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Suppressing the activity of metal particles is a key issue in the development of dc gas-insulated power transmission lines (GILs). This study investigates the effects of five different dielectric coatings of the electrodes—namely surface oxidation treatment and four different coating materials (i.e., 1032K high-resistance paint (1032K), teflon, epoxy marlin orange primer (EM primer), and iron red primer (IR primer) spray)—on the movement characteristics of ball and block metal particles under dc voltage and polarity reversal voltage in an SF6 gas environment at an absolute pressure of 0.3 MPa. The results showed that the surface oxidation treatment of the electrodes had little effect on suppressing the particle activity. The coating in the high-voltage electrode did not significantly change the particle jumping voltage, and once the particles jumped, they were adsorbed onto the coating. Coating the ground electrode significantly increased the jumping voltage of the particles. Under dc voltage, the lifting field strength of the particles exceeds 5 kV/mm which is much higher than the maximum design field strength at the ground electrode of dc GIL. The increase in coating thickness did not significantly improve the jumping field strength. Under polarity reversal voltage, the jumping field strength of the particles was lower than under dc. However, the coating of the ground electrode also had a significant effect on suppressing the particles during the reversal process. Simulation results showed that the coating hindered the charge exchange between the particles and the electrode, increased the field strength at the contact position between the particles and the electrode, and reduced the field strength on the side of the particles away from the electrode.

Introduction: A survival paradox between T4N0 (Stage IIB/IIC) and Stage IIIA colon cancer exists, even after adjusting for adequate lymph node (LN) retrieval and receipt of adjuvant chemotherapy (C). We conducted a large hospital-based study to re-evaluate this survival paradox based on the newest 8th edition staging system. Methods: The National Cancer Data Base was queried to evaluate 35,606 patients diagnosed with Stage IIB, IIC, and IIIA colon cancer between 2010 and 2017. The Kaplan–Meier method and log-rank test were used to compare unadjusted overall survival (OS). Multivariable Cox proportional hazards model was used to determine the association of stage with hazard ratios adjusted for relevant demographic and clinical variables including ≥ 12 LNs retrieved and receipt of adjuvant chemotherapy. Pvalue < 0.05 was considered statistically significant. Results: The 5-year OS for optimally treated stage IIIA colon cancer (receipt of C) was 84.3%, which was significantly higher than stage IIB/C (≥ 12 LNs retrieved + C) (72.8%; P< 0.0001). Stage was an independent predictor of OS. Among optimally treated Stage IIIA patients, T1N1 had the best survival (90.6%) while stage T4bN0 (stage IIC) had the worst (70.9%) (P< 0.0001). Compared to stage IIB, stage IIC had a 17% increased risk of overall death while stage IIIA had a 21% reduction in death (P< 0.0001). Conclusion: Stage IIB/C and Stage IIIA survival paradox persists even after accounting for receipt of adjuvant chemotherapy and adequate lymph node retrieval. Future iteration of the TNM system should take this paradox into consideration.

Monophasic Al50Ni50ribbons were fabricated by melt spinning at circumferential speeds (Sc) of 21 and 42 m/s, and subsequently annealed at various temperatures. The microstructure and corrosion behavior of ribbons were studied through various experimental methods. With increasing Sc, the as-spun and annealed ribbons at 42 m/s show a higher (100) crystal orientation factor F(100), a lower barrier to recrystallization and a higher total film resistance than the counterparts with 21 m/s. The as-spun ribbon at 42 m/s demonstrated a denser and more stable Al2O3passive film compared to the as-spun and annealed ribbons at 21 m/s. This improvement in passive film can be further enhanced by 700 °C annealing. Therefore, the corrosion resistance of AlNi ribbons can be improved by increasing Scand additional annealing at an appropriate temperature.

