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The large load and poor heat dissipation of moon rock core drilling leads to the difficulty of rock breaking and low drilling and sampling efficiency. As a new auxiliary rock breaking method, laser rock breaking is expected to be applied to perturbation sampling in lunar rock drilling. Revealing the fracture characteristics and mechanism of rock under laser irradiation is an important basis for realizing laser-assisted lunar rock sampling. Basalt was used as simulated lunar rock sample, and its mechanical response characteristics under laser irradiation were analyzed from macro to micro point of view, and the failure law under different laser power and different irradiation time was explored. The results show that the failure of the sample under laser irradiation is mainly characterized by local rock melting and dynamic crack propagation, and the surface temperature of the sample follows the characteristics of Gaussian distribution. The laser power has a greater influence on the degree of rock weakening than the irradiation time. Laser irradiation of rocks can significantly reduce rock strength, and has obvious effects on improving rock breaking efficiency and reducing in situ disturbance. It is expected to provide theoretical and technical support for assisting lunar rock drilling and sampling in the future.

The vertical deflection of the main girder on a cable-stayed bridge is a direct reflection of the vertical stiffness of bridge structure, which represents the comprehensive mechanical performance of cable-stayed bridge. Compared with the deflection caused by vehicles, the deflection caused by temperature is often more significant and the change frequency is very low, which is easy to extract from raw data, and can be used as an index to evaluate the state of cable-stayed bridge. To obtain the control value for recognizing the abnormal deflection, it is necessary to establish an accurate input-output relationship between temperature and temperature-induced deflection. However, because of the high-order nonlinear relationship between the temperature and the temperature-induced deflection, the traditional linear regression is not accurate enough in modeling this relationship. To establish a high-precision model for the deflection, this paper uses the machine learning tools with the highly nonlinear fitting performance to further model the project. Considering both the precision and modeling efficiency, the Long-Short Term Memory (LSTM) network can build the optimal model between temperature and temperature-induced deflection. Use the regression value output by LSTM as the control value combining with the statistical pattern of t-test, the 6% abnormal deflection can be recognized. The 6% sensitivity can help to recognize bridge abnormalities earlier. &nbsp

The rapid digitalization of energy sectors has led to a significant increase in coding tasks for engineers and researchers. This research article explores the potential of leveraging ChatGPT, an advanced AI language model, to revolutionize programming in the energy domain. Here, we propose a generic interactive programming framework based on ChatGPT, covering three distinct applications in energy systems ranging from simple to complex. For routine tasks such as daily unit commitment, ChatGPT can increase efficiency by automatic modelling, coding, debugging and scaling and thus re-ducing repetitive work. For complex tasks such as decentralized optimization of an integrated energy system (IES) where engineers have no prior knowledge, ChatGPT can reduce the learning cost by recommending appropriate algo-rithms. For new problems without readily available solutions such as ultra-fast unit commitment, ChatGPT can organize potential technology roadmap and provide algorithm recommendation and auto-coding for each step. The findings demonstrate the potential of ChatGPT as a powerful tool in the domain of energy sectors in terms of auto coding, new knowledge learning and new problem solving.

Ovarian cancer is a common gynecological malignant tumor. Early diagnosis is important for the prognosis of patients with ovarian cancer. To evaluate the accuracy of the Copenhagen Index (CPH-I) in detecting malignant adnexal tumors and to compare the diagnostic accuracy of CPH-I and the Risk of Ovarian Malignancy Algorithm (ROMA). PubMed, Web of Science, and Cochrane Library databases were used to retrieve eligible studies. The overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the (summary receiver operating characteristic) curve (AUC) were 0.81, 0.88, 6.61, 0.22, 30.43, and 0.91, respectively, in diagnosing malignant adnexal tumors. In addition, using ROMA, the sensitivity, specificity, and AUC were 0.83, 0.85, and 0.90, respectively. CPH-I showed high accuracy in diagnosing malignant adnexal tumors, which could be an alternative method with similar efficacy to ROMA. CPH-I was more advantageous in diagnosing adnexal tumors in postmenopausal women.

