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The article presents a novel control strategy for cable-driven aerial manipulators (UAMs) aimed at enhancing impedance control during contact operations in complex environments. A fractional-order nonsingular terminal sliding mode control (FONTSMC) integrated with a disturbance observer (DOB) is proposed to improve the robustness and precision of the UAM under lumped disturbances. This developed approach utilizes the flexibility of fractional calculus, the finite-time stability of nonsingular terminal sliding mode, and the real-time disturbance estimation capabilities of the DOB to ensure smooth and compliant contact interactions. The effectiveness of the proposed control strategy is validated through comprehensive simulation studies, which demonstrate significant improvements in control performance, stability, and disturbance rejection when compared to traditional methods. The results indicate that the FONTSMC-DOB framework is highly suitable for complex aerial manipulation tasks, offering both theoretical and practical insights into the design of advanced control systems for UAMs.

Mechanical joint interfaces are widely found in mechanical equipment, and their contact stiffness directly affects the overall performance of the mechanical system. Based on the fractal and elastoplastic contact mechanics theories, the K-E elastoplastic contact model is introduced to establish the contact stiffness model for mechanical joint interfaces. This model considers the interaction effects between micro-asperities in the fully deformed state, including elasticity, first elastoplasticity, second elastoplasticity, and complete plastic deformation state. Based on this model, the effects of fractal parameters on normal contact stiffness and contact load are analyzed. It can be found that the larger fractal dimension D or smaller characteristic scale coefficient G will weaken the interaction between micro-asperities. The smoother processing surfaces lead to higher contact stiffness in mechanical joint interfaces. The applicability and effectiveness of the proposed model are verified by comparing it with the traditional contact model calculation results. Under the same load, the interaction between micro-rough surfaces leads to an increase in both overall deformation and contact stiffness. The accuracy of the predicted contact stiffness model is also validated by comparing it with experimental results.

Sodium-ion batteries (SIBs) have emerged as a promising alternative to lithium-ion batteries (LIBs) due to the abundance and low cost of sodium resources. Cathode material plays a crucial role in the performance of sodium ion batteries determining the capacity, cycling stability, and rate capability. Na3V2(PO4)3 (NVP) is a promising cathode material due to its stable three-dimensional NASICON structure, but its discharge capacity is low and its decay is serious with the increase of cycle period. We focused on modifying NVP cathode material by coating carbon and doping Nb5+ ions for synergistic electrochemical properties of carbon-coated NVP@C as a cathode material. X-ray diffraction analysis was performed to confirm the phase purity and crystal structure of the Nb5+ doped NVP material, which exhibited characteristic diffraction peaks that matched well with the NASICON structure. Nb5+-doped NVP@C@Nbx materials were prepared using the sol–gel method and characterized by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Raman and Brunauer -Emmett-Teller (BET) analysis. First-principles calculations were performed based on density functional theory. VASP and PAW methods were chosen for these calculations. GGA in the PBE framework served as the exchange-correlation functional. The results showed the NVP unit cell consisted of six NVP structural motifs, each containing octahedral VO6 and tetrahedral PO4 groups to form a polyanionomer [V2(PO4)3] along with the c-axis direction by PO4 groups, which had Na1(6b) and Na2(18e) sites. And PDOS revealed that after Nb doping, the d orbitals of the Nb atoms also contributed electrons that were concentrated near the Fermi surface. Additionally, the decrease in the effective mass after Nb doping indicated that the electrons could move more freely through the material, implying an enhancement of the electron mobility. The electrochemical properties of the Nb5+ doped NVP@C@Nb cathode material were evaluated through cyclic voltammetry (CV), galvanostatic charge-discharge tests, electrochemical impedance spectroscopy (EIS), and X-ray photoelectric spectroscopy (XPS). The results showed that NVP@C@Nb0.15 achieved an initial discharge capacity as high as 114.27 mAhg−1, with a discharge capacity of 106.38 mAhg−1 maintained after 500 cycles at 0.5C, and the retention rate of the NVP@C@Nb0.15 composite reached an impressive 90.22%. NVP@C@Nb0.15 exhibited low resistance and high capacity, enabling it to create more vacancies and modulate crystal structure, ultimately enhancing the electrochemical properties of NVP. The outstanding performance can be attributed to the Nb5+-doped carbon layer, which not only improves electronic conductivity but also shortens the diffusion length of Na+ ions and electrons, as well as reduces volume changes in electrode materials. These preliminary results suggested that the as-obtained NVP@C@Nb0.15 composite was a promising novel cathode electrode material for efficient sodium energy storage.

Piezoelectric material-based devices have garnered considerable attention from scientists and engineers due to their unique physical characteristics, resulting in numerous intriguing and practical applications. Among these, flexural-mode piezoelectric resonators (FMPRs) are progressively gaining prominence due to their compact, precise, and efficient performance in diverse applications. FMPRs, resonators that utilize one- or two-dimensional piezoelectric materials as their resonant structure, vibrate in a flexural mode. The resonant properties of the resonator directly influence its performance, making in-depth research into the resonant characteristics of FMPRs practically significant for optimizing their design and enhancing their performance. With the swift advancement of micro-nano electronic technology, the application range of FMPRs continues to broaden. These resonators, representing a domain of piezoelectric material application in micro-nanoelectromechanical systems, have found extensive use in the field of physical sensing and are starting to be used in micropower systems and biomedicine. This paper reviews the structure, working principle, resonance characteristics, applications, and future prospects of FMPRs.

This study employs the reflection symmetry decomposition (RSD) method to extract polarization scattering features from ground object images, aiming to determine the optimal data input scheme for deep learning networks in polarimetric synthetic aperture radar classification. Eight distinct polarizing feature combinations were designed, and the classification accuracy of various approaches was evaluated using the classic convolutional neural networks (CNNs) AlexNet and VGG16. The findings reveal that the commonly employed six-parameter input scheme, favored by many researchers, lacks the comprehensive utilization of polarization information and warrants attention. Intriguingly, leveraging the complete nine-parameter input scheme based on the polarization coherence matrix results in improved classification accuracy. Furthermore, the input scheme incorporating all 21 parameters from the RSD and polarization coherence matrix notably enhances overall accuracy and the Kappa coefficient compared to the other seven schemes. This comprehensive approach maximizes the utilization of polarization scattering information from ground objects, emerging as the most effective CNN input data scheme in this study. Additionally, the classification performance using the second and third component total power values (P2 and P3) from the RSD surpasses the approach utilizing surface scattering power value (PS) and secondary scattering power value (PD) from the same decomposition.

