Search

Abstract Pancreatic ductal adenocarcinoma (PDA) mortality is primarily attributed to metastasis and chemotherapy resistance. In this research, the long non-coding RNA MACC1-AS1 was studied, playing a significant role in regulating lipid oxidation processes. This regulation could further lead to the inhibition of ferroptosis induced by chemotherapeutic drugs, making it a contributing factor to gemcitabine resistance in PDA. In both gemcitabine-resistant PDA patients and mouse models, the elevated expression level of MACC1-AS1 in the tumors was noted. Additionally, overexpression of MACC1-AS1 in pancreatic cancer cells was found to enhance tolerance to gemcitabine and suppress ferroptosis. Proteomic analysis of drug-resistant pancreatic cells revealed that overexpressed MACC1-AS1 inhibited the ubiquitination degradation of residues in the protein kinase STK33 by MDM4. Furthermore, its accumulation in the cytoplasm activated STK33, further activating the ferroptosis-suppressing proteins GPX4, thereby counteracting gemcitabine-induced cellular oxidative damage. These findings suggested that the long non-coding RNA MACC1-AS1 could play a significant role in the ability of pancreatic cancer cells to evade iron-mediated ferroptosis induced by gemcitabine. This discovery holds promise for developing clinical therapeutic strategies to combat chemotherapy resistance in pancreatic cancer.

Abstract In this article, a method is proposed for the characterisation of epoxy resin thermal and hygrothermal ageing based on microwave resonator with interdigital‐capacitor‐shaped defected ground structure (IDCS‐DGS), which can realise rapid and simple non‐destructive testing of the ageing degree of epoxy resin materials. The resonant frequency of IDCS‐DGS was proved to decrease with the increase of dielectric constant of the around material by means of simulation. The breakdown test at high voltage showed the deterioration of epoxy resin after hygrothermal ageing, which is caused by moisture absorption and hydrolysis process. In addition, thermal ageing also caused a decline in the insulation performance of epoxy resin samples. Accelerated oxidation of epoxy resin samples at high temperatures produces polar molecules that increase the dielectric constant of the samples. As for the hygrothermal ageing samples, the entrance of polar water molecules will increase the dielectric constant of epoxy resin, and thus make an effect on the resonant frequency of IDCS‐DGS. The tests of transmission performance show that after the hygrothermally aged epoxy resin samples were put on the microwave sensor, the resonant frequency decreased continuously with hygrothermal ageing time, and the deviations of resonant frequency are highly consistent with the weight variation rate of the samples.

Abstract The impact of assimilating ground‐based radar reflectivity on the rainband structure and secondary eyewall formation (SEF) of Hurricane Matthew (2016) is investigated within the framework of the Hurricane Weather Research and Forecasting model and its hybrid three‐dimensional ensemble‐variational data assimilation (DA) system. Compared to the control experiment (no radar reflectivity DA), the radar reflectivity DA experiment shows a clear signal of concentric eyewall and eyewall replacement cycle. Results demonstrate that radar reflectivity DA improves the stratiform rainband analysis, resulting in the mid‐level cooling associated with mesoscale descending inflow (MDI). The MDI further contributes to the low‐level acceleration maximum with boundary layer dynamics and triggers new convective updrafts in the SEF region. Momentum budget analysis also suggests that the mean vertical advection of absolute angular momentum plays an important role in the local momentum tendency in the SEF region in Hurricane Matthew (2016).

Pulmonary hypertension (PH) is a malignant disease with progressive increase of pulmonary vascular pressure, which eventually leads to right heart failure. More and more evidences show that immune cells and inflammation play an important role in the occurrence and development of PH. In the context of pulmonary vascular diseases, immune cells migrate into the walls of the pulmonary vascular system. This leads to an increase in the levels of cytokines and chemokines in both the bloodstream and the surrounding tissues of the pulmonary vessels. As a result, new approaches such as immunotherapy and anti-inflammatory treatments are being considered as potential strategies to halt or potentially reverse the progression of PH. We reviewed the potential mechanisms of immune cells, cytokines and chemokines in PH development. The potential relationship of vascular cells or bone morphogenetic protein receptor 2 (BMPR2) in immune regulation was also expounded. The clinical application and future prospect of immunotherapy were further discussed.

Accurate wind power prediction is essential to optimize the wind power scheduling and maximize the profits. However, the inertia and time-varying property of the wind speed pose a challenge to the wind power prediction task. The existing prediction models fail to efficiently mitigate the negative influence of these properties on the prediction results. Therefore, their generalization abilities require a further improvement. In this paper, the historical wind power segment is decomposed into sub-signals, which are considered as the fluctuation patterns of the wind power series, the variable support then is employed to describe the inertia and time-varying properties for the fluctuation patterns. The component-attention mechanism is introduced to formulate the correlation-relationship between each fluctuation pattern and the historical wind power segment, this mechanism is used to replace the self-attention mechanism for the Transformer model. A hybrid model combined VMD and Transformer is utilized for predicting the future wind power. Experiments performed on an actual wind power series validate the efficiency of the proposed model.

A GTPase binding protein, Ras interacting protein 1 (RASIP1), has been reported with a tumor-promoting role in lung cancer cells, and its role in lymphoma remains unknown. The analysis of medical databank shows that RASIP1 is upregulated in diffuse large B-cell lymphoma (DLBCL) specimens. In this article, we demonstrated that RASIP1 is highly expressed in DLBCL cell lines, compared with primary B cells. The gain- and loss-of-function experiments were performed to investigate the effects of RASIP1 on DLBCL cells. CCK-8, flow cytometry, western blot, and transwell assays demonstrated that silence of RASIP1 inhibited proliferation, cell cycle transition, and invasion and induced significant apoptosis in DLBCL cells, and ectopic expression of RASIP1 played opposite roles. Xenograft results revealed that RASIP1 facilitated the growth of DLBCL cells in vivo. These findings suggest that RASIP1 may be required for malignancy of DLBCL cells. In addition, we also found that the expression of RASIP1 was negatively regulated by forkhead box O3 (FOXO3), which has been reported to suppress the proliferation of DLBCL cells. Our results indicate that FOXO3 is bound to the promoter sequence of RASIP1 and inhibits its transcription. The suppressive effects of FOXO3 on proliferation and invasion of DLBCL cells were neutralized by RASIP1. In conclusion, we demonstrate that FOXO3 negatively regulated RASIP1 facilitates growth and invasion of DLBCL cells, provides novel diagnostic markers and therapeutic targets for DLBCL in clinic.

Preeclampsia is a specific disease during pregnancy and is a significant factor in the increased mortality in perinatal women. Gut microbiota, an intricate and abundant microbial community in the digestive tract, is crucial for host metabolism, immunity, and nutrient absorption. The onset and progression of preeclampsia are closely correlated with the changes in maternal gut microbiota. Research purpose was to compile the existing bits of present scientific data and to close the gap in the knowledge of changes in gut microbiota in preeclampsia and their association with preeclampsia. We searched studies from two electronic databases (PubMed and Web of Science) included from 2014 to 2023. This review is divided into three parts. In the first part, the author elaborates longitudinal differences of maternal gut microbiota during different gestation periods. In the second part, we discuss that gut microbiota can lead to the occurrence of preeclampsia by systemic immune response, influencing the release of active peptides, short-chain fatty acids, trimethylamine-N-oxide (TMAO) and other metabolites, vascular factors and Microorganism-immune axis. In the third part, we proposed that a high-fiber diet combined with drugs and microecological regulators may be therapeutic in enhancing or preventing the emergence and evolution of preeclampsia, which needs further exploration. Although the pathogenesis of preeclampsia is still nebulous and there is no clear and valid clinical treatment, our study provides new ideas for the pathogenesis, prevention and treatment of preeclampsia.

