Through vehicle-to-vehicle (V2V) communication, autonomizing a vehicle platoon can significantly reduce the distance between vehicles, thereby reducing air resistance and improving road traffic efficiency. The gradual maturation of platoon control technology is enabling vehicle platoons to achieve basic driving functions, thereby permitting large-scale vehicle platoon scheduling and planning, which is essential for industrialized platoon applications and generates significant economic benefits. Scheduling and planning are required in many aspects of vehicle platoon operation; here, we outline the advantages and challenges of a number of the most important applications, including platoon formation scheduling, lane-change planning, passing traffic light scheduling, and vehicle resource allocation. This paper’s primary objective is to integrate current independent platoon scheduling and planning techniques into an integrated architecture to meet the demands of large-scale platoon applications. To this end, we first summarize the general techniques of vehicle platoon scheduling and planning, then list the primary scenarios for scheduling and planning technique application, and finally discuss current challenges and future development trends in platoon scheduling and planning. We hope that this paper can encourage related platoon researchers to conduct more systematic research and integrate multiple platoon scheduling and planning technologies and applications.
Once China’s Tianwen-1 Mars probe arrived in a Mars orbit after a seven-month flight in the deep cold space environment, it would be urgently necessary to monitor its state and the surrounding environment. To address this issue, we developed a flexible deployable subsystem based on shape memory polymer composites (SMPC-FDS) with a large folding ratio, which incorporates a camera and two temperature telemetry points for monitoring the local state of the Mars orbiter and the deep space environment. Here, we report on the development, testing, and successful application of the SMPC-FDS. Before reaching its Mars remote-sensing orbit, the SMPC-FDS is designed to be in a folded state with high stiffness; after reaching orbit, it is in a deployed state with a large envelope. The transition from the folded state to the deployed state is achieved by electrically heating the shape memory polymer composites (SMPCs); during this process, the camera on the SMPC-FDS can capture the local state of the orbiter from multiple angles. Moreover, temperature telemetry points on the SMPC-FDS provide feedback on the environment temperature and the temperature change of the SMPCs during the energization process. By simulating a Mars on-orbit space environment, the engineering reliability of the SMPC-FDS was comprehensively verified in terms of the material properties, structural dynamic performance, and thermal vacuum deployment feasibility. Since the launch of Tianwen-1 on 23 July 2020, scientific data on the temperature environment around Tianwen-1 has been successfully acquired from the telemetry points on the SMPC-FDS, and the local state of the orbiter has been photographed in orbit, showing the national flag of China fixed on the orbiter.
Multifunctional structures (MFSs) integrate diverse functions to achieve superior properties. However, conventional design and manufacturing methods—which generally lack quality control and largely depend on complex equipment with multiple stations to achieve the integration of distinct materials and devices—are unable to satisfy the requirements of MFS applications in emerging industries such as aerospace engineering. Motivated by the concept of design for manufacturing, we adopt a layer regulation method with an established optimization model to design typical MFSs with load-bearing, electric, heat-conduction, and radiation-shielding functions. A high-temperature in situ additive manufacturing (AM) technology is developed to print various metallic wires or carbon fiber-reinforced high-melting-point polyetheretherketone (PEEK) composites. It is found that the MFS, despite its low mass, exceeds the stiffness of the PEEK substrate by 21.5%. The embedded electrics remain functional after the elastic deformation stage. Compared with those of the PEEK substrate, the equivalent thermal conductivity of the MFS beneath the central heat source area is enhanced by 568.0%, and the radiation shielding is improved by 27.9%. Moreover, a satellite prototype with diverse MFSs is rapidly constructed as an illustration. This work provides a systematic approach for high-performance design and advanced manufacturing, which exhibits considerable prospects for both the function expansion and performance enhancement of industrial equipment.