The electromechanical planetary gear system has high work efficiency and long service life, but factors such as heat, wear, and electrical signals can affect the transmission performance of electromechanical planetary gears. This article comprehensively considers factors such as temperature, tooth surface wear, lubrication, current and voltage, damping ratio, etc. Based on the principle of thermal deformation, Archard wear model, and equivalent circuit principle, a dynamic model of electromechanical planetary gears is established. The existing literature has not comprehensively analyzed the effects of temperature, wear, and electrical signal changes on the nonlinear characteristics of electromechanical planetary gear systems. The results show that when the motor current is between 7 A and 18 A and the voltage is lower than the rated voltage, the system is in a stable state; as the temperature rises, the system tends to stabilize; the gear wear exceeds 30 μm, and the bifurcation characteristics of the system are more pronounced.

Purpose: Planetary gears generate a lot of heat during the meshing transmission process, which results in thermal deformation of the gear teeth and affects the nonlinear dynamic characteristics of the system. It is valuable to study the influence of the thermal effect on the chaotic characteristics of planetary gear systems. Method: Based on the law of thermal deformation, considering the temperature effect and multiple nonlinear factors, including the coupling effects of time-varying meshing stiffness, meshing error, and gear backlash, a nonlinear dynamics model of the planetary gear system is established. The system's differential equation is derived from the gear system dynamics theory and solved using the Runge–Kutta method. The impact law of temperature, time-varying stiffness coefficient, and damping ratio changes on the bifurcation features of the planetary gear system is studied by combining the maximum Lyapunov exponent diagram, bifurcation diagram, time domain diagram, phase diagram, Poincare diagram, and spectrogram. Results: The planetary gear system exhibits chaotic and rich bifurcation characteristics under the coupling effect of multiple nonlinear factors. With the increase in temperature, the system experiences a kinematic process of chaos-four period-two period-single period. As the time-varying stiffness coefficient changes, the system exhibits chaotic, three-periodic, and two-periodic motion states. The effect of the engagement damping ratio change on the nonlinear characteristics of the system is significant when the value of the temperature is in the range of 0 < ∆T< 68 °C. Conclusion: The chaotic motion of the system is weakened under higher temperature and larger damping ratio, which has an obvious effect on improving the system’s stability. The pertinent conclusions can be used as future references for gear system development.

Benzocyclobutene (BCB)-based resins have garnered considerable attention because of their remarkable dielectric properties and thermal stability. However, in molecular dynamics (MD) simulations, progress in BCB-based resin research has yet to keep pace with experimental advancements, resulting in a shortage of theoretical underpinnings at the molecular level. This study focuses on a novel homopolymer, poly(2-(4-benzocyclobutenyl)-divinylbenzene(DVB-S-BCB)), and devises an interactive methodology suitable for BCB-based resins. We implemented a Python script for the joint relaxation method to construct a three-dimensional model of the cured polymer using MadeA and LAMMPS. We conducted MD simulations to investigate how the cross-linking degree and resin molecular weight influence the dielectric properties of the cured polymer. Furthermore, we analyzed the thermodynamic properties through simulation. The results illustrate that augmenting the cross-linking degree and resin molecular weight results in a higher cross-linking density and reduced free volume, thereby increasing the dielectric constant of the resin. The cross-link density does not increase indefinitely with molecular weight, and after a certain threshold is reached, it cannot have a significant effect on the dielectric constant. The degree of cross-linking exerts a more pronounced impact on the dielectric constant than the molecular weight of the resin. In addition, the simulation results denote the excellent thermodynamic properties of the cured polymer. This study also examines the dielectric and thermodynamic properties of the resin samples that were experimentally prepared. The obtained data successfully confirm the reliability of the simulation results. This study offers novel insights for future simulation research on benzocyclobutene-based resins. Additionally, it provides theoretical support for exploring experimental work on low-dielectric materials in the electronic field.

