This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to use...This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.展开更多
Water content, whether as free or lattice-bound water, is a crucial factor in determining the Earth's internal thermal state and plays a key role in volcanic eruptions, melting phenomena, and mantle convection rat...Water content, whether as free or lattice-bound water, is a crucial factor in determining the Earth's internal thermal state and plays a key role in volcanic eruptions, melting phenomena, and mantle convection rates. As electrical conductivity in the Earth's interior is highly sensitive to water content, it is an important geophysical parameter for understanding the deep Earth water content. Since its launch on May 21, 2023, the MSS-1(Macao Science Satellite-1) mission has operated for nearly one year, with its magnetometer achieving a precision of higher than 0.5 nT after orbital testing and calibration. Orbiting at 450 kilometers with a unique 41-degree inclination, the satellite enables high-density observations across multiple local times, allowing detailed monitoring of low-latitude regions and enhancing data for global conductivity imaging. To better understand the global distribution of water within the Earth's interior, it is crucial to study internal conductivity structure and water content distribution. To this aim, we introduce a method for using MSS-1 data to estamate induced magnetic fields related to magnetospheric currents. We then develop a trans-dimensional Bayesian approach to reveal Earth's internal conductivity, providing probable conductivity structure with an uncertainty analysis. Finally, by integrating known mineral composition, pressure, and temperature distribution within the mantle, we estimate the water content range in the mantle transition zone, concluding that this region may contain the equivalent of up to 3.0 oceans of water, providing compelling evidence that supports the hypothesis of a deep water cycle within the Earth's interior.展开更多
Rice is a poor source of folate,an essential micronutrient for the body.Biofortification offers an effective way to enhance the folate content of rice and alleviate folate deficiencies in humans.In this study,we confi...Rice is a poor source of folate,an essential micronutrient for the body.Biofortification offers an effective way to enhance the folate content of rice and alleviate folate deficiencies in humans.In this study,we confirmed that OsADCS and OsGTPCHI,encoding the initial enzymes necessary for folate synthesis,positively regulate folate accumulation in knockout mutants of both japonica and indica rice backgrounds.The folate content in the low-folate japonica variety was slightly increased by the expression of the indica alleles driven by the endosperm-specific promoter.We further obtained co-expression lines by stacking OsADCS and OsGTPCHI genes;the folate accumulation in brown rice and polished rice reached 5.65μg/g and 2.95μg/g,respectively,representing 37.9-fold and 26.5-fold increases compared with the wild type.Transcriptomic analysis of rice grains from six transgenic lines showed that folate changes affected biological pathways involved in the synthesis and metabolism of rice seed storage substances,while the expression of other folate synthesis genes was weakly regulated.In addition,we identified Aus rice as a high-folate germplasm carrying superior haplotypes of OsADCS and OsGTPCHI through natural variation.This study provides an alternative and effective complementary strategy for rice biofortification,promoting the rational combination of metabolic engineering and conventional breeding to breed high-folate varieties.展开更多
The heat content(HC)of water masses on the Ross Sea continental shelf plays an important role in regulating the circulations and the basal melting of the Ross Ice Shelf(RIS).Yet,the evolution of the HC on the Ross Sea...The heat content(HC)of water masses on the Ross Sea continental shelf plays an important role in regulating the circulations and the basal melting of the Ross Ice Shelf(RIS).Yet,the evolution of the HC on the Ross Sea continental shelf is still not clear due to the sparsity of observations.By employing a coupled regional ocean-sea ice-ice shelf model for the Ross Sea,this study analyzes the heat budget of water masses over the continental shelf and in the RIS cavity.According to the topographic features and the HC density,the continental shelf region is divided into 17 subdomains.The heat budget of the middle layer for every subdomain is analyzed.In addition,the heat budget for the RIS cavity is assessed for the first time.Owing to Modified Circumpolar Deep Water intrusion,water masses over the eastern shelf are warmer than over the western shelf,with the coldest water identified in the southwestern inner shelf.The horizontal heat flux mainly provides heat to the continental shelf,while the atmospheric forcing tends to warm up the ocean during the ice-melting period and cool down the ocean during the ice-freezing period.The vertical heat flux is generally upward and transports heat from the deep layer to the upper layer.In the RIS cavity,the seasonal cycle of the HC is dominated by the horizontal flux across the RIS front rather than the basal thermal forcing of the RIS.展开更多
With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process...With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process industry.This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry,including the frameworks,core applications,and future prospects.First,this paper proposes a framework for foundation models for the process industry.Second,it summarizes the key capabilities of industrial foundation models and their practical applications.Finally,it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.展开更多
The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.Howev...The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content.展开更多
Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the...Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the integrity of gas content within samples and are often constrained by estimation errors inherent in empirical formulas,which results in inaccurate gas content measurements.This study introduces a lightweight,in-situ pressure-and gas-preserved corer designed to collect coal samples under the pressure conditions at the sampling point,effectively preventing gas loss during transfer and significantly improving measurement accuracy.Additionally,a gas migration model for deep coal mines was developed to elucidate gas migration characteristics under pressure-preserved coring conditions.The model offers valuable insights for optimizing coring parameters,demonstrating that both minimizing the coring hole diameter and reducing the pressure difference between the coring-point pressure and the original pore pressure can effectively improve the precision of gas content measurements.Coring tests conducted at an experimental base validated the performance of the corer and its effectiveness in sample collection.Furthermore,successful horizontal coring tests conducted in an underground coal mine roadway demonstrated that the measured gas content using pressure-preserved coring was 34%higher than that obtained through open sampling methods.展开更多
