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In this paper, we developed a novel conformation generation model, termed SDEGen, learning how a molecule evolves in a stochastic dynamics system starting from noise and eventually relaxing to the conformation that falls into low energy minima.

A large quantity of Steel Balls Automatic precise Counting device is introduced in this paper. Inductance sensors are used for ball detection and STC15F2K60S2 microprocessor is used to do the signal processing. When steel balls are sent to the PVC pipe at the same time, some balls will connect together because of the collision. The sensor will send a connected signal instead of multiple signals if it meets the connected balls. This could cause counting mistake of the device. A correction method is used to solve this problem. The device setup angle could be gotten by using dual sensors to get the average moving speed of the steel balls according to the fixed relations between the setup angle and the speed, which is not affected by whether the steel balls overlap or not because it used two voltage Jump edge to judge the start and end moment of timer. After that, the device setup angle is used to get the standard moving time to single sensor according to the known function relationship. The counting numbers are corrected by using the standard duration to compare with each recording low voltage duration passing single sensor. This method solves the counting mistake problem when a lot of steel balls are pushed into the PVC pipe together. The device improves the efficiency and accuracy of the ball counting.

Objective: To describe the clinical characteristics and the situations of the treatment and outcome of tetanus and find out the focus of tetanus prevention and treatment to reduce morbidity and mortality in China, this paper retrospectively studied the literature and analyzed the clinical characteristics and the situations of treatment and outcome of tetanus in China. Methods: Four databases, including the Chinese Bio-Medical Literature Database, Chinese National Knowledge Infrastructure, Chinese Scientific Journal Database, and Wan-fang Data, were searched from 1 January/2000 to 30/October/2022. Descriptive statistics calculated frequencies and percentages. Results: The total 151 articles, including 6084 tetanus patients, met the inclusion criteria. 5925 patients were recorded gender in detail, of which 66.67% (3950/5925) were male, and 33.33% (1975/ 5925) were female. The average age of the detailed records was 4773 cases, with an overall average age of 46.69; the minimum and maximum mean ages are 25.00 and 65.22 years old, respectively. The number of patients’ residence places recorded was 580; those from rural areas had the highest percentage, 88.62% (514 / 580). The causes of injury recorded were 1592 cases in total; injuries caused by metals, wood, and wooden spikes, such as rusty nails and iron pieces, accounted for the highest percentage of 54.52% (868/1592). The patients recorded outcome amounted to 4305 cases, of whom 402 died, and the mortality was 9.34%. The leading causes of death included treatment terminatedby family members, asphyxia due to persistent spasms, respiratory failure, and autonomic dysfunction, in which family automatic abandonment and asphyxia accounted for the highest percentage, both 24.00% (54/225). Conclusion: the overall success rate of tetanus treatment in China has dramatically improved, but the prevention and control situation of non-neonatal tetanus is still strenuous; the focus of it should be put on the prevention of adult tetanus and standardizing the use of sedative and spasmolytic drugs. Popularize tetanus prevention and treatment knowledge to the people, and strengthen the training in grass-roots hospitals, the combined application of Chinese and western medicine may be a new direction with the value of exploring reducing the dosage of sedative and spasmolytic drugs.

This paper investigates the control problem for a quadrotor with a cable-suspended payload (QCSP). A new adaptive control strategy is designed to control the velocity of a volumetric payload with unknown mass in the presence of rotor downwash. The asymptotic stability of the resulting closed-loop system is analysed via the Lyapunov method. Furthermore, a novel structure is designed to suspend the payload on the quadrotor by a cable, and a gyroscope is installed on this structure to measure the payload's swing angle. The designed controller's performance is demonstrated by simulations implemented in a Simulink/SimMechanics environment. The effectiveness of the proposed control scheme is validated in real experiments.

Sodium-ion capacitors (SICs) are extremely promising due to the combined merits of high energy-power characteristics and considerable price advantage. However, it is still difficult to achieve high energy-power outputs and cycle stability in a typical configuration of the metal-based battery-type anode and activated carbon capacitor-type cathode due to the kinetic mismatching. In this work, a carbon nanosheet (PSCS-600) with large interlayer spacing of 0.41 nm derived from the bio-waste pine cone shell was prepared. Besides, the covalent triazine framework derived carbon (OPDN-CTF-A) was obtained through ionothermal synthesis strategy, exhibiting beneficial hierarchical pores (0.5–6 nm) and high heteroatoms (5.6 at% N, 6.6 at% O). On this basis, the all-carbon SICs were fabricated by the integration of PSCS-600 anode and OPDN-CTF-A cathode. The device delivered high energy density 111 Wh kg−1, high power output of 14,200 W kg−1 and ultra-stable cycling life (∼90.7% capacitance retention after 10,000 cycles). This work provides new ideas in fabricating carbon-carbon architectural SICs with high energy storage for practical application.