Tropical cyclone rapid intensification (RI) prediction still remains a big international challenge in numerical weather prediction. Hurricane Matthew (2016) underwent extreme and non-classic RI, intensifying from a Category 1 storm to a Category 5 hurricane within 24 h under a strong vertical shear environment. However, most models failed to capture this RI, and limited or no inner core, and outflow observations were assimilated in the NWS operational HWRF Model before the onset of RI for Matthew (2016). The goals of the study are to (1) explore the best way to assimilate the High-Density Observations (HDOB, including FL and SFMR) and AMV data; (2) study the impact of assimilating these observations on the analysis of both the inner-core and outflow structures; and (3) examine the impact of assimilating these data on the prediction of RI for Matthew. The main results are as follows: (1) With proper pre-processing of the HDOB observations and by using a 4DEnVar method, the inner-core structure analysis was improved. And the RI prediction is more consistent with the best track without spin-down for the first 24 h. Assimilating CIMMS AMV observations on top of the HDOB observations further improves both the track and intensity forecasts. Specifically, both the magnitude and timing of the peak intensity are further improved. (2) Diagnostics are conducted to understand how the assimilation of these different types of observations impacts RI prediction. Without assimilating HODB and AMV data, baseline experimentover-predict the intensification rate during the first 18 h, but under-predict RI after 18 h. However, the assimilation of FL and SFMR and CIMMS AMV correctly weakens the upper-level outflow and improves the shear-relative structure of the inner-core vortex, such as reducing the low-level moisture in the downshear left quadrant. The deep convection on the downshear side is weaker than baseline for the first 18 h but keeps enhancing, later moving cyclonically to the USL quadrant, and then causes more subsidence warming, maximizing in the USL quadrant and the maximum wind increases faster. Moreover, the rapid intensification rate is much more consistent with the best track and the forecast skill of RI is improved. Therefore, 4DEnVar assimilation with proper pre-processing of the high-density observations can indeed correct the shear-relative moisture and structural distributions of both the inner core and environment for TCs imbedded in the stronger shear, which is important for shear-TC RI prediction.

Oocytes are efficient at reprogramming terminally differentiated cells to a totipotent state. Nuclear transfer techniques can exploit this property to produce cloned animals. However, the overall efficiency is low. The use of umbilical cord mesenchymal stem cells (UC-MSCs) as donor nuclei may increase blastocyst rates, but the exact reasons for this remain unexplored. A single-cell transcriptomic approach was used to map the transcriptome profiles of eight-cell embryos that were in vitro-fertilized and handmade-cloned using umbilical cord mesenchymal stem cells and fibroblasts as nuclear donors. Differences were examined at the chromatin level, the level of differentially expressed genes, the level of histone modifications and the level of DNA methylation. This research provides critical information regarding the use of UC-MSCs as a preferred donor nucleus for nuclear transfer techniques. It also offers unique insights into the mechanism of cellular reprogramming.

Vitrification is a crucial method for preserving animal germ cells. Considering the increased oxidative stress and organelle damage incurred, it is still necessary to make the process more efficient for oocytes. As the energy source of oocytes, mitochondria are the most abundant organelle in oocytes and play a crucial role in their maturation. Here, we found that Mito-TEMPO, a mitochondria-targeted antioxidant, could efficaciously improve the oxidative stress injury of vitrified oocytes by recovering mitochondrial function via the mitochondrial respiratory chain. It was observed that Mito-TEMPO not only improves oocyte viability and meiosis but also maintains spindle structure. A subsequent study indicated that Mito-TEMPO effectively rescued mitochondrial dysfunction and attenuated vitrification-induced oxidative stress. Further investigation revealed that Mito-TEMPO regulates vitrified oocytes’ intracellular Ca2+ homeostasis and ATP content and provides strong antioxidant properties. Additionally, an analysis of the transcriptome at the single-cell level revealed that the respiratory chain mediates the beneficial effect of Mito-TEMPO on vitrified oocytes. Overall, our findings indicate that supplementing oocytes with Mito-TEMPO is an effective method to shield them from the damage caused by vitrification. In addition, the beneficial effects of Mito-TEMPO on vitrified sheep oocytes could inspire further investigations of the principles underlying oocyte cryobiology in other animals.

Abstract 2D hybrid organic–inorganic perovskites (HOIPs) are commonly found under subcritical cyclic stresses and suffer from fatigue issues during device operation. However, their fatigue properties remain unknown. Here, the fatigue behavior of (C4H9‐NH3)2(CH3NH3)2Pb3I10, the archetype 2D HOIP, is systematically investigated by atomic force microscopy (AFM). It is found that 2D HOIPs are much more fatigue resilient than polymers and can survive over 1 billion cycles. 2D HOIPs tend to exhibit brittle failure at high mean stress levels, but behave as ductile materials at low mean stress levels. These results suggest the presence of a plastic deformation mechanism in these ionic 2D HOIPs at low mean stress levels, which may contribute to the long fatigue lifetime, but is inhibited at higher mean stresses. The stiffness and strength of 2D HOIPs are gradually weakened under subcritical loading, potentially as a result of stress‐induced defect nucleation and accumulation. The cyclic loading component can further accelerate this process. The fatigue lifetime of 2D HOIPs can be extended by reducing the mean stress, stress amplitude, or increasing the thickness. These results can provide indispensable insights into designing and engineering 2D HOIPs and other hybrid organic–inorganic materials for long‐term mechanical durability.

Introduction: In this paper we introduce an adult-sized FE full-body HBM for seating comfort assessments and present its validation in different static seating conditions in terms of pressure distribution and contact forces.Methods: We morphed the PIPER Child model into a male adult-sized model with the help of different target sources including his body surface scans, and spinal and pelvic bone surfaces and an open sourced full body skeleton. We also introduced soft tissue sliding under the ischial tuberosities (ITs). The initial model was adapted for seating applications with low modulus soft tissue material property and mesh refinements for buttock regions, etc. We compared the contact forces and pressure-related parameters simulated using the adult HBM with those obtained experimentally from the person whose data was used for the model development. Four seat configurations, with the seat pan angle varying from 0° to 15° and seat-to-back angle fixed at 100°, were tested.Results: The adult HBM could correctly simulate the contact forces on the backrest, seat pan, and foot support with an average error of less than 22.3 N and 15.5 N in the horizontal and vertical directions, which is small considering the body weight (785 N). In terms of contact area, peak, and mean pressure, the simulation matched well with the experiment for the seat pan. With soft tissue sliding, higher soft tissue compression was obtained in agreement with the observations from recent MRI studies.Discussion: The present adult model could be used as a reference using a morphing tool as proposed in PIPER. The model will be published openly online as part of the PIPER open-source project (www.PIPER-project.org) to facilitate its reuse and improvement as well as its specific adaptation for different applications.

