Good Environmental Adaptability Research Articles

Nano-fiber based self-powered flexible vibration sensor for rail fasteners tightness safety detection

Rail fasteners are the key components of railway tracks, and regular inspection of them is conducive to the safe operation of railway lines. In order to establish a real-time and efficient rail fasteners tightness safety detection system, a self-powered vibration sensor based on electrospinning nanofibers with high output performance TENG is proposed for daily safety inspection of rail fasteners. The power generation performance of the vibration sensor is characterized with the open-circuit voltage of 185 V, the short-circuit current of 5.68 μA cm−2, and the power density of 4.28 W m−2 under matching load. In addition, it also has excellent working stability, good environmental adaptability and fast response time (40 ms). Therefore, the vibration sensor can not only effectively collect rail vibration energy to achieve energy self-supply, but also accurately identify the tightness of rail fasteners according to the vibration characteristics, so as to ensure the safe operation of railway lines. The manufacturing process of the vibration sensor is convenient, economical and practical, and it is hoped to provide a meaningful detection method for maintaining the safety of railway lines.

Three-Dimensional Path Planning for Unmanned Helicopter Using Memory-Enhanced Dueling Deep Q Network

Unmanned helicopter (UH) is often utilized for raid missions because it can evade radar detection by flying at ultra-low altitudes. Path planning is the key technology to realizing the autonomous action of UH. On the one hand, the dynamically changing radar coverage area and the mountains in the low airspace environment will seriously affect the flight safety of UH. On the other hand, the huge state space of the three-dimensional (3D) environment will also make traditional algorithms difficult to converge. To address the above problems, a memory-enhanced dueling deep Q-network (ME-dueling DQN) algorithm was proposed. First, a comprehensive reward function was designed, which can guide the algorithm to converge quickly and effectively improve the sparse reward problem. Then, we introduced a dual memory pool structure and proposed a memory-enhanced mechanism, which can reduce invalid exploration, further improve the learning efficiency of the algorithm, and make the algorithm more stable. Finally, the path planning ability of the proposed algorithm in multiple experimental environments was verified. Experiments showed that the proposed algorithm has good environmental adaptability and can help UH to accurately identify dangerous areas and plan a safe and reliable flight path.

Image Detection System Based on Smart Sensor Network and Ecological Economy in the Context of Fine Agriculture

In this paper, an in-depth study and analysis of the ecological economy of fine agriculture are carried out using image detection methods of smart sensor networks. The analog signal output from the wireless sensor network is filtered and thresholder to convert into a digital signal to complete the sensor monitoring data preprocessing for digital information analysis. In this paper, with the objectives of good environmental adaptability, low power consumption, low cost, and standardization, the key technologies of wireless sensor networks for fine agriculture are studied, including network structure, networking method, node positioning method, data fusion method, rapid energy self-sufficiency, and energy-saving strategy, and the performance evaluation method of wireless sensor network system, IoT-oriented middleware design method, generic node software and hardware design method, and typical application system. Firstly, a convolutional layer is used instead of a fully connected layer, which makes the network more flexible in terms of input image requirements and enables the calculation of the target rice region. Not only will many complex operations be generated, but it will also limit the generalization ability of the model. Then, by introducing a flexible connection layer based on unit and optimizing the loss function of the network, a crop convolutional neural network (Crop-Net) is finally proposed for training and testing rice images at different growth stages to improve the detection accuracy. In this paper, a network quality of service goal-driven evaluation strategy and evaluation method for agricultural wireless sensor network systems is designed to provide a reference for the establishment of industry standards for wireless sensor network systems for fine agriculture.

Simultaneous removal of high concentrations of ammonia nitrogen and calcium by the novel strain Paracoccus denitrificans AC-3 with good environmental adaptability

The novel Paracoccus denitrificans AC-3 strain was isolated and displayed outstanding purification capability for high concentrations of ammonia nitrogen (NH4+-N) and calcium (Ca2+). Meanwhile, the strain exhibited excellent environmental adaptability within a wide pH range and high levels of NH4+-N and Ca2+. Nitrogen balance analysis demonstrated that the pathways of NH4+-N removal consisted of 80.12% assimilation and 16.60% heterotrophic nitrification aerobic denitrification (HNAD). In addition, Ca2+ was removed by forming calcium carbonate (CaCO3) with carbonate (CO32−) and bicarbonate (HCO3−). CO32−and HCO3− were obtained from carbon dioxide (CO2) hydration, which was catalyzed by carbonic anhydrase (CA) secreted by strain AC-3. The alkaline environment for carbonate precipitation was provided by CA and HNAD. The resulting CaCO3 existed in the form of calcite and exhibited a unique morphology and elemental composition.