Sepsis after trauma increases the risk of mortality rate for patients in intensive care unit (ICUs). Currently, it is difficult to predict outcomes in individual patients with sepsis due to the complexity of causative pathogens and the lack of specific treatment. This study aimed to identify metabolomic biomarkers in patients with multiple trauma and those with multiple trauma accompanied with sepsis. Therefore, the metabolic profiles of healthy persons designated as normal controls (NC), multiple trauma patients (MT), and multiple trauma complicated with sepsis (MTS) (30 cases in each group) were analyzed with ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS)-based untargeted plasma metabolomics using collected plasma samples. The differential metabolites were enriched in amino acid metabolism, lipid metabolism, glycometabolism and nucleotide metabolism. Then, nine potential biomarkers, namely, acrylic acid, 5-amino-3-oxohexanoate, 3b-hydroxy-5-cholenoic acid, cytidine, succinic acid semialdehyde, PE [P-18:1(9Z)/16:1(9Z)], sphinganine, uracil, and uridine, were found to be correlated with clinical variables and validated using receiver operating characteristic (ROC) curves. Finally, the three potential biomarkers succinic acid semialdehyde, uracil and uridine were validated and can be applied in the clinical diagnosis of multiple traumas complicated with sepsis.

This study explored the environmental determinants of different months on snail density measured in April at different types of snail habitats (marshlands, inner embankments, and hills) by considering spatial effects. Data were gathered from surveys on snails that were conducted in Hunan Province in April 2016, and information was collected on environmental variables. To investigate the environmental factors influencing snail density in various types of snail habitats, the ordinary least square model, spatial lag model, and spatial error model were all used. The environmental determinants for snail density showed different effects in the three types of snail habitats. In marshlands, snail density measured in April was associated positively with the normalized difference vegetation index (NDVI) and was associated negatively with flooding duration and annual hours of sunshine. Extreme temperatures correlated strongly to snail density measured in April (P < 0.05). In areas inside embankments, snail density measured in April increased with a decreased distance between snail habitat and the nearest river (P < 0.05). In hills, extreme heat, annual hours of sunshine, NDVI in September, and annual average land surface temperature (LST) were associated negatively with snail density measured in April, whereas index of moisture (IM) was associated positively with snail density measured in April (P < 0.05). The effects of LST and hours of sunshine on snail density measured in April varied with months of the year in the three different types of snail habitats (P < 0.05). Our study might provide a theoretical foundation for preventing snail transmission and subsequent spread of schistosomiasis.

How to save the energy of unmanned aerial vehicles (UAVs) and then enable long-distance transport is a very real and difficult task. However, for UAVs, the classic object detection algorithm, such as the deep convolutional neural network–based object detection algorithm and the classic flight control algorithm, such as the PID-based position control algorithm, require significant energy, which limits the application scenarios of the UAV system. In view of this problem, this paper proposes a lightweight object detection network and a linear active disturbance rejection controller (LADRC) for the quadrotor with the cable-suspended payload (QCSP) system to improve energy efficiency. The system uses a YOLOV3 network and embeds it into the Jesson NX mobile platform to accurately detect the target position. Furthermore, a nonlinear velocity controller with a cable-suspended structure to control the velocity of the payload, a LADRC algorithm is adopted to achieve fast and accurate control of the payload position. Simulations and real flight experiments show that the proposed object detection algorithm and the LADRC control strategy can save the energy of drone effectively.

Understanding the spatial distribution of schistosome infection is critical for tailoring preventive measures to control and eliminate schistosomiasis. This study used spatial analysis to determine risk factors that may impact Schistosoma japonicum infection and predict risk in Hunan and Jiangxi Provinces in the People’s Republic of China. The study employed survey data collected in Hunan and Jiangxi in 2016. Independent variable data were obtained from publicly available sources. Bayesian-based geostatistics was used to build models with covariate fixed effects and spatial random effects to identify factors associated with the spatial distribution of infection. Prevalence of schistosomiasis was higher in Hunan (12.8%) than Jiangxi (2.6%). Spatial distribution of schistosomiasis varied at pixel level (0.1 × 0.1 km), and was significantly associated with distance to nearest waterbody (km, β = −1.158; 95% credible interval [CrI]: −2.104, −0.116) in Hunan and temperature (°C, β = −4.359; 95% CrI: −9.641, −0.055) in Jiangxi. The spatial distribution of schistosomiasis in Hunan and Jiangxi varied substantially and was significantly associated with distance to nearest waterbody. Prevalence of schistosomiasis decreased with increasing distance to nearest waterbody in Hunan, indicating that schistosomiasis control should target individuals in close proximity to open water sources as they are at highest risk of infection.