Purpose The paper aims to reduce the low-frequency resonance and residual vibration of the robot during the operation, improve the working accuracy and efficiency. A reduced weight and large load-to-weight ratio can improve the practical application of a collaborative robot. However, flexibility caused by the reduced weight and large load-to-weight ratio leads to low-frequency resonance and residual vibration during the operation of the robot, which reduces the working accuracy and efficiency. The vibrations of the collaborative robot are suppressed using a modified trajectory-planning method. Design/methodology/approach A rigid-flexible coupling dynamics model of the collaborative robot is established using the finite element and Lagrange methods, and the vibration equation of the robot is derived. Trajectory planning is performed with the excitation force as the optimization objective, and the trajectory planning method is modified to reduce the vibration of the collaborative robot and ensure the precision of the robot terminal. Findings The vibration amplitude is reduced by 80%. The maximum torque amplitude of the joint before the vibration suppression reaches 50 N·m. After vibration suppression, the maximum torque amplitude of the joint is 10 N·m, and the resonance phenomenon is eliminated during the operation process. Consequently, the effectiveness of the modified trajectory planning method is verified, where the vibration and residual vibration in the movement of the collaborative robot are significantly reduced, and the positioning accuracy and working efficiency of the robot are improved. Originality/value This method can greatly reduce the vibration and residual vibration of the collaborative robot, improve the positioning accuracy and work efficiency and promote the rapid application and development of collaborative robots in the industrial and service fields.

Mulisan decoction (MLS) is a classic formula of traditional Chinese medicine for treating hyperhidrosis. The mechanism remains unclear.To investigate the antiperspirant effect and underlying mechanisms of MLS.Fifty rats were divided into control, model, and three doses of MLS intervention groups (Rats treated with MLS presented a significant decrease in sweat point numbers (13.5%), increase in body weight (13.2%), and promotion in the balance of Th1/Th2 cytokine ratioMLS demonstrated a good antiperspirant effect and metabolism improvement. These findings inspire more clinical study validation on immune improvement and antiperspirant effect.

A novel orange-coloured bacterium, designated strain SYSU D00508T, was isolated from a sandy soil sampled from the Kumtag Desert in China. Strain SYSU D00508T was aerobic, Gram-stain-negative, oxidase-positive, catalase-positive and non-motile. Growth occurred at 4–45°C (optimum 28–30°C), pH 6.0–9.0 (optimum pH 7.0–8.0) and with 0–2.5 % NaCl (w/v, optimum 0–1.0 %). The major polar lipids consisted of phosphatidylethanolamine (PE), unidentified aminolipids (AL1-3) and unidentified polar lipids (L1-5) were also detected. The major respiratory quinone was MK-7 and the major fatty acids (>10 %) were iso-C17 : 0 3-OH, iso-C15 : 0 and iso-C15 : 1 G. The genomic DNA G+C content was 42.6 %. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain SYSU D00508T belonged to the family Chitinophagaceae and showed 93.9 % ( Segetibacter koreensis DSM18137T), 92.9 % ( Segetibacter aerophilus NBRC 106135T), 93.0 % ( Terrimonas soli JCM 32095T) and 92.8 % ( Parasegetibacter terrae JCM 19942T) similarities. Based on the phylogenetic, phenotypic and chemotaxonomic data, strain SYSU D00508T is proposed to represent a novel species of a new genus, named Aridibaculum aurantiacum gen. nov., sp. nov., within the family Chitinophagaceae . The type strain is SYSU D00508T (=KCTC 82286T=CGMCC 1.18648T=MCCC 1K05005T).

Fruits will be subjected inevitably to various external forces in the process of harvesting, transportation, processing, and storage, which will cause mechanical damage. The research on mechanical properties and damage mechanisms of fruit can effectively control its loss. In this study, fruits are divided into different types according to their morphology and structure. The impact, vibration, static pressure, and other mechanical damage on fruits are studied. It is important to identify the damaged parts of fruit after damage quickly and accurately. Therefore, this study analyzes the application of nondestructive testing technologies such as spectral detection technology, NMR (nuclear magnetic resonance) detection technology, and acoustic and electrical characteristics detection technology in fruit damage detection.

