Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study...Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study reports Ir-doped NiFe_(2)O_(4)(NFI,~5 at%Ir)spinel layer with TiO_(2) overlayer(NFI/TiO_(2)),as a scalable heterojunction anode for direct electrolysis of wastewater with circumneutral pH in a single-compartment cell.In dilute(0.1 M)NaCl solutions,the NFI/TiO_(2) marks superior activity and selectivity for chlorine evolution reaction,outperforming the benchmark IrO_(2).Robust operation in near-neutral pH was confirmed.Electroanalyses including operando X-ray absorption spectroscopy unveiled crucial roles of TiO_(2) which serves both as the primary site for Cl−chemisorption and a protective layer for NFI as an ohmic contact.Galvanostatic electrolysis of NH4+-laden synthetic wastewater demonstrated that NFI/TiO_(2)not only achieves quasi-stoichiometric NH_(4)^(+)-to-N_(2)conversion,but also enhances H_(2)generation efficiency with minimal competing reactions such as reduction of dissolved oxygen and reactive chlorine.The scaled-up WEC with NFI/TiO_(2)was demonstrated for electrolysis of toilet wastewater.展开更多
For the purpose of satisfying high demands for taste,color,flavor,and storage of meat products,water retention agents(WRAs)play an important role.Phosphate has been widely used as an attractive functional material for...For the purpose of satisfying high demands for taste,color,flavor,and storage of meat products,water retention agents(WRAs)play an important role.Phosphate has been widely used as an attractive functional material for water retention in current practical applications.However,excessive phosphate addition and longterm consumption may be harmful impacts on health and the environment.Therefore,it is vital to develop safe and efficient phosphate-free WRAs for further improving water-holding capacity(WHC)efficacy and edible safety,especially in meat products.In particular,sugar water retention agents(SWRAs)are increasingly popular because of their perfect safety,excellent WHC,and superior biological properties.This review discusses the inducements and mechanisms underlying water loss in meat products.In addition,we focused on the research progresses and related mechanisms of SWRAs in the WHC of meat products and its unique biological functions,as well as the extraction technology.Finally,the future application and development of SWRA were prospected.展开更多
Sodium chloride is one of the most widely used additives in meat curing.However,cured meat products contribute to a portion of the total sodium dietary intake.Consumers and researchers'concern about excessive sodi...Sodium chloride is one of the most widely used additives in meat curing.However,cured meat products contribute to a portion of the total sodium dietary intake.Consumers and researchers'concern about excessive sodium intake has prompted the food industry to consider ways to reduce salt content of cured meat products.The aim of this review is to provide a broad but comprehensive understanding of salt reduction strategies for cured meat products.The implications and limitations of each approach were discussed.Green technologies treatments,such as ultrasonic technology,high-pressure processing,seem to be potential to ensure microbiological safety in low-sodium cured meat products.However,these novel technologies can cause protein and fat oxidization in meat products.A combination of multiple treatments could give the desired effect.In addition,different parameter conditions need to be set according to the specific meat to achieve better salt reduction effect.展开更多
Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan ...Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan is one of the crucial issues in shipbuilding.In this paper,production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated.The uncertain factors in outfitting equipment production are usually decision-related,which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan.This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model.To address this problem,a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process.A practical case of the shipyard of China Merchants Heavy Industry Co.,Ltd.is used to evaluate the performance of the proposed method.Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.展开更多
Hydrogen generation and related energy applications heavily rely on the hydrogen evolution reaction(HER),which faces challenges of slow kinetics and high overpotential.Efficient electrocatalysts,particularly single-at...Hydrogen generation and related energy applications heavily rely on the hydrogen evolution reaction(HER),which faces challenges of slow kinetics and high overpotential.Efficient electrocatalysts,particularly single-atom catalysts (SACs) on two-dimensional (2D) materials,are essential.This study presents a few-shot machine learning (ML) assisted high-throughput screening of 2D septuple-atomic-layer Ga_(2)CoS_(4-x)supported SACs to predict HER catalytic activity.Initially,density functional theory (DFT)calculations showed that 2D Ga_(2)CoS4is inactive for HER.However,defective Ga_(2)CoS_(4-x)(x=0–0.25)monolayers exhibit excellent HER activity due to surface sulfur vacancies (SVs),with predicted overpotentials (0–60 mV) comparable to or lower than commercial Pt/C,which typically exhibits an overpotential of around 50 m V in the acidic electrolyte,when the concentration of surface SV is lower than 8.3%.SVs generate spin-polarized states near the Fermi level,making them effective HER sites.We demonstrate ML-accelerated HER overpotential predictions for all transition metal SACs on 2D Ga_(2)CoS_(4-x).Using DFT data from 18 SACs,an ML model with high prediction accuracy and reduced computation time was developed.An intrinsic descriptor linking SAC atomic properties to HER overpotential was identified.This study thus provides a framework for screening SACs on 2D materials,enhancing catalyst design.展开更多