Visual Simultaneous Localization and Mapping (SLAM) system is mainly used in real-time localization and mapping tasks of robots in various complex environments, while traditional monocular vision algorithms are struggling to cope with weak texture and dynamic scenes. To solve these problems, this work presents an object detection and clustering assisted SLAM algorithm (OC-SLAM), which adopts a faster object detection algorithm to add semantic information to the image and conducts geometrical constraint on the dynamic keypoints in the prediction box to optimize the camera pose. It also uses RGB-D camera to perform dense point cloud reconstruction with the dynamic objects rejected, and facilitates European clustering of dense point clouds to jointly eliminate dynamic features combining with object detection algorithm. Experiments in the TUM dataset indicate that OC-SLAM enhances the localization accuracy of the SLAM system in the dynamic environments compared with original algorithm and it has shown impressive performance in the localizition and can build a more precise dense point cloud map in dynamic scenes.

Rational and purposeful designs of amorphous materials with desirable structures are difficult to implement due to the complex and unordered nature of such materials. In this work, a modelling algorithm was proposed for amorphous covalent triazine-based polymers to construct atomistic representative models that can reproduce the experimentally measured properties of experimental samples. The constructed models were examined through comparisons of simulated and experimental properties, such as surface area, pore volume, and structure factor, and further validated by the good consistency observed among these properties. To assess the predictive capability of the modelling algorithm, we used a new covalent triazine-based polymer and predicted its porosity by constructing a simulated model. The predicted results on the surface area and pore volume of the simulated model were quantitatively consistent with the experimental data derived from the experimentally synthesized sample. This consistency reveals the predictive capacity of the proposed modelling algorithm. The algorithm could be a promising approach to predict and develop advanced covalent triazine-based polymers for multiple applications.

The structures of amorphous materials are generally difficult to characterize and comprehend due to their unordered nature and indirect measurement techniques. However, molecular simulation has been considered as an alternative method that can provide molecular-level information supplementary to experimental techniques. In this work, a new approach for modelling the atomistic structures of amorphous covalent triazine-based polymers is proposed and employed on two experimentally synthesized covalent triazine-based polymers. To examine the proposed modelling approach, the properties of the established models, such as surface areas, pore volumes, structure factors and N2 adsorption isotherms, were calculated and compared with the experimental data. Excellent consistencies were observed between the simulated models and experimental samples, consequently validating the proposed models and the modelling approach. Moreover, the proposed modelling approach can be applied to new covalent triazine-based polymers for predictive purposes and to provide design strategies for future synthesis works.

Indoor air quality (IAQ) monitoring has attracted increasing attention with the rapid development of industrialization and urbanization in the modern society as people typically spend more than 80% of their time in indoor environments. A novel IAQ detector (IAQD) integrated with multiple communication interfaces has been designed, built, programmed, deployed, and tested in order to meet the requirements of wide variety of scenarios. The IAQD measures the IAQ data, including temperature, humidity, CO2, dust, and formaldehyde timely. With state-of-the-art Internet of Things (IoT) technologies, the IAQD is integrated with Modbus, LoRa, WiFi, general packet radio service, and NB-IoT communication interfaces, which enables to be applied to wired communications, short-range wireless communications, and remote transmission to the cloud. The designed software in cloud allows users to track the IAQ of their home or office or industries everywhere. The performance IAQD is evaluated in terms of packet loss rate and time delay. The evaluation of IAQD are demonstrated and analyzed within the office environment over a week. Experimental results show that the proposed system is effectiveness in measuring the air-quality status and provide excellent consistency and stability.

Acoustic micro-membranes (AMMs) have theoretical advantages in terms of light weight yet high sound transmission loss (STL) at low frequency, but an actual medium- or large-scale specimen usually shows a significant performance degradation. Those lumped-parameter models developed so far lose their accuracy on theoretically describing the actual sound transmission loss of such an assembly. In this paper, the influence of the frame vibration is explored, and an acoustic theory based on a distributed parameter system is established. By coupling the vibration of the frame and the membranes, this theory shows how the acoustic impedance of the assembly depends on the number of membrane cells and the dimensions of the membranes and frame. As the assembly becomes larger, its global response is no longer dominated by the membrane but by the frame, while the latter determines the upper limit of the STL of the whole assembly. Compared to the well-developed lumped-parameter model that works only for small-scale AMMs, this work provides a theoretical foundation for designing larger size yet high loss AMMs, and may pave the way for their use in noise control engineering.

In this study, to reduce the formation of organic acid during 1,3-propanediol biosynthesis in Klebsiella pneumoniae, a method combining UV mutagenesis and high-throughput screening with pH color plates was employed to obtain K. pneumoniae mutants. When compared with the parent strain, the total organic acid formation by the mutant decreased, whereas 1,3-propanediol biosynthesis increased after 24 h anaerobic shake flask culture. Subsequently, genetic changes in the mutant were analyzed by whole-genome sequencing and verified by signal gene deletion. Mutation of the rpoS gene was confirmed to contribute to the regulation of organic acid synthesis in K. pneumoniae. Besides, rpoS deletion eliminated the formation of 2,3-butanediol, the main byproduct produced during 1,3-propanediol fermentation, indicating the role of rpoS in metabolic regulation in K. pneumoniae. Thus, a K. pneumoniae mutant was developed, which could produce lower organic acid during 1,3-propanediol fermentation due to an rpoS mutation in this study.

