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Abstract With the continuous spread of the SARS-CoV-2 globally, viral mutations have accumulated. As a result, SARS-CoV-2 became more contagious, and has a higher risk of immune escape and reinfection. To identify variants and have an awareness of the prevalence of these variants, this study selected four segments containing mutations on the S gene of the SARS-CoV-2. Then a rapid and convenient variants detection method was established using high-resolution melting(HRM) analysis combined with nested polymerase chain reaction(PCR). The total detection process takes about 5 h. Through comprehensive analysis of the results from the four reaction systems, the identification of seven important Omicron variants(BA.2, BA.2.75, BA.5.2, BF.7, BQ.1, XBB.1 and XBB.2) can be achieved, with significant differentiation in the melting curves of each variant group. The method established in this study was used to genotype positive specimens in COVID-19 nucleic acid testing, the overall concordance rate compared to whole genome sequencing results was 88.9%, and the positive concordance rate of each sublineage was greater than 80% and the negative concordance rate was greater than 94.4%. The detection of clinical specimens has demonstrated that the HRM analysis established in this study is an effective, rapid and convenient variant identification method, which can be used for monitoring SARS-CoV-2 variants and has important value in addressing public health issues caused by the ongoing mutations of the SARS-CoV-2.

Abstract To assess the impact of China’s regional emergency logistics response capabilities on economic growth sustainability, this study develops a set of comprehensive indicators. It applies the entropy weight method combined with the TOPSIS method to evaluate these capabilities across regions. Based on panel data from 30 provinces in China from 2012 to 2021, this study employs panel models, panel quantile regression, and panel threshold models to analyze the impact of emergency logistics response capability on sustainable economic growth. By measuring the regional emergency logistics response capability and examining its effects on the sustainability of economic growth, this research provides foreign investors with a clearer understanding of the ability of different regions in China to handle unexpected public incidents. This, in turn, helps reduce investment uncertainty, mitigate certain risks, and offers valuable insights for enhancing the efficiency of international investments in China. Key findings are: (1) Since 2018, the establishment of the Ministry of Emergency Management has significantly improved China’s regional emergency logistics capabilities, with the eastern region outperforming the central and western regions. (2) Enhancing China’s emergency logistics response capability helps improve the sustainability level of economic growth. This reflects how China’s emergency management departments can mitigate the adverse impacts of public emergencies on economic growth by transforming social logistics into emergency logistics. (3) As emergency response capabilities have strengthened, their impact on economic sustainability initially decreased but later increased.

Peptides, as small molecular compounds, exhibit prominent advantages in the inhibition of coronaviruses due to their safety, efficacy, and specificity, holding great promise as drugs against coronaviruses. The rapid and efficient determination of the activity of anti-coronavirus peptides (ACovPs) can greatly accelerate the development of drugs for treating coronavirus-related diseases. Hence, we present ACVPICPred, a computational model designed to predict the inhibitory activity of ACovPs based on their sequences and structural information. By leveraging bioinformatics tools AlphaFold3 for structural predictions and several feature extraction methods, the model integrates both sequence and structural features to enhance prediction accuracy. To address the limitations of existing datasets, we employed data augmentation techniques, including the introduction of noise and the SMOGN, to improve the model robustness. The model’s performance was evaluated through five-fold cross-validation, achieving a Pearson correlation coefficient of 0.7668 (p

With the country vigorously promoting structural reform on the supply side of energy, the installed capacity of new energy sources has been rising and competition in the power market has become increasingly fierce. On the other hand, the complexity and volatility of the global coal market has led to a rise in the cost of power generation enterprises using coal as their energy source. Coal heat value is one of the most important evaluation criteria for coal quality and is also the most important basis for coal procurement. Accurate prediction of coal heat value can effectively control power plant operation and procurement costs. In order to achieve efficient prediction of the heat value of coal, the Pearson coefficients were used to select the characteristics of the variables of interest, the DBSCAN algorithm was used to de-noise 1733 assay data of a power plant's own coal plant in the past two years, and spectral clustering (SC) analysis was performed on the de-noised data. The classified subsample sets were then used to build prediction models using the extreme gradient boosting (XGBoost) algorithm and compared with Ordinary Least Squares (OLS) and support vector machines (SVM) models. The performance of the models was compared with that of OLS and SVM. The results show that the accuracy of the XGBoost-based coal-fired heat value prediction model for power stations is significantly better than that of the other algorithms, and the generalization ability is stronger. The prediction model can further improve the refinement level of the model and provide a reliable and efficient method for coal-fired power station heat value prediction.

It is well known that the grain size of high-entropy ceramics is quite small owing to the sluggish diffusion effect. However, abnormal grain growth often occurs in high-entropy pseudobrookite ceramics, ultimately resulting in the formation of many abnormally grown grains with a grain size as large as 50 μm. To study this phenomenon, the grain growth behavior of high-entropy pseudobrookite ceramics was systematically investigated in this paper. The results demonstrate that the starting material powders first react with each other to form a high-entropy intermediate phase and calcined TiO2 powders (TiO2-1100 °C), and then as the sintering temperature increases, the formed high-entropy intermediate phase further reacts with TiO2-1100 °C to form high-entropy pseudobrookite ceramics. Thus, in this system, in addition to the sluggish diffusion effect, the grain sizes of the high-entropy intermediate phase and TiO2-1100 °C also affect the morphology of high-entropy pseudobrookite. Compared to nanosized TiO2, micron-sized TiO2 has a lower sintering activity. Therefore, the high-entropy intermediate phases (Mg,Co,Ni,Zn)TiO3 and TiO2-1100 °C prepared with micron-sized starting materials exhibit lower grain sizes, finally resulting in the formation of high-entropy (Mg,Co,Ni,Zn)Ti2O5 with small grain sizes. Moreover, nano-indentation and thermal conductivity tests were carried out on high-entropy (Mg,Co,Ni,Zn)Ti2O5 with different morphologies. The results show that the hardness of high-entropy (Mg,Co,Ni,Zn)Ti2O5 increases from 6.05 to 9.95 GPa as the grain size increases, whereas the thermal conductivity decreases from 2.091±0.006 to 1.583±0.006 W·m−1·K−1. All these results indicate that high-entropy (Mg,Co,Ni,Zn)Ti2O5 with a small grain size is a potential material for thermal protection.

An innovative multi-layer composite explosion containment vessel (CECV) utilizing a sliding steel plate-aluminum honeycomb-fiber cloth sandwich is put forward to improve the anti-explosion capacity of a conventional single-layer explosion containment vessel (SECV). Firstly, a series of experiments and finite element (FE) simulations of internal explosions are implemented to understand the basic anti-explosion characteristics of a SECV and the rationality of the computational models and methods is verified by the comparison between the experimental results and simulation results. Based on this, the CECV is designed in detail and a variety of FE simulations are carried out to investigate effects of the sandwich structure, the explosive quantity and the laying mode of the fiber cloth on anti-explosion performance and dynamic response of the CECV under internal explosions. Simulation results indicate that the end cover is the critical position for both the SECV and CECV. The maximum pressure of the explosion shock wave and the maximum strain of the CECV can be extremely declined compared to those of the SECV. As a result, the explosive quantity the CECV can sustain is up to 20 times of that the SECV can sustain. Besides, as the explosive quantity increases, the internal pressure of the CECV keeps growing and the plastic deformation and failure of the sandwich structure become more and more severe, yielding plastic strain of the CECV in addition to elastic strain. The results also reveal that the laying angles of the fiber cloth's five layers have an impact on the anti-explosion performance of the CECV. For example, the CECV with fiber cloth layered in 0°/45°/90°/45°/0° mode has the optimal anti-capacity, compared to 0°/0°/0°/0°/0° and 0°/30°/60°/30°/0° modes. Overall, owing to remarkable anti-explosion capacity, this CECV can be regarded as a promising candidate for explosion resistance.

