Mechanical Performance of Bio-inspired Bidirectional Corrugated Sandwich Pressure Shell Under External Hydrostatic Pressure

This paper aims to enhance the compression capacity of underwater cylindrical shells by adopting the corrugated sandwich structure of cuttlebone.The cuttlebone suffers uniaxial external compression,while underwater cylindrical shells are in a biaxial compressive stress state.To suit the biaxial compressive stress state,a novel bidirectional corrugated sandwich structure is proposed to improve the bearing capacity of cylindrical shells.The static and buckling analysis for the sandwich shell and the unstiffened cylindrical shell with the same volume-weight ratio are studied by numerical simulation.It is indicated that the proposed sandwich shell can effectively reduce the ratio between circumferential and axial stress from 2 to 1.25 and improve the critical buckling load by about 1.63 times.Numerical simulation shows that optimizing and adjusting the structural parameters could significantly improve the advantage of the sandwich shell.Then,the hydrostatic pressure tests for shell models fabricated by 3D printing are carried out.According to the experimental results,the overall failure position of the sandwich shell is at the center part of the sandwich shell.It has been found the average critical load of the proposed sandwich shell models exceeds two times that of the unstiffened shell models.Hence,the proposed bio-inspired bidirectional corrugated sandwich structure can significantly enhance the pressure resistance capability of cylindrical shells.

Data-augmented landslide displacement prediction using generative adversarial network

Landslides are destructive natural disasters that cause catastrophic damage and loss of life worldwide.Accurately predicting landslide displacement enables effective early warning and risk management.However,the limited availability of on-site measurement data has been a substantial obstacle in developing data-driven models,such as state-of-the-art machine learning(ML)models.To address these challenges,this study proposes a data augmentation framework that uses generative adversarial networks(GANs),a recent advance in generative artificial intelligence(AI),to improve the accuracy of landslide displacement prediction.The framework provides effective data augmentation to enhance limited datasets.A recurrent GAN model,RGAN-LS,is proposed,specifically designed to generate realistic synthetic multivariate time series that mimics the characteristics of real landslide on-site measurement data.A customized moment-matching loss is incorporated in addition to the adversarial loss in GAN during the training of RGAN-LS to capture the temporal dynamics and correlations in real time series data.Then,the synthetic data generated by RGAN-LS is used to enhance the training of long short-term memory(LSTM)networks and particle swarm optimization-support vector machine(PSO-SVM)models for landslide displacement prediction tasks.Results on two landslides in the Three Gorges Reservoir(TGR)region show a significant improvement in LSTM model prediction performance when trained on augmented data.For instance,in the case of the Baishuihe landslide,the average root mean square error(RMSE)increases by 16.11%,and the mean absolute error(MAE)by 17.59%.More importantly,the model’s responsiveness during mutational stages is enhanced for early warning purposes.However,the results have shown that the static PSO-SVM model only sees marginal gains compared to recurrent models such as LSTM.Further analysis indicates that an optimal synthetic-to-real data ratio(50%on the illustration cases)maximizes the improvements.This also demonstrates the robustness and effectiveness of supplementing training data for dynamic models to obtain better results.By using the powerful generative AI approach,RGAN-LS can generate high-fidelity synthetic landslide data.This is critical for improving the performance of advanced ML models in predicting landslide displacement,particularly when there are limited training data.Additionally,this approach has the potential to expand the use of generative AI in geohazard risk management and other research areas.

Method for determining the position of landslide slip-surface with a typical inclinometric curves

In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.

Damage characteristics of Cu−Cr−Zr alloy rail of electromagnetic railgun after simulated launch

The damage characteristics of different speed sections of Cu−Cr−Zr alloy rail after simulated launch were studied.The microstructure,morphologies and properties of samples were investigated by using XRD,XPS,EBSD,SEM,hardness test,electrochemical test and DSC techniques.It was found that deposition layers were formed on the surfaces of the simulated launch samples.The thickness and surface roughness of these deposition layers increased with increasing the heat effect,suggesting a launch speed dependent damage degree of the arc ablation.The hardness variation of samples is attributed to the effects of the deposition layer and deformation hardening.The surface deposition layer affects corrosion resistance and crystalline characteristics,leading to changes in subsequent service performances.Additionally,the surface texture and plastic deformation ability of the samples are related to the recrystallization degree and deformation grain amount.

Molecular dynamics simulation of the flow mechanism of shear-thinning fluids in a microchannel

Shear-thinning fluids have been widely used in microfluidic systems,but their internal flow mechanism is still unclear.Therefore,in this paper,molecular dynamics simulations are used to study the laminar flow of shear-thinning fluid in a microchannel.We validated the feasibility of our simulation method by evaluating the mean square displacement and Reynolds number of the solution layers.The results show that the change rule of the fluid system's velocity profile and interaction energy can reflect the shear-thinning characteristics of the fluids.The velocity profile resembles a top-hat shape,intensifying as the fluid's power law index decreases.The interaction energy between the wall and the fluid decreases gradually with increasing velocity,and a high concentration of non-Newtonian fluid reaches a plateau sooner.Moreover,the velocity profile of the fluid is related to the molecule number density distribution and their values are inversely proportional.By analyzing the radial distribution function,we found that the hydrogen bonds between solute and water molecules weaken with the increase in velocity.This observation offers an explanation for the shear-thinning phenomenon of the non-Newtonian flow from a micro perspective.

