while those of linear ultrasonic features in the specimens are neglectable. Experimental results indicate that the measure of QSC generation of ultrasonic wave propagation can be a prospective alternative for evaluating thermal degradation of highly attenuating materials.

Prussian blue analogue nanocrystals of the CsINiII[CrIII(CN)6] cubic network with 6 nm size were assembled as a single monolayer on highly organized pyrolytic graphite (HOPG). X-ray magnetic circular dichroism (XMCD) studies, at the Ni and Cr L2,3 edges, reveal the presence of an easy plane of magnetization evidenced by an opening of the magnetic hysteresis loop (coercive field of ≈200 Oe) when the magnetic field, B, is at 60° relative to the normal to the substrate. The angular dependence of the X-ray natural linear dichroism (XNLD) reveals both an orientation of the nanocrystals on the substrate and an anisotropy of the electronic cloud of the NiII and CrIII coordination sphere species belonging to the nanocrystals' surface. Ligand field multiplet (LFM) calculations that reproduce the experimental data are consistent with an elongated tetragonal distortion of surface NiII coordination sphere responsible for the magnetic behavior of monolayer.

Multi-view learning can be considered as a kind of classification method which explores common and unique information among different views. For dictionary learning, it can identify informative features by learning sparse representation of samples and has great advantages for classification. However, there are few researches on the problem of multi-view learning with dictionary learning. In order to improve the performance of multi-view classification, we propose a new multi-view dictionary learning with consensus of view(MVDL-CV). First of all, we learn a particular dictionary for each view and obtain the sparse representation of the sample. Then, by utilizing the regularization term between two dictionaries in consensus, we can determine the similarity of samples and obtain the discriminative sparse representation, which can be helpful to construct the improved classifiers . Further, we obtain the solution of the model through an alternating convex optimization method and present the convergence analysis of MVDL-CV. In the experiments, we compare the proposed method with previous multi-view learning methods, and the experimental results show that MVDL-CV is a feasible and competitive method.

Increasing severity and frequency of drought is predicted for large portions of the terrestrial biosphere, with major impacts already documented in wet tropical forests. Using a 4-year rainfall exclusion experiment in the Daintree Rainforest in northeast Australia, we examined canopy tree responses to reduced precipitation and soil water availability by quantifying seasonal changes in plant hydraulic and carbon traits for 11 tree species between control and drought treatments. Even with reduced soil volumetric water content in the upper 1m of soil in the drought treatment, we found no significant difference between treatments for predawn and midday leaf water potential, photosynthesis, stomatal conductance, foliar stable carbon isotope composition, leaf mass per area, turgor loss point, xylem vessel anatomy, or leaf and stem nonstructural carbohydrates. While empirical measurements of aboveground traits revealed homeostatic maintenance of plant water status and traits in response to reduced soil moisture, modeled belowground dynamics revealed that trees in the drought treatment shifted the depth from which water was acquired to deeper soil layers. These findings reveal that belowground acclimation of tree water uptake depth may buffer tropical rainforests from more severe droughts that may arise in future with climate change.

We propose an adiabatic protocol for implementing a controlled-phase gate CZ$_{\theta}$ with continuous $\theta$ of neutral atoms through a symmetrical two-photon excitation process via the second resonance line, $6P$ in $^{87}$Rb, with a single-temporal-modulation-coupling of the ground state and intermediate state. Relying on different adiabatic paths, the phase factor $\theta$ of CZ$_{\theta}$ gate can be accumulated on the logic qubit state $|11\rangle$ alone by calibrating the shape of the temporal pulse where strict zero amplitudes at the start and end of the pulse are not needed. For a wide range of $\theta$, we can obtain the fidelity of CZ$_{\theta}$ gate over $99.7\%$ in less than $1~\mu$s, in the presence of spontaneous emission from intermediate and Rydberg states. And in particular for $\theta=\pi$, we benchmark the performance of the CZ gate by taking into account various experimental imperfections, such as Doppler shifts, fluctuation of Rydberg-Rydberg interaction strength, inhomogeneous Rabi frequency, and noise of driving fields, etc, and show that the predicted fidelity is able to maintain at about $98.4\%$ after correcting the measurement error. This gate protocol provides a robustness against the fluctuation of pulse amplitude and a flexible way for adjusting the entangling phase, which may contribute to the experimental implementation of near-term noisy intermediate-scale quantum (NISQ) computation and algorithm with neutral-atom systems., Comment: 15 pages, 12 figures, accepted by Phys. Rev. Applied

This study focuses on static component generation (SCG) and its measurement wherein a group velocity mismatch (GVM) exists between the primary guided wave and the generated static component (SC). The SCGs by primary S0, A0, and SH0 waves are investigated. It is confirmed that the SCs are S0 mode. The GVM causes the temporal waveforms of the SCs to tend to increase in width with propagation distance. A feasible method is proposed accordingly for measurement of SCG with GVM using only lead zirconic titanate based transducers, wherein the SCs generated by two counter-propagating primary waves are modulated and superposed on each other.