Abstract This study introduces a simultaneous multiscale data assimilation method by implementing model space spatial scale‐dependent localization (SDL) and variable‐dependent localization (VDL) within an ensemble variational system. This method updates all resolved scales by assimilating all observations at once. The impact of such an approach is examined by a series of radar data assimilation experiments. Single‐observation experiments show that SDL concurrently and more properly updates the storm and its ambient environments compared to a traditional single scale localization (SSL) for radar data assimilation. Including VDL on top of SDL (SDLVDL) realistically decreases the spatial coverage and intensity of moisture increments compared to SDL. Comparisons are then performed on the analyses and forecasts of the 8 May 2003 Oklahoma City supercell storm. Results show that SDL improves the analyses and forecasts during the data assimilation cycling by producing more realistic enhanced low‐level convergences than SSL. SDLVDL obtains more accurate analyses and subsequent forecasts for moisture than SDL. SDLVDL yields the best performance in reflectivity forecasts and storm maintenance. Compared to SSL, SDL has higher forecast skills before 2230 UTC and produces degraded forecasts in the later lead time.

Abstract This study evaluates simulated radiance forecasts from a series of controlled experiments consisting of FV3‐LAM forecasts with different configurations of model physics and vertical resolution. The forecasts were produced during the 2020 Hazardous Weather Testbed Spring Forecasting Experiments on the same forecast cases. The evaluation includes grid‐point, neighborhood‐based and object‐based verification. The experiments include forecasts that were identical except for the physics (EMC‐LAM vs. EMC‐LAMx), vertical resolution (EMC‐LAMx vs. NSSL‐LAM), or combined initial conditions, physics and vertical resolution (GSL‐LAM). It is found that the EMC‐LAM generally provided better simulated radiance forecasts than the other three configurations at most forecast lead times, due to its unique physics configuration. All configurations generally over‐forecasted high level clouds. EMC‐LAM reduced the over‐forecasting of high clouds, but also under‐forecasted the coverage of mid‐level clouds. In contrast, at early lead times the EMC‐LAM had relatively poor performance relative to the other forecasts. Furthermore, EMC‐LAM was an outlier in terms of the vertical structure of clouds. It is also found that the NSSL‐LAM consistently improved upon the EMC‐LAMx, which had fewer vertical levels than NSSL‐LAM. Compared to EMC‐LAMx, NSSL‐LAM had less cloud over‐forecasting bias, especially with small cloud objects, and less overall error. The differences between EMC‐LAMx and GSL‐LAM were generally much smaller than the differences between EMC‐LAMx and EMC‐LAM/NSSL‐LAM. Finally, it is found that a non‐linear bias correction conditioned on symmetric brightness temperature reduced the overall root‐mean‐square error by about a factor of 2 while improving the unrealistic vertical structure of clouds in the EMC‐LAM.

Abstract In order to achieve rapid and simple non‐destructive testing of water trees in materials, a novel water tree characterisation method based on the complementary split ring resonators (CSRR) was proposed. The characteristics of circular CSRR and rectangular CSRR were analysed in high‐frequency electromagnetic simulation software. The resonant frequency of CSRR was found to be correlated to the dielectric constant of the materials. In addition, the lumped equivalent circuit parameters of CSRRs were also calculated and simulated. The results of electromagnetic simulations and circuit simulations achieved good consistency. In the experimental part, sensors based on the two kinds of CSRRs were fabricated and were used to detect the water tree defects in low‐density polyethylene samples. The experiment results showed that the method of using CSRR sensors to detect water tree is feasible.

Abstract Ensemble‐based convective‐scale radar data assimilation commonly suffers from an underdispersive background ensemble. This study introduces a multivariate additive‐inflation method to address such deficiency. The multivariate additive inflation (AI) approach generates coherent random perturbations drawn from a newly constructed convective‐scale static background error covariance matrix for all state variables including hydrometeors and vertical velocity. This method is compared with a previously proposed univariate AI approach, which perturbs each variable individually without cross‐variable coherency. Comparisons are performed on the analyses and forecasts of the 8 May 2003 Oklahoma City tornadic supercell. Within assimilation cycles, the multivariate approach is more efficient in increasing reflectivity spread and thus has a reduced spinup time than the univariate approach; the additional inclusion of hydrometeors and vertical velocity results in more background spread for both reflectivity and radial velocity. Significant differences among AI experiments also exist in the subsequent forecasts and are more pronounced for the forecasts initialized from the earlier assimilation cycles. The multivariate approach yields better forecasts of low‐level rotation, reflectivity distributions, and storm maintenance for most lead times. The additional inclusion of hydrometeor and vertical velocity in the multivariate method is beneficial in forecasts. Conversely, the additional inclusion of hydrometeor and vertical velocity in the univariate method poses negative impacts for the majority of forecast lead times.

To improve the modeling accuracy and digital predistortion compensation effect, this paper proposed a kind of polynomial based spline adaptive filter (SAF) power amplifier (PA) behavioral modeling method. The proposed model can solve the shortcomings of the traditional memory polynomial model (MP), such as higher nonlinear order, highly coefficient calculation difficulty, poor hardware stability, low modeling accuracy and poor digital predistortion compensation. Meanwhile, the proposed SAF based model can avoid the pseudo-inversion operation of the matrix when calculating the coefficients through the indirect learning structure, which can improve the compensation effect of digital predistortion. In order to compare the performance of the different models, the modeling processes of original filtering model, MP model and dynamic variation reduction (Dynamic Deviation Reduction, DDR) model based on SAF method (OSAF, MPSAF, DDRSAF) are presented respectively. The proposed models are verified by a class F PA, which are stimulated by a set of measured input and output data of an LTE signal with 20 MHz bandwidth. The measured results shows that compared with the conventional MP model, the proposed DDRSAF model presents the best model performance and improves the modeling accuracy by 6.6dB while maintaining the similar computational complexity, and the ACPR compensation effect increases by 19.58dB and 20.47dB respectively, which have the important significance for practical engineering application.

Given the influence of flow instability, parameter uncertainty, and unpredictable disturbances in electro-hydraulic lifting systems, high-precision position control for electro-hydraulic lifting systems is challenging to achieve. This study proposes an observer–sliding mode control strategy to improve the control accuracy of the tractor electro-hydraulic lifting system. Firstly, the principle of the electro-hydraulic hoisting system is analyzed. Secondly, a mathematical model of the electro-hydraulic hoisting system is established, and the electro-hydraulic hoisting system is reduced to design an observer to achieve a real-time evaluation of the unknown system state and disturbance. The observer and the sliding mode control are then integrated into a controller to improve system response. Theoretical analysis demonstrates that the controller ensures that the actuator can achieve the desired control effect even under disturbing effects. Finally, a joint AMESim–MATLAB simulation and conducting pilot studies are carried out to compare the observer–sliding mode control with PID (Proportion–Integral–Derivative) control and sliding mode control. At the same time, in the process of the simulation and test, the symmetric structure as the electro-hydraulic lifting system was used to build a ploughing depth simulation system (changes in the hydraulic cylinder thrust simulate changes in ploughing depth values). The results show that the proposed observer–sliding mode control strategy can achieve a better position and pressure tracking and parameter change robustness than PID control and sliding mode control.

