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The advent of new digital technologies has catalyzed a disruptive technological revolution, fostering significant industrial changes and advancing the green transformation of the economy and society. This paper investigates the influence of digitization on the green transformation of agribusiness firms, focusing on agriculture-related companies listed on the Shanghai and Shenzhen A-share markets from 2013 to 2021. Employing fixed-effect and mediated-effect models, the study examines the mechanisms through which digitization impacts these enterprises. The findings indicate that the relationship between digitization and green transformation in agribusiness is non-linear; a certain threshold of digitization must be achieved before it positively affects green transformation. The effect of digitization on green transformation varies according to the nature of business ownership, company size, supply chain flexibility, and regional environmental regulations. The study reveals that digitization influences green transformation through several mechanisms that promote economies of scale, technological innovation, and structural adjustments. While economies of scale derived from digitization do not directly support green transformation, they facilitate technological innovation and structural adjustments that enhance green initiatives in agribusiness.

To meet the challenges of energy sustainability, the integrated energy system (IES) has become a key component in promoting the development of innovative energy systems. Accurate and reliable multivariate load prediction is a prerequisite for IES optimal scheduling and steady running, but the uncertainty of load fluctuation and many influencing factors increase the difficulty of forecasting. Therefore, this article puts forward a multi-energy load prediction approach of the IES, which combines the fennec fox optimization algorithm (FFA) and hybrid kernel extreme learning machine. Firstly, the comprehensive weight method is used to combine the entropy weight method and Pearson correlation coefficient, fully considering the information content and correlation, selecting the key factors affecting the prediction, and ensuring that the input features can effectively modify the prediction results. Secondly, the coupling relationship between the multi-energy load is learned and predicted using the hybrid kernel extreme learning machine. At the same time, the FFA is used for parameter optimization, which reduces the randomness of parameter setting. Finally, the approach is utilized for the measured data at Arizona State University to verify its effectiveness in multi-energy load forecasting. The results indicate that the mean absolute error (MAE) of the proposed method is 0.0959, 0.3103 and 0.0443, respectively. The root mean square error (RMSE) is 0.1378, 0.3848 and 0.0578, respectively. The weighted mean absolute percentage error (WMAPE) is only 1.915%. Compared to other models, this model has a higher accuracy, with the maximum reductions on MAE, RMSE and WMAPE of 0.3833, 0.491 and 2.8138%, respectively.

Rapid identification and localization of dry bulk cargo hoppers are currently core issues in the automation control of gantry cranes at dry bulk terminals. The current conventional method relies on LiDAR systems for the identification and positioning of bulk unloading hoppers. However, this approach is complex and costly. In contrast, GPS-based positioning solutions for bulk unloading hoppers are prone to damage due to the vibrations generated during the operation process. Therefore, in this paper, a hopper localization system based on monocular camera vision is proposed to locate the position of the bulk unloading hopper. The hopper identification and localization process are divided into three stages. The first stage uses the improved YOLOv5 model to quickly and roughly locate the hopper target. The second stage uses morphological geometrical features to locate the corner points of the hopper target. The third stage determines the three-dimensional coordinates of the hopper target by solving the position of the corner points in the world coordinate system through the PnP (Perspective-n-Point) algorithm. The experimental results show that the average positioning accuracy of the coordinates of the method is above 93%, demonstrating the accuracy and effectiveness of the method.

The coal mine’s underground heading roadway suffers from a lack of effective temporary support, which contributes to low efficiency and inadequate safety in excavation operations. This paper presents a novel approach for roadway excavation, support, and anchoring, utilizing the twin-link stepping temporary support method. To address the stability requirements of the roadway roof in this support method, a numerical model of the excavation face was developed using the BBM (Bonded Block Model) method in 3DEC 7.0 software. Through numerical simulation, the repeatability of the twin-link stepping temporary support process was assessed for various roadway roof rock types, thicknesses, and burial depths. By considering aspects such as roof fragmentation, roof convergence, and relative displacement between the direct roof and the bedrock, the range of roadway roof repeatability was determined. The proposed twin-link stepping temporary support process, along with its applicable roof conditions, establishes a theoretical foundation for implementing the parallel operation mode in coal mine underground heading roadways, thereby significantly enhancing safety and efficiency.

Increasing attention is being paid to the application potential of multi-functional reconfigurable metamaterials in intelligent communication, sensor networks, homeland security, and other fields. A polarization-independent multi-functional reconfigurable metasurface based on doped vanadium dioxide (VO2) is proposed in this paper. It can be controlled to switch its function among three working modes: electromagnetically induced absorption (EIA), electromagnetically induced transparency (EIT), and asymmetrical absorption. In addition, deep learning tools have greatly accelerated the design of relevant devices. Such devices and the method proposed in this paper have important value in the field of intelligent reconfigurable metamaterials, communication, and sensing.

A battery track engineering vehicle faces challenges such as derailment and other safety concerns when navigating an R20m minimum radius curve, primarily owing to its low vertical and horizontal stabilities. To address these issues, a methodology integrating genetic optimization algorithms with a rigid and flexible coupled multi-body dynamics simulation is proposed to optimize the primary suspensions of the bogie of the vehicle. Initially, a multi-objective optimization model combining rigid and flexible coupled multi-body dynamics of battery track engineering vehicles with a genetic optimization algorithm was formulated. Subsequently, the optimal Latin hypercube design was applied to analyze the sensitivity of vertical and horizontal stability to various suspension parameters. Finally, a non-dominated sorting genetic algorithm (NSGA-II) and an archive-based micro genetic algorithm (AMGA) were applied to optimize the primary suspensions to enhance stability. Consequently, a set of optimal suspension parameter combinations was obtained. A notable enhancement was observed in the lateral stability of the optimized battery track engineering vehicles by 23.33% and in the vertical stability by 3.5% when traversing the R20m minimum radius curve, thereby establishing a theoretical foundation for further improving the running safety of railway vehicles and resolving the shortcomings of less research on the smallest radius curve.

Background: The prediction of fluid responsiveness in critical patients helps clinicians in decision making to avoid either under- or overloading of fluid. This study was designed to determine whether lung recruitment maneuver (LRM) would have an effect on the predictability of fluid responsiveness by the changes of hemodynamic parameters in pediatric patients who were receiving lung-protective ventilation and one-lung ventilation (OLV). Methods: A total of 34 children, aged 1–6 years old, scheduled for heart surgeries via right thoracotomy were enrolled. Patients were anesthetized and OLV with lung-protection ventilation settings was established, and then, positioned on left lateral decubitus. LRM and volume expansion (VE) were performed in sequence. Heart rate (HR), systolic arterial pressure (SAP), mean arterial pressure (MAP) diastolic arterial pressure (DAP), stroke volume (SV), stroke volume variation (SVV), and pulse pressure variation (PPV) were recorded via an A-line based monitor system at the following time points: before and after LRM (T1 and T2) and before and after VE (T3 and T4). An increase in stroke volume (SV) or mean arterial pressure (MAP) of ≥10% following fluid loading identified fluid responders. The predictability of fluid responsiveness by the changes of SV (ΔSVLRM) and MAP (ΔMAPLRM) after LRM and VE were statistically evaluated by receiver operating characteristic curves [area under the curves (AUC)]. Results: SVs in all patients were significantly decreased after LRM (p < 0.01) and then, increased and returned to baseline after VE (p < 0.01). In total, 16 out of 34 patients who were fluid responders had significantly lower SV after LRM compared to that in fluid non-responders. The area under the receiver operating characteristic curves for ΔSVLRM was 0.828 (95% confidence interval [CI], 0.660 to 0.935; p < 0.001) and it indicated that ΔSVLRM was able to predict the fluid responsiveness of pediatric patients. MAPs in all patients were also decreased significantly after LRM, and 12 of them fell into the category of fluid responders after VE. Statistically, ΔMAPLRM did not predict fluid responsiveness when LRM was considered as an influential factor (p = 0.07). Conclusions: ΔSVLRM, but not ΔMAPLRM, showed great reliability in the prediction of the fluid responsiveness following VE in children during one-lung ventilation with lung-protective settings. Trial registration: ChiCTR2300070690.