Due to the complicacy of geometry and structure in the arched composite structure, it is difficult to monitor various kinds of defects accurately. The developed damage probabilistic diagnostic imaging approach based on ultrasonic guided wave energy signal characteristics is very feasible for the structural health monitoring in the arched composite structures. However, the conventional probabilistic diagnostic imaging (PDI) approaches united with the signal energy damage indices ( DIs) have some limitations in the identification of the number, location and specific size information of multi-defects. Thus, the damage shape factor from the single damage-impaired path imminently demands to be majorized to raise the precision and stability of PDI approach in the damage recognition. A corrected probabilistic diagnostic imaging (CPDI) approach integrated with the damage shape factor [Formula: see text] needs to be recommended to precisely inspect the expansion of defect zones and different multi-defects in the arched composite structure. The availability and feasibility of the proposed methods has been validated by the experiments in the tested specimen. The results show that the fused frequency-domain energy DIs can be applied to indicate the expansion of defect zones quantitatively. It is proved that the defect identification accuracy of multi-defects from the CPDI approach can be improved by the majorization of damage shape factor, effectively. It is also clearly observed that the number, location and specific size information of different conditions of multi-defects can be distinguished by using the CPDI algorithm, availably.

Perforated materials in the traditional sense are rigid, usually dense, costly and inflexible. For this study, polyester/cotton blended woven fabric as the base fabric, nano-SiO2 (silicon dioxide) as the functional particles and PU (polyurethane) as the matrix were selected. Accordingly, flexible PU/SiO2 perforated coating composites with different process parameters were developed. The influence of the nano-SiO2 content, perforation diameter, perforation rate, number of fiber felt layers and cavity depth on the sound absorption coefficient were investigated. The resonant frequencies of materials with different cavity depths were evaluated by both theoretical calculation and experimental method. It was found that the flexible perforated composite has good sound absorption and mechanical properties, and has great potential for applications requiring soft and lightweight sound absorption materials.

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease characterized by myofibroblast accumulation and extracellular matrix deposition, which lead to irreversible damage of the lung’s architecture and the formation of fibrotic lesions. IPF is also a sequela in serious patients with the coronavirus disease 2019 (COVID-19). The molecular mechanisms under pulmonary fibrosis remain unclear, and there is no satisfactory treatment currently available. Piceatannol (PIC) is a naturally occurring resveratrol analog found in a variety of dietary sources such as grapes, passion fruit, and white tea. It has been reported to inhibit liver fibroblast growth and exhibited various antitumor activities, although its role in pulmonary fibrosis has not been established yet. In the present study, we evaluated the anti-fibrotic role of PIC in bleomycin (BLM)-induced pulmonary fibrosis in mice.Methods: Mice with BLM-induced pulmonary fibrosis were treated with PIC, and fibrotic changes were measured by hematoxylin-eosin (H&E) staining and hydroxyproline assay. Luciferase assay, Western blot assay, histological analysis, and immunofluorescence staining were used to evaluate the effect of PIC on fibroblast activation and autophagy in mouse embryonic fibroblast cells (NIH-3T3) and human lung fibroblast cells (HFL1). The anti-fibrotic mechanisms of PIC were either confirmed in vivo.Results: Our results showed that PIC significantly alleviated the bleomycin-induced collagen deposition and myofibroblast accumulation. In vitro and in vivo studies indicated that PIC plays a role in activating autophagy in the process of anti-fibroblast activation. Further mechanism studies demonstrated that PIC can promote autophagy via inhibiting the TGF-β1-Smad3/ERK/P38 signaling pathway, which leads to a decreased number of activated myofibroblasts.Conclusion: Our study demonstrated for the first time that PIC possesses the protective effects against bleomycin-induced pulmonary fibrosis due to the direct pulmonary protective effects which enhance the effect of autophagy in vitro and in vivo and finally leads to the decreased number of activated myofibroblasts. PIC may serve as a candidate compound for pulmonary fibrosis therapy and attenuates the sequelae of SARS-COV-2 pulmonary fibrosis.