The transition of hydrogen sourcing from carbon-intensive to water-based methodologies is underway,with renewable energy-powered proton exchange membrane water electrolysis(PEMWE)emerging as the preeminent pathway for...The transition of hydrogen sourcing from carbon-intensive to water-based methodologies is underway,with renewable energy-powered proton exchange membrane water electrolysis(PEMWE)emerging as the preeminent pathway for hydrogen production.Despite remarkable advancements in this field,confronting the sluggish electrochemical kinetics and inherent high-energy consumption arising from deteriorated mass transport within PEMWE systems remains a formidable obstacle.This impediment stems primarily from the hindered protons mass transfer and the untimely hydrogen bubbles detachment.To address these challenges,we harness the inherent variability of electrical energy and introduce an innovative pulsed dynamic water electrolysis system.Compared to constant voltage electrolysis(hydrogen production rate:51.6 m L h^(-1),energy consumption:5.37 kWh Nm-^(3)H_(2)),this strategy(hydrogen production rate:66 m L h^(-1),energy consumption:3.83 kWh Nm-^(3)H_(2))increases the hydrogen production rate by approximately 27%and reduces the energy consumption by about 28%.Furthermore,we demonstrate the practicality of this system by integrating it with an off-grid photovoltaic(PV)system designed for outdoor operation,successfully driving a hydrogen production current of up to 500 mA under an average voltage of approximately 2 V.The combined results of in-situ characterization and finite element analysis reveal the performance enhancement mechanism:pulsed dynamic electrolysis(PDE)dramatically accelerates the enrichment of protons at the electrode/solution interface and facilitates the release of bubbles on the electrode surface.As such,PDE-enhanced PEMWE represents a synergistic advancement,concurrently enhancing both the hydrogen generation reaction and associated transport processes.This promising technology not only redefines the landscape of electrolysis-based hydrogen production but also holds immense potential for broadening its application across a diverse spectrum of electrocatalytic endeavors.展开更多
In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology bas...In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.展开更多
Heat processing of food has been well validated as the trigger to generate heat-processing side product of advanced lipoxidation end products(ALEs),which potentially engenders the threat on systemic health or progress...Heat processing of food has been well validated as the trigger to generate heat-processing side product of advanced lipoxidation end products(ALEs),which potentially engenders the threat on systemic health or progression of diseases,especially the accumulated effect after long-term intake.Thus,the study was proposed to evaluate the effect of dietary ALEs on health after long-term ingestion,specifically through simulating the intake of dietary ALE in mice within 9 months to investigate the intervention effect and underlying mechanism.The unexpected observation of renal insufficiency or impairment after long-term intake of dietary ALEs indicated the negative impact on renal health,which has been verified by the pathological analysis.Further studies revealed that a high-ALEs diet disrupted the intestinal barrier,with enhanced impact after disturbing the gut microbiota to potentially lower the abundance of beneficial microbiome through producing nephrotoxic metabolites.Correlation analysis showed that the proliferation of harmful bacteria and the reduction of beneficial bacteria were strongly correlated with intestinal barrier damage and the development of renal insufficiency.Furthermore,the underlying mechanism was unveiled as that ALEs could inhibit AMPK/SIRT1 signaling to fundamentally induce renal inflammation and oxidative stress.Thus,it was revealed that long-term intake of dietary ALE could result in renal impairment,and the results emphasized the control or intervention on dietary ALE to decrease to accumulated impairment on systemic health.展开更多
Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate change.Water electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen pro...Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate change.Water electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen production technology based on the viable possibility of large-scale hydrogen production and the zero-carbon-emission nature of the process.However,for hydrogen produced via water electrolysis systems to be utilized in various fields in practice,the unit cost of hydrogen production must be reduced to$1/kg H_(2).To achieve this unit cost,technical targets for water electrolysis have been suggested regarding components in the system.In this paper,the types of water electrolysis systems and the limitations of water electrolysis system components are explained.We suggest guideline with recent trend for achieving this technical target and insights for the potential utilization of water electrolysis technology.展开更多
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 ...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.展开更多
Herein,ionomer-free amorphous iridium oxide(IrO_(x))thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells(PEMECs)via low-cost,environmentally friendly,and easily s...Herein,ionomer-free amorphous iridium oxide(IrO_(x))thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells(PEMECs)via low-cost,environmentally friendly,and easily scalable electrodeposition at room temperature.Combined with a Nafion 117 membrane,the IrO_(x)-integrated electrode with an ultralow loading of 0.075 mg cm^(-2)delivers a high cell efficiency of about 90%,achieving more than 96%catalyst savings and 42-fold higher catalyst utilization compared to commercial catalyst-coated membrane(2 mg cm^(-2)).Additionally,the IrO_(x)electrode demonstrates superior performance,higher catalyst utilization and significantly simplified fabrication with easy scalability compared with the most previously reported anodes.Notably,the remarkable performance could be mainly due to the amorphous phase property,sufficient Ir^(3+)content,and rich surface hydroxide groups in catalysts.Overall,due to the high activity,high cell efficiency,an economical,greatly simplified and easily scalable fabrication process,and ultrahigh material utilization,the IrO_(x)electrode shows great potential to be applied in industry and accelerates the commercialization of PEMECs and renewable energy evolution.展开更多
Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing researc...Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing research suggests that the effectiveness of a surrogate model can vary depending on the complexity of the design problem.A surrogate model that has demonstrated success in one scenario may not perform as well in others.In the absence of prior knowledge,finding a promising surrogate model that performs well for an unknown reservoir is challenging.Moreover,the optimization process often relies on a single evolutionary algorithm,which can yield varying results across different cases.To address these limitations,this paper introduces a novel approach called the multi-surrogate framework with an adaptive selection mechanism(MSFASM)to tackle production optimization problems.MSFASM consists of two stages.In the first stage,a reduced-dimensional broad learning system(BLS)is used to adaptively select the evolutionary algorithm with the best performance during the current optimization period.In the second stage,the multi-objective algorithm,non-dominated sorting genetic algorithm II(NSGA-II),is used as an optimizer to find a set of Pareto solutions with good performance on multiple surrogate models.A novel optimal point criterion is utilized in this stage to select the Pareto solutions,thereby obtaining the desired development schemes without increasing the computational load of the numerical simulator.The two stages are combined using sequential transfer learning.From the two most important perspectives of an evolutionary algorithm and a surrogate model,the proposed method improves adaptability to optimization problems of various reservoir types.To verify the effectiveness of the proposed method,four 100-dimensional benchmark functions and two reservoir models are tested,and the results are compared with those obtained by six other surrogate-model-based methods.The results demonstrate that our approach can obtain the maximum net present value(NPV)of the target production optimization problems.展开更多
Maillard reaction(MR)is a non-enzymatic browning reaction commonly seen in food processing,which occurs between reducing sugars and compounds with amino groups.Despite certain advantages based on Maillard reaction pro...Maillard reaction(MR)is a non-enzymatic browning reaction commonly seen in food processing,which occurs between reducing sugars and compounds with amino groups.Despite certain advantages based on Maillard reaction products(MRPs)found in some food for health and storage application have appeared,however,the MR occurring in human physiological environment can produce advanced glycation end products(AGEs)by non-enzymatic modification of macromolecules such as proteins,lipids and nucleic acid,which could change the structure and functional activity of the molecules themselves.In this review,we take AGEs as our main object,on the one hand,discuss physiologic aging,that is,age-dependent covalent cross-linking and modification of proteins such as collagen that occur in eyes and skin containing connective tissue.On the other hand,pathological aging associated with autoimmune and inflammatory diseases,neurodegenerative diseases,diabetes and diabetic nephropathy,cardiovascular diseases and bone degenerative diseases have been mainly proposed.Based on the series of adverse effects of accelerated aging and disease pathologies caused by MRPs,the possible harm caused by some MR can be slowed down or inhibited by artificial drug intervention,dietary pattern and lifestyle control.It also stimulates people's curiosity to continue to explore the potential link between the MR and human aging and health,which should be paid more attention to for the development of life sciences.展开更多
Shale gas, as an environmentally friendly fossil energy resource, has gained significant commercial development and shows immense potential. However, accurately predicting shale gas production faces substantial challe...Shale gas, as an environmentally friendly fossil energy resource, has gained significant commercial development and shows immense potential. However, accurately predicting shale gas production faces substantial challenges due to the complex law of decline, nonlinear and non-stationary features in production data, which greatly repair the robustness of current models in predicting shale gas production time series. To address these challenges and improve accuracy in production forecasting, this paper introduces a novel and innovative approach: a hybrid proxy model that combines the bidirectional long short-term memory(BiLSTM) neural network and random forest(RF) through deep learning. The BiLSTM neural network is adept at capturing long-term dependencies, making it suitable for understanding the intricate relationships between input and output variables in shale gas production.On the other hand, RF serves a dual purpose: reducing model variance and addressing the concept drift problem that arises in non-stationary time series predictions made by BiLSTM. By integrating these two models, the hybrid approach effectively captures the inherent dependencies present in long and nonstationary production time series, thereby reducing model uncertainty. Furthermore, the combination of BiLSTM and RF is optimized using the recently-proposed marine predators algorithm(MPA) to fine-tune hyperparameters and enhance the overall performance of the proxy model. The results demonstrate that the proposed BiLSTM-RF-MPA model achieves higher prediction accuracy and demonstrates stronger generalization capabilities by effectively handling the complex nonlinear and non-stationary characteristics of shale gas production time series. Compared to other models such as LSTM, BiLSTM, and RF, the proposed model exhibits superior fitting and prediction performance, with an average improvement in performance indicators exceeding 20%. This innovative framework provides valuable insights for forecasting the complex production performance of unconventional oil and gas reservoirs, which sheds light on the development of data-driven proxy models in the field of subsurface energy utilization.展开更多
