Influencing factors on ammonia emissions from gasoline vehicles: A systematic review and meta-analysis.

Ammonia, a significant precursor for secondary inorganic aerosols, plays a pivotal role in new particle formation. Inventories and source apportionment studies have identified vehicular exhaust as a primary source of atmospheric ammonia in urban regions. Existing research on the factors influencing ammonia emissions from gasoline vehicles exhibits substantial inconsistencies in both test results and analyses. The lack of a uniform pattern in ammonia emissions across different standard vehicles and the significant overlap in test results across diverse operational conditions highlight the complexities in this field of study. While individual results can be interpreted through a mechanistic lens, disparate studies often lack a common explanatory framework. To address this gap, our study leverages the robust and comprehensive approach of meta-analysis to reconcile these inconsistencies and provide a more precise understanding of the factors influencing ammonia emissions from gasoline vehicles. A large number (N = 537) of ammonia emission factors were extracted after screening >1628 publications. The combined ammonia emission factor was 23.57 ± 24.94 mg/km. Emission standards, engine type, ambient temperatures, mileage, vehicle speed, and engine displacement have a significant impact on ammonia emission factors, explaining the ammonia emission factor by up to 50.63 %, with speed being the most significant factor. All these factors are attributed to the interplay of catalyst properties, lambda, and residence time (space velocity). In the current fleet, ammonia emission control is relatively insufficient under low-speed and ultra-high speed, low temperature, and ultra-high mileage conditions. Since ammonia emission factors do not monotonically decrease with the upgrading of motor vehicle emission standards, it is called for the addition of ammonia emission factors indicators in motor vehicle emission standards, and stipulation of targeted testing procedures and testing instruments.

Transmission efficiency of one tooth difference sine tooth profile planetary reducer.

The structural size of space exploration and unmanned aerial vehicle manipulator is required to be as small as possible, and the weight must be as light as possible. However, the existing reducers have difficulties in achieving lightweight robot joint drive systems. For it, this paper proposes a single tooth difference continuous sine tooth profile K-H-V type planetary reducer in which pin type equi-speed output mechanism is used. Concerning the reducer, its structural composition and meshing characteristics are analyzed. Based on the findings, the meshing pair's force, the friction coefficient, and the meshing efficiency are investigated. The force and bearing efficiency of the planetary gear are studied, and the efficiency of the equi-speed output mechanism in addition to the total efficiency of the reducer are determined. Moreover, the efficiency of the reducer prototype is measured and compared to the calculated efficiencies. The results show that the gear modulus, the input speed, the surface roughness, and the lubricating oil viscosity have a significant effect on the meshing efficiency. Furthermore, the efficiency of the eccentric bearings is significantly lower than that of the non-eccentric bearings. Therefore, it can be increased by tuning the pressure angle, the tooth number of planetary gear, the tooth height, and the distribution circle radius of the pinhole. In addition, the power loss of the output mechanism has the greatest effect on transmission efficiency. Reducing the center distance, the inner diameter of the rotating arm bearing, and the tooth number of planetary gear, as well as increasing the outer diameter of the pin shaft can reduce the power loss of the output mechanism. The experimental efficiency of the reducer prototype is 82.47%, its computational efficiency is 83.72%, and its error is 1.25%, verifying the correctness of the efficiency calculation method.

Patronin regulates presynaptic microtubule organization and neuromuscular junction development in Drosophila.

Synapses are fundamental components of the animal nervous system. Synaptic cytoskeleton is essential for maintaining proper neuronal development and wiring. Perturbations in neuronal microtubules (MTs) are correlated with numerous neuropsychiatric disorders. Despite discovering multiple synaptic MT regulators, the importance of MT stability, and particularly the polarity of MT in synaptic function, is still under investigation. Here, we identify Patronin, an MT minus-end-binding protein, for its essential role in presynaptic regulation of MT organization and neuromuscular junction (NMJ) development. Analyses indicate that Patronin regulates synaptic development independent of Klp10A. Subsequent research elucidates that it is short stop (Shot), a member of the Spectraplakin family of large cytoskeletal linker molecules, works synergistically with Patronin to govern NMJ development. We further raise the possibility that normal synaptic MT polarity contributes to proper NMJ morphology. Overall, this study demonstrates an unprecedented role of Patronin, and a potential involvement of MT polarity in synaptic development.

