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Abstract Background Coronary heart disease (CHD) is a common cardiovascular disease that is associated with altered gut microbiota. Enteroviruses, an essential component of the gut microbiome, may play an important role in disease progression. However, the relationship between enteroviruses and CHD remains unclear. The development of high-throughput sequencing technologies has facilitated research on the interconnections between viruses and disease-related metabolites. Methods and results Mice were fed a high-fat diet (CHD group) or chow diet (Sham group) for 12 weeks, and ligation of the left anterior descending coronary artery was performed at the end of week 8. After 4 weeks, all animals were euthanised. Subsequently, the animals were evaluated for basic haemato-biochemical parameters and cardiac function, and aorta staining was performed. Based on enteroviral metagenomics and serum UPLC–MS/MS metabolomics analyses, we evaluated the association between enteroviral groups and serum metabolites of CHD mouse model. A high-fat diet and coronary ligation enabled the establishment of the CHD mouse model. Notably, the enterovirus spectrum of the sham group was significantly different from that of the CHD group, with 24 viral communities of different family and species classification, such as Tsarbombavirus, Mingyongvirus, Claudivirus, and Firehammervirus, exhibiting significant differences. In addition, 731 Differential metabolites were detected in the serum of both groups of mice. Correlation network analysis revealed a close relationship between various metabolites related to lipid metabolism and different viruses, including Tsarbombavirus, Mingyongvirus, Claudivirus, and Firehammervirus. Conclusions An animal model of CHD, characterised by lipid disturbance and myocardial ischaemia, was established using a high-fat diet and ligation of the left anterior descending branch of the coronary artery. Tsarbombavirus, Firehammervirus, Mingyongvirus, and Claudivirus were associated with metabolites in the lipid metabolism pathway. The results indicate that Tsarbombavirus may be the main genus interacting with CHD-related metabolites in mice. Conclusively, the findings of our study provide novel insights into the potential relationship enterovirus groups and metabolites associated with CHD.

Abstract Background Astragaloside IV is a main medicinal active ingredient in Astragalus membranaceus Bge. var. mongholicus (Bge.) Hsiao, which is also the key biomarker of A. membranaceus quality. Ethylene has been well-documented to involve in secondary metabolites biosynthesis in plants. Nevertheless, how ethylene regulates astragaloside IV biosynthesis in A. membranaceus is still unclear. Therefore, in the present study different dosages and time-dependent exogenous application of ethephon (Eth) were employed to analyze astragaloside IV accumulation and its biosynthesis genes expression level in hydroponically A. membranaceus. Results Exogenous 200 µmol·L− 1Eth supply is most significantly increased astragaloside IV contents in A. membranaceus when compared with non-Eth supply. After 12 h 200 µmol·L− 1 Eth treatment, the astragaloside IV contents reaching the highest content at 3 d Eth treatment(P ≤ 0.05). Moreover, After Eth treatment, all detected key genes involved in astragaloside IV synthesis were significant decrease at 3rd day(P ≤ 0.05). However, SE displayed a significant increase at the 3rd day under Eth treatment(P ≤ 0.05). Under Eth treatment, the expression level of FPS, HMGR, IDI, SS, and CYP93E3 exhibited significant negative correlations with astragaloside IV content, while expression level of SE displayed a significant positive correlation. Conclusions These findings suggest that exogenous Eth treatment can influence the synthesis of astragaloside IV by regulating the expression of FPS, HMGR, IDI, SS, CYP93E3 and SE. This study provides a theoretical basis for utilizing molecular strategies to enhance the quality of A. membranaceus.

Abstract Subauroral red (SAR) arcs are commonly observed ionospheric red line emissions. They are usually attributed to subauroral electron heating by inner magnetospheric heat flux (IMHF). However, the role of IMHF in changing the ionosphere‐thermosphere (IT) still remains elusive. We conduct controlled numerical experiments with the Thermosphere‐Ionosphere Electrodynamic General Circulation Model (TIEGCM). Coulomb collisional heat flux derived with the Comprehensive Inner Magnetosphere Ionosphere (CIMI) model and empirical subauroral polarization streams (SAPS) are implemented in TIEGCM. The heat flux causes electron temperature enhancement, electron density depletion, and consequently SAR arcs formed in the dusk‐to‐midnight subauroral ionosphere region. SAPS cause more substantial plasma and neutral heating and plasma density variations in a broader region. The maximum enhancement of subauroral red line emission rate is comparable to that caused by the heat flux. However, the visibility of SAR arcs also depends on the relative enhancement to the background brightness.

