Search

Abstract In photoperiod-sensitive plants, the CO-like gene (CONSTANS-like, COL) has a crucial function in regulating the timing of flowering. The blooming period in foxtail millet is greatly influenced by the duration of daylight; however, there is a scarcity of data regarding the molecular properties of the COL genes in the foxtail millet. In this study, we conducted a comprehensive analysis of the COL gene family in foxtail millet at the genome-wide level. We identified 11 SiCOL genes and performed gene structure analysis, which showed pronounced variation in gene length and intron number among the genes. The examination of COL proteins in foxtail millet and other plant species using phylogenetic analysis revealed that they could be clustered into three distinct groups. Cis-element analysis identified elements related to light-responsiveness, hormones, and abiotic stress in the promoter region of the SiCOL gene. Furthermore, tissue-specific expression analysis showed widespread expression of all 11 SiCOL genes in various foxtail millet tissues and organs, particularly in leaves and panicles. Collinearity analysis identified 14 syntenic gene pairs in both foxtail millet and rice. The results also revealed diurnal oscillations in the transcription levels of SiCOL genes under different light conditions. Moreover, among the 11 genes, SiCO, SiCOL1, and SiCOL6 expression levels were negatively correlated with flowering time variation in two foxtail cultivars. Additionally, upon constructing a network of predicted molecular interactions, FLOWER LOCUS-like (FTL) and Phytochromea A (PHY A) were suggested to potentially interact with SiCO, SiCOL1, and SiCOL6. SiCO, SiCOL1, and SiCOL6 have the potential for flowering and heading in foxtail millet. This research enhances our comprehension of the role and control of the SiCOL gene family constituents in foxtail millet, establishing a basis for future investigations.

Highlights Additive-assisted layer-by-layer (LBL) deposition enables organic solar cells to achieve an unprecedented power conversion efficiency of 20.8%, the highest efficiency to date. The gradient fibrillar morphology enabled by additive-assisted LBL processing promotes the formation of bulk p-i-n structure, improving exciton and carrier diffusion, and reducing recombination losses. The wrinkle pattern morphology achieved by additive-assisted LBL processing is constructed to enhance the light capture capability.

Abstract Background The integration of AI in finance has significantly reshaped the role of financial engineers, improving efficiency and decision-making. However, it also affects psychological safety and work-life balance. Financial engineers face increased pressure to keep up with evolving technologies, fear of job displacement due to automation, and blurred boundaries between work and personal life. Exploring the link between AI applications, psychological well-being, and work-life balance is crucial for optimizing individual performance and organizational success, ensuring a sustainable and supportive work environment. Objectives This qualitative study investigates how AI-integrated finance applications influence financial engineers’ psychological safety and work-life balance. By exploring financial engineers’ lived experiences and perceptions, the study seeks to provide insights into the human implications of AI adoption in finance. Methodology : The study utilized qualitative research methods, specifically thematic analysis, to examine data from 20 informants selected through theoretical sampling. Thematic analysis techniques were employed to identify recurring patterns, themes, and meanings within the data, allowing for a rich exploration of the research questions. Findings : Data analysis revealed several themes related to the impact of AI-integrated applications on financial engineers’ psychological safety and work-life balance. These themes include the perception of job security, the role of automation in workload management, and the implications of AI for professional identity and job satisfaction. Conclusions This study’s findings highlight the multifaceted effects of AI integration in finance, shedding light on the opportunities and challenges it presents for financial engineers. While AI offers potential benefits such as increased efficiency and productivity, it raises concerns about job security and work-related stress. Overall, the study underscores the importance of considering the human implications of AI adoption in finance and calls for proactive measures to support the well-being of financial professionals in an AI-driven environment.

Abstract Gas explosion is one of the five major hazards in mines, with about 36% of such incidents occurring in the excavation working face. Therefore, to investigate the impact of gas explosion propagation laws within excavation roadways, we conducted a simulation analysis of parameters such as peak of explosion overpressure, peak rate of pressure rise, and flame propagation speed in the presence of a Tunnel Boring Machine (TBM). In the presence of the TBM, the explosion overpressure approximately doubles, and the flame propagation speed also greatly increases, exacerbating the explosion hazard. Thus, when investigating gas explosion laws within excavation roadways, the presence of a TBM emerges as a significant factor that cannot be overlooked. Furthermore, an analysis of the effects of methane concentration and gas accumulation length on explosion parameters was conducted. The results indicate that when the flame passes through the TBM baffle, the average flame propagation speed increases the most when the methane concentration is 9.5%, increasing by about 6 times. In addition, as the gas accumulation length increases, both explosion overpressure and flame propagation speed gradually increase. Additionally, TBM has a certain impact on flame propagation and methane dissipation.

Solar thermochemical energy storage based on calcium looping (CaL) process is a promising technology for next-generation concentrated solar power (CSP) systems. However, conventional calcium carbonate (CaCO3) pellets suffer from slow reaction kinetics, poor stability, and low solar absorptance. Here, we successfully realized high power density and highly stable solar thermochemical energy storage/release by synergistically accelerating energy storage/release via binary sulfate and promoting cycle stability, mechanical strength, and solar absorptance via Al–Mn–Fe oxides. The energy storage density of proposed CaCO3 pellets is still as high as 1455 kJ kg−1 with only a slight decay rate of 4.91% over 100 cycles, which is higher than that of state-of-the-art pellets in the literature, in stark contrast to 69.9% of pure CaCO3 pellets over 35 cycles. Compared with pure CaCO3, the energy storage power density or decomposition rate is improved by 120% due to lower activation energy and promotion of Ca2+ diffusion by binary sulfate. The energy release or carbonation rate rises by 10% because of high O2− transport ability of molten binary sulfate. Benefiting from fast energy storage/release rate and high solar absorptance, thermochemical energy storage efficiency is enhanced by more than 50% under direct solar irradiation. This work paves the way for application of direct solar thermochemical energy storage techniques via achieving fast energy storage/release rate, high energy density, good cyclic stability, and high solar absorptance simultaneously.

The study focuses on the impact of microlensing in modern cosmology and introduces a new framework for the static spherically symmetrical wormhole in terms of the radial equation of state. Following a standard procedure, the study calculates the lensing equation, magnification, and event rate based on the radial equation of state. The analysis highlights that the image problem of the light source is complex. Furthermore, the study suggests that larger values for the throat radius of the wormhole and the radial equation of state lead to higher event rates. Additionally, it is proposed that the event rate of a wormhole will be larger compared to that of a black hole, provided their masses and distances from the light source and observer are comparable. This study offers the potential to distinguish between a wormhole and a black hole under similar conditions.

