Identification of key genes regulating the synthesis of quercetin derivatives in Rosa roxburghii through integrated transcriptomics and metabolomics

Rosa roxburghii fruit is rich in flavonoids, but little is known about their biosynthetic pathways. In this study, we employed transcriptomics and metabolomics to study changes related to the flavonoids at five different stages of R. roxburghii fruit development. Flavonoids and the genes related to their biosynthesis were found to undergo significant changes in abundance across different developmental stages, and numerous quercetin derivatives were identified. We found three gene expression modules that were significantly associated with the abundances of the different flavonoids in R. roxburghii and identified three structural UDP-glycosyltransferase genes directly involved in the synthesis of quercetin derivatives within these modules. In addition, we found that RrBEH4, RrLBD1 and RrPIF8could significantly increase the expression of downstream quercetin derivative biosynthesis genes. Taken together,these results provide new insights into the metabolism of flavonoids and the accumulation of quercetin derivatives in R. roxburghii.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Experimental study on the effect of unloading rate on gneiss rockburst

Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of unloading rates.A high-speed photography system and acoustic emission(AE)system were used to monitor the entire process of rockburst process in real-time.The results show that the intensity of gneiss rockburst decreases with decrease of unloading rate,which is manifested as the reduction of AE energy and fragments ejection velocity.The mechanisms are proposed to explain this effect:(i)The reduction of unloading rate changes the crack propagation mechanism in the process of rockburst.This makes the rockbursts change from the tensile failure mechanism at high unloading rate to the tension-shear mixed failure mechanism at low unloading rate,and more energy released in the form of shear crack propagation.Then,less strain energy is converted into kinetic energy of fragments ejection.(ii)Less plate cracking degree of gneiss has taken shape due to decrease of unloading rate,resulting in the destruction of rockburst incubation process.The enlightenments of reducing the unloading rate for the project are also described quantitatively.The rockburst magnitude is reduced from the medium magnitude at the unloading rate of 0.1 MPa/s to the slight magnitude at the unloading rate of 0.025 MPa/s,which was judged by the ejection velocity.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic,intricately governed by natural selection and historically garnering considerable attention.Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain,ushering in an unprecedented era of mutation rate research.This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates.It examines various types of mutations,explores the evolutionary dynamics and associated theories,and synthesizes both classical and contemporary hypotheses.Furthermore,this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies,mutational patterns,molecular mechanisms,and driving forces influencing variations in mutation rates across species and tissues.Finally,it proposes several potential research directions and pressing questions for future investigations.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.

Interest Rate and Some of Its Applications

Interest rates are a fundamental aspect of the economy and have a significant impact on various financial decisions such as borrowing, investing, and saving. They are the cost of borrowing money or the return on investment and are determined by various factors such as the supply and demand for credit, inflation expectations, and monetary policy decisions made by central banks. Changes in interest rates can have a major effect on the economy and can influence consumer spending, business investment, and overall economic growth. This makes it crucial for individuals, businesses, and policymakers to have a clear understanding of the dynamics of interest rates. Interest rates play an important role in determining the cost of borrowing money for individuals and businesses. A rise in interest rates can increase the cost of borrowing and make it more difficult for people and companies to access credit. This can lead to a decrease in consumer spending and business investment, which can slow down economic growth. On the other hand, a decrease in interest rates can make it easier for individuals and businesses to access credit and increase consumer spending and business investment, boosting economic growth. Central banks, such as the Federal Reserve in the United States, play a key role in determining interest rates by setting monetary policy. They use interest rate changes to influence the economy and reach their goals of stable prices, maximum employment, and moderate long-term interest rates. In conclusion, understanding the dynamics of interest rates is essential for making informed financial decisions and assessing the overall health of the economy. The impact of interest rates on the economy and individual financial decisions is far-reaching and long-lasting, making it a crucial topic for continued study and discussion.

A Comparative Study on Achievements in Negative Nominal Interest Rates Published in Literature in English and Chinese