To explore the contamination status and identify the source of the heavy metals in the sediments in the major inflow rivers of Dianchi Lake in China, sediment samples were collected and analyzed. Specifically, the distribution, source, water quality, and health risk assessment of the heavy metals were analyzed using correlation analysis (CA), principal component analysis (PCA), the heavy metal contamination factor (Cf), the pollution load index (PLI), and the potential ecological risk index (PERI). Additionally, the chemical fractions were analyzed for mobility characteristics. The results indicate that the average concentration of the heavy metals in the sediment ranked in the descending order of Zn > Cr > Cu > Pb > As > Ni > Cd > Hg, and most of the elements existed in less-mobile forms. The Cfwas in the order of Hg > Zn > Cd > As > Pb > Cr > Ni; the accumulation of Hg, Zn, Cd, and As was obvious. Although the spatial variability of the heavy metal contents was pronounced, the synthetical evaluation index of the PLI and PERI both reached a high pollution level. The PCA and CA results indicate that industrial, transportation, and agricultural emissions were the dominant factors causing heavy metal pollution. These results provide important data for improving water resource management efficiency and heavy metal pollution prevention in Dianchi Lake.

The frequency of forest fires has increased dramatically due to climate change. The occurrence of forest fires affects the carbon and nitrogen cycles and react to climate change to form a positive feedback mechanism. These effects further impact the distribution of microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) and the soil microbial community structure. In addition, permafrost degradation can significantly affect the microorganisms in the soil. Based on these findings, this review examines the effects of fire intensity and post-fire recovery time on permafrost, the soil microbial community, MBC, MBN, and their interrelationships. This review demonstrated that (1) fires alter the condition of surface vegetation, reduce the organic layer thickness, redistribute snow, accelerate permafrost degradation, and even lead to permanent changes, where the restoration of the pre-fire state would require several decades or even centuries; (2) soil microbial community structure, soil MBC, and MBN negatively correlate with fire intensity, and the effects become more pronounced with increasing fire intensity; and (3) the structural diversity and stability of the soil microbial community were improved with time, and the amount of MBC and MBN increases as the years after a fire go by; it would still take more than ten years to recover to the pre-fire level. However, the relationship between permafrost degradation and soil microbes after forest fires is still unclear due to a lack of quantitative research on the mechanisms underlying the changes in soil microorganisms resulting from fire-induced permafrost degradation. Therefore, expanding quantitative studies and analyses of the mechanisms of interactions between forest fires, permafrost, and soil microorganisms can provide a scientific basis for understanding ecosystem carbon pools and dual-carbon targets in Arctic–boreal permafrost regions.

Air pollution severely threatens people’s health and sustainable economic development. In the era of the digital economy, modern information technology is profoundly changing the way governments govern, the production mode of enterprises, and the living behavior of residents. Whether digital technology can bring ecological welfare needs to be further studied. Based on panel data from 269 Chinese cities from 2006 to 2021, this study empirically examines the impact of digital technology on air pollution by using the two-way fixed effect model. The results show that digital technology will significantly reduce the concentration of fine particles in the air and help protect the atmospheric environment. The results are still valid after using the interactive fixed effect model and the two-stage least square method after the robustness test and causality identification. Digital technology can also reduce the air pollution by promoting green innovation, improving energy efficiency, and easing market segmentation. The effect of digital technology on reducing the concentration of fine particles in the air is heterogeneous. Digital technology plays a more substantial role in reducing pollution in resource-based cities and areas with a high degree of modernization of the commodity supply chain. The positive effect of digital technology in reducing air pollution is affected by the amount of air pollutants emitted. When the concentration of PM2.5 in the air is high, the role of digital technology in protecting the atmosphere will be strongly highlighted. This research is a beneficial exploration of protecting the atmospheric environment by using digital technology while building an ecological civilization society. The conclusion will help urban managers, the public, and business operators entirely use modern equipment such as 5G, remote sensing, and the Internet of Things in their respective fields to protect the atmospheric environment.

Rice production in the Anhui province is threatened by fungal diseases. We obtained twenty-five fungal isolates from rice and wild rice leaves showing leaf spot disease collected along the Yangtze River. A phylogenetic analysis based on internal transcribed spacer (ITS), translation elongation factor 1 alpha (TEF1-α), and beta tubulin (TUB2) sequences revealed one isolate (SS-2-JB-1B) grouped with Nigrospora sphaerica, one (QY) with Nigrospora chinensis, twenty-two with Nigrospora oryzae, and one isolate (QY-2) grouped in its own clade, which are related to but clearly different from N. oryzae. Nineteen tested isolates, including sixteen strains from the N. oryzae clade and the three isolates of the other three clades, caused disease on detached rice leaves. The three isolates that did not belong to N. oryzae were also able to cause disease in rice seedlings, suggesting that they were rice pathogens. Isolate QY-2 differed from the other isolates in terms of colony morphology, cell size, and susceptibility to fungicides, indicating that this isolate represents a new species that we named Nigrospora anhuiensis. Our analysis showed that N. sphaerica, N. chinensis, and the new species, N. anhuiensis, can cause rice leaf spot disease in the field. This research provides new knowledge for understanding rice leaf spot disease.

The gas sensitivity of the W defect in WS2 (VW/WS2) to five toxic gases—HCHO, CH4, CH3HO, CH3OH, and CH3CH3—has been examined in this article. These five gases were adsorbed on the VW/WS2 surface, and the band, density of state (DOS), charge density difference (CDD), work function (W), current–voltage (I–V) characteristic, and sensitivity of adsorption systems were determined. Interestingly, for HCHO-VW/WS2, the energy level contribution of HCHO is closer to the Fermi level, the charge transfer (B) is the largest (0.104 e), the increase in W is more obvious than other adsorption systems, the slope of the I–V characteristic changes more obviously, and the calculated sensitivity is the highest. To sum up, VW/WS2 is more sensitive to HCHO. In conclusion, VW/WS2 has a great deal of promise for producing HCHO chemical sensors due to its high sensitivity and selectivity for HCHO, which can aid in the precise and efficient detection of toxic gases.