The exponential increase in the number of genomes deposited in public databases can help us gain a more holistic understanding of the phylogeny and epidemiology of Klebsiella pneumoniae. However, inferring the evolutionary relationships of K. pneumoniae based on big genomic data is challenging for existing methods. In this study, core genes of K. pneumoniae were determined and analysed in terms of differences in GC content, mutation rate, size, and potential functions. We then developed a stable genes-based method for big data analysis and compared it with existing methods. Our new method achieved a higher resolution phylogenetic analysis of K. pneumoniae. Using this genes-based method, we explored global phylogenetic relationships based on a public database of nearly 953 genomes. The results provide useful information to facilitate the phylogenetic and epidemiological analysis of K. pneumoniae, and the findings are relevant for security applications.

The electronic nose is the olfactory organ of the robot, which is composed of a large number of sensors to perceive the smell of objects through free diffusion. Traditionally, it is difficult to realize the active perception function, and it is difficult to meet the requirements of small size, low cost, and quick response that robots require. In order to address these issues, a novel electronic nose with active perception was designed and an ensemble learning method was proposed to distinguish the smell of different objects. An array of three MQ303 semiconductor gas sensors and an electrochemical sensor DART-2-Fe5 were used to construct the novel electronic nose, and the proposed ensemble learning method with four algorithms realized the active odor perception function. The experiment results verified that the accuracy of the active odor perception can reach more than 90%, even though it used 30% training data. The novel electronic nose with active perception based on the ensemble learning method can improve the efficiency and accuracy of odor data collection and olfactory perception.

Short-term prognosis of advanced schistosomiasis has not been well studied. We aimed to construct prognostic models using machine learning algorithms and to identify the most important predictors by utilising routinely available data under the government medical assistance programme. An established database of advanced schistosomiasis in Hunan, China was utilised for analysis. A total of 9541 patients for the period from January 2008 to December 2018 were enrolled in this study. Candidate predictors were selected from demographics, clinical features, medical examinations and test results. We applied five machine learning algorithms to construct 1 year prognostic models: logistic regression (LR), decision tree (DT), random forest (RF), artificial neural network (ANN) and extreme gradient boosting (XGBoost). An area under the receiver operating characteristic curve (AUC) was used to evaluate the model performance. The important predictors of the optimal model for unfavourable prognosis within 1 year were identified and ranked. There were 1249 (13.1%) cases having unfavourable prognoses within 1 year of discharge. The mean age of all participants was 61.94 years, of whom 70.9% were male. In general, XGBoost showed the best predictive performance with the highest AUC (0.846; 95% confidence interval (CI): 0.821, 0.871), compared with LR (0.798; 95% CI: 0.770, 0.827), DT (0.766; 95% CI: 0.733, 0.800), RF (0.823; 95% CI: 0.796, 0.851), and ANN (0.806; 95% CI: 0.778, 0.835). Five most important predictors identified by XGBoost were ascitic fluid volume, haemoglobin (HB), total bilirubin (TB), albumin (ALB), and platelets (PT). We proposed XGBoost as the best algorithm for the evaluation of a 1 year prognosis of advanced schistosomiasis. It is considered to be a simple and useful tool for the short-term prediction of an unfavourable prognosis for advanced schistosomiasis in clinical settings.

Background Constant emerging sites infested with Oncomelania hupensis (O. hupensis) impede the goal realization of eliminating schistosomiasis. The study assessed the spatial and temporal distributions of new Oncomelania snail habitats in Hunan Province from 1949 to 2016. Methods We used the data from annual snail surveys throughout Hunan Province for the period from 1949 to 2016. Global Moran’s I, Anselin local Moran’s I statistics (LISA) and a retrospective space-time permutation model were applied to determine the spatial and temporal distributions of emerging snail-infested sites. Results There were newly discovered snail-infested sites almost every year in 1949–2016, except for the years of 1993, 2009 and 2012. The number of emerging sites varied significantly in the five time periods (1949–1954, 1955–1976, 1977–1986, 1986–2003 and 2004–2016) (H = 25.35, p I being 0.52, 0.49 and 0.44, respectively. High-value spatial clusters (HH) were mainly concentrated along the Lishui River and in Xiangyin County. There were four marshland clusters, two hill clusters and three inner embankment clusters after 1976. Conclusions Lower reaches of the Lishui River and the Dongting Lake estuary were the high-risk regions for new Oncomelania snail habitats with long durations. Snail surveillance should be strengthened at stubborn snail-infested sites at the inner embankments. Grazing prohibition in snail-infested grasslands should be a focus in marshlands. The management of bovines in Xiangyin County is of great importance. Graphical Abstract