Satellite networks with edge computing servers promise to provide ubiquitous and low-latency computing services for the Internet of Things (IoT) applications in the future satellite-terrestrial integrated network (STIN). For some emerging IoT applications, the services require real-time user-dependent state information, such as time-varying task states and user-specific configurations, to maintain service continuity. Service migration is crucial for dynamic task offloading to synchronize the user-dependent state information between computing servers. However, how to offload computing tasks at low latency with the impact of service migration remains challenging due to the high-speed movement and load imbalance of low Earth orbit (LEO) satellite networks. In this work, we investigate the task offloading problem with service migration for satellite edge computing (SEC) using inter-satellite cooperation. Facing dynamic service requirements with limited on-board bandwidth, energy, and storage resources of satellite networks, we formulate the problem with the aim of minimizing the service delay to optimize the offloading path selection. By leveraging a deep reinforcement learning (DRL) approach, we propose a distributed scheme based on the Dueling-Double-Deep-Q-Learning (D3QN) algorithm. Simulation results show that the proposed scheme can effectively reduce the service delay, and outperform the benchmark algorithms.

At present, the main detection instruments for observing sporadic E (Es) layers are ground-based radars, dense networks of ground-based global navigation satellite system (GNSS) receivers, and GNSS radio occultation, but they cannot capture the whole picture of the horizontal structure of Es layers. This study employs the Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension model (WACCM-X 2.1) to derive the horizontal structure of the ion convergence region (HSICR) to explore the shapes of the large-scale Es layers over East Asia for the period from June 1 to August 31, 2008. The simulation produced the various shapes of the HSICRs elongated in the northwest−southeast, northeast−southwest, or composed of individual small patches. The close connection between Es layer critical frequency (foEs) and vertical ion convergence indicates that the HSICR is a good candidate for revealing and explaining the horizontal structure of the large-scale Es layers.

The color features of strawberries at different growth stages vary slightly and occluded during growth. To address these challenges, this study proposes a lightweight multi-stage detection method based on You Only Look Once version 7-tiny (YOLOv7-tiny) for strawberries in complex environments. First, the size of the model is reduced by replacing the ordinary convolution of the neck network used for deep feature extraction and fusion with lightweight Ghost convolution. Then, by introducing the Coordinate Attention (CA) module, the model’s focus on the target detection area is enhanced, thereby improving the detection accuracy of strawberries. The Wise Intersection over Union (WIoU) loss function is integrated to accelerate model convergence and enhance the recognition accuracy of occluded targets. The advanced Adaptive nesterov momentum algorithm (Adan) is utilized for gradient descent, processing averaged sample data. Additionally, considering the small size of strawberry targets, a detection head specifically for small targets is added, performing detection on a 160 × 160 × 64 feature map, which significantly improves the detection performance for small strawberries. Experimental results demonstrate that the improved network model achieves an mAP@0.5 of 88.2% for multi-stage strawberry detection, which is 2.44% higher than the original YOLOv7-tiny algorithm. Meanwhile, GFLOPs and Params are reduced by 1.54% and 12.10%, respectively. In practical detection and inference, the improved model outperforms current mainstream target detection models, enabling a quicker and more accurate identification of strawberries at different growth stages, thus providing technical support for intelligent strawberry picking.

