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The impact of the self-sealing band on interior ballistics is investigated during the gun launching, and a high-precision interior ballistics coupling algorithm that takes leakage into account is proposed. This study focuses on a 65 mm short-barrel, equal-caliber balanced cannon, integrating Abaqus finite element software with an interior ballistics calculation programme. It uses a User-defined AMPlication Load (VUAMP) subroutine to achieve real-time coupling calculations of the chamber pressure and self-sealing band deformation, correcting variations in the chamber pressure. Experimental results show that the coupling algorithm offers the higher precision compared to traditional interior ballistics models and can effectively capture the impact of leakage on the interior ballistics performance. Further research reveals that changes in the charge amount and assembly gap significantly affect the sealing performance of the self-sealing band and the leakage of propellant gases, which in turn influence the chamber pressure and projectile velocity. The high-precision coupling algorithm proposed in this paper provides the effective theoretical support for the design of the self-sealing band and the analysis of cannon performance.
This study examined the variability of language profiles in Spanish–English bilingual children with and without developmental language disorder (DLD). The data included 529 children between the ages of 5 and 10 years. Eighty-eight of these children were identified as having DLD. A latent profile analysis was conducted based on children’s morphosyntax and semantics performance in Spanish and English. The optimal model identified five different profiles, illustrating the heterogeneity in bilingual development. Children with DLD were observed across all profiles, but most were classified in the only two profiles where lower morphosyntax than semantic performance was observed across languages. These results show the variability in both bilingual children with and without DLD. Additionally, the hallmark deficit of DLD in morphosyntax was confirmed, with the morphological weakness being observed in each of the bilingual children’s languages. Children’s background factors (age, maternal education and language exposure) were associated with profile characteristics.
Turbulent emulsions are ubiquitous in chemical engineering, food processing, pharmaceuticals and other fields. However, our experimental understanding of this area remains limited due to the multiscale nature of turbulent flow and the presence of extensive interfaces, which pose significant challenges to optical measurements. In this study, we address these challenges by precisely matching the refractive indices of the continuous and dispersed phases, enabling us to measure local velocity information at high volume fractions. The emulsion is generated in a turbulent Taylor–Couette flow, with velocity measured at two radial locations: near the inner cylinder (boundary layer) and in the middle gap (bulk region). Near the inner cylinder, the presence of droplets suppresses the emission of angular velocity plumes, which reduces the mean azimuthal velocity and its root mean squared fluctuation. The former effect leads to a higher angular velocity gradient in the boundary layer, resulting in greater global drag on the system. In the bulk region, although droplets suppress turbulence fluctuations, they enhance the cross-correlation between azimuthal and radial velocities, leaving the angular velocity flux contributed by the turbulent flow nearly unchanged. In both locations, droplets suppress turbulence at scales larger than the average droplet diameter and increase the intermittency of velocity increments. However, the effects of the droplets are more pronounced near the inner cylinder than in the bulk, likely because droplets fragment in the boundary layer but are less prone to break up in the bulk. Our study provides experimental insights into how dispersed droplets modulate global drag, coherent structures and the multiscale characteristics of turbulent flow.
The presence of dispersed-phase droplets can result in a notable increase in a system's drag. However, our understanding of the mechanism underlying this phenomenon remains limited. In this study, we use three-dimensional direct numerical simulations with a modified multi-marker volume-of-fluid method to investigate liquid–liquid two-phase turbulence in a Taylor–Couette geometry. The dispersed phase has the same density and viscosity as the continuous phase. The Reynolds number $Re\equiv r_i\omega _i d/\nu$ is fixed at 5200, the volume fraction of the dispersed phase is up to $40\,\%$, and the Weber number $We\equiv \rho u^2_\tau d/\sigma$ is approximately 8. It is found that the increase in the system's drag originates from the contribution of interfacial tension. Specifically, droplets experience significant deformation and stretching in the streamwise direction due to shear near the inner cylinder. Consequently, the rear end of the droplets lags behind the fore head. This causes opposing interfacial tension effects on the fore head and rear end of the droplets. For the fore head of the droplets, the effect of interfacial tension appears to act against the flow direction. For the rear end, the effect appears to act in the flow direction. The increase in the system's drag is attributed primarily to the effect of interfacial tension on the fore head of the droplets which leads to the hindering effect of the droplets on the surrounding continuous phase. This hindering effect disrupts the formation of high-speed streaks, favouring the formation of low-speed ones, which are generally associated with higher viscous stress and drag of the system. This study provides new insights into the mechanism of drag enhancement reported in our previous experiments.