Sensing and cognition by homeowners and technicians for home maintenance are prime examples of human–building interaction. Damage, decay, and pest infestation present signals that humans interpret and then act upon to remedy and mitigate. The maintenance cognition process has direct effects on sustainability and economic vitality, as well as the health and well-being of building occupants. While home maintenance practices date back to antiquity, they readily submit to augmentation and improvement with modern technologies. This paper describes the use of networked smart technologies embedded with machine learning (ML) and presented in electronic formats to better inform homeowners and occupants about safety and maintenance issues, as well as recommend courses of remedial action. The demonstrated technologies include robotic sensing in confined areas, LiDAR scans of structural shape and deformation, moisture and gas sensing, water leak detection, network embedded ML, and augmented reality interfaces with multi-user teaming capabilities. The sensor information passes through a private local dynamic network to processors with neural network pattern recognition capabilities to abstract the information, which then feeds to humans through augmented reality and conventional smart device interfaces. This networked sensor system serves as a testbed and demonstrator for home maintenance technologies, for what can be termed Home Maintenance 4.0.

Low-alloy wear-resistant steel often requires the addition of trace alloy elements to enhance its performance while also considering the cost-effectiveness of production. In order to comparatively analyze the strengthening mechanisms of Mo and Cr elements and further explore economically feasible production processes, we designed two types of low-alloy wear-resistant steels, based on C-Mn series wear-resistant steels, with individually added Mo and Cr elements, comparing and investigating the roles of the alloying elements Mo and Cr in low-alloy wear-resistant steels. Utilizing JMatPro software to calculate Continuous Cooling Transformation (CCT) curves, conducting thermal simulation quenching experiments using a Gleeble-3800 thermal simulator, and employing equipment such as a metallographic microscope, transmission electron microscope, and tensile testing machine, this study comparatively investigated the influence of Mo and Cr on the microstructural transformation and mechanical properties of low-alloy wear-resistant steels under different cooling rates. The results indicate that the addition of the Mo element in low-alloy wear-resistant steel can effectively suppress the transformation of ferrite and pearlite, reduce the martensitic transformation temperature, and lower the critical cooling rate for complete martensitic transformation, thereby promoting martensitic transformation. Adding Cr elements can reduce the austenite transformation zone, decrease the rate of austenite formation, and promote the occurrence of low-temperature phase transformation. Additionally, Mo has a better effect on improving the toughness of low-temperature impact, and Cr has a more significant improvement in strength and hardness. The critical cooling rates of C-Mn-Mo steel and C-Mn-Cr steel for complete martensitic transition are 13 °C/s and 24 °C/s, respectively. With the increase in the cooling rate, the martensitic tissues of the two experimental steels gradually refined, and the characteristics of the slats gradually appeared. In comparison, the C-Mn-Mo steel displays a higher dislocation density, accompanied by dislocation entanglement phenomena, and contains a small amount of residual austenite, while granular ε-carbides are clearly precipitated in the C-Mn-Cr steel. The C-Mn-Mo steel achieves its best performance at a cooling rate of 25 °C/s, whereas the C-Mn-Cr steel only needs to increase the cooling rate to 35 °C/s to attain a similar comprehensive performance to the C-Mn-Mo steel.

The two existing clades of Galloanseres, orders Galliformes (landfowl) and Anseriformes (waterfowl), exhibit dramatically different evolutionary trends. Mitochondria serve as primary sites for energy production in organisms, and numerous studies have revealed their role in biological evolution and ecological adaptation. We assembled the complete mitogenome sequences of two species of the genus Aythya within Anseriformes: Aythya baeri and Aythya marila. A phylogenetic tree was constructed for 142 species within Galloanseres, and their divergence times were inferred. The divergence between Galliformes and Anseriformes occurred ~79.62 million years ago (Mya), followed by rapid evolution and diversification after the Middle Miocene (~13.82 Mya). The analysis of selective pressure indicated that the mitochondrial protein-coding genes (PCGs) of Galloanseres species have predominantly undergone purifying selection. The free-ratio model revealed that the evolutionary rates of COX1 and COX3 were lower than those of the other PCGs, whereas ND2 and ND6 had faster evolutionary rates. The CmC model also indicated that most PCGs in Anseriformes exhibited stronger selective constraints. Our study suggests that the distinct evolutionary trends and energy requirements of Galliformes and Anseriformes drive different evolutionary patterns in the mitogenome.

Microrobots are effective for monitoring infrastructure in narrow spaces. However, they have limited computing power, and most of them are not wireless and stable enough for accessing infrastructure in difficult-to-reach areas. In this paper, we describe the fabrication of a microrobot with bristle-bot locomotion using a novel centrifugal yaw-steering control scheme. The microrobot operates in a network consisting of an augmented reality headset and an access point to monitor infrastructures using augmented reality (AR) haptic controllers for human–robot collaboration. For the development of the microrobot, the dynamics of bristle-bots in several conditions were studied, and multiple additive manufacturing processes were investigated to develop the most suitable prototype for structural health monitoring. Using the proposed network, visual data are sent in real time to a hub connected to an AR headset upon request, which can be utilized by the operator to monitor and make decisions in the field. This allows the operators wearing an AR headset to inspect the exterior of a structure with their eyes, while controlling the surveying robot to monitor the interior side of the structure.

Fugitive dust (FD) is a nuisance and potential health issue, particularly in environmental justice communities that can experience high levels of contaminated FD. This community-initiated study examined FD from a scrap metal processor in Detroit, Michigan, to determine whether the FD was contaminated, how it migrated through the community, whether wipe or composite road dust samples were preferable, and whether literature profiles adequately characterized this source. The study was motivated by community concerns, as well as a massive subsidence/upheaval event resulting from excessive accumulation of mill scale, which is a type of scrap metal, at the facility. We collected 57 wipe samples from windows and other surfaces, and 20 composite road dust and surface soil samples, which were analyzed by X-ray fluorescence. Concentrations were expressed using the fraction of the reconstructed mass. We also compared results to air quality monitoring data and calculated pollution indices and enrichment factors. Samples collected near the processor had high levels of Cr, Cu, Fe, Ni, Sr, and Zn compared with background soils, and levels remained elevated in residential areas several blocks distant. Composite road dust/sediment samples appeared preferable to wipe samples for chemical characterization. The available chemical profiles did not match the FD composition, suggesting the need for local profiles. The high level of Fe, which is consistent with mill scale, was a novel finding and caused the road dust to exceed health protection screening levels. Numerous metal scrap facilities operate locally and nationally, and our results show the need to improve controls to limit or eliminate FD emissions from industrial sources using enforced policies that reduce dust generation and truck track-out.