Machine learning is currently one of the research hotspots in the field of landslide prediction. To clarify and evaluate the differences in characteristics and prediction effects of different machine learning models, Conghua District, which is the most prone to landslide disasters in Guangzhou, was selected for landslide susceptibility evaluation. The evaluation factors were selected by using correlation analysis and variance expansion factor method. Applying four machine learning methods namely Logistic Regression (LR), Random Forest (RF), Support Vector Machines (SVM), and Extreme Gradient Boosting (XGB), landslide models were constructed. Comparative analysis and evaluation of the model were conducted through statistical indices and receiver operating characteristic (ROC) curves. The results showed that LR, RF, SVM, and XGB models have good predictive performance for landslide susceptibility, with the area under curve (AUC) values of 0.752, 0.965, 0.996, and 0.998, respectively. XGB model had the highest predictive ability, followed by RF model, SVM model, and LR model. The frequency ratio (FR) accuracy of LR, RF, SVM, and XGB models was 0.775, 0.842, 0.759, and 0.822, respectively. RF and XGB models were superior to LR and SVM models, indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.

BackgroundThe ZFHX3gene plays vital roles in embryonic development, cell proliferation, neuronal differentiation and neuronal death. This study aims to explore the relationship between ZFHX3variants and epilepsy.MethodsWhole-exome sequencing was performed in a cohort of 378 patients with partial (focal) epilepsy. A Drosophila Zfh2knockdown model was used to validate the association between ZFHX3and epilepsy.ResultsCompound heterozygous ZFHX3variants were identified in eight unrelated cases. The burden of ZFHX3variants was significantly higher in the case cohort, shown by multiple/specific statistical analyses. In Zfh2knockdown flies, the incidence and duration of seizure-like behaviour were significantly greater than those in the controls. The Zfh2knockdown flies exhibited more firing in excitatory neurons. All patients presented partial seizures. The five patients with variants in the C-terminus/N-terminus presented mild partial epilepsy. The other three patients included one who experienced frequent non-convulsive status epilepticus and two who had early spasms. These three patients had also neurodevelopmental abnormalities and were diagnosed as developmental epileptic encephalopathy (DEE), but achieved seizure-free after antiepileptic-drug treatment without adrenocorticotropic-hormone/steroids. The analyses of temporal expression (genetic dependent stages) indicated that ZFHX3orthologous were highly expressed in the embryonic stage and decreased dramatically after birth.ConclusionZFHX3is a novel causative gene of childhood partial epilepsy and DEE. The patients of infantile spasms achieved seizure-free after treatment without adrenocorticotropic-hormone/steroids implies a significance of genetic diagnosis in precise treatment. The genetic dependent stage provided an insight into the underlying mechanism of the evolutional course of illness.

Hypoxia is a hallmark of cancer development. However, the molecular mechanisms by which hypoxia promotes tumor metastasis are not fully understood. In this study, we demonstrate that hypoxia promotes breast cancer metastasis through suppression of ΔNp63α in a HIF1α-independent manner. We show that hypoxia-activated XBP1s forms a stable repressor protein complex with HDAC2 and EZH2 to suppress ΔNp63α transcription. Notably, H3K27ac is predominantly occupied on the ΔNp63 promoter under normoxia, while H3K27me3 on the promoter under hypoxia. We show that XBP1s binds to the ΔNp63 promoter to recruit HDAC2 and EZH2 in facilitating the switch of H3K27ac to H3K27me3. Pharmacological inhibition or the knockdown of either HDAC2 or EZH2 leads to increased H3K27ac, accompanied by the reduced H3K27me3 and restoration of ΔNp63α expression suppressed by hypoxia, resulting in inhibition of cell migration. Furthermore, the pharmacological inhibition of IRE1α, but not HIF1α, upregulates ΔNp63α expression in vitro and inhibits tumor metastasis in vivo. Clinical analyses reveal that reduced p63 expression is correlated with the elevated expression of XBP1, HDAC2, or EZH2, and is associated with poor overall survival in human breast cancer patients. Together, these results indicate that hypoxia-activated XBP1s modulates the epigenetic program in suppression of ΔNp63α to promote breast cancer metastasis independent of HIF1α and provides a molecular basis for targeting the XBP1s/HDAC2/EZH2-ΔNp63α axis as a putative strategy in the treatment of breast cancer metastasis.