Background: As one of the four most valuable animal medicines, Fel Ursi, named Xiong Dan (XD) in China, has the effect of clearing heat, calming the liver, and brightening the eyes. However, due to the special source of XD and its high price, other animals’ bile is often sold as XD or mixed with XD on the market, seriously affecting its clinical efficacy and consumers’ rights and interests. In order to realize identification and adulteration analysis of XD, UHPLC-QTOF-MSE and multivariate statistical analysis were used to explore the differences in XD and six other animals’ bile. Methods: XD, pig gall (Zhu Dan, ZD), cow gall (Niu Dan, ND), rabbit gallbladder (Tu Dan, TD), duck gall (Yan Dan, YD), sheep gall (Yang Dan, YND), and chicken gall (Ji Dan, JD) were analyzed by UHPLC-QTOF-MSE, and the MS data, combined with multivariate analysis methods, were used to distinguish between them. Meanwhile, the potential chemical composition markers that contribute to their differences were further explored. Results: The results showed that XD and six other animals’ bile can be distinguished from each other obviously, with 27 ions with VIP > 1.0. We preliminarily identified 10 different bile acid-like components in XD and the other animals’ bile with significant differences (p < 0.01) and VIP > 1.0, such as tauroursodeoxycholic acid, Glycohyodeoxycholic acid, and Glycodeoxycholic acid. Conclusions: The developed method was efficient and rapid in accurately distinguishing between XD and six other animals’ bile. Based on the obtained chemical composition markers, it is beneficial to strengthen quality control for bile medicines.

Abstract Concurrent pollution of fine particulate matter (PM2.5) and ozone has been increasingly reported in China recently. Here, we further confirm widespread co‐occurring summertime PM2.5‐ozone extremes in southern China. Annual‐average frequency of co‐occurrence is above 50% from 2015 to 2022, especially in Pearl River Delta region (72 ± 12%). The spatial extent (city numbers) and temporal persistence (co‐occurrence days) for cities with co‐occurrence frequency >50% increase at a rate of two cities/year and 14 days/year, respectively. We further identify typical synoptic conditions (e.g., typhoon periphery circulation, West Pacific subtropical high) conducive to widespread co‐occurrence. Through combining multi‐source data, Random Forest model well predicts PM2.5‐ozone co‐occurrence and identifies common precursors (e.g., volatile organic compounds) as important variables. Finally, we postulate co‐occurrence is linked to synoptic conditions and secondary generation of PM2.5‐ozone from shared precursors. Our results suggest high potentials for co‐occurring PM2.5‐ozone extremes in southern China and control strategies on common precursors to mitigate concurrent pollution.

Abstract Janus membranes with asymmetric wettability have been considered cutting‐edge for energy/environmental‐sustainable applications like water/fog harvester, breathable skin, and smart sensor; however, technical challenges in fabrication and accurate regulation of asymmetric wettability limit their development. Herein, by using water‐assisted hydrogen‐bonded (H‐bonded) assembly of small molecules at water/oil interface, a facile strategy is proposed for one‐step fabrication of membranes with well‐regulable asymmetric wettability. Asymmetric orderly patterns, beneficial for mass transport based on abundant high‐permeability sites and large surface area, are constructed on opposite membrane surfaces. Upon tuning water‐assisted H‐bonding via H‐sites/configuration design and temperature/pH modulation, double‐hydrophobic, double‐hydrophilic, and hydrophobic‐hydrophilic membranes are facilely fabricated. The Janus membranes show smart vapor‐responsive curling and unidirectional water transport with promising flux of 1158±25 L m−2 h−1 under natural gravity and 31500±670 L·(m−2 h−1 bar−1) at negative pressure. This bottom‐up approach offers a feasible‐to‐scalable avenue to precise‐manipulation of Janus membranes for advanced applications, providing an effective pathway for developing tailor‐made self‐assembled nanomaterials.