CLIL,which stands for Content and Language Integrated Learning,is an instructional approach that gives ample curricular and pedagogical attention to content and language outcomes in multilingual educational settings.I...CLIL,which stands for Content and Language Integrated Learning,is an instructional approach that gives ample curricular and pedagogical attention to content and language outcomes in multilingual educational settings.Increasingly,it is heralded as a way to responsibly enact top-down English-Medium-of-Instruction(EMI)policies at the university level,where teachers and students are tasked with developing their English proficiency while remaining competitive in the international job market.However,teachers and teacher educators hoping to implement this approach in their science,technology,engineering and mathematics(STEM)content courses face significant challenges.This article serves as an introduction to a vip-edited special issue that reports on several aspects related to a project of international collaboration called Project SCILLA,an acronym for“STEM Content Integrated with Language-Learning Activities”.We first provide a brief overview of the project,which was developed and carried out in collaboration between Michigan State University and a consortium of 10 rural universities in Kazakhstan as a way to support STEM educators who wish to adapt their teaching practices to Kazakhstan’s Ministry of Education.We then offer an overview of the six articles that comprise the special issue,and call for deliberate and dialogic international collaboration as a way to support teachers responding to language policy demands.展开更多
Nitrogen(N)uptake is regulated by water availability,and a water deficit can limit crop N responses by reducing N uptake and utilization.The complex and multifaceted interplay between water availability and the crop N...Nitrogen(N)uptake is regulated by water availability,and a water deficit can limit crop N responses by reducing N uptake and utilization.The complex and multifaceted interplay between water availability and the crop N response makes it difficult to predict and quantify the effect of water deficit on crop N status.The nitrogen nutrition index(NNI)has been widely used to accurately diagnose crop N status and to evaluate the effectiveness of N application.The decline of NNI under water-limiting conditions has been documented,although the underlying mechanism governing this decline is not fully understood.This study aimed to elucidate the reason for the decline of NNI under waterlimiting conditions and to provide insights into the accurate utilization of NNI for assessing crop N status under different water-N interaction treatments.Rainout shelter experiments were conducted over three growing seasons from 2018 to 2021 under different N(75 and 225 kg N ha^(-1),low N and high N)and water(120 to 510 mm,W0 to W3)co-limitation treatments.Plant N accumulation,shoot biomass(SB),plant N concentration(%N),soil nitrate-N content,actual evapotranspiration(ET_a),and yield were recorded at the stem elongation,booting,anthesis and grain filling stages.Compared to W0,W1 to W3 treatments exhibited NNI values that were greater by 10.2 to 20.5%,12.6to 24.8%,14 to 24.8%,and 16.8 to 24.8%at stem elongation,booting,anthesis,and grain filling,respectively,across the 2018-2021 seasons.This decline in NNI under water-limiting conditions stemmed from two main factors.First,reduced ET_(a) and SB led to a greater critical N concentration(%N_(c))under water-limiting conditions,which contributed to the decline in NNI primarily under high N conditions.Second,changes in plant%N played a more significant role under low N conditions.Plant N accumulation exhibited a positive allometric relationship with SB and a negative relationship with soil nitrate-N content under water-limiting conditions,indicating co-regulation by SB and the soil nitrate-N content.However,this regulation was influenced by water availability.Plant N accumulation sourced from the soil nitrate-N content reflects soil N availability.Greater soil water availability facilitated greater absorption of soil nitrate-N into the plants,leading to a positive correlation between plant N accumulation and ET_(a)across the different water-N interaction treatments.Therefore,considering the impact of soil water availability is crucial when assessing soil N availability under water-limiting conditions.The findings of this study provide valuable insights into the factors contributing to the decline in NNI among different water-N interaction treatments and can contribute to the more accurate utilization of NNI for assessing winter wheat N status.展开更多
Carbon can change the phase components of low-density steels and influence the mechanical properties.In this study,a new method to control the carbon content and avoid the formation ofδ-ferrite by decarburization tre...Carbon can change the phase components of low-density steels and influence the mechanical properties.In this study,a new method to control the carbon content and avoid the formation ofδ-ferrite by decarburization treatment was proposed.The microstructural changes and mechanical characteristics with carbon content induced by decarburization were systematically examined.Crussard-Jaoul(C-J)analysis was employed to examine the work hardening characteristics during the tensile test.During decarburization by heat treatments,the carbon content within the austenite phase decreased,while Mn and Al were almost unchanged;this made the steel with full austenite transform into the austenite and ferrite dual phase.Meanwhile,(Ti,V)C carbides existed in both matrix phase and the mole fraction almost the same.In addition,the formation of other carbides restrained.Carbon loss induced a decrease in strength due to the weakening of the carbon solid solution.For the steel with the single austinite,the deformation mode of austenite was the dislocation planar glide,resulting in the formation of microbands.For the dual-phase steel,the deformation occurred by the dislocation planar glide of austenite first,with the increase in strain,the cross slip of ferrite took place,forming dislocation cells in ferrite.At the late stage of deformation,the work hardening of austinite increased rapidly,while that of ferrite increased slightly.展开更多