Salt and drought stress are common abiotic factors that exert a detrimental influence on seed germination, potentially leading to significantly impaired growth and production in rice. Gaining a comprehensive understanding of the molecular response of seeds to abiotic stress during the germination is of paramount importance. In the present study, we identified two R3-MYB genes in rice, namely OsTCL1and OsTCL2, and characterized their roles in regulating seed germination under salt and drought stress. Plants with tcl1and tcl2mutant alleles exhibited delayed seed germination, particularly under stress conditions. The tcl1 tcl2double mutant showed an even more pronounced reduction in germination during initial stages of germination, thereby indicating a redundant regulatory function of OsTCL1 and OsTCL2 in seed germination under abiotic stresses. Furthermore, we demonstrated that the transcript levels of several phospholipase D (PLD) genes were downregulated in the tcl1 tcl2mutant, resulting in a decreased level of the phosphatidic acid (PA) product. Application of 1-butanol, a competitive substrate inhibitor of PLD-dependent production of PA, attenuated the stress response of the tcl1 tcl2mutant. This suggests that OsTCL1 and OsTCL2 partially modulate seed germination through the PLD-PA signaling pathway. Moreover, there were alterations in the expression of genes involved in abscisic acid (ABA) biosynthesis, metabolism and signaling transduction in the double mutant. These changes affected the endogenous ABA level and ABA response, thereby influencing seed germination. Application of both 1-butanol and ABA synthesis inhibitor sodium tungstate (Na2WO4) nearly eliminated the differences in stress response between wild type and the tcl1 tcl2mutant. This indicates that OsTCL1 and OsTCL2 synergistically coordinate seed germination under abiotic stresses through both the PLD-PA signaling and ABA-mediated pathways.

Phosphorus (P) is a finite natural resource and is increasingly considered to be a challenge for global sustainability. Agriculture in China plays a key role in global sustainable P management. Rhizosphere and soil-based P management are necessary for improving P-use efficiency and crop productivity in intensive agriculture in China. A previous study has shown that the future demand for phosphate fertilizer by China estimated by the LePA model (legacy phosphorus assessment model) can be greatly reduced by soil-based P management (the building-up and maintenance approach). The present study used the LePA model to predict the phosphate demand by China through combined rhizosphere and soil-based P management at county scale under four P fertilizer scenarios: (1) same P application rate as in 2012; (2) rate maintained same as 2012 in low-P counties or no P fertilizer applied in high-P counties until targeted soil Olsen-P (TPOlsen) level is reached, and then rate was the same as P-removed at harvest; (3) rate in each county decreased to 1–7 kg ha–1yr–1after TPOlsenis reached in low-P counties, then increased by 0.1–9 kg ha–1yr–1until equal to P-removal; (4) rate maintained same as 2012 in low-P counties until TPOlsenis reached and then equaled to P-removal, while the rate in high-P counties is decreased to 1–7 kg ha–1yr–1until TPOlsenis reached and then increased by 0.1–9 kg ha–1yr–1until equal to P-removal. Our predictions showed that the total demand for P fertilizer by whole China was 693 Mt P2O5and according to scenario 4, P fertilizer could be reduced by 57.5% compared with farmer current practice, during the period 2013–2080. The model showed that rhizosphere P management led to a further 8.0% decrease in P fertilizer use compared with soil-based P management. The average soil Olsen-P level in China only needs to be maintained at 17 mg kg–1to achieve high crop yields. Our results provide a firm basis for government to issue-relevant policies for sustainable P management in China.

Surface charge accumulation is a key factor that must be considered in the design of dc gas-insulated transmission line (GIL) insulators. In this letter, the insulator surface potential distribution of a ±320-kV GIL is measured under different voltage polarities and temperature gradients in the 0.5-MPa SF6. In order to explain the surface potential distribution, the mechanism of surface potential generation is proposed. We found that physical mechanisms, including micro gas ionization from the grounded enclosure, homopolar charge injection from the high-voltage conductor, and bulk polarization of insulator, all contribute to the surface potential distribution. Heteropolar surface potential dominates at both voltage polarities. Besides, the heteropolar potential becomes more pronounced at a temperature gradient of 40 °C. It indicates that free charges generated by gas-side ionization are the primary potential source. Under temperature gradient, the gas ionization is enhanced due to the dramatically increased electric field, from 2.5 to 4.3 kV/mm, on the surface of the grounded enclosure near the insulator. The findings provide importance reference for the design of dc GIL insulator.