Antibiotic resistance leads to longer hospital stays, higher medical costs, and increased mortality. However, research into the relationship between climate change and antibiotic resistance remains inconclusive. This study aims to address the gap in the literature by exploring the association of antibiotic resistance with regional ambient temperature and its changes over time.Data were obtained from the China Antimicrobial Surveillance Network (CHINET), monitoring the prevalence of carbapenem-resistantA 1 °C increase in average ambient temperature was associated with 1.14-fold increase (95%-Higher prevalence of antibiotic resistance is associated with increased regional ambient temperature. The development of antibiotic resistance under rising ambient temperature differs across various strains of bacteria.The National Key RD Program of China (grant number: 2018YFA0606200), National Natural Science Foundation of China (grant number: 72074234), Fundamental Scientific Research Funds for Central Universities, P.R. China (grant number: 22qntd4201), China Medical Board (grant number: CMB-OC-19-337).

Increasing seawater exposure is causing mortality of coastal forests, yet the physiological response associated with seawater-induced tree mortality, particularly in non-halophytes, is poorly understood. We investigated the shifts in carbon and nitrogen (N) metabolism of mature Sitka-spruce trees that were dying after an ecosystem-scale manipulation of tidal seawater exposure. Soil porewater salinity and foliar ion concentrations increased after seawater exposure and were strongly correlated with the percentage of live foliated crown (PLFC; e.g., crown ‘greenness’, a measure of progression to death). Co-occurring with decreasing PLFC was decreasing photosynthetic capacity, N-investment into photosynthesis, N-resorption efficiency and non-structural carbohydrate (soluble sugars and starch) concentrations, with the starch reserves depleted to near zero when PLFC dropped below 5%. Combined with declining PLFC, these changes subsequently decreased total carbon gain and thus exacerbated the carbon starvation process. This study suggests that an impairment in carbon and N metabolism during the mortality process after seawater exposure is associated with the process of carbon starvation, and provides critical knowledge necessary to predict sea-level rise impacts on coastal forests.

Reduced web section (RWS) connections and welded flange plate (WFP) connections can both effectively improve the seismic performance of a structure by moving plastic hinges to a predetermined location away from the column face. In this paper, two kinds of steel frames—with RWS connections and WFP connections—as well as different frames with welded unreinforced flange connections were studied through seismic fragility analysis. The numerical simulation was conducted by using multiscale FE modelling. Based on the incremental dynamic analysis and pushover analysis methods, probabilistic seismic demand analysis and seismic capability analysis were carried out, respectively. Finally, combined with the above analysis results, probabilistic seismic fragility analysis was conducted on the frame models. The results showed that the RWS connection and WFP connection (without double plates) have little influence on reducing the maximum inter-storey drift ratio under earthquake action. RWS connections slightly reduce the seismic capability in non-collapse stages and improve the seismic collapse resistance of a structure, which exhibits good structural ductility. WFP connections can comprehensively improve the seismic capability of a structure, but the seismic collapse resistance is worse than that of RWS connections when the structure has a large number of storeys. The frame with WFP connections has a lower failure probability at every seismic limit state, while the frame with RWS connections sacrifices some of its structural safety in non-collapse stages to reduce the collapse probability.

Nickel and nickel-based composites are of vital importance in many fields, while temperature loading can greatly influence the strength and performance of the materials. Nondestructive evaluation and characterization of such thermal damage can be used to predict the failure of metallic structures, thermal barrier coatings and so on, especially in a non-contact way under certain strict circumstances, such as testing at high temperature or in radiative environment. Herein, a contactless ultrasonic technique employing electromagnetic acoustic transducers (EMATs) combined with the resonance ultrasound spectroscopy is applied to make up the low energy transition efficiency of EMATs and enhance the signal-to-noise ratio of ultrasonic testing signals. The method is adopted to assess the thermal damages of different levels in artificially heat loaded nickel plates. The damage sensitivity of third order harmonics generated from shear waves is discussed, along with linear ultrasonic features including wave velocity and attenuation. Experimental results show that the proposed nonlinear electromagnetic acoustic resonance (EMAR) technique can be used to evaluate the thermal damage in ferromagnetic material with improved reliability and sensitivity over linear ones.

A liquid spreading over another is a universal physical process in the nature, which was investigated by the scaling law to reveal the underlying mechanical mechanism over the decades. However, scaling laws are restricted to piecewise physical stages, respectively. It is a challenge to present a full physical picture for a dynamic spreading process covering a wide-spectrum speed. We propose a general wall-confined spreading dynamics (WCSD) model originating from molecular kinetic theory (MKT). It creatively illustrates the order and domination between driving energy and energy dissipation (or transfer) using a phase diagram according to theory and experiments. This work reveals the deep mechanical mechanism of WCSD which provides an indirect guidance on the solution processing methods of two-dimensional molecular crystals (2DMCs) growth.