Gradients have been exploited in proposal distributions to accelerate the convergence of Markov chain Monte Carlo algorithms on discrete distributions. However, these methods require a natural differentiable extension of the target discrete distribution, which often does not exist or does not provide effective gradient guidance. In this paper, we develop a gradient-like proposal for any discrete distribution without this strong requirement. Built upon a locally-balanced proposal, our method efficiently approximates the discrete likelihood ratio via Newton's series expansion to enable a large and efficient exploration in discrete spaces. We show that our method can also be viewed as a multilinear extension, thus inheriting its desired properties. We prove that our method has a guaranteed convergence rate with or without the Metropolis-Hastings step. Furthermore, our method outperforms a number of popular alternatives in several different experiments, including the facility location problem, extractive text summarization, and image retrieval., Published at AISTATS 2023

The purpose of this study is to construct an automatic carpal bone age evaluation system for Chinese children based on TW3-C Carpal method by deep learning and to evaluate the accuracies in test set and clinical test set.A total of 8184 radiographs of Chinese Han healthy children (2-14 years old) were collected from the 2005 China Skeletal Development Survey data and from the accumulated radiographs in bone age studies over the years. Three experienced radiologists and the China-05 standard maker jointly evaluated each bone development stage, and the consensual stage was decided as the reference standard. According to each epiphysis development stage, 10% of them were derived by stratified random sampling as test sets, and the remaining radiographs were used as training sets and validation sets. Furthermore, the overall performance of the model was estimated by comparing the mean difference, 95% limits of agreement, mean absolute difference (MAD) and root mean square (RMS) between the model predictions and the reference standard.The percentage agreement of ratings in each epiphysis in the test set ranged from 82.82% to 90.06%, with an average of 86.94%. Compared with the reference standard, the automated bone age system has a mean difference of 0.01 years old, ± 0.45 years old in 95% confidence interval by single reading, an 85.93% percentage agreement of ratings, a 90.5% bone age accuracy rate, 0.20 years old of MAD, and 0.32 years old of RMS in the clinical test set.The automatic bone age system for Chinese children has a comparable accuracy and stable determination compared with experienced radiologists.

BackgroundMost previous studies on acupuncture in the treatment of knee osteoarthritis (KOA) have focused on improving functional efficacy and safety, while related mechanisms have not been systematically reviewed. Acupuncture modulates cytokines to attenuate cartilage extracellular matrix degradation and apoptosis, key to the pathogenesis of KOA, but the mechanisms are complex.ObjectivesThe purpose of this study is to assess the efficacy of acupuncture quantitatively and summarily in animal studies of KOA.MethodsNine databases including PubMed, Embase, Web of Science (including Medline), Cochrane library, Scopus, CNKI, Wan Fang, and VIP were searched to retrieve animal studies on acupuncture interventions in KOA published since the inception of the journal. Relevant literature was screened, and information extracted. Meta-analysis was performed using Revman 5.4 and Stata 17.0 software.ResultsThe 35 included studies involved 247 animals, half of which were in acupuncture groups and half in model groups. The mean quality level was 6.7, indicating moderate quality. Meta-analysis showed that acupuncture had the following significant effects on cytokine levels in p38MAPK and mitochondrial pathways: (1) p38MAPK pathway: It significantly inhibits p38MAPK, interleukin-1beta (IL-1β), tumor necrosis factor alpha (TNF-α), phosphorylated (p)-p38MAPK, matrix metalloproteinase-13 (MMP-13), MMP-1, a disintegrin and metalloproteinase with thrombospondin motifs-5 (ADAMST-5) expression, and significantly increased the expression of collagen II and aggrecan. (2) mitochondrial pathway: It significantly inhibited the expression of Bcl-2-associated X protein (Bax), cysteine protease-3 (caspase-3), caspase-9, and Cytochrome-c (Cyt-c). And significantly increased the expression of B cell lymphocytoma-2 (Bcl-2). In addition, acupuncture significantly reduced chondrocyte apoptosis, Mankin’s score (a measure of cartilage damage), and improved cartilage morphometric characteristics.ConclusionAcupuncture may inhibit cytokine expression in the p38MAPK pathway to attenuate cartilage extracellular matrix degradation, regulate cytokines in the mitochondrial pathway to inhibit chondrocyte apoptosis, and improve cartilage tissue-related phenotypes to delay cartilage degeneration. These findings provide possible explanations for the therapeutic mechanisms and clinical benefits of acupuncture for KOA.Systematic review registrationhttps://inplasy.com, identifier INPLASY20 2290125.