Water turbidity detection based on laser scattering‐Raman ratio method

AbstractIn this paper, we introduce a newly developed water turbidity detection system and present a novel turbidity retrieval method based on the laser scattering‐Raman ratio (LSRR). The detection system is based on laser spectroscopy technology, which delivers the laser light into the water sample and collects the scattering light, the Raman light, and the corresponding fluorescence through a Y‐type optical fiber. Experimental measurements on standard formazin solutions were carried out. The linear correlation coefficient between LSRR and the real turbidity values was up to 0.971. We propose two empirical formulas that can be employed to detect water turbidity with a wide range of practical applications. Our water turbidity detection system can be easily integrated into other detection systems due to its compact size, good environmental adaptability, and simple workflow; it shows a great potential for application prospects in the near further.

Slug-inspired Magnetic Soft Millirobot Fully Integrated with Triboelectric Nanogenerator for On‐board Sensing and Self‐powered Charging

Untethered bioinspired soft millirobots have significant advantages in the terms of good environmental adaptability, remote control and high locomotion efficiency, showing potential applications in various biomedical settings. However, to make the bio-inspired soft robot be a highly animal-like machine, more effective bio-functionalities should be integrated into the robot. Herein, inspired by Grey Field Slug, we develop a Slug-inspired magnetic soft millirobot fully integrated with triboelectric nanogenerator (named Slug-inspired TENG-Robot) for on-board sensing and self-powered charging. Under untethered actuation of rotating magnetic field, TENG-Robot generates trains of pedal waves through periodic body fluctuations from the tail to head, producing a forward locomotion on the various terrains (e.g. plane, slope, gap, and tunnel). Synchronously, TENG-Robot harvests the self-transformation induced triboelectricity in closed contact-separation mode during this locomotion. TENG-Robot can self-detect the crawl process and self-power for charging the on-board capacitors via triboelectrification effect during the locomotion. Interestingly, Slug-inspired TENG-Robot integrated with various flexible circuits can light itself like firefly, charge the external electronic devices like electric eel, and response to high temperature stimulus like most animals. We believe the bio-inspired design strategies of TENG-Robot may pave important foundation to understand the principles underlying the behavior of animals and transfer them to the development of ever-more capable robots.

Research on a mmWave Beam-Prediction Algorithm with Situational Awareness Based on Deep Learning for Intelligent Transportation Systems

Simply speaking, automatic driving requires the calculation of a large amount of traffic data and, finally, the obtainment of the optimal driving route and speed. However, the key technical difficulty is the obtainment of data; thus, radar has become an indispensable hardware for automatic driving. Compared to the optical and infrared radar, millimeter-wave radar is not affected by the shape and color of the target, and it is not affected by the atmospheric turbulence, compared to ultrasonic, and so it has a stable detection performance and good environmental adaptability. It is little affected by changes in the weather, and the external environment, rain, snow, dust, and sunshine have no interference in it. The Doppler frequency shift is large, and the accuracy of the relative velocity measurement is improved. However, one challenge for vehicles in fast environments is millimeter-wave-based communication. Because of the short wavelength of the millimeter wave and the high path and penetration losses, the beamforming technology of a large-scale antenna array plays a key role in the construction and maintenance of millimeter-wave communication links. Millimeter waves have wide channel bandwidths, unique channel characteristics, and hardware limitations, and so there are many challenges in the direct use of beamforming technology in millimeter-wave communication. Traditional beam training cannot meet the requirements of low overhead and low delay. This paper, in order to obtain beam information, introduces the context-awareness module to the deep-learning net, which is derived from past observation data. This paper establishes a model that contains the receiver and the surrounding vehicles to perceive the environment. Then, a long short-term memory (LSTM) neural network is used to foresee the acquired power, which is quantized by several beam powers. According to the conclusion, the prediction accuracy is greatly increased, and the model could yield throughput with almost zero overhead and little performance loss.