Atmospheric particulate matter (PM) poses great adverse effects through the production of reactive oxygen species (ROS). Various components in PM are acknowledged to induce ROS formation, while the interactions among chemicals remain to be elucidated. Here, we systematically investigate the influence of Brown carbon (BrC) surrogates (e.g., imidazoles, nitrocatechols and humic acid) on hydroxyl radical (·OH) generation from transition metals (TMs) in simulated lung fluid. Present results show that BrC has an antagonism (interaction factor: 20–90 %) with Cu2+ in ·OH generation upon the interaction with glutathione, in which the concentrations of BrC and TMs influence the extent of antagonism. Rapid ·OH generation in glutathione is observed for Fe2+, while ·OH formation is very little for Fe3+. The compositions of antioxidants (e.g., glutathione, ascorbate, urate), resembling the upper and lower respiratory tract, respond differently to BrC and TMs (Cu2+, Fe2+ and Fe3+) in ·OH generation and the degree of antagonism. The complexation equilibrium constants and site numbers between Cu2+ and humic acid were further analyzed using fluorescence quenching experiments. Possible complexation products among TMs, 4-nitrocatechol and glutathione were also identified using quadropule-time-of-flight mass spectrometry. The results suggest atmospheric BrC widely participate in complexation with TMs which influence ·OH formation in the human lung fluid, and complexation should be considered in evaluating ROS formation mediated by ambient PM.

Considering the performance degradation of structures in cold regions, the frost resistance and flexural performance of reinforced PP-ECC beams under the coupled action of freeze-thaw cycles and constant flexural load are investigated in this study. During the coupling test, the ultrasonic wave speed of the beams is recorded and the freeze-thaw damages in different regions of the beam are analyzed. Then, the flexural performance test is conducted on the beams, and the failure mode, number of cracks, maximum crack width, and flexural load-bearing capacity of the beams are measured. It is found that, with the increase of the number of freeze-thaw cycles, the freeze-thaw damage in the PP-ECC beam is more severe, and the flexural load-bearing capacity gradually decreases. Also, the number of cracks and cracking strength of the beams decrease, and the maximum crack width increases. With the increase of the flexural load, the frost resistance of both the tension zone and the bending shear zone of the beam is getting weaker, aggravating the freeze-thaw damage. Applying the constant load with a stress ratio of 0.25 results in the improvement of the frost resistance of the compression zone, thus reducing the freeze-thaw damage and increasing the load-bearing capacity of the beam. However, if the constant load is too large (stress ratio = 0.5), the freeze-thaw damage in the compression zone is aggravated, and the load-bearing capacity of the beam is reduced. Regardless of different degrees of freeze-thaw damage, the ductile failure of the beam is shown.

Gold nanorods (GNRs) coated with silica shells are excellent photothermal agents with high surface functionality and biocompatibility. Understanding the correlation of the coating process with both structure and property of silica-coated GNRs is crucial to their optimizing preparation and performance, as well as tailoring potential applications. Herein, we report a machine learning (ML) prediction of coating silica on GNR with various preparation parameters. A total of 306 sets of silica-coated GNRs altogether were prepared via a sol–gel method, and their structures were characterized to extract a dataset available for eight ML algorithms. Among these algorithms, the eXtreme gradient boosting (XGboost) classification model affords the highest prediction accuracy of over 91%. The derived feature importance scores and relevant decision trees are employed to address the optimal process to prepare well-structured silica-coated GNRs. The high-throughput predictions have been adopted to identify optimal process parameters for the successful preparation of dumbbell-structured silica-coated GNRs, which possess a superior performance to a conventional cylindrical core–shell counterpart. The dumbbell silica-coated GNRs demonstrate an efficient enhanced photothermal performance in vivo and in vitro, validated by both experiments and time domain finite difference calculations. This study epitomizes the potential of ML algorithms combined with experiments in predicting, optimizing, and accelerating the preparation of core–shell inorganic materials and can be extended to other nanomaterial research.

Due to the rugged construction, high starting torque, wide speed range, inherent fault-tolerance and high operating efficiency, switched reluctance motors (SRMs) have been used in many fields such as household appliances, electric vehicles and industrial drives. At low and medium speeds, the current chopping control (CCC) are usually used for SRMs. The current sensors must be connected in series with each phase winding for detecting the phase current, and the number of sensors is usually equal to the number of motor phases. In order to reduce the number of current sensors and the cost of the drive system, this paper propose a general phase current reconstruction method for SRM drive system with two current sensors. Firstly, the excitation, freewheeling and demagnetization circuits of the asymmetric half-bridge power converter are separated into two different paths. The sensors placement method, winding connection method and calculation formula of each phase current are introduced in detail. Then the influence of the turn-off angles on the overlap interval of each phase current is analyzed, and the proposed reconstruction method is further extended to multi-phase SRM. This method can simplify the current decoupling process and is easy to implement without changing the asymmetric half-bridge topology and operating states. Finally, the feasibility of the proposed phase current reconstruction algorithm is verified by simulation and experiment.