In order to achieve the large-scale application of manufactured sand in railway high-strength concrete structure,a series of high-strength manufactured sand concrete(HMC)are prepared by taking the manufactured sand li...In order to achieve the large-scale application of manufactured sand in railway high-strength concrete structure,a series of high-strength manufactured sand concrete(HMC)are prepared by taking the manufactured sand lithology(tuff,limestone,basalt,granite),stone powder content(0,5%,10%,15%)and concrete strength grade(C60,C80,C100)as variables.The evolution of mechanical properties of HMC and the correlation between cubic compressive strength and other mechanical properties are studied.Compared to river sand,manufactured sand enhances the cubic compressive strength,axial compressive strength and elastic modulus of concrete,while its potential microcracks weaken the flexural strength and splitting tensile strength of concrete.Stone powder content displays both positive and negative effects on mechanical properties of HMC,and the stone powder content is suggested to be less than 10%.The empirical formulas between cubic compressive strength and other mechanical properties are proposed.展开更多
This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain an...This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical content.The participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security weaknesses.This multi faceted exploration led to an indepth evaluation of the model’s performance and security.Notably,the correlation between accuracy,detection rate,and error rate was scrutinized.This analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance variability.The study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical applications.Applying blockchain to generative AI-created medical content addresses key personal information protection issues.By utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical images.This approach not only enhances security but also enables transparent and tamperproof record-keeping.Additionally,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient privacy.In conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient privacy.The proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content management.Further research and advancements in this area will undoubtedly contribute to the development of robust and privacy-preserving healthcare systems,and visual diagnostic systems.展开更多
Zirconium alloy cladding materials inevitably undergo hydrogen absorption in the processing and operation process of the reactor,and its static and dynamic mechanical properties are closely related to the hydrogen con...Zirconium alloy cladding materials inevitably undergo hydrogen absorption in the processing and operation process of the reactor,and its static and dynamic mechanical properties are closely related to the hydrogen content.Samples with hydrogen content ranging from 23μg/g to 132μg/g were obtained using the method of gas-phase hydrogen charging,and the influence of hydrogen content on static/dynamic mechanical properties of Zr-Sn-Nb-Fe alloy was studied.The results show that the effect of weak hydrogen charging on the ultimate tensile strength,yield strength,and elongation of zirconium alloy is not obvious.There are a large number of dimples on the fracture surface of the tensile sample before and after hydrogen charging,which is a typical ductile fracture.However,the impact toughness of Zr-Sn-Nb-Fe alloy decreases significantly after trace hydrogen charging.The impact sample without hydrogen charging shows the mixed fracture mechanism of ductile fracture and microcleavage fracture.The increase in hydrogen permeability leads to the emergence of hydride,and the deformation of high strain rate under the impact loading condition leads to secondary cracks in the microstructure.The initiation and expansion of the secondary cracks is the main reason for the reduction of the impact toughness.展开更多
Aseries of [(Fe_(0.6)Co_(0.2)Ni_(0.2))_(0.75-0.03x)B_(0.2)Si_(0.05+0.03x)]_(96)Nb_(4) amorphous alloy composite coatings were prepared by adjusting the silicon content(x=0,1,2,3,4,5,and 6)and their microstructures and...Aseries of [(Fe_(0.6)Co_(0.2)Ni_(0.2))_(0.75-0.03x)B_(0.2)Si_(0.05+0.03x)]_(96)Nb_(4) amorphous alloy composite coatings were prepared by adjusting the silicon content(x=0,1,2,3,4,5,and 6)and their microstructures and tribological properties were investigated by laser cladding technique.Additionally,the effect of Si on the glass forming ability(GFA)of the layers was understood.Results show that an appropriate Si content can refine the microstructure of the FeCoNiBSiNb laser cladding layers and improve the mechanical and tribological properties.The hardness of the coating layer increases monotonically with the Si content.At the Si content of 4.8at%(x=0),the coating layer exhibits a relatively low hardness(734.2HV 0.1).Conversely,at the silicon content of 13.44at%(x=3),the coating layer exhibits the highest hardness(1106HV 0.1).The non-crystalline content and tensile strength exhibit an initial increase,followed by a subsequent decrease.At x=2,the coating exhibits its maximum fracture strength(2880 MPa).However,when x>2,the fracture strength of the coating decreases with an increase in x.Conversely,with an increase in Si content,the wear volume loss initially decreases and then increases.At a Si content of 10.56at%(x=2),the coating exhibits the highest non-crystalline content(42%),the highest tensile strength(2880 MPa),and the most favorable dry friction performance.展开更多
Cyber-physical systems(CPS)represent a sophisticated integration of computational and physical components that power critical applications such as smart manufacturing,healthcare,and autonomous infrastructure.However,t...Cyber-physical systems(CPS)represent a sophisticated integration of computational and physical components that power critical applications such as smart manufacturing,healthcare,and autonomous infrastructure.However,their extensive reliance on internet connectivity makes them increasingly susceptible to cyber threats,potentially leading to operational failures and data breaches.Furthermore,CPS faces significant threats related to unauthorized access,improper management,and tampering of the content it generates.In this paper,we propose an intrusion detection system(IDS)optimized for CPS environments using a hybrid approach by combining a natureinspired feature selection scheme,such as Grey Wolf Optimization(GWO),in connection with the emerging Light Gradient Boosting Machine(LightGBM)classifier,named as GWO-LightGBM.While gradient boosting methods have been explored in prior IDS research,our novelty lies in proposing a hybrid approach targeting CPS-specific operational constraints,such as low-latency response and accurate detection of rare and critical attack types.We evaluate GWO-LightGBM against GWO-XGBoost,GWO-CatBoost,and an artificial neural network(ANN)baseline using the NSL-KDD and CIC-IDS-2017 benchmark datasets.The proposed models are assessed across multiple metrics,including accuracy,precision,recall,and F1-score,with an emphasis on class-wise performance and training efficiency.The proposed GWO-LightGBM model achieves the highest overall accuracy(99.73%)for NSL-KDD and(99.61%)for CIC-IDS-2017,demonstrating superior performance in detecting minority classes such as Remote-to-Local(R2L)and Other attacks—commonly overlooked by other classifiers.Moreover,the proposed model consumes lower training time,highlighting its practical feasibility and scalability for real-time CPS deployment.展开更多