In order to simulate the impacts of carbon peaking and carbon neutrality goals on power system supply side transformation from, the system dynamics method is used to analyze the main influencing factors for carbon emissions in the process of power structure transformation and their correlations under four different development scenarios. The evolution of power generation structure and power carbon emission in four development paths are studied. The results show that the power system supply side transformation would be affected by many factors. Under the premise of policy support, the development of market absorption mechanism and absorption technology would contribute to the transformation of the power generation structure, which is of great significance to the realization of the dual carbon targets.

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. Here we report 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. 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 9.73J/cm

Background Preoperative administration of methylprednisolone reduced circulating markers of endothelial activation. This randomized, double-blind, placebo-controlled trial was to evaluate whether a single preoperative dose of methylprednisolone reduced the rate of postoperative delirium (POD) in older patients undergoing gastrointestinal surgery and its association with the shedding of endothelial glycocalyx markers. Methods About 168 patients, aged 65–80 years and scheduled for laparoscopic gastrointestinal surgery, were randomized to 2 mg/kg methylprednisolone (Group M, n = 84) or equivalent dose of placebo (Group C, n = 84). The primary outcome was the incidence of delirium during the first 5 days after surgery, assessed by the Confusion Assessment Method (CAM). POD severity was rated daily using CAM-Severity (CAM-S). Levels of syndecan-1, heparan sulfate, tumor necrosis factor-α (TNF-α), and brain-derived neurotrophic factor (BDNF) were measured at baseline, 1 day, and 3 days after surgery. Results Compared with placebo, methylprednisolone greatly reduced the incidence of delirium at 72 hours following surgery (9 [10.7%] vs 20 [23.8%], p = .03, OR = 2.22 [95% CI 1.05–4.59]). No between-group difference was found in the cumulative CAM-S score (p = .14). The levels of heparan sulfate, syndecan-1, and TNF-α in Group M were lower than that in Group C (p < .05 and p < .01), while the level of BDNF in Group M was higher than that in Group C (p < .01). Conclusions Preoperative administration of methylprednisolone does not reduce the severity of POD, but may reduce the incidence of delirium after gastrointestinal surgery in older patients, which may be related to a reduction in circulating markers of endothelial degradation, followed by the increase of BDNF level. Clinical Trials Registration Number Chinese Clinical Trial.gov, ChiCTR2000028792. Registered January 4, 2020. http://www.chictr.org.cn/showproj.aspx?proj=47807

The Omicron variant is sweeping the world, which displays striking immune escape potential through mutations at key antigenic sites on the spike protein, making broad-spectrum SARS-CoV-2 prevention or therapeutical strategies urgently needed. Previously, we have reported a hACE2-targeting neutralizing antibody 3E8, which could efficiently block both prototype SARS-CoV-2 and Delta variant infections in prophylactic mouse models, having the potential of broad-spectrum to prevent SARS-CoV-2. However, preparation of monoclonal neutralizing antibodies is severely limited by the time-consuming process and the relative high cost. Here, we utilized a modified VEEV replicon with two subgenomic (sg) promoters engineered to express the light and heavy chains of the 3E8 mAb. The feasibility and protective efficacy of replicating mRNA encoding 3E8 against Omicron infection in the hamster were demonstrated through the lung targeting delivery with the help of VEEV-VRP. Overall, we developed a safe and cost-effective platform of broad-spectrum to prevent SARS-CoV-2 infection.

