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With the development of ecological civilization construction, urban planning and development in China have entered a phase in which optimizing and constructing ecological spaces is required. As a national livable city, Xuchang has experienced rapid economic development in recent years, leading to significant urban expansion that has impacted the layout of ecological space networks in the central urban area and its surroundings. Therefore, identifying and optimizing the spatial layout of ecological corridors in Xuchang City are crucial for ecological development and park city construction. This study utilizes multisource geospatial data to identify and extract ecological corridors in the central urban area of Xuchang City. Ecological resistance and gravity models are employed to identify and verify that the primary ecological corridor pattern in Xuchang City is situated in Weidu District, which is a central urban area. Finally, 11 main ecological corridors in the central urban area are delineated. In response to the identification of ecological corridors, this study integrates spatial analysis methods and text analysis methods to evaluate the characteristics of urban ecological corridors. The results indicate that Xudu Park extends outward, serving as the hub of the ecological network, and that West Lake Park and Luming Lake Park form the core of the urban park system. Finally, based on the spatial relationships, ecological benefits, and citizen experience of each ecological corridor and the green parks it traverses, strategies for optimizing the layout of urban ecological corridors are proposed.

This paper introduces a current control method for permanent magnet synchronous motors (PMSMs) using a disturbance sliding mode observer (DSMO) in conjunction with a linear quadratic regulator (LQR). This approach enhances control performance, streamlines the tuning of controller parameters, and offers robust optimal control that is resistant to system disturbances. The LQR controller based on state feedback is advantageous for its simplicity in parameter adjustment and achieving an optimal control effect easily under specific performance indicators. It is suitable for the optimal control of strong linear systems that can be accurately modeled. However, most practical systems are difficult to model accurately, and the time-varying system parameters and existing nonlinearity limit the engineering application of LQR. In the PMSM current control loop, there is strong nonlinear disturbance manifesting as the nonlinearity of its dynamic model. Additionally, substantial noise and variations in system parameters within actual motor circuits hinder the linear quadratic regulator from attaining optimal performance. A disturbance sliding mode observer is proposed to enhance the LQR controller, enabling superior performance in nonlinear current loop control. Simulation and actual hardware experiments were conducted to verify the performance and robustness of the control scheme proposed in this paper. Compared with the widely used PI controller in engineering and sliding mode control (SMC) specialising in disturbance rejection, it offers the advantage of straightforward parameter tuning and can swiftly achieve the robust and optimal control performance that engineers prioritize.

Tibetan pig is a unique pig breed native to the Qinghai–Tibet Plateau. To investigate viral communities associated with porcine respiratory disease complex (PRDC), 167 respiratory samples were collected from Tibetan pigs in the Ganzi Tibetan autonomous prefecture of Sichuan province. Following library construction and Illunima Novaseq sequencing, 18 distinct viruses belonging to 15 viral taxonomic families were identified in Tibetan pigs with PRDC. Among the 18 detected viruses, 3 viruses were associated with PRDC, including porcine circovirus type 2 (PCV-2), Torque teno sus virus (TTSuV), and porcine cytomegalovirus (PCMV). The genomic sequences of two PCV-2 strains, three TTSuV strains, and one novel Porprismacovirus strain were assembled by SOAPdenovo software (v2). Sequence alignment and phylogenetic analysis showed that both PCV-2 strains belonged to PCV-2d, three TTSuVs were classified to TTSuV2a and TTSuV2b genotypes, and the Porprismacovirus strain PPMV-SCgz-2022 showed a close genetic relationship with a virus of human origin. Recombination analysis indicated that PPMV-SCgz-2022 may have originated from recombination events between Human 16,806 × 66-213 strain and Porcine 17,668 × 82-593 strain. Furthermore, the high proportion of single infection or co-infection of PCV2/TTSuV2 provides insight into PRDC infection in Tibetan pigs. This is the first report of the viral communities in PRDC-affected Tibetan pigs in this region, and the results provides reference for the prevention and control of respiratory diseases in these animals.

Leaf mass per area (LMA) is a key structural parameter that reflects the functional traits of leaves and plays a vital role in simulating the material and energy cycles of plant ecosystems. In this study, vertical whorl-by-whorl sampling of LMA was conducted in a young Larix principis-rupprechtii plantation during the growing season at the Saihanba Forest Farm. The vertical and seasonal variations in LMA were analysed. Subsequently, a predictive model of LMA was constructed. The results revealed that the LMA varied significantly between different crown whorls and growing periods. In the vertical direction of the crown, the LMA decreased with increasing crown depth, but the range of LMA values from the tree top to the bottom was, on average, 30.4 g/m2, which was approximately 2.5 times greater in the fully expanded phase than in the early leaf-expanding phase. During different growing periods, the LMA exhibited an allometric growth trend that increased during the leaf-expanding phase and then tended to stabilize. However, the range of LMA values throughout the growing period was, on average, 40.4 g/m2. Among the univariate models, the leaf dry matter content (LDMC) performed well (adjusted determination coefficient (Ra2) = 0.45, root mean square error (RMSE) = 13.48 g/m2) in estimating the LMA. The correlation between LMA and LDMC significantly differed at different growth stages and at different vertical crown whorls. The dynamic predictive model of LMA constructed with the relative depth in the crown (RDINC) and date of the year (DOY) as independent variables was reliable in both the assessments (Ra2 = 0.68, RMSE = 10.25 g/m2) and the validation (absolute mean error (MAE) = 8.05 g/m2, fit index (FI) = 0.682). Dynamic simulations of crown LMA provide a basis for elucidating the mechanism of crown development and laying the foundation for the construction of an ecological process model.

Passive differential optical absorption spectroscopy (DOAS) is widely used to monitor the three-dimensional distribution of atmospheric pollutants. However, the observational and retrieval accuracy of this technique is significantly influenced by the precise wavelength calibration of solar spectra. Current calibration methods face challenges in automation when dealing with complex remote-sensing conditions. We introduce a novel automatic wavelength calibration algorithm for passive DOAS based on sequence-matching technology to estimate the spectral parameters of the spectrometer channels, integrating advanced processing measures such as feature structure enhancement and sub-pixel interpolation. These measures significantly reduce the dependency on reference spectrum resolution and accurately correct even minor spectral shifts. We perform sensitivity experiments using synthetic spectra to determine optimal retrieval configurations, followed by field tests at four cities on the Yangtze River Delta, China, to calibrate and compare passive DOAS instruments of various resolutions. Comparative verification in these field studies demonstrated that our algorithm was suitable for rapid spectral calibration within a wider resolution range of 0.03 nm to 0.1 nm with a wavelength inversion error < 0.01 nm. This highlights the applicability and calibration precision of our algorithm.

