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The synchronous variation of Tibetan Plateau vortex (TPV) and southwest vortex (SWV) is an important way to trigger heavy precipitation in southwest and eastern China. However, the physical process and mechanism of the coordinated change of two vortices are still unclear. A synchronous variation process of the TPV and SWV during the super-strong and super-long Meiyu period in 2020 (during 1-4 June of 2020) is selected to analyze the evolution characteristics of the strength and structure corresponding to the special time node (T1-T5) when two vortices coexist, as well as the potential vorticity budget with the data including the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5) hourly data and the precipitation observations. It's found that during the period T1-T2, TPV moves eastward on the Tibetan Plateau. When the SWV is generated (T1), it is far away from the TPV, and it is considered that two vortices have no interaction at that time. At the time of T3, when the TPV moves to the lower slope terrain on the eastern side of the Tibetan Plateau, its intensity is significantly weakened. Also at that monment, the TPV begins to change in coordination with the SWV. During T4-T5, two vortices strengthen and continue to change synchronously, and then merge into cyclonic circulation on their east side. Combined with the intensity changes of two vortices, the TPV and SWV with non-overlapping horizontal positions can also undergo synchronous variations, when their characteristics of intensity changes are roughly similar. From the analysis results of the potential vorticity diagnostic equation, two vortices have different evolution mechanisms before the synchronous variation, but their evolution mechanisms are basically the same when the synchronous variation occurs. It can be concluded that, when there is no synchronous variation (T1-T2), the TPV mainly relies on the heating field to maintain the eastward movement, and the SWV is maintained by the horizontal potential vorticity flux divergence. When the two vortices change synchronously (T3-T5), their intensity changes are similar, and the evolution mechanisms of them are consistent. The maintenance of two vortices mainly depends on the horizontal potential vorticity flux divergence, followed by the heating field.

In the transmission process, acceleration signal collected by the stability and instability detection device of EMU is easily interfered due to the long wiring and complex electromagnetic environment. If the interference signal is not fully suppressed, it is easy to produce aliasing phenomenon in the sampling process of analog conversion, resulting in false alarms or missing alarms, and affecting driving safety. The traditional anti-aliasing filter method uses analog high order (5~7 order) low pass filter to remove the interference signal outside the effective bandwidth. Although it meets the anti-aliasing requirement, it has some problems such as complex circuit, poor consistency and inconvenient parameter modification. Aiming at the problems, an improved digital-analog hybrid anti-aliasing filter scheme is proposed. Firstly, frequencies of aliasing points in the sampling process are improved by high-order over-sampling, so that the complexity of the analog filter circuit can be greatly reduced to the first-order one. Then, a digital FIR low-pass filter is used to remove the redundant signals brought by the over-sampling process. Test results show that the performance of the stability and instability detection device by the improved scheme is basically consistent with that of the one by pure hardware scheme, which meets the requirements of practical applications. Meanwhile, the problems of consistency and flexibility of high-order hardware filter circuit in traditional design are solved.

In recent years, significant strides have been made in the field of synthetic aperture radar (SAR) ship detection through the application of deep learning techniques. These advanced methods have substantially improved the accuracy of ship detection. Nonetheless, SAR images present distinct challenges, including complex backgrounds, small ship targets, and noise interference, thereby rendering the detectors particularly demanding. In this paper, we introduce LRTransDet, a real-time SAR ship detector. LRTransDet leverages a lightweight vision transformer (ViT) and a multi-scale feature fusion neck to address these challenges effectively. First, our model implements a lightweight backbone that combines convolutional neural networks (CNNs) and transformers, thus enabling it to simultaneously capture both local and global features from input SAR images. Moreover, we boost the model’s efficiency by incorporating the faster weighted feature fusion (Faster-WF2) module and coordinate attention (CA) mechanism within the feature fusion neck. These components optimize computational resources while maintaining the model’s performance. To overcome the challenge of detecting small ship targets in SAR images, we refine the original loss function and use the normalized Wasserstein distance (NWD) metric and the intersection over union (IoU) scheme. This combination improves the detector’s ability to efficiently detect small targets. To prove the performance of our proposed model, we conducted experiments on four challenging datasets (the SSDD, the SAR-Ship Dataset, the HRSID, and the LS-SSDD-v1.0). The results demonstrate that our model surpasses both general object detectors and state-of-the-art SAR ship detectors in terms of detection accuracy (97.8% on the SSDD and 93.9% on the HRSID) and speed (74.6 FPS on the SSDD and 75.8 FPS on the HRSID), all while demanding 3.07 M parameters. Additionally, we conducted a series of ablation experiments to illustrate the impact of the EfficientViT, the Faster-WF2 module, the CA mechanism, and the NWD metric on multi-scale feature fusion and detection performance.