Plant root systems serve as a natural reinforcing material,significantly improving soil stability.Furthermore,the tensile strength of soil is crucial in mitigating the formation of cracks.Consequently,this study aims ...Plant root systems serve as a natural reinforcing material,significantly improving soil stability.Furthermore,the tensile strength of soil is crucial in mitigating the formation of cracks.Consequently,this study aims to investigate the influence of plant roots on the tensile strength of soil.For this investigation,Amorpha fruticose was selected due to its large root diameter and the ease of root extraction.Indoor tensile tests were conducted on individual roots and root-soil complexes under three varying factors.The results indicate a power law relationship between root diameter and tensile strength.Increased root content and dry density notably enhance the tensile strength of the root-soil complex while roots mitigate damage associated with soil brittleness.When root content increases from 0 to 10,the maximum enhancement in tensile strength of the root-soil complex reaches 42.3 kPa.The tensile strength of the root-soil complex at a dry density of 1.7 g/cm^(3)is four to five times greater than that of the complex at a dry density of 1.4 g/cm^(3).Moreover,as moisture content increases,the tensile strength of the root-soil complex initially rises before declining,with an increase range of 7.7-35.8 kPa.These findings provide a scientific basis for understanding the role of vegetation roots in soil tensile strength and for guiding slope reinforcement strategies.展开更多
The phase composition and microstructure of alkaline vanadium slag were characterized using scanning electron microscopy and energy-dispersive X-ray spectroscopy(SEM-EDS)and X-ray diffraction(XRD).A crystallization mo...The phase composition and microstructure of alkaline vanadium slag were characterized using scanning electron microscopy and energy-dispersive X-ray spectroscopy(SEM-EDS)and X-ray diffraction(XRD).A crystallization model of spinel was established to calculate the effects of basicity(the mass ratio of CaO to SiO_(2))and P_(2)O_(5) on crystal growth rates and precipitation patterns.Based on the crystal size distribution(CSD)theory,the size distribution and growth mechanisms of spinel crystals in alkaline vanadium slag at different temperatures were investigated.The results revealed that,at a cooling rate of 5 K/min,the mean grain size of spinel increased from 12.77 to 21.52μm as the temperature decreased from 1748 to 1598 K,with spinel growth being controlled by the interface.At 1548 K,the spinel particle size reached 31.04μm,indicating a supply-controlled growth mechanism as the temperature decreased from 1598 to 1548 K.Increased P_(2)O_(5) content hindered the crystal growth,while an increase in basicity promoted nucleation and growth.Furthermore,MnCr_(2)O_(4) preferentially crystallized and grew in alkaline vanadium slag.展开更多
Context:In irrigated agriculture,the salt stress is a major problem due to accumulation of salt from the irrigation water in the soil layers.Objectives:The aim of this study is to determinate the effect of salinity on...Context:In irrigated agriculture,the salt stress is a major problem due to accumulation of salt from the irrigation water in the soil layers.Objectives:The aim of this study is to determinate the effect of salinity on some agromorphological traits and seed nutritional quality of three sesames(Sesamum indicum L.)varieties.Methodology:This is how four solutions of different NaCl concentrations from 0,60,120 to 240 mM were used to water sesame plants at the five-leaves stage and this for two months in completely randomized device with four repetitions.Results:The results show a negative effect of the salinity growth and yield parameters,mineral elements,ascorbic acid(to 21.4% in White cultivar,28% in Brown and 24.2% in Black cultivar from 0 to 240 mM NaCl),oil(to 22.6%in White cultivar,32% in Brown and 25.5% in Black cultivar from 0 to 240 mM NaCl)and accumulation of Na(Sodium)content(to 11.8% in White cultivar,15.3% in Brown and 12.2% in Black cultivar from 0 to 240 mM NaCl),osmolytes as proteins(to 14.5% in White cultivar,11.5% in Brown and 9.6%in Black cultivar from 0 to 240 mM NaCl)and antioxydants components.Varieties White and Brown were less affected by salinity.Conclusion:White variety exhibited higher adaptive potential under salinity stress when compared to Brown variety(rich in fiber)and closely followed by Black variety.Thus White variety could be recommended for consumer oil,minerals and proteins.As for Black variety,it could be used,as glucid and antioxydants additives in food.展开更多
In this study,compacted loess samples with varying compaction water content but identical dry density were prepared to investigate the evolution of their hydraulic conductivity and compression behavior.Additionally,en...In this study,compacted loess samples with varying compaction water content but identical dry density were prepared to investigate the evolution of their hydraulic conductivity and compression behavior.Additionally,environmental scanning electron microscopy(ESEM)and nuclear magnetic resonance(NMR)analyses were conducted to gain microstructural insights into loess behavior at the laboratory scale.The results indicate that the maximum saturated hydraulic conductivity is observed at the lowest compaction water content,particularly in the early stage of permeability tests.In particular,for loess compacted at water contents below the optimum(as determined by the modified Proctor compaction test),the hydraulic conductivity decreases throughout the permeability tests.Conversely,when the water content exceeds the optimum level,the hydraulic conductivity shows an increasing trend.In terms of compression behavior,when the as-compacted samples are loaded in oedometer conditions,an increase in material compressibility is observed with increasing compaction water content.Again,a different phenomenological behavior was observed when the compaction water content exceeded the optimum,i.e.an abrupt increase in loess compressibility.ESEM tests provide microstructural confirmation of this evidence,as the surface morphology of the compacted loess changes significantly with increasing compaction water content.The microstructural evolution was also quantified in terms of area ratio using image processing software.Finally,NMR was used to quantify the intra-and inter-aggregate water at different compaction water contents,once again highlighting a threshold for the presence or absence of inter-aggregate water similar to the optimum water content.展开更多
基金funded by the Office of the Vice-President for Research and Development of Cebu Technological University.
文摘This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.
基金financially supported by the National Natural Science Foundation of China(42250102,42250101)the Macao Foundation.