Early control of elevated blood pressure is the most promising treatment for acute intracerebral haemorrhage. We aimed to establish whether implementing a goal-directed care bundle incorporating protocols for early intensive blood pressure lowering and management algorithms for hyperglycaemia, pyrexia, and abnormal anticoagulation, implemented in a hospital setting, could improve outcomes for patients with acute spontaneous intracerebral haemorrhage.

Zero defection manufacturing (ZDM) is the pursuit of the manufacturing industry. However, there is a lack of the implementation method of ZDM in the multi-stage manufacturing process (MMP). Implementing ZDM and controlling product quality in MMP remains an urgent problem in intelligent manufacturing. A novel predict-prevention quality control method in MMP towards ZDM is proposed, including quality characteristics monitoring, key quality characteristics prediction, and assembly quality optimization. The stability of the quality characteristics is detected by analyzing the distribution of quality characteristics. By considering the correlations between different quality characteristics, a deep supervised long-short term memory (SLSTM) prediction network is built for time series prediction of quality characteristics. A long-short term memory-genetic algorithm (LSTM-GA) network is proposed to optimize the assembly quality. By utilizing the proposed quality control method in MMP, unqualified products can be avoided, and ZDM of MMP is implemented. Extensive empirical evaluations on the MMP of compressors validate the applicability and practicability of the proposed method.

The quality prediction of machining processes is essential for maintaining process stability and improving component quality. The prediction accuracy of conventional methods relies on a significant amount of process signals under the same operating conditions. However, obtaining sufficient data during the machining process is difficult under most operating conditions, and conventional prediction methods require a certain amount of training data. Herein, a new multiconditional machining quality prediction model based on a deep transfer learning network is proposed. A process quality prediction model is built under multiple operating conditions. A deep convolutional neural network (CNN) is used to investigate the connections between multidimensional process signals and quality under source operating conditions. Three strategies, namely structure transfer, parameter transfer, and weight transfer, are used to transfer the trained CNN network to the target operating conditions. The machining quality prediction model predicts the machining quality of the target operating conditions using limited data. A multiconditional forging process is designed to validate the effectiveness of the proposed method. Compared with other data-driven methods, the proposed deep transfer learning network offers enhanced performance in terms of prediction accuracy under different conditions.

Herein, the fatigue performance of cement-stabilised loess (CSL) designed using two compaction methods were investigated. The reliability of the vertical vibration testing method (VVTM) was verified by comparing the physical properties of the laboratory samples prepared using the VVTM and the proctor compaction test (PCT) and the mechanical properties of the core samples obtained using these methods and from the construction site. Further, the CSL samples fabricated using the two compaction methods were subjected to indirect tensile fatigue tests to establish a fatigue equation. Finally, the influence of the compaction method, compaction degree and cement content on the fatigue performance of CSL was analysed based on the fatigue equation of CSL. Results showed that the correlation between the mechanical strength of the CSL sample prepared using VVTM and the core sample obtained from the construction site is more than 90%. The fatigue equation based on the Weibull distribution can effectively evaluate the fatigue life of CSL. Furthermore, the fatigue performance of VVTM sample is better than PCT sample. The equivalent fatigue life of VVTM sample with 4% cement dosage can be increased by at least 33% compared with PCT sample under the same condition. With the increase of compaction degree or cement content, the fatigue performance is gradually enhanced.