Summary: In this study, we establish a population-based human induced pluripotent stem cell (hiPSC) drug screening platform for toxicity assessment. After recruiting 1,000 healthy donors and screening for high-frequency human leukocyte antigen (HLA) haplotypes, we identify 13 HLA-homozygous “super donors” to represent the population. These “super donors” are also expected to represent at least 477,611,135 of the global population. By differentiating these representative hiPSCs into cardiomyocytes and neurons we show their utility in a high-throughput toxicity screen. To validate hit compounds, we demonstrate dose-dependent toxicity of the hit compounds and assess functional modulation. We also show reproducible in vivo drug toxicity results using mouse models with select hit compounds. This study shows the feasibility of using a population-based hiPSC drug screening platform to assess cytotoxicity, which can be used as an innovative tool to study inter-population differences in drug toxicity and adverse drug reactions in drug discovery applications.

To make accurate and comprehensive evaluation of the catenary and diagnose the causes of the catenary fault, a method of catenary state evaluation and diagnosis based on the principal component analysis control chart was proposed, which can make full use of the multidimensional detection parameters of the catenary. The principal component analysis was used to reduce the dimension of catenary parameters, the principal component T2 control chart was calculated to show the change of principal component of catenary state data, the residual SPE control chart was calculated to show the change of their correlation, and the contribution rate control chart was calculated to show the cause of abnormal state data. The method can not only transform the multidimensional detection parameters of the catenary into a statistic to realize the simple and intuitive evaluation of the catenary state but also can accurately determine the cause of the abnormal state, so as to provide technical support for the targeted condition-based maintenance of the catenary.

The SCO2 turbine machines exchange energy through supercritical carbon dioxide. Their impeller has the features of high-temperature and −speed to enhance energy conversion efficiency, but the rotor needs to be cooled to be compatible with bearings and seals. The paper introduces a pivotal parameter optimization of a concentrating solar SCO2 turbine rotor and seeks to control the harmonic response amplitude while preserving the distance between the critical speed and the working speed. The optimization considers several parameters including bearing span, stiffness, effective mass and damping of the bearing hub, and gas film stiffness coefficients of the cooler. The optimization is accomplished using a multi-objective and −scale quantum harmonic oscillator algorithm (mMQHOA) that couples an information interaction algorithm and transfer matrix model. The application of information interaction accelerates the convergence speed of the objective functions. The verification results from the three-dimensional finite element (3D-FE) indicate that the non-dominant design reduces resonance amplitude of the disc by approximately 71.91%, while the critical frequency increases by about 34.33% in the direction away from the operating frequency, and imply a trade-off relationship between harmonic response amplitude and critical speed. It is further reveal that the increased gas film stiffness of cooler in the primary level interval (

Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

Supercritical carbon dioxide (SCO2) Brayton cycle microturbine can be used for the next generation of solar power. In order to comprehensively optimize the supporting system and cooling device parameters of Brayton cycle shafting, the concept of chaos interval is introduced by chaotic mapping, and the CIMPSO algorithm is proposed to optimize the multi-objective rotor system model with nonlinear variables.The results show that the resonance amplitude of the optimized model is effectively attenuated, and the critical speed point is far away from the working speed, which shows the robustness of the optimization algorithm. Finally, based on arbitrary several sets of optimization solutions and empirical parameters, the finite element model of shafting is established for simulation, and the results show that the optimized solution has certain guiding significance for the design of the rotor system.The cooling device is designed and simulated by CFD method based on the optimal solution set. Both the inlet boundary conditions of given pressure (1 MPα) and given mass flow rate (0.1 kg/s) numerical calculations were carried out to characterize the cooling performance, for different jet impingement configurations (Hr/din = 0.0125 ∼ 5).Several sets of analyses show the strong effects of the jet-to-target spacing (Hr/din) on the rotor thermal performance at a given diameter (din) of the nozzle. Average temperature (Tc) at the free end of the rotor show that, as jet-to-target distance decreases (0.0125 ≤ Hr/din ≤ 0.33), the heat dissipation efficiency of the cooling device with the given pressure boundary condition tends to decrease, while the conclusion is opposite when the inlet boundary condition is set to the given mass flow rate. And there is an interval for the optimal combination (Hr/din) to promote the cooling efficiency.