文摘Water content, whether as free or lattice-bound water, is a crucial factor in determining the Earth's internal thermal state and plays a key role in volcanic eruptions, melting phenomena, and mantle convection rates. As electrical conductivity in the Earth's interior is highly sensitive to water content, it is an important geophysical parameter for understanding the deep Earth water content. Since its launch on May 21, 2023, the MSS-1(Macao Science Satellite-1) mission has operated for nearly one year, with its magnetometer achieving a precision of higher than 0.5 nT after orbital testing and calibration. Orbiting at 450 kilometers with a unique 41-degree inclination, the satellite enables high-density observations across multiple local times, allowing detailed monitoring of low-latitude regions and enhancing data for global conductivity imaging. To better understand the global distribution of water within the Earth's interior, it is crucial to study internal conductivity structure and water content distribution. To this aim, we introduce a method for using MSS-1 data to estamate induced magnetic fields related to magnetospheric currents. We then develop a trans-dimensional Bayesian approach to reveal Earth's internal conductivity, providing probable conductivity structure with an uncertainty analysis. Finally, by integrating known mineral composition, pressure, and temperature distribution within the mantle, we estimate the water content range in the mantle transition zone, concluding that this region may contain the equivalent of up to 3.0 oceans of water, providing compelling evidence that supports the hypothesis of a deep water cycle within the Earth's interior.
基金supported by the Central Public-Interest Scientific Institution Basal Research Fund,China(Grant No.CPSIBRF-CNRRI-202403)。
文摘Rice is a poor source of folate,an essential micronutrient for the body.Biofortification offers an effective way to enhance the folate content of rice and alleviate folate deficiencies in humans.In this study,we confirmed that OsADCS and OsGTPCHI,encoding the initial enzymes necessary for folate synthesis,positively regulate folate accumulation in knockout mutants of both japonica and indica rice backgrounds.The folate content in the low-folate japonica variety was slightly increased by the expression of the indica alleles driven by the endosperm-specific promoter.We further obtained co-expression lines by stacking OsADCS and OsGTPCHI genes;the folate accumulation in brown rice and polished rice reached 5.65μg/g and 2.95μg/g,respectively,representing 37.9-fold and 26.5-fold increases compared with the wild type.Transcriptomic analysis of rice grains from six transgenic lines showed that folate changes affected biological pathways involved in the synthesis and metabolism of rice seed storage substances,while the expression of other folate synthesis genes was weakly regulated.In addition,we identified Aus rice as a high-folate germplasm carrying superior haplotypes of OsADCS and OsGTPCHI through natural variation.This study provides an alternative and effective complementary strategy for rice biofortification,promoting the rational combination of metabolic engineering and conventional breeding to breed high-folate varieties.
基金supported by the National Key R&D Program of China (Grant No. 2024YFF0506603)the Independent Research Foundation of the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (Grant Nos. SML2023SP201 and SML2021SP306)+2 种基金the Natural Science Foundation of Guangdong Province, China (Grant No. 2024A1515012717)the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (Grant Nos. 313021004, 313022009 and 313022001)the Program of Innovation 2030 on Smart Ocean, Zhejiang University
文摘The heat content(HC)of water masses on the Ross Sea continental shelf plays an important role in regulating the circulations and the basal melting of the Ross Ice Shelf(RIS).Yet,the evolution of the HC on the Ross Sea continental shelf is still not clear due to the sparsity of observations.By employing a coupled regional ocean-sea ice-ice shelf model for the Ross Sea,this study analyzes the heat budget of water masses over the continental shelf and in the RIS cavity.According to the topographic features and the HC density,the continental shelf region is divided into 17 subdomains.The heat budget of the middle layer for every subdomain is analyzed.In addition,the heat budget for the RIS cavity is assessed for the first time.Owing to Modified Circumpolar Deep Water intrusion,water masses over the eastern shelf are warmer than over the western shelf,with the coldest water identified in the southwestern inner shelf.The horizontal heat flux mainly provides heat to the continental shelf,while the atmospheric forcing tends to warm up the ocean during the ice-melting period and cool down the ocean during the ice-freezing period.The vertical heat flux is generally upward and transports heat from the deep layer to the upper layer.In the RIS cavity,the seasonal cycle of the HC is dominated by the horizontal flux across the RIS front rather than the basal thermal forcing of the RIS.
基金supported by the National Natural Science Foundation of China(62225302,623B2014,and 62173023).
文摘With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process industry.This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry,including the frameworks,core applications,and future prospects.First,this paper proposes a framework for foundation models for the process industry.Second,it summarizes the key capabilities of industrial foundation models and their practical applications.Finally,it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.
基金financially supported by the National Natural Science Foundation of China(No.52174297).
文摘The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content.
基金supported by the National Natural Science Foundation of China(Nos.51827901,42477191,and 52304033)the Fundamental Research Funds for the Central Universities(No.YJ202449)+1 种基金the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(No.SKLGME022009)the China Postdoctoral Science Foundation(No.2023M742446).
文摘Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the integrity of gas content within samples and are often constrained by estimation errors inherent in empirical formulas,which results in inaccurate gas content measurements.This study introduces a lightweight,in-situ pressure-and gas-preserved corer designed to collect coal samples under the pressure conditions at the sampling point,effectively preventing gas loss during transfer and significantly improving measurement accuracy.Additionally,a gas migration model for deep coal mines was developed to elucidate gas migration characteristics under pressure-preserved coring conditions.The model offers valuable insights for optimizing coring parameters,demonstrating that both minimizing the coring hole diameter and reducing the pressure difference between the coring-point pressure and the original pore pressure can effectively improve the precision of gas content measurements.Coring tests conducted at an experimental base validated the performance of the corer and its effectiveness in sample collection.Furthermore,successful horizontal coring tests conducted in an underground coal mine roadway demonstrated that the measured gas content using pressure-preserved coring was 34%higher than that obtained through open sampling methods.
基金funding from the U.S.-Kazakhstan University Partnerships program funded by the U.S.Mission to Kazakhstan and administered by American Councils[Award number SKZ100-19-CA-0149].