In this study, a novel artificial intervertebral disc implant with modified “Bucklicrystal” structure was designed and 3D printed using thermoplastic polyurethane. The new implant has a unique auxetic structure with building blocks joined “face-to-face”. The accompanied negative Poisson’s ratio enables its excellent energy absorption and stability under compression. The deformation and load distribution behavior of the implant under various loading conditions (bending, torsion, extension and flexion) has been thoroughly evaluated through finite element method. Results show that, compared to natural intervertebral disc and conventional 3D implant, our new implant exhibits more effective stress transfer and attenuation under practical loading conditions. The implant's ability to contract laterally under compression can be potentially used to alleviate the symptoms of lumbar disc herniation. Finally, the biocompatibility of the implant was assessed in vitroand its ability to restore the physiological function of the disc segment was validated in vivousing an animal model.

Background: To evaluate if there are differences in outcomes for patients with stage III colon cancer in those from urban vs. rural commuting areas. Methods: Data were evaluated on patients diagnosed with stage III colon cancer between 2012 and2018 from the Louisiana Tumor Registry. Patients were classified into rural and urban groups. Data on overall survival, time from diagnosis to surgery and time from surgery to chemotherapy, and sociodemographic factors (including race, age, and poverty level) were recorded. Results: Of 2652 patients identified, 2159 were urban (81.4%) and 493 rural (18.6%). No age difference between rural and urban patients (p= 0.56). Stage IIIB accounted for 66.7%, followed by IIIC (21.6%) and IIIA (11%), with a significant difference between rural and urban patients based on stage (p= 0.02). There was no difference in the extent of surgery (p= 0.34) or tumor size (p= 0.72) between urban and rural settings. No difference in undergoing chemotherapy (p= 0.12). There was a statistically significant difference in receiving timely treatment for hospital volume (p< 0.0001) and poverty level (p< 0.0001), but no difference in time from diagnosis to surgery (p= 0.48), and time from surgery to chemotherapy (p= 0.27). Non-Hispanic Blacks were less likely to receive timely treatment when compared with non-Hispanic Whites for both surgery and adjuvant chemotherapy, (aHR 0.91, 95% CI 0.83–0.99) and (aHR 0.86, 95% CI 0.77–0.97), respectively. There was no difference in Kaplan–Meier overall survival curves comparing rural vs. urban patients (p= 0.77). Conclusions: There was no statistical difference in overall survival, time to surgery, and time to adjuvant chemotherapy between rural and urban patients with Stage III colon cancer. Graphical abstract:

The surface deterioration process of aluminum-stranded conductors in high-voltage alternating current (ac) electricity grids is naturally gradual, dynamic, and slow, which will greatly influence the remaining life of conductors. An effective method for deterioration recognition of conductors is to design an evaluation model with energy-dispersive X-ray spectroscopy (EDS). The small number of labeled samples is commonly available for the deterioration recognition task. The conventionally successful deep learning (DL)-based applications are dependent on large-scale data to train an effective model, which restricts the application of DL in the aging recognition scenario. A deep meta-learning (DML) model with 1-D-convolutional neural networks (1D-CNNs) is proposed for the recognition of deteriorated conductors based on EDS, which learns the representation of each support class by the embedding function. Then, it performs classification tasks by comparing the Euclidean distance between the query sample and this representation. A comprehensive systematic comparison with nonneural network methods, conventional DL, and deep transfer learning shows that the proposed model substantially improves the classification accuracy of aging conductors.

This paper presents the design details and control methodologies for on-chip heaters that can provide fast and accurate local temperature control for reliability testing applications. The on-chip heater uses the Joule heating effect of a metal or poly line to heat the surrounding devices-under-test (DUT) to a target temperature as high as 300°C. Many generations of on-chip heaters, including different heater positions, heater areas, and heater layers, have been demonstrated in technology nodes from 350nm to 16nm. To accurately operate the heater and extend the heater’s operation lifetime for long-term reliability testing, we have also developed control methodologies for precise and reliable heater control.