Given the large range of resolvable space and time scales in large-domain convection-allowing for ensemble forecasts, there is a need to better understand optimal initial-condition perturbation strategies to sample the forecast uncertainty across these space and time scales. This study investigates two initial-condition perturbation strategies for CONUS-domain ensemble forecasts that extend into the two-day forecast lead time using traditional and object-based verification methods. Initial conditions are perturbed either by downscaling perturbations from a coarser resolution ensemble (i.e., LARGE) or by adopting the analysis perturbations from a convective-scale, EnKF system (i.e., MULTI). It was found that MULTI had more ensemble spread than LARGE across all scales initially, while LARGE’s perturbation energy surpassed that of MULTI after 3 h and continued to maintain a surplus over MULTI for the rest of the 36h forecast period. Impacts on forecast bias were mixed, depending on the forecast lead time and forecast threshold. However, MULTI was found to be significantly more skillful than LARGE at early forecast hours for the meso-gamma and meso-beta scales (1–9h), which is a result of a larger and better-sampled ensemble spread at these scales. Despite having a smaller ensemble spread, MULTI was also significantly more skillful than LARGE on the meso-alpha scale during the 20–24h period due to a better spread-skill relation. MULTI’s performance on the meso-alpha scale was slightly worse than LARGE’s performance during the 6–12h period, as LARGE’s ensemble spread surpassed that of MULTI. The advantages of each method for different forecast aspects suggest that the optimal perturbation strategy may require a combination of both the MULTI and LARGE techniques for perturbing initial conditions in a large-domain, convection-allowing ensemble.

Abstract The present study introduces the online non‐linear bias correction for the assimilation of all‐sky GOES‐16 Advanced Baseline Imager (ABI) channel 9 (6.9 μm) radiances in a rapidly cycled EnKF for convective scale data assimilation (DA). This study is the first to explore the use of the radar reflectivity as the anchoring observation for ABI all sky radiance assimilation. The online and offline nonlinear bias correction methods are compared and evaluated for a case of rapidly developing supercells over Oklahoma and Texas. The analysis and background of the online bias correction perform better than the offline approach during the suppression of spurious clouds and the establishment of non‐precipitating and precipitating regions when the supercell storms are observed to develop. The online approach not only improves the analysis and background over the radar anchored region but also the unanchored non‐precipitating regions compared to the offline approach. Both quantitative and subjective verification of the deterministic forecasts showed consistent superior performance from the online bias correction over the offline approach. Diagnostics reveal that the online bias correction retains useful information in the innovation, which in turn improves subsequent analysis, background and background ensemble spread for both the thermodynamic and dynamic fields. The effect is accumulated during the DA cycling that is responsible for the superior analysis and forecast of the supercells.

Run-of-mine fragmentation is an important aspect of mine productivity optimization, as it affects all mine-to-mill processes. The current blasting fragmentation calculation methods do not consider the 3D geometric information. Therefore, their calculation results are imprecise. 3D laser scanning is a technique for extracting the 3D geometric information of an object by constructing a 3D point cloud model, with which extra information on the geometrical characteristics of an object could be captured than with the technique of 2D image processing. In this paper, 3D laser scanning technology was utilized for the calculation of the rock blocks on the surface of a muck pile, and the information about the surface blocks was utilized as the samples for the statistical estimation of blasting fragmentation of muck pile (BFMP). Monte Carlo simulation was utilized as the statistical estimation method for the BFMP. In the lab experiment, results from 2D image processing technique and from 3D laser scanning technique combined with statistical estimate were compared with the physical measurements utilizing a water tank, which show that results with 3D laser scanning are more similar to the physical measurement. Finally, the applicability of 3D laser scanning technology combined with statistical methods to the calculation of blast fragmentation was estimated through field tests in Biesikuduke and Santanghu mine, two open-pit coal mines in Xinjiang Province of western China. Results show that the accuracy of the statistical estimation results of BFMP has a particle size deviation of 1–3 cm.

In this article, a novel digital predistortion (DPD) model based on complex-valued pipelined Chebyshev functional link recurrent neural network (CPCFLRNN) for joint compensation of wideband transmitter distortions and impairments is proposed. The functional link neural network (FLNN) model has attracted much attention from scholars, and many improved models using this structure, such as Chebyshev FLNN, have been applied in the DPD of power amplifiers (PAs). However, these existing neural network models cannot deal with complex-valued input signals simultaneously, and the real-valued model structure will introduce cumbersome training algorithm and result in a long training time. The pipelined recurrent neural network (PRNN) has been successfully applied to nonlinear signal prediction because of its excellent ability for dealing with nonlinear nonstationary signals. Therefore, the PRNN model containing Chebyshev structure is extended to complex domain for the first time to obtain the CPCFLRNN model for DPD application. Considering the strong correlation of in-phase and quadrature phase (I/Q) components of the transmitter signal, the real time recurrent learning (RTRL) algorithm based on fully complex activation function is selected and extended to complex domain to obtain the complex-valued RTRL (CRTRL) algorithm for CPCFLRNN model training. A GaN PA was employed to verify the effectiveness of the proposed models. And the input signal is a 30MHz LTE signals which consists of I/Q imbalance and dc offsets. The experimental results show that the proposed CPCFLRNN model have more accurate modeling effect and better linearization performance compared with the conventional DPD models.

The magnesium lithium thermal control oxidation is a commonly used conductive anti-corrosion treatment method for aerospace. The corrosion behaviors of thermal control oxidation films for LA103Z alloys were studied in 3.5% NaCl solution. The corrosion characteristics with different immersion time were characterized by using scanning electron microscopy, energy spectroscopy, and electrochemical methods. The results showed that the corrosion of Mg-Li alloy with chemical oxidation film starts from pitting corrosion, gradually expands in depth in the early stage, forms corrosion holes, and then gradually develops into river-like morphology. In the last stage, the increasing corrosion products slow down the corrosion rate and gradually covers the entire sample surface. The corrosion product mainly consists of MgO, LiF, and MgCl2. Combined with the electrochemical characteristics, the corrosion mechanism was investigated.

In this study, a solid-liquid mixing system model was established to simulate the coexistence of floating particles (FP) and sinking particles (SP) in the early stage of anaerobic digestion, and the mixing effect and energy consumption of the system were investigated. Four typical blades were selected to compare the solid phase distribution of straw particles under different blade stirring, and the distribution of FP and SP in the coexistence system was clarified. Then the combination of full-factorial design and numerical simulation was applied to compare the effect of blade diameter and blade width on particle mixing, which was better than that of immersion depth. A comprehensive equation was further established to balance the weight between the particle mixing effect and energy consumption and improve the blade design. It provided theoretical support for the design and amplification of subsequent stirring equipment.