Sepsis is a systemic inflammatory response syndrome in which the host response to infection is dysregulated, leading to circulatory dysfunction and multi-organ damage. It has a high mortality rate and its incidence is increasing year by year, posing a serious threat to human life and health. Mesenchymal stem cells (MSC) have the following properties: hematopoietic support, provision of nutrients, activation of endogenous stem/progenitor cells, repair of tissue damage, elimination of inflammation, immunomodulation, promotion of neovascularization, chemotaxis and migration, anti-apoptosis, anti-oxidation, anti-fibrosis, homing, and many other effects. A large number of studies have confirmed that MSC from different sources have their own characteristics. This article reviews the pathogenesis of sepsis, the biological properties of MSC, and the advantages and disadvantages of different sources of MSC for the treatment of sepsis and their characteristics.

This study presents a comprehensive technical, environmental, and economic analysis of a thermal power plant utilizing solid oxide fuel cells (SOFC) to meet urban demands for electrical power, fresh water, and hydrogen. The integrated system includes SOFC with anode and cathode recycling, multi-effect desalination, a power generation cycle with a heat recovery unit using a thermoelectric generator, and a hydrogen compression unit. A detailed parametric analysis was conducted to identify optimal conditions for key outputs such as total cost rate and exergy efficiency, employing genetic algorithms and artificial neural networks. According to the economic evaluation, the SOFC stack accounts for 65.11 % of total costs at 139.8 $/h, with the inverter contributing 11.9 %. The environmental analysis shows that the proposed system emits the least CO2 per energy unit compared to SOFC/GT and SOFC/GT/RC systems. The parametric study indicates that increasing the pressure ratio enhances the output power of the SOFC and the production of the gas turbine. However, this also leads to higher compressor consumption, thereby reducing net power. Furthermore, increasing the current density results in greater production of electricity, hydrogen, and freshwater, while also raising the exhaust gas temperature, which aids in the desalination process. The optimization results show an exergy efficiency of 61.38 % and a total cost rate of 132.9 $/h, with artificial neural networks reducing optimization time from 124 h to 14 min.

In response to the development of the concepts of “carbon neutrality” and “carbon peak”, it is critical to developing materials with high near-infrared (NIR) solar reflectivity and high emissivity in the atmospheric transparency window (ATW; 8–13 μm) to advance zero energy consumption radiative cooling technology. To regulate emission and reflection properties, a series of high-entropy rare earth stannate ceramics (HE-RE2Sn2O7: (Y0.2La0.2Nd0.2Eu0.2Gd0.2)2Sn2O7, (Y0.2La0.2Sm0.2Eu0.2Lu0.2)2Sn2O7, and (Y0.2La0.2Gd0.2Yb0.2Lu0.2)2Sn2O7) with severe lattice distortion were prepared using a solid phase reaction followed by a pressureless sintering method for the first time. Lattice distortion is accomplished by introducing rare earth elements with different cation radii and mass. The as-synthesized HE-RE2Sn2O7 ceramics possess high ATW emissivity (91.38%–95.41%), high NIR solar reflectivity (92.74%–97.62%), low thermal conductivity (1.080–1.619 W·m−1·K−1), and excellent chemical stability. On the one hand, the lattice distortion intensifies the asymmetry of the structural unit to cause a notable alteration in the electric dipole moment, ultimately enlarging the ATW emissivity. On the other hand, by selecting difficult excitation elements, HE-RE2Sn2O7, which has a wide band gap (Eg), exhibits high NIR solar reflectivity. Hence, the multi-component design can effectively enhance radiative cooling ability of HE-RE2Sn2O7 and provide a novel strategy for developing radiative cooling materials.

Lower early strength has been one of the bottlenecks of low-carbon supersulfated cement (SSC), consisting of slag (∼85 wt.%), gypsum (∼10 wt.%), and a small amount of an alkali activator (Portland cement (PC), ∼5 wt.%). The work aims at improving the early strength of SSC with the addition of calcium formate (CF). Different dosages (1 wt.%, 2 wt.%, 3 wt.%) of CF were added to the SSC. Then, compressive strength, heat flow, hydration product assemblage, and hydration degree of slag were obtained to reveal the role of CF. The results show that CF would significantly increase the compressive strength of the SSC, and the higher the dosage of CF, the more pronounced the effect is. 3 wt.% of CF would increase the 3-day and 28-day compressive strength of the SSC by 126% and 172%, respectively. CF would accelerate the hydration of slag, increase the hydration degree of slag and production of C-(A)-S-H gels; however, it would inhibit the rapid production of AFt during the first 3 days, and have little influence on the final production of AFt. In addition, the lower the crystal-gel ratio (the ratio between AFt and C-(A)-S-H gel by mass) is, the higher the compressive strength. The enhancement effect of CF was attributed to a more appropriate hydration environment (higher Ca2+ concentration and lower pH value), which could promote the precipitation of C-(A)-S-H gels, inhibit the rapid formation of Aft, and reduce the crystal-gel ratio of the system.

Coal gasification fine slag (CGFS) has high utilization value, but the low recovery rate of residue carbon greatly restricts its resource utilization. The oil agglomeration separation method has obvious advantages in the CGFS separation process, but its separation efficiency is severely limited by the symbiotic structure of carbon and ash. In order to break through the bottleneck problem of residue carbon separation and enrichment technology by oil agglomeration method, the effects of ultrasonic time, ultrasonic power, fluid shear time and their interaction on oil agglomeration and separation were investigated in this paper. Combined with BET, particle size distribution, FT-IR, XPS and SEM-EDS analysis methods, the strengthening mechanism of ultrasonic cavitation and fluid shear (UC-FS) pretreatment on oil agglomeration separation was revealed. The results show that when the ultrasonic power is 270 W, the ultrasonic treatment time is 29 min, and the fluid shear time is 23 min, the concentrate with ash content of 9.55% and the tailings with ash content of 91.51% can be obtained, and the combustible recovery rate can be increased to 90.54%. Ultrasonic cavitation gradually loosens the original dense carbon ash structure, and promotes the development of the pore structure of CGFS in coordination with the scouring effect of fluid shear, which increases the dissociation degree of carbon ash particles and thus reduces the ash content of concentrate. UC-FS pretreatment can effectively increase the proportion of hydrophobic groups such as C—C, C=C and C—H on the surface of carbon residue, increase its contact angle from 110.34° to 121.16°, and further expand the difference of hydrophilic and hydrophobic properties on the surface of carbon and ash particles, thus improving the effect of oil agglomeration separation. The mechanism of UC-FS synergistic pretreatment to improve the efficient separation of carbon ash particles is mainly attributed to the micro-abrasive effect generated by the coupling of ultrasonic cavitation bubbles and fine-grained microspheres. This study can provide theoretical basis and technical guidance for the separation and utilization of CGFS.