In order to effectively prevent and control coal spontaneous combustion and improve the safety of coal mining, bagasse carboxymethy cellulose (BCC) prepared from bagasse (BS) and sodium carboxymethyl cellulose (CMC) were used as the substrates. A gel (BCC-CMC) for inhibiting coal spontaneous combustion was prepared using a chemical crosslinking method involving zirconium citrate crosslinking and glucono-delta-lactone (GDL) modification. X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy were utilized to characterize both the crystal and molecular structure of bagasse and its derived bagasse carboxymethyl cellulose. The results indicated that new carboxymethyl groups were introduced into bagasse during the treatment, facilitating the successful extraction and preparation of sodium carboxymethyl cellulose. The results of viscosity and bonding tests demonstrated that the concentration and dosage of CMC had the most significant influence on the gel viscosity, which remained higher and more stable at room temperature. The coal bonded by the gel coal mixture can effectively seal surface cracks, with a bonding degree of up to 70.72 %. TG-DTG, temperature-programmed oxidation experiment and FTIR analyses revealed that, compared to raw coal, coal samples treated with gel exhibited improved stability, fewer active groups, and fewer oxygen-containing functional groups, effectively inhibiting coal’s low temperature oxidation and reducing the risk of spontaneous combustion. The gel is environmentally friendly, cost-effective, and exhibits good flame retardant properties. This study is of great significance for preventing and controlling coal spontaneous combustion, effectively ensuring the safe production of coal resources and the safety of mine workers, achieving the green sustainable development of the mine.

The hydraulic testing of pre-existing fractures (HTPF) is one of the most promising in situ stress measurement methods, particularly for three-dimensional stress tensor determination. However, the stress tensor determination based on the HTPF method requires at least six tests or a minimum of 14–15 tests (under different conditions) for reliable results. In this study, we modified the HTPF method by considering the shear stress on each pre-existing fracture, which increased the number of equations for the stress tensor determination and decreased the number of tests required. Different shear stresses were attributed to different fractures by random sampling; therefore, the stress tensors were obtained by searching for the optimal solution using the least squares criterion based on the Monte Carlo method. Thereafter, we constrained the stress tensor based on the tensile strength criterion, compressive strength criterion, and vertical stress constraints. The inverted stress tensors were presented and analyzed based on the tensorial nature of the stress using the Euclidean mean stress tensor. Two stress-measurement campaigns in Weifang (Shandong Province, China) and Mercantour road tunnel (France) were implemented to highlight the validity and efficiency of the modified HTPF (M-HTPF) method. The results showed that the M-HTPF method can be applied for stress tensor inversion using only three to four tests on pre-existing fractures, neglecting the stress gradient. The inversion results were confined to relatively small distribution dispersions and were significantly reliable and stable due to the shear stresses on the fractures and the stress constraints employed. The M-HTPF method is highly feasible and efficient for complete stress tensor determination in a single borehole.

Methane/air explosion is one of the common hazards in process and mining industries. In this study, the methane explosion propagation is studied, and two-dimensional configuration is considered. The gas phase equations are solved using an OpenFOAM code for compressible reacting flow, EXiFOAM. The effects of the low blockage ratio (LBR) obstacles are investigated. The results show that the flame propagation speed, flame structure, shock wave propagation, and gas flow are considerably affected by LBR obstacles. Specifically, the flame propagation speed first increases and then decreases. As the initial pressure increases, the flame propagation speed gradually increases. The maximum speed is up to 500 m/s, when the initial pressure is 1.5 MPa. If the flame propagation is prevented, resulting in the flame deformation. Moreover, the flame disruptive phenomenon is captured due to the reflected waves. In front of the obstacle, the cellular structures of the high-pressure distribution are formed. Note that the tiny cellular structures are produced in the wake of the leading shock. Furthermore, a high-speed flow region and two low-speed flow regions are produced around the LBR obstacles. It is found that as the initial pressure increases, the explosion pressure is larger, while the temperature change is not obvious. These research findings have implications for enhancing safety production in coal mines.

Abstract Crystallization speed of phase change material is one of the main obstacles for the application of phase change memory (PCM) as storage class memory in computing systems, which requires the combination of nonvolatility with ultra‐fast operation speed in nanoseconds. Here, we propose a novel approach to speed up crystallization process of the only commercial phase change chalcogenide Ge2Sb2Te5 (GST). By employing TiO2 as the dielectric layer in phase change device, operation speed of 650 ps has been achieved, which is the fastest among existing representative PCM, and is comparable to the programing speed of commercial dynamic random access memory (DRAM). Because of its octahedral atomic configuration, TiO2 can provide nucleation interfaces for GST, thus facilitating the crystal growth at the determinate interface area. Ti–O–Ti–O four‐fold rings on the (110) plane of tetragonal TiO2 is critical for the fast‐atomic rearrangement in the amorphous matrix of GST that enables ultra‐fast operation speed. The significant improvement of operation speed in PCM through incorporating standard dielectric material TiO2 in DRAM paves the way for the application of phase change memory in high performance cache‐type data storage.

The state of in situ stress is a crucial parameter in subsurface engineering, especially for critical projects like nuclear waste repository. As one of the two ISRM suggested methods, the overcoring (OC) method is widely used to estimate the full stress tensors in rocks by independent regression analysis of the data from each OC test. However, such customary independent analysis of individual OC tests, known as no pooling, is liable to yield unreliable test-specific stress estimates due to various uncertainty sources involved in the OC method. To address this problem, a practical and no-cost solution is considered by incorporating into OC data analysis additional information implied within adjacent OC tests, which are usually available in OC measurement campaigns. Hence, this paper presents a Bayesian partial pooling (hierarchical) model for combined analysis of adjacent OC tests. We performed five case studies using OC test data made at a nuclear waste repository research site of Sweden. The results demonstrate that partial pooling of adjacent OC tests indeed allows borrowing of information across adjacent tests, and yields improved stress tensor estimates with reduced uncertainties simultaneously for all individual tests than they are independently analysed as no pooling, particularly for those unreliable no pooling stress estimates. A further model comparison shows that the partial pooling model also gives better predictive performance, and thus confirms that the information borrowed across adjacent OC tests is relevant and effective.

Abstract Gliomas are the most common primary intracranial tumor worldwide. The maintenance of telomeres serves as an important biomarker of some subtypes of glioma. In order to investigate the biological role of RTEL1 in glioma. Relative telomere length (RTL) and RTEL1 mRNA was explored and regression analysis was performed to further examine the relationship of the RTL and the expression of RTEL1 with clinicopathological characteristics of glioma patients. We observed that high expression of RTEL1 is positively correlated with telomere length in glioma tissue, and serve as a poor prognostic factor in TERT wild-type patients. Further in vitro studies demonstrate that RTEL1 promoted proliferation, formation, migration and invasion ability of glioma cells. In addition, in vivo studies also revealed the oncogene role of RTEL1 in glioma. Further study using RNA sequence and phospho-specific antibody microarray assays identified JNK/ELK1 signaling was up-regulated by RTEL1 in glioma cells through ROS. In conclusion, our results suggested that RTEL1 promotes glioma tumorigenesis through JNK/ELK1 cascade and indicate that RTEL1 may be a prognostic biomarker in gliomas.