Seneca Valley Virus (SVV), a member of the Picornaviridae family, is an emerging porcine virus that can cause vesicular disease in pigs. However, the immune evasion mechanism of SVV remains unclear, as does its interaction with other pathways. STING (Stimulator of interferon genes) is typically recognized as a critical factor in innate immune responses to DNA virus infection, but its role during SVV infection remains poorly understood. In the present study, we observed that STING was degraded in SVV-infected PK-15 cells, and SVV replication in the cells was affected when STING was knockdown or overexpressed. The STING degradation observed was blocked when the SVV-induced autophagy was inhibited by using autophagy inhibitors (Chloroquine, Bafilomycin A1) or knockdown of autophagy related gene 5 (ATG5), suggesting that SVV-induced autophagy is responsible for STING degradation. Furthermore, the STING degradation was inhibited when reticulophagy regulator 1 (FAM134B), a reticulophagy related receptor, was knocked down, indicating that SVV infection induces STING degradation via reticulophagy. Further study showed that in eukaryotic translation initiation factor 2 alpha kinase 3 (PERK)/activating transcription factor 6 (ATF6) deficient cells, SVV infection failed to induce reticulophagy-medaited STING degradation, indicating that SVV infection caused STING degradation via PERK/ATF6-mediated reticulophagy. Notably, blocking reticulophagy effectively hindered SVV replication. Overall, our study suggested that SVV infection resulted in STING degradation via PERK and ATF6-mediated reticulophagy, which may be an immune escape strategy of SVV. This finding improves the understanding of the intricate interplay between viruses and their hosts and provides a novel strategy for the development of novel antiviral drugs.

Both Manganese (Mn2+) and MSA-2 can activate the downstream signal pathway through stimulator of interferon genes (STING) and induce the expression of type I interferon, which is important for hosts to protect against DNA viruses. However, its effect on RNA viruses remains unknown. In this study, we used Seneca Valley virus (SVV) as a model RNA virus to investigate the inhibitory effects of Mn2+ and MSA-2 on the virus replication in the porcine cells (PK-15 cells). The results showed that both MSA-2 and Mn2+ were able to inhibit the SVV replication in PK-15 cells. The combination of MAS-2 and Mn2+ could confer better protection against SVV. Further studies showed that MSA-2 and Mn2+ could activate TBK1, IRF3 and NFκB through STING and induce the expression of IFN-β, IL-6 and TNF-α. The present study confirmed that MSA-2 synergized with Mn2+ in STING activation to generate a better antiviral effect in vitro, which would be helpful for the further development of effective antiviral drugs in the future.

Cold-formed steel (CFS) structures are widely used in construction and infrastructure due to their lightweight and high-strength properties. However, their thin-walled nature makes them geometrically sensitive to compressive loading. The Digital Twin (DT)-based numerical simulation method is developed using the actual geometries of CFS shapes, which are acquired by a 3D laser scanner. The DT-based numerical simulation incorporates the reconstructed measurement point clouds into the finite element modeling, ensuring that actual geometric features are retained. A series of tests, including material and axial compression testing, are conducted to validate the modeling parameters, such as mesh sizes and boundary conditions. The advantages of the DT-based numerical simulation method are highlighted compared to the traditional CFS member numerical simulation, which incorporates only the first mode of geometric imperfection. Additionally, DT-based numerical simulations offer more accurate load capacities and deformation predictions. Moreover, the automated and validated DT-based numerical simulation demonstrates prevalence in modeling efficiency and computation effectiveness. The DT-based numerical simulation method holds potential for application in smart structural analysis, where accurate geometries derived from extensive measurement point clouds are integrated into numerical modeling.

Quorum-sensing (QS) is involved in numerous physiological processes in bacteria, such as biofilm formation, sporulation, and virulence formation. Therefore, the search for new quorum-sensing inhibitors (QSI) is a promising strategy that opens up a new perspective for controlling QS-mediated bacterial pathogens. To explore new QSIs, a strain named Streptomyces sp. D67 with QS inhibitory activity was isolated from the soil of the arid zone around the Kumutag Desert in Xinjiang. Phylogenetic analyses demonstrated that strain D67 shared the highest similarity with Streptomyces ardesiacus NBRC 15402T (98.39%), which indicated it represented a potential novel species in the Streptomyces genus. The fermentation crude extracts of strain D67 can effectively reduce the violacein production produced by Chromobacterium violaceum CV026 and the swarming and swimming abilities of Pseudomonas aeruginosa. It also has significant inhibitory activity on the production of virulence factors such as biofilm, pyocyanin, and rhamnolipids of P. aeruginosa in a significant concentration-dependent manner, but not on protease activity. A total of 618 compounds were identified from the fermentation crude extracts of strain D67 by LC-MS, and 19 compounds with significant QS inhibitory activity were observed. Overall, the strain with QS inhibitory activity was screened from Kumutag Desert in Xinjiang for the first time, which provided a basis for further research and development of new QSI.

Elucidating the correlation between soil microbial communities and forest productivity is the focus of research in the field of forest ecology. Nonetheless, the relationship between stand age, soil quality, soil microorganisms, and their combined influence on productivity is still unclear. In this study, five development stages (14, 25, 31, 39, and >80 years) of larch (Larix principis-rupprechtii) forests were investigated in Inner Mongolia and Shanxi provinces of China. We evaluated soil quality using the Integrated Soil Quality Index (SQI) and analyzed changes in bacterial and fungal communities using high-throughput sequencing. Regression models were also established to examine the impacts of stand age, microbial diversity, and SQI on productivity. The findings revealed an ascending trend in soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), available potassium (AK), and SQI in 14, 25, 31, and 39-year-old stands. The abundance of oligotrophic bacteria Acidobacteria exhibited a gradual decline with increasing forest age, whereas copiotroph bacteria Proteobacteria displayed a progressive increase. Stands older than 80 years exhibited a higher abundance of both the saprophytic fungus Ascomycota and mycorrhizal fungus Basidiomycota. Forest age had a significant impact on microbial diversity, particularly in terms of bacterial diversity, impacting both α and β diversity. The soil bacterial community structure was influenced by AK, SOM, TN, TP, and pH. Conversely, the fungal community structure was regulated by crucial factors including SOM, TN, TP, TK, AK, and pH. Fungal diversity demonstrated a significant and positive correlation with the basal area increment (BAI) of larch. Furthermore, microbial diversity accounted for 23.6% of the variation in BAI. In summary, the findings implied a robust association between microbial composition, diversity, and soil chemical properties throughout the chronosequence of larch forests. These factors collectively played a crucial role in influencing the productivity of larch forest.

Urban public buildings carbon emissions exhibit an upward trend and have a large potential in carbon emission reduction. The analysis of spatiotemporal characteristics and driving factors for urban public buildings carbon emissions is essential in formulating effective policies for carbon reduction, meeting commitments to peak carbon emissions and achieving carbon neutrality. This study takes China’s urban public buildings carbon emissions as the research object, employing methods such as spatial autocorrelation analyses, kernel density estimation analyses, and the LMDI decomposition methods to explore the spatiotemporal characteristics and regional disparities in carbon emissions from 2006 to 2019. Furthermore, it quantifies the contributions of driving factors to the spatiotemporal changes in urban public buildings carbon emissions. The results show the following: (1) Urban public buildings carbon emissions among provinces are consistently increasing, indicating an overall upward trend. The spatial distribution highlights significant regional disparities. (2) The spatial characteristics of urban public buildings carbon emissions were basically stable. The eastern coastal regions demonstrate a high-high cluster, while the western regions exhibit a low-low cluster. The overall cluster evolution showed a decreasing trend from east to west. (3) Per capita urban public building area, economic density, urbanization rate, and population size serve as driving factors for carbon emissions from urban public buildings, while energy efficiency and energy consumption intensity act as inhibitory factors. The findings of this research can assist policymakers in getting a deeper comprehension of urban public buildings carbon emissions and providing a scientific basis to formulate appropriate carbon emission reduction policies.