The presence of a dispersed phase can significantly modulate the drag in turbulent systems. We derived a conserved quantity that characterizes the radial transport of azimuthal momentum in the fluid–fluid two-phase Taylor–Couette turbulence. This quantity consists of contributions from advection, diffusion and two-phase interface, which are closely related to density, viscosity and interfacial tension, respectively. We found from interface-resolved direct numerical simulations that the presence of the two-phase interface consistently produces a positive contribution to the momentum transport and leads to drag enhancement, while decreasing the density and viscosity ratios of the dispersed phase to the continuous phase reduces the contribution of local advection and diffusion terms to the momentum transport, respectively, resulting in drag reduction. Therefore, we concluded that the decreased density ratio and the decreased viscosity ratio work together to compete with the presence of a two-phase interface for achieving drag modulation in fluid–fluid two-phase turbulence.
Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.
Methods
A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.
Results
Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.
Conclusions
These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.
The wheat aphid Sitobion miscanthi (CWA) is an important harmful pest in wheat fields. Insecticide application is the main method to effectively control wheat aphids. However, CWA has developed resistance to some insecticides due to its extensive application, and understanding resistance mechanisms is crucial for the management of CWA. In our study, a new P450 gene, CYP4CJ6, was identified from CWA and showed a positive response to imidacloprid and thiamethoxam. Transcription of CYP4CJ6 was significantly induced by both imidacloprid and thiamethoxam, and overexpression of CYP4CJ6 in the imidacloprid-resistant strain was also observed. The sensitivity of CWA to these two insecticides was increased after the knockdown of CYP4CJ6. These results indicated that CYP4CJ6 could be associated with CWA resistance to imidacloprid and thiamethoxam. Subsequently, the posttranscriptional regulatory mechanism was assessed, and miR-316 was confirmed to participate in the posttranscriptional regulation of CYP4CJ6. These results are crucial for clarifying the roles of P450 in the resistance of CWA to insecticides.
Support vector machines (SVMs) based on brain-wise functional connectivity (FC) have been widely adopted for single-subject prediction of patients with schizophrenia, but most of them had small sample size. This study aimed to evaluate the performance of SVMs based on a large single-site dataset and investigate the effects of demographic homogeneity and training sample size on classification accuracy.
Methods
The resting functional Magnetic Resonance Imaging (fMRI) dataset comprised 220 patients with schizophrenia and 220 healthy controls. Brain-wise FCs was calculated for each participant and linear SVMs were developed for automatic classification of patients and controls. First, we evaluated the SVMs based on all participants and homogeneous subsamples of men, women, younger (18–30 years), and older (31–50 years) participants by 10-fold nested cross-validation. Then, we hold out a fixed test set of 40 participants (20 patients and 20 controls) and evaluated the SVMs based on incremental training sample sizes (N = 40, 80, …, 400).
Results
We found that the SVMs based on all participants had accuracy of 85.05%. The SVMs based on male, female, young, and older participants yielded accuracy of 84.66, 81.56, 80.50, and 86.13%, respectively. Although the SVMs based on older subsamples had better performance than those based on all participants, they generalized poorly to younger participants (77.24%). For incremental training sizes, the classification accuracy increased stepwise from 72.6 to 83.3%, with >80% accuracy achieved with sample size >240.
Conclusions
The findings indicate that SVMs based on a large dataset yield high classification accuracy and establish models using a large sample size with heterogeneous properties are recommended for single subject prediction of schizophrenia.
The thermal conductivity of a molecular gas consists of the translational and internal parts. Although in continuum flows the total thermal conductivity itself is adequate to describe the heat transfer, in rarefied gas flows they need to be modelled separately, according to the relaxation rates of translational and internal heat fluxes in an homogeneous system. This paper is dedicated to quantifying how these relaxation rates affect rarefied gas dynamics. The kinetic model of Wu et al. (J. Fluid Mech., vol. 763, 2015, pp. 24–50) is adapted to recover the relaxation of heat fluxes, which is validated by the direct simulation Monte Carlo method. Then the model of Wu et al., which has the freedom to adjust the relaxation rates, is used to investigate the rate effects of thermal relaxation in problems such as the normal shock wave, creep flow driven by Maxwell's demon and thermal transpiration. It is found that the relaxation rates of heat flux affect rarefied gas flows significantly, even when the total thermal conductivity is fixed.
