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Highly pathogenic avian influenza virus (HPAIV) A H5 clade 2.3.4.4 has caused worldwide outbreaks in domestic poultry, occasional spillover to humans, and increasing deaths of diverse species of wild birds since 2014. Wild bird migration is currently acknowledged as an important ecological process contributing to the global dispersal of HPAIV H5. However, it is unclearhow seasonal bird migration facilitates global virus dispersal, andwhich avian species are exposed to HPAI H5 clade 2.3.4.4 viruses and where. To shed light on ongoing global outbreaks, we sought to explore these questions through phylodynamic analyses based on empirical data of bird movement tracking and virus genome sequences. First, based on viral phylogeography and bird migration networks, we demonstrate that seasonal bird migration can explain salient features of the global dispersal of clade 2.3.4.4. Second, we detect synchrony between the seasonality of bird annual cycle phases and virus lineage movements. We reveal the differing vulnerable bird orders at geographical origins and destinations of HPAIV H5 lineage movements. Notably, we highlight the potential importance of relatively under-discussed Suliformes and Ciconiiformes, in addition to Anseriformes and Charadriiformes, in virus lineage movements. Our study provides a phylodynamic framework that links the bird movement ecology and genomic epidemiology of avian influenza; it highlights the importance of integrating bird behaviour and life history in avian influenza studies.

Halting the global decline of migratory birds requires a better understanding of migration ecology. Stopover sites are a crucial yet understudied aspect of bird conservation, mostly due to challenges associated with understanding broad-scale patterns of transient habitat use. Here, we use a national network of weather radar stations to identify stopover hotspots and assess multiscale habitat associations of migratory landbirds across the eastern United States during autumn migration. We mapped seasonal bird densities over 5 y (2015 to 2019) from 60 radar stations covering 63.2 million hectares. At a coarse scale, we found that landbirds migrate across a broad front with small differences in migrant density between radar domains. However, relatively more birds concentrate along the Mississippi River and Appalachian Mountains. At a finer scale, we identified radar pixels that consistently harbored high densities of migrants for all 5 y, which we classify as stopover hotspots. Hotspot probability increased with percent cover of all forest types and decreased with percent cover of pasture and cultivated crops. Moreover, we found strong concentrating effects of deciduous forest patches within deforested regions. We also found that the prairie biome in the Midwest (now mostly cropland) is likely a migration barrier, with large concentrations of migrants at the prairie–forest boundary after crossing the agricultural Midwest. Overall, the broad-front migration pattern highlights the importance of locally based conservation efforts to protect stopover habitats. Such efforts should target forests, especially deciduous forests in highly altered landscapes. These findings demonstrate the value of multiscale habitat assessments for the conservation of migratory landbirds.

Pantograph-catenary system is a key component of high-speed railway. Under high speed and strong current operation conditions, the surface roughness of the sliding electrical contact between contact wire and slide changes continuously. It will cause the fluctuation of contact resistance and lower the electrical contact property of the system. Therefore, it is of great significance to study the relationships between the contact resistance and surface roughness characteristics. In this paper, lots of current-carrying friction experiments were carried out under different contact pressure, contact current and sliding speed conditions. A roughness tester was used to measure the roughness of the contact surface after experiment. Four characteristic parameters were proposed to describe the roughness. They are the root mean square and the maximum peak height of the rough surface, the peak count and the curvature radius of asperity respectively. The function relationships between these characteristic parameters and experimental conditions were obtained and discussed. On the basis of Greenwood-Williamson contact model, a new mathematical model of contact resistance in pantograph-catenary system considering rough surface characteristics were established and verified. It can be used to further study the current conduction mechanism of sliding electrical contact in pantograph-catenary system and evaluate the electrical contact performance.