Ion conductive membranes (ICMs) with highly conductive proton selectivity are of significant importance and greatly desired for energy storage devices. However, it is extremely challenging to construct fast proton-selective transport channels in ICMs. Herein, a membrane with highly conductive proton selectivity was fabricated by incorporating porous carbon sieving nanospheres with a hollow structure (HCSNs) in a polymer matrix. Due to the precise ion sieving ability of the microporous carbon shells and the fast proton transport through their accessible internal cavities, this advanced membrane presented a proton conductivity (0.084 S·cm−1) superior to those of a commercial Nafion 212 (N212) membrane (0.033 S·cm−1) and a pure polymer membrane (0.049 S·cm−1). The corresponding proton selectivity of the membrane (6.68 × 105 S·min·cm−3) was found to be enhanced by about 5.9-fold and 4.3-fold, respectively, compared with those of the N212 membrane (1.13 × 105 S·min·cm−3) and the pure membrane (1.56 × 105 S·min·cm−3). Low-field nuclear magnetic resonance (LF-NMR) clearly revealed the fast proton-selective transport channels enabled by the HCSNs in the polymeric membrane. The proposed membrane exhibited an outstanding energy efficiency (EE) of 84% and long-term stability over 1400 cycles with a 0.065% capacity decay per cycle at 120 mA·cm−2 in a typical vanadium flow battery (VFB) system.
The clay mineral content of Daqing Gulong shale is in the range of about 35%-45%, with particle sizes less than 0.0039 mm. The horizontal fluidity of oil in Gulong shale is poor, with near-zero vertical flowability. As a result, Gulong shale has been considered to lack commercial value. In recent years, however, interdisciplinary research in geoscience, percolation mechanics, thermodynamics, and surface mechanics has demonstrated that Gulong shale oil has a high degree of maturity and a high residual hydrocarbon content. The expulsion efficiency of Gulong shale in the high mature stage is 32%-48%. Favorable storage spaces in Gulong shale include connecting pores and lamellar fractures developed between and within organic matter and clay mineral complexes. The shale oil mainly occurs in micro- and nano-pores, bedding fractures, and lamellar fractures, with a high gas-oil ratio and medium-high movable oil saturation. Gulong shale has the characteristics of high hardness, a high elastic modulus, and high fracture toughness. This study achieves breakthroughs in the exploration and development of Gulong shale, including the theories of hydrocarbon generation and accumulation, the technologies of mobility and fracturing, and recoverability. It confirms the major transition of Gulong shale from oil generation to oil production, which has extremely significant scientific value and application potential for China’s petroleum industry.
Model parameters estimation is a pivotal issue for runoff modeling in ungauged catchments. The nonlinear relationship between model parameters and catchment descriptors is a major obstacle for parameter regionalization, which is the most widely used approach. Runoff modeling was studied in 38 catchments located in the Yellow-Huai-Hai River Basin (YHHRB). The values of the Nash-Sutcliffe efficiency coefficient (NSE), coefficient of determination (R2), and percent bias (PBIAS) indicated the acceptable performance of the soil and water assessment tool (SWAT) model in the YHHRB. Nine descriptors belonging to the categories of climate, soil, vegetation, and topography were used to express the catchment characteristics related to the hydrological processes. The quantitative relationships between the parameters of the SWAT model and the catchment descriptors were analyzed by six regression-based models, including linear regression (LR) equations, support vector regression (SVR), random forest (RF), k-nearest neighbor (kNN), decision tree (DT), and radial basis function (RBF). Each of the 38 catchments was assumed to be an ungauged catchment in turn. Then, the parameters in each target catchment were estimated by the constructed regression models based on the remaining 37 donor catchments. Furthermore, the similarity-based regionalization scheme was used for comparison with the regression-based approach. The results indicated that the runoff with the highest accuracy was modeled by the SVR-based scheme in ungauged catchments. Compared with the traditional LR-based approach, the accuracy of the runoff modeling in ungauged catchments was improved by the machine learning algorithms because of the outstanding capability to deal with nonlinear relationships. The performances of different approaches were similar in humid regions, while the advantages of the machine learning techniques were more evident in arid regions. When the study area contained nested catchments, the best result was calculated with the similarity-based parameter regionalization scheme because of the high catchment density and short spatial distance. The new findings could improve flood forecasting and water resources planning in regions that lack observed data.