With the development of the social economy, research on stock market prediction is in full swing. However, the fluctuations in stock price and returns are influenced by many factors, including political policies, market environment, investor psychology, and so on. The traditional analysis method, based on subjective experience, requires significant time and effort, and its prediction accuracy is often poor. Now, the application of machine learning algorithms to predict stock returns has become a hot topic among scholars. This article comprehensively analyzes the advantages and disadvantages of support vector machine (SVM), tree-based algorithms, and neural network algorithms in processing tabular data and time series data. It proposes a hybrid model based on the deep neural network (DNN) and TabNet models, combining the strengths of the DNN and tree-based models. In the model training stage, two neural networks are established to accept the inputs of ID features and numerical features, respectively, and multiple fully connected layers are used to complete the construction of the DNN model. The TabNet is implemented based on the attention transformer and feature transformer, and the prediction results of the two models are fused. The proposed model has a best Pearson correlation coefficient (PCC) value and a lowest root mean square error (RMSE) value at the same time, because the hybrid algorithm performs particularly well on large data sets with the least feature engineering and has strong interpretability, such as quantifying the contribution of different features in the model, it has certain theoretical significance and wide application value.

IntroductionDue to global industrialization and urbanization, natural disasters, accidents, and public health emergencies happen frequently. These events cause significant loss of life and property damage to countries worldwide. In the context of frequent public emergencies, enhancing emergency logistics response capabilities is crucial, ensuring rapid supply of rescue materials and support for rescue personnel, thereby saving lives and reducing economic losses.MethodsIn order to identify the changes and enhancement paths of the emergency logistics response capability of Chinese regions under the shocks of public emergencies, this paper innovatively constructs emergency logistics response capability measurement indicators. This paper uses the entropy weight TOPSIS method and panel quantile regression model to quantify the change and enhancement paths of China’s regional emergency logistics response capability under different events.ResultsIt is found that: (1) The gap in emergency logistics response capability among Chinese regions is widening, with the internal difference in the eastern region higher than that in the west, while the difference in the central region is relatively low. (2) China’s emergency management department can effectively transform social logistics into emergency logistics, thereby promoting the improvement of emergency logistics response capabilities. (3) Sudden geological disasters break through the limits of social logistics resources when they cross lower scales, resulting in the failure of emergency logistics response capabilities.DiscussionThis paper expands research on assessing emergency logistics capabilities, addressing issues in existing assessments such as reliance on single indicators and subjective measurement methods. Additionally, it quantifies the dynamic changes in China’s regional emergency logistics response capabilities under public emergencies by extending the study of event content, types, and impacts. This enhances discussions on the effects of public emergencies. Finally, from an empirical perspective, the paper explores pathways to enhance regional emergency logistics response capabilities in China. In practice, this paper assists countries worldwide in assessing whether different regions of China can effectively provide emergency support for various resources in direct investments, thus providing a scientific basis for investment decisions.

Abstract Tea is an indispensable beverage in people’s daily life. However, the relationship between tea intake and dental caries and periodontitis is controversial. We extracted datasets for tea intake and oral diseases from genome-wide association studies (GWASs) conducted by the UK Biobank and the Gene Lifestyle Interactions in Dental Endpoints consortium. We selected 38 single-nucleotide polymorphisms (SNPs) significantly associated with tea intake as instrumental variables (IVs) (P

The relationship between rust layer evolution and the corresponding corrosion resistance of 55AlZnMg coatings in NaCl solution were investigated by Scanning electron microscope, micro-Raman spectroscopy and electrochemical impedance spectroscopy. Alloy phases composing the coating were not corroded synchronically, and thus the coating would not transfer into a rust layer integrally along the depth direction. The rapid thickening of the rust layer was triggered with an outward migration of such cations as Zn2+ and Al3+, which were generated from the preferential corrosion of interdendritic MgZn2/Zn-rich phases. During this process, benefiting from the compact rust layer consisting of protective corrosion products (e.g., simonkolleite, hydrozincite and layered double hydroxide), the corrosion resistance of the coating was sharply enhanced until the immersion for 28 days. Later, because of transformations of simonkolleite and hydrozincite, the stratification of the rust layer and micro-cracks caused by the formation of Zn(OH)2 in large quantities, which led to a formation of fast diffusion tunnel and thus impaired the corrosion resistance of the coating. It could be concluded that the corrosion resistance of 55AlZnMg coatings in NaCl solution were not only determined by the properties of its corrosion products, but also, on the overall properties of rust layer.

Aiming at the problems of low processing efficiency and uneven material removal during shear rheological polishing (SRP) of polycrystalline tungsten, this paper introduces the Fenton-like reaction between H2O2 and Cu2+ to enhance the chemical effect on material removal. Passivation behavior and removal mechanisms were investigated using electrochemical tests, scanning electron microscopy, atomic force microscopy, and other characterization methods. Results show that the Fenton-like reaction exhibits excellent activity under the combined action of H2O2 and Cu(NO3)2, obtaining a satisfactory material removal rate of 702.22 Å⋅min−1 and a surface roughness Rq of 7.05 nm. The efficacy of the H2O2+Cu(NO3)2 slurry lies in its superior removal and passivation performance, attributed to the generation of hydroxyl radicals through the Fenton-like reaction. These radicals facilitate the formation of a WO3 passivation layer with good corrosion resistance on the surface, while enabling easy removal through mechanical wear. In addition, the plastic deformation mechanism of passivation layer was also studied by nanoscratch tests and transmission electron microscopy. It is found that a pure plastic flow groove can be obtained in the load range of 3–100 mN, accompanied by the formation of asymmetric deformation and pile-ups in the subsurface of the main plastic zone.

Laser melting deposition–produced Ti6Al4V additive manufacturingparts tend to manifest as coarse columnar grains. This paper optimises the laser pulse frequency to manage the microstructuralcharacteristics of Ti6Al4V parts and enhance their tensile properties and corrosion resistance. A fiber laser processing equipment with a laser power of 1200 W and a spot diameter of 2.0 mm was employed for all experiments, which provides pulsed lasers at 4, 40, 400, and 4000 Hz at a scanning speed of 8 mm/s and a duty cycle of 95 % for comparative research.The findings demonstrated that increasing the pulse frequency improved the deposition efficiency.An appropriate pulse frequency could promote the refinement and columnar-to-equiaxed transition (CET) of primary β grains.At 400 Hz, the Ti6Al4V-deposited parts yielded refined equiaxed grains.The average grain size in the middle of the sample was about 206.8 μm,and the microstructure mainly comprised fine α-laths in a lamellar structure, which yielded the best overall performance of the parts, with the ultimate tensile strength and elongation reaching 1083 MPa and 4.09 %, respectively.Therefore, improvingthe structural properties of partsby regulating the deposition process, which is conducive to the online regulation of the forming quality of laser deposition parts, is an effective and feasible approach.