China is currently recognized as the leading global energy consumer and CO2 emitter. A significant amount of carbon emissions can be attributed to urban public buildings. Establishing an equitable and efficient carbon emission allocation mechanism is a crucial step to meeting the ambitious targets in China’s 2030 carbon peak plan. In this study, we estimate the total amount of CO2 emissions from urban public buildings by 2030 and propose a preliminary scheme of carbon quota assignment for each province. By means of applying the zero-sum gains data envelopment analysis (ZSG-DEA) model, the carbon emission quotas allocation of urban public buildings in China’s 30 provinces is proposed, and the corresponding pressure to reduce provincial carbon emissions is analyzed. The results indicate that Qinghai has the lowest carbon emission rate (0.01%) for urban public buildings, while Guangdong has the highest (9.06%). Among the provinces, Jiangsu, Jiangxi, and Tianjin face the least pressure in reducing carbon emissions from urban public buildings. On the other hand, Hebei, Beijing, and Anhui are under great pressure to decrease carbon emissions. Notably, Hebei is predicted to have the highest emission reduction requirement of 95.66 million tons. In terms of pressures on carbon emissions reduction for urban public buildings, Jiangsu, Jiangxi, and Tianjin exhibit the least pressure. Hebei, Beijing, and Anhui are facing intense pressure to decrease carbon emissions. These findings offer policymakers valuable insights into developing a fair and efficient carbon allowance allocation strategy, while also contributing to China’s efforts to mitigate carbon emissions and combat climate change.

The present cross-sectional survey was carried out to investigate the distribution and risk factors of FMD in Pakistan’s northern border regions. About 385 serum samples were compiled from small ruminants (239) and large ruminants (146) and tested using 3ABC-Mab-bELISA. An overall apparent seroprevalence of 67.0% was documented. The highest seroprevalence of 81.1% was reported in the Swat, followed by 76.6% in Mohmand, 72.7% in Gilgit, 65.6% in Shangla, 63.4% in Bajaur, 46.6% in Chitral and lowest 46.5% in Khyber region. Statistically significant variations in seroprevalence of 51.5%, 71.8%, 58.3%, and 74.4% were recorded in sheep, goats, cattle, and buffaloes, respectively. From the different risk factors investigated, age, sex, species of animal, seasons, flock/herd size, farming methods, outbreak location, and nomadic animal movement were found to be significantly associated (p < 0.05) with the seroprevalence of FMD. It was concluded that proper epidemiological study, risk-based FMD surveillance in small ruminants, vaccination strategy, control measures for transboundary animal movement, collaborations, and awareness programs need to be practiced in the study regions to investigate the newly circulating virus strains in large and small ruminants and associated factors for the wide seroprevalence to plan proper control policies to bound the consequence of FMD in the region.

Fibrinolytic enzymes are a kind of proteolytic enzymes that can hydrolyze fibrin and dissolve blood clots. They could be used as a therapeutic agent for treating thrombosis. It is important for the treatment of cardiovascular disease to find and develop new thrombolytic drugs. In order to explore new fibrinolytic enzymes, a strain named 214L-11 with protease and fibrinolytic enzyme activity, which was isolated from the Flaming Mountain of Xinjiang Province, was screened using the skimmed milk plate, the blood powder agarose plate and the fibrin plate methods. Phylogenetic analyses showed that strain 214L-11 shared the highest similarity with Streptomyces fumanus NBRC 13042T (98.88%), which indicated that it represented a potential novel species in the Streptomyces genus. The fibrinolytic enzyme produced by 214L-11 displayed thrombolytic and anticoagulant activities, and it could degrade a single specific protein in the thrombus, thereby destroying the thrombus structure. The fermentation medium optimized through response surface methodology was 15 g/L soluble starch, g/L KNO3 0.58, 0.43 g/L peptone, 0.01 g/L FeSO4·7H2O, 0.5 g/L MgSO4·7H2O, 0.2 g/L Mn2+, 0.5 g/L NaCl and 1 L distilled water, pH 8, and the maximum amount of fibrinolytic enzyme produced by strain 214L-11 in the optimal fermentation medium was 1255.3 FU/mL. Overall, the fibrinolytic enzyme-producing strain was screened from the Flaming Mountain of Xinjiang for the first time, which provided a basis for further research and the development of new efficient and safe hemolytic drugs.

Venous blood gas analytes are commonly examined in animals, and the results may be important when evaluating the overall health status of an animal. Pangolins are critically endangered mammals, and there is limited information on their physiological reference values in the literature. The aim of this study was to analyze venous blood gas and biochemical parameters before and during isoflurane anesthesia in wild healthy Sunda and Chinese pangolins. The results obtained showed that the blood gas index trends of the two pangolin species before and after isoflurane anesthesia were the same. After anesthesia, the partial pressure of carbon dioxide (pCO2), partial pressure of oxygen (pO2), total carbon dioxide (CO2), mean blood bicarbonate (HCO3−), extracellular fluid compartment (BEecf) base excess and the mean blood glucose (Glu) levels of both pangolin species showed a significant increase compared to the pre-anesthesia period. In contrast, the mean blood potassium (K+), lactate (Lac) and mean blood pH levels were significantly lower. No significant differences in the mean blood sodium (Na+) or blood ionized calcium (iCa) levels were observed during anesthesia. This study is important for future comparisons and understanding the health status of this endangered species.

Wearable sensors integrating multiple functionalities are highly desirable in artificial wearable devices, which are of great significance in the field of biomedical research and for human–computer interactions. However, it is still a great challenge to simultaneously perceive multiple external stimuli such as pressure and temperature with one single sensor. Combining the piezoresistive effect with the negative temperature coefficient of resistance, in this paper, we report on a pressure–temperature dual-parameter sensor composed of a polydimethylsiloxane film, carbon nanotube sponge, and poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate). The proposed multifunctional sensor can stably monitor pressure signals with a high sensitivity of 16 kPa−1, has a range of up to 2.5 kPa, and also has a fast response time. Meanwhile, the sensor can also respond to temperature changes with an ultrahigh sensitivity rate of 0.84% °C−1 in the range of 20 °C to 80 °C. To validate the applicability of our sensor in practical environments, we conducted real-scene tests, which revealed its capability for monitoring = human motion signals while simultaneously sensing external temperature stimuli, reflecting its great application prospects for electronic wearable devices.

In this work, bacterial community composition and actinobacteria resources were explored in extremely hot and hyper-arid areas of Flaming Mountain. This was achieved through a combination of PCR amplicon sequencing of bacterial 16S rRNA gene and cultivation-dependent isolation and characterization efforts. According to the high-throughput sequencing results and soil characteristics, 11 kinds of media were firstly designed to isolate actinobacteria, following the screening and identification of related strains. The results showed that a total of 2994 operational taxonomic units (OTUs) were obtained, involving 22 phyla, 77 orders and 121 genera. Among them, actinobacteria with the relative abundance of 8% ranked third, accounting for 33 genera and 47 species. A total of 132 strains distributed by eight families and 11 genera of actinobacteria were isolated from 11 media, of which six strains were potential new species. Furthermore, the functional characteristics of isolated strains were preliminarily evaluated. The results showed that the obtained strains generally had tolerance against heat, salt and alkali. Fifty-two strains had antibacterial activity, 69 strains could produce hydrolases, and 12.4% of the strains had quorum sensing inhibitory activity. The present study has laid a solid foundation for further understanding the bacterial diversity and exploiting actinobacteria resources in the Flaming Mountain area.