To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the process.The development history of other reservoirs in the same class tends to be studie...To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the process.The development history of other reservoirs in the same class tends to be studied to make predictions accurate.However,the permeability field,well patterns,and development regime must all be similar for two reservoirs to be considered in the same class.This results in very few available experiences from other reservoirs even though there is a lot of historical information on numerous reservoirs because it is difficult to find such similar reservoirs.This paper proposes a learn-to-learn method,which can better utilize a vast amount of historical data from various reservoirs.Intuitively,the proposed method first learns how to learn samples before directly learning rules in samples.Technically,by utilizing gradients from networks with independent parameters and copied structure in each class of reservoirs,the proposed network obtains the optimal shared initial parameters which are regarded as transferable information across different classes.Based on that,the network is able to predict future production indices for the target reservoir by only training with very limited samples collected from reservoirs in the same class.Two cases further demonstrate its superiority in accuracy to other widely-used network methods.展开更多
Soluble receptor for advanced glycation end products(sRAGE)acts as a decoy sequestering of RAGE ligands,thus preventing the activation of the ligand-RAGE axis linking human diseases.However,the molecular mechanisms un...Soluble receptor for advanced glycation end products(sRAGE)acts as a decoy sequestering of RAGE ligands,thus preventing the activation of the ligand-RAGE axis linking human diseases.However,the molecular mechanisms underlying sRAGE remain unclear.In this study,THP-1 monocytes were cultured in normal glucose(NG,5.5 mmol/L)and high glucose(HG,15 mmol/L)to investigate the effects of diabetesrelevant glucose concentrations on sRAGE and interleukin-1β(IL-1β)secretion.The modulatory effects of epigallocatechin gallate(EGCG)in response to HG challenge were also evaluated.HG enhanced intracellular reactive oxygen species(ROS)generation and RAGE expression.The secretion of sRAGE,including esRAGE and cRAGE,was reduced under HG conditions,together with the downregulation of a disintegrin and metallopeptidase 10(ADAM10)and nuclear factor erythroid 2-related factor 2(Nrf2)nuclear translocation.Mechanistically,the HG effects were counteracted by siRAGE and exacerbated by siNrf2.Chromatin immunoprecipitation results showed that Nrf2 binding to the ADAM10 promoter and HG interfered with this binding.Our data reinforce the notion that RAGE and Nrf2 might be sRAGE-regulating factors.Under HG conditions,the treatment of EGCG reduced ROS generation and RAGE activation.EGCG-stimulated cRAGE release was likely caused by the upregulation of the Nrf2-ADAM10 pathway.EGCG inhibited HG-mediated NLRP3 inflammasome activation at least partly by stimulating sRAGE,thereby reducing IL-1βrelease.展开更多
The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously pen...The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.展开更多
We establish the Stinespring dilation theorem of the link product of quantum channels in two different ways,discuss the discrimination of quantum channels,and show that the distinguishability can be improved by self-l...We establish the Stinespring dilation theorem of the link product of quantum channels in two different ways,discuss the discrimination of quantum channels,and show that the distinguishability can be improved by self-linking each quantum channel n times as n grows.We also find that the maximum value of Uhlmann's theorem can be achieved for diagonal channels.展开更多
The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way...The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way to judge whether the subsea production control system is normal.However,subsea sensors degrade rapidly due to harsh working environments and long service time.This leads to frequent false alarm incidents.A combinatorial reasoning-based abnormal sensor recognition method for subsea production control system is proposed.A combinatorial algorithm is proposed to group sensors.The long short-term memory network(LSTM)is used to establish a single inference model.A counting-based judging method is proposed to identify abnormal sensors.Field data from an offshore platform in the South China Sea is used to demonstrate the effect of the proposed method.The results show that the proposed method can identify the abnormal sensors effectively.展开更多
For each real number x∈(0,1),let[a_(1)(x),a_(2)(x),…,a_n(x),…]denote its continued fraction expansion.We study the convergence exponent defined byτ(x)=inf{s≥0:∞∑n=1(a_(n)(x)a_(n+1)(x))^(-s)<∞},which reflect...For each real number x∈(0,1),let[a_(1)(x),a_(2)(x),…,a_n(x),…]denote its continued fraction expansion.We study the convergence exponent defined byτ(x)=inf{s≥0:∞∑n=1(a_(n)(x)a_(n+1)(x))^(-s)<∞},which reflects the growth rate of the product of two consecutive partial quotients.As a main result,the Hausdorff dimensions of the level sets ofτ(x)are determined.展开更多
基金supported by the National Research Foundation of Korea(NRF)grants(2022R1A2C4001228,2022M3H4A4097524,2022M3I3A1082499,and 2021M3I3A1084818)the Technology Innovation Program(20026415)of the Ministry of Trade,Industry&Energy(MOTIE,Korea)the supports from Nanopac for fabrication of scaled-up reactor.
文摘Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study reports Ir-doped NiFe_(2)O_(4)(NFI,~5 at%Ir)spinel layer with TiO_(2) overlayer(NFI/TiO_(2)),as a scalable heterojunction anode for direct electrolysis of wastewater with circumneutral pH in a single-compartment cell.In dilute(0.1 M)NaCl solutions,the NFI/TiO_(2) marks superior activity and selectivity for chlorine evolution reaction,outperforming the benchmark IrO_(2).Robust operation in near-neutral pH was confirmed.Electroanalyses including operando X-ray absorption spectroscopy unveiled crucial roles of TiO_(2) which serves both as the primary site for Cl−chemisorption and a protective layer for NFI as an ohmic contact.Galvanostatic electrolysis of NH4+-laden synthetic wastewater demonstrated that NFI/TiO_(2)not only achieves quasi-stoichiometric NH_(4)^(+)-to-N_(2)conversion,but also enhances H_(2)generation efficiency with minimal competing reactions such as reduction of dissolved oxygen and reactive chlorine.The scaled-up WEC with NFI/TiO_(2)was demonstrated for electrolysis of toilet wastewater.