This paper presents an in-depth analysis of the robust optimization of the China–Europe freight train transportation organization under uncertain cargo transportation demand. The study commences by constructing a robust optimization model tailored for specific environments, which is further extended to address the complexities of uncertain freight demand. A notable aspect of this research is the adoption of an innovative approach to manage the uncertainties in freight transportation demand at each node, employing a box-type uncertainty set distribution. This methodology allows for an effective and balanced optimization strategy that accommodates the dynamic nature of demand fluctuations. The research findings underscore that increased robustness in the optimization model is associated with higher transportation costs within the China–Europe freight train network, especially under conditions of variable demand. The model demonstrates a preference for adjusting transportation costs to maintain the stability of the transportation scheme, particularly in response to wider variations in cargo demand. This strategy, prioritizing cost-effectiveness and adaptability, highlights the importance of a comprehensive approach to managing demand uncertainties. The significant contributions of this paper include the development of a robust, economically viable, and efficient transportation organization plan for China–Europe freight trains, equipped to navigate the challenges posed by uncertain cargo demand at the originating nodes. The study’s emphasis on the practical application of advanced optimization techniques and uncertainty management methods marks a notable advancement in the field of freight train transportation. Additionally, the paper suggests avenues for further research in the intricate and evolving landscape of freight transportation, providing valuable insights for future studies.

In recent decades, with the rising living standards of rural China, the amount and volume of household waste has increased continuously, causing serious environmental and human health risks. Effective garbage classification reduces garbage volume, decreases the difficulty of garbage disposal, and facilitates the recycling of resources, thereby improving environmental quality. Domestic garbage classification (DGC) has been practiced frequently in developed countries and is now at a relatively mature stage. There is no robust model for garbage classification available globally as of yet, and each country has its policy frameworks to reduce, recycle, and reuse (3R) garbage. Little attention has been paid to knowing whether and to what extent incentive-based policies called “rewards and punishments” improve garbage classification and further help achieve targets of sustainable development goals (SDGs). Recently, developing countries, like China, have begun to incorporate DGC into their laws and promote enforcement measures in a few cities. However, empirical studies on residents’ willingness to accept DGC punishments and rewards are still relatively scarce and a hot topic of global scientific discussion. To enrich the knowledge, this study collected datasets from 9983 valid questionnaires from east China (16 selected independent variables), and analyzed the key factors affecting residents’ acceptance of punishments and rewards, employing logit models. The results found that the level of education plays an important role for residents that are more inclined to accept DGC rewards and punishments. Moreover, farmers were insensitive to DGC rewards but very sensitive and unsupportive of punishments, and the hardware facilities of the quarter had a greater impact on residents’ willingness to accept DGC rewards and punishments. Findings recommend that rewards be the main focus and punishments be supplemented, thus the incentive-based policies should be improved through law enforcement and implementation of robust policy frameworks in order to promote residents’ acceptance of rewards and punishments and to accelerate better garbage classification.

Flexible capacity applications demand a large energy storage density and high breakdown electric field strength of flexible films. Here, P(VDF-HFP) with ultra-thin Al2O3 nanosheet composite films were designed and fabricated through an electrospinning process followed by hot-pressing into a sandwich structure. The results show that the insulating ultra-thin Al2O3 nanosheets and the sandwich structure can enhance the composites’ breakdown strength (by 24.8%) and energy density (by 30.6%) compared to the P(VDF-HFP) polymer matrix. An energy storage density of 23.5 J/cm3 at the ultrahigh breakdown strength of 740 kV/mm can be therefore realized. The insulating test and phase-field simulation results reveal that ultra-thin nanosheets insulating buffer layers can reduce the leakage current in composites; thus, it affects the electric field spatial distribution to enhance breakdown strength. Our research provides a feasible method to increase the breakdown strength of ferroelectric polymers, which is comparable to those of non-ferroelectric polymers.

This paper proposes a temporary support system for improving the efficiency and safety of underground roadway excavation in coal mines. Firstly, this study establishes a calculation model for the initial supporting force of the excavation of roadway temporary support and a gray system-based automatic prediction model for the initial supporting force level, based on the mechanism of temporary support controlling the roof. These models enable the prediction of the required initial supporting force at different locations along the roadway’s temporary support area, thereby providing a basis for controlling the initial supporting force of the temporary support system. To achieve efficient and adaptive control of the initial supporting force of temporary supports at different locations, this study designs a support force controller based on Simulated Annealing Particle Swarm Optimization Proportional-Integral-Derivative (SAPSO-PID). This study establishes a mathematical model for the hydraulic cylinder pressure system controlled by the temporary support overflow valve and conducts a stability analysis and model verification. The study constructs a simulation control system for the initial supporting force based on SAPSO-PID using the combined simulation platform of AMESim and Matlab. The simulation results demonstrate that the proposed support force control system efficiently achieves adaptive control of the initial supporting force of temporary supports. An experimental system in the underground roadway of a coal mine is constructed to validate the results of the simulation analysis.

Fish body length is an essential monitoring parameter in aquaculture engineering. However, traditional manual measurement methods have been found to be inefficient and harmful to fish. To overcome these shortcomings, this paper proposes a non-contact measurement method that utilizes binocular stereo vision to accurately measure the body length of fish underwater. Binocular cameras capture RGB and depth images to acquire the RGB-D data of the fish, and then the RGB images are selectively segmented using the contrast-adaptive Grab Cut algorithm. To determine the state of the fish, a skeleton extraction algorithm is employed to handle fish with curved bodies. The errors caused by the refraction of water are then analyzed and corrected. Finally, the best measurement points from the RGB image are extracted and converted into 3D spatial coordinates to calculate the length of the fish, for which measurement software was developed. The experimental results indicate that the mean relative percentage error for fish-length measurement is 0.9%. This paper presents a method that meets the accuracy requirements for measurement in aquaculture while also being convenient for implementation and application.

Urban highway tunnels are frequent accident locations, and predicting and analyzing road conditions after accidents to avoid traffic congestion is a key measure for tunnel traffic operation management. In this paper, 200 traffic accident data from the YingTian Street Tunnel in Nanjing city were analyzed and encoded to extract the main factors affecting tunnel traffic conditions from three aspects: time, traffic flow, and tunnel environment. Next, graph convolution long short-term memory networks were used to predict and fill in missing traffic flow data. Finally, seven independent variables selected by Pearson correlation analysis were input into the constructed BP neural network and random forest model to predict tunnel traffic conditions during accidents and accident duration. Experimental results show that the accuracy of random forest and BP neural networks in predicting traffic flow is 83.39% and 82.94%, respectively, and that the absolute error of the two models in predicting accident duration is 75% and 60% within 25 min, respectively. Both models perform well in predicting traffic conditions, and the random forest models perform better in terms of robustness and generalization in predicting crash duration. The experimental results have important implications for tunnel operation management during accidents.