Adult respiratory distress syndrome due to viral pneumonia occurs predominantly in immunodeficient populations; adult respiratory distress syndrome secondary to human herpesvirus HHV-6 and HHV-7 pneumonia is extremely rare. Whipple’s disease, caused by Tropheryma whipplei, a Gram-positive bacillus and obligate intracellular pathogen, is clinically challenging to diagnose. Whipple’s disease is a chronic multisystem infectious disease caused by T. whipplei, most often affecting the gastrointestinal tract and joints, seldom the lungs. Both pathogens are opportunistic. We report a case of mixed infectious pneumonia in a patient with type 2 diabetes mellitus. The patient presented with dyspnea and intermittent fever. Imaging revealed multiple large patchy consolidations in the left lung. Routine anti-infective therapy was ineffective. Metagenomic next generation sequencing of bronchoalveolar lavage fluid indicated HHV-6 and HHV-7 pneumonia concurrent with T. whipplei and Streptococcus co-infections. Meropenem was administered to improve treatment. This case represents a rare mixed lung infection by multiple uncommon pathogens, and is of particular clinical significance.

BackgroundMore than 700 million people worldwide suffer from diseases of the pancreas, such as diabetes, pancreatitis and pancreatic cancer. Often dysregulation of potassium (K+) channels, co-transporters and pumps can promote development and progression of many types of these diseases. The role of K+ transport system in pancreatic cell homeostasis and disease development remains largely unexplored. Potassium isotope analysis (δ41K), however, might have the potential to detect minute changes in metabolic processes relevant for pancreatic diseases.MethodsWe assessed urinary K isotope composition in a case-control study by measuring K concentrations and δ41K in spot urines collected from patients diagnosed with pancreatic cancer (n=18), other pancreas-related diseases (n=14) and compared those data to healthy controls (n=16). ResultsOur results show that urinary K+ levels for patients with diseased pancreas (benign and pancreatic cancer) are significantly lower than the healthy controls. For δ41K, the values tend to be higher for individuals with pancreatic cancer (mean δ41K = -0.58 ± 0.33‰) than for healthy individuals (mean δ41K = -0.78 ± 0.19‰) but the difference is not significant (p=0.08). For diabetics, urinary K+ levels are significantly lower (p=0.03) and δ41K is significantly higher (p=0.009) than for the healthy controls. These results suggest that urinary K+ levels and K isotopes can help identify K disturbances related to diabetes, an associated factors of all-cause mortality for diabetics.ConclusionAlthough the K isotope results should be considered exploratory and hypothesis-generating and future studies should focus on larger sample size and δ41K analysis of other K-disrupting diseases (e.g., chronic kidney disease), our data hold great promise for K isotopes as disease marker.

Abstract This study investigates lexical development in second language (L2) learning from the perspective of complex dynamic system theory (CDST) using a complex network method. Based on authentic written output texts from L2 Chinese learners of different proficiency levels and language backgrounds, we successfully differentiate between different proficiency levels using a bi-gram lexical network model at a corpus level. A more in-depth investigation reveals that when compared to traditional lexical complexity indices, such as average word length and hapax legomena percentage (though Guiraud proves to be a robust predictor), the lexical network indices, such as network density and network clusters, provide a more profound understanding of L2 proficiency distinctions and a more precise approximation of the target language. Moreover, our findings illuminate the consistent manifestation of complex network characteristics within L2 Chinese lexical networks across all proficiency levels. Additionally, word association features, encompassing more than just word frequency information, provide comprehensive properties of the interlanguage system, as supported by their information gain values. We argue that studies within the CDST framework should integrate both lexical frequency and lexical network features to gain a comprehensive understanding of L2 lexical development.

Coarse β-columnar grains are often present in Ti–6Al–4V laser-additive-manufactured samples, resulting in anisotropic and inferior fatigue performance under dynamic loading. Fine-equiaxed grains (FEGs) with a mean grain size of approximately 139 μm were successfully obtained by a novel deposition strategy through coordinated regulation of direct energy deposition technological parameters. Microstructures were transformed from α′ martensite to α'' martensite. As a result, the comprehensive performance was significantly improved. Without the use of an argon atmosphere glovebox and post heat treatment, the tensile strength and elongation in the horizontal direction of the FEGs were 1091 MPa and 4.09%, respectively. The corrosion resistance was 11.71-fold higher than that of the coarse columnar grains (CCGs). Improving the microstructure and performance by optimizing pulsed laser parameters is simple, effective, and conducive to online regulation of the quality of laser additive samples.

Transmission lines serve as pivotal equipment within the power system. Conductors, the primary medium for power transmission and distribution, directly influence the construction cost, operational performance, and long-term benefits of transmission line projects. This study first provides a detailed introduction to the life cycle cost of transmission lines. It utilizes linear regression analysis, the grey model, and the autoregressive integrated moving average model to forecast the electricity sales benefit and quantify the carbon reduction benefits of energy-saving conductors through a methodology. Through the life cycle cost model, we found that operating costs, particularly energy loss costs, dominate the total expenses, accounting for 65% to 66.2%. The JLHA3-425 scheme offers the lowest life cycle cost of 22,891.66 k$. Comparing economic indicators like ENPV, EIRR, and DPP confirmed that the JLHA3-425 medium-strength aluminum alloy stranded wire emerged as the most economically viable option among the evaluated schemes, holding substantial promise for fostering economic and environmental sustainability in electrical power transmission.

Conventional deep learning methods for fault detection often assume that the training and the testing sets share the same fault domain spaces. However, some fault patterns are rare, and many real-world faults have not appeared in the training set. As a result, it is hard for the trained model to achieve desirable performance on the testing set. In this paper, we introduce a novel domain generalization, Load-Domain (LD) domain generalization, which is based on the analysis of the Case Western Reserve University (CWRU) bearing dataset and takes advantage of the physical information of this dataset. For this scenario, we propose a feature shift model called Feature Shift Network (FSN). FSN is trained for feature shift on adjacent source domains and finally shifts target domain features into adjacent source domain feature space to achieve the purpose of domain generalization. Furthermore, through the hybrid classification method, the generalization performance of the model on unseen target domains is effectively improved. The results on the CWRU bearing dataset demonstrate that FSN is better than the existing models in the LD domain generalization. Furthermore, we have another test on the rotated MNIST, which also shows FSN can achieve the best performance.

In order to fully achieve energy saving goals, it is necessary to establish a comprehensive evaluation system for carbon reduction in transmission and transformation projects. Subsequently, weights were assigned to these indicators using a combination of the fuzzy analytical hierarchy process (FAHP) and the entropy weight method (EWM) through both subjective and objective methods. Finally, the ultimate weights were obtained by applying the principle of minimum information. During the construction of the evaluation model, the rank–sum ratio (RSR) method was introduced into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for approximating ideal solution ranking. And the Euclidean distance in TOPSIS was replaced with standardized Euclidean distance, effectively avoiding evaluation discrepancies caused by different dimensions. The modified TOPSIS-RSR method was utilized to evaluate and rank power transmission and transformation projects in four regions. By comparing the test values of the two models, the superiority of the enhanced model was confirmed. Furthermore, the GM (1,1) model is used to predict the electricity sales volume of the optimal ranking area. This evaluation model can also be applied to the benefit evaluation of carbon reduction benefits in power transmission and transformation projects in other regions.