This research presents a “flexible support structure between reflective mirrors” through a coupling analysis method to restrain the surface shaping error of reflectors in the optical system of airborne LiDAR bathymetry (ALB) under various working conditions. The flexible structure proposed adjusts the mechanical relationship between the reflectors and the support structure to reduce reflector mirror deformation. The optical system is first modeled using Zemax and exported to SolidWorks to create a 3D model of the optical receiving system. Ansys is then used to conduct stiffness testing and surface analysis on the support structure of the annular thin cylinder. According to the analysis results, the first-order frequency of the support structure using a ring-shaped thin cylinder is as high as 353.64 Hz, which indicates that it has good dynamic characteristics. The PV value of the reflector mirror deformation under the thermal coupling reaches 32.59 nm, and the RMS value reaches 8.62 nm. Additionally, it is discovered that the maximum acceleration response of the reflector mirror under the applied 1 g acceleration excitation reaches 4.22 g when carrying out the dynamics analysis of the support structure. Under random vibration analysis, the maximum acceleration RMS value of the reflector mirror assembly reaches 2.18 g, and the maximum stress of the flexible device of the support structure reaches 2.65 MPa. Especially, five groups of experimental results demonstrated that the proposed coupling analysis method can receive the echo signals, the reflector mirror support structure designed in this paper, and the flexible structure is stable and reliable.

In this study, electrical steel laminated composites with positive Si gradient (PO-G), counter Si gradient (CO-G), and cross Si gradient (CR-G) were fabricated by hot-press sintering, cold rolling and annealing. The microstructure evolution during processing, as well as the magnetic and mechanical properties were investigated. The results indicate that the microstructure of the high-silicon layer and medium-silicon layer in the hot-pressed composites featured columnar grains throughout the thickness. The microstructure of the low-silicon layer in the hot-pressed CO-G sample consisted of equiaxed grains. However, a mixed structure dominated by columnar grains with some equiaxed grains was observed in the inner low-silicon layer of the PO-G and CR-G samples. Following cold rolling, the thickness ratio of each layer remained largely unchanged. After annealing, the microstructure of each layer transformed into columnar grains. The average grain size of the high-silicon layer, medium-silicon layer, and low-silicon layers in the three composites were approximately 20–23 μm, 33–38 μm, and 42–49 μm, respectively. Compared with the CO-G and CR-G samples, the annealed PO-G composite exhibited lower core loss at 400–1000 Hz and superior tensile strength. Furthermore, the core loss of the three composites was greater than that of the initial medium-silicon and high-silicon materials. This can be attributed to the increased hysteresis loss due to the existence of multi-layer interface.

Abstract Side‐chain symmetry‐breaking strategy plays an important role in developing photovoltaic materials for high‐efficiency all‐small‐molecule organic solar cells (ASM OSCs). However, the power conversion efficiencies (PCEs) of ASM OSCs still lag behind their polymer‐based counterparts, which can be attributed to the difficulties in achieving favorable morphology. Herein, two asymmetric porphyrin‐based donors named DAPor‐DPP and DDPor‐DPP were synthesized, presenting stronger intermolecular interaction and closer molecular stacking compared to the symmetric ZnP‐TEH. The DAPor‐DPP:6TIC blend afforded a favorable morphology with nanoscale phase separation and more ordered molecular packing, thus achieving more efficient charge transportation and suppressed charge recombination. Consequently, the DAPor‐DPP:6TIC‐based device exhibited superior photovoltaic parameters, yielding a champion PCE of 16.62% higher than that of the DDPor‐DPP‐based device (14.96%). To our knowledge, 16.62% can be ranked as one of the highest PCE values among the binary ASM OSC filed. This work provides a prospective approach to address the challenge of ASM OSCs in improving film morphology and further achieving high efficiency via side‐chain symmetry‐breaking strategy, exhibiting great potential in constructing efficient ASM OSCs.

Solar-driven CO2-to-fuel conversion assisted by another major greenhouse gas CH4 is promising to concurrently tackle energy shortage and global warming problems. However, current techniques still suffer from drawbacks of low efficiency, poor stability, and low selectivity. Here, a novel nanocomposite composed of interconnected Ni/MgAlOx nanoflakes grown on SiO2 particles with excellent spatial confinement of active sites is proposed for direct solar-driven CO2-to-fuel conversion. An ultrahigh light-to-fuel efficiency up to 35.7%, high production rates of H2 (136.6 mmol min−1g−1) and CO (148.2 mmol min−1g−1), excellent selectivity (H2/CO ratio of 0.92), and good stability are reported simultaneously. These outstanding performances are attributed to strong metal-support interactions, improved CO2 absorption and activation, and decreased apparent activation energy under direct light illumination. MgAlOx@SiO2 support helps to lower the activation energy of CH* oxidation to CHO* and improve the dissociation of CH4 to CH3* as confirmed by DFT calculations. Moreover, the lattice oxygen of MgAlOx participates in the reaction and contributes to the removal of carbon deposition. This work provides promising routes for the conversion of greenhouse gasses into industrially valuable syngas with high efficiency, high selectivity, and benign sustainability.

The prediction of frictional air resistance using the inherent properties of roadways is of great significance for ventilation network computation and flow regulation in underground mines. This study proposes an improved stacked learning and error correction-based prediction model for the frictional air resistance of mine airways, called friction factor. A prediction set is established by selecting ten factors, including tunnel spatial features and support forms, with the ventilation resistance coefficient as the label. The improved stacked model consists of two layers. The first layer is the base learning module, which is composed of four components: Principal Components Analysis and Back Propagation (PCA-BP), GA-Projection Pursuit Regression (GA-PPR), Random Forest (RF), LightGBM (LGBM). The second layer is the meta-learning module, which is composed of the Ridge Regression (RR). Compared to traditional stacked models, the improved model first uses the Extreme Gradient Boosting (XG Boost) learner to evaluate the significance of input feature variables to eliminate redundancy and improve accuracy, thus enhancing prediction precision and computational efficiency. Then, the first-layer prediction results are weighted based on the errors of different prediction models in the training set using K-fold cross-validation. Box-Cox transformation is applied to the training set data from the first layer to the second layer to improve prediction normality and homogeneity. The error correction prediction model extracts the historical prediction errors from the meta-learning module and constructs an error prediction model using support vector machines (SVR), which are then combined with the meta-learning results to obtain the final prediction. The improved stacked model is compared with traditional ensemble learning models and single prediction models, and quantified using three metrics: root mean square error (RMSE), mean absolute error (MAE), and R-squared (R2). The results demonstrate that the proposed improved model effectively enhances the prediction accuracy of the ensemble learning models, providing a new prediction method for the accurate acquisition of the friction factor of mine airways.

The main factor limiting the widespread use of industrial robots in machining applications is the relatively low stiffness of the robot. Stiffness performance not only affects the quality of robotic milling but also affects the accuracy of the milling process. It is necessary to improve the stiffness performance in the robotic machining process. A new robot stiffness performance index is proposed to evaluate the robot stiffness in the direction normal to the surface of the workpiece to be machined. This index is based on the functional redundancy characteristics of the robot. The relationship between the redundant axis angle and the stiffness performance index at a random point in Cartesian space, and the stiffness performance index values on a random path in Cartesian space are obtained. The robot posture optimization model is established and a new robot milling posture optimization method is introduced. The experimental results prove a significant reduction in machining error and a significant increase in machining accuracy after using the proposed robotic milling posture optimization method, which proves the validity of the proposed stiffness performance index, and the robot milling posture optimization method can be widely used in the industry. Finally, the distribution of stiffness performance index is analyzed to predict the regions of better robot stiffness performance in the workbench, which can be used as a criterion before the milling operation to optimize the robot configuration to improve milling accuracy and save time.