The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a public health emergency of international concern. The current study aims to explore whether the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are associated with the development of death in patients with COVID-19. A total of 131 patients diagnosed with COVID-19 from 13 February 2020 to 14 March 2020 in a hospital in Wuhan designated for treating COVID-19 were enrolled in the current study. These 131 patients had a median age of 64 years old (interquartile range: 56–71 years old). Furthermore, among these patients, 111 (91.8%) patients were discharged and 12 (9.2%) patients died in the hospital. The pooled analysis revealed that the NLR at admission was significantly elevated for non-survivors, when compared to survivors (P < 0.001). The NLR of 3.338 was associated with all-cause mortality, with a sensitivity of 100.0% and a specificity of 84.0% (area under the curve (AUC): 0.963, 95% confidence interval (CI) 0.911–1.000; P < 0.001). In view of the small number of deaths (n = 12) in the current study, NLR of 2.306 might have potential value for helping clinicians to identify patients with severe COVID-19, with a sensitivity of 100.0% and a specificity of 56.7% (AUC: 0.729, 95% CI 0.563–0.892; P = 0.063). The NLR was significantly associated with the development of death in patients with COVID-19. Hence, NLR is a useful biomarker to predict the all-cause mortality of COVID-19.
Based on an accurate numerical solution of the kinetic equation using well-resolved spatial and velocity grids, the separation of rarefied gas flow in a microchannel with double rectangular bends is investigated over a wide range of Knudsen and Reynolds numbers. Rarefaction effects are found to play different roles in flow separation (vortex formation) at the concave and convex corners. Flow separations near the concave and convex corners are only observed for a Knudsen number up to $0.04$ and $0.01$, respectively. With further increase of the Knudsen number, flow separation disappears. Due to the velocity slip at the solid walls, the concave (convex) vortex is suppressed (enhanced), which leads to the late (early) onset of separation of rarefied gas flows with respect to the Reynolds number. The critical Reynolds numbers for the emergence of concave and convex vortices are found to be as low as $0.32\times 10^{-3}$ and $30.8$, respectively. The slip velocity near the concave (convex) corner is found to increase (decrease) when the Knudsen number increases. An adverse pressure gradient appears near the concave corner for all the examined Knudsen numbers, while for the convex corner it only occurs when the Knudsen number is less than $0.1$. Due to the secondary flow and adverse pressure gradient near the rectangular bends, the mass flow rate ratio between the bent and straight channels of the same length is a non-monotonic function of the Knudsen number. Our results clarify the diversified and often contradictory observations reported in the literature about flow rate enhancement and vortex formation in bent microchannels.
Maternal supraphysiological estradiol (E2) environment during pregnancy leads to adverse perinatal outcomes. However, the influence of oocyte exposure to high E2 levels on perinatal outcomes remains unknown. Thus, a retrospective cohort study was conducted to explore the effect of high E2 level induced by controlled ovarian stimulation (COH) on further outcomes after frozen embryo transfer (FET). The study included all FET cycles (n = 10,581) between 2014 and 2017. All cycles were categorized into three groups according to the E2 level on the day of the human Chorionic Gonadotropin trigger. Odds ratios (ORs) and their confidence intervals (CIs) were calculated to evaluate the association between E2 level during COH and pregnancy outcomes and subsequent neonatal outcomes. From our findings, higher E2 level was associated with lower percentage of chemical pregnancy, clinical pregnancy, ongoing pregnancy, and live birth as well as increased frequency of early miscarriage. Preterm births were more common among singletons in women with higher E2 level during COH (aOR1 = 1.93, 95% CI: 1.22–3.06; aOR2 = 2.05, 95% CI: 1.33–3.06). Incidence of small for gestational age (SGA) was more common in both singletons (aOR1 = 2.01, 95% CI: 1.30–3.11; aOR2 = 2.51, 95% CI: 1.69–3.74) and multiples (aOR1 = 1.58, 95% CI: 1.03–2.45; aOR2 = 1.99, 95% CI: 1.05–3.84) among women with relatively higher E2 level. No association was found between high E2 level during COH and the percentage of macrosomia or large for gestational age. In summary, oocyte exposure to high E2 level during COH should be brought to our attention, since the pregnancy rate decreasing and the risk of preterm birth and SGA increasing following FET.