Abstract Bilayer graphene (BLG) is intriguing for its unique properties and potential applications in electronics, photonics, and mechanics. However, the chemical vapor deposition synthesis of large-area high-quality bilayer graphene on Cu is suffering from a low growth rate and limited bilayer coverage. Herein, we demonstrate the fast synthesis of meter-sized bilayer graphene film on commercial polycrystalline Cu foils by introducing trace CO2 during high-temperature growth. Continuous bilayer graphene with a high ratio of AB-stacking structure can be obtained within 20 min, which exhibits enhanced mechanical strength, uniform transmittance, and low sheet resistance in large area. Moreover, 96 and 100% AB-stacking structures were achieved in bilayer graphene grown on single-crystal Cu(111) foil and ultraflat single-crystal Cu(111)/sapphire substrates, respectively. The AB-stacking bilayer graphene exhibits tunable bandgap and performs well in photodetection. This work provides important insights into the growth mechanism and the mass production of large-area high-quality BLG on Cu.

Triazine herbicides are common contaminants in coastal waters, and they are recognized as inhibitors of photosystem II, causing significant hinderance to the growth and reproduction of phytoplankton. However, the influence of these herbicides on microalgal toxin production remains unclear. This study aimed to examine this relationship by conducting a comprehensive physiological and 4D label-free quantitative proteomic analysis on the harmful dinoflagellate Karenia mikimotoi in the presence of the triazine herbicide dipropetryn. The findings demonstrated a significant decrease in photosynthetic activity and pigment content, as well as reduced levels of unsaturated fatty acids, reactive oxygen species (ROS), and hemolytic toxins in K. mikimotoi when exposed to dipropetryn. The proteomic analysis revealed a down-regulation in proteins associated with photosynthesis, ROS response, and energy metabolism, such as fatty acid biosynthesis, chlorophyll metabolism, and nitrogen metabolism. In contrast, an up-regulation of proteins related to energy-producing processes, such as fatty acid β-oxidation, glycolysis, and the tricarboxylic acid cycle, was observed. This study demonstrated that dipropetryn disrupts the photosynthetic systems of K. mikimotoi, resulting in a notable decrease in algal toxin production. These findings provide valuable insights into the underlying mechanisms of toxin production in toxigenic microalgae and explore the potential effect of herbicide pollution on harmful algal blooms in coastal environments.

Abstract The product functions (PFs) extracted by local mean decomposition (LMD) of the noisy signal contain obvious energy‐concentrated pulses. As a result, the conventional amplitude threshold filtering used in wavelet transform (WT)‐based and empirical mode decomposition (EMD)‐based de‐noising methods is no longer applicable. To address this issue, an improved signal de‐noising method is proposed by using the multi‐level local mean decomposition (ML‐LMD), the superposition and recombination (SR) of high‐order PFs, the outlier detection, and waveform smoothing (OD‐WS) to remove noise by eliminating the pulse components. The proposed method's superior noise reduction performance is demonstrated through theoretical analysis and experimental verification. Compared to well‐known methods like WT‐based and EMD‐based de‐noising, the results show that the proposed method has significant comparative advantages in reducing noise in rolling bearing signals.

This study addresses the challenges faced by coal-fired power plants in adapting to energy fluctuations following the integration of renewable energy sources into the power grid. The flexible operation of thermal power plants has become a focal point in academic research. A numerical model of a coal-fired power plant was developed in this study using the Long Short-Term Memory (LSTM) algorithm and the Particle Swarm Optimization (PSO) algorithm based on actual operation data analysis. The combined PSO-LSTM approach improved the accuracy of the model by optimizing parameters. Validation of the model was performed using a Dymola physical simulation model, demonstrating that the PSO-LSTM coupled numerical model accurately simulates coal-fired power plant operations with a goodness of fit reaching 0.998. Overall system performance for comprehensively evaluating the rate and accuracy of unit operation is proposed. Furthermore, the model’s capability to simulate the load variation process of automatic generation control (AGC) under different load command groups was assessed, aiding in optimizing the best load command group. Optimization experiments show that the performance index of output power is optimal within the experimental range when the set load starts and stops are the same and the power of load command γ = 1.8. Specifically, the 50–75% Turbine Heat Acceptance (THA) load rise process enhanced the overall system performance index by 55.1%, while the 75–50% THA load fall process improved the overall system performance index by 54.2%. These findings highlight the effectiveness of the PSO-LSTM approach in optimizing thermal power plant operations and enhancing system performance under varying load conditions.

The influence of wettability on the permeability performance of water–oil two-phase flow has attracted increasing attention. Dispersed flow and stratified flow are two flow regimes for water–oil two-phase flow in capillary fractures. The theoretical models of relative permeability considering wettability were developed for these two water–oil flow regimes from the momentum equations of the two-fluid model. Wettability coefficients were proposed to study the impact of wettability on relative permeabilities. Experiments were conducted to study the relative permeabilities of laminar water–oil two-phase flow in water-saturated and oil-saturated horizontal capillary fractures with different hydraulic diameters. These fractures were made of polymethylmethacrylate (PMMA) and polytetrafluoroethylene (PTFE), which had different surface wettabilities. In this experiment, the regimes are dispersed flow and stratified flow. The results show that the effect of wettability on the relative permeabilities increases as the hydraulic diameters of capillary fractures decrease for water–oil two-phase flow. The relative permeabilities in a water-saturated capillary fracture are higher than those in an oil-saturated capillary fracture of the same material. The relative permeabilities in a PTFE capillary fracture are larger than those in a PMMA capillary fracture under the same saturated condition. Wettability has little effect on the permeability performances of water–oil two-phase flow in water-saturated capillary fractures, but is significant for those in oil-saturated capillary fractures.

The development of a new generation of solid particle solar receivers (SPSRs) with high solar absorptivity (0.28–2.5 μm) and high infrared emissivity (1–22 μm) is crucial and has attracted much attention for the attainment of the goals of “peak carbon” and “carbon neutrality”. To achieve the modulation of infrared emission and solar absorptivity, two types of medium- and high-entropy rare-earth hexaboride (ME/HEREB6) ceramics, (La0.25Sm0.25Ce0.25Eu0.25)B6 (MEREB6) and (La0.2Sm0.2Ce0.2Eu0.2Ba0.2)B6 (HEREB6), with severe lattice distortions were synthesized using a high-temperature solid-phase method. Compared to single-phase lanthanum hexaboride (LaB6), HEREB6 ceramics show an increase in solar absorptivity from 54.06% to 87.75% in the range of 0.28–2.5 μm and an increase in infrared emissivity from 76.19% to 89.96% in the 1–22 μm wavelength range. On the one hand, decreasing the free electron concentration and the plasma frequency reduces the reflection and ultimately increases the solar absorptivity. On the other hand, the lattice distortion induces changes in the B–B bond length, leading to significant changes in the Raman scattering spectrum, which affects the damping constant and ultimately increases the infrared emissivity. In conclusion, the multicomponent design can effectively improve the solar energy absorption and heat transfer capacity of ME/HEREB6, thus providing a new avenue for the development of solid particles.