Abstract Background Evidence on the role of physical activity (PA) on healthcare utilization and expenditure is limited in China. We aimed to examine the association between the total physical activity (TPA) per week, healthcare service use and expenditure. Methods We extracted the data from China Health and Retirement Longitudinal Study (CHARLS) 2011, 2013, and 2015. Participants more than 50 years old who completed the follow-up for the three waves were enrolled. We converted the volume of vigorous physical activity (VPA) into an equivalent volume of moderate physical activity (MPA) and calculated the TPA per week for each participant. 12,927 of the 17,708 participants in CHARLS were included in our analysis. More than one-third of participants over 50 years old never participate in any moderate or intensity activity, and the median of self-reported moderate or intensity PA was about 525 (IQR 0–1680) MET-minutes per week in 2015. Results Compared to inactive subjects, the highest level of TPA was significantly related to the decreased risk number of inpatient visits (IRR: 0.58; 95% CI:0.50–0.67, p

This research endeavors to delve comprehensively into the ramifications of behavioral guidance policies pertaining to construction waste resource utilization (CWRU) on the behavioral awareness and attitudes of Chinese construction contractors. The implicit attitudes of 98 construction contractor workers toward construction waste collection, sorting, and reuse were quantitatively assessed by simulating different types of behavior-guided policies using the External Affective Simon Task (EAST) method with unconscious reaction time as an indicator. At the same time, the questionnaire survey was combined to collect and analyze the scores of these workers’ exogenous attitudes toward CWRU, with a view to revealing the contractors’ intrinsic behavioral awareness and exogenous attitudinal tendencies. The study reveals that economic incentive behavioral guidance policies are pivotal in fostering the collection, sorting, and reuse of construction waste. Furthermore, it novelly uncovers the distinct advantages of laws and regulations frameworks in safeguarding the fundamental aspects of construction waste collection. Notably, publicity and education behavioral policies emerge as a cornerstone in elevating the significance of construction waste collection and sorting, highlighting the cruciality of enhancing public awareness and knowledge to propel CWRU. The results of the study not only provide empirical evidence to understand the inherent attitudes of construction contractor workers toward CWRU behavior but also provide practical support for future policymakers. By advocating for economic incentives, strengthening regulations, and leading education, the multi-pronged approach promotes China’s CWRU accelerates the green transformation of the construction industry.

Abstract This study aimed to evaluate the safety of dump slopes in high-altitude areas subjected to severe dry–wet cycles. The slope of No. 1 and No. 2 in-service dumps in limestone mining areas for cement in high-altitude mining areas is taken as the research object. The unsaturated soil shear strength and matrix suction distribution equations were imported based on the unsaturated–saturated seepage theory. Therefore, the evolution characteristics of the unsaturated–saturated seepage field in the dump are analyzed by numerical calculation, and the safety state of the dump slope is evaluated. The results indicated the following rules: under the action of four dry–wet cycles, the surface soil of the dump slope changes from an unsaturated state to a saturated state. Furthermore, with the increase in the times of the dry–wet cycle, the maximum vertical displacement of the No. 1 and No. 2 dump slopes increased. The numerical calculations of the maximum cumulative vertical displacement of the slope were consistent with the actual monitoring data. The factor of safety of the dump slope decreased continuously with the increase in the times of dry–wet cycles. Nevertheless, it still met the safety and stability standards. It was concluded that the slope of the in-service dump remains stable after enduring four severe cycles of dry–wet.

Understanding the effect of changing wind speed on the evolution of spontaneous combustion of coal in goaf is crucial for ensuring safety in coal mining. This study focuses on the periodic disturbed airflow generated in the excavation roadway and its impact on the wind speed and goaf of the connected working face. The study reveals that (1) there is a negative correlation between the change of local ventilator wind speed and the wind speed at the working face. (2) the “periodic acceleration” ventilation leads to an increase in temperature at the fixed monitoring point. The maximum temperature is reached later than in normal ventilation conditions. (3) the change period of wind speed is positively correlated with the maximum temperature of the goaf. High wind speeds lead to a greater increase in temperature. (4) the temperature of the monitoring point in the goaf, the maximum internal temperature and the area of coal spontaneous combustion are more sensitive to the “periodic deceleration” disturbance airflow. In conclusion, the findings of this study provide valuable insights for the prevention and control of spontaneous combustion of coal in goaf. It highlights the importance of considering the effects of disturbed airflow in underground coal mining operations.

Metabolic engineering has been widely used for production of natural medicinal molecules. However, engineering high-yield platforms is hindered in large part by limited knowledge of complex regulatory machinery of metabolic network. N6-Methyladenosine (m6A) modification of RNA plays critical roles in regulation of gene expression. Herein, we identify 1470 putatively m6A peaks within 1151 genes from the haploid Saccharomyces cerevisiae strain. Among them, the transcript levels of 94 genes falling into the pathways which are frequently optimized for chemical production, are remarkably altered upon overexpression of IME4 (the yeast m6A methyltransferase). In particular, IME4 overexpression elevates the mRNA levels of the methylated genes in the glycolysis, acetyl-CoA synthesis and shikimate/aromatic amino acid synthesis modules. Furthermore, ACS1 and ADH2, two key genes responsible for acetyl-CoA synthesis, are induced by IME4 overexpression in a transcription factor-mediated manner. Finally, we show IME4 overexpression can significantly increase the titers of isoprenoids and aromatic compounds. Manipulation of m6A therefore adds a new layer of metabolic regulatory machinery and may be broadly used in bioproduction of various medicinal molecules of terpenoid and phenol classes.

In the field of wireless strain monitoring, it is difficult for the traditional metal-made antenna sensor to conform well with steel structures and monitor large strain deformation. To solve this problem, this study proposes a flexible antenna strain sensor based on a ductile graphene film, which features a 6.7% elongation at break and flexibility due to the microscopic wrinkle structure and layered stacking structure of the graphene film. Because of the use of eccentric embedding in the feeding form, the sensor can be miniaturized and can simultaneously monitor strain in two directions. The sensing mechanism of the antenna is analyzed using a void model, and an antenna is designed based on operating frequencies of 3 GHz and 3.5 GHz. The embedding size is optimized using a Smith chart and impedance matching principle. Both the simulation and experimental results verify that the resonant frequency and strain magnitude are linearly inversely proportional. The experimental results show that the strain sensitivity is 1.752 kHz/με along the geometric length and 1.780 kHz/με along the width, with correlation coefficients of 0.99173 and 0.99295, respectively.

Previous control methods developed by our research team cannot satisfy the high accuracy requirements of unmanned surface vessel (USV) path-tracking during bathymetric mapping because of the excessive overshoot and slow convergence speed. For this reason, this study developed an adaptive fuzzy integral-derivative line-of-sight (AFIDLOS) method for USV path-tracking control. Integral and derivative terms were added to counteract the effect of the sideslip angle with which the USV could be quickly guided to converge to the planned path for bathymetric mapping. To obtain high accuracy of the look-ahead distance, a fuzzy control method was proposed. The proposed method was verified using simulations and outdoor experiments. The results demonstrate that the AFIDLOS method can reduce the overshoot by 79.85%, shorten the settling time by 55.32% in simulation experiments, reduce the average cross-track error by 10.91% and can ensure a 30% overlap of neighboring strips of bathymetric LiDAR outdoor mapping when compared with the traditional guidance law.