Advanced schistosomiasis has become a major public health problem in areas with a heavy burden of schistosomiasis infection. Our objective was to determine the incidence and prevalence of advanced schistosomiasis and risk factors associated with case fatality of advanced schistosomiasis. Data were abstracted from hospitalization records of patients with advanced schistosomiasis from Hunan Province, China. The incidence and prevalence of advanced schistosomiasis were determined and the risk factors for death in advanced patients were assessed using logistic regression analysis. A total of 10,362 patients with advanced schistosomiasis were recruited into our study and 65% of them were categorized as the ascites type. There were 1249 deaths between 2005 and 2018 and the case fatality was 12.05%. The incidence of advanced schistosomiasis increased from 2002 to 2010, peaked in 2010 and then leveled off. The prevalence of advanced schistosomiasis increased from 2005 to 2014, and was stable afterwards. HBV was a risk factor for death in advanced patients (adjusted odds ratio (aOR=1.93, 95% confidence interval (CI: 1.55 to 2.41). Patients without splenectomy had a higher risk of death (aOR=1.29, 95%CI: 1.08 to 1.56). Upper gastrointestinal bleeding was positively associated with the risk of death (aOR=1.42, 95% CI: 1.15 to 1.76). Besides, abnormal ALT, ascites and anemia were also significantly associated with the risk of death in advanced patients. Advanced schistosomiasis was effectively controlled in recent years. Splenectomy could reduce the case fatality of advanced patients. HBV infection, abnormal ALT, upper gastrointestinal bleeding and anemia also predicted the risk of death for advanced patients.

This paper presents a versatile multi-sensor fusion method and decision-making algorithm for ambulatory and continuous patient monitoring purposes via a body sensor network (BSN). Gait features including spatio-temporal parameters, gait asymmetry, and regularity were identified and estimated from individual patients data collected from clinical trials. Hence, a continuous assessment and diagnosis of the improvement or the deterioration of the lower limb rehabilitation process is ensured. The experimental results from 10-m free walking trials indicated that the proposed method has a good consistency with the clinically used observational method. The gait assessment results were comparable with previous studies. Gait segmentation succeed even when the pace deviates significantly from the healthy subjects' reference value, which provides proof of objectivity and effectiveness of this preliminary research, namely, using wearable inertial measurement unit (IMUs) as an indicator to detect gait abnormality in subjects with neurological disorders. The hypothesis of gait quality-related clinical trials were designed and validated via both machine learning approach and feature layer data fusion. With further validations, the proposed inertial sensor-based gait assessment approach has the potential to be applied both routinely in clinical practice and for tele-health scenes such as fall detection of the elder at home.

N,O-containing micropore heteroatom carbon frameworks (MHCFs@600) were synthesized by ionothermal synthesis approach using 4,4′-(4-oxophthalazine-1,3(4H)-diyl)dibenzonitrile. (CH3CH2CH2CH2)4N+(PF6)− was then introduced into the hierarchical pore structure with pore size ranging from 0.3 to 5.8 nm by simple and high-efficiency host–guest interaction to obtain an electrode material (f-MHCFs@600) rich in N (6.15 wt %), O (8.22 wt %), P (1.61 wt %), and F (5.86 wt %). After introduction of F and P, the prepared f-MHCFs@600 showed a voltage window (1.4 V) larger than the theoretical potential of water (1.23 V). f-MHCFs@600 exhibited a high specific capacitance of 244.8 F g–1 at 0.1 A g–1 and an excellent cycling stability (capacitance retention of 98.5% over 10 000 cycles) in a three-electrode system at a high voltage window (1.4 V) because of the stable existence of P and F. In particular, compared to the MHCFs@600, RΩ decreased from 1.68 to 0.318 Ω and Rct changed from 25 to 4.2 Ω in the high-frequency area ...

With lightweight, high energy conversion and low cost, the triboelectric nanogenerators (TENGs) have presented its tremendous potential as a portable sustainable power source to small-scale portable/wearable electronic device. However, the insufficient output power of TENG is a bottleneck for its practical applications. Here, we report an ultrahigh output power, a whirligig-inspired TENG (Wi-TENG) designed according to an antiqueue whirligig toy that is capable of converting low-frequency pulling motion into a high-frequency rotation. It shows that the rotor in the Wi-TENG achieves a maximum speed of 11,250 rpm. Ultrahigh charge transfer quantity of ~ 310 μC and output power of 40.18 mW are obtained by per pulling of Wi-TENG. Moreover, a maximum short-circuit current of 317 μA and a constant open-circuit voltage peak value of 153 V can be generated by the Wi-TENG, which can rapidly charge a commercial capacitance (100 μF) to ~14 V within 10 s. After power management, this Wi-TENG is successfully demonstrated as a portable sustainable power source for driving a commercial blood glucose meter or a temperature-humidity sensor. This study presents the potential of Wi-TENG as a reliable portable instant power supply for personal health monitoring devices.

Cyber security has become a serious concern as the internet penetrates every corner of our life over the last two decades. The rapidly developing human–machine interfacing calls for an effective and continuous authentication solution. Herein, we developed a two-factor, pressure-enhanced keystroke-dynamics-based security system that is capable of authenticating and even identifying users through their unique typing behavior. The system consists of a rationally designed triboelectric keystroke device that converts typing motions into analog electrical signals, and a support vector machine (SVM) algorithm-based software platform for user classification. This unconventional keystroke device is self-powered, stretchable and water/dust proof, which makes it highly mobile and applicable to versatile working environments. The promising application of this novel system in the financial and computing industry can push cyber security to the next level, where leaked passwords would possibly be of no concern.