A heat-reflective coating can be used to solve various problems, including rutting and deformation caused by the excessively high asphalt pavement temperatures during summer. However, the durability of the heat-reflective coatings applied to asphalt pavement has not been extensively researched. The colour changes, crack development and attenuation of the cooling performance are studied along with the changes in skid resistance and cooling performance because of wear. Subsequently, the lifespan of the heat-reflective coating is predicted based on the results. This study indicates that the amount of spraying is positively correlated with the cooling performance. After 120 days of aging, a B–A type coating shows no cracks or any decay in performance. When the wear rate is less than 40%, the skid resistance of the coating meets the required specifications and the coating exhibits good cooling performance. The lifespan of the heat-reflective coating is predicted to be one year.

The phenomenon of gear backlash is observed to increase as the planetary gears undergo wear, leading to an exacerbation of vibrations within the gear gearbox system. This heightened wear further contributes to the generation of substantial heat, consequently causing an elevation in temperature. As a consequence, the thermal deformation of the gear occurs, thereby affecting its capacity to effectively transmit power. This study presents the development of a nonlinear dynamic model for a gear system, incorporating the influence of wear and temperature. The model is constructed by integrating the Archard wear model with the thermal deformation idea. The present work investigates the influence of wear and temperature on the nonlinear dynamic characteristics of a gear system using a range of analytical techniques, such as bifurcation diagrams, maximum Lyapunov index charts, phase diagrams, and Poincare cross-section diagrams. The results indicate that as the temperature increases, the system transitions from multi-cycle motion to single cycle motion. When there is slight wear (28 microns), increasing the temperature appropriately can suppress the chaotic motion of the system. When there is severe wear (70 microns), the gears must be replaced.

CELSR1gene, encoding cadherin EGF LAG seven‐pass G‐type receptor 1, is mainly expressed in neural stem cells during the embryonic period. It plays an important role in neurodevelopment. However, the relationship between CELSR1and disease of the central nervous system has not been defined. In this study, we performed trios‐based whole‐exome sequencing in a cohort of 356 unrelated cases with partial epilepsy without acquired causes and identified CELSR1variants in six unrelated cases. The variants included one de novo heterozygous nonsense variant, one de novo heterozygous missense variant, and four compound heterozygous missense variants that had one variant was located in the extracellular region and the other in the cytoplasm. The patients with biallelic variants presented severe epileptic phenotypes, whereas those with heterozygous variants were associated with a mild epileptic phenotype of benign epilepsy with centrotemporal spikes (BECTS). These variants had no or low allele frequency in the gnomAD database. The frequencies of the CELSR1variants in this cohort were significantly higher than those in the control populations. The evidence from ClinGen Clinical‐Validity Framework suggested a strong association between CELSR1variants and epilepsy. These findings provide evidence that CELSR1is potentially a candidate pathogenic gene of partial epilepsy of childhood.