A target-driven visual navigation method based on intrinsic motivation exploration and space topological cognition

Target-driven visual navigation is essential for many applications in robotics, and it has gained increasing interest in recent years. In this work, inspired by animal cognitive mechanisms, we propose a novel navigation architecture that simultaneously learns exploration policy and encodes environmental structure. First, to learn exploration policy directly from raw visual input, we use deep reinforcement learning as the basic framework and allow agents to create rewards for themselves as learning signals. In our approach, the reward for the current observation is driven by curiosity and calculated by a count-based approach and temporal distance. While agents learn exploration policy, we use temporal distance to find waypoints in observation sequences and incrementally describe the structure of the environment in a way that integrates episodic memory. Finally, space topological cognition is integrated into the model as a path planning module and combined with a locomotion network to obtain a more generalized approach to navigation. We test our approach in the DMlab, a visually rich 3D environment, and validate its exploration efficiency and navigation performance through extensive experiments. The experimental results show that our approach can explore and encode the environment more efficiently and has better capability in dealing with stochastic objects. In navigation tasks, agents can use space topological cognition to effectively reach the target and guide detour behaviour when a path is unavailable, exhibiting good environmental adaptability.

Preparation and Properties of Silicon-Modified Epoxy Grouting Material for Repairing Microcracks

To improve the performance of epoxy grouting materials and achieve better repair of microcracks in cast-in-place concrete bridge deck pavements, polydimethylsiloxane (PDMS) and diluent were used to modify epoxy resin. The mechanical properties of silicon-modified epoxy grouting materials produced using different preparation processes were analyzed, and the best preparation process was optimized. The working performance of silicon-modified epoxy grouting material was determined, and the environmental adaptability before and after composite modification was explored. The results showed that the suitable reaction temperature, time, and PDMS content are 100°C, 3 min, and 8%, respectively. The higher the temperature, the better was the groutability and the shorter was the curing time. Therefore, the construction temperature should be at least 35°C. The impact resistance and strength of the grouting materials were improved significantly after the addition of PDMS. In addition, the strength essentially was formed after 5 days. This indicates that the curing age is 5 days. Silicon-based modified epoxy grouting materials have good environmental adaptability. After thermal shock, 30-day temperature variation treatment, and 30 freeze–thaw cycles, the flexibility and bonding properties of the materials were excellent, and were much higher than those of the unmodified materials. Although the tensile strength was slightly lower than that of the unmodified materials, it still remained at about 60 MPa.

Physically-crosslinked activated CaCO3/polyaniline-polypyrrole-modified GO/alginate hydrogel sorbent with highly efficient removal of copper(II) from aqueous solution

• A 3D activated CaCO 3 /PAN-PPy-modified GO/alginate hydrogel sorbent was fabricated. • Synergism among components help to gel network formation and pollutants removal. • CaCO 3 as pore-former, pH buffer and activated additive was help to Cu(II) removal. • High sorption capacity and fast kinetics for the alginate-based hydrogel sorbent. • The gel can be easily separated and show good environment adaptability and stability. Herein, alginate-based porous nanocomposite hydrogel (CPGA) was produced using alginate as entrapment agent, polyaniline-polypyrrole-modified graphene oxide (GPP) as functional filler, and CaCO 3 as pore-former for enhanced Cu(II) removal from water. Synergism among tri-components help to 3D network formation and Cu(II) removal. The parameters of components, solution pH, contact time, adsorbate concentration, temperature, coexisting substances and dosage were investigated in batch sorption mode. Spontaneous and endothermal adsorption process of Cu(II) by CPGA followed pseudo-second-order model and Freundlich model with experimental maximum adsorption capacity of ∼ 291.2 mg/g, which was better than most of reported alginate-based sorbents. CPGA showed good anti-interference ability in the presence of NaCl and humic acid as well as in actual Cu(II)-polluted lake water. In the multi-ions system, little sorption loss was observed for Pb(II), Cu(II) and Cd(II) capture, and even strengthened Cr(VI) removal relative to those in the single system. Furtherly, minor discrepancy (<10%) was noted after eight successive adsorption-desorption cycles. FTIR and XPS revealed that reactive N-/O-containing groups was mainly responsible for Cu(II) removal; the residual CaCO 3 acted the role of pH-buffer and provided refresh binding sites for the gel. This work could expand the potential applicability of alginate-based sorbents for heavy metal removal from water.