Development of nanosecond spike pulse power supply for electrochemical micromachining.

The use of pulse voltage can greatly improve the precision of electrochemical microfabrication, and the narrower the pulse width of the applied pulse voltage signal, the higher the machining precision. However, the commonly used chopper circuit topology of pulse power supplies is limited by the maximum switching frequency of the field-effect transistor. To address this problem, this paper proposes a nanosecond pulse electrochemical micromachining power supply based on a differential circuit. The power supply uses the STM32F103C8T6 microcontroller as the control core to output high-performance rectangular waves through a DDS device. After differential, rectification, filtering, and power amplification processing, stable, frequency, amplitude, and pulse width adjustable spike pulse voltage signals are obtained. By establishing a system mathematical model and optimizing the time constant of the differential circuit, theoretically, the sub-nanosecond pulse width can be obtained. Prototype performance tests show that the power supply has a maximum frequency of 20 MHz, a minimum pulse width of 1.8 ns, and a maximum peak voltage of 10 V. By using this power supply for microhole electrochemical machining experiments, nanometer-level machining precision has been achieved.

Ultrahigh bandwidth measuring approach of an I-FOG based on axial magnetic sensitivity.

The bandwidth is one of the key indicators of the interferometric fiber optic gyroscope (I-FOG) in the application with high frequency jitter. The traditional bandwidth measurement equipment, such as the angular vibration table, can only provide angular vibrations of hundreds of hertz and cannot meet the measurement needs of a high bandwidth gyro. We propose an approach, with which a signal of several thousand hertz can be provided and can measure a high bandwidth of I-FOGs. The bandwidth measurement approach is based on the axial magnetic sensitivity. We present the measurement principle, derive the axial magnetic sensitivity expression of the fiber coil in I-FOGs, and demonstrate the bandwidth measuring system. With this system, the bandwidth of an I-FOG is measured and the experimental result shows that the bandwidth is ∼10 kHz. It is proved that this new, to the best of our knowledge, approach is capable of testing the bandwidth of the I-FOG at ultrahigh frequencies.

Evaluating city road dust emission characteristics with a dynamic method: A case study in Luoyang, China.

Road dust, a significant contributor to non-exhaust particulate matter emissions in urban transport, poses considerable health risks, necessitating accurate and high-resolution data for effective control. The traditional AP-42 method offers data on point-specific dust emissions, while vehicle-based testing ascertains the relative emission intensity in the road network. However, a clear mathematical relationship between these measurements has been elusive, limiting efficiency in emission control. By integrating the On-board Conventional Pollutant Monitoring System with the AP-42 method, we devised a dynamic link between the concentration of particles in vehicle plumes and actual road dust emissions. This relationship is substantiated by a notable correlation (R2 = 0.91) between our emission factors and those calculated using the AP-42 method. Significant variations emerged in dust emission factors across road types, with changes between -30.1 % to +57.79 % from the average (0.05 g·vehicle-1·km-1), in tandem with traffic flow fluctuations of approximately ±90 %. Meteorological factors, except for continuous rainfall, showed minimal impact on dust emissions. However, our findings revealed a significant underestimation (58.87 %) of road dust PM10 emissions by the AP-42 method. Intriguingly, we found that short-range emission hotspots substantially contribute to total emissions, suggesting a potential 50 % reduction by controlling merely 8.8 % ± 2.5 % of the total road length. Our research elucidates the interplay between road dust emissions, road types, and human activities. The application of a dynamic, high-resolution assessment method enhances our understanding of the impacts of road dust on urban particulate pollution, allows accurate hotspot identification, and aids in developing efficacious strategies for air quality enhancement.

Velocity and Out-Step Frequencies for a Micro-Swimmer Based on Spiral Carbon Nanotubes.