Interest rates are the key to the resource allocations of financial markets.The frequent appearance of negative nominal interest rates(NNIR)may lead to a failure of the transmission mechanism and arouse system risks in the financial markets.Meanwhile,negative nominal interest rates is a new policy with no consensus reached by academia or policymakers.It is necessary to review the research results and promote consensus to reveal the nature and impact mechanisms of NNIR.Therefore,we retrieved original articles from the Web of Science(WoS)and China National Knowledge Infrastructure(CNKI)published from 1999 to 2020 on NNIR to determine the characteristics of current research results from various perspectives and compare literature in English and Chinese of highly productive institutions and researchers,hot topics,evolution contexts,research frontiers,and ecological characteristics.There are three major findings.In terms of research ecology,the ecological structure of the top research institutions,both domestic and abroad,remains steady,but the structure of the researchers is not stable.In terms of a research domain,NNIR is studied from many dimensions,and the early established research domains still have long-lasting impacts in English literature.In contrast,Chinese literature mainly focuses on discussing applicable policies with no highly focused domain and research topic with great influence yet.Finally,the focus in both English and Chinese literature has changed.Since the original research framework is insufficient in explanatory power,literature in English is beginning to pay attention to the empirical analyses of practical policies,and Chinese scholars are turning to theoretical study to enhance the in-depth understanding of this phenomenon.Researchers in China should focus on collecting high-quality research materials and pay more attention to the progress of empirical research in English literature to improve Chinese research efficiency and quality and then promote research progress in China.

Organic solar cells with D18 or derivatives offer efficiency over 19%

In recent years,organic solar cells(OSCs)have garnered significant attention due to their distinctive attributes,such as flexibility,lightweight,and solution processing,which position them as alternatives for next-generation solar technologies[1−5].Thanks to breakthroughs in materials development,the power conversion efficiency(PCE)for single-junction OSCs has already surpassed 19%[6−13].The development of photoactive materials is pivotal in enhancing the PCEs,and several reviews have provided insights into materials design[14−18].Herein,we highlight single-junction OSCs based on D18 and its derivatives[19,20].

Fluorinated semi-interpenetrating polymer networks for enhancing the mechanical performance and storage stability of polymer-bonded explosives by controlling curing and phase separation rates

Herein, the effect of fluoropolymer binders on the properties of polymer-bonded explosives(PBXs) was comprehensively investigated. To this end, fluorinated semi-interpenetrating polymer networks(semiIPNs) were prepared using different catalyst amounts(denoted as F23-CLF-30-D). The involved curing and phase separation processes were monitored using Fourier-transform infrared spectroscopy, differential scanning calorimetry, a haze meter and a rheometer. Curing rate constant and activation energy were calculated using a theoretical model and numerical method, respectively. Results revealed that owing to its co-continuous micro-phase separation structure, the F23-CLF-30-D3 semi-IPN exhibited considerably higher tensile strength and elongation at break than pure fluororubber F2314 and the F23-CLF-30-D0 semi-IPN because the phase separation and curing rates matched in the initial stage of curing.An arc Brazilian test revealed that F23-CLF-30-D-based composites used as mock materials for PBXs exhibited excellent mechanical performance and storage stability. Thus, the matched curing and phase separation rates play a crucial role during the fabrication of high-performance semi-IPNs;these factors can be feasibly controlled using an appropriate catalyst amount.

Fullerenes and derivatives as electrocatalysts: Promises and challenges

Carbon-based metal-free nanomaterials are promising alternatives to precious metals as electrocatalysts of key energy storage and conversion technologies.Of paramount significance are the establishment of design principles by understanding the catalytic mechanisms and identifying the active sites.Distinct from sp2-conjugated graphene and carbon nanotube,fullerene possesses unique characteristics that are growingly being discovered and exploited by the electrocatalysis community.For instance,the well-defined atomic and molecular structures,the good electron affinity to tune the electronic structures of other substances,the intermolecular self-assembly into superlattices,and the on-demand chemical modification have endowed fullerene with incomparable advantages as electrocatalysts that are otherwise not applicable to other carbon ma-terials.As increasing studies are being reported on this intriguing topic,it is necessary to provide a state-of-the-art overview of the recent progress.This review takes such an initiative by summarizing the promises and challenges in the electrocatalytic applications of fullerene and its derivatives.The content is structured according to the composition and structure of fullerene,including intact fullerene(e.g.,fullerene composite and superlattices)and fullerene derivatives(e.g.,doped,endohedral,and disintegrated fullerene).The synthesis,characterization,catalytic mechanisms,and deficiencies of these fullerene-based materials are explicitly elaborated.We conclude it by sharing our perspectives on the key aspects that future efforts shall consider.

INTERFACE BEHAVIOR AND DECAY RATES OF COMPRESSIBLE NAVIER-STOKES SYSTEM WITH DENSITY-DEPENDENT VISCOSITY AND A VACUUM

In this paper,we study the one-dimensional motion of viscous gas near a vacuum,with the gas connecting to a vacuum state with a jump in density.The interface behavior,the pointwise decay rates of the density function and the expanding rates of the interface are obtained with the viscosity coefficientμ(ρ)=ρ^(α)for any 0<α<1;this includes the timeweighted boundedness from below and above.The smoothness of the solution is discussed.Moreover,we construct a class of self-similar classical solutions which exhibit some interesting properties,such as optimal estimates.The present paper extends the results in[Luo T,Xin Z P,Yang T.SIAM J Math Anal,2000,31(6):1175-1191]to the jump boundary conditions case with density-dependent viscosity.