The rib working resistance of push-the-bit rotary steerable drilling system seriously affects its dynamic performance. For example, the backing pressure problem caused by steps in the well wall during the working process of CNOOC Welleader static push-the-bit rotary steerable drilling tool is discussed in this paper. Based on the structure and working principle of CNOOC Welleader system, a corresponding theoretical model of force analysis is established, and an optimal design method to reduce the backing pressure problem is proposed in combination with numerical simulation and experimental research. The results show that changing the front chamfer area of Welleader system from circular arc to polyline is beneficial to reducing the backing pressure problem. The simulation results show that for steps of 1mm, 2mm and 3mm height, the optimal polyline angle is concentrated in the range of 10°-11°, in which the Angle of 10.5° has a good performance against the steps of three heights. Finally, by making corresponding test blocks, it was found that the peak value of forward resistance when the 10.5°test block crossed the steps of 1mm, 2mm and 3mm height decreased by 19.8%, 25.0% and 13.9% respectively, and the mean value decreased by 30.8%, 27.2% and 24.1% respectively, which was close to the simulation results, and verified the accuracy of the finite element analysis results.

Lumbar Disc Herniation (LDH) is a syndrome in which lumbar disc degeneration, rupture of the annulus fibrosus, and herniation of the nucleus pulposus irritate and compress the nerve roots and cauda equina, resulting in the main manifestations of lumbar pain and/or lower extremity pain. There is evidence in various clinical areas that exercise is effective in treating LDH, and exercise intervention for more than 2 weeks reduces disease activity in LDH. However, the mechanism of exercise’s action in reducing disease activity in LDH is unclear. In this article, we first summarize and highlight the effectiveness of exercise in treating LDH and provide guideline recommendations regarding exercise type, intensity, frequency, and duration. Then, we integrate the existing evidence and propose biological mechanisms for the potential effects of exercise on neuromechanical compression, inflammatory chemical stimuli, and autoimmune responses from the perspective of LDH pathogenesis as an entry point. However, a large body of evidence was obtained from non-LDH populations. Future research needs to investigate further the proposed biological mechanisms of exercise in reducing disease activity in LDH populations. This knowledge will contribute to the basic science and strengthen the scientific basis for prescribing exercise therapy for the routine clinical treatment of LDH.

Prevention and control measures of spontaneous combustion of coal and gas accumulation in a goaf require an accurate description of its gas flow state. However, the commonly used fluid dynamics in porous media is not suitable for the new-born goaf with fracture cavity combination, multi-scale, and large blocks. In this study, we propose a cavity flow algorithm to accurately describe the gas flow state in the new-born goaf. The genetic algorithm (GA) is used to randomly generate the binary matrix of a goaf caving shape. The difference between the gas flow state calculated by the lattice Boltzmann method (LBM) and the measured data at the boundary or internal measuring points of the real goaf is taken as the GA fitness value, and the real goaf caving shape and the gas flow state are quickly addressed by GA. The experimental model of new-born goaf is established, and the laser Doppler anemometry (LDA) experiment is carried out. The results show that the Jaccard similarity coefficient between the reconstructed caving shape and the real caving shape is 0.7473, the mean square error between the calculated wind speed and the LDA-measured value is 0.0244, and the R2 coefficient is 0.8986, which verify the feasibility of the algorithm.

Objective: To compare the quantitative susceptibility mapping (QSM) susceptibility values and pathology composition with different types of thrombi in the middle cerebral artery (MCA), and assess the value of susceptibility weight imaging in thrombus component diagnosis in stroke. Materials and methods: This study included 15 patients (73.47 ± 10.7 years; 6 males and 9 females) who underwent magnetic resonance imaging before mechanical thrombectomy due to acute middle cerebral artery occlusion between January 2017 and December 2019. All patients had the susceptibility vessel sign (SVS) on SWI (susceptibility weighted imaging), and the thrombus susceptibility was measured by signal processing in nuclear magnetic resonance SPIN software. The retrieved thrombi underwent histopathologic analysis, and the correlation between thrombus susceptibility and the pathologic composition was analyzed by two independent Kolmogorov–Smirnov tests. The location and length of thrombi were evaluated on both SWI and DSA, and the correlation was explored using two independent samples Wilcoxon rank test. The correlations between susceptibility and the infarct core volumes (ADC < 620 mm2/s volume map), hypoperfusion volumes (Tmax > 6 s volume map), 90-day modified Rankin scale (mRS), and the National Institutes of Health Stroke Scale (NIHSS) at admission were analyzed by Spearman’s correlation analysis. Results: Among the 15 retrieved thrombi, the mean thrombus susceptibility of RBC-dominant and fibrin-dominant thrombi were 209.88 ± 11.32 and 155.70 ± 28.20 (ppb), respectively (p = 0.037). The average distance of the proximal end of the thrombi to the midline was 24.67 ± 8.43 mm and 24.62 ± 8.44 mm, as measured by SWI and DSA (digital subtraction angiography), respectively (p < 0.001). The correlation between thrombus susceptibility was weakly negatively correlated with ADC < 620 mm2/s volume map (r = 0.356, p = 0.193) and poorly correlated with Tmax > 6 s volume map (r = 0.252, p = 0.365), 90-day mRS (r = 0.182, p = 0.517), and NIHSS at admission (r = 0.262, p = 0.345). Conclusions: The measurements of the Quantitative susceptibility value of thrombi may help predict the composition of thrombi in patients with acute middle cerebral artery occlusion. QSM provides a more accurate method to evaluate the thrombi.

Abstract The rupture of coal pillar can lead to spontaneous combustion or collapse of goaf, which endangers the safety of workers. To explore the relationship between the crack depth of the coal structure and the signal received by the piezoelectric ceramic sensor, the output data of coal samples were analyzed by using the piezoelectric effect, combined with the experiment and ABAQUS simulation. Based on the signal amplitude, the output signal characteristics of the coal model with different crack depths were analyzed, and the evaluation index of coal crack cracking degree (D c ) was defined. The results show that the piezoelectric fluctuation method can effectively identify the local cracks of coal. When the distance between the lead Piezoelectric Transducer (PZT) patch and crack position is constant, the amplitude of the PZT patch output signal will decay with the deepening of the crack depth, while the value of increases with the increase of crack depth. This study provides a theoretical basis for mine disaster prevention and control.