Igniting interface magnetic ordering of magnetic topological insulators by building a van der Waals heterostructure can help to reveal novel quantum states and design functional devices. Here, we observe an interesting exchange bias effect, indicating successful interfacial magnetic coupling, in CrI

Igniting interface magnetic ordering of magnetic topological insulators by building a van der Waals heterostructure can help to reveal novel quantum states and design functional devices. Here, we observe an interesting exchange bias effect, indicating successful interfacial magnetic coupling, in CrI3/MnBi2Te4 ferromagnetic insulator/antiferromagnetic topological insulator (FMI/AFM-TI) heterostructure devices. The devices originally exhibit a negative exchange bias field, which decays with increasing temperature and is unaffected by the back-gate voltage. When we change the device configuration to be half-covered by CrI3, the exchange bias becomes positive with a very large exchange bias field exceeding 300 mT. Such sensitive manipulation is explained by the competition between the FM and AFM coupling at the interface of CrI3 and MnBi2Te4, pointing to coverage-dependent interfacial magnetic interactions. Our work will facilitate the development of topological and antiferromagnetic devices.

Series arc fault is a common phenomenon in the power system, it will directly affect the working reliability, but there is no mature method to detect it due to its concealment and chaos. Common detection methods that build on the arc fault eigenvectors obtained by manual analysis are subjective and incomprehensive. A series arc fault diagnosis and line selection method based on recurrent neural network (RNN) for a multi-load system was proposed in this paper. Firstly, a series arc fault experiment under a multi-load system was carried out, the training set and test set were built by using the data obtained from the experiment. Then, the RNN model was built, trained, and tested through the training set and test set. Finally, the fast-continuous detection method and the probability-based classification result correction method were proposed, and the detection speed and accuracy were improved much further. The results show that the proposed method is effective for diagnosing series arc fault and line selection under a multi-load system, without analysis of arc fault characteristics.

In order to analyze the making arc characteristics of AgSnO2 contact, experiments were carried out with a self-developed experimental equipment. It was found that contact resistance had no obvious change with the increase of the number of experiments.In the later stage of the experiment, the contact bounces occurred during the contact closing process, which not only prolonged the making arc duration, but also increased making arc energy. When the contact was eroded to a certain extent by arc, making welding occurs.

In order to study a kind of detection and line selection method of arc fault in actual power supply and distribution lines, arc fault experiments with multi-load loop were carried out. First, five-layer decomposition of main loop current was made by using wavelet packet. The effective coefficients were selected based on the change rate of a wavelet packet energy entropy before and after the arc fault occurs. Then, an effective signal of the arc fault was reconstructed. Second, the effective signal was decomposed into seven independent modes with a variational mode decomposition method. Its time–frequency distribution was obtained by solving the Wigner–Ville distribution and performing a linear summation of each mode. Third, the time-domain and time–frequency features of arc fault were extracted by analyzing the time-domain waveform and time–frequency distribution of the effective signal. An arc fault identification and line-selection model was established by using a support vector machine optimized by particle swarm optimization and grid search. Then, the accuracy of both arc fault detection and line selection were tested. Test results indicated that the proposed method can detect effectively arc fault and select fault line accurately.

Background: Ovarian Sertoli-Leydig cell tumor (SLCT) is an extremely rare sex–cord stromal tumor of the ovary. Notably, ovarian SLCT with mucinous epithelium and liposarcoma is even rarer.There is also evidence that the presence of heterologous elements is a poor prognostic factor of SLCTs. Very often, ovarian SLCT patient first presents with high androgen levels and sometimes a clarge mass in the pelvic cavity, making it difficult for early diagnosis. Case presentation: In this study, we reported a SLCT patient with heterologous elements and elevated the serum alpha-fetoprotein (AFP) levels. A 22-year old nulliparous female was first admitted with clinical symptoms of abdominal pain, a large mass in the pelvic cavity and elevated serum AFP levels, and for this she underwent left adnexectomy. Pathological examination revealed ovarian SLCT with intestinal type mucinous epithelium and liposarcoma, and immunohistochemical staining revealed positive staining for AFP in the intestinal type mucinous epithelium. The patient became pregnant naturally four years later, but SLCT was found in the opposite ovary with liposarcoma but no significant increase in serum AFP levels.Further, we reviewed the literature in order to improve preoperative diagnosis and evaluation of long-term prognosis of SLCTs with heterologous elements.Conclusion: The increase in serum AFP levels could be used for preoperative diagnosis of the presence of heterologous elements and the postoperative recurrence.