Due to their strong transmission loss (TL) at low frequencies, acoustic micro-membranes (AMMs) have been the subject of many studies. In this paper, a theoretical model for AMMs is established which gives a direct insight into their sound insulation qualities. Analysis of the model’s acoustics shows how the sound insulation provided by a membrane can be significantly enhanced, and reveals the intrinsic characteristic of AMMs in mid-low frequency range. Further analysis on two AMMs separated by an air gap gives a quantitative description on how performance varies with the air gap. Using the theoretical model developed here, it is a straightforward matter to adjust an AMM’s parameters to achieve a desired level of attenuation. This work opens the way for the potential application of AMMs in noise control engineering.

For clusters of UAVs, the scale and density of the cluster determine its ability to solve the task. With the increasing density of aerial vehicles, effectively planning a reasonable flight path and avoiding conflicts among flight paths have become key problems for UAV clusters. The traditional control method is to detect potential conflicts through radar monitoring or location reporting in the air and to then change the flight path, including the height, heading, and speed, through manual instruction. To solve the problem of path conflicts for UAV clusters, a method for calculating the collision probabilities of UAVs is established under the constraints of mission space and the number of UAVs. In cluster flight mode, automatic tracking and prediction of UAV cluster tracks are implemented to avoid path conflicts in clusters. In addition, to address the inconsistency problem because of noise caused by the state information of multi UAV communication under a dynamic environment, a state estimation method is proposed based on the Kalman algorithm. To achieve aircraft track planning, cluster state prediction and collision probability are eventually calculated to avoid the clusters of formation UAVs conflicting on paths during flight. Finally, the simulation results verify the validity and effectiveness of the proposed method in multi UAV formation flight planning.

Acoustic performance of a micro-perforated panel with an incompletely partitioned cavity (MPPIPC) is investigated. A MPPIPC is achieved by inserting separators, which are shorter than the depth of the cavity, periodically behind the micro-perforated panel (MPP). Due to these separators, the sound field in the cavity is significantly changed. This paper reveals these unique sound reflection modes among the separators, based on which a theoretical model is proposed to calculate the absorption coefficient of a MPPIPC in the diffusion field. Experiments verified the theoretical predictions. These results indicate that the appropriately arranged insertion can improve the performance of a MPP absorber effectively at low frequencies.

Many efforts have been made to learn the fertilization effects on greenhouse gas (GHG) emissions in the current crop season of multiple cropping systems, however, residual effects on the succeeding crop season are not clear. Based on a thirty-year fertilization experiment, we investigated the impacts of wheat fertilization on GHG emissions in the succeeding soybean season. There were five fertilization regimes for the wheat-soybean cropping system, including sole organic manure (M), balanced chemical NPK fertilizer (NPK), chemical NPK plus manure (NPKM), chemical NP plus wheat straw (NPS), and no fertilizer application (CK). Fertilization significantly affected GHG emissions not only in the current fertilizing season of winter wheat but also in the non-fertilizing season of summer soybean. Compared to the NPK treatment, the M and NPKM treatments stimulated annual soil CO 2 and N 2 O emissions, and reduced CH 4 emissions. The M and NPKM treatments also significantly increased soil organic C and total N contents, soil microbial biomass C and N, and NH 4 N and NO 3 N concentrations, especially in the soybean season. Although fertilizers were only applied in wheat season, the emissions of CO 2 and N 2 O were higher in the soybean season. At the cropping system scale, the treatments of M and NPKM significantly increased annual global warming potential (GWP) by 75.5% and 38.3%, respectively, compared to the NPK. Sole manure application (M) significantly increased greenhouse gas intensity (GHGI) in comparison with the NPK, while there was no significant increment in the GHGI caused by the treatments of chemical fertilizer plus manure (NPKM) and crop straw (NPS).

Galvanized steel pipes are widely used for indoor gas distribution. Leakage in the pipeline system is prone to occur in screw thread connection as opposed to tube itself. Early detection of small leak is of great significance to ensure the safety and comfort in doors. This work presents an experimental investigation on AE based small leak detection of galvanized steel pipe due to screw thread loosening. The waveform, frequency and energy signatures of the AE signals are first extracted and compared. Regarding the fact that the small leak signals lack obvious characteristics and are easily submerged in background noise, a pattern recognition method based on support vector machine (SVM) is employed for leak detection. Through training and testing on the experimental data, it is verified that the algorithm based on SVM with RBF kernel function is of the highest accuracy and efficiency with a 1.9% false alarm rate at most.