The world’s coral reefs are threatened by the cumulative impacts of global climate change and local stressors. Driven largely by a desire to understand the interactions between corals and their symbiotic microorganisms, and to use this knowledge to eventually improve coral health, interest in coral microbiology and the coral microbiome has increased in recent years. In this review, we summarize the role of the coral microbiome in maintaining a healthy metaorganism by providing nutrients, support for growth and development, protection against pathogens, and mitigation of environmental stressors. We explore the concept of coral microbiome engineering, that is, precise and controlled manipulation of the coral microbiome to aid and enhance coral resilience and tolerance in the changing oceans. Although coral microbiome engineering is clearly in its infancy, several recent breakthroughs indicate that such engineering is an effective tool for restoration and preservation of these valuable ecosystems. To assist with identifying future research targets, we have reviewed the common principles of microbiome engineering and its applications in improving human health and agricultural productivity, drawing parallels to where coral microbiome engineering can advance in the not-too-distant future. Finally, we end by discussing the challenges faced by researchers and practitioners in the application of microbiome engineering in coral reefs and provide recommendations for future work.
The aging timescale of particles is a key parameter in determining their impacts on air quality, human health, and climate. In this study, a one-year simulation of the age distributions of the primary and secondary inorganic fine particulate matter (PM2.5) components was conducted over China using an age-resolved Community Multiscale Air Quality (CMAQ) model. The results indicate that primary PM2.5 (PPM) and ammonium mainly originate from fresh local emissions, with approximately 60%-80% concentrated in 0-24 h age bins in most of China throughout the year. The average age is about 15-25 h in most regions in summer, but increases to 40-50 h in southern region of China and the Sichuan Basin (SCB) in winter. Sulfate is more aged than PPM, indicating an enhanced contribution from regional transport. Aged sulfate with atmospheric age > 48 h account for 30%-50% of total sulfate in most regions and seasons, and the concentrations in the > 96 h age bin can reach up to 15 µg·m−3 in SCB during winter. Dramatic seasonal variations occur in the Yangtze River Delta, Pearl River Delta, and SCB, with highest average age of 60-70 h in winter and lowest of 40-45 h in summer. The average age of nitrate is 20-30 h in summer and increases to 40-50 h in winter. The enhanced deposition rate of nitric acid vapor combined with the faster chemical reaction rate of nitrogen oxides leads to a lower atmospheric age in summer. Additionally, on pollution days, the contributions of old age bins (> 24 h) increase notably for both PPM and secondary inorganic aerosols in most cities and seasons, suggesting that regional transport plays a vital role during haze events. The age information of PM2.5, provided by the age-resolved CMAQ model, can help policymakers design effective emergent emission control measures to eliminate severe haze episodes.
China is confronting aggravated ozone (O3) pollution, leading to adverse health impacts. This study quantifies the regional contributions to O3 in China using two approaches; estimating ① where goods are produced (the production method), and ② where goods are consumed (the consumption method). The production method predicts higher local source contribution than the consumption method; this difference can be attributed to exports. Occurrence of high-O3 episodes suggests a major contribution to O3 concentration as a result of trade activities. Based on the consumption method, 9219 out of 18 532 daily premature mortalities were caused by local sources in north China, while it increased to 14 471 of the production method when neglecting contributions due to export and consumption in other regions. This study suggests that O3 control should consider both where goods are consumed and emissions are emitted, especially taking account of international trade activities.