Liver-targeting nanoparticles have emerged as a promising platform for the induction of immune tolerance by taking advantage of the liver’s unique tolerogenic properties and nanoparticles’ physicochemical flexibility. Such an approach provides a versatile solution to the treatment of a diversity of immunologic diseases. In this review, we begin by assessing the design parameters integral to cell-specific targeting and the tolerogenic induction of nanoplatforms engineered to target the four critical immunogenic hepatic cells, including liver sinusoidal epithelial cells (LSECs), Kupffer cells (KCs), hepatic stellate cells (HSCs), and hepatocytes. We also include an overview of multiple therapeutic strategies in which nanoparticles are being studied to treat many allergies and autoimmune disorders. Finally, we explore the challenges of using nanoparticles in this field while highlighting future avenues to expand the therapeutic utility of liver-targeting nanoparticles in autoimmune processes.

Short message services (SMS), microblogging tools, instant message apps, and commercial websites produce numerous short text messages every day. These short text messages are usually guaranteed to reach mass audience with low cost. Spammers take advantage of short texts by sending bulk malicious or unwanted messages. Short texts are difficult to classify because of their shortness, sparsity, rapidness, and informal writing. The effectiveness of the hidden Markov model (HMM) for short text classification has been illustrated in our previous study. However, the HMM has limited capability to handle new words, which are mostly generated by informal writing. In this paper, a hybrid model is proposed to address the informal writing issue by weighting new words for fast short text filtering with high accuracy. The hybrid model consists of an artificial neural network (ANN) and an HMM, which are used for new word weighting and spam filtering, respectively. The weight of a new word is calculated based on the weights of its neighbor, along with the spam and ham (i.e., not spam) probabilities of short text message predicted by the ANN. Performance evaluations on benchmark datasets, including the SMS message data maintained by University of California, Irvine; the movie reviews, and the customer reviews are conducted. The hybrid model operates at a significantly higher speed than deep learning models. The experiment results show that the proposed hybrid model outperforms other prominent machine learning algorithms, achieving a good balance between filtering throughput and accuracy.

Sonar images have the characteristics of lower resolution and blurrier edges compared to optical images, which make the feature-matching method in underwater target tracking less robust. To solve this problem, we propose a particle filter (PF)-based underwater target-tracking method utilizing Zernike moment feature matching. Zernike moments are used to construct the feature-description vector for feature matching and contribute to the update of particle weights. In addition, the particle state transition method is optimized by using a first-order autoregressive model. In this paper, we compare Hu moments and Zernike moments, and we also compare whether to optimize the particle state transition on the tracking results or not based on the effects of each option. The experimental results based on the AUV (autonomous underwater vehicle) prove that the robustness and accuracy of this innovative method is better than the other combined methods mentioned in this paper.

Municipal solid waste landfills are major contributors to anthropogenic emissions of methane (CH4), which is the major component of natural gas, a potent greenhouse gas, and a precursor for the formation of tropospheric ozone. The development of sensitive, selective, and fast-response instrumentation allows the deployment of mobile measurement platforms for CH4 measurements at landfills. The objectives of this study are to use mobile monitoring to measure ambient levels of CH4 at eight large operating landfills in southeast Michigan, USA; to characterize diurnal, daily and spatial variation in CH4 levels; and to demonstrate the influence of meteorological factors. Elevated CH4 levels were typically found along the downwind side or corner of the landfill. Levels peaked in the morning, reaching 38 ppm, and dropped to near-baseline levels during midday. Repeat visits showed that concentrations were highly variable. Some variation was attributable to the landfill size, but both mechanistically-based dilution-type models and multivariate models identified that wind speed, boundary layer height, barometric pressure changes, and landfill temperature were key determinants of CH4 levels. Collectively, these four factors explained most (r2 = 0.89) of the variation in the maximum CH4 levels at the landfill visited most frequently. The study demonstrates the ability to assess spatial and temporal variation in CH4 levels at landfills using mobile monitoring along perimeter roads. Such monitoring can identify the location of leaks and the best locations for long-term emission monitoring using fixed site monitors.

Human activity recognition (HAR) is an important research area with a wide range of application scenarios, such as smart homes, healthcare, abnormal behavior detection, etc. Wearable sensors, computer vision, radar, and other technologies are commonly used to detect human activity. However, they are severely limited by issues such as cost, lighting, context, and privacy. Therefore, this paper explores a high-performance method of using channel state information (CSI) to identify human activities, which is a deep learning-based spatial module-temporal convolutional network (SM-TCNNET) model. The model consists of a spatial feature extraction module and a temporal convolutional network (TCN) that can extract the spatiotemporal features in CSI signals well. In this paper, extensive experiments are conducted on the self-picked dataset and the public dataset (StanWiFi), and the results show that the accuracy reaches 99.93% and 99.80%, respectively. Compared with the existing methods, the recognition accuracy of the SM-TCNNET model proposed in this paper is improved by 1.8%.

The Corsac fox (Vulpes corsac) is a species of fox distributed in the arid prairie regions of Central and Northern Asia, with distinct adaptations to dry environments. Here, we applied Oxford-Nanopore sequencing and a chromosome structure capture technique to assemble the first Corsac fox genome, which was then assembled into chromosome fragments. The genome assembly has a total length of 2.2 Gb with a contig N50 of 41.62 Mb and a scaffold N50 of 132.2 Mb over 18 pseudo-chromosomal scaffolds. The genome contained approximately 32.67% of repeat sequences. A total of 20,511 protein-coding genes were predicted, of which 88.9% were functionally annotated. Phylogenetic analyses indicated a close relation to the Red fox (Vulpes vulpes) with an estimated divergence time of ~3.7 million years ago (MYA). We performed separate enrichment analyses of species-unique genes, the expanded and contracted gene families, and positively selected genes. The results suggest an enrichment of pathways related to protein synthesis and response and an evolutionary mechanism by which cells respond to protein denaturation in response to heat stress. The enrichment of pathways related to lipid and glucose metabolism, potentially preventing stress from dehydration, and positive selection of genes related to vision, as well as stress responses in harsh environments, may reveal adaptive evolutionary mechanisms in the Corsac fox under harsh drought conditions. Additional detection of positive selection for genes associated with gustatory receptors may reveal a unique desert diet strategy for the species. This high-quality genome provides a valuable resource for studying mammalian drought adaptation and evolution in the genus Vulpes.