The Role of Indigenous Mycorrhizae of Corn Plants in Various Soil Types in Gunung Kidul, Indonesia

Indigenous Vesicular-Arbuscular Mycorrhizae (VAM) are natural mycorrhizae from specific areas that have good environmental adaptability. This study, conducted from January to November 2020 at the Faculty of Agriculture, Universitas Gadjah Mada, aimed to isolate the vesicular-arbuscular mycorrhizal fungus so that it can be used as information on the type and role of VAM on Gunung Kidul soil. The research was arranged in a Completely Randomized Design (CRD) with three factors. The first factor was soil type from Gunung Kidul Regency (Inceptisol, Mollisol, and Alfisol), the second factor was sterilization (sterilized soil and unsterilized soil), and the third factor was corn variety (local and hybrid). Analysis of soil and plant growth was performed by using Analysis of Variance (ANOVA) and Tukey's Honestly Significant Difference (Tukey's HSD) Test. Genetic detection of root infecting VAM was performed by using Terminal Restriction Fragment Length Polymorphism (T-RFLP) method with FAM AML1-AML2 labeled primers. The VAM detected in the roots of hybrid variety included Acaulospora sp., Gigaspora sp., and Septoglomus sp., and those in the roots of local variety were Acaulospora sp., Gigaspora sp., and Funelisformis sp. The results showed that the role of VAM could be seen through unsterilized soil so that there was no VAM elimination in the soil. Unsterilized soil showed the best results of root infection, leaf fresh and dry weight, leaf phosphor (P) content, and leaf P uptake. Meanwhile, Alfisol showed the best result of root infection, fresh weight, dry weight, leaf P content, and leaf P uptake. The treatment of plant varieties showed that the varieties did not significantly affect the root infection, fresh weight, dry weight, leaf P content, and leaf P uptake.

Development and Performance Analysis of Pneumatic Soft‐Bodied Bionic Flipper

The sea lion fore flipper has superior underwater movement performance. Its structural characteristics and propulsion mechanism are drawn, combined with the large deformation and hyperelastic properties of silicone, a pneumatic soft‐bodied bionic flipper with strong underwater mobility, good environmental adaptability, and flexible attitude transformation. Based on Yeoh's second‐order constitutive model of silicone, the nonlinear dynamic analysis of the main limb of the bionic flipper is carried out, and the deformation analysis theoretical model is established. Then, the force analysis of infinitesimal and integral of the wing fin of the bionic flipper is analyzed by the blade element theory, to obtain the theoretical model of underwater propulsion dynamic performance. The superiority of the hydrodynamic performance of the bionic flipper is analyzed and confirmed using the bidirectional fluid–structure coupling numerical simulation algorithm. An experimental test platform is built to test the physical model of the bionic flipper. The motion and dynamic characteristics curves of the bionic flipper are obtained and compared with the corresponding numerical simulation results. The results show that the theoretical model and numerical simulation are accurate, and the structure is feasible, which can provide methods and references for the research and implementation of the underwater propeller.

Germanium carbon (Ge1-xCx)/diamond-like carbon (DLC) antireflective and protective coating on zinc sulfide window

The Ge1-xCx/DLC antireflective and protective coating was designed and deposited on the ZnS substrate to improve the long-wave infrared transmittance, the hardness and the environmental adaptability of the ZnS window. The Ge1-xCx film and DLC film were deposited by ion beam sputtering and chemical vapor deposition, respectively. The surface morphology, chemical bonds and hardness of the films were investigated. The optical constants of the films were determined from whole infrared optical spectrum. After depositing hard protective coating and antireflective coating on ZnS substrate, the transmittance of the ZnS is greatly improve in the range of 7.5μm–9.7 μm, and the average value of transmittance is 90%. The hardness of the protective coating is 16 GPa, which is much higher than that of the ZnS substrate. The hard protective coating also shows good environmental adaptability. These results suggest that the coating has the potential to be used as an antireflective and protective coating in long-wave infrared region of 7.5μm–9.7 μm.