Decarbonisation of power systems is essential for realising carbon neutrality, in which the economic cost caused by carbon is needed to be qualified. Based on the formulation of locational marginal price (LMP), this paper proposes a locational marginal electricity-carbon price (EC-LMP) model to reveal carbon-related costs caused by power consumers. A carbon-price-integrated optimal power flow (C-OPF) is then developed to maximise the economic efficiency of the power system considering the costs of electricity and carbon. Case studies are presented to demonstrate the new formulation and the results demonstrate the efficacy of the EC-LMP-based C-OPF on decarbonisation and economy.

The conventional wind farm (WF) power generation modelling method highly relies on wind hindcast produced by record time-series data or numerical weather modelling. However, estimating production at future sites is challenging in the absence of local wind monitoring. To address this, a data-driven WF modelling and model transfer strategy is proposed in this work. It considers the challenge of how to transpose metered data from existing operational WFs to sites that might feature as a prospective site for a new WF. By modelling 14 WFs distributed across Scotland using a machine learning (ML) approach, this study proved that it was possible to effectively model metered production at a site using modelled wind speed and direction. In addition, this study also found that when the latitude difference between two WFs is less than 0.2 degrees and the distance is less than 50km, two WFs in non-mountainous areas can share an MLmodel. The results of the shared ML model remain superior to the results of the given power curve from manufacturers, after adjusting the results by the ratio of the power curve in these two WFs. The WF model transfer strategy investigated in this work offered a novel approach to transposing WF production estimates to new sites and appeared to offer better value than simple power curves, which is of importance at the early planning stage for sites selection, although it would likely not fully replace detailed micrositing modelling as are well established in the industry.

To improve the environment perception ability of wheeled mobile robots (WMRs), the visual behavior mechanism of the negative-correlation motion of chameleons is introduced into the binocular vision system of WMRs, and a shifty-behavior-based environment perception model with chameleon-inspired active vision for WMRs is established, where vision–motor coordination is achieved. First, a target search sub-model with chameleon-inspired binocular negative-correlation motion is built. The relationship between the rotation angles of two cameras and the neck and the camera’s field of view (FOV), overlapping angle, region of interest, etc., is analyzed to highlight the binocular negative-correlation motion compared with binocular synchronous motion. The search efficiency of the negative-correlation motion is doubled compared with binocular synchronous motion, and the search range is also greatly improved. Second, the FOV model of chameleon-inspired vision perception based on a shifty-behavior mode is set up. According to the different functional requirements of target searching and tracking stages, the shift of the robot visual behavior is analyzed from two aspects, measuring range and accuracy. Finally, a chameleon-inspired active-vision-based environment perception strategy for mobile robots is constructed based on the shifty-behavior mode, and experimental verification is deployed, which achieves the reproduction of the visual behavior of chameleons in the vision system of mobile robots with satisfactory results.

Chinese solar greenhouse (CSG) is an energy-saving agricultural building which is used to grow vegetables in winter. The north wall of CSG plays an crucial role in concerning the production yield and quality during the winter months. To improve the thermal performance of north wall, different internal surface structures (ISS) with same materials were compared. Based on the field experiment and the proposed valuation, the dynamic heat storage-release characteristics of the north walls have been analyzed and discussed. The results showed that compared with the flat wall and the striped wall, the alveolate wall has better properties of heat storage and thermal insulation. Moreover, relative humidity in this type of greenhouse is more suitable for growing crops. The alveolate wall can improve indoor thermal environment and reduce the sensitivity to external environment. The obtained results can provide a basis for the scientific construction of the CSG north wall. It has significant potential for the area in high latitude, high altitude and long winter.

The distribution law of residual stress in multi-channel scanned plasma cladding of Co-based alloy under different process parameters was studied by means of simulation and tests, and the optimum process parameters were optimized. The simulation model of the plasma cladding stress field was established by ABAQUS software, and the influence law of the working current, scanning speed, and scanning mode on the residual stress of the Co-based alloy multi-channel scanning was studied. A set of optimal cladding process parameters were obtained. The residual stress of the cladding layer was measured by the blind hole method and compared with the stress value in the finite element model. The results show that there is residual tensile stress on the surface of the cladding layer. The residual stress along the direction of the scanning path is greater than that along the direction of the scan sequence. The residual stress increases with the increase of the working current. The scanning speed is greater, and the residual stress is smaller. The residual stress of the short-edge scanning is greater than that of the long-edge scanning. The residual stress of the successive scanning is greater than that of the reciprocating scanning. The long-edge reciprocating scanning is the best scanning mode. The best combination of process parameters is the working current of 90 A, the scanning speed of 100 mm/min, and the long-edge reciprocating scanning mode.