Coral mud is a special rock and sediment mass and is widely distributed in the South China Sea. Studying the deformation of coral mud is important for infrastructure development in the South China Sea. When choosing a model to describe the long-term deformation of coral mud, it is difficult for a simple nonlinear deformation model to accurately and universally describe the complex deformation processes of the sediment; a complex model is too time-consuming and difficult to apply to practical engineering. In this article, based on a classical element model, the Burgers model, certain elements are modified in combination with one-dimensional oedometer tests under normally consolidated situations. Then, combined with an unloading and reloading test, the modified Burgers model is further improved, and a modified Burgers model considering stress history is obtained. The modified Burgers model considering the stress history only has four parameters, all of which have practical physical significance, which makes the model easy to use. Different loading times and cyclic loading and unloading tests prove that the model has good stability and can, not only simulate the deformation characteristics of sediment, but can also provide good variation rules for the parameters.

RNA-binding proteins (RBPs) can regulate multiple pathways by binding to RNAs, playing a variety of functions, such as localization, stability, and immunity. In recent years, with the development of technology, researchers have discovered that RBPs play a key role in the N6-methyladenosine (m6A) modification process. M6A methylation is the most abundant form of RNA modification in eukaryotes, which is defined as methylation on the sixth N atom of adenine in RNA. Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) is one of the components of m6A binding proteins, which plays an important role in decoding m6A marks and performing various biological functions. IGF2BP3 is abnormally expressed in many human cancers, often associated with poor prognosis. Here, we summarize the physiological role of IGF2BP3 in organisms and describe its role and mechanism in tumors. These data suggest that IGF2BP3 may be a valuable therapeutic target and prognostic marker in the future.

Several observational studies have confirmed that the severe acute respiratory syndrome coronavirus2 (SARS-CoV-2) might substantially affect the gastrointestinal (GI) system by replicating in human small intestine enterocytes. Yet, so far, no study has reported the effects of inactivated SARS-CoV-2 virus vaccines on gut microbiota alterations. In this study, we examined the effects of the BBIBP-CorV vaccine (ChiCTR2000032459, sponsored by the Beijing Institute of Biological Products/Sinopharm), on gut microbiota. Fecal samples were collected from individuals whoreceived two doses of intramuscular injection of BBIBP-CorV and matched unvaccinated controls. DNA extracted from fecal samples was subjected to 16S ribosomal RNA sequencing analysis. The composition and biological functions of the microbiota between vaccinated and unvaccinated individuals were compared. Compared with unvaccinated controls, vaccinated subjects exhibited significantly reduced bacterial diversity, elevated firmicutes/bacteroidetes (F/B) ratios, a tendency towards Faecalibacterium-predominant enterotypes, and altered gut microbial compositions and functional potentials. Specifically, the intestinal microbiota in vaccine recipients was enriched with Faecalibacterium and Mollicutes and with a lower abundance of Prevotella, Enterococcus, Leuconostocaceae, and Weissella. Microbial function prediction by phylogenetic investigation of communities using reconstruction of unobserved states (PICRUSt) analysis further indicated that Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in carbohydrate metabolism and transcription were positively associated with vaccine inoculation, whereas capacities in neurodegenerative diseases, cardiovascular diseases, and cancers were negatively affected by vaccines. Vaccine inoculation was particularly associated with gut microbiota alterations, as was demonstrated by the improved composition and functional capacities of gut microbiota.

Improving the digital economy and environmental governance efficiency are important methods for current high-quality economic development. Based on the panel data of 11 cities in Zhejiang, on the eastern coast of China, fine particulate matter smaller than a 2.5 μm (PM2.5) environmental efficiency (PMEE) was measured by the undesirable output Slack-Based Measure-Data Envelopment Analysis (SBM-DEA) model. The fixed effect regression model, the divergences in the difference model and other empirical methods were obtained to test the driving mechanism of social-economic factors on the PMEE. The results showed that: (1) the concentration of PM2.5 was continually decreasing, and environmental quality experienced a continuous improvement in Zhejiang province in the observation period, although cities such as Hangzhou, Jiaxing and Shaoxing have relatively severe PM2.5 pollution. (2) The total average value of PMEE in Zhejiang was 0.6430 over the observation period, while there was still a lot of room for improvement when compared to the production frontier. Additionally, PMEE in each city showed a fluctuating growth trend. Cities with a higher PMEE were mainly Zhoushan, Hangzhou and Ningbo. (3) The level of the digital economy had a positive role in promoting the PMEE, which was statistically significant. The level of pollution control and technological innovation also had a significantly positive effect. However, the ratio of the industrial output value to the gross domestic product (GDP) presented a negative effect on the PMEE. In the future, it is suggested that the development of the urban digital economy should be accelerated in an all-around way to improve the efficiency of government pollution control and to improve the technical efficiency of PM2.5 via innovative technological progress.

The development of nanosystems, which can photooxygenate amyloid-β (Aβ), detect the Tau protein, and inhibit effectively the Tau aggregation, is increasingly important in the diagnosis and therapy of Alzheimer’s disease (AD). Herein, UCNPs-LMB/VQIVYK (UCNPs: upconversion nanoparticles, LMB: Leucomethylene blue, and VQIVYK: Biocompatible peptide) is designed as a HOCl-controlled released nanosystem for AD synergistic treatment. Under exposure to high levels of HOCl, the released MB from UCNPs-LMB/VQIVYK will produce singlet oxygen (1O2) under red light to depolymerize Aβ aggregation and reduce cytotoxicity. Meanwhile, UCNPs-LMB/VQIVYK can act as an inhibitor to decrease Tau-induced neurotoxicity. Besides, UCNPs-LMB/VQIVYK can be used for upconversion luminescence (UCL) due to its unexceptionable luminescence properties. This HOCl-responsive nanosystem offers a new therapy for AD treatment.

The magmatic process within upper crust encompasses various contents such as the transition between magmatic and hydrothermal systems and changes in oxygen fugacity (ƒO2), which ultimately play key roles in the formation of porphyry Cu deposits (PCDs). However, tracing these magmatic processes, especially in porphyry systems, is not an easy task. This study reported the detailed process of magmatic fluid exsolution and systematical variation of magmatic ƒO2 within the upper crust of a Tongchang–Chang’anchong porphyry Cu deposit, based on detailed investigations of mineral crystallization sequences and compositional features of the minerals in the fertile porphyries. Results indicate that the fertile porphyries show a high initial ƒO2, with ΔFMQ ≥ +3.0 (ΔFMQ is the deviation of logƒO2 from the fayalite–magnetite–quartz (FMQ) buffer). The magmatic ƒO2 (ΔFMQ) continued to decrease to ~+2 until fluid exsolution occurred at ~790 °C due to wall-rock contamination. The magmatic fluid exsolution process caused a temporary increase in the ƒO2 (to ΔFMQ = ~+3.4). The high magmatic ƒO2 during this process (790–750 °C) resulted in a higher content of ore-forming materials in the exsolved magmatic fluid. When the temperature dropped below 750 °C, the magmatic ƒO2 began to continuously decrease and eventually reached ΔFMQ = ~+0.6. The lower magmatic ƒO2 hindered the further migration of ore-forming materials through the exsolved fluid during this process (< 750 °C). Results of this study indicate that the initial magma during the upper crustal magmatic process of PCDs generally has a high ƒO2, and the contamination of reduced components can significantly decrease the magmatic ƒO2. The early magmatic fluid exsolution process can maintain a high magmatic ƒO2 condition, thereby efficiently extracting ore-forming minerals and producing ore-forming fluids, which is the key to the formation of PCDs. The latter continuous decrease in magmatic ƒO2 during the fluid exsolution process may be the reason preventing the Tongchang–Chang’anchong porphyry Cu deposit to form a giant PCD.