Ceramic‐based dielectric metamaterials

AbstractDielectric metamaterials based on ceramics have attracted considerable interest in the past few years owing to their low dielectric loss, simple structure, excellent multifield tunability, and good environmental adaptability. They are considered to be promising alternative to metal‐based metamaterials and can lead to a new strategy for the development of passive devices. In this review, the recent progress of ceramic‐based dielectric metamaterials in electromagnetic applications, energy applications, non‐Hermitian systems, and natural materials with near‐zero or negative refraction are summarized. The design principle and mechanism, as well as manufacturing technologies, are also introduced, and the current development trend of ceramic‐based dielectric metamaterials are proposed.

Effect of copy number variation of PLA2G2A gene to growth traits in Chinese cattle.

As a member of genetic polymorphism, copy number variation has been a commonly used method in the world for investigating effect of genetic polymorphism on gene expression. Effect of genetic polymorphism made on livestock development has been more and more important in beef cattle molecular breeding. The characteristics of Chinese cattle are excellent meat quality, tolerant to rough feeding, good environmental adaptability and so on. But there are some obvious weaknesses still exist in the process of cattle growth and development, such as weak hindquarters and growth slowly. To improve the growth performance and market competitiveness of Chinese cattle, a lot of studies have been made about finding and investigating effective molecular marker. In this study, Q-PCR and data association analysis were used for PLA2G2A gene copy number variation detection and related effect analysis in Chinese cattle. Results showed that PLA2G2A gene has a significant effect on two breeds of Chinese cattle on growth traits, which could be a basic materials and effective information of cattle molecular markers breeding. PLA2G2A, member of secreted phospholipases A2 (sPLA2) in superfamily of phospholipase A2, could catalyze the process of glycerophospholipids hydrolysis from position of sn-2 acyl with the release of free fatty acids and lysophospholipids. Researches about PLA2G2A gene are mostly focus on disease, including tumors and diabetes, the number of study occurred on animal breeding is weak. In this study, blood samples were collected from five breeds of Chinese cattle (Qingchuan cattle, Xianan cattle, Yunling cattle, Pinan cattle and Guyuan cattle) for PLA2G2A gene CNV type detection. SPSS 20.0 software and method of ANOVA were used to analyzed the association between types of CNV and growth traits. Results reveal that the distribution of different copy number types in different cattle breeds is different. In QC, XN and GY cattle, the frequencies of Deletion and Duplication are about 40%; in YL cattle, the frequency of Deletion type exceeds 60%; in PN cattle, the frequency of Duplication is closed to 80%. Association analysis indicate that CNV of PLA2G2A gene showed a positive effect in cattle growth: in QC cattle, Chest depth with Normal type copy number possess a increased trend (P<0.05); individuals with Deletion type copy number have better performance on Height at sacrum, Heart girth and Body height in GY cattle (P<0.05). The functional role and molecular mechanism of PLA2G2A gene in animal growth and development are still unclear, and it is necessary for processing a further research. This research aims to provide basic materials for molecular breeding of Chinese cattle.

Linking environmental signals to plant metabolism: The combination of field trials and environment simulators

Breeding crops with enhanced nutrients is one of the major goals of plant breeding. Notably, plants intensively produce various specialized plant metabolites (e.g., phenolic compounds and carotenoids) in response to diverse external stimuli and changing environmental conditions, which have been reported as health-promoting compounds with various health benefits (Dong and Lin, 2021). On the other hand, the varied growth environment and global climate change necessitates crops to have the qualities of good environmental adaptability (Eshed and Lippman, 2019).

Radiation tolerance analysis of 4H-SiC PIN diode detectors for neutron irradiation

Silicon carbide (SiC) detector shows sufficient merits for the application of radiation measurement in harsh neutron radiation fields due to the strong radiation tolerance, good environment adaptability, and excellent electrical properties. In order to meet the demand for higher precision measurements, the reliability of SiC detectors under harsh neutron irradiation environments must be characterized. In this work, electrical characteristics, α-particle response, and pulse response speed of 4H-SiC PIN diode detectors were carefully investigated under 1 MeV equivalent neutron irradiation fluence from 5 × 1012 cm−2 to 1 × 1014 cm−2. Before neutron irradiation, SiC detector showed dark current as low as 10 pA at 200 V bias, with superior charge collection efficiency of more than 98%, perfect energy resolution within 0.9%, and ultrafast response speed with a rise time and decay time of 2.1 ns and 5.9 ns, respectively. After a neutron irradiation at fluence of 1 × 1014 cm−2, noticeable changes were found in the forward IV characteristics of SiC detector, but the dark current was stable below 1 nA, with only 5.7% and 0.26% degradation in charge collection efficiency and energy resolution respectively, and the pulse response speed remained unchanged. These results demonstrate 4H-SiC PIN diode detector has superior neutron radiation tolerance, and the obtained evolution characteristics are very valuable for improving the measuring accuracy of SiC detectors in the intense neutron field.