Although titanium and titanium alloys have become the preferred materials for various medical implants, surface modification technology still needs to be strengthened in order to adapt to the complex physiological environment of the human body. Compared with physical or chemical modification methods, biochemical modification, such as the introduction of functional hydrogel coating on implants, can fix biomolecules such as proteins, peptides, growth factors, polysaccharides, or nucleotides on the surface of the implants, so that they can directly participate in biological processes; regulate cell adhesion, proliferation, migration, and differentiation; and improve the biological activity on the surface of the implants. This review begins with a look at common substrate materials for hydrogel coatings on implant surfaces, including natural polymers such as collagen, gelatin, chitosan, and alginate, and synthetic materials such as polyvinyl alcohol, polyacrylamide, polyethylene glycol, and polyacrylic acid. Then, the common construction methods of hydrogel coating (electrochemical method, sol–gel method and layer-by-layer self-assembly method) are introduced. Finally, five aspects of the enhancement effect of hydrogel coating on the surface bioactivity of titanium and titanium alloy implants are described: osseointegration, angiogenesis, macrophage polarization, antibacterial effects, and drug delivery. In this paper, we also summarize the latest research progress and point out the future research direction. After searching, no previous relevant literature reporting this information was found.

Canocapavir is a novel antiviral agent with characteristics of core protein allosteric modulators (CpAMs) that is currently in a phase II clinical trial for treatment of hepatitis B virus (HBV) infection. Herein, we show that Canocapavir prevented the encapsidation of HBV pregenomic RNA and increased the accumulation of cytoplasmic empty capsids, presumably by targeting the hydrophobic pocket at the dimer-dimer interface of HBV core protein (HBc). Canocapavir treatment markedly reduced the egress of naked capsids, which could be reversed by Alix overexpression through a mechanism other than direct association of Alix with HBc. Moreover, Canocapavir interfered with the interaction between HBc and HBV large surface protein, resulting in diminished production of empty virions. Of particular note, Canocapavir induced a conformational change of capsids, with the C-terminus of HBc linker region fully exposed on the exterior of capsids. We posit that the allosteric effect may have great importance in the anti-HBV activity of Canocapavir, given the emerging virological significance of HBc linker region. In support of this notion, the mutation at HBc V124W typically recapitulated the conformational change of the empty capsid with aberrant cytoplasmic accumulation. Collectively, our results indicate Canocapavir as a mechanistically distinct type of CpAMs against HBV infection.

Scientists have been attempting to improve the properties of mesoporous materials and expand their application since the 1990s, and the combination with hydrogels, macromolecular biological materials, is one of the research focuses currently. Uniform mesoporous structure, high specific surface area, good biocompatibility, and biodegradability make the combined use of mesoporous materials more suitable for the sustained release of loaded drugs than single hydrogels. As a joint result, they can achieve tumor targeting, tumor environment stimulation responsiveness, and multiple therapeutic platforms such as photothermal therapy and photodynamic therapy. Due to the photothermal conversion ability, mesoporous materials can significantly improve the antibacterial ability of hydrogels and offer a novel photocatalytic antibacterial mode. In bone repair systems, mesoporous materials remarkably strengthen the mineralization and mechanical properties of hydrogels, aside from being used as drug carriers to load and release various bioactivators to promote osteogenesis. In hemostasis, mesoporous materials greatly elevate the water absorption rate of hydrogels, enhance the mechanical strength of the blood clot, and dramatically shorten the bleeding time. As for wound healing and tissue regeneration, incorporating mesoporous materials can be promising for enhancing vessel formation and cell proliferation of hydrogels. In this paper, we introduce the classification and preparation methods of mesoporous material-loaded composite hydrogels and highlight the applications of composite hydrogels in drug delivery, tumor therapy, antibacterial treatment, osteogenesis, hemostasis, and wound healing. We also summarize the latest research progress and point out future research directions. After searching, no research reporting these contents was found.

Identifying sources of air pollutants is essential for informing actions to reduce emissions, exposures, and adverse health impacts. This study updates and extends apportionments of particulate matter (PM2.5) in Detroit, MI, USA, an area with extensive industrial, vehicular, and construction activity interspersed among vulnerable communities. We demonstrate an approach that uses positive matrix factorization models with combined spatially and temporally diverse datasets to assess source contributions, trend seasonal levels, and examine pandemic-related effects. The approach consolidates measurements from 2016 to 2021 collected at three sites. Most PM2.5 was due to mobile sources, secondary sulfate, and secondary nitrate; smaller contributions arose from soil/dust, ferrous and non-ferrous metals, and road salt sources. Several sources varied significantly by season and site. Pandemic-related changes were generally modest. Results of the consolidated models were more consistent with respect to trends and known sources, and the larger sample size should improve representativeness and stability. Compared to earlier apportionments, contributions of secondary sulfate and nitrate were lower, and mobile sources now represent the dominant PM2.5 contributor. We show the growing contribution of mobile sources, the need to update apportionments performed just 5–10 years ago, and that apportionments at a single site may not apply elsewhere in the same urban area, especially for local sources.

An AA6061 aluminum alloy tube was fabricated by compacting machining chips via thermomechanical consolidation, including hot pressing and hot extrusion. The microstructure evolution and formation of oxide particles were investigated in correlation to tensile mechanical properties. It was found that fine Al/Mg oxide particles were formed due to the fracture of oxide layers on the chips and the reaction between Mg and Al2O3 during hot extrusion. The oxide particles inhibited the growth of recrystallized α-Al grains, leading to the formation of a microstructure consisting of coarse elongated grains with sizes of 420 μm and fine equiaxed grains with sizes of 10 μm. After T6 heat treatment, a microstructure with finer grains (grain sizes: 34 μm) formed due to further recrystallization induced by residual strain. The tensile mechanical properties testing results indicated that a good combination of strength (296 MPa) and ductility (7.6%) was achieved in the T6 heat treated samples, which were likely attributed to the high-quality inter-chip bonding, as well as the fine oxide particles which were small enough that further crack nucleation and growth around them were inhibited during tensile deformation. For the purpose of comparison, the microstructure and mechanical properties of the as-extruded and T6 heat treated samples produced by hot extrusion of the cast ingot of AA6061 aluminum alloy were also investigated. The lower tensile strength of solid-state recycled tube sample might be associated with the consumption of Mg atoms by the oxidation reaction, leading to the lower density of β″ precipitates in precipitation strengthening.