Hepatocellular carcinoma (HCC) is one of the most common cancers and the fourth leading cause of death in men. YEATS domain containing 2 (YEATS2) gene encodes a scaffolding subunit of the ATAC complex. We found that YEATS2 was upregulated in HCC tissues and was associated with a poor prognosis. However, the role of YEATS2 in HCC remains unclear. The purpose of this study was to investigate the effect of YEATS2 on the progression of HCC and to elucidate its related mechanisms. We found that overexpression of YEATS2 promoted tumor cell proliferation, migration, and invasion through the PI3K/AKT signaling pathway and regulation of extracellular matrix. These findings help to understand the role of YEATS2 in HCC, and YEATS2 may become a new target for HCC therapy.

Adulteration of meat with carnivorous animals (such as cats, dogs, foxes, and minks) can cause ethical problems and lead to disease transmission; however, DNA quantitative methods for four carnivorous species in one tube reaction are still rare. In this study, a carnivore-specific nuclear DNA sequence that is conserved in carnivorous animals but has base differences within the sequence was used to design universal primers for its conserved region and corresponding species-specific probes for the hypervariable region. A novel universal primer multiplex real-time PCR (UP-M-rtPCR) approach was developed for the specific identification and quantitation of cat, dog, fox, and mink fractions in a single reaction, with a 0.05 ng absolute limit of detection (LOD) and 0.05% relative LOD. This approach simplifies the PCR system and improves the efficiency of simultaneous identification of multiple animal-derived ingredients in meat. UP-M-rtPCR showed good accuracy (0.48–7.04% relative deviation) and precision (1.42–13.78% relative standard deviation) for quantitative analysis of cat, dog, fox, and mink DNA as well as excellent applicability for the evaluation of meat samples.

With the modernization of GLONASS, four M+ and two K satellites are able to broadcast code-division multiple-access signals at a G3 frequency. The evaluation of the G3 frequency is necessary, among which the satellite-induced code pseudorange variation is one of the most important indicators. Using the code-minus-carrier (CMC) combination, it was found that the magnitude of the code pseudorange variations at the G3 frequency is about 1 m, which is primarily caused by the fact that G3 is transmitted from a different antenna, the same as G1 and G2. However, different from BDS-2 medium Earth orbit and inclined geo-synchronous orbit satellites, the code pseudorange variations at the GLONASS G3 frequency have a very weak relationship with the elevation angle, while a strong correlation exists with the time series, by using wavelet transformation and correlation analysis. Validation is carried out using a single-site model and a continuous multi-site model over 24 h, and the correction performance of these two models is comparable. The systematic deviation of the CMC and Melbourne–Wübbena combinations are significantly corrected, so only random errors remain. With a more concentrated distribution of the pseudorange residuals of single point positioning, the standard deviation of the pseudorange residuals is reduced.

The treatment of metal-contaminated sediment generated in environmental dredging projects often requires both reduction and remediation, and the electric field has good application prospects in the integration of reduction and remediation. In this study, based on the electro-osmosis, vacuum, and vacuum electro-osmosis methods, a detachable test system was made. Experiments of the three methods were carried out independently on the reduction and remediation of dredged sediment from Tai Lake under pollution-free and Cu-contaminated conditions. The results show that copper contamination weakens the effect of reduction, and the production of copper precipitates makes the soil more prone to cracking and blocking drainage channels, which has the greatest impact on the electro-osmosis method. In terms of copper concentration, vacuum electro-osmosis achieves the transport and discharge of contaminants, and has the best remediation effect. The removal rates at the anode and cathode are 45.1% and 50.0%, respectively. A correlation model based on electrical conductivity, moisture content, and contaminant concentration was established to facilitate the determination of contaminant concentrations in actual projects. Electro-migration plays a dominant role in the remediation process, and the reduction affects the electric field distribution and, thus, the migration efficiency.

Using first principles based on density functional theory (DFT), the CO, NH3, NO, and NO2 gas adsorbed on intrinsic Graphite-like ZnO (g−ZnO) and vacancy-deficient g−ZnO were systematically studied. For intrinsic g−ZnO, the adsorption energy of NH3, NO, and NO2 adsorption defective g−ZnO systems increased significantly due to the introduction of Zn vacancy (VZn). Especially, for NH3, NO, and NO2 adsorbed Zn-vacancy g−ZnO (VZn/g−ZnO) systems increased to 1.366 eV, 2.540 eV and 2.532 eV, respectively. In addition, with the introduction of vacancies, the adsorption height of the gases adsorbed on VZn/g−ZnO system is significantly reduced, especially the adsorption height of the NH3 adsorbed on VZn/g−ZnO system is reduced to 0.686 Å. It is worth mentioning that the introduction of O-vacancy (VO) significantly enhances the charge transfer between NO or NO2 and VO/g−ZnO. This suggest that the defective g−ZnO is more suitable for detecting NH3, NO and NO2 gas. It is interesting to note that the adsorption of NO and NO2 gases gives rise to magnetic moments of 1 μB and 0.858 μB for g−ZnO, and 1 μB and 1 μB for VO/g−ZnO. In addition, VZn induced 1.996 μB magnetic moments for intrinsic g−ZnO, and the CO, NH3, NO and NO2 change the magnetic of VZn/g−ZnO. The adsorption of NO2 causes the intrinsic g−ZnO to exhibit metallic properties, while the adsorption of NH3 gas molecules causes VZn/g−ZnO also to show metallic properties. The adsorption of NO and NO2 causes VZn/g−ZnO to display semi-metallic properties. These results facilitate the enrichment of defect detection means and the design of gas detection devices.

Fluid shear stress (FSS) facilitates bone remodeling by regulating osteogenic differentiation, and extracellular matrix maturation and mineralization. However, the underlying molecular mechanisms of how mechanical stimuli from FSS are converted into osteogenesis remain largely unexplored. Here, we exposed MC3T3-E1 cells to FSS with different intensities (1 h FSS with 0, 5, 10, and 20 dyn/cm2 intensities) and treatment durations (10 dyn/cm2 FSS with 0, 0.5, 1, 2 and 4 h treatment). The results demonstrate that the 1 h of 10 dyn/cm2 FSS treatment greatly upregulated the expression of osteogenic markers (Runx2, ALP, Col I), accompanied by AnxA6 activation. The genetic ablation of AnxA6 suppressed the autophagic process, demonstrating lowered autophagy markers (Beclin1, ATG5, ATG7, LC3) and decreased autophagosome formation, and strongly reduced osteogenic differentiation induced by FSS. Furthermore, the addition of autophagic activator rapamycin to AnxA6 knockdown cells stimulated autophagy process, and coincided with more expressions of osteogenic proteins ALP and Col I under both static and FSS conditions. In conclusion, the findings in this study reveal a hitherto unidentified relationship between FSS-induced osteogenic differentiation and autophagy, and point to AnxA6 as a key mediator of autophagy in response to FSS, which may provide a new target for the treatment of osteoporosis and other diseases.

