Valorization of Camellia oleifera oil processing byproducts to value-added chemicals and biobased materials: A critical review

The C.oleifera oil processing industry generates large amounts of solid wastes,including C.oleifera shell(COS)and C.oleifera cake(COC).Distinct from generally acknowledged lignocellulosic biomass(corn stover,bamboo,birch,etc.),Camellia wastes contain diverse bioactive substances in addition to the abundant lignocellulosic components,and thus,the biorefinery utilization of C.oleifera processing byproducts involves complicated processing technologies.This reviewfirst summarizes various technologies for extracting and converting the main components in C.oleifera oil processing byproducts into value-added chemicals and biobased materials,as well as their potential applications.Microwave,ultrasound,and Soxhlet extractions are compared for the extraction of functional bioactive components(tannin,flavonoid,saponin,etc.),while solvothermal conversion and pyrolysis are discussed for the conversion of lignocellulosic components into value-added chemicals.The application areas of these chemicals according to their properties are introduced in detail,including utilizing antioxidant and anti-in-flammatory properties of the bioactive substances for the specific application,as well as drop-in chemicals for the substitution of unrenewable fossil fuel-derived products.In addition to chemical production,biochar fabricated from COS and its applications in thefields of adsorption,supercapacitor,soil remediation and wood composites are comprehensively reviewed and discussed.Finally,based on the compositions and structural characteristics of C.oleifera byproducts,the development of full-component valorization strategies and the expansion of the appli-cationfields are proposed.

Upcycling plastic wastes into value-added products via electrocatalysis and photoelectrocatalysis

Plastic,renowned for its versatility,durability,and cost-effectiveness,is indispensable in modern society.Nevertheless,the annual production of nearly 400 million tons of plastic,coupled with a recycling rate of only 9%,has led to a monumental environmental crisis.Plastic recycling has emerged as a vital response to this crisis,offering sustainable solutions to mitigate its environmental impact.Among these recycling efforts,plastic upcycling has garnered attention,which elevates discarded plastics into higher-value products.Here,electrocatalytic and photoelectrocatalytic treatments stand at the forefront of advanced plastic upcycling.Electrocatalytic or photoelectrocatalytic treatments involve chemical reactions that facilitate electron transfer through the electrode/electrolyte interface,driven by electrical or solar energy,respectively.These methods enable precise control of chemical reactions,harnessing potential,current density,or light to yield valuable chemical products.This review explores recent progress in plastic upcycling through electrocatalytic and photoelectrocatalytic pathways,offering promising solutions to the plastic waste crisis and advancing sustainability in the plastics industry.

Artificial photosynthesis for high-value-added chemicals:Old material,new opportunity

Solar energy utilization has drawn attention due to ever-increasing environmental and energy issues.Photoelectrochemical(PEC)and photocatalytic(PC)water splitting for hydrogen production,which is the most popular and well-established solar-to-chemical conversion process,has been studied thoroughly to date but is now facing limitations related to low conversion efficiency.To resolve this issue,research in PEC cells or photocatalysts has recently aimed to produce alternative value-added chemicals by modifying their redox reactions,which potentially enables high economic reward to compensate for the low efficiency.Here,various kinds of redox reactions that decouple classic water splitting reactions to produce value-added chemicals via PEC and PC processes are introduced.Successful coupling of CO_(2) reduction,O_(2) reduction and organic synthesis with either water oxidation or water reduction is comprehensively discussed from the perspective of basic fundamental and product selectivity in terms of the band structure of materials,cocatalyst design,and thermodynamics and kinetics of the reactions.Throughout the review,future challenges and opportunities are suggested with respect to the redesigned artificial synthesis,which might be an alternative development for the commercialization of PEC or PC value-added chemical production technologies in the near future.

