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.

Dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates

Interactive holography offers unmatched levels of immersion and user engagement in the field of future display.Despite of the substantial progress has been made in dynamic meta-holography,the realization of real-time,highly smooth interactive holography remains a significant challenge due to the computational and display frame rate limitations.In this study,we introduced a dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates.To our knowledge,this is the first reported practical dynamic interactive metasurface holographic system.We spa-tially divided the metasurface device into multiple distinct channels,each projecting a reconstructed sub-pattern.The switching states of these channels were mapped to bitwise operations on a set of bit values,which avoids complex holo-gram computations,enabling an ultra-high computational frame rate.Our approach achieves a computational frame rate of 800 kHz and a display frame rate of 23 kHz on a low-power Raspberry Pi computational platform.According to this methodology,we demonstrated an interactive dynamic holographic Tetris game system that allows interactive gameplay,color display,and on-the-fly hologram creation.Our technology presents an inspiration for advanced dynamic meta-holography,which is promising for a broad range of applications including advanced human-computer interaction,real-time 3D visualization,and next-generation virtual and augmented reality systems.

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.

Characteristics and mechanism of Ni^(2+)and Cd^(2+)adsorption by recovered perlite from agar extraction residue

Ni^(2+)and Cd^(2+)in wastewater accumulated through the ecological chain and could jeopardize human health.Adsorption of Ni^(2+)and Cd^(2+)from wastewater using recovered perlite was an important way to solve the problem of resource utilization of solid waste from agar production.Our previous study confirmed that recovered perlite from agar extraction residue had better pore size and specific surface area than commercial perlite.However,the adsorption efficiency and adsorption mechanism of recovered perlite were the main factors limiting its adsorption application.The adsorption process of Ni^(2+)and Cd^(2+)by recovered perlite in aqueous solution was described by the pseudo-second-order kinetic equation,and the relevant adsorption mechanism was mainly chemisorption.Compared with commercial perlite,the adsorption removal rate of Ni^(2+)and Cd^(2+)by enzymatic recovered perlite could reach 92.9%and 89.2%,respectively,and were improved by 12.63%and 13.03%.Langmuir isothermal adsorption model could better describe the isothermal adsorption process of recovered perlite on heavy metal Ni^(2+)and Cd^(2+),and the relevant adsorption mechanism was mainly monolayer adsorption.The X-ray photoelectron spectroscopy(XPS)results indicated that the decrease of Si—O Si^(2+)hydroxyl coordination bond and the increase of C—Si bond might make the binding effect of recovered perlite with heavy metals stronger.The competitive adsorption of Ni^(2+)and Cd^(2+)by recovered perlite was still dominated by chemisorption and monolayer adsorption.This study was expected to provide a theoretical basis and technical support for the removal of Ni^(2+)and Cd^(2+)from wastewater using recovered perlite from seaweed residue.

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.

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.

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.

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.

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.

Cooperative Rate Splitting Transmit Design for Full-Duplex-Enabled Multiple Multicast Communication Systems

This paper examines the performance of Full-Duplex Cooperative Rate Splitting(FD-CRS)with Simultaneous Wireless Information and Power Transfer(SWIPT)support in Multiple Input Single Output(MISO)networks.In a Rate Splitting Multiple Access(RSMA)multicast system with two local users and one remote user,the common data stream contains the needs of all users,and all users can decode the common data stream.Therefore,each user can receive some information that other users need,and local users with better channel conditions can use this information to further enhance the reception reliability and data rate of users with poor channel quality.Even using Cell-Center-Users(CCUs)as a cooperative relay to assist the transmission of common data can improve the average system speed.To maximize the minimum achievable rate,we optimize the beamforming vector of Base Station(BS),the common streamsplitting vector,the cooperative distributed beamvector and the strong user transmission power under the power budget constraints of BS and relay devices and the service quality requirements constraints of users.Since the whole problem is not convex,we cannot solve it directly.Therefore,we propose a low complexity algorithm based on Successive Convex Approximation(SCA)technology to find the optimal solution to the problemunder consideration.The simulation results show that FD C-RSMA has better gain andmore powerful than FD C-NOMA,HD C-RSMA,RSMA and NOMA.

Experimental clearance rate and intraguild predation of jellyfish Cyanea nozakii

Cyanea nozakii,a common jellyfish distributed in offshore China,has a complex trophic relationship with other zooplankton groups.However,few studies have reported the predation rates and prey selection patterns of C.nozakii medusae on different prey items.Research is also lacking on the intraguild predation of Aurelia coerulea(another common bloom jellyfish in offshore China)by C.nozakii.To address the knowledge gaps,the clearance rates of C.nozakii for different prey items,including copepods(small<1000μm and large>1000μm),fish larvae,and gelatinous prey(hydromedusae,A.coerulea ephyrae,and chaetognaths),were measured.The influence of predator size on the clearance rate was also determined.Additionally,we examined the intraguild predation of C.nozakii on A.coerulea medusae.The clearance rates of C.nozakii varied widely with prey organisms,being independent of prey concentrations.Gelatinous organisms,except for chaetognaths,were captured with considerably high efficiency,followed by fish larvae and copepods,indicating the preferential prey selection of gelatinous organisms by C.nozakii.The clearance rate increased linearly with the cross-sectional area of C.nozakii.Body size in medusae may,to some extents,underpin their capacity to capture more prey by increasing the encounter rate and capture success through ontogeny.C.nozakii preyed voraciously on A.coerulea in high feeding efficiency,but the clearance rate decreased with increasing A.coerulea(as prey)size.This phenomenon of intraguild predation suggests a speculative hypothesis of potential population regulation of A.coerulea by C.nozakii.The information regarding the feeding ecology of C.nozakii reported in this study is important for understanding plankton dynamics in marine ecosystems with extensive occurrences of this jellyfish.