Starch is a vital component of wheat grain and flour, characterized by two distinct granule types: A-type starch (AS) with granules larger than 10 µm in diameter, and B-type starch (BS) with granules measuring no more than 10 µm in diameter. This review comprehensively evaluates the isolation, purification, and biosynthesis processes of these types of granules. In addition, a comparative analysis of the structure and properties of AS and BS is presented, encompassing chemical composition, molecular, crystalline and morphological structures, gelatinization, pasting and digestive properties. The variation in size distribution of granules leads to differences in physicochemical properties of starch, influencing the formation of polymeric proteins, secondary and micro-structures of gluten, chemical and physical interactions between gluten and starch, and water absorption and water status in dough system. Thus, starch size distribution affects the quality of dough and final products. In this review, we summarize the up-to-date knowledge of AS and BS, and propose the possible strategies to enhance wheat yield and quality through coordinated breeding efforts. This review serves as a valuable reference for future advancements in wheat breeding.

Abstract International flights have accelerated the global spread of Coronavirus Disease 2019 (COVID-19). Determination of the optimal quarantine period for international travelers is crucial to prevent the local spread caused by imported COVID-19 cases. We performed a retrospective epidemiological study using 491 imported COVID-19 cases in Chengdu, China, to describe the characteristic of the cases and estimate the time from arrival to confirmation for international travelers using nonparametric survival methods. Among the 491 imported COVID-19 cases, 194 (39.5%) were asymptomatic infections. The mean age was 35.6 years (SD = 12.1 years) and 83.3% were men. The majority (74.1%) were screened positive for SARS-CoV-2, conducted by Chengdu Customs District, the People’s Republic of China. Asymptomatic cases were younger than presymptomatic or symptomatic cases (P

Abstract Objectives Heart failure (HF) has been implicated in osteoporosis. However, causality remains unestablished. Here, we sought to assess causal associations of genetic liability to HF with osteoporosis using Mendelian randomization (MR) analyses. Methods Independent single nucleotide polymorphisms associated with HF at genome-wide significance were derived from a large genome-wide association study (GWAS) (including up to 977,323 individuals). We obtained summary statistics for forearm (FA) bone mineral density (BMD) (n = 8,143), femoral neck (FN) BMD (n = 32,735), lumbar spine (LS) BMD (n = 28,498), heel (HE) BMD (n = 426,824), and fracture (n = 1,214,434) from other GWAS meta-analyses. Inverse variance weighted (IVW) and several supplementary methods were performed to calculate the MR estimates. Results Genetically determined HF has no causal effect on FA-BMD (odds ratio (OR) 1.17; 95% confidence interval (CI) 0.82, 1.66; P = 0.389), FN-BMD (OR 1.01; 95% CI 0.85, 1.19; P = 0.936), LS-BMD (OR 0.96; 95% CI 0.80, 1.17; P = 0.705), HE-BMD (OR 1.01; 95% CI 0.90, 1.13; P = 0.884), and fracture risk (OR 1.00; 95% CI 0.92, 1.10; P = 0.927). Complementary analyses returned broadly consistent results. Conclusion This MR study provides genetic evidence that HF may not lead to an increased risk of reduced BMDs or fracture.

Abstract Background Epidemiological evidence relating obesity to peptic ulcer disease (PUD) has been mixed. Here we sought to determine the causality in the association of obesity with PUD risk using the Mendelian randomization (MR) approach. Methods This study was based on summary-level data for body mass index (BMI), waist-to-hip ratio (WHR), and PUD derived from large genome-wide association studies (GWASs). Single nucleotide polymorphisms significantly associated with BMI and WHR (P

Exosomes are produced by the majority of eukaryotic cells and are capable of transporting a variety of substances, including non-coding RNAs, between cells. Metastasis is a significant cause of death from cancer. Numerous studies have established an important role for exosomal non-coding RNAs in tumor metastasis. Exosomal non-coding RNAs from a variety of cells have been shown to affect tumor metastasis via several mechanisms. Exosomes transmit non-coding RNAs between tumor cells, fibroblasts, endothelial cells, and immune cells within the tumor microenvironment. Exosomal non-coding RNAs also have an effect on epithelial-mesenchymal transition, angiogenesis, and lymphangiogenesis. Exosomes derived from tumor cells have the ability to transport non-coding RNAs to distant organs, thereby facilitating the formation of the metastatic niche. Due to their role in tumor metastasis, exosomal non-coding RNAs have the potential to serve as diagnostic or prognostic markers as well as therapeutic targets for tumors. The purpose of this paper is to review and discuss the mechanisms of exosomal non-coding RNAs, their role in tumor metastasis, and their clinical utility, aiming to establish new directions for tumor metastasis, diagnosis, and treatment research.

In this work, we quantitatively explore how a finite gauge boson mass affects dynamical mass generation and the chiral phase transition in thermal QED3. To this end, we numerically solve the Dyson–Schwinger equations by considering the contributions coming from the wave function renormalization and the spatial part of the boson propagator at first and then compute the chiral condensate and some of thermodynamic quantities. It is found that the wave function renormalization and the spatial part of the boson propagator are crucial for the numerical solutions of the dressing functions and the value of critical temperature. The behaviors of the thermodynamic quantities and the chiral condensate as a function of temperature consistently imply that the chiral phase transition is none other than a second order one. That critical temperature decreases with increasing gauge boson mass verifies that the gauge boson mass will weaken the interactions between fermions and so suppress dynamical mass generation.

The low-low-temperature electrostatic precipitator (LLT-ESP) is considered one of the mainstream technological approaches for achieving ultra-low ash emissions and has already been applied in many coal-fired power plants. Particulate matter and SO3 can both be removed by LLT-ESP. However, the removal performance of SO3 is relatively lower than that of particulate matter, which is caused by the condensation characteristics of SO3. In this paper, the condensation characteristics of SO3 were investigated on a simulated experimental system, and several measurement and characteristic methods were used to investigate mechanisms. After reducing the flue gas temperature with a heat exchanger, the size distribution of particulate matter, the mass concentration of SO3 on different sizes of particulate matter, as well as the microscopic morphology and elemental composition of particulate matter, were all experimentally studied. The results indicate that gaseous SO3 transformed into a liquid phase by heterogeneous or homogeneous condensation and then adhered to the surface of particulate matter through nucleation–condensation, collision–coalescence, and adsorption reactions. Furthermore, the removal efficiency of SO3 in LLT-ESP was also investigated under various conditions, such as ash concentration and flue gas temperature drop, suggesting that a higher ash concentration and a more significant temperature drop were beneficial for improving SO3 removal efficiency. Nevertheless, it is worth noting that the impact was limited by a further increase in ash concentration and a drop in flue gas temperature.

Transformers, as the hub equipment of the power system, are highly valued by engineering and scientific researchers in production practice and scientific research. The goal of transformer research is to ensure the safe operation of transformers while considering their economic benefits, arrange transformer inspections reasonably to reduce inspection costs, and save labor and maintenance costs reasonably. This study first provides a brief analysis of the life cycle cost of transformers. The life cycle of transformers is divided into initial cost, operating cost, maintenance cost, fault cost, and scrap cost. Based on the distribution of transformer failure rate, the corresponding life cycle cost of transformers is calculated. Taking 110 kV transformers as an example, the differences in the impact of key factors on the full life cycle cost are analyzed to achieve high quality, high reliability, economically optimal equipment procurement.