Discovery and structure-activity relationship studies of novel tetrahydro-β-carboline derivatives as apoptosis initiators for treating bacterial infections

Developing and excavating new agrochemicals with highly active and safe is an important tactic for protecting crop health and food safety.In this paper,to discover the new bactericide candidates,we designed,prepared a new type of1,2,3,4-tetrahydro-β-carboline(THC)derivatives and evaluated the in vitro and in vivo bioactivities against the Xanthomonas oryzae pv.oryzae(Xoo),Xanthomonas axonopodis pv.citri(Xac),and Pseudomonas syringae pv.actinidiae(Psa).The in vitro bioassay results exhibited that most title molecules possessed good activity toward the three plant pathogenic bacteria,the compound A17 showed the most active against Xoo and Xac with EC50 values of 7.27 and 4.89 mg mL^(-1)respectively,and compound A8 exhibited the best inhibitory activity against Psa with EC50value of 4.87 mg mL^(-1).Pot experiments showed that compound A17 exhibited excellent in vivo antibacterial activities to manage rice bacterial leaf blight and citrus bacterial canker,with protective efficiencies of 52.67 and 79.79%at 200 mgmL^(-1),respectively.Meanwhile,compound A8 showed good control efficiency(84.31%)against kiwifruit bacterial canker at 200 mg mL^(-1).Antibacterial mechanism suggested that these compounds could interfere with the balance of the redox system,damage the cell membrane,and induce the apoptosis of Xoo cells.Taken together,our study revealed that tetrahydro-β-carboline derivatives could be a promising candidate model for novel broadspectrum bactericides.

Genetic and Agronomic Parameter Estimates of Growth, Yield and Related Traits of Maize (Zea mays L.) under Different Rates of Nitrogen Fertilization

This study evaluated the genetic and agronomic parameter estimates of maize under different nitrogen rates. The trial was established at the Njala Agricultural Research Centre experimental site during 2021 and 2022 in a split block design with three maize varieties (IWCD2, 2009EVDT, and DMR-ESR-Yellow) and seven nitrogen (0, 30, 60, 90, 120, 150 and 180 kg∙N∙ha−1) rates. Findings showed that cob diameter and anthesis silking time (ASI) had intermediate heritability, ASI had high genetic advance, ASI and grain yield had high genotypic coefficient of variation (GCV), while traits with high phenotypic coefficient of variation (PCV) were plant height, ASI, grain yield, number of kernel per cob, number of kernel rows, ear length, and ear height. The PCV values were higher than GCV, indicating the influence of the environment in the studied traits. Nitrogen rates and variety significantly (p < 0.05) influenced grain yield production. Mean grain yields and economic parameter estimates increased with increasing nitrogen rates, with the 30 and 180 kg∙N∙ha−1 plots exhibiting the lowest and highest grain yields of 1238 kg∙ha−1 and 2098 kg∙ha−1, respectively. Variety and nitrogen effects on partial factor productivity (PFPN), agronomic efficiency (AEN), net returns (NR), value cost ratio (VCR) and marginal return (MR) indicated that these parameters were significantly affected (p < 0.05) by these factors. The highest PFPN (41.3 kg grain kg−1∙N) and AEN (29.4 kg grain kg−1∙N) were obtained in the 30 kg∙N∙ha−1 plots, while the highest VCR (2.8) and MR (SLL 1.8 SLL−1 spent on N) were obtained in the 180 kg∙N∙ha−1. The significant influence of variety and nitrogen on traits suggests that increasing yields and maximizing profits require use of appropriate nitrogen fertilization and improved farming practices that could be exploited for increased productivity of maize.

MOFs‑Derived Strategy and Ternary Alloys Regulation in Flower‑Like Magnetic‑Carbon Microspheres with Broadband Electromagnetic Wave Absorption