Foot-and-mouth disease (FMD) is an acute contagious disease of cloven-hoofed animals such as cattle, pigs, and sheep. Current emergency FMD vaccines are of limited use for early protection because their protective effect starts 7 days after vaccination. Therefore, antiviral drugs or additives are used to rapidly stop the spread of the virus during FMD outbreaks. Manganese (Mn2+) was recently found to be an important substance necessary for the host to protect against DNA viruses. However, its antiviral effect against RNA viruses remains unknown. In this study, we found that Mn2+ has antiviral effects on the FMD virus (FMDV) both in PK15 cells and mice. The inhibitory effect of Mn2+ on FMDV involves NF-κB activation and up-regulation of interferon-stimulated genes. Animal experiments showed that Mn2+ can be highly effective in protecting C57BL/6N mice from being infected with FMDV. Overall, we suggest Mn2+ as an effective antiviral additive for controlling FMDV infection.

Organic–inorganic hybrid materials built by inorganic and organic building units have attracted intensive interest in the past decades due to unique chemical and physical properties. However, rare organic–inorganic hybrid materials show excellent permanent magnetic properties. Here, we develop a facile chemical solution method to bottom-up synthesize a new hybrid (Fe2Se3)2[Fe(dien)2]0.9. This hybrid phase with the space group P21/c (14) possesses a rodlike shape with a diameter of 100–2000 nm and a length of 5–50 µm. The hybrid rods are ferrimagnetic with a Curie temperature (TC) of 11 K. They show a high coercivity (HC) of 4.67 kOe and a saturation magnetization (MS) of 13.5 emu/g at 2 K. Compared with orthorhombic (FeSe2)2Fe(dien)2, the excellent magnetic performance of the hybrid rods is ascribed to the monoclinic hybrid structure built by Fe(dien)2 complexes and Fe2Se3 double chains. Our study provides guidance for connecting inorganic fragments of FeSe2 single chains, Fe2Se3 double chains or β-Fe3Se4 layers with Fe(dien)2 complexes for organic–inorganic hybrid phases with varied crystal structures and magnetic properties.

The common feature for a nontrivial hard problem is the existence of nontrivial topological structures, non-planarity graphs, nonlocalities, or long-range spin entanglements in a model system with randomness. For instance, the Boolean satisfiability (K-SAT) problems for K ≥ 3 MSATK≥3 are nontrivial, due to the existence of non-planarity graphs, nonlocalities, and the randomness. In this work, the relation between a spin-glass three-dimensional (3D) Ising model MSGI3D with the lattice size N = mnl and the K-SAT problems is investigated in detail. With the Clifford algebra representation, it is easy to reveal the existence of the long-range entanglements between Ising spins in the spin-glass 3D Ising lattice. The internal factors in the transfer matrices of the spin-glass 3D Ising model lead to the nontrivial topological structures and the nonlocalities. At first, we prove that the absolute minimum core (AMC) model MAMC3D exists in the spin-glass 3D Ising model, which is defined as a spin-glass 2D Ising model interacting with its nearest neighboring plane. Any algorithms, which use any approximations and/or break the long-range spin entanglements of the AMC model, cannot result in the exact solution of the spin-glass 3D Ising model. Second, we prove that the dual transformation between the spin-glass 3D Ising model and the spin-glass 3D Z2 lattice gauge model shows that it can be mapped to a K-SAT problem for K ≥ 4 also in the consideration of random interactions and frustrations. Third, we prove that the AMC model is equivalent to the K-SAT problem for K = 3. Because the lower bound of the computational complexity of the spin-glass 3D Ising model CLMSGI3D is the computational complexity by brute force search of the AMC model CUMAMC3D, the lower bound of the computational complexity of the K-SAT problem for K ≥ 4 CLMSATK≥4 is the computational complexity by brute force search of the K-SAT problem for K = 3 CUMSATK=3. Namely, CLMSATK≥4=CLMSGI3D≥CUMAMC3D=CUMSATK=3. All of them are in subexponential and superpolynomial. Therefore, the computational complexity of the K-SAT problem for K ≥ 4 cannot be reduced to that of the K-SAT problem for K < 3.

Cardiovascular disease and its consequences on human health have never stopped and even show a trend of appearing in increasingly younger generations. The establishment of an excellent deep learning algorithm model to assist physicians in identifying and the early screening of ECG abnormalities can effectively improve the accuracy of diagnosis. Therefore, in this study, the deep residual network model is adapted for feature extraction and classification of ECG signals by pooling embedded into layers and double channel connection. At the same time, the wavelet adaptive threshold denoising algorithm is used to complete the high signal-to-noise filtering of ECG signals. Then, the alternate pooling residual network (APRN) is compared with the convolutional neural network (CNN), CNN with one residual unit (CNN-R), and the deep residual network (ResNet-18) using ECG datasets from the American MIT-BIH arrhythmia and ST segment abnormality database, European ST-T database, and sudden cardiac death ambulatory ECG database. The results are as follows: The average classification accuracy of the APRN on the four datasets is 97.89%, while the accuracies on CNN, CNN-R, and ResNet-18 are 97.17%, 97.53%, and 97.73%, respectively. In addition, compared with ResNet-18, the classification accuracy of our APRN on each class of data improves by 16.44% in total.

Gastric cancer has become a global health issue, severely disrupting daily life. Early detection in gastric cancer patients and immediate treatment contribute significantly to the protection of human health. However, routine gastric cancer examinations carry the risk of complications and are time-consuming. We proposed a framework to predict gastric cancer non-invasively and conveniently. A total of 703 tongue images were acquired using a bespoke tongue image capture instrument, then a dataset containing subjects with and without gastric cancer was created. As the images acquired by this instrument contain non-tongue areas, the Deeplabv3+ network was applied for tongue segmentation to reduce the interference in feature extraction. Nine tongue features were extracted, relationships between tongue features and gastric cancer were explored by using statistical methods and deep learning, finally a prediction framework for gastric cancer was designed. The experimental results showed that the proposed framework had a strong detection ability, with an accuracy of 93.6%. The gastric cancer prediction framework created by combining statistical methods and deep learning proposes a scheme for exploring the relationships between gastric cancer and tongue features. This framework contributes to the effective early diagnosis of patients with gastric cancer.