Three new layered mixed metal phosphonates [CoMg(notpH2)(H2O)2]ClO4·nH2O (CoMg·nH2O), [Co2Sr2(notpH2)2(H2O)5](ClO4)2·nH2O (CoSr·nH2O), and [CoBa(notpH2)(H2O)1.5]ClO4 (CoBa) were synthesized by reacting a tripodal metalloligand CoIII(notpH3) [notpH6 = C9H18N3(PO3H2)3] with alkaline earth metal ions. Along with an increase in the radius of the alkaline earth metal ions, the 6-coordinate {MgO6}, 7-coordinate {SrO7}, and 9-coordinate {BaO9} geometries are the distorted octahedron, capped triangular prism, and tricapped triangular prism, respectively. Consequently, the metalloligand Co(notpH2)− adopts variable coordination modes to bind the alkaline earth metal nodes, forming diverse layer topologies in the three mixed metal phosphonates. The AC impedance measurements revealed that the proton conductivities at 25 °C and 95% relative humidity (RH) follow the sequence: CoMg·nH2O > CoSr·nH2O > CoBa. As expected, CoMg·nH2O exhibits a 28-fold enhanced value for proton conductivity (4.36 × 10−4 S cm−1) compared with the previously reported isostructural compound, CoCa·nH2O, at 25 °C and 95% RH due to the greater Lewis acid strength of Mg(II) lowering the pKa of the coordinated water.

Malignant tumors are always a critical threat to human health, with complex pathogenesis, numerous causative factors, and poor prognosis. The features of cancers, such as gene mutations, epigenetic alterations, and the activation and inhibition of signaling pathways in the organism, play important roles in tumorigenesis and prognosis. MicroRNA (miRNA) enables the control of various molecular mechanisms and plays a variety of roles in human cancers, such as radiation sensitivity and tumor immunity, through the regulation of target genes. MiR-149-5p participates in the process and is closely related to lipogenesis, the migration of vascular endothelial cells, and the expression of stem-cell-related proteins. In recent years, its role in cancer has dramatically increased. In this review, we summarize the regular physiological roles of miRNAs, specifically miR-149-5p, in the organism and discuss the tumor-suppressive or oncogenic roles of miR-149-5p in different human cancers with respect to signaling pathways involved in regulation. Possible clinical applications of miR-149-5p in future targeted therapies and prognosis improvement in oncology are suggested.

The process of ubiquitination regulates the degradation, transport, interaction, and stabilization of substrate proteins, and is crucial for cell signal transduction and function. TNF receptor-associated factor 4, TRAF4, is a member of the TRAF family and is involved in the process of ubiquitination as an E3 ubiquitin protein ligase. Here, we found that TRAF4 expression correlates with glioma subtype and grade, and that TRAF4 is significantly overexpressed in glioblastoma and predicts poor prognosis. Knockdown of TRAF4 significantly inhibited the growth, proliferation, migration, and invasion of glioblastoma cells. Mechanistically, we found that TRAF4 only interacts with the Tudor domain of the AKT pathway activator SETDB1. TRAF4 mediates the atypical ubiquitination of SETDB1 to maintain its stability and function, thereby promoting the activation of the AKT pathway. Restoring SETDB1 expression in TRAF4 knockdown glioblastoma cells partially restored cell growth and proliferation. Collectively, our findings reveal a novel mechanism by which TRAF4 mediates AKT pathway activation, suggesting that TRAF4 may serve as a biomarker and promising therapeutic target for glioblastoma.

Despite the increasing interest in understanding the mechanism of household livelihood decisions to increase household livelihood welfare, the combined role of livelihood capitals and human settlements in livelihood decisions is unclear. Therefore, in this paper we carried out extensive empirical research to explore the causal pathway between human settlements (including infrastructure, public services, and social governance) and livelihood capitals (including human, natural, physical, financial, and social capitals) on agricultural land transfer, taking employment choices as an intermediary factor. On this basis, this study analyzed the regional differences in the decision-making mechanisms of agricultural land transfer behaviors in eastern, central, and western regions of China through a multi-group structural equation model. The results demonstrated that capital accumulation can directly increase the possibility of agricultural land inflow (β = 0.130, p < 0.01), but can indirectly reduce the dependence on agricultural land by stimulating non-agricultural employment (β = −0.613, p < 0.01). The improvement in human settlement promotes the agricultural land inflow (outside the western region) and indirectly enhances the willingness to enter into agriculture. The employment choices play a significant mediating role by strengthening the livelihood capitals and weakening human settlements. To achieve the intense agricultural development and sustainable development of rural areas, the improvement of both rural human settlements and household livelihood capitals should be considered.

Molecular doping is an excellent instrument to modify the electronic properties of two−dimensional materials. In our work, the structure and electronic properties of the adsorption systems of g−ZnO adsorbed by organic molecules (including Tetracyanoethylene (TCNE), Tetracyanoquinodimethane (TCNQ), and Tetrahydrofulvalene (TTF)) were investigated computationally using Density Functional Theory (DFT). The results showed that the TCNE and TCNQ, as electron receptors, doped the LUMO energy level above the valence band maximum (VBM) of the g−ZnO band structure, demonstrating effective p−type doping. The n−type doping of g−ZnO was obtained that the TTF molecules, as electron donors, doped the HOMO energy level below the conduction band minimum (CBM) of the band structure for g−ZnO. In addition, the TCNE, TCNQ, and TTF breathed additional holes or electrons into the monolayer g−ZnO, creating surface dipole moments between the g−ZnO and organic molecules, which caused work function to be adjustable, ranging from 3.871 eV to 5.260 eV. Our results prove that organic molecular doping was instrumental in improving the performance of g−ZnO−based nano−electronic devices, providing theoretical support for the fabrication of p−doping or n−doping nano−semiconductor components. The tunable range of field emission capability of g−ZnO−based electronic devices was also extended.

Photonic-based thermometers have been attracting intense research interest as a potential alternative to traditional electrical thermometers due to their physical and chemical stability and immunity to electromagnetic interference. However, due to the high requirements for the stability of the laser source, the existing studies on resolution are only theoretical predictions and do not include real-measured results. In this paper, we report on the fabrication and characterization of an on-chip silicon whispering-gallery-mode (WGM) ring resonator thermometer. The strip grating and the ring structure were fabricated on the silicon-on-insulator (SOI) substrate by two-step etching. The quality-factor (Q-factor), temperature sensitivity, and measurement range of the packaged device were 21,400, 42 pm/K, and 150 K, respectively. The real-measured temperature resolution of 2.9 mK was achieved by virtue of the power and polarization stabilization of the laser source.