Background: Telomerase reverse transcriptase promoter (TERT-p) mutation has been frequently found, but associated with contrary prognosis, in both low-grade gliomas and glioblastomas. For the low-grade gliomas (Grades II-III), TERT-p mutant patients have a better prognosis than the wildtype patients, whereas for the GBMs (Grade IV), TERT-p mutation is related to a poor prognosis. We hypothesize that there exist high-risk patients in LGGs who share GBM-like molecular features, including TERT-p mutation, and need more intensive treatment than other LGGs. A molecular signature is needed to identify these high-risk patients for an accurate and timely treatment.Methods: Using the within-sample relative expression orderings of gene pairs, we identified the gene pairs with significantly stable REOs, respectively, in both the TERT-p mutant LGGs and GBMs but with opposite directions in the two groups. These reversely stable gene pairs were used as the molecular signature to stratify the LGGs into high-risk and low-risk groups.Results: A signature consisting of 21 gene pairs was developed, which can classify LGGs into two groups with significantly different overall survival. The high-risk group has a similar genetic mutation profile and a similar survival profile as GBMs, and these high-risk tumors may progress to a more malignant state.Conclusion: The 21 gene-pair signature based on REOs is capable of identifying high-risk patients in LGGs and guiding the clinical choice for appropriate and timely intervention.

To improve the accuracy of rainfall estimation by microwave links, this article presents a method for classifying wet and dry periods based on the support vector machine (SVM). The average, minimum, and maximum attenuation measurements in 5 min are applied as the feature vector of the SVM after the analysis of the relation between the statistical parameters of the attenuation measurements from seven microwave links and the wet/dry periods. When the baseline attenuation is needed for retrieving the path-averaged rain rate, the method can classify the wet/dry periods and estimate a dynamic baseline with an optimal combination of the statistical parameters of the attenuation measurements based on the prior training. Experiments are conducted to test the classification method. The results show that the classification accuracy is higher than 0.8, which is a satisfactory result. Most values of the true positive rate are higher than 0.9, which indicates that the method can correctly classify most of the wet periods. Additionally, the values of the false positive rate are less than 0.3, and most of the values are less than 0.2, suggesting that the method incorrectly classifies the dry period as the wet period with a low probability. The results demonstrate that the classification method is capable of classifying the wet and dry periods with a high accuracy, which can help improve the precision of the baseline of microwave links and rainfall estimation.

The design of high-efficiency CO2 adsorbents with low cost, high capacity, and easy desorption is of high significance for reducing carbon emissions, which yet remains a great challenge. This work proposes a facile construction strategy of amino-functional dynamic covalent materials for effective CO2 capture from flue gas. Upon the dynamic imine assembly of N-site rich motif and aldehyde-based spacers, nanospheres and hollow nanotubes with spongy pores were constructed spontaneously at room temperature. A commercial amino-functional molecule tetraethylenepentamine could be facilely introduced into the dynamic covalent materials by virtue of the dynamic nature of imine assembly, thus inducing a high CO2 capacity (1.27 mmol·g−1) from simulated flue gas at 75 °C. This dynamic imine assembly strategy endowed the dynamic covalent materials with facile preparation, low cost, excellent CO2 capacity, and outstanding cyclic stability, providing a mild and controllable approach for the development of competitive CO2 adsorbents.