Heavy rare-earth (HRE) elements are important for the preparation of high-coercivity permanent magnets. A further understanding of the thermodynamic properties of HRE phases, and the magnetization reversal mechanism of magnets are still critical issues to obtain magnets that can achieve better performance. In this work, the Nd–Dy–Fe–B multicomponent system is investigated via the calculation of the phase diagram (CALPHAD) method and micromagnetic simulation. The phase composition of magnets with various ratios of Nd and Dy is assessed using critically optimized thermodynamic data. γ-Fe and Nd2Fe17 phases are suppressed when partial Nd is substituted with Dy (2Fe14B phase favorable. The influence of the magnetic properties of grain boundaries (GBs) on magnetization reversal is detected by the micromagnetic simulations with the 3D polyhedral grains model. Coercivity was enhanced with both 3 nm nonmagnetic and the hard-magnetic GBs for the pinning effect besides the GBs. Moreover, the nucleation and propagation of reversed domains in core-shell grains are investigated, which suggests that the magnetic structure of grains can also influence the magnetization reversal of magnets. This study provides a theoretical route for a high-efficiency application of the Dy element, realizing a deterministic enhancement of the coercivity in Nd–Fe–B-based magnets.

A TiN/TiNC/Al2O3 multilayer coating was deposited on an Inconel 625 alloy by the chemical vapor deposition method as a protective barrier to improve the corrosion resistance in supercritical water. The corrosion characteristics were evaluated in a reactor at 500 °C and 25 MPa for 72 h. The surface morphology of the coated samples was relatively dense with no obvious cracks or pores observed. The XRD analysis revealed that the coatings were composed of TiN, TiNC and α-Al2O3 phases. After exposure to supercritical water, the surface morphology of the coatings was still dense and kept integrity. The phase composition of the coatings was also not changed, with no obvious corrosion scales detected. This result demonstrates the effectiveness of TiN/TiNC/Al2O3 coatings as a protective coating under harsh supercritical water environments.

Fano resonance, which is based on a plasmonic metasurface, has many potential applications in various fields, such as biochemical sensors, slow light effect, and integrated optical circuits. In this study, a rectangular-like nanotetramer metasurface structure composed of four round-head nanorods was designed. The transmission spectrum, surface charge, and electrical field distributions of the proposed structure were simulated using the finite element method. A double Fano resonance profile was observed in the transmission spectrum. One of the Fano resonances was caused by the symmetry breaking and plasmon hybridization between the horizontal double rods, whereas the other resonance was due to the plasmonic modes’ hybridization among four nanorods. These resonances could be independently tuned because of different formation mechanisms. The number of Fano resonances could be adjusted by changing the coupling distance between the horizontal and vertical rods. The results contributed to designing the highly sensitive sensors based on the plasmonic metasurface.

A plasmonic refractive index sensor based on surface plasmon polaritons (SPPs) that consist of metal–insulator–metal (MIM) waveguides and a whistle-shaped cavity is proposed. The transmission properties were simulated numerically by using the finite element method. The Fano resonance phenomenon can be observed in their transmission spectra, which is due to the coupling of SPPs between the transmission along the clockwise and anticlockwise directions. The refractive index-sensing properties based on the Fano resonance were investigated by changing the refractive index of the insulator of the MIM waveguide. Modulation of the structural parameters on the Fano resonance and the optics transmission properties of the coupled structure of two MIM waveguides with a whistle-shaped cavity were designed and evaluated. The results of this study will help in the design of new photonic devices and micro-sensors with high sensitivity, and can serve as a guide for future application of this structure.

Although nickel-based alloys are widely used in industries due to their oxidation and corrosion resistance, the pursuit of better performance in harsh environments is still a great challenge. In this work, we developed a sol–gel method to synthesize Ni3Al coating on a nickel alloy, assisted by a post-annealing process, and investigated the oxidation-resistant performance. The coating thickness can be controlled by designing the deposition times, which keep the pure Ni3Al phase stable. In addition, the surface morphologies indicate that the coating is compact without obvious voids or cracks. Furthermore, the oxidation-resistant property of the coating was investigated by carrying out a supercritical water oxidation experiment. The crystalline structure and surface morphology of the samples before and after 72-h oxidation demonstrated the superior oxidation resistance of the coating. This work provides a convenient method to fabricate an oxidation-resistant coating on a nickel-based alloy, which would be significant for prolonging the service life of vessels under oxidation conditions, especially for supercritical water reactions.

Objectives: To characterize the microflora profile of supragingival biofilm in patients with and without full-crown prostheses. Methods: Plaque samples of full-crown prostheses and teeth in patients with porcelain-fused-to-metal crowns, all-ceramic crowns, and no prostheses were collected (three patients per group), using 16S rRNA high-throughput sequencing technology to conduct DNA sequencing on the samples and using Qiime, R, and PICRUSt2 software to perform bioinformatics analyses and functional analyses on sequencing data. Results: In total, 110,209 valid sequences were obtained in the experiment, corresponding to 11 phyla and 120 genera. The predominant species shared by the three groups were phyla Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria and genera Rothia, Porphyromonas, Prevotella, Streptococcus, Veillonella, Leptotrichia, Neisseria, Citrobacter, and Pseudomonas. The species-difference analysis showed that genus Hameophilus significantly increased after the patient wore the dental prosthesis. Compared with the no-prosthesis samples, the functional analysis showed that cell motility increased in the samples from full-crown prostheses, while replication and repair, and translation decreased. Conclusions: This study reveals the changes in the oral microbial community of patients with full-crown prostheses, which could provide insights regarding the safety of materials for long-term use in the oral cavity.

Microelectromechanical system (MEMS) pressure sensors have a wide range of applications based on the advantages of mature technology and easy integration. Among them, piezoresistive sensors have attracted great attention with the advantage of simple back-end processing circuits. However, less research has been reported on the performance of piezoresistive pressure sensors in dynamic environments, especially considering the vibrations and shocks frequently encountered during the application of the sensors. To address these issues, this paper proposes a design method for a MEMS piezoresistive pressure sensor, and the fabricated sensor is evaluated in a series of systematic dynamic environmental adaptability tests. After testing, the output sensitivity of the sensor chip was 9.21 mV∙bar−1, while the nonlinearity was 0.069% FSS. The sensor overreacts to rapidly changing pressure environments and can withstand acceleration shocks of up to 20× g. In addition, the sensor is capable of providing normal output over the vibration frequency range of 0–5000 Hz with a temperature coefficient sensitivity of −0.30% FSS °C−1 over the temperature range of 0–80 °C. Our proposed sensor can play a key role in applications with wide pressure ranges, high-frequency vibrations, and high acceleration shocks, as well as guide MEMS-based pressure sensors in high pressure ranges and complex environmental adaptability in their design.

The rapid development of public buildings has greatly increased the country’s energy consumption and carbon emissions. Excessive carbon emissions contribute to global warming. This paper aims to measure the carbon emissions in the operation of public buildings, and to identify the multiple influencing factors of carbon emissions in operational public buildings. First, the spatial and temporal variation characteristics of carbon emissions from public buildings in 30 provinces of China from 2008–2019 are analyzed. Second, a green building index is constructed, and the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model is utilized to explore the relationship between each influencing factor and carbon emissions, using spatial and temporal geographically weighted regression analysis. The results show that the effects of population, urbanization rate, GDP per capita, green building index, and industrial structure on carbon emissions from public buildings all show spatial correlation and differences. There are east-west differences in the operational carbon emissions of public buildings in China’s provinces. Cluster evolution shows a spatially increasing trend from west to east. To some extent, policymakers can develop appropriate policies for different provinces through the findings.