基金funded by National Natural Science Foundation of China(51901160)。
文摘For the purpose of satisfying high demands for taste,color,flavor,and storage of meat products,water retention agents(WRAs)play an important role.Phosphate has been widely used as an attractive functional material for water retention in current practical applications.However,excessive phosphate addition and longterm consumption may be harmful impacts on health and the environment.Therefore,it is vital to develop safe and efficient phosphate-free WRAs for further improving water-holding capacity(WHC)efficacy and edible safety,especially in meat products.In particular,sugar water retention agents(SWRAs)are increasingly popular because of their perfect safety,excellent WHC,and superior biological properties.This review discusses the inducements and mechanisms underlying water loss in meat products.In addition,we focused on the research progresses and related mechanisms of SWRAs in the WHC of meat products and its unique biological functions,as well as the extraction technology.Finally,the future application and development of SWRA were prospected.
基金financially supported by Youth Talent Support Programme of Guangdong Provincial Association for Science and Technology(SKXRC202317)the Open Project of Beijing Laboratory of Food Quality and Safety/Key Laboratory of Alcoholic Beverages Quality and Safety of China Light Industry(FQS-202201)+3 种基金Characteristic Innovation Project of Guangdong Universities(2022KTSCX058)Special Projects in Key Field of Guangdong Universities(2022ZDZX4015,2022ZDZX4016)Guangdong Maoming Binhai New Area Marine Fishery Industrial Park Project(0835-220FA8102621)Guangdong Provincial Key Laboratory of Lingnan Specialty Food Science and Technology(2021B1212040013)。
文摘Sodium chloride is one of the most widely used additives in meat curing.However,cured meat products contribute to a portion of the total sodium dietary intake.Consumers and researchers'concern about excessive sodium intake has prompted the food industry to consider ways to reduce salt content of cured meat products.The aim of this review is to provide a broad but comprehensive understanding of salt reduction strategies for cured meat products.The implications and limitations of each approach were discussed.Green technologies treatments,such as ultrasonic technology,high-pressure processing,seem to be potential to ensure microbiological safety in low-sodium cured meat products.However,these novel technologies can cause protein and fat oxidization in meat products.A combination of multiple treatments could give the desired effect.In addition,different parameter conditions need to be set according to the specific meat to achieve better salt reduction effect.
基金supported in part by the High-tech ship scientific research project of the Ministry of Industry and Information Technology of the People’s Republic of China,and the National Nature Science Foundation of China(Grant No.71671113)the Science and Technology Department of Shaanxi Province(No.2020GY-219)the Ministry of Education Collaborative Project of Production,Learning and Research(No.201901024016).
文摘Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan is one of the crucial issues in shipbuilding.In this paper,production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated.The uncertain factors in outfitting equipment production are usually decision-related,which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan.This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model.To address this problem,a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process.A practical case of the shipyard of China Merchants Heavy Industry Co.,Ltd.is used to evaluate the performance of the proposed method.Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.
文摘Hydrogen generation and related energy applications heavily rely on the hydrogen evolution reaction(HER),which faces challenges of slow kinetics and high overpotential.Efficient electrocatalysts,particularly single-atom catalysts (SACs) on two-dimensional (2D) materials,are essential.This study presents a few-shot machine learning (ML) assisted high-throughput screening of 2D septuple-atomic-layer Ga_(2)CoS_(4-x)supported SACs to predict HER catalytic activity.Initially,density functional theory (DFT)calculations showed that 2D Ga_(2)CoS4is inactive for HER.However,defective Ga_(2)CoS_(4-x)(x=0–0.25)monolayers exhibit excellent HER activity due to surface sulfur vacancies (SVs),with predicted overpotentials (0–60 mV) comparable to or lower than commercial Pt/C,which typically exhibits an overpotential of around 50 m V in the acidic electrolyte,when the concentration of surface SV is lower than 8.3%.SVs generate spin-polarized states near the Fermi level,making them effective HER sites.We demonstrate ML-accelerated HER overpotential predictions for all transition metal SACs on 2D Ga_(2)CoS_(4-x).Using DFT data from 18 SACs,an ML model with high prediction accuracy and reduced computation time was developed.An intrinsic descriptor linking SAC atomic properties to HER overpotential was identified.This study thus provides a framework for screening SACs on 2D materials,enhancing catalyst design.