文摘CLIL,which stands for Content and Language Integrated Learning,is an instructional approach that gives ample curricular and pedagogical attention to content and language outcomes in multilingual educational settings.Increasingly,it is heralded as a way to responsibly enact top-down English-Medium-of-Instruction(EMI)policies at the university level,where teachers and students are tasked with developing their English proficiency while remaining competitive in the international job market.However,teachers and teacher educators hoping to implement this approach in their science,technology,engineering and mathematics(STEM)content courses face significant challenges.This article serves as an introduction to a vip-edited special issue that reports on several aspects related to a project of international collaboration called Project SCILLA,an acronym for“STEM Content Integrated with Language-Learning Activities”.We first provide a brief overview of the project,which was developed and carried out in collaboration between Michigan State University and a consortium of 10 rural universities in Kazakhstan as a way to support STEM educators who wish to adapt their teaching practices to Kazakhstan’s Ministry of Education.We then offer an overview of the six articles that comprise the special issue,and call for deliberate and dialogic international collaboration as a way to support teachers responding to language policy demands.
基金supported by the National Natural Science Foundation of China(51609247)the Henan Provincial Natural Science Foundation,China(222300420589,202300410553)+4 种基金the Central Public-interest Scientific Institution Basal Research Fund,China(FIRI2022-22)the Science&Technology Fundamental Resources Investigation Program,China(2022FY101601)the Science and Technology Project of Xinxiang City,Henan Province,China(GG2021024)the Major Special Science and Technology Project of Henan Province,China(221100110700)the Joint Fund of Science and Technology Research and Development Plan of Henan Province,China(Superior Discipline Cultivation)(222301420104)。
文摘Nitrogen(N)uptake is regulated by water availability,and a water deficit can limit crop N responses by reducing N uptake and utilization.The complex and multifaceted interplay between water availability and the crop N response makes it difficult to predict and quantify the effect of water deficit on crop N status.The nitrogen nutrition index(NNI)has been widely used to accurately diagnose crop N status and to evaluate the effectiveness of N application.The decline of NNI under water-limiting conditions has been documented,although the underlying mechanism governing this decline is not fully understood.This study aimed to elucidate the reason for the decline of NNI under waterlimiting conditions and to provide insights into the accurate utilization of NNI for assessing crop N status under different water-N interaction treatments.Rainout shelter experiments were conducted over three growing seasons from 2018 to 2021 under different N(75 and 225 kg N ha^(-1),low N and high N)and water(120 to 510 mm,W0 to W3)co-limitation treatments.Plant N accumulation,shoot biomass(SB),plant N concentration(%N),soil nitrate-N content,actual evapotranspiration(ET_a),and yield were recorded at the stem elongation,booting,anthesis and grain filling stages.Compared to W0,W1 to W3 treatments exhibited NNI values that were greater by 10.2 to 20.5%,12.6to 24.8%,14 to 24.8%,and 16.8 to 24.8%at stem elongation,booting,anthesis,and grain filling,respectively,across the 2018-2021 seasons.This decline in NNI under water-limiting conditions stemmed from two main factors.First,reduced ET_(a) and SB led to a greater critical N concentration(%N_(c))under water-limiting conditions,which contributed to the decline in NNI primarily under high N conditions.Second,changes in plant%N played a more significant role under low N conditions.Plant N accumulation exhibited a positive allometric relationship with SB and a negative relationship with soil nitrate-N content under water-limiting conditions,indicating co-regulation by SB and the soil nitrate-N content.However,this regulation was influenced by water availability.Plant N accumulation sourced from the soil nitrate-N content reflects soil N availability.Greater soil water availability facilitated greater absorption of soil nitrate-N into the plants,leading to a positive correlation between plant N accumulation and ET_(a)across the different water-N interaction treatments.Therefore,considering the impact of soil water availability is crucial when assessing soil N availability under water-limiting conditions.The findings of this study provide valuable insights into the factors contributing to the decline in NNI among different water-N interaction treatments and can contribute to the more accurate utilization of NNI for assessing winter wheat N status.
基金financially supported by the National Natural Science Foundation of China(Nos.U2141207,52171111,and 52001083)the Youth Talent Project of China National Nuclear Corporation(No.CNNC2021Y-TEPHEU01)+3 种基金the China Postdoctoral Science Foundation(No.2020M681077)the Natural Science Foundation of Heilongjiang,China(No.LH2019E030)the Heilongjiang Postdoctoral Science Foundation,China(No.LBH-Z19125)he Heilongjiang Touyan Innovation Team Program,China,and the Natural Science Foundation of Heilongjiang(No.LH2020E060)。
文摘Carbon can change the phase components of low-density steels and influence the mechanical properties.In this study,a new method to control the carbon content and avoid the formation ofδ-ferrite by decarburization treatment was proposed.The microstructural changes and mechanical characteristics with carbon content induced by decarburization were systematically examined.Crussard-Jaoul(C-J)analysis was employed to examine the work hardening characteristics during the tensile test.During decarburization by heat treatments,the carbon content within the austenite phase decreased,while Mn and Al were almost unchanged;this made the steel with full austenite transform into the austenite and ferrite dual phase.Meanwhile,(Ti,V)C carbides existed in both matrix phase and the mole fraction almost the same.In addition,the formation of other carbides restrained.Carbon loss induced a decrease in strength due to the weakening of the carbon solid solution.For the steel with the single austinite,the deformation mode of austenite was the dislocation planar glide,resulting in the formation of microbands.For the dual-phase steel,the deformation occurred by the dislocation planar glide of austenite first,with the increase in strain,the cross slip of ferrite took place,forming dislocation cells in ferrite.At the late stage of deformation,the work hardening of austinite increased rapidly,while that of ferrite increased slightly.