3D bicontinuous nanoporous copper (NPC) with tunable structure was facilely synthesized by one-step chemical dealloying of Ti-Cu amorphous alloys with minor Co addition (0, 4 and 6 at.%). As-dealloyed NPC shows a sandwich-like hierarchical porous structure with micropore in the inner layer and mesopore in the outer layer. The pore size of NPC can be adjusted by the Co content and corrosion time. In addition, the minor Co element in the matrix alloy can promote the formation of more uniform pore and ligament of NPC, which was evaluated by the surface diffusivity of NPC. The formation mechanism of NPC was discussed using phase separation theory. The NPC/Cu2O composite consists of a large number of 3D continuous ligaments and few tetrahedral Cu2O particles grown on the NPC substrate. As catalysts, NPC/Cu2O composite exhibits excellent degradation performance for methyl orange (MO) dye in the dark assisted by the ultrasonic irradiation due to hierarchical porous structure and the synergistic effect of Cu ligaments and Cu2O particles. The relationship between the efficient MO degradation rate of NPC/Cu2O catalysts and temperature has been discussed. Fenton-like reaction shows that NPC/Cu2O catalysts supplemented with hydrogen peroxide (H2O2) can generate HO· radicals, which resolve MO dye molecules into H2O, CO2 and inorganic species.

Cable’s fundamental frequency (CFF) is an important characteristic of the working state of long-span cable-stayed bridges. The change in the bridge’s temperature field will influence CFF by altering the cable’s tension and the cables’ sags. An accurate regression model between the temperature-induced variation of CFF and the real-time changing temperature field should be established. Then, the reference value of the temperature-induced variation of CFF can be obtained after inputting the real-time temperature data. In this study, an intelligent real-time prediction model for CFF is proposed based on the full-bridge temperature field, including the average temperature of the main beam, the vertical temperature difference of the main beam, and the temperature of the cable tower. Besides, a machine learning method named the long short-term memory (LSTM) network is exploited to ensure the nonlinear fitting performance of the model, and a paradigm for optimal hyperparameter selection and training strategy selection is provided. To verify the superiority of the LSTM-based model, the output accuracy of the linear regression, BP network, and LSTM network was tested and compared using the monitoring data collected from cable sensors in the main span and side span, which provides an important basis for the intelligent maintenance and sustainable operation of the bridge cables.

This paper elaborates on a digital simulation study on supernormal particle flow used to investigate and analyze the process of picking up jujube branches, which was a meaningful attempt to search for accurate and effective advanced numerical analogy methods in the agricultural field. In this paper, the meshless technology based on the element-free Galerkin method was used for the first time to present the effects of particle size, particle number and particle acting force on the movement of irregular particles, and the influence of the gear rotation speed, the feeding amount, and the jujube branch size on the movement behavior as well as the picking rate. It can describe not only the particles’ dynamic movement in the process of picking up jujube twigs, such as feeding, collision, throwing and rolling, but also the effect of the quality and shape caused by the particle size, which in turn affects the surface force of particles and interparticle acting force, thereby affecting the weight function in the analytical solution, the total feeding amount and the effect of the acting force resulting from the particles’ contact, roll and collision caused by gear rotation. The findings reveal that the digital simulation, based on the meshless Galerkin technology and Rocky software, is effective in dealing with issues related to supernormal particle flow. By eliminating the influence of geometric shapes on calculations, the method boasts an effective solution to the movement problems of irregularly shaped particles, which would be further applied in the agriculture field.