Aluminum salt (AS), one of the most commonly used vaccine adjuvants, has immuno-modulatory activity, but how the administration of AS alone may impact the activation of the skin immune system under inflammatory conditions has not been investigated. Here, we studied the therapeutic effect of AS injection on two distinct skin inflammatory mouse models: an imiquimod (IMQ)-induced psoriasis-like model and an MC903 (calcipotriol)—induced atopic dermatitis-like model. We found that injection of a high dose of AS not only suppressed the IMQ-mediated development of T-helper 1 (Th1) and T-helper 17 (Th17) immune responses but also inhibited the IMQ-mediated recruitment and/or activation of neutrophils and macrophages. In contrast, AS injection enhanced MC903-mediated development of the T-helper 2 (Th2) immune response and neutrophil recruitment. Using an in vitro approach, we found that AS treatment inhibited Th1 but promoted Th2 polarization of primary lymphocytes, and inhibited activation of peritoneal macrophages but not bone marrow derived neutrophils. Together, our results suggest that the injection of a high dose of AS may inhibit Th1 and Th17 immune response-driven skin inflammation but promote type 2 immune response-driven skin inflammation. These results may provide a better understanding of how vaccination with an aluminum adjuvant alters the skin immune response to external insults.

Excessive fat accumulation is a common phenomenon in cultured fish, which can cause metabolic disease such as fatty liver. However, the relative regulatory approach remains to be explored. Based on this, two feeding trials were conducted. Firstly, fish were fed either a normal-fat diet (NFD) or a high-fat diet (HFD) for eight weeks and sampled at the 2nd, 4th, 6th, and 8th week after feeding (Experiment I). In the first four weeks, fish fed an HFD grew faster than those fed an NFD. Conversely, the body weight and weight gain were higher in the NFD group at the 6th and 8th weeks. Under light and transmission electron microscopes, fat accumulation of the liver was accompanied by an obvious endoplasmic reticulum (ER) swell. Accordingly, the expressions of atf-6, ire-1, perk, eif-2α, atf-4, grp78, and chop showed that ER stress was activated at the 6th and 8th weeks. In Experiment II, 50 mg/kg 4-PBA (an ERs inhibitor) was supplemented to an HFD; this was named the 4-PBA group. Then, fish was fed with an NFD, an HFD, and a 4-PBA diet for eight weeks. As the result, the excessive fat deposition caused by an HFD was reversed by 4-PBA. The expression of ER stress-related proteins CHOP and GRP78 was down-regulated by 4-PBA, and the transmission electron microscope images also showed that 4-PBA alleviated ER stress induced by the feeding of an HFD. Furthermore, 4-PBA administration down-regulated SREBP-1C/ACC/FAS, the critical pathways of fat synthesis. In conclusion, the results confirmed that ER stress plays a contributor role in the fat deposition by activating the SREBP-1C/ACC/FAS pathway. 4-PBA as an ER stress inhibitor could reduce fat deposition caused by an HFD via regulating ER stress.

With the rapid development of engineered nanomaterials (ENMs) in biomedical applications, their biocompatibility and cytotoxicity need to be evaluated properly. Recently, it has been demonstrated that inflammasome activation may be a vital contributing factor for the development of biological responses induced by ENMs. Among the inflammasome family, NLRP3 inflammasome has received the most attention because it directly interacts with ENMs to cause the inflammatory effects. However, the pathways that link ENMs to NLRP3 inflammasome have not been thoroughly summarized. Thus, we reviewed recent findings on the role of major ENMs properties in modulating NLRP3 inflammasome activation, both in vitro and in vivo, to provide a better understanding of the underlying mechanisms. In addition, the interactions between ENMs and NLRP3 inflammasome activation are summarized, which may advance our understanding of safer designs of nanomaterials and ENM-induced adverse health effects.

As a unique surface wettability, superhydrophobicity has great application value. A variety of preparation methods for superhydrophobic surfaces have been reported, which have the disadvantages of high cost and complicated process. In order to design a method that is easy to operate, low-cost, and suitable for large-scale preparation of superhydrophobic surfaces, in this paper, hydrophobic nano-SiO2 particles are used as spray fillers, and superhydrophobic surfaces are successfully obtained by the spraying process. According to the classical Cassie and Wenzel theory, the influence of the concentration change of hydrophobic nano-SiO2 particles on their wettability is explained, and the appropriate spray concentration parameters are obtained. The results show that the proportion of hydrophobic nano-SiO2 particles is lower than 0.05 g/mL, which will lead to insufficient microstructure on the surface of the coating, and cannot support the droplets to form the air bottom layer. However, an excessively high proportion of hydrophobic nano-SiO2 particles will reduce the connection effect of the silicone resin and affect the durability of the surface. Through theoretical analysis, there are Wenzel state, tiled Cassie state, and stacked Cassie state in the spraying process. When the substrate surface enters the Cassie state, the lower limit of the contact angle is 149°. This study has far-reaching implications for advancing the practical application of superhydrophobic surfaces.

Recent advances in precision manufacturing technology and a thorough understanding of the properties of piezoelectric materials have made it possible for researchers to develop innovative microrobotic systems, which draw more attention to the challenges of utilizing microrobots in areas that are inaccessible to ordinary robots. This review paper provides an overview of the recent advances in the application of piezoelectric materials in microrobots. The challenges of microrobots in the direction of autonomy are categorized into four sections: mechanisms, power, sensing, and control. In each section, innovative research ideas are presented to inspire researchers in their prospective microrobot designs according to specific applications. Novel mechanisms for the mobility of piezoelectric microrobots are reviewed and described. Additionally, as the piezoelectric micro-actuators require high-voltage electronics and onboard power supplies, we review ways of energy harvesting technology and lightweight micro-sensing mechanisms that contain piezoelectric devices to provide feedback, facilitating the use of control strategies to achieve the autonomous untethered movement of microrobots.

Novel covalent organic framework (COF) composites containing a bipyridine multimetal complex were designed and obtained via the coordination interaction between bipyridine groups and metal ions. The obtained Pt and polyoxometalate (POM)–loaded COF complex (POM–Pt@COF–TB) exhibited excellent oxidation of methane. In addition, the resultant Co/Fe–based COF composites achieved great performance in an electrocatalytic oxygen evolution reaction (OER). Compared with Co–modified COFs (Co@COF–TB), the optimized bimetallic modified COF composites (Co0.75Fe0.25@COF–TB) exhibited great performance for electrocatalytic OER activity, showing a lower overpotential of 331 mV at 10 mA cm−2. Meanwhile, Co0.75Fe0.25@COF–TB also possessed a great turnover frequency (TOF) value (0.119 s−1) at the overpotential of 330 mV, which exhibited high efficiency in the utilization of metal atoms and was better than that of many reported COF-based OER electrocatalysts. This work provides a new perspective for the future coordination of COFs with bimetallic or polymetallic ions, and broadens the application of COFs in methane conversion and electrocatalytic oxygen evolution.