Mobile cloud computing provides applications of cloud computing technology on mobile Internet. In the era of the 5G networks, mobile cloud computing offers the possibility of heavy computational in parallel through different mobile terminals. This also offers us to use mobile cloud computing to analyze fluctuations in user buying incentives over the course of a year. In various business scenarios, the purchase incentive of the public is often considered as being controlled by multiple factors and changes dramatically during holiday seasons. This paper proposed an evolutionary algorithm for monitoring purchase incentive of the public which can be distributed in mobile cloud computing. In this paper, we demonstrate that the public's shopping behavior of a commodity is a consequence of a collective behavior propagating through a social network and can be modeled as a simple ODEs model. Then, based on this new model, we develop an extended differential evolution algorithm that is deployed on mobile terminals and combined with the 5G network computing to estimate public incentives from historical sales datasets. The results suggest that this method can successfully monitor the public's purchase incentive. In addition, the overall purchase incentive changes dramatically during holiday seasons but fluctuates with similar patterns every year.

The Micro Unmanned Robot Observation Network (MURON) is a planned in-situ observation network over the surface of West Pacific Ocean, and it is designed to sample high spatial and temporal resolution observations of wind and mass fields over the ocean surface. The impacts of MURON observations for Tropical Cyclone (TC) intensity forecast are investigated using Observation System Simulation Experiments. The regional Ensemble Kalman Filter (EnKF) system of Gridpoint Statistical Interpolation is used with the Advanced Research version of the Weather Research and Forecasting model to conduct OSSEs for typhoon Haiyan (2013) while Haiyan goes through rapid intensification. Assimilating MURON observations improves the TC structure and intensity analysis and forecast. The intensity forecast is improved largely due to the correction of initial vorticity and vertical transport of mass flux. The improvement of intensity forecast is attributed largely to the assimilated MURON wind observations when Haiyan is at the tropical disturbance stage, and then by the MURON mass observations when Haiyan enters the tropical storm stage. In addition, our results show that the quality of moisture analysis is sensitive to the choice of the moisture control variable (CV) in the EnKF system. Using the default pseudo relative humidity (PRH) as the moisture CV degrades the accuracy of the moisture analysis. This is likely due to the neglect of updated temperature field during the nonlinear conversion from the PRH CV to the mixing ratio variable and due to the larger deviation of the PRH from Gaussian distribution. The use of mixing ratio moisture CV mitigates these problems.

The initial conditions for hurricanes are difficult to improve due to the lack of inner-core observations over the ocean. An enhanced atmospheric motion vectors (AMVs) dataset from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) has recently become available and covers the inner-core region of hurricanes. This study tries to find an optimal data assimilation (DA) configuration to better utilize the observations for the Hurricane Weather Research and Forecasting (HWRF) model with hurricane Irma (2017). The results show that (a) without vortex relocation (VR), the hourly three-dimensional ensemble–variational (3DEnVar) outperforms the 6-hourly 3DEnVar DA configuration in almost all aspects, except for long-term track predictions. The assimilation of inner-core AMVs further improves the corresponding intensity forecasts for both hourly and 6-hourly 3DEnVar DA. (b) The 6-hourly 3DEnVar DA predictions with VR can be significantly improved upon their non-VR counterparts. However, VR can be detrimental to hourly 3DEnVar minimum sea level pressure (MSLP) predictions due to the spuriously enhanced upper-level warm core. The improvements from the assimilation of additional inner-core AMVs are thus limited under hourly VR. Reducing VR frequency can reduce the detrimental effects of hourly 3DEnVar. (c) An updated observation error profile for the enhanced AMVs benefits the hourly 3DEnVar DA more than the 6-hourly 3DEnVar DA.

In view of the near slope blasting in Barun open-pit mine, which has merged sublevel mining, the operation safety conditions of middle-sized and large equipment in the second phase expansion are poor and need urgent improvement. To increase the efficiency of expansion and reduce costs, a 24-m-high bench and large spacing parameter for loosening blasting are proposed. The analysis of the physical mechanism of the stress wave attenuation in the rock indicates that the cylindrical charge is equivalent to several spherical charges. Considering the pressure attenuation, reflection, transmission, and superposition of the spherical charge after the equivalence, a double exponential function correction equation of the stress wave attenuation is obtained based on the Mises strength criterion. The stress of any point in the rock medium with various spacing parameter is obtained by calculation. ANSYS/LS-DYNA was used to simulate and study the stress distribution of a 24-m-high bench with various spacing parameter. Meanwhile, the accuracy of the correction equation was verified. The parameters of the high-bench blasting with good effect and low cost were determined to be 15 m × 5.5 m, and field tests were carried out. Results show that the large spacing parameter for 24-m-high bench loosening blasting in Barun open-pit mine is efficient and economical in medium-hard rock blasting. This study provides a reference for the practical exploration of the expansion of high benches in open-pit mines in China. The calculation error of the corrected double exponential function is near the numerical simulation result. It is suitable for all kinds of professional designers.

Current highly automated vehicle concepts include reclined seat layouts that could allow occupants to relax during the drive. The main objective of this study was to investigate the effects of seat pan and pelvis angles on the kinematics and injury risk of a reclined occupant by numerical simulation of a frontal sled test. The occupant, represented by a detailed 50th percentile male human body model, was positioned on a semi-rigid seat. Three seat pan angles (5, 15, and 25 degrees from the horizontal) were used, all with a seatback angle of 40 degrees from the vertical. Three pelvis angles (60, 70, and 80 degrees from the vertical), representing a nominal and two relaxed sitting positions, were used for each seat pan angle. The model was restrained using a pre-inflated airbag and a three-point seatbelt equipped with a pretensioner and a load limiter before being subjected to two frontal crash pulses. Both model kinematic response and predicted injury risk were affected by the seat pan and the pelvis angles in a reclined seatback position. Submarining occurrence and injury risk increased with lower seat pan angle, higher pelvis angle, and acceleration pulse severity. In some cases (in particular for a 15 degrees seat pan), a small variation in seat pan or pelvis angle resulted in large differences in terms of kinematics and predicted injury. This study highlights the potential effects of the seat pan and pelvis angles for reclined occupant protection. These parameters should be assessed experimentally with volunteers to determine which combinations are most likely to be adopted for comfort and with post mortem human surrogates to confirm their significance during impact and to provide data for model validation. The sled and restraint models used in this study are provided under an open-source license to facilitate further comparisons.

Objectives This study set out to analyze the difference of heat shock protein 27 (HSP27) and its phosphorylation in patients with lower extremity arteriosclerosis obliterans (LEASO) at different stages. This research also examined their clinical significance in this disease. Methods Blood samples from 60 patients with LEASO were collected and divided into two groups according to ankle-brachial index (ABI): group A (ABI ≤ 0.43) and group B (ABI > 0.43). The expression of HSP27 in each stage of Fontaine was measured by ELISA, and the difference of HSP27 concentration and ABI between the two groups was analyzed. Meanwhile, three normal femoral artery specimens (normal group) and three atherosclerotic femoral artery specimens (lesion group) were collected, and HSP27 and its Phospho-HSP27 (Ser15), Phospho-HSP27 (Ser78) and Phospho-HSP27 (Ser82) were detected by western blotting. The data of the protein level between the normal group and the lesion group was made a statistical analysis. Results HSP27 concentration in group A was (40.73 ± 15.99) ng/ml, and ABI was 0.26 ± 0.20. HSP27 concentration in group B was (66.30 ± 24.70) ng/ml, and ABI was 0.64 ± 0.20. The protein expression of HSP27 and its phosphorylation in the normal group was 0.82 ± 0.13, 0.66 ± 0.12, 0.91 ± 0.24 and 0.90 ± 0.16, respectively; the protein expression of the lesion group was 0.45 ± 0.08, 0.42 ± 0.09, 0.39 ± 0.12 and 0.58 ± 0.11. Conclusion Patients with higher LEASO Fontaine stage and lower ABI had a lower HSP27 concentration. Serum HSP27 concentration was negatively correlated with the severity of LEASO, while HSP27 concentration was positively correlated with ABI value. The content of HSP27 and its phosphorylation of lesion group is significantly lower than that of normal group, which may be closely related to the occurrence and development of atherosclerosis.