Previous studies using resting-state functional neuroimaging have revealed alterations in whole-brain images, connectome-wide functional connectivity and graph-based metrics in groups of patients with schizophrenia relative to groups of healthy controls. However, it is unclear which of these measures best captures the neural correlates of this disorder at the level of the individual patient.
Methods
Here we investigated the relative diagnostic value of these measures. A total of 295 patients with schizophrenia and 452 healthy controls were investigated using resting-state functional Magnetic Resonance Imaging at five research centres. Connectome-wide functional networks were constructed by thresholding correlation matrices of 90 brain regions, and their topological properties were analyzed using graph theory-based methods. Single-subject classification was performed using three machine learning (ML) approaches associated with varying degrees of complexity and abstraction, namely logistic regression, support vector machine and deep learning technology.
Results
Connectome-wide functional connectivity allowed single-subject classification of patients and controls with higher accuracy (average: 81%) than both whole-brain images (average: 53%) and graph-based metrics (average: 69%). Classification based on connectome-wide functional connectivity was driven by a distributed bilateral network including the thalamus and temporal regions.
Conclusion
These results were replicated across the three employed ML approaches. Connectome-wide functional connectivity permits differentiation of patients with schizophrenia from healthy controls at single-subject level with greater accuracy; this pattern of results is consistent with the ‘dysconnectivity hypothesis’ of schizophrenia, which states that the neural basis of the disorder is best understood in terms of system-level functional connectivity alterations.
Estimating the robot state within a known map is an essential problem for mobile robot; it is also referred to “localization”. Even LiDAR-based localization is practical in many applications, it is difficult to achieve global localization with LiDAR only for its low-dimension feedback, especially in environments with repetitive geometric features. A sensor-fusion-based localization system is introduced in this paper, which has the capability of addressing the global localization problem. Both LiDAR and vision sensors are integrated, making use of the rich information introduced by vision sensor and the robustness from LiDAR. A hybrid grid-map is built for global localization, and a visual global descriptor is applied to speed up the localization convergence, combined with a pose refining pipeline for improving the localization accuracy. Also, a trigger mechanism is introduced to solve kidnapped problem and verify the relocalization result. The experiments under different conditions are designed to evaluate the performance of the proposed approach, as well as a comparison with the existing localization systems. According to the experimental results, our system is able to solve the global localization problem, and the sensor-fusion mechanism in our system has an improved performance.
Previous neuroimaging studies demonstrated that retinal detachment (RD) subjects were associated with abnormal spontaneous brain activities; however, whether the altered interhemispheric functional connectivity (FC) occurred in RD patients remains unknown. The current study tried to explore the alternations of interhemispheric FC of the whole brain in unilateral RD patients using the voxel-mirrored homotopic connectivity (VMHC) method and their connections to clinical features. Methods: We recruited 30 patients with RD (16 males and 14 females) and 30 healthy controls (HCs) (16 males and 14 females) whose age and sex were closely matched. All subjects underwent the rs-fMRI scans. The VMHC method was applied to directly assess the hemispheres’ functional interaction. The VMHC in these brain areas, which could be used as biomarkers to differentiate RD from HC, was identified by the receiver operating characteristic (ROC) curve analyses. The relations between these patients’ clinical features and their mean VMHC signal values in multiple brain regions were calculated by Pearson correlation analysis. Results: RD patients had significantly lower VMHC values than HCs in the bilateral occipital lobe (Brodmann areas, BA 18), bilateral superior temporal gyrus (BA 39), and bilateral cuneus (BA 19). Moreover, the mean VMHC signal values of the bilateral cuneus were in positive correlation with the duration of the RD (r = 0.446, P = 0.013). Conclusion: Our results provided an evidence of disturbed interhemispheric FC in the visual area occurred in RD patients, which might provide some useful information to understand the neural mechanism of RD patients with acute vision loss. Furthermore, the VMHC values might indicate the progress of the RD.
An all-fiberized high-average-power narrow linewidth ns pulsed laser with linear polarization is demonstrated. The laser system utilizes a typical master oscillator power amplifier (MOPA) configuration. The stimulated Brillouin scattering (SBS) is effectively suppressed due to the short fiber length and large mode area in the main amplifier, combined with the narrow pulse duration smaller than the phonon lifetime of SBS effect. A maximal output power of 466 W is obtained with a narrow linewidth of ${\sim}$203.6 MHz, and the corresponding slope efficiency is ${\sim}$80.3%. The pulse duration is condensed to be ${\sim}$4 ns after the amplification, corresponding to the peak power of 8.8 kW and the pulse energy of $46.6~\unicode[STIX]{x03BC}\text{J}$. Near-diffraction-limited beam quality with an $M^{2}$ factor of 1.32 is obtained at the output power of 442 W and the mode instability (MI) is observed at the maximal output power. To the best of our knowledge, this is the highest average output power of the all-fiberized narrow linewidth ns pulsed fiber laser with linear polarization and high beam quality, which is a promising source for the nonlinear frequency conversion, laser lidar, and so on.