The existing producing processes of micro spiral swimmers are complex. Here, a microswimmer with a magnetic layer on the surface of the spiral carbon nanotubes is proposed, which has a simple producing process. For the microswimmer, its equations of the velocities and out-step frequency are deduced. Using these equations, the velocities and out-step frequency of the microswimmer and their changes with related parameters are investigated. Results show that its velocities are proportional to the radius and helix angle of the spiral carbon nanotubes, and its out-step frequencies are proportional to magnetic field strength, the helix angle and magnetic layer thicknesses of the spiral carbon nanotubes, and inversely proportional to the fluid viscosity. The out-step frequency of the microswimmer is measured, which is in good agreement with the calculative ones.

Multi-field coupled dynamics for a movable tooth drive system integrated with shape memory alloys.

The harmonic movable tooth drive system integrated with shape memory alloys has a small size and a large output torque. Its dynamics performance is the key factor for evaluating the drive system. Here, for the drive system, based on its structure and working principle, the coupled dynamics equations are deduced. Using the equations, changes of the natural frequencies of the drive system during the operation are investigated. Effects of the system parameters and SMA wires phase change process on the natural frequencies are analyzed. The nonlinear resonant frequencies of the drive system and its amplitude-frequency relationship are studied. Results show that natural frequencies of the drive system change periodically which is caused by SMA phase transformation during operation. The eccentricity, movable tooth radius, the wave generator radius and SMA wire length have also important effects on the natural frequencies of the drive system. The nonlinear resonant frequencies are smaller than linear resonant frequencies. In the design of the drive system, the coupled nonlinear effects of the temperature, phase change, stress and strain of the SMA wires, and the system parameters of the movable tooth drive system should be considered. In this paper, the coupled nonlinear dynamics model of the harmonic movable tooth drive system integrated with shape memory alloys is proposed in which the coupled effects of the temperature, phase change, stress and strain of the SMA, and the system parameters of the movable tooth drive system are considered.

Electrochemical micro-machining based on double feedback circuits.

Pulsed electrochemical micromachining accuracy predominantly depends on pulse duration. To obtain high accuracy, an expensive power source with ultra-short pulse duration is needed. An electrochemical micromachining method based on double feedback circuits is proposed in this work to achieve this aim. A positive feedback circuit plus a negative feedback circuit is used in the circuit of the pulsed electrochemical micromachining. Thus, the gains of the feedback circuits can control the pulse duration of the machining system. Experiments show that the machining resolution can be improved notably by an increase in the feedback gains. Using the method, one micro double cure beam is produced, and its accuracy gets to nanometer level under the condition of using an ordinary pulse duration power source.

A Piezoelectrically Excited ZnO Nanowire Mass Sensor with Closed-Loop Detection at Room Temperature.

One-dimensional nanobeam mass sensors offer an unprecedented ability to measure tiny masses or even the mass of individual molecules or atoms, enabling many interesting applications in the fields of mass spectrometry and atomic physics. However, current nano-beam mass sensors suffer from poor real-time test performance and high environment requirements. This paper proposes a piezoelectrically excited ZnO nanowire (NW) mass sensor with closed-loop detection at room temperature to break this limitation. It is detected that the designed piezo-excited ZnO NW could operate at room temperature with a resonant frequency of 417.35 MHz, a quality factor of 3010, a mass sensitivity of -8.1 Hz/zg, and a resolution of 192 zg. The multi-field coupling dynamic model of ZnO NW mass sensor under piezoelectric excitation was established and solved. The nonlinear amplitude-frequency characteristic formula, frequency formula, modal function, sensitivity curve, and linear operating interval were obtained. The ZnO NW mass sensor was fabricated by a top-down method and its response to ethanol gas molecules was tested at room temperature. Experiments show that the sensor has high sensitivity, good closed-loop tracking performance, and high linearity, which provides great potential for the detection of biochemical reaction process of biological particles based on mechanics.

Image Semantic Recognition and Segmentation Algorithm of Colorimetric Sensor Array Based on Deep Convolutional Neural Network.