Oxidative stress is a common phenomenon in aquaculture, which can be induced by nutritional or environmental factors. Generally, oxidative stress causes poor growth performance, metabolic dysregulation, and even the death of aquatic animals. To identify a nutritional intervention strategy, high-fat diet (HFD) feeding (Experiment I) and acute ammonia nitrogen challenge (Experiment II) tests were carried out. In Experiment I, HFD feeding significantly decreased the growth performance concomitantly with excessive fat deposition in the liver and abdomen. The addition of 4-PBA in the diet improved the excessive fat accumulation. The activities of antioxidative enzymes were suppressed, and the levels of lipid and protein peroxidation were increased, indicating that HFD feeding induced oxidative stress. The endoplasmic reticulum stress (ERs) related genes were downregulated in the HFD group. Under a transmission electron microscope (TEM), more swollen and dilated ER lumen could be observed. These results indicated that the HFD induced ERs activation. Although 4-PBA acted as a potent ERs inhibitor, as evidenced by the alleviated alterations of ERs molecules and the ER ultrastructure, the oxidative stress was also attenuated by 4-PBA. In Experiment II, dietary 4-PBA improved the tolerance to the acute ammonia nitrogen challenge, as lower mortality and serum aminotransferase activity was found. Further results showed that 4-PBA decreased the peroxidation content and attenuated ERs, thus confirming the correlation between oxidative stress and ERs. Our findings showed that dietary 4-PBA supplementation can attenuate oxidative stress induced by a HFD or acute ammonia challenge; the mechanism is related to its potent inhibition effect for ERs.

Methane (CH4) is the major component of natural gas, a potent greenhouse gas, and a precursor for the formation of tropospheric ozone. Sizable CH4 releases can occur during gas extraction, distribution, and use, thus, the detection and the control of leaks can help to reduce emissions. This study develops, refines, and tests algorithms for detecting CH4 peaks and estimating the background levels of CH4 using mobile monitoring, an approach that has been used to determine the location and the magnitude of pipeline leaks in a number of cities. The algorithm uses four passes of the data to provide initial and refined estimates of baseline levels, peak excursions above baseline, peak locations, peak start and stop times, and indicators of potential issues, such as a baseline shift. Peaks that are adjacent in time or in space are merged using explicit criteria. The algorithm is refined and tested using 1-s near-ground CH4 measurements collected on 20 days while driving about 1100 km on surface streets in Detroit, Michigan by the Michigan Pollution Assessment Laboratory (MPAL). Sensitivity and other analyses are used to evaluate the effects of each parameter and to recommend a parameter set for general applications. The new algorithm improves the baseline estimates, increases sensitivity, and more consistently merges nearby peaks. Comparisons of two data subsets show that results are repeatable and reliable. In the field study application, we detected 534 distinct CH4 peaks, equivalent to ~0.5 peaks per km traveled; larger peaks detected at nine locations on multiple occasions suggested sizable pipeline leaks or possibly other CH4 sources.

Municipal solid waste landfills are significant sources of atmospheric methane, the second most important greenhouse gas after carbon dioxide. Large emissions of methane from landfills contribute not only to global climate change, but also to local ozone formation due to the enhancement of radical chain lengths in atmospheric reactions of volatile organic compounds and nitrogen oxides. Several advanced techniques were deployed to measure methane emissions from two landfills in the Southeast Michigan ozone nonattainment area during the Michigan–Ontario Ozone Source Experiment (MOOSE). These techniques included mobile infrared cavity ringdown spectrometry, drone-mounted meteorological sensors and tunable diode laser spectrometry, estimation of total landfill emissions of methane based on flux plane measurements, and Gaussian plume inverse modeling of distributed methane emissions in the presence of complex landfill terrain. The total methane emissions measured at the two landfills were of the order of 500 kg/h, with an uncertainty of around 50%. The results indicate that both landfill active faces and leaking gas collection systems are important sources of methane emissions.

Cross-technology Communication (CTC) is a novel technique enabling data transmission among devices equipped with different physical layers in a heterogeneous wireless network. Particularly, by enabling cross-technology communication between ZigBee and WiFi, the energy-saving problem and media access control under cross-technology interference would be resolved easily. However, the current CTC designs are either too slow or destructive to ongoing ZigBee transmissions. In this paper, we propose a new Cross-technology Communication framework based on ZigBee chip-level side channel. The proposed design enables the high-throughput ZigBee-to-WiFi cross-technology communication while maintaining transparency to the existing ZigBee network. Specifically, we modify some ZigBee chips within one ZigBee symbol to create a side channel at the CTC sender (ZigBee) for carrying CTC bits while the CTC receiver (WiFi) can detect those modifications and demodulate the CTC bits at WiFi preamble detection. Both theoretical analysis and experiments show that our design would be transparent to ZigBee and throughput can reach 31.25 Kbps—1000× the state-of-the-art CTC design.

The present study determined the effects of live yeast (LY) supplementation during middle–late gestation and the lactation period in primiparous sows on reproductive parameters, lactation performance, and immunity, and also explores the carryover effects in their offspring. On day (d) 60 of gestation, 16 crossbred primiparous sows were randomly assigned to two dietary treatments (with or without supplementation of 425 mg/kg of live yeast; LYT and CT, respectively) homogeneous for body weight (BW) and backfat thickness. Experimental diets were applied from day 60 of gestation to the end of lactation. At weaning, 60 piglets with an average BW of each treatment were selected based on their source litter and assigned to two groups corresponding to the original treatments received by their mothers. Each group had five replicates of six piglets each and was fed a basal diet for 42 days. The results showed that LY supplementation significantly increased the serum IgA and IgG concentrations of sows at farrowing and weaning stages, and of piglets on day 14 and 28 post weaning. No significant differences were found in reproductive and lactation performance, while minor effects were observed on antioxidant capacity. In conclusion, live yeast addition during middle–late gestation and the whole lactation period resulted in enhanced immunity of primiparous sows and their offspring, therefore, improving maternal and progeny health.