Global conservation promotes solutions to different dimensions of threat and response: land-use change, climate change, pollution, and so forth. Countering each threat has its band of proponents who advocate for their cause as paramount, increasingly, given limited resources, by downplaying the relative importance of others. Not only does this encourage a compartmentalised view of the world, which is ecologically unsound, it allows politicians and others to cherry-pick responses in light of political expediency or local demands. We should instead aim to achieve win-win conservation strategies that address multiple threats to diversity acting at different timescales, as well as 'horizon threats', which occur at large scales and may be the most challenging conservation issues to address in both the present and the future.

In this paper, a nonlinear partial-state feedback control is designed for a 3-DOF pantograph–catenary system by using backstepping approach, such that the contacting force of the closed-loop system is capable of tracking its reference profile. In the control design, the pantograph–catenary model is transformed into a triangular form, facilitating the utilization of backstepping. Derivatives of virtual controls in backstepping are calculated explicitly. A high-order differentiator is designed to estimate the unknown time derivatives of elasticity coefficient; and an observer is proposed to reconstruct the unmeasurable states. It can be proved theoretically that, with the proposed nonlinear partial-state feedback control, the tracking error of the contacting force is ultimately bounded with tunable ultimate bounds. Theoretical results are demonstrated by numerical simulations.

Background To investigate the therapeutic effects of menstrual blood derived mesenchymal stem cells (MB-MSCs) combined with Bushen Tiaochong recipe (BSTCR) on epirubicin induced premature ovarian failure (POF) in mice. Methods Twenty-four female C57BL/6 mice of 6–8 weeks were intraperitoneally injected with epirubicin to induce POF, and then they were randomized into 4 groups of 6 mice each and treated with PBS, MB-MSCs, BSTCR, and MB-MSCs combined with BSTCR, respectively. Six mice of the same age were used as controls. Vaginal smear, TUNEL and hematoxylin-eosin staining were to observe estrous cycles, ovarian cell apoptosis and follicles. Enzyme-linked immunosorbent analysis determined serum estradiol, follicle-stimulating hormone (FSH) and anti-Müllerian hormone (AMH) levels. RT-qPCR and Western Blot analysis were to determine GADD45b, CyclinB1, CDC2 and pCDC2 expressions. Results Epirubicin treatment resulted in a decrease in the number of primordial, primary, secondary and antral follicles, an increase in the number of atretic follicles and ovarian cell apoptosis, a decrease in estradiol and AMH levels, an increase in FSH levels, and estrous cycle arrest. However, MB-MSCs combined with BSTCR rescued epirubicin induced POF through down-regulating GADD45b and pCDC2 expressions, and up-regulating CyclinB1 and CDC2 expressions. The combined treatment showed better therapeutic efficacy than BSTCR or MB-MSCs alone. Conclusions MB-MSCs combined with BSTCR improved the ovarian function of epirubicin induced POF mice, which might be related to the inhibition of GADD45b expression and the promotion of CyclinB1 and CDC2 expressions. The combined treatment had better therapeutic efficacy than BSTCR or MB-MSCs alone.

The increasing presence of microplastics in marine environment is a critical issue and the plastic-metal contamination has received much attention. However, conventional methods for heavy metal determination are time-consuming, need sample pretreatments, require a strict operation environment, or have high limits of detection. In this study, heavy metals contaminated microplastics samples collected from a remote coral island were quantified and analyzed by using Laser-Induced Breakdown Spectroscopy (LIBS). The characters of the trace metals in microplastics were used to determine the sources of the contaminants, and the potential origins of the metals were demonstrated from the statistical analysis. LIBS is a facile and non-destructive trace analysis technique and the strategy led to rapid and multi-metals detection of individual samples. Heavy metals such as copper (Cu), lead (Pb), iron (Fe), cadmium (Cd), zinc (Zn), manganese (Mn), chromium (Cr) were detected and quantified in the individual microplastics samples. The findings showed that LIBS is a promising strategy for the characterization of microplastics and for the analysis of the source of heavy metals contaminants present in the microplastics particles.