Shedding light on the dynamics of charge transfer is fundamental and important to understand the light-photocurrent power conversion in transition-metal dichalcogenide (TMD) heterostructures. Herein, based on time-dependent ab initio nonadiabatic molecular dynamics simulation, we studied the photoinduced carrier transfer dynamics in the WS2/WSe2 heterostructure and further analyzed the effects of stacking configuration and temperature. Our calculations show that the time scales of ultrafast hole transfer in the C7 and T stacking configurations are 35 fs and 30 fs, respectively, which are mainly caused by the adiabatic charge transfer mechanism. Meanwhile, the time scales of ultrafast electron transfer in the C7 and T stacking configurations are 12 fs and 40 fs, respectively, which are in good agreement with the experimental result. We also investigated in detail the photoinduced carrier transfer pathways of C7 and T stacking configurations, which appear to have some significant differences. In addition, we found that the temperature basically has no effect on the electron transfer dynamics of the WS2/WSe2 heterostructure; this is in excellent agreement with the experimental observation. In short, the reported findings can provide more in-depth insights into the photoinduced carrier transfer dynamics of TMD-based van der Waals heterostructures.

The crop canopy structure has a significant impact on greenhouse microclimate, in return, the intercepted solar radiation and thermal properties of the plant canopy under greenhouse microclimate directly affect plant photosynthesis and so yield. However, in practice, it is very difficult and time-consuming to accurately measure how plants interact with microclimate over time. In this study, a new method was developed to evaluate micro-light climate and thermal performance on the example of Liaoshen-type Solar Greenhouses (LSG) including a detailed 3D tomato canopy structure, simulated using a functional–structural plant model (FSPM). The detailed surface temperature of each greenhouse component and the tomato crop on organ level down to the leaflets were simulated using advanced light modelling techniques. Taking the simulated light absorptions as input, the thermal conditions were obtained using specific energy balance equations. The simulated greenhouse temperature of the cover, roof, inside air, wall, canopy, and soil showed an overall good correlation to the observed values. The presented model can be seen as the first step towards a realistic 3D greenhouse/canopy simulation including extended energy balance computation based on physical-based light simulation, which can be directly transferred to other types of greenhouses and plant species.

Soil is the largest carbon reservoir in terrestrial ecosystems, and thus minor changes in it can dramatically affect atmospheric CO concentrations. The fragile ecological environment in the northwestern arid zone of China is susceptible to natural and anthropogenic disturbances, which lead to variations in structure and function of the ecosystem, as well as carbon source–sink dynamics. In this study, digital soil maps of soil organic carbon stocks (SOCS) were produced at a 90-m resolution for two periods (the 1980s and 2010s) based on historical soil profile data and a random forest model. The results showed that the prediction accuracy for SOCS in the topsoil (0–30 cm) was superior to that of the subsoil (30–100 cm). Among them, the mean annual evapotranspiration, normalized difference vegetation index during the growing season, multi-year mean temperature, and clay content were the main environmental factors affecting the spatial distribution of SOCS. In the past 30 years, the SOCS of the northwestern arid zone have decreased by 585.50 Tg, with a mean decline of 19.52 Tg C yr . The changes in SOCS caused by land-use conversion and reductions in SOCS were further shown to be attributable to grassland desertification and agricultural reclamation. These findings are valuable for exploring the carbon cycle in terrestrial ecosystems in the context of global climate change and for achieving China’s goal of carbon neutrality.

Two-dimensional metal-organic nanosheets (2D MONs) are an emerging class of ultrathin, porous, and crystalline materials. The organic/inorganic hybrid nature offers MONs distinct advantages over other inorganic nanosheets in terms of diversity of organic ligands and metal notes. Compared to bulk three-dimensional metal-organic frameworks, 2D MONs possess merits of high density and readily accessible catalytic sites, reduced diffusion pathways for reactants/products, and fast electron transport. These features endow MONs with enhanced physical/chemical properties and are ideal for heterogeneous catalysis. In this Review, state-of-the-art synthetic methods for the fabrication of 2D MONs were summarized. The advances of 2D MONs-based materials for electrocatalysis and photocatalysis, including hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), carbon dioxide reduction reaction (CO