Semantic feature recognition in colour images is required for identifying uneven patterns in object detection and classification. The semantic features are identified by segmenting the colorimetric sensor array features through machine learning paradigms. Semantic segmentation is a method for identifying distinct elements in an image. This can be considered a task involving image classification at the pixel level. This article introduces a semantic feature-dependent array segmentation method (SFASM) to improve recognition accuracy due to irregular semantics. The proposed method incorporates a deep convolutional neural network for detecting the semantic and un-semantic features based on sensor array representations. The colour distributions per array are identified for horizontal and vertical semantics analysis. In this analysis, deep learning classifies the uneven patterns based on colour distribution, i.e. the consecutive and scattered colour distribution pixels in an array are correlated for their similarity. This similarity identification is maximized through max-pooling and recurrent iterations, preventing detection errors. The proposed method classifies the semantic features for further correlation sections, improving the accuracy. The proposed method's performance is thus validated using the metrics precision, analysis time and F1-Score.

A Precise Closed-Loop Controlled ZnO Nanowire Resonator Operating at Room Temperature.

To realize the real-time measurement of masses of nanoparticles, virus molecules, organic macromolecules, and gas molecules, and to analyze their physical and chemical properties, a ZnO nanowire (NW) resonator operating at room temperature with an ultrahigh resonant frequency, real-time detection, and high precision was designed and developed in this study. The machining method is simple and easy to integrate into an integrated circuit. A closed-loop detection system based on a phase-locked loop (PLL) and frequency modulation technology (FM) was used to perform closed-loop testing of electromagnetically excited ZnO NW. The first-order resonance frequency of the resonator was 10.358 MHz, the quality factor Q value was about 600, the frequency fluctuation value fRMS was about 300 Hz, and the FM range could reach 200 kHz. The equivalent circuit model of the resonator was established, the parasitic parameters during the test were obtained, and the frequency accuracy and phase noise of the resonator were analyzed and tested. The experimental results show that the closed-loop system can automatically control the resonator in a wide range of frequency bands, with good tracking performance of the resonant frequency, small frequency fluctuation, and low phase noise level.

A Security Concept Based on Scaler Distribution of a Novel Intrusion Detection Device for Wireless Sensor Networks in a Smart Environment.

Following the significant improvement of technology in terms of data collection and treatment during the last decades, the notion of a smart environment has widely taken an important pedestal in the science industry. Built in order to better manage assets, smart environments provide a livable environment for users or citizens through the deployment of sensors responsible for data collection. Much research has been done to provide security to the involved data, which are extremely sensitive. However, due to the small size and the memory constraint of the sensors, many of these works are difficult to implement. In this paper, a different concept for wireless sensor security in smart environments is presented. The proposed security system, which is based on the scaler distribution of a novel electronic device, the intrusion detection system (IDS), reduces the computational functions of the sensors and therefore maximizes their efficiency. The IDS also introduces the concept of the feedback signal and "trust table" used to trigger the detection and isolation mechanism in case of attacks. Generally, it ensures the whole network security through cooperation with other IDSs and, therefore, eliminates the problem of security holes that may occur while adopting such a security technique.

NLRP1 inflammasome contributes to chronic stress-induced depressive-like behaviors in mice.

BACKGROUND: Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, and inflammation has been considered crucial components of the pathogenesis of depression. NLRP1 inflammasome-driven inflammatory response is believed to participate in many neurological disorders. However, it is unclear whether NLRP1 inflammasome is implicated in the development of depression. METHODS: Animal models of depression were established by four different chronic stress stimuli including chronic unpredictable mild stress (CUMS), chronic restrain stress (CRS), chronic social defeat stress (CSDS), and repeat social defeat stress (RSDS). Depressive-like behaviors were determined by sucrose preference test (SPT), forced swim test (FST), tail-suspension test (TST), open-field test (OFT), social interaction test (SIT), and light-dark test (LDT). The expression of NLRP1 inflammasome complexes, BDNF, and CXCL1/CXCR2 were tested by western blot and quantitative real-time PCR. The levels of inflammatory cytokines were tested by enzyme-linked immunosorbent assay (ELISA) kits. Nlrp1a knockdown was performed by an adeno-associated virus (AAV) vector containing Nlrp1a-shRNA-eGFP infusion. RESULTS: Chronic stress stimuli activated hippocampal NLRP1 inflammasome and promoted the release of pro-inflammatory cytokines IL-1ß, IL-18, IL-6, and TNF-α in mice. Hippocampal Nlrp1a knockdown prevented NLRP1 inflammasome-driven inflammatory response and ameliorated stress-induced depressive-like behaviors. Also, chronic stress stimuli caused the increase in hippocampal CXCL1/CXCR2 expression and low BDNF levels in mice. Interestingly, Nlrp1a knockdown inhibited the up-regulation of CXCL1/CXCR2 expression and restored BDNF levels in the hippocampus. CONCLUSIONS: NLRP1 inflammasome-driven inflammatory response contributes to chronic stress induced depressive-like behaviors and the mechanism may be related to CXCL1/CXCR2/BDNF signaling pathway. Thus, NLRP1 inflammasome could become a potential antidepressant target.