基金National Natural Science Foundation of China(No.52476192,No.52106237)Natural Science Foundation of Heilongjiang Province(No.YQ2022E027)。
文摘The transition of hydrogen sourcing from carbon-intensive to water-based methodologies is underway,with renewable energy-powered proton exchange membrane water electrolysis(PEMWE)emerging as the preeminent pathway for hydrogen production.Despite remarkable advancements in this field,confronting the sluggish electrochemical kinetics and inherent high-energy consumption arising from deteriorated mass transport within PEMWE systems remains a formidable obstacle.This impediment stems primarily from the hindered protons mass transfer and the untimely hydrogen bubbles detachment.To address these challenges,we harness the inherent variability of electrical energy and introduce an innovative pulsed dynamic water electrolysis system.Compared to constant voltage electrolysis(hydrogen production rate:51.6 m L h^(-1),energy consumption:5.37 kWh Nm-^(3)H_(2)),this strategy(hydrogen production rate:66 m L h^(-1),energy consumption:3.83 kWh Nm-^(3)H_(2))increases the hydrogen production rate by approximately 27%and reduces the energy consumption by about 28%.Furthermore,we demonstrate the practicality of this system by integrating it with an off-grid photovoltaic(PV)system designed for outdoor operation,successfully driving a hydrogen production current of up to 500 mA under an average voltage of approximately 2 V.The combined results of in-situ characterization and finite element analysis reveal the performance enhancement mechanism:pulsed dynamic electrolysis(PDE)dramatically accelerates the enrichment of protons at the electrode/solution interface and facilitates the release of bubbles on the electrode surface.As such,PDE-enhanced PEMWE represents a synergistic advancement,concurrently enhancing both the hydrogen generation reaction and associated transport processes.This promising technology not only redefines the landscape of electrolysis-based hydrogen production but also holds immense potential for broadening its application across a diverse spectrum of electrocatalytic endeavors.
基金financially supported by National Key R&D Program(2021YFF0701905)。
文摘In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.
基金supported by grants from the National Natural Science Foundation of China(32030083)。
文摘Heat processing of food has been well validated as the trigger to generate heat-processing side product of advanced lipoxidation end products(ALEs),which potentially engenders the threat on systemic health or progression of diseases,especially the accumulated effect after long-term intake.Thus,the study was proposed to evaluate the effect of dietary ALEs on health after long-term ingestion,specifically through simulating the intake of dietary ALE in mice within 9 months to investigate the intervention effect and underlying mechanism.The unexpected observation of renal insufficiency or impairment after long-term intake of dietary ALEs indicated the negative impact on renal health,which has been verified by the pathological analysis.Further studies revealed that a high-ALEs diet disrupted the intestinal barrier,with enhanced impact after disturbing the gut microbiota to potentially lower the abundance of beneficial microbiome through producing nephrotoxic metabolites.Correlation analysis showed that the proliferation of harmful bacteria and the reduction of beneficial bacteria were strongly correlated with intestinal barrier damage and the development of renal insufficiency.Furthermore,the underlying mechanism was unveiled as that ALEs could inhibit AMPK/SIRT1 signaling to fundamentally induce renal inflammation and oxidative stress.Thus,it was revealed that long-term intake of dietary ALE could result in renal impairment,and the results emphasized the control or intervention on dietary ALE to decrease to accumulated impairment on systemic health.
基金supported by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)grant from the Ministry of Trade,Industry&Energy,Republic of Korea(No.20213030040590)the National R&D Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(NRF-2021K1A4A8A01079455)。
文摘Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate change.Water electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen production technology based on the viable possibility of large-scale hydrogen production and the zero-carbon-emission nature of the process.However,for hydrogen produced via water electrolysis systems to be utilized in various fields in practice,the unit cost of hydrogen production must be reduced to$1/kg H_(2).To achieve this unit cost,technical targets for water electrolysis have been suggested regarding components in the system.In this paper,the types of water electrolysis systems and the limitations of water electrolysis system components are explained.We suggest guideline with recent trend for achieving this technical target and insights for the potential utilization of water electrolysis technology.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00302697,2022H1D3A3A01077254)。
文摘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.
基金the support from the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Hydrogen and Fuel Cell Technologies Office Awards DE-EE0008426 and DE-EE0008423National Energy Technology Laboratory under Award DEFE0011585.
文摘Herein,ionomer-free amorphous iridium oxide(IrO_(x))thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells(PEMECs)via low-cost,environmentally friendly,and easily scalable electrodeposition at room temperature.Combined with a Nafion 117 membrane,the IrO_(x)-integrated electrode with an ultralow loading of 0.075 mg cm^(-2)delivers a high cell efficiency of about 90%,achieving more than 96%catalyst savings and 42-fold higher catalyst utilization compared to commercial catalyst-coated membrane(2 mg cm^(-2)).Additionally,the IrO_(x)electrode demonstrates superior performance,higher catalyst utilization and significantly simplified fabrication with easy scalability compared with the most previously reported anodes.Notably,the remarkable performance could be mainly due to the amorphous phase property,sufficient Ir^(3+)content,and rich surface hydroxide groups in catalysts.Overall,due to the high activity,high cell efficiency,an economical,greatly simplified and easily scalable fabrication process,and ultrahigh material utilization,the IrO_(x)electrode shows great potential to be applied in industry and accelerates the commercialization of PEMECs and renewable energy evolution.