Driven by the concept of agricultural sustainable development, crop planting structure optimization (CPSO) has become an effective measure to reduce regional crop water demand, ensure food security, and protect the environment. However, traditional optimization of crop planting structures often ignores the impact on regional food supply-demand relations and interprovincial food trading. Therefore, using a system analysis concept and taking virtual water output as the connecting point, this study proposes a theoretical CPSO framework based on a multi-aspect and full-scale evaluation index system. To this end, a water footprint (WF) simulation module denoted as soil and water assessment tool-water footprint (SWAT-WF) is constructed to simulate the amount and components of regional crop WFs. A multi-objective spatial CPSO model with the objectives of maximizing the regional economic water productivity (EWP), minimizing the blue water dependency (BWFrate), and minimizing the grey water footprint (GWFgrey) is established to achieve an optimal planting layout. Considering various benefits, a full-scale evaluation index system based on region, province, and country scales is constructed. Through an entropy weight technique for order preference by similarity to an ideal solution (TOPSIS) comprehensive evaluation model, the optimal plan is selected from a variety of CPSO plans. The proposed framework is then verified through a case study of the upper-middle reaches of the Heihe River Basin in Gansu province, China. By combining the theory of virtual water trading with system analysis, the optimal planting structure is found. While sacrificing reasonable regional economic benefits, the optimization of the planting structure significantly improves the regional water resource benefits and ecological benefits at different scales.
The multifunctional secondary metabolites known as cyclic lipopeptides (CLPs), which are produced by a large variety of bacteria, have become a key category of plant immunity elicitors. Pseudomonas-CLPs (Ps-CLPs) are extremely diverse in structure and biological activity. However, an understanding of CLP-plant structure-function interactions currently remains elusive. Here, we identify medpeptin, a novel CLP from Pseudomonas mediterranea that consists of 22 amino acids. Medpeptin is synthesized by a non-ribosomal peptide synthase (NRPS) gene cluster and regulated by a quorum-sensing system. Further research indicates that medpeptin does not exhibit antimicrobial activity; instead, it induces plant cell death immunity and confers resistance to bacterial infection. Comparative transcriptome analysis and virus-induced gene silencing (VIGS) reveal a set of immune signaling candidates involved in medpeptin perception. Silencing of a cell-wall leucine-rich repeat extensin protein (NbLRX3) or a receptor-like protein kinase (NbRLK25)—but not BAK1 or SGT1—compromises medpeptin-triggered cell death and resistance to pathogen infection in Nicotiana benthamiana. Our findings point to a noncanonical mechanism of CLP sensing and suggest perspectives for the development of plant disease resistance.
Terpenoids are the largest family of natural products. They are made from the building block isoprene pyrophosphate (IPP), and their bioproduction using engineered cell factories has received a great deal of attention. To date, the insufficient metabolic supply of IPP remains a great challenge for the efficient synthesis of terpenoids. In this work, we discover that the imbalanced metabolic flux distribution between the central metabolism and the IPP supply hinders IPP accumulation in Bacillus subtilis (B. subtilis). Therefore, we remodel the IPP metabolism using a series of genetically encoded two-input-multi-output (TIMO) circuits that are responsive to pyruvate or/and malonyl-CoA, resulting in an IPP pool that is significantly increased by up to four-fold. As a proof-of-concept validation, we design an IPP metabolism remodeling strategy to improve the production of three valuable terpenoids, including menaquinone-7 (MK-7, 4.1-fold), lycopene (9-fold), and β-carotene (0.9-fold). In particular, the titer of MK-7 in a 50-L bioreactor reached 1549.6 mg∙L−1, representing the highest titer reported so far. Thus, we propose a TIMO genetic circuits-assisted IPP metabolism remodeling framework that can be generally used for the synergistic fine-tuning of complicated metabolic modules to achieve the efficient bioproduction of terpenoids.