Abstract In this study, the surface crack-propagation law and pore damage characteristics of coal samples of different water contents after they undergo leaching in liquid nitrogen are investigated using a 4 K scientific-research camera, HC-U7 non-metal ultrasonic detector, nuclear magnetic resonance testing technology, and self-made multi-functional three axial fluid–solid coupling test system. Experimental investigations are conducted on coal samples of different water contents before and after they undergo liquid-nitrogen freezing and thawing in order to determine the propagation law of surface fissures, the development law of internal micro-fissures, the development process of internal pores, the change law of the pore-size distribution, and the law of coal-sample deformation and gas seepage during the stress process. The test results show that, with the increase in water content in the liquid-nitrogen leaching process, the frost heave force on the coal surface increases, and the greater the increase ratio of the coal porosity, the faster is the development of micro-cracks and pores. Under the action of liquid nitrogen, the number of micro-pores, meso-pores, and macro-pores in the coal sample increased, and with the formation of new cracks and the connection of the original cracks, liquid-nitrogen freezing and thawing can promote the development of the pore structure in the coal body. The permeability changes of coal samples of different water contents during unloading failure exhibit obvious stage characteristics. The above results demonstrate that the moisture content of coal has a significant effect on the development of surface cracks and pore-damage characteristics of coal after liquid-nitrogen freezing and thawing, and there is a positive correlation between the surface crack expansion and internal damage of the coal samples of different moisture contents leached in liquid nitrogen.

Purpose – With the Chinese marine economy developing rapidly, the environmental problem has been occurring frequently, which needs green finance that supports energy conservation, environmental protection, and sustainable development to solve. Design/methodology/approach – In this paper, the entropy method is used to measure the development level of green finance, the DEA-ML index is used to measure the green total factor productivity which is used to indicate the high-quality development level of the marine economy in 11 coastal provinces (cities), then the grey correlation degree between them whose result shows that there is a certain correlation between the two variables is calculated. The fixed-effect model was used to analyze the relationship between them. Findings – The results show that the development level of green finance can promote the high-quality development of the marine economy, but there are still some problems in the process of green finance supporting the marine economy. Originality/value – This paper seeks new growth drivers, green finance, for the high-quality development of the marine economy, which few scholars have studied.

Background: Castration-resistant prostate cancer (CRPC) is a deadly malignancy without effective therapeutics. Cyclovirobuxine (CVB) can play an anticancer role by inhibiting mitochondrial function, regulating tumor cell apoptosis, dysregulating autophagy, and other mechanisms. This study aimed to examine the function and mechanism of CVB in CRPC to provide new insights into CRPC treatment. Methods: The effect of CVB on PC3 and C4-2 cell viability was determined using a CCK8 assay. Core therapeutic targets of CVB in CRPC cells were identified using RNA sequencing, online database, and PPI network analyses. Western blotting, RT–qPCR and molecular docking were performed to evaluate the regulation of core targets by CVB. Utilizing GO and KEGG enrichment analyses, the probable anti-CRPC mechanism of CVB was investigated. Immunofluorescence, flow cytometry and colony formation assays were used to verify the potential phenotypic regulatory role of CVB in CRPC. Results: CVB inhibited CRPC cell activity in a concentration-dependent manner. Mechanistically, it primarily regulated BRCA1-, POLD1-, BLM-, MSH2-, MSH6- and PCNA-mediated mismatch repair, homologous recombination repair, base excision repair, Fanconi anemia repair, and nucleotide excision repair pathways. Immunofluorescence, Western blot, flow cytometry and colony formation experiments showed that CVB induced DNA damage accumulation, cell apoptosis, and cell cycle arrest and inhibited CRPC cell proliferation. Conclusion: CVB can induce DNA damage accumulation in CRPC cells by targeting DNA repair pathways and then induce cell apoptosis and cell cycle arrest, eventually leading to inhibition of the long-term proliferation of CRPC cells.

Background and aimsObesity is an independent risk factor for cardiovascular disease development. Here, we aimed to examine and compare the predictive values of three novel obesity indices, lipid accumulation product (LAP), visceral adiposity index (VAI), and triglyceride-glucose (TyG) index, for cardiovascular subclinical organ damage.MethodsA total of 1,773 healthy individuals from the Hanzhong Adolescent Hypertension Study cohort were enrolled. Anthropometric, biochemical, urinary albumin-to-creatinine ratio (uACR), brachial-ankle pulse wave velocity (baPWV), and Cornell voltage-duration product data were collected. Furthermore, the potential risk factors for subclinical organ damage were investigated, with particular emphasis on examining the predictive value of the LAP, VAI, and TyG index for detecting subclinical organ damage.ResultsLAP, VAI, and TyG index exhibited a significant positive association with baPWV and uACR. However, only LAP and VAI were found to have a positive correlation with Cornell product. While the three indices did not show an association with electrocardiographic left ventricular hypertrophy, higher values of LAP and TyG index were significantly associated with an increased risk of arterial stiffness and albuminuria. Furthermore, after dividing the population into quartiles, the fourth quartiles of LAP and TyG index showed a significant association with arterial stiffness and albuminuria when compared with the first quartiles, in both unadjusted and fully adjusted models. Additionally, the concordance index (C-index) values for LAP, VAI, and TyG index were reasonably high for arterial stiffness (0.856, 0.856, and 0.857, respectively) and albuminuria (0.739, 0.737, and 0.746, respectively). Lastly, the analyses of continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI) demonstrated that the TyG index exhibited significantly higher predictive values for arterial stiffness and albuminuria compared with LAP and VAI.ConclusionLAP, VAI, and, especially, TyG index demonstrated utility in screening cardiovascular subclinical organ damage among Chinese adults in this community-based sample. These indices have the potential to function as markers for early detection of cardiovascular disease in otherwise healthy individuals.

In engineering measurements, metal foil strain gauges suffer from a limited range and low sensitivity, necessitating the development of flexible sensors to fill the gap. This paper presents a flexible, high-performance piezoresistive sensor using a composite consisting of graphene nanoplatelets (GNPs) and polydimethylsiloxane (PDMS). The proposed sensor demonstrated a significantly wider range (97%) and higher gauge factor (GF) (6.3), effectively addressing the shortcomings of traditional strain gauges. The microstructure of the GNPs/PDMS composite was observed using a scanning electron microscope, and the distribution of the conductive network was analyzed. The mechanical behavior of the sensor encapsulation was analyzed, leading to the determination of the mechanisms influencing encapsulation. Experiments based on a standard equal-strength beam were conducted to investigate the influence of the base and coating dimensions of the sensor. The results indicated that reducing the base thickness and increasing the coating length both contributed to the enhancement of the sensor’s performance. These findings provide valuable guidance for future development and design of flexible sensors.

Abstract Neural precursor cell expressed developmentally downregulated 4‐like (NEDD4L), a member of the E3 ubiquitin‐protein ligases, encoded by NEDD4L gene, was found to be involved in in salt sensitivity by regulating sodium reabsorption in salt‐sensitive rats. The authors aimed to explore the associations of NEDD4L genetic variants with salt sensitivity, blood pressure (BP) changes and hypertension incidence in Chinese adults. Participants from 124 families in Northern China in the Baoji Salt‐Sensitive Study Cohort in 2004, who received the chronic salt intake intervention, including a 7‐day low‐salt diet (3.0 g/day) and a 7‐day high‐salt diet (18 g/day), were analyzed. Besides, the development of hypertension over 14 years was evaluated. NEDD4L single nucleotide polymorphism (SNP) rs74408486 was shown to be significantly associated with systolic BP (SBP), diastolic BP (DBP) and mean arterial pressure (MAP) responses to low‐salt diet, while SNPs rs292449 and rs2288775 were significantly associated with pulse pressure (PP) response to high‐salt diet. In addition, SNP rs4149605, rs73450471, and rs482805 were significantly associated with the longitudinal changes in SBP, DBP, MAP, or PP at 14 years of follow‐up. SNP rs292449 was significantly associated with hypertension incidence over the 14‐year follow‐up. Finally, this gene‐based analysis found that NEDD4L was significantly associated with longitudinal BP changes and the incidence of hypertension over the 14‐year follow‐up. This study indicated that gene polymorphism in NEDD4L serve an important function in salt sensitivity, longitudinal BP change and development of hypertension in the Chinese population.