基金Funded by the National Natural Science Foundation of China(Nos.U1934206,52108260)China Academy of Railway Sciences Fund(No.2021YJ078)+1 种基金Railway Engineering Construction Standard Project(No.2023-BZWW-006)New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘In order to achieve the large-scale application of manufactured sand in railway high-strength concrete structure,a series of high-strength manufactured sand concrete(HMC)are prepared by taking the manufactured sand lithology(tuff,limestone,basalt,granite),stone powder content(0,5%,10%,15%)and concrete strength grade(C60,C80,C100)as variables.The evolution of mechanical properties of HMC and the correlation between cubic compressive strength and other mechanical properties are studied.Compared to river sand,manufactured sand enhances the cubic compressive strength,axial compressive strength and elastic modulus of concrete,while its potential microcracks weaken the flexural strength and splitting tensile strength of concrete.Stone powder content displays both positive and negative effects on mechanical properties of HMC,and the stone powder content is suggested to be less than 10%.The empirical formulas between cubic compressive strength and other mechanical properties are proposed.
文摘This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical content.The participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security weaknesses.This multi faceted exploration led to an indepth evaluation of the model’s performance and security.Notably,the correlation between accuracy,detection rate,and error rate was scrutinized.This analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance variability.The study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical applications.Applying blockchain to generative AI-created medical content addresses key personal information protection issues.By utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical images.This approach not only enhances security but also enables transparent and tamperproof record-keeping.Additionally,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient privacy.In conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient privacy.The proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content management.Further research and advancements in this area will undoubtedly contribute to the development of robust and privacy-preserving healthcare systems,and visual diagnostic systems.
文摘Zirconium alloy cladding materials inevitably undergo hydrogen absorption in the processing and operation process of the reactor,and its static and dynamic mechanical properties are closely related to the hydrogen content.Samples with hydrogen content ranging from 23μg/g to 132μg/g were obtained using the method of gas-phase hydrogen charging,and the influence of hydrogen content on static/dynamic mechanical properties of Zr-Sn-Nb-Fe alloy was studied.The results show that the effect of weak hydrogen charging on the ultimate tensile strength,yield strength,and elongation of zirconium alloy is not obvious.There are a large number of dimples on the fracture surface of the tensile sample before and after hydrogen charging,which is a typical ductile fracture.However,the impact toughness of Zr-Sn-Nb-Fe alloy decreases significantly after trace hydrogen charging.The impact sample without hydrogen charging shows the mixed fracture mechanism of ductile fracture and microcleavage fracture.The increase in hydrogen permeability leads to the emergence of hydride,and the deformation of high strain rate under the impact loading condition leads to secondary cracks in the microstructure.The initiation and expansion of the secondary cracks is the main reason for the reduction of the impact toughness.
文摘Aseries of [(Fe_(0.6)Co_(0.2)Ni_(0.2))_(0.75-0.03x)B_(0.2)Si_(0.05+0.03x)]_(96)Nb_(4) amorphous alloy composite coatings were prepared by adjusting the silicon content(x=0,1,2,3,4,5,and 6)and their microstructures and tribological properties were investigated by laser cladding technique.Additionally,the effect of Si on the glass forming ability(GFA)of the layers was understood.Results show that an appropriate Si content can refine the microstructure of the FeCoNiBSiNb laser cladding layers and improve the mechanical and tribological properties.The hardness of the coating layer increases monotonically with the Si content.At the Si content of 4.8at%(x=0),the coating layer exhibits a relatively low hardness(734.2HV 0.1).Conversely,at the silicon content of 13.44at%(x=3),the coating layer exhibits the highest hardness(1106HV 0.1).The non-crystalline content and tensile strength exhibit an initial increase,followed by a subsequent decrease.At x=2,the coating exhibits its maximum fracture strength(2880 MPa).However,when x>2,the fracture strength of the coating decreases with an increase in x.Conversely,with an increase in Si content,the wear volume loss initially decreases and then increases.At a Si content of 10.56at%(x=2),the coating exhibits the highest non-crystalline content(42%),the highest tensile strength(2880 MPa),and the most favorable dry friction performance.
基金supported by Culture,Sports and Tourism R&D Program through the Korea Creative Content Agency grant funded by the Ministry of Culture,Sports and Tourism in 2024(Project Name:Global Talent Training Program for Copyright Management Technology in Game Contents,Project Number:RS-2024-00396709,Contribution Rate:100%).
文摘Cyber-physical systems(CPS)represent a sophisticated integration of computational and physical components that power critical applications such as smart manufacturing,healthcare,and autonomous infrastructure.However,their extensive reliance on internet connectivity makes them increasingly susceptible to cyber threats,potentially leading to operational failures and data breaches.Furthermore,CPS faces significant threats related to unauthorized access,improper management,and tampering of the content it generates.In this paper,we propose an intrusion detection system(IDS)optimized for CPS environments using a hybrid approach by combining a natureinspired feature selection scheme,such as Grey Wolf Optimization(GWO),in connection with the emerging Light Gradient Boosting Machine(LightGBM)classifier,named as GWO-LightGBM.While gradient boosting methods have been explored in prior IDS research,our novelty lies in proposing a hybrid approach targeting CPS-specific operational constraints,such as low-latency response and accurate detection of rare and critical attack types.We evaluate GWO-LightGBM against GWO-XGBoost,GWO-CatBoost,and an artificial neural network(ANN)baseline using the NSL-KDD and CIC-IDS-2017 benchmark datasets.The proposed models are assessed across multiple metrics,including accuracy,precision,recall,and F1-score,with an emphasis on class-wise performance and training efficiency.The proposed GWO-LightGBM model achieves the highest overall accuracy(99.73%)for NSL-KDD and(99.61%)for CIC-IDS-2017,demonstrating superior performance in detecting minority classes such as Remote-to-Local(R2L)and Other attacks—commonly overlooked by other classifiers.Moreover,the proposed model consumes lower training time,highlighting its practical feasibility and scalability for real-time CPS deployment.