Emerging evidence suggests that microbial dysbiosis plays vital roles in many human cancers. However, knowledge of whether the microbial community in thyroid tumor is related to tumorigenesis remains elusive. In this study, we aimed to explore the microbial community in thyroid tissues and its contribution to papillary thyroid cancer (PTC). In parallel, we performed microbial profiling and transcriptome sequencing in the tumor and adjacent normal tissues of a large cohort of 340 PTC and benign thyroid nodule (BTN) patients. Distinct microbial signatures were identified in PTC, BTN, and their adjacent non-tumor tissues. Intra-thyroid tissue bacteria were verified by means of bacteria staining, fluorescence in situ hybridization, and immunoelectron microscopy. We found that 17 bacterial taxa were differentially abundant in PTC compared with BTN, which included enrichment in PTC of the pathobionts Rhodococcus, Neisseria, Streptococcus, Halomonas, and Devosia, and depletion of the beneficial bacteria Amycolatopsis. These differentially abundant bacteria could differentiate PTC tumor tissues (PTC-T) from BTN tissues (BTN-T) with an area under the curve (AUC) of 81.66%. Microbial network analysis showed increased correlation strengths among the bacterial taxa in PTC-T in comparison with BTN-T. Immune-function-corresponding bacteria (i.e., Erwinia, Bacillus, and Acinetobacter) were found to be enriched in PTC with Hashimoto’s thyroiditis. Moreover, our integrative analysis revealed that the PTC-enriched bacteria had a positive association with key PTC-oncogenic pathway-related genes, including BRAF, KRAS, IRAK4, CTNNB1, PIK3CA, MAP3K7, and EGFR. In conclusion, our results suggest that intratumor bacteria dysbiosis is associated with the thyroid tumorigenesis and oncogenic signaling pathways of PTC.
An increasing number of studies have indicated that gut microbiota and its metabolites are crucial in the development of hyperlipidemia. Bifidobacterium longum (B. longum) CCFM1077 has been shown to have lipid-lowering effects in animals. This study aimed to evaluate the potential of B. longum CCFM1077 in lowering the lipid levels in patients with hyperlipidemia and investigate the effect of this bacterium on serum lipid abnormalities, gut microbiota, and fecal metabolites in these patients. This study was a six-week, randomized, double-blind, and placebo-controlled pilot clinical trial. Subjects with hyperlipidemia (N = 62) were randomly assigned to receive placebo (N = 31) or B. longum CCFM1077 (1 × 1010 colony-forming units (CFUs) per day; N = 31). Serum lipid levels including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), total triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C) were examined at the baseline and interventional endpoints. Changes in the gut microbiota composition and diversity were measured based on 16S ribosomal RNA (rRNA) sequencing of the V3-V4 region at the end of the intervention period. Non-targeted metabolomics of the feces was performed using ultra-performance liquid chromatography (UPLC)-Q-Exactive Orbitrap/mass spectrometer. Oral administration of B. longum CCFM1077 for six weeks significantly decreased the serum levels of TC (p < 0.01) and LDL-C (p < 0.01) in patients with hyperlipidemia. B. longum CCFM1077 treatment markedly increased gut microbiota diversity and the relative abundance of anti-obesity-related genera, including Lactobacillus, Butyricicoccus, Bifidobacterium, and Blautia, whereas it decreased the relative abundance of obesity-related genera, including Alistipes, Megamonas, and Catenibacterium. Additionally, some key metabolites (bile acids (BAs), biotin, and caffeine) and their corresponding metabolic pathways (primary BA biosynthesis, and taurine and hypotaurine, biotin, purine, and caffeine metabolisms) were enriched by B. longum CCFM1077, and thus it may lower lipid levels. B. longum CCFM1077 is a probiotic strain with the potential to lower serum TC and LDL-C levels patients with hyperlipidemia. The underlying mechanism may be related to the increased abundance of anti-obesity-related genera and fecal metabolites. These findings provide a foundation for future clinical applications of lipid-lowering probiotics in managing individuals with hyperlipidemia.