Human-induced nitrogen (N) and phosphorus (P) enrichment have profound effects on grassland net primary production (NPP) and species richness. However, a comprehensive understanding of the relative contribution of N vs. P addition and their interaction on grassland NPP increase and species loss remains elusive. We compiled data from 80 field manipulative studies and conducted a meta-analysis (2107 observations world-wide) to evaluate the individual and combined effects of N and P addition on grassland NPP and species richness. We found that both N addition and P addition significantly enhanced grassland above-ground NPP (ANPP; 33.2% and 14.2%, respectively), but did not affect total NPP, below-ground NPP (BNPP), and species evenness. Species richness significantly decreased with N addition (11.7%; by decreasing forbs) probably due to strong decreased soil pH, but not with P addition. The combined effects of N and P addition were generally stronger than the individual effects of N or P addition, and we found the synergistic effects on ANPP, and additive effects on total NPP, BNPP, species richness, and evenness within the combinations of N and P addition. In addition, N and P addition effects were strongly affected by moderator variables (e.g. climate and fertilization type, duration and amount of fertilizer addition). These results demonstrate a higher relative contribution of N than P addition to grassland NPP increase and species loss, although the effects varied across climate and fertilization types. The existing data also reveals that more long-term (≥5 years) experimental studies that combine N and P and test multifactor effects in different climate zones (particularly in boreal grasslands) are needed to provide a more solid basis for forecasting grassland community response and C sequestration response to nutrient enrichment at the global scale.

Bone homeostasis only exists when the physical function of osteoblast and osteoclast stays in the balance between bone formation and resorption. Bone resorption occurs when the two processes are uncoupled, shifting the balance in favour of bone resorption. Excessive activation of osteoclasts leads to a range of osteolytic bone diseases including osteoporosis, aseptic prosthesis loosening, rheumatoid arthritis, and osteoarthritis. Receptor activator of nuclear factor kappa-B ligand (RANKL) and its downstream signaling pathways are recognized as key mediators that drive the formation and activation of osteoclastic function. Hence, osteoclast formation and/or its function remain as dominant targets for research and development of agents reaching the treatment towards osteolytic diseases. Chrysin (CHR) is a flavonoid with a wide range of anti-inflammatory and anti-tumor effects. However, its effect on osteoclasts remains unknown. In this study, we found the effects of CHR on inhibiting osteoclast differentiation which were assessed in terms of the number and size of TRAcP positive multinucleated osteoclasts (OCs). Further, the inhibitory effects of CHR on bone resorption and osteoclast fusion of pre-OC were assessed by hydroxyapatite resorption pit assay and F-actin belts staining; respectively. Western blotting analysis of RANKL-induced signaling pathways and immunofluorescence analysis for p65 nuclear translocation in response to RANKL-induced osteoclasts were used to analyze the mechanism of action of CHR affecting osteoclasts. Lastly, the murine calvarial osteolysis model revealed that CHR could protect against particle-induced bone destruction in vivo. Collectively, our data strongly suggested that CHR with its promising anti-tumor effects would also be a potential therapeutic agent for osteolytic diseases.

Nutrient resorption from senescing tissues is the most critical nutrient source for plants in degradation grasslands, playing critical roles to primary productivity and interspecies competitiveness. Hence within-species and among-species variation of nutrient resorption is one of the mechanisms explaining the increasing productivity and decreasing biodiversity after enclosure. Yet, the response of plant nutrient resorption to enclosure remains poorly documented. We conducted a 6-year manipulative field study to estimate the effects of enclosure on nutrient resorption efficiency in five dominant species in a degraded subalpine pasture. Both soil, mature and senesced leaves showed significant increases in N, P, and K contents in response to enclosure. Despite some species-specific differences, enclosure generally increased the nutrient resorption in graminoids, but decreased in forbs (with the exception of phosphorus for Potentilla anserine), indicating an important difference in the adaptation of plant functional types to enclosure which may in turn strongly impact the productivity and structure of pasture vegetation under long-term enclosure. This study shows the positive effects of enclosure management on soil and plant nutrients accumulation, and our results highlight the importance of among-species and within-species variations in plant nutrient resorption to explain the effects of enclosure on biodiversity loss and productivity increase in a degraded ecosystem.