Tongue diagnosis is an important part of the diagnostic process in traditional Chinese medicine (TCM). It primarily relies on the expertise and experience of TCM practitioners in identifying tongue features, which are subjective and unstable. We proposed a tongue feature classification framework based on convolutional neural networks to reduce the differences in diagnoses among TCM practitioners. Initially, we used our self-designed instrument to capture 482 tongue photos and created 11 data sets based on different features. Then, the tongue segmentation task was completed using an upgraded facial landmark detection method and UNET. Finally, we used ResNet34 as the backbone to extract features from the tongue photos and classify them. Experimental results show that our framework has excellent results with an overall accuracy of over 86 percent and is particularly sensitive to the corresponding feature regions, and thus it could assist TCM practitioners in making more accurate diagnoses.

The Ising model describes a many-body interacting spin (or particle) system, which can be utilized to imitate the fundamental forces of nature. Although it is the simplest many-body interacting system of spins (or particles) with Z2 symmetry, the phenomena revealed in Ising systems may afford us lessons for other types of interactions in nature. In this work, we first focus on the mathematical structure of the three-dimensional (3D) Ising model. In the Clifford algebraic representation, many internal factors exist in the transfer matrices of the 3D Ising model, which are ascribed to the topology of the 3D space and the many-body interactions of spins. They result in the nonlocality, the nontrivial topological structure, as well as the long-range entanglement between spins in the 3D Ising model. We review briefly the exact solution of the ferromagnetic 3D Ising model at the zero magnetic field, which was derived in our previous work. Then, the framework of topological quantum statistical mechanics is established, with respect to the mathematical aspects (topology, algebra, and geometry) and physical features (the contribution of topology to physics, Jordan–von Neumann–Wigner framework, time average, ensemble average, and quantum mechanical average). This is accomplished by generalizations of our findings and observations in the 3D Ising models. Finally, the results are generalized to topological quantum field theories, in consideration of relationships between quantum statistical mechanics and quantum field theories. It is found that these theories must be set up within the Jordan–von Neumann–Wigner framework, and the ergodic hypothesis is violated at the finite temperature. It is necessary to account the time average of the ensemble average and the quantum mechanical average in the topological quantum statistical mechanics and to introduce the parameter space of complex time (and complex temperature) in the topological quantum field theories. We find that a topological phase transition occurs near the infinite temperature (or the zero temperature) in models in the topological quantum statistical mechanics and the topological quantum field theories, which visualizes a symmetrical breaking of time inverse symmetry.

High-performance medical acoustic sensors are essential in medical equipment and diagnosis. Commercially available medical acoustic sensors are capacitive and piezoelectric types. When they are used to detect heart sound signals, there is attenuation and distortion due to the sound transmission between different media. This paper proposes a new bionic acoustic sensor based on the fish ear structure. Through theoretical analysis and finite element simulation, the optimal parameters of the sensitive structure are determined. The sensor is fabricated using microelectromechanical systems (MEMS) technology, and is encapsulated in castor oil, which has an acoustic impedance close to the human body. An electroacoustic test platform is built to test the performance of the sensor. The results showed that the MEMS bionic sensor operated with a bandwidth of 20–2k Hz. Its linearity and frequency responses were better than the electret microphone. In addition, the sensor was tested for heart sound collection application to verify its effectiveness. The proposed sensor can be effectively used in clinical auscultation and has a high SNR.

A method of the Riemann–Hilbert problem is employed for Zhang’s conjecture 2 proposed in Philo. Mag. 87 (2007) 5309 for a ferromagnetic three-dimensional (3D) Ising model in a zero external magnetic field. In this work, we first prove that the 3D Ising model in the zero external magnetic field can be mapped to either a (3 + 1)-dimensional ((3 + 1)D) Ising spin lattice or a trivialized topological structure in the (3 + 1)D or four-dimensional (4D) space (Theorem 1). Following the procedures of realizing the representation of knots on the Riemann surface and formulating the Riemann–Hilbert problem in our preceding paper [O. Suzuki and Z.D. Zhang, Mathematics 9 (2021) 776], we introduce vertex operators of knot types and a flat vector bundle for the ferromagnetic 3D Ising model (Theorems 2 and 3). By applying the monoidal transforms to trivialize the knots/links in a 4D Riemann manifold and obtain new trivial knots, we proceed to renormalize the ferromagnetic 3D Ising model in the zero external magnetic field by use of the derivation of Gauss–Bonnet–Chern formula (Theorem 4). The ferromagnetic 3D Ising model with nontrivial topological structures can be realized as a trivial model on a nontrivial topological manifold. The topological phases generalized on wavevectors are determined by the Gauss–Bonnet–Chern formula, in consideration of the mathematical structure of the 3D Ising model. Hence we prove the Zhang’s conjecture 2 (main theorem). Finally, we utilize the ferromagnetic 3D Ising model as a platform for describing a sensible interplay between the physical properties of many-body interacting systems, algebra, topology, and geometry.

Foot-and-mouth disease (FMD) is characterized by a pronounced lymphopenia that is associated with immune suppression. However, the mechanisms leading to lymphopenia remain unclear. In this study, the number of total CD4+, CD8+ T cells, B cells, and NK cells in the peripheral blood were dramatically reduced in C57BL/6 mice infected with foot-and-mouth disease virus (FMDV) serotype O, and it was noted that mice with severe clinical symptoms had expressively lower lymphocyte counts than mice with mild or without clinical symptoms, indicating that lymphopenia was associated with disease severity. A further analysis revealed that lymphocyte apoptosis and trafficking occurred after FMDV infection. In addition, coinhibitory molecules were upregulated in the expression of CD4+ and CD8+ T cells from FMDV-infected mice, including CTLA-4, LAG-3, 2B4, and TIGIT. Interestingly, the elevated IL-10 in the serum was correlated with the appearance of lymphopenia during FMDV infection but not IL-6, IL-2, IL-17, IL-18, IL-1β, TNF-α, IFN-α/β, TGF-β, and CXCL1. Knocking out IL-10 (IL-10-/-) mice or blocking IL-10/IL-10R signaling in vivo was able to prevent lymphopenia via downregulating apoptosis, trafficking, and the coinhibitory expression of lymphocytes in the peripheral blood, which contribute to enhance the survival of mice infected with FMDV. Our findings support that blocking IL-10/IL-10R signaling may represent a novel therapeutic approach for FMD.

Viral infections can give rise to a systemic decrease in the total number of lymphocytes in the blood, referred to as lymphopenia. Lymphopenia may affect the host adaptive immune responses and impact the clinical course of acute viral infections. Detailed knowledge on how viruses induce lymphopenia would provide valuable information into the pathogenesis of viral infections and potential therapeutic targeting. In this review, the current progress of viruses-induced lymphopenia is summarized and the potential mechanisms and factors involved are discussed.