In the process of tunnel excavation, large charge wedge cutting blasting is widely used to improve the effect of cut blasting and speed up the excavation rate, which is tantamount to increasing the construction cost. In order to save economic cost and improve cutting blasting effect, wedge cutting models with five different cutting angles were experimented and studied by using concrete materials on the basis of similarity theory analysis. The relationships among cutting depth, blasting volume, blasting fragment, and cutting angle are studied and deduced by the dimensional analysis method. The polynomial fitting of cutting depth, blasting volume, blasting fragment, and cutting angle is carried out according to the experimental data, and the corresponding fitting formula is obtained. The optimum cutting depth, hole utilization rate, blasting volume, and blasting fragment were obtained when the wedge cutting angle was 67° under the same charge. The values were 1.665 × 10−1 m, 92.5%, 8.390 × 10−3 m3, and 49.07 mm, respectively. With the use of TC4850N type blasting vibration meter, the blasting vibrations on the wedge in four directions are tested and analyzed. The results show that when wedge cutting inclination is 65 degrees, the peak vibration velocity is the minimum and the vibration intensity of the wedge cutting inclined side is generally smaller than that of the vertical side. Considering the cutting depth, blasting volume, blasting fragment, blasting vibration hazard, drilling error, tunneling construction cost, and other factors, the 65°∼69° wedge cutting blasting in engineering practice can improve the blasting tunneling rate and increase economic benefits. The experimental results show that the blasting tunneling rate is increased and the economic benefit is increased with the minimum construction tunneling cost, which has certain engineering significance.

A time-delay estimation method is proposed for single-input single-output (SISO) delay systems. A copula is constructed from uniformly sampled input-output data to build the relationship between the input and output of the system. Taking time-delay as the parameter to be estimated, the logarithm likelihood function is formulated and separated into two parts, i.e., the dependence structure likelihood and the margin-related part. Then, the time-delay is obtained through maximizing the dependence structure likelihood. The highlight of this method is that the structure prior to the studied system is not required to estimate the time-delay. Comparative simulation examples are provided to demonstrate the validity of this method.

Convection-allowing model (CAM) ensembles contain a distinctive ability to predict convective initiation location, mode, and morphology. Previous studies on CAM ensemble verification have primarily used neighborhood-based methods. A recently introduced object-based probabilistic (OBPROB) framework provides an alternative and novel framework in which to re-evaluate aspects of optimal CAM ensemble design with an emphasis on ensemble storm mode and morphology prediction. Herein, we adopt and extend the OBPROB method in conjunction with a traditional neighborhood-based method to evaluate forecasts of four differently configured 10-member CAM ensembles. The configurations include two single-model/single-physics, a single-model/multi-physics, and a multi-model/multi-physics configuration. Both OBPROB and neighborhood frameworks show that ensembles with more diverse member-to-member designs improve probabilistic forecasts over single-model/single-physics designs through greater sampling of different aspects of forecast uncertainties. Individual case studies are evaluated to reveal the distinct forecast features responsible for the systematic results identified from the different frameworks. Neighborhood verification, even at high reflectivity thresholds, is primarily impacted by mesoscale locations of convective and stratiform precipitation across scales. In contrast, the OBPROB verification explicitly focuses on convective precipitation only and is sensitive to the morphology of similarly located storms.

The steady-state assumption commonly used in object-based tracking algorithms may be insufficient to determine the right track when a convective storm goes through a complicated evolution. Such an issue is exacerbated by the relatively coarse output frequency of current convection allowing model (CAM) forecasts (e.g., hourly), giving rise to many spatially well resolved but temporally not well resolved storms that steady-state assumption could not account for. To reliably track simulated storms in CAM outputs, this study proposed an object-based method with two new features. First, the method explicitly estimated the probability of each probable track based on either its immediate past and future motion or a reliable “first-guess motion” derived from storm climatology or near-storm environmental variables. Second, object size was incorporated into the method to help identify temporally not well resolved storms and minimize false tracks derived for them. Parameters of the new features were independently derived from a storm evolution analysis using 2-min Multi-Radar Multi-Sensor (MRMS) data and hourly CAM forecasts produced by the University of Oklahoma (OU) Multiscale data Assimilation and Predictability Laboratory (MAP) from May 2019. The performance of the new method was demonstrated with hourly MRMS and CAM forecast examples from May 2018. A systematic evaluation of four severe weather events indicated 99% accuracy achieved for over 600 hourly MRMS tracks derived with the proposed tracking method.

This study first describes the extended Grid-Point Statistical Interpolation analysis system (GSI)-based ensemble-variational data assimilation (DA) system within the North American Mesoscale Rapid Refresh (NAMRR) system for the Nonhydrostatic Multiscale Model on the B grid (NMMB). Experiments were conducted to examine three critical aspects of data assimilation configuration in this system. Ten retrospective high-impact convective cases during the warm season of 2015–2016 were adopted for testing. A 10-member, 18 h ensemble forecast was launched for each experiment. Specifically, the experiment using horizontal (vertical) localization radii (Lr) of 300 km (0.55-scaled height measured in the nature log of pressure) overall had more skills than that of 500 km (1.1-scaled height) for conventional in-situ observation assimilation. Diagnostics suggest that the higher forecast skills could be attributed to applying smaller Lr in the boundary with large temperature and moisture gradients. For radar DA, the experiment was more skillful with horizontal (vertical) Lr of 15 km (1.1-scaled height) than that of 12 km (0.55-scaled height). Diagnostics suggest that the improved forecasts were achieved by using wider Lr to spread radar observations into unobserved areas more effectively. Slight forecast skill differences between the relaxation inflation factors of 95% and 65% are presented. The impact of varying inflation magnitudes primarily occurred in the upper-level spread.

Recirculation of airflows in a mine ventilation system can cause concentration of contaminated air which results in an unsafe working environment for people working in an underground mine. Due to the difficulty in finding the recirculation of airflows in complicated mine ventilation system, depth-first search method is proposed to find the recirculation of airflows in complicated mine ventilation systems. The searching procedure of a simply depth-first search method is introduced briefly. Then the depth-first search method is modified for searching recirculation of airflows in complicated mine ventilation systems. The proposed method is implemented through MATLAB in the form of storing ventilation information in a matrix. A few recirculation of airflows are found and are confirmed by the mine ventilation simulation result. It is concluded that the proposed method is a valuable tool in finding recirculation of airflows in a complicated mine ventilation system.