For straw incorporation, three crucial factors affect the soil microbial community and various enzyme activities: straw length, amount and burial depth. To analyse the individual and interactive effects of these three factors on the soil microbial community and various enzyme activities, 23 treatments with five levels of the three variables (straw length, amount and burial depth) were applied in a quadratic orthogonal rotation combination design. A comprehensive indicator was constructed that could represent soil microbial functional diversity and enzyme activity by determining the weights of measured indicators and using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results indicated that the soil microbiological indicators have a higher criteria weight than soil enzyme activity indicators. The final weight orders of indicators were as follows: Shannon–Weaver > invertase > Shannon evenness > urease > catalase > McIntosh index > Simpson diversity > phosphatase. The soil comprehensive values constructed by the TOPSIS method are reliable. The optimal combination for the improvement of soil microbial functional diversity and enzyme activity was a straw length of 13–24 cm, burial depth of 10–17 cm and straw amount of 370–650 g/m2.
China makes a unique and vital contribution to maintaining global and regional waterbird diversity and conservation. Despite considerable historical conservation efforts, the continued loss of waterbird diversity and abundance necessitates a contemporary review of Chinese sites of conservation significance. The Ecological Protection Red Line (EPRL) was proposed by China’s Central Government in 2013 to protect areas providing crucial ecosystem services and provides the opportunity for such a review to enhance waterbird conservation in China. By incorporating various sources of data, surveys and information, we identified a suite of sites of waterbird conservation significance in China, following the Ramsar Site Criteria/Important Bird and Biodiversity Area (IBA) Criteria. In total, we identified 422 sites, of which the existing 286 IBA sites formed the basis of the site safeguard network. Altogether, these sites of waterbird conservation significance constitute over 727,000 km2 (7.6% of China’s land surface). Over half of the area of these sites is outside China’s national nature reserves, thus confirming the importance and urgency of including them in the EPRL for the effective conservation of waterbird sites. We suggest that this assessment of sites of waterbird importance offers a useful model to apply to other taxa, such as terrestrial birds and mammals.
A congruent melting compound LiNaV2O6 has been synthesized by high-temperature solution reaction and it has been grown with sizes up to 11 × 6 × 2 mm3 by the top-seeded growth method for the first time. LiNaV2O6 crystallizes in the monoclinic system with space group C2/c, with a = 10.184(2) Å, b = 9.067(2) Å, c = 5.8324(11) Å, β = 108.965(14)°. UV–Vis–NIR diffuse reflectance spectrum of LiNaV2O6 shows that it has a wide transmittance range from 385 to 2500 nm. The ab initio calculations show that the birefringence of LiNaV2O6 is 0.136 at 589.3 nm. Therefore, LiNaV2O6 may be a new birefringent material. Based on the analysis of the relationship between crystal structure and linear optical properties, it is found that the large birefringence is attributed to the particular arrangement of V–O anionic groups.
In this study, crystal orientation and polymorphism formation in electrospun poly(vinylidene fluoride) (PVDF)/polyacrylonitrile (PAN) blend fibers after melt-recrystallization were studied. To achieve uniform alignment of electrospun fibers, mechanical stretching was applied to the as-spun nonwoven fibers at 110 °C. Pure ferroelectric β-PVDF crystals in the PAN matrix were achieved, and both polar β-PVDF and polar PAN crystals oriented with their chain axes parallel to the fiber axes. After melt-recrystallization of PVDF, a significant amount of ferroelectric β crystals was retained in addition to the formation of nonpolar α crystals. A polarized Fourier transform infrared study showed that the degree of orientation of ferroelectric β-PVDF crystals was higher than that of nonpolar α crystals, suggesting that the β-PVDF crystals should form at the PVDF/PAN interfaces because of strong dipolar and hydrogen bonding interactions between vinylidene fluoride and acrylonitrile units. The nonpolar α-PVDF crystals should form in the center of PVDF domains.