基金The authors would like to acknowledge financial support from the Joint Funds of the National Nature Science Foundation of China(No.U22A20232)Supported by Open Project Funding of Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes,Ministry of Education(HGKFZ07)+2 种基金the National Natural Science Foundation of China(No.51978249)Innovation Research Team Project of the Hubei Provincial Department of Science and Technology(JCZRQT202500027)the International Collaborative Research Fund for Young Scholars in the Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes.
文摘Plant root systems serve as a natural reinforcing material,significantly improving soil stability.Furthermore,the tensile strength of soil is crucial in mitigating the formation of cracks.Consequently,this study aims to investigate the influence of plant roots on the tensile strength of soil.For this investigation,Amorpha fruticose was selected due to its large root diameter and the ease of root extraction.Indoor tensile tests were conducted on individual roots and root-soil complexes under three varying factors.The results indicate a power law relationship between root diameter and tensile strength.Increased root content and dry density notably enhance the tensile strength of the root-soil complex while roots mitigate damage associated with soil brittleness.When root content increases from 0 to 10,the maximum enhancement in tensile strength of the root-soil complex reaches 42.3 kPa.The tensile strength of the root-soil complex at a dry density of 1.7 g/cm^(3)is four to five times greater than that of the complex at a dry density of 1.4 g/cm^(3).Moreover,as moisture content increases,the tensile strength of the root-soil complex initially rises before declining,with an increase range of 7.7-35.8 kPa.These findings provide a scientific basis for understanding the role of vegetation roots in soil tensile strength and for guiding slope reinforcement strategies.
基金supported by the National Natural Science Foundation of China(No.51974047)the Natural Science Foundation of Chongqing,China(No.cstc2022ycjh-bgzxm0003)the Large Instrument Foundation of Chongqing University,China(No.202303150239)。
文摘The phase composition and microstructure of alkaline vanadium slag were characterized using scanning electron microscopy and energy-dispersive X-ray spectroscopy(SEM-EDS)and X-ray diffraction(XRD).A crystallization model of spinel was established to calculate the effects of basicity(the mass ratio of CaO to SiO_(2))and P_(2)O_(5) on crystal growth rates and precipitation patterns.Based on the crystal size distribution(CSD)theory,the size distribution and growth mechanisms of spinel crystals in alkaline vanadium slag at different temperatures were investigated.The results revealed that,at a cooling rate of 5 K/min,the mean grain size of spinel increased from 12.77 to 21.52μm as the temperature decreased from 1748 to 1598 K,with spinel growth being controlled by the interface.At 1548 K,the spinel particle size reached 31.04μm,indicating a supply-controlled growth mechanism as the temperature decreased from 1598 to 1548 K.Increased P_(2)O_(5) content hindered the crystal growth,while an increase in basicity promoted nucleation and growth.Furthermore,MnCr_(2)O_(4) preferentially crystallized and grew in alkaline vanadium slag.
文摘Context:In irrigated agriculture,the salt stress is a major problem due to accumulation of salt from the irrigation water in the soil layers.Objectives:The aim of this study is to determinate the effect of salinity on some agromorphological traits and seed nutritional quality of three sesames(Sesamum indicum L.)varieties.Methodology:This is how four solutions of different NaCl concentrations from 0,60,120 to 240 mM were used to water sesame plants at the five-leaves stage and this for two months in completely randomized device with four repetitions.Results:The results show a negative effect of the salinity growth and yield parameters,mineral elements,ascorbic acid(to 21.4% in White cultivar,28% in Brown and 24.2% in Black cultivar from 0 to 240 mM NaCl),oil(to 22.6%in White cultivar,32% in Brown and 25.5% in Black cultivar from 0 to 240 mM NaCl)and accumulation of Na(Sodium)content(to 11.8% in White cultivar,15.3% in Brown and 12.2% in Black cultivar from 0 to 240 mM NaCl),osmolytes as proteins(to 14.5% in White cultivar,11.5% in Brown and 9.6%in Black cultivar from 0 to 240 mM NaCl)and antioxydants components.Varieties White and Brown were less affected by salinity.Conclusion:White variety exhibited higher adaptive potential under salinity stress when compared to Brown variety(rich in fiber)and closely followed by Black variety.Thus White variety could be recommended for consumer oil,minerals and proteins.As for Black variety,it could be used,as glucid and antioxydants additives in food.
基金the China Postdoctoral Science Foundation(Grant No.2024MD753992)Shaanxi Geotechnical Mechanics and Engineering Young Talent Support Program Project(Grant No.YESS2024005)the National Natural Science Foundation of China(Grant No.41931285).
文摘In this study,compacted loess samples with varying compaction water content but identical dry density were prepared to investigate the evolution of their hydraulic conductivity and compression behavior.Additionally,environmental scanning electron microscopy(ESEM)and nuclear magnetic resonance(NMR)analyses were conducted to gain microstructural insights into loess behavior at the laboratory scale.The results indicate that the maximum saturated hydraulic conductivity is observed at the lowest compaction water content,particularly in the early stage of permeability tests.In particular,for loess compacted at water contents below the optimum(as determined by the modified Proctor compaction test),the hydraulic conductivity decreases throughout the permeability tests.Conversely,when the water content exceeds the optimum level,the hydraulic conductivity shows an increasing trend.In terms of compression behavior,when the as-compacted samples are loaded in oedometer conditions,an increase in material compressibility is observed with increasing compaction water content.Again,a different phenomenological behavior was observed when the compaction water content exceeded the optimum,i.e.an abrupt increase in loess compressibility.ESEM tests provide microstructural confirmation of this evidence,as the surface morphology of the compacted loess changes significantly with increasing compaction water content.The microstructural evolution was also quantified in terms of area ratio using image processing software.Finally,NMR was used to quantify the intra-and inter-aggregate water at different compaction water contents,once again highlighting a threshold for the presence or absence of inter-aggregate water similar to the optimum water content.