A hybrid continuum-discontinuum method is introduced to model the rock failure process in Brazilian tensile strength (BTS) test. The key component of the hybrid continuum-discontinuum method, i.e. transition from continuum to discontinuum through fracture and fragmentation, is introduced in detail. A laboratory test is conducted first to capture the rock fracture pattern in the BTS test while the tensile strength is calculated according to the peak value of the loading forces. Then the proposed method is used to model the rock behaviour during BTS test. The stress propagation is modelled and compared with those modelled by finite element method in literatures. In addition, the crack initiation and propagation are captured and compared with the facture patter in laboratory test. Moreover, the force-loading displacement curve is obtained which represents a typical brittle material failure process. Furthermore, the stress distributions along the vertical direction are compared with the theoretical solution. It is concluded that the hybrid continuum-discontinuum method can model the stress propagation process and the entire rock failure process in BTS test. The proposed method is a valuable numerical tool for studying the rock behaviour involving the fracture and fragmentation processes.

Six-hourly three-dimensional ensemble variational (3DEnVar) (6H-3DEnVar) data assimilation (DA) assumes constant background error covariance (BEC) during a six-hour DA window and is, therefore, unable to account for temporal evolution of the BEC. This study evaluates the one-hourly 3DEnVar (1H-3DEnVar) and six-hourly 4DEnVar (6H-4DEnVar) DA methods for the analyses and forecasts of hurricanes with rapidly evolving BEC. Both methods account for evolving BEC in a hybrid EnVar DA system. In order to compare these methods, experiments are conducted by assimilating inner core Tail Doppler Radar (TDR) wind for Hurricane Edouard (2014) and by running the Hurricane Weather Research and Forecasting (HWRF) model. In most metrics, 1H-3DEnVar and 6H-4DEnVar analyses and forecasts verify better than 6H-3DEnVar. 6H-4DEnVar produces better thermodynamic analyses than 1H-3DEnVar. Radar reflectivity shows that 1H-3DEnVar produces better structure forecasts. For the first 24–48 h of the intensity forecast, 6H-4DEnVar forecast performs better than 1H-3DEnVar verified against the best track. Degraded 1H-3DEnVar forecasts are found to be associated with background storm center location error as a result of underdispersive ensemble storm center spread. Removing location error in the background improves intensity forecasts of 1H-3DEnVar.

The Split Hopkinson Pressure Bar (SHPB) is an apparatus for testing the dynamic stress-strain response of the cement mortar specimen with pre-set joints at different angles to explore the influence of joint attitudes of underground rock engineering on the failure characteristics of rock mass structure. The nuclear magnetic resonance (NMR) has also been used to measure the pore distribution and internal cracks of the specimen before and after the testing. In combination with numerical analysis, the paper systematically discusses the influence of joint angles on the failure mode of rock-like materials from three aspects of energy dissipation, microscopic damage, and stress field characteristics. The result indicates that the impact energy structure of the SHPB is greatly affected by the pre-set joint angle of the specimen. With the joint angle increasing, the proportion of reflected energy moves in fluctuation, while the ratio of transmitted energy to dissipated energy varies from one to the other. NMR analysis reveals the structural variation of the pores in those cement specimens before and after the impact. Crack propagation direction is correlated with pre-set joint angles of the specimens. With the increase of the pre-set joint angles, the crack initiation angle decreases gradually. When the joint angles are around 30°–75°, the specimens develop obvious cracks. The crushing process of the specimens is simulated by LS-DYNA software. It is concluded that the stresses at the crack initiation time are concentrated between 20 and 40 MPa. The instantaneous stress curve first increases and then decreases with crack propagation, peaking at different times under various joint angles; but most of them occur when the crack penetration ratio reaches 80–90%. With the increment of joint angles in specimens through the simulation software, the changing trend of peak stress is consistent with the test results.

Pressure sensors are good candidates for measuring driver postural information, which is indicative for identifying driver’s intention and seating posture. However, monitoring systems based on pressure sensors must overcome the price barriers in order to be practically feasible. This study, therefore, was dedicated to explore the possibility of using pressure sensors with lower resolution for driver posture monitoring. We proposed pressure features including center of pressure, contact area proportion, and pressure ratios to recognize five typical trunk postures, two typical left foot postures, and three typical right foot postures. The features from lower-resolution mapping were compared with those from high-resolution Xsensor pressure mats on the backrest and seat pan. We applied five different supervised machine-learning techniques to recognize the postures of each body part and used leave-one-out cross-validation to evaluate their performance. A uniform sampling method was used to reduce number of pressure sensors, and five new layouts were tested by using the best classifier. Results showed that the random forest classifier outperformed the other classifiers with an average classification accuracy of 86% using the original pressure mats and 85% when only 8% of the pressure sensors were available. This study demonstrates the feasibility of using fewer pressure sensors for driver posture monitoring and suggests research directions for better sensor designs.

A hybrid finite-discrete element method (FEM/DEM) is introduced to model the excavation damage zone induced by blast in a deep tunnel. The key components of the hybrid finite-discrete element method, i.e. transition from continuum to discontinuum through fracture and fragmentation, and detonation-induced gas expansion and flow through fracturing rock, are introduced in detail. The stress and crack initiation and propagation of an uniaxial compression test is then modelled by the proposed method and compared with those well documented in literature to calibrate the hybrid FEM/DEM. The modelled stress-loading displacement curve presents a typical failure process of brittle materials. The calibrated method is then used to model the stress and crack initiation and propagation induced by blast for the last step of excavation in a deep tunnel. A separation contour, which connects the borehole through the radial cracks from each borehole, is observed during the excavation process. The newly formed tunnel wall is produced and the main components of excavation damage zone (EDZ) are obtained. Therefore, the proposed treatment has the capabilities of modelling blast-induced EDZ and rock failure process. It is concluded that the hybrid FEM/DEM is a valuable numerical tool for studying excavation damage zone in terms of crack initiation and propagation and stress distribution.

It has been well proved that melatonin participates in the regulation of the seasonal reproduction of ewes. However, the effects of short term treatment of melatonin on ewe’s ovulation are still to be clarified. In this study, the effects of melatonin on the number of embryos harvested from superovulation, and the pregnant rate in recipients after embryo transferred have been investigated. Hu sheep with synchronous estrus treatment were given melatonin subcutaneously injection (0, 5, and 10 mg/ewe, respectively). It was found that the estrogen level in the group of 5 mg melatonin was significantly higher than that of other two groups at the time of sperm insemination (p

A personalized pelvis and femur shape is required to build a finite element buttock thigh model when experimentally investigating seating discomfort. The present study estimates the shape of pelvis and femur using a principal component analysis (PCA) based method with a limited number of palpable anatomical landmarks (ALs) as predictors. A leave-one-out experiment was designed using 38 pelvises and femurs from a same sample of adult specimens. As expected, prediction errors decrease with the number of ALs. Using the maximum number of easily palpable ALs (13 for pelvis and 4 for femur), average errors were 5.4 and 4.8 mm respectively for pelvis and femur. Better prediction was obtained when the shapes of pelvis and femur were predicted separately without merging the data of both bones. Results also show that the PCA based method is a good alternative to predict hip and lumbosacral joint centers with an average error of 5.0 and 9.2 mm respectively.