A strategy based on grafting organocatalytic units as side-chain on the organic linkers, a TEMPO radical decorated terphenyl-dicarboxylic acid linker was synthesized. By employing acetic acid as modulator, TEMPO radical decorated UiO-68-TEMPO nanocrystals were synthesized by using H2tpdc-TEMPO as organic linker and ZrOCl2 as metal source under solvothermal conditions. UiO-68-TEMPO are monodispersed nanocrystals with side in the range of 800-1200 nm, with high BET areas (up to 1320 m2/g), and contain a large number of TEMPO radicals as evidenced by solid-state EPR spectrum. UiO-68-TEMPO nanocrystals enable selective oxidation of a broad range of alcohols, including primary aromatic alcohols, secondary aromatic alcohols, and heterogeneous atomic alcohols, with high efficiency and selectivity. The catalytic activity of UiO-68-TEMPO nanocrystals remains 75% after catalysis for four cycles. Finally, a plausible catalytic mechanism for the oxidation of benzyl alcohol by UiO-68-TEMPO was proposed, that is the TBN co-catalyst produces NO2/NO redox mediator, which enables the oxidation of TEMPO radicals to oxoammonium cations by O2, and finally oxidize benzyl alcohol to benzaldehyde.

The unpredictable out-of-plane buckling of the upper chords is an important problem of half-through truss bridges widely used in many places. Many specifications adopt the theory of elastic stability as a means to obtain the critical buckling force of the upper chord. In these specifications, the axial force in the upper chord is simplified to parabolic or equivalent force distribution in the span. However, the calculation results of these simplified models can not always satisfy calculation precision in practical projects. To obtain a critical buckling load of the upper chord, using energy method, a mechanical model with trapezoidal axial force distribution is put forward to establish an elastic theoretical model with higher precision. Three bridges with different span are analyzed and theoretical results are in good agreement with buckling analysis by use of finite element method. The trapezoidal axial force distribution model has higher precision than equivalent and parabolic axial force distribution models used in the current specifications. Meanwhile, the effective length coefficient of the upper chord is derived by use of Euler's Formula, and a simplified table based on TAFDM is presented to obtain aluminum half-wave number and the effective length coefficient of the upper chord.

Three-dimensional bicontinuous nanoporous copper (NPC) with a pore size of 10–60 nm was fabricated by dealloying titanium–copper–cobalt amorphous ribbons in 0.23 M hydrofluoric acid (HF) solution for 1–12 h. It is found that dealloyed ribbons show sandwich-like layered structure in the cross-section and the pore size in the outer layer is larger than that in the core layer. The NPC ribbons, polarised in 1 M potassium hydroxide (KOH) solution for 30 min, delivered an excellent electrochemical performance with a specific capacitance of 202.3 mF/cm2 at the current density of 5 mA/cm2 in 1 M KOH electrolyte and good cycling stability of 90% capacitance retention after 5000 cycles at 20 mA/cm2.

Synthesizing QA pairs with a question generator (QG) on the target domain has become a popular approach for domain adaptation of question answering (QA) models. Since synthetic questions are often noisy in practice, existing work adapts scores from a pretrained QA (or QG) model as criteria to select high-quality questions. However, these scores do not directly serve the ultimate goal of improving QA performance on the target domain. In this paper, we introduce a novel idea of training a question value estimator (QVE) that directly estimates the usefulness of synthetic questions for improving the target-domain QA performance. By conducting comprehensive experiments, we show that the synthetic questions selected by QVE can help achieve better target-domain QA performance, in comparison with existing techniques. We additionally show that by using such questions and only around 15% of the human annotations on the target domain, we can achieve comparable performance to the fully-supervised baselines., Comment: ACL 2022 Main Conference

Additional file 1: Figure S1. Reproducibility, library quality and basic statistics of BL-HiChIP. Figure S2. Statistics of chromatin-chromatin interactions captured by BL-HiChIP. Figure S3. Correlation and reproducibility between GRID-seq replicates. Figure S4. RNA–chromatin interactions captured by GRID-seq. Figure S5. Chromatin loops affecting transcription regulation. Figure S6. Comparison between TAD and LD approaches and statistics of newly-identified 223 SNPs. Figure S7. IGV plot of two candidate functional SNPs associated with LMP and LMD traits. Figure S8. Allele frequency of three SNPs and major caRNAs associated with 54 GWAS target genes.