To investigate the economic impact of carbon reduction technology on power transmission and transformation projects, carbon reduction technologies adapted to power transmission and transformation projects were investigated, and the evaluation indicator system for cost-benefit in power transmission and transformation projects was established based on AHP (Analytic Hierarchy Process) and EWM (Entropy Weight Method). Taking 110 kV and 220 kV transmission and transformation projects in a province located in northwest China as an example, a sensitivity analysis was carried out for the weight of each carbon reduction technology. Additionally, based on the evaluation indicator system, eight alternative carbon reduction schemes were proposed, and the net present value and scheme scores were analyzed with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). The results showed that in the criterion layer of the 110 kV case, the highest proportion of weight is “high-efficiency transformer”, accounting for 34.12%, and in the indicator layer, the highest proportion of weight is “ parasitic losses”, accounting for 12.35%. After conducting error analysis on the 110 kV and 220 kV cases, it was found that the errors were within an acceptable range both in the criterion layer and index layer. Moreover, it is expected to achieve greater economic benefits through lower costs according to Scheme VI, and due to the limitations of carbon reduction technologies and the lack of a relevant policy system, it is difficult to achieve the goal of covering costs with benefits for the eight schemes studied.

The transformer is a fundamental piece of equipment for power grids. The analysis and optimization of their life-cycle costs are of great importance to reinforce the economic efficiency of electrical networks. This paper constructs a comprehensive transformer life-cycle cost (LCC) model by fusing life-cycle cost theory with relevant transformer expenditure. It proceeds to examine the life-cycle cost aspects of the transformer, delving into its cost dynamics under various influencing factors, establishing interconnections between these factors and analyzing the cost relationship. By employing MATLAB software (Matlab 2021a) along with the whale optimization algorithm (WOA) this paper optimizes the objective function. Through this, it establishes the LCC model for 20 power transformers, obtaining the optimal objective function curve and the maximum value for LCC optimization of the transformer. Unlike previous research, this study adds a detailed analysis of several factors that influence LCC. At the same time, it develops a more complete, scientific and rational LCC optimization model. An illustrative example validates the model and the superiority of the whale optimization algorithm. The algorithm not only shows its scientific basis and superiority, but also serves as a guiding mechanism for LCC management in transformer engineering practices. Ultimately, it emerges as a fundamental tool to improve the efficiency of power grid asset management.

ObjectiveTo conduct a gene tracing-based analysis on a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive oropharyngeal swab specimen from a suspected coronavirus disease 2019 (COVID-19) case without epidemiologically-confirmed exposure history and with negative results in confirmation tests in Chengdu city, Sichuan province for providing evidence to the operation of clinics engaged in COVID-19 vaccination.MethodsAn epidemiological investigation was conducted on a suspected COVID-19 case reported by a medical institution providing both COVID-19 vaccination and SARS-CoV-2 nucleic acid screening services in a district of Chengdu city, Sichuan province on February 24, 2021. The information on case′s onset and treatment, travel and close contacts within 14 days before the onset were collected and analyzed. Specimen collection and laboratory nucleic acid testing were conducted for the case, the case′s close contacts and living environment, and the environment and work clothes of medical staff of the reporting medical institution. Second generation gene sequencing and gene tracing analysis were performed for the case′s positive specimen collected for the screening test. ResultsThe suspected case was a 57-year old man seeking medication for cough, throat discomfort, and runny nose at a medical institution provided both COVID-19 vaccination and SARS-CoV-2 nucleic acid screening services and having a oropharyngeal swab test for screening SARS-CoV-2 infection at the medical institution on February 23, 2021. The case reported no history of travelling abroad himself and his close contacts, contacting with confirmed/suspected COVID-19 patients, potential exposure to SARS-CoV-2, and COVID-19 vaccination. No positive results of SARS-CoV-2 nucleic acid were detected for case′s oropharyngeal/nasal and anal swab specimens, close contacts′ oropharyngeal swab specimens, swab specimens of living/working/relevant public place environment, swab specimens of environment and working clothes of the staff of the medical institution for retests performed one day after the case′s screening test. The results of gene sequencing for the case′s positive specimen at the screening test showed a 99.99% sequence homology with the sample of COVID-19 vaccine for inoculation service at the medical institution. The Pangolin type was B for both the case′s specimen and the vaccine sample. ConclusionThe clinical manifestation and laboratory test of the suspected case were not consistent with the diagnosis criterion for COVID-19 patient and asymptomatic SARS-CoV-2 infection. The case′s false SARS-CoV-2 positivity of the suspected specimen at the screening test probably results from vaccination related contamination of the case′s oropharyngeal swab specimen at the medical institution proving both COVID-19 vaccination and SARS-CoV-2 nucleic acid screening services. The result needs to be concerned when conducting SARS-CoV-2 nucleic acid screening.

Measurement(s) Inhibition effect of anti-coronavirus peptide Technology Type(s) Antiviral assay

Abstract The Xihuashan and Yaogangxian granitic plutons in South China comprise highly evolved multiphase Li‐rich granites and host quartz‐vein‐type tungsten deposits. The δ7Li values of Phase A (early stage), B (middle stage), and C (late stage) from the Xihuashan pluton are 1.0–1.2‰, 1.1–3.0‰, and 2.4–2.8‰ respectively, increasing through chemical evolution. The granites from the Yaogangxian pluton also display gradually enriched in heavy Li isotopes in a later stage, although systematically lighter than those of the Xihuashan pluton. In both plutons, the δ7Li shows good correlations with SiO2 and Li concentrations as well as Rb/Sr, Nb/Ta, and Zr/Hf ratios, indicating Li isotopic fractionation most likely caused by magmatic differentiation. In situ analyses show that the minerals of Xihuashan pluton record a continuous elemental spectrum, reflecting the results of progressive magmatic differentiation. The δ7Li values of quartz, feldspar, mica, and zircon all correlate well with the chemical evolutions of granitic magma, systematically elevated in Phases B and C relative to Phase A. The Li isotope data of the mineral separates further document that the enrichment of 7Li in the residual melt was most likely due to the equilibrium fractionation between the mineral and melts. The data are interpreted to reflect that intense magmatic differentiation was responsible for Li isotopic variations coupled with the enrichment in the Li, F, P, and rare metals in the late‐phase granites of the Xihuashan pluton. The lithium isotope behavior documented in this study provides new insights into magmatic differentiation and associated rare‐metal mineralization.