Food processing wastewater purification by microalgae cultivation associated with high value-added compounds production——A review

Microalgae have been considered as an efficient microorganism for wastewater treatment with simultaneously bioenergy and high value-added compounds production.However,the high energy cost associated with complicated biorefinery(e.g.microalgae cultivation,harvesting,drying,extraction,conversion,and purification)is a critical challenge that inhibits its large-scale application.Among different nutrition(e.g.carbon,nitrogen and phosphorous)sources,food processing wastewater is a relative safe and suitable one for microalgae cultivation due to its high organic content and low toxicity.In this review,the characteristic of different food wastewater is summarized and compared.The potential routes of value-added products(i.e.biofuel,pigment,polysaccharide,and amino acid)production along with wastewater purification are introduced.The existing challenges(e.g.biorefinery cost,efficiency and mechanism)of microalgal-based wastewater treatment are also discussed.The prospective of microalgae-based food processing wastewater treatment strategies(such as microalgae-bacteria consortium,poly-generation of bioenergy and value-added products)is forecasted.It can be observed that food wastewater treatment by microalgae could be a promising strategy to commercially realize waste source reduce,conversion and reutilization.

Influence of Pt/Ru anodic ratio on the valorization of ethanol by PEM electrocatalytic reforming towards value-added products

The ethanol electro-reforming process was studied over PtRu/C catalysts synthesized by the modified polyol method with different compositions.In particular,this work reports the influence of anodic Pt:Ru ratio(5:1,2:1 and 1:2)on the organic product distribution(acetaldehyde,acetic acid and ethyl acetate)and pure hydrogen generation at different current densities operation levels.Physicochemical characterization of the catalysts was made by X-ray diffraction(XRD),temperature-programmed reduction(TPR)and N_(2) adsorption-desorption measurements.XRD patterns showed that Ru is introduced into the Pt structure,forming an alloy between both metals.Also,the degree of alloy was higher by increasing the Ru amounts.From TPR profiles Pt was found to be properly reduced while Ru was both in metallic state and forming RuO2.The electrochemical behaviour of each catalyst towards ethanol electroreforming process was investigated through electrochemical techniques in a half cell and a single proton exchange membrane(PEM)cell systems.An intermediate Pt:Ru ratio was found to result in high current density and electrochemical surface area(ECSA)values along with lower amounts of adsorbed species.Also,Ru addition seems to diminish the degree of degradation of the catalyst.Based on characterization and in agreement with essays carried out in a PEM cell at mild conditions(80℃ and 1 atm),PtRu/C 2:1 anode provided the best electrocatalytic results in terms of current density(740 mA cm^(-2)),hydrogen production and selectivity toward acetic acid(up to 15%apart from acetaldehyde and ethyl acetate)while requiring the lowest energy consumption.

Brief analysis on value-added tax transformation and its influence on enterprises

From Jan. 1st, 2009, the value-added tax transformation will be performed in all industries around the country. Based on value-added tax types and retrospection of reform practices, this article analyzes the background of the national value-added tax transformation and points out the influence of full implementation of the value-added tax transformation on various enterprises.

Evolution trends and structural decomposition of China's green value-added over 40 years of reform and opening-up

China's 40-year history of reform and opening-up includes rapid economic development as well as pollution and environmental governance.Using a four-stage division,this study explores the evolution trend and structural decomposition of China's green value-added by constructing a non-competitive input-output table for environmental pollution from 1978 to 2017.The results indicate that pollution production coefficients increased continuously,and the green value-added index decreased.Additionally,the structural decomposition showed that investment and export were critical for economic growth during the period,though they were accompanied by serious pollution problems.The pollution generated by the raw material(represented by coal mining)and processing industries(represented by the textiles)were not controlled effectively.Pollution treatment for these industries should be strengthened in the future.The study has implications for government officials,policy makers,and academics.First,China should make green development a core concept for economic development,increase environmental pollution governance,develop a“green GDP,”incorporate the external costs of environmental pollution into the national economic accounting system.Second,it must change the investment and export structure as well as the traditional economic development pattern that exacerbates pollution.Specifically,the country should develop industries with low pollution and promote the export of industries producing high value-added products and increase green GDP per capita.Third,it should closely monitor the development of highly polluting industries.Upgrading technology to reduce pollution and strengthening pollution treatment will reduce the number of polluting industries and improve environmental governance efficiency.

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.

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.

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.

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.

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.