Numerical investigation was carried out to study the heat transfer performance for a high-speed rotating cylindrical surface subjected to single row array round jets impingement, under a very small gap spacing. Various parameters that affect heat transfer, such as the fluid density, flow velocity and Nusselt number distributions of the radius clearance were studied based on varied nozzle to target surface spacing H and mass flow rate. It has been found that the fluid density was a dominant factor and the velocity was the secondary factor for the gas jet heat transfer performances. The overall heat transfer was improved with a reduction in the number of nozzles, for given inlet mass flow rate boundary conditions. The decrease of H/di (di, nozzle diameter) may have positive or negative effects on the heat transfer performance from the impingement surface. Reducing the radius gap H, for a certainty, increases the average density of the fluid in the clearance, which is desirable in applications that enhance heat transfer performance. But when the radius gap (H) is small enough, increasing di may have a negative impact on heat transfer.

To shorten the residence time of the H2/O2 interface and restrict the start-up voltage of the stack during the start-up process of a proton exchange membrane fuel cell(PEMFC),the effect differences of direct start-up,hydrogen purging time and auxiliary load current on the performance of PEMFC were studied by experiment. A fuel system start-up control strategy was proposed which combines hydrogen-purging the anode with starting the auxiliary load current. Experimental results prove that the start-up control strategy limits the start-up voltage of the fuel cell,shortens the residence time of the H2/O2 interface during the start-up process of the stack,and is conducive to improve the single-battery voltage balance. So it is a kind of effective PEMFC start-up control strategy.

The China spallation neutron source (CSNS) was built and started running since 2018. It produces neutrons by impinging 1.6 GeV protons onto a tungsten target with 25 Hz repetition frequency. A beam line exploiting the back-streaming neutrons (Back-n) was built mainly for nuclear data measurement and started commissioning simultaneously with CSNS in 2018. There are two experimental endstations along the Back-n beam line: endstation 1 (#ES1) with a neutron flight path of about 55 m and endstation 2 (#ES2) with about 76 m. The neutron energy spectra of both #ES1 and #ES2 were measured since it is important for feasibility study and analysis. In this paper, the measurement of the neutron energy spectrum of Back-n #ES1 is reported. It is measured by a multi-layer fission chamber using the 235U samples as the neutron converters. The neutron energy spectrum from 0.1 eV to 30 MeV is obtained. The integral neutron flux (from 0.1 eV to 30 MeV) normalized to the proton beam power of 100 kW is 1.55×107 neutrons/cm2/s.

Differential cross-section data for the n-p and n-d elastic scattering (1H(n, el), 2H(n, el)) are collected and analyzed from EXFOR library. For En > 20 MeV, the experimental results for both reactions are scarce with large uncertainties and discrepancies in general. For En ≤ 20 MeV, the experimental results lack systematicness, most of which were measured around En = 14 MeV even though the differential cross sections of n-p scattering in 1 keV ≤ En ≤ 20 MeV region are recommended as standard. Taking these facts into account, more accurate and systematic measurements are planned. The experiments will be conducted using ΔE-E detectors of the Light-charged Particle Detector Array (LPDA) system at China Spallation Neutron Source (CSNS) Back-n White Neutron Source (WNS), and simulations are carried out. Using polyethylene and deuterated polyethylene as samples, both n-p and n-d scattering reactions are simulated along with the neutron-induced 12C background reactions, and the 2-D spectra and the counting rates of the ΔE-E detectors are obtained. According to the simulations, the applicable neutron energy range and positions of the detectors are recommended, and the beam time for the event and background measurements is suggested.