The design of network layer protocol is one of the key issues in the research of Internet of things(IoT). We propose to design a network layer protocol with focus on the application of specific scenario. In this paper, the indoor environment monitoring application scenario is taken as an example and a matching network layer protocol is proposed. In view of the characteristics of multiple fixed nodes in the indoor environment monitoring scenarios, routing hierarchical design is carried out. The inner layer is based on the greedy algorithm, and the outer mobile nodes establish routing by grouping broadcast requests. On this basis, the concept of node importance weight is set as the basis for network establishment and routing repair. The performance evaluation shows that the greedy networking algorithms with multiple fixed nodes is better than the classical AODV, DSDV, ZBR and other wireless sensor network protocols in terms of packet delivery rate and average end-to-end delay in the application scenarios of indoor environmental monitoring.

Based on the high-frequency structure of the T-shape staggered double-vane, an electron optical system (EOS) with uniform magnetic field for 220 GHz sheet beam TWT is formed with the help of 3-D simulation software CST. The simulation results show that the current and anode voltage of the electron gun are 158 mA and 22.1 kV, respectively, and the electron beam transmission efficiency is 97.2% under the axial magnetic field of 0.38 T in a 37 mm length drift tube with $\pmb{0.8} \mathbf{mm}\ \times \ \pmb{0.15}\ \mathbf{mm}$ beam tunnel.

Covalent triazine-based frameworks (CTFs) have been considered as new promising candidates for host materials in lithium–sulfur batteries (LSBs). However, few people have focused on the molecular structure design of the building units of the CTFs to improve the sulfur loading contents and electrochemical performance, whereas the different types, contents of functional groups, and molecular lengths largely dominate the battery’s performance. Herein, we purposefully designed and synthesized N, O-containing CTFs (NO-CTF-1 and NO-CTF-2) by the N, O-containing building units for LSB electrodes and explored the influence of heteroatoms (N and O) on the polysulfide redox conversion reactions in detail. N and O heteroatoms with extra pair of electrons in NO-CTFs can interact with the strong Lewis acid of terminal Li atoms in lithium polysulfides. The unique pore structure and the fast heterogeneous nucleation process of Li2S accelerate the conversion of lithium polysulfides in a working battery. As a result, NO-CTF-1 delivers a high reversible capacity of 1250 mA h g−1 at 0.1 C, an outstanding cycling stability with a capacity retention of 92% at 0.5 C (300 cycles), and an excellent rate performance of up to 678 mA h g−1 at 2 C. This work provides a new insight into the LSB electrode materials to rationally design the building unit of CTFs and inspires the exploration of the effect of nitrogen, oxygen, and other heteroatoms on the heterogeneous nucleation of Li2S.

Triboelectric nanogenerator (TENG) has the output characteristics of high voltage but low current/charge-transfer, making its low efficiency in powering most of electronics. To address this problem, power management circuits consisting of coupled inductors or transformers are usually employed. Here we report an inductor-free, auto-power-management design based on automatic switches between serial-connected and parallel-connected capacitors in a rationally designed manner, so that the output voltage can be lowered and the output charge is enhanced in proportion. In conjunction to theoretical analysis, a TENG along with proof-of-concept power-management units as automatically driven by the triggering motion for TENG is fabricated, which improves the rate for charging a supercapacitor by 5 times. Compared to previous work, this power-management design shows advantages of capability for harvesting low power/frequency scale energy, high scalability, and light weight, which paves a new approach for achieving high-efficient portable TENG-based self-powered system.

The process of charge transfer based on triboelectrification (TE) and contact electrification (CE) has been recently utilized as the basis for a new and promising energy harvesting technology, i.e., triboelectric nanogenerators, as well as selfpowered sensors and systems. The electrostatic charge transfer between two surfaces can occur in both the TE and the CE modes depending on the involvement of relative sliding friction. Does the sliding behavior in TE induce any fundamental difference in the charge transfer from the CE? Few studies are available on this comparison because of the challenges in ruling out the effect of the contact area using traditional macro-scale characterization methods. This paper provides the first study on the fundamental differences in CE and TE at the nanoscale based on scanning probe microscopic methods. A quantitative comparison of the two processes at equivalent contact time and force is provided, and the results suggest that the charge transfer from TE is much faster than that from CE, but the saturation value of the transferred charge density is the same. The measured frictional energy dissipation of ∼11 eV when the tip scans over distance of 1 A sheds light on a potential mechanism: The friction may facilitate the charge transfer process via electronic excitation. These results provide fundamental guidance for the selection of materials and device structures to enable the TE or the CE in different applications; the CE mode is favorable for frequent moderate contact such as vibration energy harvesting and the TE mode is favorable for instant movement such as harvesting of energy from human walking.