Reactive ball-milling synthesis of Co-Fe bimetallic catalyst for efficient hydrogenation of carbon dioxide to value-added hydrocarbons

Catalytic hydrogenation of CO_(2) using renewable hydrogen not only reduces greenhouse gas emissions,but also provides industrial chemicals.Herein,a Co-Fe bimetallic catalyst was developed by a facile reactive ball-milling method for highly active and selective hydrogenation of CO_(2) to value-added hydrocarbons.When reacted at 320℃,1.0 MPa and 9600 mL h^(-1) g_(cat)^(-1),the selectivity to light olefin(C_(2)^(=)-C_(4)^(=)) and C_(5)+ species achieves 57.3% and 22.3%,respectively,at a CO_(2) co nversion of 31.4%,which is superior to previous Fe-based catalysts.The CO_(2) activation can be promoted by the CoFe phase formed by reactive ball milling of the Fe-Co_(3)O_(4) mixture,and the in-situ Co_(2)C and Fe_(5)C_(2) formed during hydrogenation are beneficial for the C-C coupling reaction.The initial C-C coupling is related to the combination of CO species with the surface carbon of Fe/Co carbides,and the sustained C-C coupling is maintained by self-recovery of defective carbides.This new strategy contributes to the development of efficient catalysts for the hydrogenation of CO_(2) to value-added hydrocarbons.

PoC: An IMS-based Wireless Value-added Service

This article introduces the Push-to-talk over Cellular( PoC) service, a new mobile value-added service based on the IP Multimedia Subsystem (IMS). Its implementation scheme is discussed and its Session Initiation Protocol (SIP) signaling exchange flow is described. Target user groups are predicted based on the analysis of the strengths and weaknesses of the PoC service. The article purports that the PoC system could undoubtedly be used as a platform for new services such as multimedia messaging, instant messaging, presence, and picture receiving and sending. Just like the short message service, the PoC service will help the terminal vendors, equipment vendors, content providers and operators setup a win-for-all industrial value chain.

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.

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.

Export Value-Added of China’s Manufacturing Sector:Estimation and Mechanism Analysis

Estimation of domestic and overseas value-added of manufacturing sector is an important and difficult subject for the science-based evaluation of a country＇s trade interests under global value chain. Traditional HIY approach overestimates the domestic value- added of export. Although Koopman＇s method made certain improvements, it cannot utilize traditional I/O matrix and direct input coefficient matrix under the condition of incomplete information. By creating GAMS model, this paper addresses the above-mentioned problems and employs an improved model for the estimation of variations in domestic and overseas value-added of Chinese exports between 2002 and 2012. Our results indicate that by neglecting the export of processing trade, HIY approach overestimates the domestic value- added ratio of Chinese exports. As more imported intermediate inputs have been used in the export of processing trade, the estimation result of this paper have corrected deviations in the forecast of overseas value-added ratio and its tendencies based on HIY method Further analysis of specific factors of domestic value-added of export led to the discovery that the domestic value-added of export of processing trade and mixed trade is highly vulnerable to the impact of international capital inflow. It can be seen that the improved method for the estimation of value-added has indeed corrected the deviations in the estimation of China＇s value-added. In conclusion, China should accelerate the development of export of non- processing trade and trade in high-end services, and balance the relationship of export between local firms and foreign-funded firms, with a view to improving trade dependence and increasing the trade status of Chinese manufaeturing firms in global value chain.

International Competitiveness of China’s Manufacturing Sectors:Estimation Based on Trade in Value-added

Based on trade in value-added, this paper has estimated the revealed comparative advantage （RCA） of China＇s various manufacturing sectors between 1995 and 2011 and compared with the RCA indexes measured using conventional aggregate accounting approach. Results indicate that： （1） the RCA index measured using conventional aggregate accounting approach has underestimated China＇s comparative advantage of labor-intensive sectors but overestimated China＇s comparative advantage in capital, knowledge and technology-intensive manufacturing sectors, giving rise to a serious misjudgment. （2） The RCA measured using value-added approach shows that in the industry chain layout of global manufacturing sectors, China＇s comparative advantage is still concentrated in labor-intensive manufacturing sectors but has signs of weakening; in capital, knowledge and technology-intensive sectors, China is yet to develop any significant comparative advantage; there are signs that China is developing comparative advantage in capital-intensive sectors yet China＇s comparative disadvantage in knowledge and technology-intensive sectors has no significant tendency to improve. This result not only helps correct the misjudgment of China＇s competitiveness in manufacturing sectors based on conventional aggregate accounting approach but offers important policy implications for setting strategic directions and policies for China＇s manufacturing transition and upgrade.

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.