Distributed electric propulsion (DEP) uses multiple propellers driven by motors distributed along the leading edge of the wing to produce beneficial aerodynamic interactions. However, the wing will be in the sliding flow of the propeller and the lift and drag characteristics of the wing will change accordingly. The performance of the propeller will also be affected by the wing in its rear. In this paper, combined with wind tunnel tests, the low Reynolds aerodynamic properties of multiple DEP structures are numerically simulated by solving the Reynolds averaged Navier-Stokes (RANS) equation of multiple reference frames (MRF) or slip grid technology. The results demonstrate that the lift and drag of DEP increase in all cases, with the magnitude depending on the angle of attack (AOA) and the relative positions of propellers and wing. When the AOA is less than 16° (stall AOA), the change of lift is not affected by it. By contrast, when the AOA is greater than 16° the L/D(lift-to-drag ratio) of the DEP system increases significantly. This is because the propeller slipstream delays laminar flow separation and increases the stall AOA. At the same time, the inflow and the downwash effect, which is generated on both sides of the rotating shaft, result in the actual AOA of the wing being greater than the free flow AOA with a fluctuation distribution of the lift coefficient along the span. Also, for the propeller in the DEP, the blocking effect of the wing and the vortex of the trailing edge of the wing result in a significant increase in thrust.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer with a high risk of metastasis and recurrence. Although chemotherapy has greatly improved the clinical outcome of TNBC patients, acquired drug resistance remains a huge challenge for TNBC treatment. Breast cancer stem cells (BCSCs) play a critical role in breast cancer development, metastasis, recurrence, and chemotherapy resistance. Thus, it is of great importance to decipher the underlying molecular mechanism of BCSCs regulation for TNBC drug resistance. In this study, we demonstrate that the F-box protein FBXL2 is a critical negative regulator of BCSCs stemness and that downregulation of FBXL2 plays a causal role in TNBC drug resistance. We show that expression levels of FBXL2 significantly influence CD44high/CD24lowsubpopulation and the mammosphere formation ability of TNBC cells. Ectopic expression of FBXL2 inhibits initiation of TNBC and overcomes paclitaxel resistance in vivo. In addition, activation of FBXL2 by nebivolol, a clinically used small-molecule inhibitor of the beta-1 receptor, markedly overcomes BCSCs-induced paclitaxel resistance. Mechanistically, we show that FBXL2 targets transcriptional factor E47 for polyubiquitin- and proteasome-mediated degradation, resulting in inhibition of BCSC stemness. Clinical analyses indicate that low expression of FBXL2 correlates with high expression of E47 as well as with high stemness features, and is associated with poor clinical outcomes of breast cancer patients. Taken together, these results highlight that the FBXL2-E47 axis plays a critical role in the regulation of BCSC stemness and paclitaxel resistance. Thus, targeting FBXL2 might be a potential therapeutic strategy for drug-resistant TNBC.

With the aim of developing novel annulations via ketene intermediates, allenyl imide and alkynoates bearing good leaving groups are used for their function in a tandem conjugate addition–elimination reaction (SN2′ type) promoted by nucleophilic phosphine catalysts. By utilizing thioamides as 1S,3N-bis-nucleophiles, [3+3] and [3+2] annulations have been established to allow rapid access to 1,3-thiazin-4-ones and 5-alkenyl thiazolones in high yields, respectively. Furthermore, the possible reaction mechanisms are proposed on the basis of deuterium labeling experiments and density functional theory calculations.

A precise and fast optical thermometer based on a tunable diode laser absorption spectroscopy is developed for breath diagnostics with relevance to noncontact body temperature measurement. As water vapor (H_2O) is the major component in human breath, two optimal absorption lines of H_2O at 1392 nm and 1371 nm are selected for sensitive body temperature measurement by systematically investigating the near-infrared spectral database. The optical thermometer is developed using two distributed feedback diode lasers with the time-division multiplexing technique to achieve real-time measurement. The sensor performance such as accuracy, repeatability, and time response is tested in a custom-designed gas cell with its temperature controlled in the range of 20°C–50°C. By measuring the test air with different water concentrations, the sensor consistently shows a quadratic response to temperature with an R-squared value of 0.9998. Under the readout rate of 1 s, the sensor achieves a measurement precision of 0.16°C, suggesting its potential applications to fast, accurate, and noncontact body temperature measurements.

The paper proposed a practice teaching mode by making analysis on Didi data set. There are more and more universities have provided the big data analysis courses with the rapid development and wide application of big data analysis technology. The theoretical knowledge of big data analysis is professional and hard to understand. That may reduce students' interest in learning and learning motivation. And the practice teaching plays an important role between theory learning and application. This paper first introduces the theoretical teaching part of the course, and the theoretical methods involved in the course. Then the practice teaching content of Didi data analysis case was briefly described. And the study selects the related evaluation index to evaluate the teaching effect through questionnaire survey and verify the effectiveness of teaching method. The results show that 78% of students think that practical teaching can greatly improve students' interest in learning, 89% of students think that practical teaching can help them learn theoretical knowledge, 89% of students have basically mastered the method of big data analysis technology introduced in the course, 90% of students think that the teaching method proposed in this paper can greatly improve students' practical ability. The teaching mode is effective, which can improve the learning effect and practical ability of students in data analysis, so as to improve the teaching effect.