Harvesting biomechanical energy is an important route for providing electricity to sustainably drive wearable electronics, which currently still use batteries and therefore need to be charged or replaced/disposed frequently. Here we report an approach that can continuously power wearable electronics only by human motion, realized through a triboelectric nanogenerator (TENG) with optimized materials and structural design. Fabricated by elastomeric materials and a helix inner electrode sticking on a tube with the dielectric layer and outer electrode, the TENG has desirable features including flexibility, stretchability, isotropy, weavability, water-resistance and a high surface charge density of 250 μC m−2. With only the energy extracted from walking or jogging by the TENG that is built in outsoles, wearable electronics such as an electronic watch and fitness tracker can be immediately and continuously powered., Harvesting bio-mechanical energy is a promising route to powering wearable electronics, however design obstacles remain. Here the authors report on a triboelectric nanogenerator with optimized materials and design that can sustainably power an electronic watch and fitness tracker solely by human motion.

Ocean wave associated energy is huge, but it has little use toward world energy. Although such blue energy is capable of meeting all of our energy needs, there is no effective way to harvest it due to its low frequency and irregular amplitude, which may restrict the application of traditional power generators. In this work, we report a hybrid nanogenerator that consists of a spiral-interdigitated-electrode triboelectric nanogenerator (S-TENG) and a wrap-around electromagnetic generator (W-EMG) for harvesting ocean energy. In this design, the S-TENG can be fully isolated from the external environment through packaging and indirectly driven by the noncontact attractive forces between pairs of magnets, and W-EMG can be easily hybridized. Notably, the hybrid nanogenerator could generate electricity under either rotation mode or fluctuation mode to collect energy in ocean tide, current, and wave energy due to the unique structural design. In addition, the characteristics and advantages of outputs indicate that the S-TENG is irreplaceable for harvesting low rotation speeds (100 rpm) or motion frequencies (2 Hz) energy, which fits the frequency range for most of the water wave based blue energy, while W-EMG is able to produce larger output at high frequencies (10 Hz). The complementary output can be maximized and hybridized for harvesting energy in a broad frequency range. Finally, a single hybrid nanogenerator unit was demonstrated to harvest blue energy as a practical power source to drive several LEDs under different simulated water wave conditions. We also proposed a blue energy harvesting system floating on the ocean surface that could simultaneously harvest wind, solar, and wave energy. The proposed hybrid nanogenerator renders an effective and sustainable progress in practical applications of the hybrid nanogenerator toward harvesting water wave energy offered by nature.

The Dongying Formation (Ed) and the first member of the Shahejie Formation (Es1) in the central Raoyang Sag cover about 1705 m-long sedimentary series of terrestrial lacustrine infill. We employed the gamma-ray (GR) log data as a paleoclimatic and paleoenvironmental proxy to conduct the high-resolution cyclostratigraphy research in well W33 and W62. Prominent sedimentary cycles in decameters and meters were revealed by multi-taper (MTM) power spectra, evolutionary fast Flourier transformation (FFT) and correlation coefficient analyses in the Es1 and Ed intervals. The 405 kyr long eccentricity, 125 kyr and 100 kyr short eccentricity, 40 kyr obliquity, and 23 kyr precession can be recognized with a wavelength ratio of approximately 20:5:2:1, respectively. By tuning the 405 kyr filter output in well W33 to the orbital target curve of La2010d astronomical solution, we established an astronomical time scale (ATS) that provided absolute age controls during the Oligocene and shed light on the event correlation among isolated depressions in the Bohai Bay Basin. Sediment accumulation rates (SARs) were derived from the extracted 405 kyr long eccentricity and were tested with an average of 17 cm/kyr. Age boundaries of Ng/Ed1, Ed1/Ed2, Ed2/Ed3, Ed3/Es1 and Es1/Es2 are 23.03 Ma, 24.34 Ma, 25.53 Ma, 29.05 Ma and 33.10 Ma, respectively. Based on the ATS and SARs, we discussed the depositional evolution within age boundaries, cause of high SARs and origin of formation overpressure. After the largest lake transgression, shallow-water deltas and fluvial plains transitionally dominate the central Raoyang Sag with shallowing water depth. Thin interlayers of mudstones and sandstones originate from shallow-water deltaic systems with low sand-to-mud ratios. Under high SARs enhanced by mountain uplift and low sand-to-mud ratios, formation overpressure results mainly from high porosities in under-compacted mudstone intervals.

Triboelectric nanogenerators (TENGs) have been invented as a new technology for harvesting mechanical energy, with enormous advantages. One of the major themes in their development is the improvement of the power output, which is fundamentally determined by the triboelectric charge density. Besides the demonstrated physical surface engineering methods to enhance this density, chemical surface functionalization to modify the surface potential could be a more effective and direct approach. In this paper, we introduced the method of using self-assembled monolayers (SAMs) to functionalize surfaces for the enhancement of TENGs' output. By using thiol molecules with different head groups to functionalize Au surfaces, the influence of head groups on both the surface potential and the triboelectric charge density was systematically studied, which reveals their direct correlation. With amine as the head group, the TENG's output power is enhanced by ∼4 times. By using silane-SAMs with an amine head group to modify the silica surface, this approach is also demonstrated for insulating triboelectric layers in TENGs. This research provides an important route for the future research on improving TENGs' output through materials optimization.