Broadband electromagnetic(EM)wave absorption materials play an important role in military stealth and health protection.Herein,metal–organic frameworks(MOFs)-derived magnetic-carbon CoNiM@C(M=Cu,Zn,Fe,Mn)microspheres are fabricated,which exhibit flower-like nano–microstructure with tunable EM response capacity.Based on the MOFs-derived CoNi@C microsphere,the adjacent third element is introduced into magnetic CoNi alloy to enhance EM wave absorption performance.In term of broadband absorption,the order of efficient absorption bandwidth(EAB)value is Mn>Fe=Zn>Cu in the CoNiM@C microspheres.Therefore,MOFs-derived flower-like CoNiMn@C microspheres hold outstanding broadband absorption and the EAB can reach up to 5.8 GHz(covering 12.2–18 GHz at 2.0 mm thickness).Besides,off-axis electron holography and computational simulations are applied to elucidate the inherent dielectric dissipation and magnetic loss.Rich heterointerfaces in CoNiMn@C promote the aggregation of the negative/positive charges at the contacting region,forming interfacial polarization.The graphitized carbon layer catalyzed by the magnetic CoNiMn core offered the electron mobility path,boosting the conductive loss.Equally importantly,magnetic coupling is observed in the CoNiMn@C to strengthen the magnetic responding behaviors.This study provides a new guide to build broadband EM absorption by regulating the ternary magnetic alloy.

Present-day Upper-crustal Strain Rate Field in Southeastern Tibet and its Geodynamic Implications:Constraints from GPS Measurements with ABIC Method

The Earth’s surface kinematics and deformation are fundamental to understanding crustal evolution.An effective research approach is to estimate regional motion field and deformation fields based on modern geodetic networks.If the discrete observed velocity field is obtained,the velocity related fields,such as dilatation rate and maximum shear strain rate,can be estimated by applying varied mathematical approaches.This study applied Akaike's Bayesian Information Criterion(ABIC)method to calculate strain rate fields constrained by GPS observations in the southeast Tibetan Plateau.Comparison with results derived from other three methods revealed that our ABIC-derived strain rate fields were more precise.The maximum shear strain rate highlighted the Xianshuihe–Xiaojiang fault system as the main boundary for the outward migration of material in southeastern Tibet,indicating rotation of eastern Tibet material around the eastern Himalaya rather than whole extrusion along a fixed channel.Additionally,distinct dilatation rate patterns in the northeast and southwest regions of the fault system were observed.The northeast region,represented by the Longmenshan area,exhibited negative dilatational anomalies;while the southwest region,represented by the Jinsha River area north of 29°N,displayed positive dilatational anomalies.This indicates compression in the former and extension in the latter.Combined with deep geophysical observations,we believe that the upper and lower crusts of the Jinsha River area north of 29°N are in an entire expanding state,probably caused by the escape-drag effect of material.The presence of a large,low-viscosity region south of 29°N may not enable the entire escape of the crust,but instead result in a differential escape of the lower crust faster than the upper crust.

High-Value-Added Utilization of Turpentine:Screening of Anti-Influenza Virus Agents fromβ-Pinene Derivatives

Turpentine is a renewable and resourceful forest product.The deep processing and utilization of turpentine,particularly its primary componentβ-pinene,has garnered widespread attention.This study aimed to synthesize 40 derivatives ofβ-pinene,including nopinone,3-cyanopyridines of nopinone,myrtanyl acid,myrtanyl acylthioureas,and myrtanyl amides.We assessed the antiviral activities of theseβ-pinene derivatives against influenza virus A/Puerto Rico/8/34(H1N1)using the 3-(4,5-dimetylthiazol-2-yl)-2,5-diphenyltetrazolium bromide method.Theβ-pinene derivatives were used before and after cellular infection with the influenza virus to evaluate their preventive and therapeutic effects against the H1N1 virus.The results showed that only compound 10o exhibited a preventive effect against the H1N1 virus with a half-maximal inhibitory concentration(IC50)value of 47.6μmol/L.Among the compounds,4e,4i,and 4l demonstrated therapeutic effects against cellular infection,with compound 4e displaying the most potent therapeutic effect(IC50=17.5μmol/L),comparable to the positive control ribavirin.These findings indicated that certainβ-pinene derivatives exhibited in vitro antiviral activity against the H1N1 influenza A virus,warranting further investigation as potential anti-influenza agents.

Intelligent reflecting surface for sum rate enhancement in MIMO systems

The research for the Intelligent Reflecting Surface(IRS)which has the advantages of cost and energy efficiency has been studied.Channel capacity can be effectively increased by appropriately setting the phase value of IRS elements according to the channel conditions.However,the problem of obtaining an appropriate phase value of IRs is difficult to solve due to the non-convex problem.This paper proposes an iterative algorithm for the alternating optimal solution in the Single User Multiple-Input-Multiple-Output(SU-MIMO)systems.The proposed iterative algorithm finds an alternating optimal solution that is the phase value of IRS one by one.The results show that the proposed method has better performance than that of the randomized IRS systems.The number of iterations for maximizing the performance of the proposed algorithm depends on the channel state between the IRS and the receiver.