Bisulfite sequencing is considered as the gold standard approach for measuring DNA methylation, which acts as a pivotal part in regulating a variety of biological processes without changes in DNA sequences. In this study, we introduced the most prevalent methods for processing bisulfite sequencing data and evaluated the consistency of the data acquired from different measurements in liver cancer. Firstly, we introduced three commonly used bisulfite sequencing assays, i.e., reduced-representation bisulfite sequencing (RRBS), whole-genome bisulfite sequencing (WGBS), and targeted bisulfite sequencing (targeted BS). Next, we discussed the principles and compared different methods for alignment, quality assessment, methylation level scoring, and differentially methylated region identification. After that, we screened differential methylated genes in liver cancer through the three bisulfite sequencing assays and evaluated the consistency of their results. Ultimately, we compared bisulfite sequencing to 450 k beadchip and assessed the statistical similarity and functional association of differentially methylated genes (DMGs) among the four assays. Our results demonstrated that the DMGs measured by WGBS, RRBS, targeted BS and 450 k beadchip are consistently hypo-methylated in liver cancer with high functional similarity.

An effective stress absorption layer can reduce the reflection crack. It can help to extend the service life of road. In this research, an enhanced stress absorption layer of slow crack (ESALOSC) is proposed and compared with the ordinary SBS modified asphalt stress absorbing layer. The strain data of two stress absorption layers under different loads, speeds and temperatures are collected by embedding sensors in the road, and the dynamic response laws of the two stress absorption layers under different conditions are analyzed. The results show that the asphalt pavement is a viscoelastic body and the measured results are consistent with the theoretical solution of layered elasticity: both stress absorbing layers are subjected to pressure. According to the comparison between dynamic overload test and static overload test, the strain deviation between the two sections increases from 11.6% of static load to 25.2% of dynamic load (40 km/h). It indicates that the reinforced effect of geogrid is more obvious under dynamic load. By establishing the relationship between vehicle speed and dynamic response, a vehicle speed and dynamic response model for the ESALOSC is proposed. Based on the test data measured at four temperatures, a model of the temperature and dynamic response in the ESALOSC is proposed. The accuracy and effectiveness of the two models are verified by comparing with other experimental results. The ESALOSC is of great significance for improving the crack resistance of road. The research results provide technical support and theoretical model for the development of long-life pavement in China.

The main purposes of this study are to analyse the evaluation of tailings dam stability under multiple factors and prevent accidents more effectively by proposing a composite risk analysis model. The evaluation model combining the TOPSIS model and bow tie model is presented in this paper. Firstly, a new formula was adopted to calculate the integrated weights based on the subjective and objective weights and the theory of the TOPSIS model was introduced. Secondly, taking a uranium tailings reservoir in south China as an example, the index values and constant weights of the 10 dams are determined according to eight aspects of accumulating dam crest elevation, dam slope, mechanical properties, seepage capacity, topographical conditions, flood control capacity, rainstorm resistance capacity and earthquake resistance capacity. Thirdly, the fitting degree between the stability and ideal solution of each dam is calculated by using the TOPSIS model. The stability fitting degree of the 10 dams is 76%, 93%, 82%, 90%, 66%, 79%, 85%, 96%, 32%, 89% in sequence. This result shows that among the 10 dams, the 9# dam ranks the lowest in stability. The actual results are in good consistency with those calculated by the TOPSIS model, which can provide a scientific and reliable new idea for the safety of other multi-index comprehensive evaluations. It is worth mentioning that it can still maintain high accuracy of dam stability evaluation under multiple indexes and multiple dams. Also, the comprehensive evaluation model proposed in this paper can more effectively reflect the subtle differences between similar evaluation objects. Fourthly, safety barriers from both the cause of the accident and the consequences was established by using the bow tie model to block the path of the accident, and to propose safety measures to make the evaluation system more complete.

The actual lifetimes of many highways are lower than that expected based on the initial pavement design, which brings increasingly prohibitive costs of pavement maintenance and repair. Although many works have been done, the real service lifetimes are still disappointing, and the researchers are also trying their best to increase the projects’ life span. In this study, to comprehensively predict the durability and lifetime of newly designed asphalt mixture structures, an asphalt pavement project consisting of three hot mix asphalt (HMA) mixtures were evaluated. The mixtures were constructed in the pavement project of the Weiwu expressway in Gansu Province. Pavement properties of the asphalt mixtures, rutting and temperature fatigue factors of the dynamic modulus are discussed. The fatigue resistance is supposed to improve on increasing the vehicles’ speed below the freezing point, which may be more suitable for applications in expressways. Meanwhile, the lifetime is measured according to the number of fatigue axle loads calculated, which were corrected between the specimens in the lab and the field core samples. Durability analysis prediction can be obtained based on the fatigue lifetime predictive model accordingly, which can provide more information about the fatigue lifetime and the rehabilitation planning of existing pavements in the future accordingly.