Predicting earthquakes through reasonable methods can significantly reduce the damage caused by secondary disasters such as tsunamis. Recently, machine learning (ML) approaches have been employed to predict laboratory earthquakes using stick-slip dynamics data obtained from sheared granular fault experiments. Here, we adopt the combined finite-discrete element method (FDEM) to simulate a two-dimensional sheared granular fault system, from which abundant fault dynamics data (i.e., displacement and velocity) during stick-slip cycles are collected at 2203 “sensor” points densely placed along and inside the gouge. We use the simulated data to train LightGBM (Light Gradient Boosting Machine) models and predict the gouge-plate friction coefficient (an indicator of stick-slips and the friction state of the fault). To optimize the data, we build the importance ranking of input features and select those with top feature importance for prediction. We then use the optimized data and their statistics for training and finally reach a LightGBM model with an acceptable prediction accuracy (R2 = 0.94). The SHAP (SHapley Additive exPlanations) values of input features are also calculated to quantify their contributions to the prediction. We show that when sufficient fault dynamics data are available, LightGBM, together with the SHAP value approach, is capable of accurately predicting the friction state of laboratory faults and can also help pinpoint the most critical input features for laboratory earthquake prediction. This work may shed light on natural earthquake prediction and open new possibilities to explore useful earthquake precursors using artificial intelligence.

Abstract Real-time mine ventilation network solution is the core way to realize the actual intelligent ventilation, and ventilation friction resistance coefficient is a significant parameter of network solution. With the help of fractal theory to characterize the three-dimensional roughness characteristics of tunnel surrounding rock. A method to describe the roughness by fractal dimension and fractal intercept. We put the fractal dimension and fractal intercept into Matlab to randomly generate three-dimensional laser scanning data of tunnels. The fusion of the two fractal parameters made the three-dimensional roughness surface information more comprehensive. It has been applied to field practice accurately. Compared to the simulation results show that the relative error of the new prediction results is 3%. Comprehensive evaluation analysis shows that the new friction wind resistance formula can fully reflect the influence of three-dimensional rough surfaces on airflow friction resistance. With the help of three-dimensional laser scanning technology, we can calculate the airflow friction resistance of the tunnel quickly and accurately, which provides a reference for the development of key technology and the theory of intelligent ventilation parameter measurement.

A mechanical model of a circular section of a tunnel roadway considering damage is established to improve the impact protection performance of the “roadway rock-support” system and provide a theoretical basis for designing coal mine impact ground pressure roadway support. The formula of the critical rock burst load of a circular roadway is derived according to the instability theory of rock burst disturbance response. The influence of mechanical properties of surrounding rock and roadway support strength on the critical rock burst load of a roadway rock-support system is studied using the control variable method. The research shows that 1) under the support condition of a roadway, with the increase of uniaxial compressive strength, softening modulus, and internal friction angle of surrounding rock, the critical rock burst load of a roadway has an increasing trend; the critical rock burst load of roadway decreases with the increase of the elastic modulus of the surrounding rock. 2) Under the condition of no support, with the increase of uniaxial compressive strength, elastic modulus, and internal friction angle of surrounding rock, the critical rock burst load of roadway tends to increase. With the decrease of the surrounding rock’s softening modulus, the critical rock burst load of the roadway decreases. When the aforementioned four kinds of surrounding rock influence factors are the same, the critical load of rock burst under the supporting condition is much larger than that under the non-supporting condition. 3) A new impact tendency index K is defined as the ratio of the softening modulus and the elastic modulus. 4) The critical load of rock burst increases approximately linearly with the increase of support stress. The critical load of a rock burst is about 400 times as large as the supporting stress. Increasing roadway support strength can greatly improve the stability of the supporting and roadway surrounding rock system, and the stability of the supporting and roadway surrounding rock system can be improved by reasonably changing the mechanical properties of the surrounding rock.

Introduction: In the coal mining process, the intense mining pressure is an important factor hindering the safe and efficient production of the working face. In severe cases, it causes deformations in roadways such as roof breakages and rockbursts, and leads to instability. This can result in the roof falling over a large area and the coal wall, thereby inducing dynamic disasters. These aspects have restricted the economic benefits of coal.Methods: In this study, we set four model limitations based on the limited scope of action of the mining pressure itself and the quantitative relationships between mining pressures in different regions. A multiple linear regression model with these limitations is proposed for predicting the mining pressure for preventing roof breakages and rockbursts. Based on a hydraulic support monitoring dataset from a fully mechanized caving face of coal mining, the mining pressure prediction model is trained by using the first 70% of the dataset. And the linear regression coefficient of the model and the predicted value of the mining pressure are obtained. Then, the last 30% of the dataset was used for the validation of the model.Results: The research results show that the constrained multiple linear regression model can achieve remarkable prediction results. According to predictions of tens of thousands of on-site mining pressure datasets, the predicted data and actual pressure data have the same change trend and maintain a low relative error.Discussion: Therefore, after real-time mining pressure monitoring, the system obtains the roof pressure of the fully mechanized mining face. According to the dataset, the proposed prediction model algorithm quickly predicts the roof pressure value of the next mining section and effectively forewarns roof breakages and other accidents.

This paper introduces a diluted prediction method for bitcoin and gold based on cycle prediction. This method does not need to quantify the external parameters like robot learning and neural network autoregressive model, but mainly uses ARIMA to feedback the parameter values into risk coefficients under the condition of obtaining the optimal solution circularly, and the price prediction of a single period in the future is carried out with a fixed number of samples, thus realizing the high-precision prediction of bitcoin and gold prices. In the application simulation, the real data of bitcoin and gold from 2016 to 2021 are selected. After 1000 times of Monte Carlo simulations, 919 times of the yield is more than 3 times, 157 times of the yield is more than 8 times, and the minimum yield is about 2 times. At the same time, this paper puts forward an investment strategy for this prediction method, which realizes a very safe profit with a final return rate of 6.2 times under the condition of making full use of the prediction risk coefficient. The prediction method and investment scheme bring a brand-new high-precision prediction method and targeted investment strategy with high safety coefficient to all the investors, which has great economic value.