Emerging evidence suggests that mitochondrial dysfunction mediates the pathogenesis for non-alcoholic fatty liver disease (NAFLD). Hydroxytyrosol (HT) is a key component of extra virgin olive oil which can exert beneficial effects on NAFLD through modulating mitochondria. However, the mechanism of the impacts of HT still remains elusive. Thus, an in vivo and a series of in vitro experiments were carried out to examine the impacts of hydroxytyrosol (HT) on lipid metabolism and mitochondrial function in fish. For the in vivo experiment, two diets were produced to contain 10% and 16% fat as normal-fat and high-fat diets (NFD and HFD) and two additional diets were prepared by supplementing 200 mg/kg of HT to the NFD and HFD. The test diets were fed to triplicate groups of spotted seabass (Lateolabrax maculatus) juveniles for 8 weeks. The results showed that feeding HFD leads to increased fat deposition in the liver and induces oxidative stress, both of which were ameliorated by HT application. Furthermore, transmission electron microscopy revealed that HFD destroyed mitochondrial cristae and matrix and induced severe hydropic phenotype, while HT administration relieved these alterations. The results of in vitro studies using zebrafish liver cell line (ZFL) showed that HT promotes mitochondrial function and activates PINK1-mediated mitophagy. These beneficial effects of HT disappeared when the cells were treated with cyclosporin A (Csa) as a mitophagy inhibitor. Moreover, the PINK1-mediated mitophagy activation by HT was blocked when compound C (CC) was used as an AMPK inhibitor. In conclusion, our findings demonstrated that HT alleviates fat accumulation, oxidative stress and mitochondrial dysfunction, and its effects are deemed to be mediated via activating mitophagy through the AMPK/PINK1 pathway.

The present study was conducted to investigate the effects of dietary hydroxytyrosol (HT) on oxidative stress, inflammation and mitochondrial homeostasis in blunt snout bream (Megalobrama amblycephala). Fish were fed a low-fat diet (LFD, 5% lipid), a high-fat diet (HFD, 15% lipid), an LFD supplementing 200 mg/kg HT, or an HFD supplementing 200 mg/kg HT. After 10-week feeding, significant reduction of growth was observed in fish fed HFD, compared with other groups. HFD caused oxidative stress and more apoptosis of hepatocytes, while HT addition resulted in significant decrease of ROS and MDA contents, and the apoptotic hepatocytes. Moreover, the expression of genes involving inflammation of HFD group were elevated. Supplementing HT to HFD can attenuate this. All the activities of complexes of mitochondria in the HFD group were decreased compared with those in the LFD group, while supplementing HT to HFD significantly increased complex I-III activities. Furthermore, HFD downregulated the expressions of Atg5 and NRF-1 which induced the failure of mitophagy and biogenesis, while, supplementing HT to HFD reversed these expressions involving mitochondrial autophagy and biogenesis. In summary, adding HT to HFD relieved oxidative stress, apoptosis and inflammation, likely due to its regulation of mitochondrial homeostasis.

Sand production has caused many serious problems in weakly consolidated reservoirs. Therefore, it is very urgent to find out the mechanism for this process. This paper employs a coupled lattice Boltzmann method and discrete element method (LBM-DEM) to study the sand production process of the porous media. Simulation of the sand production process is conducted and the force chain network evolvement is analyzed. Absolute and relative permeability changes before and after the sand production process are studied. The effect of injection flow rate, cementation strength, and confining pressure are investigated. During the simulation, strong force chain rupture and force chain reorganization can be identified. The mean shortest-path distance of the porous media reduces gradually after an initial sharp decrease while the mean degree and clustering coefficient increase in the same way. Furthermore, the degree of preferential wettability for water increases after the sand production process. Moreover, a critical flow rate below which porous media can reach a steady state exists. Results also show that porous media under higher confining pressure will be more stable due to the higher friction resistance between particles to prevent sand production.

Steel corrosion has become the main reason for the deterioration of reinforced concrete structures. Due to the heterogeneity of concrete and the spatial variation of environmental conditions, macrocell corrosion is often formed by localized corrosion, which is more detrimental if the anode is supported by large numbers of cathodes. The macrocell corrosion caused by concrete carbonation has been seldom studied. Furthermore, the influence of geometrical conditions on cathode-controlled corrosion in the chloride environment needs to be further clarified. In this work, the macrocell corrosion of steel embedded in concrete specimens exposed to accelerated carbonation, chloride contamination, and chloride penetration is studied using a modified ASTM G109 method. Concrete specimens with various binder types, geometrical parameters (i.e., concrete cover thickness and the diameter of embedded steel), and boundary conditions were tested. A simplified mathematical model for the prediction of the steel corrosion rate was developed considering two-dimensional oxygen diffusion. The results showed that, at the same level of anodic potential drops, the corrosion current rate in chloride-induced corrosion is higher than that of carbonation-induced corrosion. Chloride contamination is less detrimental to concrete incorporated with slag and pulverized fly ash than it is to pure ordinary Portland cement (OPC), likely due to enhanced chloride binding capacity. The results also indicated that the model considering two-dimensional diffusion can accurately predict the cathodic reaction process on corroded steel bars, which provides a theoretical basis for considering the correction coefficient of steel bar position in the establishment of a steel bar corrosion rate model.

Selective laser melting was used to prepare the ceramic particles reinforced nickel alloy owing to its high designability, high working flexibility and high efficiency. In this paper, a carbides particles reinforced Haynes 230 alloy was prepared using SLM technology to further strengthen the alloy. Microstructures of the carbide particles reinforced Haynes 230 alloy were investigated using electron microscopy (SEM), electron probe microanalysis (EPMA) and transmission electron microscopy (TEM). Meanwhile, the tensile tests were carried out to determine the strengths of the composite. The results show that the microstructure of the composite consisted of uniformly distributed M23C6 and M6C type carbides and the strengths of the alloy were higher than the matrix alloy Haynes 230. The increased strengths of the carbide reinforced Haynes 230 alloy (room temperature yield strength 113 MPa increased, ~ 33.2%) can be attributed to the synergy strengthening including refined grain strengthening, Orowan strengthening and dislocation strengthening.

Additive manufacturing (AM) of nickel-based superalloys is of high interest for application in complex hot end parts. However, it has been widely suggested that the microstructure-properties of the additive manufacturing processed superalloys are not yet fully clear. In this study, the GTD222, an important superalloy for high-temperature hot-end part, were prepared using selective laser melting and then subjected to heat treatment. The microstructure evolution of the GTD222 was investigated and the mechanical properties of heat treated GTD222 were tested. The results have shown that the grain size of the heat treated GTD222 was close to its as-built counterparts. Meanwhile, a large amount of γ’ and nano-scaled carbides were precipitated in the heat treated GTD222. The microstructure characteristics implied that the higher strength of the heat treated GTD222 can be attributed to the γ’ and nano-scaled carbides. This study provides essential microstructure and mechanical properties information for optimizing the heat treatment process of the AM processed GTD222.