The Medieval Wall System of China and Mongolia is one of the longest wall systems in the world, but its specific chronology, function, and purpose remain ambiguous. Constructed at various points throughout the 10th to 13th centuries CE, this network of walls, forts, and enclosures covers an estimated 4000 km and spans a wide range of ecozones, from the deserts of western China to the steppes of northern Mongolia and the Khingan mountain range. In this article we used historical atlases, topographic maps, and an array of different kinds of data derived from satellite remote sensing, to produce one of the first accurate maps of the Medieval Wall System. Through this large-scale mapping program, we are now able to evaluate previous work that estimates the length of the wall system and different areas of construction. By measuring the structures associated with the wall and the length of the wall itself, we identified at least three different areas of construction along the Medieval Wall System. Future studies may be able to use similar tools to develop more accurate maps of other wall systems throughout Eurasia to further advance the comparative study of ancient wall systems.

In this study, the magnetic properties, coercivity mechanism, and magnetization reversal process were investigated for Ce-(Y)-Pr-Fe-B films. After the addition of Y and subsequent heating treatment, the formations of REO (RE ≡ Ce and Pr) and REFe2 (RE ≡ rare earths) phases are inhibited, and the microstructure of Ce-Y-Pr-Fe-B film is optimized. Meanwhile, the coercivity and the squareness of the hysteresis loop are significantly improved. The coercivity mechanism of Ce-Y-Pr-Fe-B film is determined to be a mixture of nucleation and pinning mechanisms, but dominated by the nucleation mechanism. The demagnetization results show that the nucleation of reversal magnetic domains leads to irreversible reversal. Our results are helpful to understand the coercivity mechanism and magnetization reversal of permanent magnetic films with multi-main phases.

In recent years, the preparation of flexible thermoelectric generators by screen printing has attracted wide attention due to easy processing and high-volume production. In this work, we propose an n-type Ag2Se/polymer polyvinylpyrrolidone (PVP) film based on screen printing and investigate the effect of PVP on thermoelectric performance by varying the ratio of PVP. When the content ratio of Ag2Se to PVP is 30:1, i.e., PI30, the fabricated PI30 film has the best thermoelectric property. The maximum power factor (PF) of the PI30 is 4.3 μW·m−1·K−2, and conductivity reaches 81% of its initial value at 1500 bending cycles. Then, the film thermoelectric generator (F-TEG) fabricated by PI30 is tested for practical application; the output voltage and the maximum output power are 21.6 mV and 233.3 nW at the temperature difference of 40 K, respectively. This work demonstrates that the use of PVP combined with screen printing to prepare F-TEG is a simple and rapid method, which provides an efficient preparation solution for the development of environmentally friendly and wearable flexible thermoelectric devices.

A method of the Riemann–Hilbert problem is applied for Zhang’s conjecture 1 proposed in Philo. Mag. 87 (2007) 5309 for a ferromagnetic three-dimensional (3D) Ising model in the zero external field and the solution to the Zhang’s conjecture 1 is constructed by use of the monoidal transform. At first, the knot structure of the ferromagnetic 3D Ising model in the zero external field is determined and the non-local behavior of the ferromagnetic 3D Ising model can be described by the non-trivial knot structure. A representation from the knot space to the Clifford algebra of exponential type is constructed, and the partition function of the ferromagnetic 3D Ising model in the zero external field can be obtained by this representation (Theorem I). After a realization of the knots on a Riemann surface of hyperelliptic type, the monodromy representation is realized from the representation. The Riemann–Hilbert problem is formulated and the solution is obtained (Theorem II). Finally, the monoidal transformation is introduced for the solution and the trivialization of the representation is constructed (Theorem III). By this, we can obtain the desired solution to the Zhang’s conjecture 1 (Main Theorem). The present work not only proves the Zhang’s conjecture 1, but also shows that the 3D Ising model is a good platform for studying in deep the mathematical structure of a physical many-body interacting spin system and the connections between algebra, topology, and geometry.

α″-Fe16N2 nanomaterials with a shape anisotropy for high coercivity performance are of interest in potential applications such as rare-earth-free permanent magnets, which are difficult to synthesize in situ anisotropic growth. Here, we develop a new and facile one-pot microemulsion method with Fe(CO)5 as the iron source and tetraethylenepentamine (TEPA) as the N/C source at low synthesis temperatures to fabricate carbon-coated tetragonal α″-Fe16N2 nanocones. Magnetocrystalline anisotropy energy is suggested as the driving force for the anisotropic growth of α″-Fe16N2@C nanocones because the easy magnetization direction of tetragonal α″-Fe16N2 nanocrystals is along the c axis. The α″-Fe16N2@C nanocones agglomerate to form a fan-like microstructure, in which the thin ends of nanocones direct to its center, due to the magnetostatic energy. The lengths of α″-Fe16N2@C nanocones are ~200 nm and the diameters vary from ~10 nm on one end to ~40 nm on the other end. Carbon shells with a thickness of 2–3 nm protect α″-Fe16N2 nanocones from oxidation in air atmosphere. The α″-Fe16N2@C nanocones synthesized at 433 K show a room-temperature saturation magnetization of 82.6 emu/g and a coercive force of 320 Oe.

Since black silicon was discovered by coincidence, the special material was explored for many amazing material characteristics in optical, surface topography, and so on. Because of the material property, black silicon is applied in many spheres of a photodetector, photovoltaic cell, photo-electrocatalysis, antibacterial surfaces, and sensors. With the development of fabrication technology, black silicon has expanded in more and more applications and has become a research hotspot. Herein, this review systematically summarizes the fabricating method of black silicon, including nanosecond or femtosecond laser irradiation, metal-assisted chemical etching (MACE), reactive ion etching (RIE), wet chemical etching, electrochemical method, and plasma immersion ion implantation (PIII) methods. In addition, this review focuses on the progress in multiple black silicon applications in the past 10 years. Finally, the prospect of black silicon fabricating and various applications are outlined.

The dynamics of a disclination loop (s = ±1/2) in nematic liquid crystals constrained between two coaxial cylinders were investigated based on two-dimensional Landau–de Gennes tensorial formalism by using a finite-difference iterative method. The effect of thickness (d = R2 − R1, where R1 and R2 represent the internal and external radii of the cylindrical cavity, respectively) on the director distribution of the defect was simulated using different R1 values. The results show that the order reconstruction occurs at a critical value of dc, which decreases with increasing inner ratio R1. The loop also shrinks, and the defect center deviates from the middle of the system, which is a non-planar structure. The deviation decreases with decreasing d or increasing R1, implying that the system tends to be a planar cell. Two models were then established to analyze the combined effect of non-planar geometry and electric field. The common action of these parameters facilitates order reconstruction, whereas their opposite action complicates the process.

Peste des petits ruminants (PPR) is one of the highly contagious transboundary viral diseases of small ruminants. Host microRNA (miRNA) expression patterns may change in response to virus infection, and it mainly works as a post-transcriptional moderator in gene expression and affects viral pathogenesis and replication. In this study, the change of miRNA expression profile in peripheral blood lymphocyte (PBMC) from sheep inoculated with PPR vaccine virus in vivo as well as primary sheep testicular (ST) cells inoculated with PPR vaccine virus in vitro were determined via deep sequencing technology. In PBMC cells, 373 and 115 differentially expressed miRNAs (DEmiRNAs) were identified 3 days and 5 days post inoculated (dpi), respectively. While, 575 DEmiRNAs were identified when comparing miRNA profiles on 5 dpi with 3 dpi. Some of the DEmiRNAs were found to change significantly via time-course during PPR vaccine virus inoculated. Similarly, in ST cells, 136 DEmiRNAs were identified at 3 dpi in comparison with mock-inoculation. A total of 12 DEmiRNAs were validated by real-time quantitative PCR (RT-qPCR). The oar-miR-150, oar-miR-370-3p and oar-miR-411b-3p were found common differentially expressed in both PPR vaccine virus-inoculated PBMC cells and ST cells. Targets prediction and functional analysis of the DEmiRNAs uncovered mainly gathering in antigen processing and presentation pathways, protein processing in endoplasmic reticulum pathways and cell adhesion molecules pathways. Our study supplies information about the DEmiRNAs in PPR vaccine virus-inoculated PBMC cells and ST cells, and provides clues for further understanding the function of miRNAs in PPR vaccine virus replication.