Current-carrying sliding friction pair is the key part of many systems such as high-speed railway’s pantograph-catenary system, electromagnetic gun’s launch system, and space satellite’s solar panel system. Arc discharge phenomenon will occur due to sliding electrical contact fault. It will radiate high-intensity electromagnetic noise. The electromagnetic radiation noise (EMRN) will disturb communication system, even cause failure of the whole system. EMRN experiments under single arc conditions were carried out with the self-developed experimental system in anechoic chamber environment. The time domain characteristics of EMRN were analyzed under different measure distance and contact current conditions. The time domain waveform of EMRN is symmetrical and convergent. Its continuous time is shorter than 0.8 $\mu \text{s}$ . A mathematical model of the time domain waveform was established by using the least-square method. The performance of the model was evaluated by using determination coefficient, residual standard deviation, and correlation coefficient. The time domain waveform obtained from the model is almost the same as the waveform measured from experiments.

Background To explore the effect of mesenchymal stem cells isolated from menstrual blood (MB-MSCs) on epirubicin-induced damage to human ovarian granulosa cells (GCs) and its potential mechanisms. Methods The estradiol, progesterone, anti-Müllerian hormone, inhibin A, and inhibin B levels were determined using enzyme-linked immunosorbent assay. The proliferation of GCs was detected by Cell Counting Kit-8 assays. The cell cycle distribution was detected by propidiumiodide single staining. The apoptosis of GCs was determined using Annexin V and 7-AAD double staining. The differentially expressed genes of GCs were analyzed with Affymetrix Human Transcriptome Array 2.0 gene chip and verified with Western blot analysis. Results Epirubicin inhibited the secretion of estradiol, progesterone, anti-Müllerian hormone, inhibin A, and inhibin B and the proliferation of GCs; arrested these GCs in G2/M phase; and promoted the apoptosis of GCs. However, MB-MSCs repaired epirubicin-induced damage to GCs. Differentially expressed genes of GCs, Gadd45b, CyclinB1, and CDC2, were found by microarray and bioinformatics analysis. Western blot showed that epirubicin upregulated Gadd45b protein expression and downregulated CyclinB1 and CDC2 protein expression, while MB-MSCs downregulated Gadd45b protein expression and upregulated CyclinB1 and CDC2 protein expression. Conclusions MB-MSCs repaired epirubicin-induced damage to GCs, which might be related to the inhibition of Gadd45b protein expression.

In high speed current sliding electrical contact, the friction force between the contact surfaces directly reflects the reliability of electrical contact. Based on the experimental data analysis of the sliding electric contact machine, a kind of rules model of the sliding electrical contact friction force under fluctuating load is established using method of data mining. Firstly, some different running conditions are taken to simulate the actual operating environment. So the numerical value of influencing factors is changed in the experiment, such as sliding speed, current intensity, frequency and amplitude of fluctuating load. And all of these are the antecedent of the rules model, while the friction force data obtained from the experiment are taken as consequent of rules. Then the rules are established, which shows the mapping relationship from antecedent terms to consequent term. Also the rule quality function is given, with which the rules is pruned by the optimization algorithm. At last, the high quality friction rules model is mined, and also the results of the rules’ model are analyzed.

Due to the power quality problems and the use of some nonlinear loads such as soft starters, rectifiers, and frequency converters, the circuit current will contain complicated harmonic components, which may affect the identification accuracy of arc fault. Aiming at the interferences of power supply harmonics and nonlinear load noise, a kind of recognition method based on kernel principal component analysis (KPCA) and firefly algorithm optimized support vector machine (FA-SVM) was proposed. KPCA was used to separate the harmonics and load noise interferences in the voltage and current signals. Kurtosis and skewness of the fifth and sixth principal components were used as arc fault features. The FA-SVM was designed to recognize arc fault. The arc fault experiments were carried out under complicated harmonic conditions. The effectiveness of the presented method was verified by experiments.