Knee Arthroplasty Incidence Rate vs. Revision of Knee Arthroplasty and Its Associated Comorbidities in Colombia

Introduction: Total knee arthroplasty (TKA) has been established as a transformative solution in the treatment of advanced degenerative diseases of the knee, such as osteoarthritis, rheumatoid arthritis, and posttraumatic arthritis. In this sense, TKA surgery, which seeks to replace the damaged joint with prosthetic components, has proven to be highly effective in relieving pain, improving joint function, and, ultimately, significantly increasing patients’ quality of life. The present study describes the TKA and revision knee arthroplasty (RKA) rates and, identifies the associated co morbidities in the Colombian context. Methods: A retrospective cohort study was carried out. It describes demographic and clinical characteristics between two groups of patients, TKA or RKA, and its association with mortality at 30 days, 90 days, or one year after the intervention. Results: The incidence rate of the population undergoing TKA was approximately 11.71 cases per 100,000 inhabitants. Furthermore, the incidence rate for revision knee arthroplasty (RKA) procedures in the same period was around 0.96 per 100,000 inhabitants. In both groups at 30 days postoperatively, a total mortality rate of 0.09%was recorded. When the follow-up was extended to 90 days, it increased to 0.15%;at one year postoperatively, it rose to 0.88%. Conclusion: Mortality after surgery was low in Colombia in 2019. Although RKA is a beneficial procedure, in certain circumstances, it was noted that it carries a higher risk compared to primary TKA. Our results emphasize the importance of careful evaluation of co morbidities and risk factors in patients undergoing these surgical procedures. The application of quality-of-life questionnaires should be considered in future studies on effectiveness and mortality for TKA and RKA in our country.

Recent Progress in Improving Rate Performance of Cellulose-Derived Carbon Materials for Sodium-Ion Batteries

Cellulose-derived carbon is regarded as one of the most promising candidates for high-performance anode materials in sodium-ion batteries;however,its poor rate performance at higher current density remains a challenge to achieve high power density sodium-ion batteries.The present review comprehensively elucidates the structural characteristics of cellulose-based materials and cellulose-derived carbon materials,explores the limitations in enhancing rate performance arising from ion diffusion and electronic transfer at the level of cellulose-derived carbon materials,and proposes corresponding strategies to improve rate performance targeted at various precursors of cellulose-based materials.This review also presents an update on recent progress in cellulose-based materials and cellulose-derived carbon materials,with particular focuses on their molecular,crystalline,and aggregation structures.Furthermore,the relationship between storage sodium and rate performance the carbon materials is elucidated through theoretical calculations and characterization analyses.Finally,future perspectives regarding challenges and opportunities in the research field of cellulose-derived carbon anodes are briefly highlighted.

Impact of cooling rate on exfoliation corrosion resistance of a Li-containing 7xxx aluminum alloy

The impact of cooling rate after solution heat treatment on exfoliation corrosion resistance of a Li-containing 7xxx aluminum alloy was investigated by accelerated immersion and electrochemical impedance spectroscopy test,optical microscope,electron backscatter diffraction and scanning transmission electron microscope.With the decrease of cooling rate from 1700℃/s to 4℃/s,exfoliation corrosion resistance of the aged specimens decreases with rating changing from EA to EC and the maximum corrosion depth increasing from about 169.4μm to 632.1μm.Exfoliation corrosion tends to develop along grain boundaries in the specimens with cooling rates higher than about 31℃/s and along both grain boundaries and sub-grain boundaries in the specimens with lower cooling rates.The reason has been discussed based on the changes of the microstructure and microchemistry at grain boundaries and sub-grain boundaries due to slow cooling.

High-efficiently doping nitrogen in kapok fiber-derived hard carbon used as anode materials for boosting rate performance of sodium-ion batteries

The engineering of plant-based precursor for nitrogen doping has become one of the most promising strategies to enhance rate capability of hard carbon materials for sodium-ion batteries;however,the poor rate performance is mainly caused by lack of pyridine nitrogen,which often tends to escape because of high temperature in preparation process of hard carbon.In this paper,a high-rate kapok fiber-derived hard carbon is fabricated by cross-linking carboxyl group in 2,6-pyridinedicarboxylic acid with the exposed hydroxyl group on alkalized kapok with assistance of zinc chloride.Specially,a high nitrogen doping content of 4.24%is achieved,most of which are pyridine nitrogen;this is crucial for improving the defect sites and electronic conductivity of hard carbon.The optimized carbon with feature of high nitrogen content,abundant functional groups,degree of disorder,and large layer spacing exhibits high capacity of 401.7 mAh g^(−1)at a current density of 0.05 A g^(−1),and more importantly,good rate performance,for example,even at the current density of 2 A g^(−1),a specific capacity of 159.5 mAh g^(−1)can be obtained.These findings make plant-based hard carbon a promising candidate for commercial application of sodium-ion batteries,achieving high-rate performance with the enhanced pre-cross-linking interaction between plant precursors and dopants to optimize aromatization process by auxiliary pyrolysis.