Abstract The gut microbiota is now known as a key factor in mammalian physiology and health. Our understanding of the gut microbial communities and their effects on ecology and evolution of their hosts is extremely limited in bats which represent the second largest mammalian order. In the current study, gut microbiota of three sampling sources (small intestine, large intestine, and feces) were characterized in two sympatric and insectivorous bats (Rhinolophus sinicus and Myotis altarium) by high‐throughput sequencing of the V3‐V4 region of the 16S rRNA gene. Combining with published studies, this work reveals that Gammaproteobacteria may be a dominant class in the whole Chiroptera and Fusobacteria is less observed in bats although it has been proven to be dominant in other mammals. Our results reveal that the sampling source influences alpha diversity of the microbial community in both studied species although no significant variations of beta diversity were observed, which support that fecal samples cannot be used as a proxy of the microbiota in other gut regions in wild animals.

With the implementation of the Xiongan New Area and the urbanization construction plan surrounding the Beijing-Tianjin satellite, it is urgent to study and apply the sponge-permeable paving materials to solve the “urban waterlogging and heat island effect.” In this paper, the hydration microscopic characteristics of cementitious materials are analyzed by means of the differential scanning calorimetry (DSC) test. The test of water-cement ratio, porosity, and gradation structure on the strength and permeability coefficient is emphasized, and the strength change rule of porous permeable concrete is obtained. The research results are shown as follows: (1) The DSC test shows that the effect of temperature on the hydration process of cement is obvious. With the increase of temperature, the two exothermic peaks of cement hydration increase significantly and tend to overlap and the exothermic process is shortened. At 85°C, only one exothermic peak appeared, indicating that C3S hydration and ettringite formation process were completed at the same time in a relatively short time. (2) The optimal water-binder ratio of pervious concrete ranges from 0.24 to 0.30, and the optimal porosity ranges should be controlled within the range of 15%–25%. Moreover, the open gradation of pervious concrete mix ratio design is selected, and the cement content should be within the range of 20%–25%. (3) The mathematical model of permeability coefficient and porosity ratio of permeable concrete is established: k=−0.0003n2+0.0057n−0.0044; the mathematical model of permeability coefficient and compressive strength of open-graded pervious concrete: k=0.99006−0.05389c+8.02×10−4c2. The research results can provide theoretical support and technical guidance for the design and construction of permeable materials of sponge cities in Xiongan New Area and surrounding ring new area, which are of great engineering value.

Decision makers must often choose how many sensors to deploy, of what types, and in what locations to meet a given operational or scientific outcome. An observation system simulation experiment (OSSE) is a numerical experiment that can provide critical decision support to these complex and expensive choices. An OSSE uses a "truth model" or "nature run" to simulate what an observation system would measure and then passes these measurements to an assimilation model. Then, the output of the assimilation model is compared to that of the truth model to assess improvement and the impact of the observation system. Orion Space Solutions has developed the OSSE tool (OSSET) to perform OSSEs for ionospheric electron density specification quickly and accurately. In this study, we use OSSET to predict the impact of adding commercial radio occultation total electron content (TEC) data to an assimilation model. We compare the OSSE's predictions to the real performance at a group of validation ionosondes and find good agreement. We also demonstrate the global assessments that are possible with the OSSET using the improvement in critical frequency specification as an example. From this, we find that commercial radio occultation data can improve the critical frequency specification by nearly 20% at high latitudes, which are not covered by COSMIC-2. The commercial satellites are in sun-synchronous orbits with constant local times, and this improvement is concentrated at these local times. [ABSTRACT FROM AUTHOR]