基金This work is supported by the National Natural Science Foundation of China under Grant 52274057,52074340 and 51874335the Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-008+2 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSNthe Science and Technology Support Plan for Youth Innovation of University in Shandong Province under Grant 2019KJH002111 Project under Grant B08028.
文摘Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing research suggests that the effectiveness of a surrogate model can vary depending on the complexity of the design problem.A surrogate model that has demonstrated success in one scenario may not perform as well in others.In the absence of prior knowledge,finding a promising surrogate model that performs well for an unknown reservoir is challenging.Moreover,the optimization process often relies on a single evolutionary algorithm,which can yield varying results across different cases.To address these limitations,this paper introduces a novel approach called the multi-surrogate framework with an adaptive selection mechanism(MSFASM)to tackle production optimization problems.MSFASM consists of two stages.In the first stage,a reduced-dimensional broad learning system(BLS)is used to adaptively select the evolutionary algorithm with the best performance during the current optimization period.In the second stage,the multi-objective algorithm,non-dominated sorting genetic algorithm II(NSGA-II),is used as an optimizer to find a set of Pareto solutions with good performance on multiple surrogate models.A novel optimal point criterion is utilized in this stage to select the Pareto solutions,thereby obtaining the desired development schemes without increasing the computational load of the numerical simulator.The two stages are combined using sequential transfer learning.From the two most important perspectives of an evolutionary algorithm and a surrogate model,the proposed method improves adaptability to optimization problems of various reservoir types.To verify the effectiveness of the proposed method,four 100-dimensional benchmark functions and two reservoir models are tested,and the results are compared with those obtained by six other surrogate-model-based methods.The results demonstrate that our approach can obtain the maximum net present value(NPV)of the target production optimization problems.
基金financially supported by grants from the National Natural Science Foundation of China (82170873,81871095)the National Natural Science Foundation of China (81974503)the Tsinghua University Spring Breeze Fund (20211080005)。
文摘Maillard reaction(MR)is a non-enzymatic browning reaction commonly seen in food processing,which occurs between reducing sugars and compounds with amino groups.Despite certain advantages based on Maillard reaction products(MRPs)found in some food for health and storage application have appeared,however,the MR occurring in human physiological environment can produce advanced glycation end products(AGEs)by non-enzymatic modification of macromolecules such as proteins,lipids and nucleic acid,which could change the structure and functional activity of the molecules themselves.In this review,we take AGEs as our main object,on the one hand,discuss physiologic aging,that is,age-dependent covalent cross-linking and modification of proteins such as collagen that occur in eyes and skin containing connective tissue.On the other hand,pathological aging associated with autoimmune and inflammatory diseases,neurodegenerative diseases,diabetes and diabetic nephropathy,cardiovascular diseases and bone degenerative diseases have been mainly proposed.Based on the series of adverse effects of accelerated aging and disease pathologies caused by MRPs,the possible harm caused by some MR can be slowed down or inhibited by artificial drug intervention,dietary pattern and lifestyle control.It also stimulates people's curiosity to continue to explore the potential link between the MR and human aging and health,which should be paid more attention to for the development of life sciences.
基金supported by Sichuan Natural Science Foundation (Grant No. 2023NSFSC0423)CNPC Innovation Found (Grant No. 2022DQ02-0207)+2 种基金Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202201510)supported by a grant from the Human Resources Development program (No. 20216110100070) of the Korea Institute of Energy Technology Evaluation and Planning (KETEP)funded by the Ministry of Trade, Industry, and Energy of the Korean Government。
文摘Shale gas, as an environmentally friendly fossil energy resource, has gained significant commercial development and shows immense potential. However, accurately predicting shale gas production faces substantial challenges due to the complex law of decline, nonlinear and non-stationary features in production data, which greatly repair the robustness of current models in predicting shale gas production time series. To address these challenges and improve accuracy in production forecasting, this paper introduces a novel and innovative approach: a hybrid proxy model that combines the bidirectional long short-term memory(BiLSTM) neural network and random forest(RF) through deep learning. The BiLSTM neural network is adept at capturing long-term dependencies, making it suitable for understanding the intricate relationships between input and output variables in shale gas production.On the other hand, RF serves a dual purpose: reducing model variance and addressing the concept drift problem that arises in non-stationary time series predictions made by BiLSTM. By integrating these two models, the hybrid approach effectively captures the inherent dependencies present in long and nonstationary production time series, thereby reducing model uncertainty. Furthermore, the combination of BiLSTM and RF is optimized using the recently-proposed marine predators algorithm(MPA) to fine-tune hyperparameters and enhance the overall performance of the proxy model. The results demonstrate that the proposed BiLSTM-RF-MPA model achieves higher prediction accuracy and demonstrates stronger generalization capabilities by effectively handling the complex nonlinear and non-stationary characteristics of shale gas production time series. Compared to other models such as LSTM, BiLSTM, and RF, the proposed model exhibits superior fitting and prediction performance, with an average improvement in performance indicators exceeding 20%. This innovative framework provides valuable insights for forecasting the complex production performance of unconventional oil and gas reservoirs, which sheds light on the development of data-driven proxy models in the field of subsurface energy utilization.