The Northwest Pacific tropical cyclone (TC) intensification is classified into rapid intensification (RI), normal intensification (NI), and slow intensification (SI) categories. The initial location and intensity, the preceding intensity change, the motion direction, the occurrence month, and the intensification duration time are all found to differ for RI cases compared with NI and SI cases. The dependence of RI, NI, and SI on environmental conditions is further examined statistically by using the intensification rates of named TCs, for the 21-year period 1995–2015, obtained from JTWC best track data, and the environmental conditions derived from the ERA-Interim reanalysis data and GODAS high-resolution global ocean analysis data. It was found that deep-layer and upper-mid vertical wind shear (VWS), upper-level outflow, sea surface temperature (SST), and ocean heat content (OHC) are statistically different among RI, NI, and SI both before and during intensification. RI is enhanced by weaker and decreasing VWS, warmer oceans, and stronger and increasing outflow. In contrast, SI typically occurs with larger and increasing VWS, cooler oceans, and weaker, static outflow. The impacts of low-level VWS and net moisture inflow are only significantly different between RI and SI and between NI and SI, but not between RI and NI. Another key finding is that increased upper-level outflow and decreased VWS are important precursors and hence are possible predictors, of RI onset. The direction of upper-level outflow affects TC intensification, with NW and NE outflow being more favorable for TC RI than SE and SW outflow.

A long-lived supercell developed in Northwest Bulgaria on 15 May 2018 and inflicted widespread damage along its track. The first part of this article presents a detailed overview of the observed storm evolution. Doppler radar observations reveal that the storm acquired typical supercellular signatures and maintained reflectivity values in excess of 63 dBZ for more than 4 h. The thunderstorm was also analyzed through lightning observations that highlighted important characteristics of the overall supercell dynamics. In its second part, the study investigates the predictability of the severe weather outbreak. In the medium forecast ranges, the global European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble indicated the presence of favorable conditions for the development of deep moist convection 4 days prior to the event. A set of three convection-allowing ensemble simulations also demonstrated that the practical predictability of the supercell was approximately 12 h, which is considerably higher than some previously reported estimates. Nevertheless, the skill of the convective forecasts appears to be limited by the presence of typical model errors, such as the timing of convection initiation and the development of spurious convective activity. The relevance of these errors to the optimal ensemble size and to the design of future convection-allowing numerical weather prediction (NWP) systems is further discussed.

Starches from the bulbils of Dioscoreae opposita Thunb. cv. Tiegun were isolated by aqueous steeping (SBS), enzyme extraction (EBS), and alkaline extraction (ABS) methods, respectively. The physicochemical, mineral composition, thermal and morphological characteristics of these starches were investigated. The starch granules were oval, spherical and kidney-shaped and its crystal type is a mixture of A-type and B-type patterns. The starches having larger average granule size showed more amylose and phosphorus contents than those with smaller average granule size. Differential scanning calorimetry (DSC) showed that the SBS had an endothermic transition ranging from 65.8 °C to 76.3 °C with an enthalpy of 2.0 J/g. The endothermic transitions of ABS and EBS showed the regions of 67.9 °C to 73.0 °C, and 66.8 °C to 82.0 °C, respectively. The gelationization enthalpies of ABS and EBS were 13.8 and 11.5 J/g, respectively. Additionally, ABS presented greater clarity in comparison with EBS and SBS. Pasting properties indicated that ABS had the highest peak viscosity, breakdown, but SBS had the lowest trough, final viscosity, setback, and pasting temperature. Generally, ABS and EBS could be used as food thickener or frozen food additives. SBS and EBS were potential technological alternatives in quality preservation of frozen starch-based products and other industrial applications.

Background and objective Tumor suppressor in lung cancer-1 (TSLC1) belongs to immunoglobulin superfamily of cell adhesion molecule and differentially expressed in adenocarcinoma of the lung (4.1B)belongs to NF2/ERM/4.1 protein superfamily. They may suppress carcinogenesis via construction of the adjacent cell adhesion stability. The aim of this study is to detect the expressions of TSLC1 and 4.1B in non-small cell lung cancer and the clinical pathological significances. Methods The expressions of TSLC1 and 4.1B were detected by RT-PCR in 52 cases of non-small cell lung cancer and corresponding adjacent cancer lung tissues. Results The expressions of TSLC1 and 4.1B in cancer tissues were significantly lower than that in adjacent cancer lung tissues (0.349±0.008 vs 0.555±0.010; 0.209±0.040 vs 0.721±0.071) (P < 0.01). The expressions of TSLC1 and 4.1B showed a significant correlation with cancer differentiation and TNM staging (P < 0.05), but not with gender, age and pathological type (P > 0.05). The expressions of TSLC1 and 4.1B were positively correlated (r=0.471, P < 0.001). Conclusion Down-regulated expressions of TSLC1 and 4.1B in non-small cell lung cancer, both may participate in a cascade of non-small cell lung cancer occurrence and development. TSLC1 and 4.1B are promising targets for non-small cell lung cancer diagnosis and treatment.

The impact of observations can be dependent on many factors in a data assimilation (DA) system including data quality control, preprocessing, skill of the model, and the DA algorithm. The present study focuses on comparing the impacts of observations assimilated by two different DA algorithms. A three-dimensional ensemble-variational (3DEnsVar) hybrid data assimilation system was recently developed based on the Gridpoint Statistical Interpolation (GSI) data assimilation system and was implemented operationally for the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS). One question to address is, how the impacts of observations on GFS forecasts differ when assimilated by the traditional GSI-three dimensional variational (3DVar) and the new 3DEnsVar. Experiments were conducted over a 6-week period during Northern Hemisphere winter season at a reduced resolution. For both the control and data denial experiments, the forecasts produced by 3DEnsVar were more accurate than GSI3DVar experiments. The results suggested that the observations were better and more effectively exploited to increment the background forecast in 3DEnsVar. On the other hand, in GSI3DVar, where the observation will be making mostly local, isotropic increments without proper flow dependent extrapolation is more sensitive to the number and types observations assimilated.

This paper presents a novel capacitive microelectromechanical systems (MEMS) accelerometer with slanted supporting beams and all-silicon sandwich structure. Its sensing mechanism is quite similar to an ordinary sandwich-type MEMS accelerometer, except that its proof mass is suspended by a beam parallel to the {111} plane of a (100) silicon wafer. In this way, each sensing element can detect accelerations in two orthogonal directions. Four of these sensing elements could work together and constitute a 3-axis micro-accelerometer by using a simple planar assembly process. This design avoids the traditional 3-axis accelerometer’ disadvantage of possible placement inaccuracy when assembling on three different planes and largely reduces the package volume. The slanted-beam accelerometer’s performance was modeled and analyzed by using both analytical calculations and finite element method (FEM) simulations. A prototype of one sensing element was fabricated and tested. Measured results show that this accelerometer has a good bias stability 76.8 ppm (1σ, tested immediately after power on), two directional sensitivities (sensitivity angle α = 45.4°) and low nonlinearity (