This paper focuses on the opportunity to use multiple star trackers to help space situational awareness and space surveillance. Catalogs of space debris around Earth are usually based on ground-based measurements, which rely on data provided by ground-based radar observations and ground-based optical observations. However, space-based observations offer new opportunities because they are independent of the weather and the circadian rhythms to which the ground system is subjected. Consequently, space-based optical observations improve the possibility of space debris detection and cataloging. This work deals with a feasibility study of an innovative strategy, which consists of the use of a star sensor with a dedicated algorithm to run directly on board. This approach minimizes the impact on the original mission of the satellite, and on this basis, it has also the function of space debris monitoring. Therefore, theoretically, every satellite with a star tracker can be used as a space surveillance observer. In this paper, we propose a multi-star space debris detecting and positioning method with constant geocentric observation. Using the multi-star tracker joint positioning method, the angle measurement data of the star tracker is converted into the spatial coordinates of the target. In addition, the Gaussian MMSE difference correction algorithm is used to realize the target positioning of multiple optical observations, and the spatial target position information of the multi-frame images is fused, thus completing the solution of the orbit equation. The simulation results show that the proposed method is sufficient to detect and position space debris. It also demonstrates the necessity and feasibility of cooperative network observation by multiple star trackers.

The evaporation of sessile droplets is not only a common occurrence in daily life, but it also plays a vital role in many scientific and industrial fields. However, most of the current research is focused on the evaporation of droplets in the air environment, where vapor transport is controlled by the diffusion model, but when the droplet evaporation is in its own pure vapor environment, the above model will no longer apply, and the evaporation will be dominated by kinetic theory. Thus the Hertz–Knudsen model can be applied to describe the evaporation kinetics. However, in most of the studies, it is assumed that the temperature distribution is uniform along the vapor-liquid interface of the droplet, but due to the evaporative cooling effect, this assumption is not correct in actual evaporation. In this paper, theoretical analysis and numerical simulation were combined to study the characteristics of droplet evaporation with multiphysics coupling. In the theoretical model, heat conduction in the droplet and substrate was coupled with vapor transport at the droplet surface. In the numerical simulation, internal thermocapillary flow and heat transfer of the droplet were coupled with vapor transport at the droplet surface. The effects of contact angle, thermocapillary convection, ambient pressure ratio, and substrate superheat on the droplet evaporation characteristics were quantitatively analyzed. It was found that the high substrate superheat or low ambient pressure ratio will enhance the droplet thermocapillary convection as well as evaporation rate. Furthermore, a critical contact angle was found; below this value, the droplet evaporation rate was inversely proportional to the contact angle, but upon this value, the trend was reversed. These findings have important implications for revealing the physical mechanism of kinetics-controlled droplet evaporation in a pure vapor environment.

To study the influence of the fractal distribution of particle size on the critical state characteristics of calcareous sand, a type of calcareous sand from a certain reef of the South China Sea was used in this study. For comparison, standard quartz sand was also used. A series of drained shear tests on the two sands were then conducted to investigate their critical state characteristics. It was demonstrated that the fractal dimension is suitable for characterizing the particle size distribution (PSD) of calcareous sand with different fine sand content. The critical state equation of sand proposed by Li and Wang (1998) is suitable for fitting the critical state line of calcareous sand. In the plane of deviatoric stress versus the effective confining pressure (q–p′ plane) and the plane of void ratio versus (p′/pa)α, the critical state lines of calcareous sand are always above those of quartz sand. The critical state lines of calcareous sand with different fractal dimensions in the q–p′ plane are unique. However, in the e–(p′/pa)α plane, the critical state lines appear to rotate anticlockwise as the fractal dimension increases. In addition, there is an “intersection” in the e–(p′/pa)α plane. Considering the influence of the fractal distribution of particle size, an expression for the critical state line of calcareous sand in the e–(p′/pa)α plane was proposed. The related constitutive model was also revised, where a complete set of model parameters suitable for modeling calcareous sand was provided.

Tubulin alpha 1b (TUBA1B) is an important microtubule isoform that is involved in the formation of the cytoskeleton. The objective of our study was to explore the potential of TUBA1B in predicting the prognosis of HCC and patients’ response to immunotherapy. Raw data was extracted from TCGA and GEO databases, and then HCCDB, TIMER, HPA, and GEPIA websites, as well as R software, were used to perform bioinformatics analysis to investigate the potential of TUBA1B as a prognostic and immunotherapeutic marker for hepatocellular carcinoma (HCC). We found that both TUBA1B mRNA and protein were highly expressed in HCC. TUBA1B was proved to be an independent prognostic predictor of HCC. Additionally, TUBA1B expression was associated with the infiltration of several immune cells in HCC. Moreover, TUBA1B was coexpressed with immune-related genes and immune checkpoints. Patients expressing high TUBA1B responded better to immune checkpoint inhibitor (ICI) therapy. GO and KEGG analyses revealed that TUBA1B may be involved in the processes of cell cycle, spliceosome, and DNA replication. In conclusion, TUBA1B is expected to be a prognostic and immunotherapeutic marker for HCC.

The strength of the soil–structure interface can be mobilised when subjected to cyclic loading. To capture the cyclic mobilisation of the soil–structure interface, an advanced elastoplastic constitutive model is developed within the framework of fractional plasticity, where no additional use of an additional plastic potential is required. Considering the influence of material state and soil fabric on the plastic response of the soil–structure interface, the state-dependent fractional order and hardening modulus are proposed. Further numerical simulation of the developed model shows that it can reasonably capture the mobilised strength and deformation of the soil–structure interface under cyclic loads.

The CHYR (CHY ZINC-FINGER AND RING FINGER PROTEIN) proteins have been functionally characterized in iron regulation and stress response in Arabidopsis, rice and Populus. However, their roles in soybean have not yet been systematically investigated. Here, in this study, 16 GmCHYR genes with conserved Zinc_ribbon, CHY zinc finger and Ring finger domains were obtained and divided into three groups. Moreover, additional 2–3 hemerythrin domains could be found in the N terminus of Group III. Phylogenetic and homology analysis of CHYRs in green plants indicated that three groups might originate from different ancestors. Expectedly, GmCHYR genes shared similar conserved domains/motifs distribution within the same group. Gene expression analysis uncovered their special expression patterns in different soybean tissues/organs and under various abiotic stresses. Group I and II members were mainly involved in salt and alkaline stresses. The expression of Group III members was induced/repressed by dehydration, salt and alkaline stresses, indicating their diverse roles in response to abiotic stress. In conclusion, our work will benefit for further revealing the biological roles of GmCHYRs.

Radiotherapy has been used for more than a hundred years to cure or locally control tumors. Regression of tumors outside of the irradiated field was occasionally observed and is known as the abscopal effect. However, the occurrence of systemic anti-tumor effects was deemed too rare and unpredictable to be a therapeutic goal. Recent studies suggest that immunotherapy and radiation in combination may enhance the abscopal response. Increasing numbers of cases are being reported since the routine implementation of immune checkpoint inhibitors, showing that combined radiotherapy with immunotherapy has a synergistic effect on both local and distant (i.e., unirradiated) tumors. In this review, we summarize pre-clinical and clinical reports, with a specific focus on the mechanisms behind the immunostimulatory effects of radiation and how this is enhanced by immunotherapy.