基金This work is supported by the National Natural Science Foundation of China under Grant 52274057,52074340 and 51874335the Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-008+2 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSNthe Science and Technology Support Plan for Youth Innovation of University in Shandong Province under Grant 2019KJH002111 Project under Grant B08028.
文摘To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the process.The development history of other reservoirs in the same class tends to be studied to make predictions accurate.However,the permeability field,well patterns,and development regime must all be similar for two reservoirs to be considered in the same class.This results in very few available experiences from other reservoirs even though there is a lot of historical information on numerous reservoirs because it is difficult to find such similar reservoirs.This paper proposes a learn-to-learn method,which can better utilize a vast amount of historical data from various reservoirs.Intuitively,the proposed method first learns how to learn samples before directly learning rules in samples.Technically,by utilizing gradients from networks with independent parameters and copied structure in each class of reservoirs,the proposed network obtains the optimal shared initial parameters which are regarded as transferable information across different classes.Based on that,the network is able to predict future production indices for the target reservoir by only training with very limited samples collected from reservoirs in the same class.Two cases further demonstrate its superiority in accuracy to other widely-used network methods.
文摘Soluble receptor for advanced glycation end products(sRAGE)acts as a decoy sequestering of RAGE ligands,thus preventing the activation of the ligand-RAGE axis linking human diseases.However,the molecular mechanisms underlying sRAGE remain unclear.In this study,THP-1 monocytes were cultured in normal glucose(NG,5.5 mmol/L)and high glucose(HG,15 mmol/L)to investigate the effects of diabetesrelevant glucose concentrations on sRAGE and interleukin-1β(IL-1β)secretion.The modulatory effects of epigallocatechin gallate(EGCG)in response to HG challenge were also evaluated.HG enhanced intracellular reactive oxygen species(ROS)generation and RAGE expression.The secretion of sRAGE,including esRAGE and cRAGE,was reduced under HG conditions,together with the downregulation of a disintegrin and metallopeptidase 10(ADAM10)and nuclear factor erythroid 2-related factor 2(Nrf2)nuclear translocation.Mechanistically,the HG effects were counteracted by siRAGE and exacerbated by siNrf2.Chromatin immunoprecipitation results showed that Nrf2 binding to the ADAM10 promoter and HG interfered with this binding.Our data reinforce the notion that RAGE and Nrf2 might be sRAGE-regulating factors.Under HG conditions,the treatment of EGCG reduced ROS generation and RAGE activation.EGCG-stimulated cRAGE release was likely caused by the upregulation of the Nrf2-ADAM10 pathway.EGCG inhibited HG-mediated NLRP3 inflammasome activation at least partly by stimulating sRAGE,thereby reducing IL-1βrelease.
基金supported by the 2022 National Natural Science Foundation of China(No.62277002)the National Key Research and Development Program of China(2022YFC3303500).
文摘The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61877054,12031004,and 12271474).
文摘We establish the Stinespring dilation theorem of the link product of quantum channels in two different ways,discuss the discrimination of quantum channels,and show that the distinguishability can be improved by self-linking each quantum channel n times as n grows.We also find that the maximum value of Uhlmann's theorem can be achieved for diagonal channels.
基金supported by the National Key Research and Development Program of China (No.2022YFC2806102)the National Natural Science Foundation of China (No.52171287,52325107)+3 种基金High-tech Ship Research Project of Ministry of Industry and Information Technology (No.2023GXB01-05-004-03,No.GXBZH2022-293)the Science Foundation for Distinguished Young Scholars of Shandong Province (No.ZR2022JQ25)the Taishan Scholars Project (No.tsqn201909063)the Fundamental Research Funds for the Central Universities (No.24CX10006A)。
文摘The subsea production system is a vital equipment for offshore oil and gas production.The control system is one of the most important parts of it.Collecting and processing the signals of subsea sensors is the only way to judge whether the subsea production control system is normal.However,subsea sensors degrade rapidly due to harsh working environments and long service time.This leads to frequent false alarm incidents.A combinatorial reasoning-based abnormal sensor recognition method for subsea production control system is proposed.A combinatorial algorithm is proposed to group sensors.The long short-term memory network(LSTM)is used to establish a single inference model.A counting-based judging method is proposed to identify abnormal sensors.Field data from an offshore platform in the South China Sea is used to demonstrate the effect of the proposed method.The results show that the proposed method can identify the abnormal sensors effectively.
基金supported by the Scientific Research Fund of Hunan Provincial Education Department(21B0070)the Natural Science Foundation of Jiangsu Province(BK20231452)+1 种基金the Fundamental Research Funds for the Central Universities(30922010809)the National Natural Science Foundation of China(11801591,11971195,12071171,12171107,12201207,12371072)。
文摘For each real number x∈(0,1),let[a_(1)(x),a_(2)(x),…,a_n(x),…]denote its continued fraction expansion.We study the convergence exponent defined byτ(x)=inf{s≥0:∞∑n=1(a_(n)(x)a_(n+1)(x))^(-s)<∞},which reflects the growth rate of the product of two consecutive partial quotients.As a main result,the Hausdorff dimensions of the level sets ofτ(x)are determined.