Security patterns encompass security-related issues in secure software system development and operations that often appear in certain contexts. Since the late 1990s, about 500 security patterns have been proposed. Although the technical components are well investigated, the direction, overall picture, and barriers to implementation are not. Here, a systematic literature review of 240 papers is used to devise a taxonomy for security pattern research. Our taxonomy and the survey results should improve communications among practitioners and researchers, standardize the terminology, and increase the effectiveness of security patterns.

Carbon aerogels (CA) derived from bamboo cellulose fibers were coupled with TiO2 to form CA/TiO2 hybrids, which exhibited extraordinary performance on the photo-catalytic degradation of methylene blue (MB). The structure and morphology of CA/TiO2 were characterized by field emission scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, and Raman spectrum. The CA displayed a highly porous and interconnected three-dimensional framework structure, while introducing the catalytic active sites of TiO2 onto the aerogel scaffold could remarkably enhance its photo-catalytic activity. The adsorption and photo-catalytic degradation of MB by the CA/TiO2 hybrid were investigated. The maximum adsorption capacity of CA/TiO2 for MB was 18.5 mg/g, which outperformed many similar materials reported in the literature. In addition, compared with other photo-catalysts, the present CA/TiO2 demonstrated superior photo-catalytic performance. Almost 85% of MB in 50 mL solution with a MB concentration of 10 mg/L could be effectively degraded by 15 mg CA/TiO2 in 300 min.

Many machine learning methods have been applied for short messaging service (SMS) spam detection, including traditional methods such as naïve Bayes (NB), vector space model (VSM), and support vector machine (SVM), and novel methods such as long short-term memory (LSTM) and the convolutional neural network (CNN). These methods are based on the well-known bag of words (BoW) model, which assumes documents are unordered collection of words. This assumption overlooks an important piece of information, i.e., word order. Moreover, the term frequency, which counts the number of occurrences of each word in SMS, is unable to distinguish the importance of words, due to the length limitation of SMS. This paper proposes a new method based on the discrete hidden Markov model (HMM) to use the word order information and to solve the low term frequency issue in SMS spam detection. The popularly adopted SMS spam dataset from the UCI machine learning repository is used for performance analysis of the proposed HMM method. The overall performance is compatible with deep learning by employing CNN and LSTM models. A Chinese SMS spam dataset with 2000 messages is used for further performance evaluation. Experiments show that the proposed HMM method is not language-sensitive and can identify spam with high accuracy on both datasets.

Polyethylene oxide-based solid polymer electrolytes (SPEs) are of research interest because of their potential applications in all-solid-state Li+ batteries. However, despite their advantages in terms of compatibility with the electrodes and easy processing, polyethylene oxide (PEO)/Li+ complexes often suffer from low conductivity at room temperature. Understanding the conduction mechanism and, in turn, developing strategies to improve the conductivity have long been the main objectives underlying research into PEO/Li+ complex electrolytes. Here, we prepared several special PEO/Li+ complex samples where the PEO/Li+ complex structures were located on the surfaces of PEO crystals and consisted of high content chain ends. We found two different Li+ species in the PEO/Li+ complex structures via solid-state nuclear magnetic resonance (NMR). The 2D 7Li exchange NMR showed the exchange process between the different Li+ species. The exchange dynamics of the Li+ ions provide a molecular mechanism of the Li+ transportation in the surface of PEO crystal lamella, which is further correlated with the ionic conduction mechanism of the PEO/Li+ complex structure.

In Beijing, China, the rational consumption of energy is affected by the insufficient linkage mechanism of the energy pricing system, the unreasonable price ratio and other issues. This paper combines the characteristics of Beijing’s energy market, putting forward the society-economy equilibrium indicator R maximization taking into consideration the mitigation cost to determine a reasonable price ratio range. Based on the computable general equilibrium (CGE) model, and dividing four kinds of energy sources into three groups, the impact of price fluctuations of electricity and natural gas on the Gross Domestic Product (GDP), Consumer Price Index (CPI), energy consumption and CO2 and SO2 emissions can be simulated for various scenarios. On this basis, the integrated effects of electricity and natural gas price shocks on the Beijing economy and environment can be calculated. The results show that relative to the coal prices, the electricity and natural gas prices in Beijing are currently below reasonable levels; the solution to these unreasonable energy price ratios should begin by improving the energy pricing mechanism, through means such as the establishment of a sound dynamic adjustment mechanism between regulated prices and market prices. This provides a new idea for exploring the rationality of energy price ratios in imperfect competitive energy markets.

Rabbit hemorrhagic disease virus (RHDV) is the causative agent of rabbit hemorrhagic disease (RHD). RHD, characterized by hemorrhaging, liver necrosis, and high morbidity and mortality in rabbits and hares, causes severe economic losses in the rabbit industry worldwide. Due to the lack of an efficient in-vitro propagation system for RHDV, the current vaccine is produced via chemical inactivation of crude RHDV preparation derived from the livers of infected rabbits. Inactivated vaccines are effective for controlling RHD, but the potential problems of biosafety and animal welfare have negative effects on the application of inactivated vaccines. In this study, an oral Lactobacillus casei (L. casei) vaccine was used as an antigen delivery system to express RHDV capsid protein VP60(VP1)-eGFP fusion protein. The expression of the recombinant protein was confirmed via western blotting and immunofluorescence (IFA). Our results indicate that oral administration of this probiotic vaccine can stimulate secretory immunoglobulin A (SIgA)-based mucosal and IgG-based humoral immune responses in rabbits. The immunized rabbits were completely protected against challenge with RHDV. Our findings indicate that the L. casei expression system is a new strategy for the development of a safe and efficient vaccine against RHDV.

Google Earth (GE) releases free images in high spatial resolution that may provide some potential for regional land use/cover mapping, especially for those regions with high heterogeneous landscapes. In order to test such practicability, the GE imagery was selected for a case study in Wuhan City to perform an object-based land use/cover classification. The classification accuracy was assessed by using 570 validation points generated by a random sampling scheme and compared with a parallel classification of QuickBird (QB) imagery based on an object-based classification method. The results showed that GE has an overall classification accuracy of 78.07%, which is slightly lower than that of QB. No significant difference was found between these two classification results by the adoption of Z-test, which strongly proved the potentials of GE in land use/cover mapping. Moreover, GE has different discriminating capacity for specific land use/cover types. It possesses some advantages for mapping those types with good spatial characteristics in terms of geometric, shape and context. The object-based method is recommended for imagery classification when using GE imagery for mapping land use/cover. However, GE has some limitations for those types classified by using only spectral characteristics largely due to its poor spectral characteristics.