The strapdown inertial navigation system can provide the navigation information for the boom-type roadheader in the unmanned roadway tunneling working face of the coal mine. However, the complex vibration caused by the cutting process of the boom-type roadheader may result in significant errors of its attitude and position measured by the strapdown inertial navigation system. Thus, an error compensation method based on the vibration characteristics of the roadheader is proposed in this paper. In order to further analyze the angular and linear vibration of the fuselage, as the main vibration sources of the roadheader, the dynamic model of the roadheader is formulated based on the cutting load. Following that, multiple sub-samples compensation algorithms for the coning and sculling errors are constructed. Simulation experiments were carried out under different subsample compensation algorithms, different coal and rock characteristics, and different types of roadheader. The experimental results show that the proposed error compensation algorithm can eliminate the effect of the angular and linear vibration on the measurement accuracy. The coning and sculling error of the strapdown inertial navigation system can reduce at least 52.21% and 42.89%, respectively. Finally, a strapdown inertial navigation error compensation accuracy experiment system is built, and the validity and superiority of the method proposed in this paper are verified through calculation and analysis of the data collected on the actual tunneling work face.

Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human–robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined.

Smoking is a major risk factor for chronic obstructive pulmonary disease (COPD) and causes remodeling of the small airways. However, the exact smoke-induced effects on the different types of small airway epithelial cells (SAECs) are poorly understood. Here, using air–liquid interface (ALI) cultures, single-cell RNA-sequencing reveals previously unrecognized transcriptional heterogeneity within the small airway epithelium and cell type-specific effects upon acute and chronic cigarette smoke exposure. Smoke triggers detoxification and inflammatory responses and aberrantly activates and alters basal cell differentiation. This results in an increase of inflammatory basal-to-secretory cell intermediates and, particularly after chronic smoke exposure, a massive expansion of a rare inflammatory and squamous metaplasia associated KRT6A+ basal cell state and an altered secretory cell landscape. ALI cultures originating from healthy non-smokers and COPD smokers show similar responses to cigarette smoke exposure, although an increased pro-inflammatory profile is conserved in the latter. Taken together, the in vitro models provide high-resolution insights into the smoke-induced remodeling of the small airways resembling the pathological processes in COPD airways. The data may also help to better understand other lung diseases including COVID-19, as the data reflect the smoke-dependent variable induction of SARS-CoV-2 entry factors across SAEC populations.

A transparent clay manufactured using Carbopol® UltrezTM 10 (simplified as U10) was introduced, and its manufacturing processes were briefly described. Both relative transparency (RT) and modulation transfer function (MTF) methods were used to quantify the optical character variation via soil thickness. The transparency of this new transparent clay was analyzed and compared with four traditional transparent materials. The thixotropic properties of this synthetic transparent clay were measured in detail through the laboratory vane test. An exponential function was used to describe the thixotropy and sensitivity of the clay. The results showed that the new transparent clay has a relatively higher optical transparency than the majority of previous materials. Good-fitting results showed a similar development trend in thixotropy for the synthetic transparent clay and the natural ones. Furthermore, the sensitivity of the transparent clay was low to medium, which can simulate marine soil. With higher optical transparency than and similar thixotropy and sensitivity as natural clays, Carbopol® UltrezTM 10 shows great potential as a substitute for natural clay and is expected to be widely used in model tests.

Optical instrumentation with reliable performance is essential for the research of exoplanet atmosphere characteristics. However, due to long distances and weak signals, exoplanets are difficult to be imaged by traditional optical systems. To this end, a novel optical system based on transit spectroscopy is proposed in this paper. On the basis of the principle of the transit-spectroscopy method and the astronomical parameters of observed targets, the optional parameter ranges of a dedicated optical system are analyzed. The transit signal-to-noise ratio (SNR) is introduced for the determination of telescope aperture and throughput. Furthermore, an example of the optical system with a space telescope and spectrometer is proposed according to the above optical index, which is proven to meet the performance requirements. The optical system is required to cover the wavelength of 0.5–8 μm and the field of view (FOV) of 27.9″ within the diffraction limit. The collecting aperture should be greater than 2 m, and spectral resolutions of two spectrometer channels should approximately be 100 (2–4 μm) and 30 (4–8 μm). The point-spread function (PSF) of each channel at the minimal wavelength should cover 2 pixels. The telescope and dichroic system provide diffraction-limited input beams with the required aperture, FOV, and wavelength for the spectrometer slits. The simulation results of the optical system show that the spectral resolutions of the dual-channel spectrometer were 111–200 and 43–94. The image points of the spectrometer in each wavelength were smaller than the Airy spot within the slit FOV, and the full width at half-maximum (FWHM) of PSF at λmin provided 2 pixels of 18 μm sampling. The feasibility of the demonstrated optical parameters is proven by the design.

Greenspace exposure (GSE) may have a positive impact on mental health. However, existing research lacks a classification analysis of the influence pathways of different GSE on mental health. Meanwhile, the research method is limited to the measurement of the green space ratio (GSR) based on remote sensing data, which ignores people’s real perception of greenspace. This paper aims to further expand the measurement method of GSE, taking Hangzhou, China as an example, and to reveal the influence mechanism of different GSE modes on mental health. We obtained the personal information, mental health, physical activity, and other data of the interviewees through a questionnaire (n = 461). Combined with a remote sensing satellite and the Baidu Street view database, the method of image interpretation and deep learning was used to obtain the GSR, green visual ratio (GVR), and green visual exposure (GVE). The structural equation model is used to analyze the relationship between different variables. The results showed that: (1) GSE has a certain positive effect on mental health; (2) there are differences in the influence mechanism of multiple measures of GSE on mental health—the GVR and GVE measures based on the interaction perspective between human and greenspace make the influence mechanism more complicated, and produce direct and indirect influence paths; and (3) greenspace perception, sense of community, and physical activity can act as mediators, and have indirect effects. Finally, we call for expanding the measurement index and methods of GSE and integrating them into the management and control practices of urban planning to promote the healthy development of communities and even cities.

Listeria monocytogenes is a Gram-positive bacterial pathogen and the causative agent of listeriosis, a severe foodborne infection. L. monocytogenes is notorious for its ability to persist in food processing environments (FPEs) via a variety of adaptive traits. Even though traits such as cold tolerance, biofilm formation and sanitizer resistance have been extensively investigated for their roles in persistence of L. monocytogenes in FPEs, much less is known about resistance to bacteriophages. Previous studies explored phage resistance mechanisms in laboratory-created mutants but it is imperative to investigate phage resistance that is naturally exhibited in FPE-derived strains. Here, we integrated the analysis of whole genome sequence data from a panel of serotype 1/2a strains of sequence types 321 and 391 from turkey processing plants, with the determination of cell surface substituents required for phage adsorption and phage infection assays with the four wide-host-range phages A511, P100, 20422-1 and 805405-1. Using a specific set of recombinant phage protein probes, we discovered that phage-resistant strains lacked one or both of the serogroup 1/2-specific wall teichoic acid carbohydrate decorations, N-acetylglucosamine and rhamnose. Furthermore, these phage-resistant strains harbored substitutions in lmo1080, lmo1081, and lmo2550, which mediate carbohydrate decoration of the wall teichoic acids.