Spatiotemporal disequilibrium and spillover effect of fine particulate matter across China.

Massive monitoring data requires effective statistical analysis methods. This paper aims to visualize the spatiotemporal characteristics and spillover effect of air pollutants. Ground-based PM2.5 data in 336 cities across China revealed a tough but improving situation. The PM2.5 average annual concentrations in 2016 and 2017 were 47 ± 18 µg/m3 and 44 ± 16 µg/m3 respectively, but a worse, or at least a not-improving PM2.5 situation happened in winter. A slight declining north-south disequilibrium and a growing east-west disequilibrium exhibited in 2017, along with an increasing weight of eastern and southern pollution in the proportion of the overall pollution level. North-south disequilibrium existed stably throughout the year but east-west disequilibrium was erratic. Nearly half of the cities exhibited significant spillover effects, presenting 2 clusters with spillover by high concentrations and 3 clusters with spillover by low concentrations. Most cities in Hebei, Shandong and Henan provinces showed a high but decreasing spillover effect, but increasing trend happened in the cities in Anhui and Shanxi provinces. A significant correlation appeared between the city population and PM2.5 concentration. Population density explained about 25% of the PM2.5 concentration change, and the explanation ability increased in 2017. A higher influence of population on PM2.5 concentration happened in the early stage of city development, and the influence exhibited spatial differences. The city population and PM2.5 spillover effect existed an overall positive correlation, but the population only addressed about 10% of the spillover effect change. Our findings provide important information for the joint prevention and control of air pollution in China, and the approach proposed in this paper is applicable to other fields.

Optically guided level set for underwater object segmentation.

Combining underwater optical imaging principles and the level set, this paper proposes a novel type of level set method called optically guided level set. This novel method can transform optical challenges in underwater environments (such as the illumination bias and wavelength-selective absorption) into valuable guidance for underwater object segmentation. Using the underwater optical guidance, our novel method can generate accurate object segmentation results by suitable initialization and regular evolving of the level set. The optical guidance core lies in two observations pertaining to the underwater optical imaging process: (i) the overlap between the object region and optical collimation region and (ii) the correspondence between the object structure and irradiation distribution inside the optical collimation. The high accuracy of our proposed method is demonstrated via comparisons to the state-of-the-art level set and salient object detection methods for public underwater images collected in diverse environments. Moreover, by using the work presented in this paper, we plan to demonstrate optical principles' potential for improving computer vision research, which is a promising research topic with many practical applications.

A Micro-Resonant Gas Sensor with Nanometer Clearance between the Pole Plates.

In micro-resonant gas sensors, the capacitive detection is widely used because of its simple structure. However, its shortcoming is a weak signal output caused by a small capacitance change. Here, we reduced the initial clearance between the pole plates to the nanometer level, and increased the capacitance between the pole plates and its change during resonator vibration. We propose a fabricating process of the micro-resonant gas sensor by which the initial clearance between the pole plates is reduced to the nanometer level and a micro-resonant gas sensor with 200 nm initial clearance is fabricated. With this sensor, the resonant frequency shifts were measured when they were exposed to several different vapors, and high detection accuracies were obtained. The detection accuracy with respect to ethanol vapor was 0.4 ppm per Hz shift, and the detection accuracy with respect to hydrogen and ammonias vapors was 3 ppm and 0.5 ppm per Hz shift, respectively.

Spatiotemporal characteristics of PM2.5 and PM10 at urban and corresponding background sites in 23 cities in China.