Peste des Petits Ruminant (PPR) is an important transboundary, OIE-listed contagious viral disease of primarily sheep and goats caused by the PPR virus (PPRV), which belongs to the genus Morbillivirus of the family Paramyxoviridae. The mortality rate is 90−100%, and the morbidity rate may reach up to 100%. PPR is considered economically important as it decreases the production and productivity of livestock. In many endemic poor countries, it has remained an obstacle to the development of sustainable agriculture. Hence, proper control measures have become a necessity to prevent its rapid spread across the world. For this, detailed information on the pathogenesis of the virus and the virus host interaction through cellular receptors needs to be understood clearly. Presently, two cellular receptors; signaling lymphocyte activation molecule (SLAM) and Nectin-4 are known for PPRV. However, extensive information on virus interactions with these receptors and their impact on host immune response is still required. Hence, a thorough understanding of PPRV receptors and the mechanism involved in the induction of immunosuppression is crucial for controlling PPR. In this review, we discuss PPRV cellular receptors, viral host interaction with cellular receptors, and immunosuppression induced by the virus with reference to other Morbilliviruses.

The mechanism by which the foot-and-mouth disease virus (FMDV) initiates infection of cells is thought to involve the attachment of the viral capsid to host integrins on the surface of target cells. However, the role of integrins in FMDV infection still needs to be fully understood, although it has been demonstrated that integrin αvβ6 interferes with FMDV in vitro and results in neutralization of its infectivity. In the present study, we describe the cloning and sequencing of suckling mouse integrin β6 and the subsequent expression of two segments of integrin β6 extracellular domains: β6-1 (which contains the ligand-binding domain) and β6-2. Sequencing of the mouse integrin β6 subunit revealed close homology (~90%) with its human counterpart. When recombinant integrin extracellular domains β6-1 and β6-2 formulated with adjuvant were inoculated into guinea pigs, anti-integrin antibody expression was high before FMDV challenge. Interestingly, guinea pigs (50%) inoculated with integrin β6-1 were protected from FMDV infection; in contrast, none of the animals inoculated with integrin β6-2 were protected. This result indicates that an integrin blockade may be able to interfere with FMDV infection in vivo, which raises the possibility that targeting integrin in vivo may be the basis for a new strategy to control FMDV infection.

The high hazard mechanical system (HHMS) has three characteristics in the petroleum and petrochemical industry (PPI): high risk, high cost, and high technology requirements. For a HHMS, part, component, and subsystem failures will result in varying degrees and various types of risk consequences, including unexpected downtime, production losses, economic costs, safety accidents, and environmental pollution. Thus, obtaining the quantitative risk level and distribution in a HHMS to control major risk accidents and ensure safe production is of vital importance. However, the structure of the HHMS is more complex than some other systems, making the quantitative risk analysis process more difficult. Additionally, a variety of uncertain risk data hinder the realization of quantitative risk analysis. A few quantitative risk analysis techniques and studies for HHMS exist, especially in the PPI. Therefore, a study on the quantitative risk analysis method for HHMS was completed to obtain the risk level and distribution of high-risk objects. Firstly, Fuzzy Set Theory (FST) was applied to address the uncertain risk data for the occurrence probability (OP) and consequence severity (CS) in the risk analysis process. Secondly, a fuzzy fault tree analysis (FFTA) and a fuzzy event tree analysis (FETA) were used to achieve quantitative risk analysis and calculation. Thirdly, a fuzzy bow-tie model (FBTM) was established to obtain a quantitative risk assessment result according to the analysis results of the FFTA and FETA. Finally, the feasibility and practicability of the method were verified with a case study on the quantitative risk analysis of one reciprocating pump system (RPS). The quantitative risk analysis method for HHMS can provide more accurate and scientific data support for the development of Asset Integrity Management (AIM) systems in the PPI.

A plasmonic waveguide coupled system that uses a metal-insulator-metal (MIM) waveguide with two silver baffles and a coupled ring cavity is proposed in this study. The transmission properties of the plasmonic system were investigated using the finite element method. The simulation results show a Fano profile in the transmission spectrum, which was caused by the interaction of the broadband resonance of the Fabry-Perot (F-P) cavity and the narrow band resonance of the ring cavity. The Fabry-Perot (F-P) cavity in this case was formed by two silver baffles dividing the MIM waveguide. The maximum sensitivity of 718 nm/RIU and the maximum figure of merit of 4354 were achieved. Furthermore, the effects of the structural parameters of the F-P cavity and the ring cavity on the transmission properties of the plasmonic system were analyzed. The results can provide a guide for designing highly sensitive on-chip sensors based on surface plasmon polaritons.

A surface plasmon polariton refractive index sensor based on Fano resonances in metal–insulator–metal (MIM) waveguides coupled with rectangular and ring resonators is proposed and numerically investigated using a finite element method. Fano resonances are observed in the transmission spectra, which result from the coupling between the narrow-band spectral response in the ring resonator and the broadband spectral response in the rectangular resonator. Results are analyzed using coupled-mode theory based on transmission line theory. The coupled mode theory is employed to explain the Fano resonance effect, and the analytical result is in good agreement with the simulation result. The results show that with an increase in the refractive index of the fill dielectric material in the slot of the system, the Fano resonance peak exhibits a remarkable red shift, and the highest value of sensitivity (S) is 1125 nm/RIU, RIU means refractive index unit. Furthermore, the coupled MIM waveguide structure can be integrated with other photonic devices at the chip scale. The results can provide a guide for future applications of this structure.

A intensity-modulated optical fiber relative humidity (RH) sensor based on the side coupling induction technology (SCIT) is presented and experimentally demonstrated. The agarose gel and the twisted macro-bend coupling structure are first combined for RH sensing applications. The refractive index (RI) of the agarose gel increases with the increase of the RH and is in linear proportion from 20 to 80%RH. The side coupling power, which changes directly with the RI of the agarose gel, can strip the source noise from the sensor signal and improve the signal to noise ratio substantially. The experiment results show that the sensitivity of the proposed sensor increases while the bend radius decreases. When the bend radius is 8 mm, the sensor has a linear response from 40% to 80% RH with the sensitivity of 4.23 nW/% and the limit of detection of 0.70%. A higher sensitivity of 12.49 nW/% is achieved when RH raises from 80% to 90% and the limit of detection decreases to 0.55%. Furthermore, the proposed sensor is a low-cost solution, offering advantages of good reversibility, fast response time, and compensable temperature dependence.