Abstract Corin, a transmembrane serine protease that can cleave pro‐atrial natriuretic peptide (Pro‐ANP) into smaller bioactive molecule atrial natriuretic peptide, has been shown to be involved in the pathophysiology of hypertension, cardiac hypertrophy. We sought to examine the associations of corin genetic variations with salt sensitivity, blood pressure (BP) changes and hypertension incidence. We studied participants of the original Baoji Salt‐Sensitive cohort, recruited from 124 families from seven Chinese villages in 2004 who sequentially received a usual baseline salt diet, a 7‐day low salt diet (3 g/day) and a 7‐day high salt diet (18 g/day), respectively. They were followed up for 8 years (in 2009, 2012) to evaluate the development of hypertension. Corin SNP rs3749584 was significantly associated with diastolic BP (DBP) and mean arterial pressure (MAP) response to low‐salt diet, while rs4695253, rs17654278 were associated with pulse pressure (PP) response to low‐salt diet. SNPs rs4695253, rs12509275, rs2351783, rs2271036, rs2271037 were significantly associated with systolic BP (SBP), DBP, and MAP responses to high‐salt diet. In addition, SNPs rs12641823, rs6834933, rs2271036, and rs22710367 were significantly associated with the longitudinal changes in SBP, DBP, MAP, or PP over 8 years of follow‐up. SNP rs73814824 was significantly associated with the incidence of hypertension over 8 years. Gene‐based analysis showed that corin gene was significantly associated with longitudinal BP changes and hypertension incidence after 8‐year follow‐up. This study suggests that corin may play a role in salt sensitivity, BP progression, and development of hypertension.

The increasing gap between China’s oil demand and its own production capacity leads to greater dependence on imported oil. This paper investigates that how does the growing dependence would change the dynamic relationship between oil price fluctuation and inflation in China by applying an extended wavelet analysis framework. The results indicate that there is a positive oil volatility–inflation pass through in the short term, with occasional feedback from inflation to oil price. And in the medium and long term, the pass through persists over time, which differ from previous studies based on data from other countries. The findings also embody consistent causality from oil price fluctuation to inflation and significant positive correlation. In general, our results justify the theory of cost-push inflation and fit the fact that China has been experiencing significant economic transitions.

The Himalayan leucogranites provide a good opportunity to investigate the crustal evolution of the southern Qinghai-Tibet Plateau. In this study, we present zircon U-Pb and monazite U-Th-Pb ages, zircon Hf isotopes and whole-rock Sr-Nd-Pb isotopes and major and trace elements for the Liemai two-mica granite, eastern Himalaya. Together with previously published data we revalued the petrogenesis of the Early Eocene magmatic rocks in this region and their geological implications. The zircon and monazite U-(Th)-Pb dating results showed that the Liemai two-mica granite was generated at ∼ 43 Ma, similar to adjacent Yardoi, Dala and Quedang adakitic two-mica granites, Ridang subvolcanic rocks and Yardoi leucogranite. The Liemai two-mica granite, similar to these coeval adakitic two-mica granites, is enriched in SiO2, Al2O3, Th, U, Pb, La, and Sr, and depleted in MgO, total iron, Yb and Y with high Sr/Y and (La/Yb)N ratios (showing adakitic affinities), and exhibits enriched Sr-Nd-Pb-Hf isotopic compositions, suggesting an origin of a thickened lower crust consisting mainly of garnet amphibolite. Although the Ridang subvolcanic rocks and Yardoi leucogranite show similar Sr-Nd-Hf isotopes to these adjacent coeval two-mica granites, perceptible differences in whole-rock major and trace elements can be observed. Broadly, these granites can be divided into high-Mg# granites (HMGs, the two-mica granites) and low-Mg# granites (LMGs, the Ridang subvolcanic rocks and Yardoi leucogranite). The former has relatively higher contents of total iron, MgO, Mg#, TiO2, P2O5, LREE, Y, Th, Sr, incompatible elements (Cr and Ni) and Eu/Eu* values, and lower contents of SiO2 and Rb/Sr and Rb/Ba ratios, thus is less evolved than the latter. According to recent studies of differentiation processes in silicic magma reservoirs, we proposed that the HMGs represent a congealed crystal mush that was composed of ‘cumulate crystals’ and a trapped interstitial liquid, while the LMGs represent the almost pure liquid that was extracted from the crystal mush. Modeling using the trace elements Sr and Ba shows that the extraction probably occurred when the crystallinity of the mush was ∼ 60%–63%, at least for the most evolved LMGs sample. The HMGs correspond to a residual crystal mush that had a terminal porosity of ∼ 21%–25% filled with a trapped interstitial liquid. Underplating of mafic magmas following slab breakoff of the Neo-Tethys oceanic lithosphere caused partial melting of the amphibolitic lower crust, which had been thickened to ~50 km prior to ~43 Ma.

A low-carbon and energy-saving sintering process with uniform temperature distribution has been developed to address several issues associated with the sintering of drill bits in medium-frequency furnaces, namely, the large circumferential temperature differences, uneven heating of the mold, and low energy utilization. Theoretical calculations indicated that the output energy of the conventional drill bit sintering process was 12.7 kW·h, with an energy loss of 8.84 kW·h. The low-carbon sintering process achieved an output energy of 4.2 kW·h, with an energy loss of only 0.26 kW·h. Consequently, the energy utilization rates for the two processes were 30.4% and 93.8%, respectively. It was observed through the experiment that when sintering 76/49 mm drill bits at insulation temperatures of 900 °C and 1080 °C, the circumferential temperature differences in the mold were 43.7 °C and 48 °C, respectively, in the conventional drill bit sintering process. In contrast, the circumferential temperature differences in the mold were reduced to 8.7 °C and 11.3 °C, respectively, in the low-carbon and energy-saving sintering process with uniform temperature. This indicates that the average circumferential temperature difference in the mold can be reduced by 81.61% at 900 °C and by 76.46% at 1080 °C, leading to improved drill bit quality.

Abstract Uromodulin, also named Tamm Horsfall protein, have been associated with renal function and sodium homeostasis regulation. The authors sought to examine the effects of salt intake on plasma and urinary uromodulin levels and the association of its genetic variants with salt sensitivity in Chinese adults. Eighty patients from our natural population cohort were maintained sequentially either on a usual diet for 3 days, a low‐salt diet (3.0 g) for 7 days, and a high‐salt diet (18.0 g) for an additional 7 days. In addition, the authors studied 514 patients of the Baoji Salt‐Sensitive Study, recruited from 124 families who received the same salt intake intervention, and investigated the association of genetic variations in uromodulin gene with salt sensitivity. Plasma uromodulin levels were significantly lower on a high‐salt diet than on a baseline diet (28.3 ± 4.5 vs. 54.9 ± 8.8 ng/ml). Daily urinary excretions of uromodulin were significantly decreased on a high‐salt diet than on a low‐salt diet (28.7 ± 6.7 vs. 157.2 ± 21.7 ng/ml). SNPs rs7193058 and rs4997081 were associated with the diastolic blood pressure (DBP), mean arterial pressure (MAP) responses to the high‐salt diet. In addition, several SNPs in the uromodulin gene were significantly associated with pulse pressure (PP) response to the low‐salt intervention. This study shows that dietary salt intake affects plasma and urinary uromodulin levels and that uromodulin may play a role in the pathophysiological process of salt sensitivity in the Chinese populations.