Air pollution episodes in China are frequent and a more comprehensive understanding of pollution sources and impacts is needed to design appropriate strategies and set emission reduction targets. This study analyzes PM2.5 and PM10 concentrations measured in 23 cities at 178 urban sites and at 23 corresponding "urban contrast" sites in China with the goals of understanding spatial and temporal trends and quantifying the regional component of PM pollution. The contrast sites, located an average of 29km from cities in the upwind direction, are intended to represent "background" levels. Using daily measurements from April 2013 to March 2014, we assess compliance with air quality standards, PM2.5/PM10 ratios and urban "increments," defined as the increase in PM levels in the city compared to the contrast site. Spatial and temporal patterns at daily, monthly and annual levels are shown using distributions, correlations, spatial autocorrelation, and factor analyses. At the contrast sites, PM2.5 and PM10 concentrations averaged 56±26 and 91±44µgm-3, respectively, and China's daily and annual average air quality standards were frequently exceeded. PM2.5 and PM10 concentrations in most cities exceeded levels at the corresponding contrast sites, but by an average of only 14±14 and 26±27µgm-3, respectively. Seasonal changes in PM2.5 and PM10 concentrations and urban increments were striking, e.g., levels increased 2 to 3-fold in winter at several sites. The significance of exurban and regional sources of PM2.5 is demonstrated by the small urban increments, the strong correlations across broad regions, and the correlation between daily levels at city and contrast sites. These sources will require control to achieve air quality goals, in particular, the PM10 and PM2.5 targets announced by the Chinese government in 2013.

Distance effects in electrochemical micromachining.

Considering exponential dependence of currents on double-layer voltage and the feedback effect of the electrolyte resistance, a distance effect in electrochemical micromachining is found, namely that both time constant and double-layer voltage depend on the separation of electrodes. The double-layer voltage is the real voltage used in processing. Under DC voltage, the apparent voltages between two electrodes are constant for different separations, but the real voltages change with the separations. Small separations exert substantial effects on the real voltages. Accordingly, a DC-voltage small-separation electrochemical micromachining technique was proposed. The double-layer voltage drops sharply as the small separation increases. Thus, the electrochemical reactions are confined to electrode regions in very close proximity even under DC voltage. The machining precision can be significantly enhanced by reducing the voltage and separation between electrodes. With this technique, the machining of conducting materials with submicrometre precision was achieved.

Characteristics of PM2.5 Concentrations across Beijing during 2013-2015.

High concentrations of particulate matter (PM2.5) and frequent air pollution episodes in Beijing have attracted widespread attention. This paper utilizes data from the new air pollution network in China to examine the current spatial and temporal variability of PM2.5 at 12 monitoring sites in Beijing over a recent 2-year period (April 2013) to March 2015). The long term (2-year) average concentration was 83 µg·m-3, well above Chinese and international standards. Across the region, annual average concentrations varied by 20 µg·m-3 (25% of the average level), with lower levels in suburban areas compared to periurban and urban areas, which had similar concentrations. The spatial variation in PM2.5 concentrations was associated with several land use and economic variables, including the fraction of vegetated land and building construction activity, which together explained 71% of the spatial variation. Daily air quality was characterized as "polluted" (above 75 µg·m-3) on 36 to 47% of days, depending on site. There were 77 pollution episodes during the study period (defined as two or more consecutive days with Beijing-wide 24-hour average concentrations over 75 µg·m-3), and 2 to 5 episodes occurred each month, including summer months. The longest episode lasted 9 days and daily concentrations exceeded 450 µg·m-3. Daily PM2.5 levels were autocorrelated (rlag1 = 0.516) and associated with many meteorological variables, including barometric pressure, relative humidity, hours of sunshine, surface and ambient temperature, precipitation and scavenging coefficient, and wind direction. Parsimonious models with meteorological and autoregressive terms explained over 60% of the variation in daily PM2.5 levels. The first autoregressive term and hours of sunshine were the most important variables in these models, however, the latter variable is PM2.5-dependent and thus not an explanatory variable. The present study can serve as a baseline to compare the improved air quality in Beijing expected in future years.