Development of oxidized hydroxyethyl cellulose-based hydrogel enabling unique mechanical, transparent and photochromic properties for contact lenses

With the development of smart devices, higher requirements are put forward for the stimuli-responsive materials. Stimuli-hydrogels as one kind of stimuli-responsive materials with hydrophilicity, demonstrate huge potential in developing intelligent devices for biomedical application. On this basis, we herein report that a sample method was devised to develop a novel composite hydrogel mainly based on oxidized hydroxyethyl cellulose and allyl co-polymer. Subsequently, a series of tests toward this oxidized hydroxyethyl cellulose-based hydrogel due to its structure and performance was applied. Here, the oxidized hydroxyethyl cellulose molecular chains were used as biomacromolecule templates to form Schiff base, borate and hydrogen bonds to obtain unique mechanical properties (fast recovery with almost no-hysteresis and remarkable compressive capacity), while a double bond functionalized spirooxazine (allyl spirooxazine derivative) was applied to endow photo- and pH sensitivity to the oxidized hydroxyethyl cellulose-based transparent hydrogel (T% = 93%) substrate. Furthermore, the oxidized hydroxyethyl cellulose-based hydrogel did exhibit good pH environment adaptability and noncytotoxicity in vitro test. Based on the advanced characteristics, the designed oxidized hydroxyethyl cellulose-based hydrogel has potential applications prospect in the development of safe, fashionable and pH- detectable contact lenses, thereby providing a new strategy for the development of smart, stylish contact lenses.

Forecasting rice latitude adaptation through a daylength-sensing-based environment adaptation simulator.

Global climate change necessitates crop varieties with good environmental adaptability. As a proxy for climate adaptation, crop breeders could select for adaptability to different latitudes, but the lengthy procedures for that slow development. Here, we combined molecular technologies with a streamlined in-house screening method to facilitate rapid selection for latitude adaptation. We established the daylength-sensing-based environment adaptation simulator (DEAS) to assess rice latitude adaptation status via the transcriptional dynamics of florigen genes at different latitudes. The DEAS predicted the florigen expression profiles in rice varieties with high accuracy. Furthermore, the DEAS showed potential for application in different crops. Incorporating the DEAS into conventional breeding programmes would help to develop cultivars for climate adaptation.

Numerical Analysis and Experimental Investigation on a Novel Piezoelectric-Actuated Rail-Type Mobile Platform

A novel piezoelectric-actuated rail-type mobile platform is proposed in this article, which has potential application in the inspection and maintenance tasks of the Tokamak vacuum vessel as it holds good environmental adaptability to extreme environments, such as strong magnetic fields, high vacuum, and high temperature. The rail-type piezoelectric-actuated mobile platform consists of a rail and a framed piezoelectric actuator operating with two orthogonal bending vibrations. The framed piezoelectric actuator moves on the rail by friction. At first, a semianalytical model is created for the framed piezoelectric actuator utilizing the transfer matrix method in order to reveal its dynamic behavior. Then, the prototype of the proposed framed piezoelectric actuator is manufactured and assembled, and its vibration characteristics are measured to verify the feasibility of the developed transfer matrix model. Additionally, the mechanical output performances of the rail-type mobile platform prototype are investigated experimentally, and it is observed that the maximum speed of the mobile platform prototype reached 384.68 mm/s when the amplitude of the driving voltage is 400 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pp</sub> , its maximum load-weight to self-weight ratio reached 7.6 when the excitation voltage is 300 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pp</sub> , its maximum output force is about 1.8 N under the excitation voltage of 400 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pp</sub> , and the minimum displacement resolution is 4 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m when operated in the stepping mode. Finally, the extreme environment (temperature: 0–120 °C and vacuum: 3×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> –10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup> Pa) tests are carried out to measure the output performances of the mobile platform prototype. The results show that the platform prototype is capable of carrying loads in a high-temperature and high-vacuum environment.