Host-directed therapy (HDT) is an emerging novel approach for treating multidrug-resistant Staphylococcus aureus (S. aureus) infection. Functioning as the indispensable specific cellular receptor for α-toxin (Hla), a-disintegrin and metalloproteinase 10 (ADAM10) is exploited to accelerate S. aureus infection through diverse mechanisms. The extraordinary contribution of ADAM10 to S. aureus pathogenesis renders it an attractive HDT target for combating S. aureus infection. Our study is the first to demonstrate the indispensable role of ADAM10 in S. aureus-induced necroptosis, and it enhances our knowledge of the role of ADAM10 in S. aureus infection. Using a fluorogenic substrate assay, we further identified kaempferol as a potent ADAM10 inhibitor that effectively protected mice from S. aureus infection by suppressing Hla-mediated barrier disruption and necroptosis. Collectively, our work presents a novel host-directed therapeutic strategy for using the promising candidate kaempferol to treat S. aureus infection and other diseases relevant to the disordered upregulation of ADAM10.
The coronavirus disease 2019 (COVID-19) pandemic caused by frequently mutating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a worldwide impact. However, detailed data on the potential aerosol transmission of SARS-CoV-2 in real-world and controlled laboratory settings remain sparse. During the COVID-19 pandemic in Shanghai, China in 2022, samples were collected in a Fangcang shelter hospital, a large-scale temporary hospital rapidly built by converting the existing National Exhibition and Convention Center (Shanghai) into a health care facility. Aerosol samples at different sites and intervals around patients and in public areas, surface samples, and pharyngeal swab samples from corresponding patients were included. Samples were tested for SARS-CoV-2 using real-time quantitative polymerase chain reaction (RT-qPCR) assays, followed by sequencing if the cycle threshold (Ct) value was < 30. The positivity rate for SARS-CoV-2 in aerosol samples was high in contaminated zones (37.5%, 104/277), especially around the bed (41.2%, 68/165) and near ventilation inlets (45.2%, 14/31). The prevalence of SARS-CoV-2 around the bed, public areas, and air inlets of exhaust vents fluctuated and was closely related to the positivity rate among patients at corresponding sampling sites. Some surface samples of different personal protective equipment from medical staff had high positivity rates. Sixty sequences of joined ORF1ab and spike genes obtained from sixty samples represented two main clusters of Omicron SARS-CoV-2. There was consistency in virus sequences from the same patient and their environment, and the detected virus sequences matched those of virus strains in circulation during the collection periods, which indicated a high likelihood of cross-contamination in the Fangcang shelter hospital. In summary, the results provide a quantitative and real landscape of the aerosol transmission of SARS-CoV-2 and a patient-centered view of contamination in large and enclosed spaces and offer a useful guide for taking targeted measures to avoid nosocomial infections during the management of SARS-CoV-2 or other respiratory virus diseases in a Fangcang shelter hospital.
The number of coronavirus disease 2019 (COVID-19) cases continues to surge, overwhelming healthcare systems and causing excess mortality in many countries. Testing of infectious populations remains a key strategy to contain the COVID-19 outbreak, delay the exponential spread of the disease, and flatten the epidemic curve. Using the Omicron variant outbreak as a background, this study aimed to evaluate the effectiveness of testing strategies with different test combinations and frequencies, analyze the factors associated with testing effectiveness, and optimize testing strategies based on these influencing factors. We developed a stochastic, agent-based, discrete-time susceptible-latent-infectious-recovered model simulating a community to estimate the association between three levels of testing strategies and COVID-19 transmission. Antigen testing and its combination strategies were more efficient than polymerase chain reaction (PCR)-related strategies. Antigen testing also showed better performance in reducing the demand for hospital beds and intensive care unit beds. The delay in the turnaround time of test results had a more significant impact on the efficiency of the testing strategy compared to the detection limit of viral load and detection-related contacts. The main advantage of antigen testing strategies is the short turnaround time, which is also a critical factor to be optimized to improve PCR strategies. After modifying the turnaround time, the strategies with less frequent testing were comparable to daily testing. The choice of testing strategy requires consideration of containment goals, test efficacy, community prevalence, and economic factors. This study provides evidence for the selection and optimization of testing strategies in the post-pandemic era and provides guidance for optimizing healthcare resources.