Having a unique physical characteristics and stable semiconductor properties,silicon carbide（ Si C） monocrystal wafer has been widely used in integrated circuits,space optics and other fields.In manufacturing process of Si C monocrystal wafer,cutting is primary key process,which the cutting costs accounts for more than 50% of the whole wafer processing costs.In this paper,the datum and relevant literature of domestic and foreign were reviewed to,the current research status of Si C cutting technology,especially cutting with wire saw,and cutting equipment were studied.Moreover,the existing problems in Si C cut by wire saw and in cutting equipment was analyzed.It is proposed that the future researching direction of Si C wafer cutting technology by wire saw.

The flow-guided sieve-valve tray(FGS-VT)with high efficiency was designed to overcome the shortcoming of low operating flexibility of the flow-guided sieve tray. Its dimensions and geometry, as well as structure characteristics, were presented. The hydrodynamics and mass transfer performance, including dry-plate pressure drop, wet plate-pressure drop, weeping, entrainment and tray efficiency, of two types of FGS-VTs (FGS-VTs with 14 and 8 valves, respectively) and one flow-guided sieve tray were tested in an air-water-oxygen cold model experiment with a 0.6 m diameter plexiglass column. The results demonstrate that FGS-VT with 14 valves works better than FGS-VT with 8 valves, and in comparison with the flow-guided sieve tray, the flow-guided sieve-valve tray with 14 valves has higher tray efficiency, bigger operating flexibility, and lower wet-plate pressure drop (when all the valves are opened fully).Additionally, two typical applications to separate the mixture with high viscosity, solid, powder, easy-to-foam or easy self-polymerization components proved the unique advantages of FGS-VT.

For the process of optimizing the process parameters in the process of cutting the hard and brittle materials such as single-crystal SiC by diamond wire saw, the process parameters such as wire saw speed, workpiece feed speed and workpiece rotation speed are the design variables, and the sawing force and surface roughness are the processing targets by orthogonal experimental design. The grey system theory is introduced to optimize the multi-objective cutting process. According to the experimental data, the grey correlation resolution coefficient is determined. The significant relationship between the processing parameters and the target characteristics is analyzed. The optimal combination of process parameters under multi-target conditions is obtained, namely the workpiece feed rate is 0.025mm/min, the wire saw speed is 1.6m/s, and the workpiece rotating speed is 16r/min.

* Context.--Whether androgen receptor (AR) expression can predict prognosis in breast cancer is under debate. Objective.--To analyze, retrospectively, the prognostic and treatment-predictive ability of AR status in breast cancer. Design.--A total of 5765 patients diagnosed with primary invasive breast cancer without distant metastasis in the adjuvant setting were analyzed. The propensity score-matching method was used to develop a new cohort of 3978 patients (1989 patients each) in which important prognostic factors were balanced. Results.--Positive AR expression is an independent prognostic factor for disease-free survival and overall survival. Estrogen receptor [(ER).sup.+] and progesterone receptor [(PR).sup.+] [AR.sup.+] breast cancer patients had the longest survival, whereas [ER.sup.-][PR.sup.-][AR.sup.+] breast cancer patients had the shortest survival. The ER/PR/AR combinations could not predict the treatment effects for adjuvant trastuzumab but could be used for adjuvant chemotherapy and endocrine therapy selection. The worst survival was found in [ER.sup.+][PR.sup.-][AR.sup.-] patients receiving toremifene, [ER.sup.+][PR.sup.-][AR.sup.+] patients receiving exemestane, [ER.sup.+][PR.sup.+][AR.sup.-] patients receiving anthracycline, and [ER.sup.-][PR.sup.-][AR.sup.+] patients receiving taxanes. [ER.sup.+][PR.sup.-][AR.sup.-], [ER.sup.-][PR.sup.-][AR.sup.+], and [ER.sup.-][PR.sup.-][AR.sup.-] patients were associated with the worst survival among those who received radiotherapy and anthracycline plus taxanes. Conclusions.--AR in combination with ER and PR could predict the prognosis and treatment effects of chemotherapy, endocrine therapy, and radiotherapy in the adjuvant setting., Breast cancer is classified into different molecular types based on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67 expression, which can predict prognosis [...]