ObjectiveTo examine the distribution and effects of the subclass of insulin antibodies on glucose control and side events in patients with type 2 diabetes treated with premixed insulin analog.MethodsA total of 516 patients treated with premixed insulin analog were sequentially enrolled from the First Affiliated Hospital of Nanjing Medical University from June 2016 to August 2020. Subclass-specific insulin antibodies (IAs) (IgG1-4, IgA, IgD, IgE, and IgM) were detected in IA-positive patients by electrochemiluminescence. We analyzed glucose control, serum insulin, and insulin-related events between IA-positive and IA-negative groups, as well as among patients with different IA subclasses.ResultsOverall, 98 of 516 subjects (19.0%) were positive for total IAs after premixed insulin analog therapy; of these participants, 92 had subclass IAs, and IgG-IA was the predominant subclass, followed by IgE-IA. IAs were associated with serum total insulin increase and local injection-site reactions but not glycemic control and hypoglycemia. In the subgroup analysis in patients with IA-positive, the IgE-IA and IA subclass numbers were more associated with increased serum total insulin levels. Additionally, IgE-IA might be correlated more strongly with local responses and weakly with hypoglycemia, while IgM-IA might be correlated more strongly with hypoglycemia.ConclusionWe concluded that IAs or IA subclasses might be associated with unfavorable events in patients receiving premixed insulin analog therapy, which can be used as an adjunctive monitoring indicator in clinical insulin trials.

IntroductionSoy isoflavone, a class of polyphenolic compounds exclusively occurred in legumes, is an important bioactive compound for both plants and human beings. The outline of isoflavones biosynthesis pathway has been drawn up basically in the previous research. However, research on the subject has been mostly restricted to investigate the static regulation of isoflavone content in soybean, rather than characterize its dynamic variation and modulation network in developing seeds.MethodsIn this study, by using eight recombinant inbred lines (RIL), the contents of six isoflavone components in the different stages of developing soybean seeds were determined to characterize the dynamic variation of isoflavones, and the isoflavones accumulation pattern at physiological level was investigated. Meanwhile, we integrated and analyzed the whole genome expression profile of four lines and 42 meta-transcriptome data, based on the multiple algorithms.ResultsThis study: 1) obtained 4 molecular modules strongly correlated with isoflavone accumulation; 2) identified 28 novel major genes that could affect the accumulation of isoflavones in developing seeds free from the limitation of environments; 3) discussed the dynamic molecular patterns regulating isoflavones accumulation in developing seed; 4) expanded the isoflavone biosynthesis pathway.DiscussionThe results not only promote the understandings on the biosynthesis and regulation of isoflavones at physiological and molecular level, but also facilitate to breed elite soybean cultivars with high isoflavone contents.

Abstract The zinc complex of 3,5-di-tert-butyl salicylate (Zn{[CH3)3C]2Sal}2 2−) is a zinc ion chelate of salicylate. In this study, we found that this compound inhibits viability, invasion, and migration and induces apoptosis in triple-negative breast cancer 4T1 cells. RNA-seq showed that the expression of 17 genes was upregulated and 26 genes were downregulated significantly by Zn{[CH3)3C]2Sal}2 2− treatment. Further GO and KEGG analysis showed that the activity of Zn{[CH3)3C]2Sal}2 2− against triple-negative breast cancer cells may be involved in the JAK-STAT3, HIF-1, and TNF signaling pathways. The expression of key genes was verified by RT–PCR. The phosphorylation of STAT3 and its upstream SRC decreased drastically upon Zn{[CH3)3C]2Sal}2 2− treatment, as demonstrated by western blot. Our results indicate that Zn{[CH3)3C]2Sal}2 2− inhibits the activity of TNBC cells by downregulating the STAT3 signaling through the SRC pathway.

Grid-tied distributed generators (DGs) need to be equipped with anti-islanding protection to avoid the impact of unplanned islanding, which would affect system stability, auto-reclosing, and personal safety. Among the active anti-islanding protections, impedance measurements based on signal injection have the advantages of a low non-detection zone (NDZ) and are less prone to maloperation during grid disturbances; however, there are problems with signal interference in multi-DG systems. Hence, the impedance angle measurement method with signals injected synchronously is proposed. In this method, each DG injects phase-coherent signals to detect islanding using zero-cross points of the voltage (ZCPV) to avoid the protection failures caused by signal interference. An islanding identification criterion based on the measured impedance angle is proposed by analyzing the impedance characteristics of grid connection and islanding, which avoids the influence of variation of the DG operation state on islanding detection. Finally, we present a signal injection strategy and performance analysis in combination with an existing DG control platform, avoiding additional hardware investment. RTDS-based simulation verification shows that the proposed method can 100% avoid DG maloperation due to voltage and frequency disturbances during grid-connected operation and exit operation within 2 s when islanding occurs.

To better consume high-density photovoltaics, in this article, the application of energy storage devices in the distribution network not only realizes the peak shaving and valley filling of the electricity load but also relieves the pressure on the grid voltage generated by the distributed photovoltaic access. At the same time, photovoltaic power generation and energy storage cooperate and have an impact on the tidal distribution of the distribution network. Since photovoltaic output has uncertainty, the maximum photovoltaic output in each scenario is determined by the clustering algorithm, while the storage scheduling strategy is reasonably selected so the distribution network operates efficiently and stably. The tidal optimization of the distribution network is carried out with the objectives of minimizing network losses and voltage deviations, two objectives that are assigned comprehensive weights, and the optimization model is constructed by using a particle swarm algorithm to derive the optimal dispatching strategy of the distribution network with the cooperation of photovoltaic and energy storage. Finally, a model with 30 buses is simulated and the system is optimally dispatched under multiple scenarios to demonstrate the necessity of conducting coordinated optimal dispatch of photovoltaics and energy storage.

In this paper, a two-stage equalization topology based on Zero-Voltage Switching Quasi-Resonant Converter (ZVS QRC) is proposed to solve the problems of long equalization time and low energy utilization of series lithium-ion battery packs. The equalization topology is divided into two forms: intra-group and inter-group, ZVS QRCs are adopted in both intra-group and inter-group, which can equalize any single cell within a group, and the equalization circuit within each pack can equalize simultaneously, which greatly reduces the equalization time, and reduces the switching loss during the equalization process by introducing quasi-resonant circuit to improve the energy utilization. Taking the State of Charge (SOC) as the equalization target, a group equalization strategy based on the Credibility Factor (C-F) inference model is proposed. The strategy defines the SOC unbalance degree of a single battery, gets the group unbalance degree according to the C-F inference model, and gets the group equalization state from the unbalance degree, to control the group for equalization. Matlab/Simulink software is used to build the model and simulate it. The experimental results demonstrate that the proposed topology saves approximately 25% of the equalization time compared to the traditional Buck-Boost group equalization topology. Under the same static and charge/discharge conditions, the equalization time is reduced by about 21% and the energy utilization is improved by about 6% after using the C-F inference model for equalization compared to the fixed-threshold method.

The effect of seed power on the inter-modal four-wave mixing (IM-FWM) effect in a distributed side-pumped fiber amplifier is investigated for the first time, to the best of our knowledge. By using a seed source smaller than 70 W, the effect of seed power on the IM-FWM is studied experimentally. Surprisingly, it is found that the IM-FWM effect becomes stronger with the weaker seed. To analyze the physics behind this result, a numerical model is introduced, and the numerical results are in good agreement with the experimental observations. It is revealed that the IM-FWM enhancement is induced by the gain competition between the signal light and the anti-Stokes light of the IM-FWM. It is also found that there is an optimized seed power for suppressing the IM-FWM effect. The experimental and numerical results which are presented in this work can provide significant guidance for understanding the IM-FWM in fiber lasers and amplifiers.