Discovery and characterization of a new hydrothermal field at 2°N on the slow-spreading Carlsberg Ridge

A new hydrothermal field(Tianshi)was discovered on the rift valley wall through plume anomaly surveys and geological work conducted in 2012 and 2018 between 2°35′N and 2°43′N of the slow-spreading Carlsberg Ridge(CR).Here,the results of two expeditions conducted to detect and characterize the new hydrothermal field are reported.Mineralogical and geochemical data,as well as 14 C ages of a sediment core collected near the field are presented to reveal the hydrothermal history.Results show that the Tianshi field is a basalt-hosted hydrothermal system.Geochemical data of the sediments collected near the field indicate a strong hydrothermal contribution,and hydrothermal Fe and Cu fluxes range from 30 to 155 mg/(cm^(2)·ka)and 0.59 to 11.49 mg/(cm^(2)·ka),respectively.Temporal variations in the fluxes of hydrothermal Fe indicate that there have been at least three amplified hydrothermal venting events(H 1,H 2,and H 3)in the Tianshi field over the last 35.2 ka,in 28.6-35.2 ka BP,22.0-27.6 ka BP,and 1.2-11.4 ka BP,respectively.Hydrothermal event H 2 was driven by an increased magmatic production associated with sea level fall during the Last Glacial Maximum,while event H 3 was promoted by tectonic activity associated with a rapid sea level rise.This study further verified the role of sea level change in modulating hydrothermal activity on mid-ocean ridges.

Ultrasonic scalpel based on fusiform phononic crystal structure

In response to the ultrasonic scalpels with the vibrational modal coupling which leads to a decrease in efficiency,an ultrasonic scalpel based on fusiform phononic crystals(PnCs)is proposed.An accurate theoretical model is constructed,which is mainly composed of electromechanical equivalent circuit models to analyze the frequency response function and the frequency response curves of the admittance.Bragg band gaps exist in the fusiform PnCs owing to the periodic constraint,which can suppress the corresponding vibrational modes.The vibration characteristics(vibration mode,frequency,and displacement distribution)of the ultrasonic scalpel are analyzed,and the validity of the electromechanical equivalent circuit method is verified.The results indicate that other vibration modes near the working frequency can be isolated.In addition,blades based on fusiform PnCs have a function akin to that of the horn,which enables displacement amplification.

Biogeochemistry of sedimentary organic matter in the Yongjiang River estuary in the southern part of Hangzhou Bay,China,since the Late Pleistocene

A sediment core(YJK19-02)collected from the southern outlet of Hangzhou Bay near the Yongjiang River estuary in East China was analyzed for grain size,lignin,bulk elemental composition,stable carbon isotope,and rare earth elements(REEs)to determine the sources and diagenesis of sedimentary organic matter(OM)of the estuary and adjacent areas since the Late Pleistocene.δ^(13)C values(-24.80‰–-23.60‰),total organic carbon/total nitrogen(TOC/TN)molar ratios(8.00–12.14),and light rare earth element/heavy rare earth element ratios(LREE/HREE=8.34–8.91)revealed the predominance of terrestrial sources of OM,mainly from the Changjiang(Yangtze)River.The lignin parameters of syringyl/vanillyl(S/V=0.20–0.73)and cinnamyl/vanillyl(C/V=0.03–0.19)ratios indicate the predominance of nonwoody angiosperms,and the vanillic acid/vanillin ratios[(Ad/Al)_(V)=0.32–1.57]indicate medium to high degrees of lignin degradation.An increasing trend ofΛ(total lignin in mg/100-mg OC)values from ca.14500 a BP to ca.11000 a BP reflected the increase in temperature during the Late Pleistocene.However,a time lag effect of temperature on vegetation abundance was also revealed.The relatively higher and stableΛvalues correspond to the higher temperature during the mid-Holocene from ca.8500 a BP to ca.4500 a BP.Λvalues decreased from ca.4000 a BP to the present,corresponding to historical temperature fluctuations during this time.Our results show that the vegetation abundance in the Yongjiang River Basin since the Late Pleistocene was related to the temperature fluctuation duo to climate change.

Morphological,phylogenetic and metabolite profile of Prorocentrum clipeus,a newly recorded epiphytic dinoflagellate in the northern Yellow Sea

More than 30 species of benthic Prorocentrum have been identified,some of which produce okadaic acid(OA)and its derivatives,dinophysistoxins(DTXs),which cause diarrhetic shellfish poisoning(DSP).Increasing numbers of benthic Prorocentrum species have been reported in tropical and subtropical waters of China.In contrast,only a few benthic Prorocentrum species have been reported in temperate waters.In this study,morphological descriptions obtained using light microscopy,scanning electron microscopy and molecular characterization of one Prorocentrum clipeus strain isolated from the Yellow Sea are presented.Prorocentrum clipeus cells were nearly circular in shape,with a collar,ridge,and one protrusion.The periflagellar area was wide U-shaped,with two curved projections on platelet 1a.Nine periflagellar platelets of different sizes were observed.The morphology closely fits that of the species isolated from other locations.Phylogenetic analysis based on the molecular sequences of the small subunit(SSU)rDNA,internal transcribed spacer(ITS),and large subunit(LSU)rDNA was performed.A comprehensive metabolomic analysis incorporating target,suspect and non-target screenings was first applied to investigate the intracellular and extracellular metabolite profiles of the current isolate of P.clipeus.According to the results of the target and suspect screenings,179 metabolites or toxins produced by DSP-related algal species,including OA,dinophysistoxin-1(DTX1),dinophysistoxin-2(DTX2)and pectenotoxin-2(PTX2),were not detected.Non-target screening involving feature-based molecular networking(FBMN)provided a global view of major metabolites produced by the P.clipeus DF128 strain and revealed 23 clusters belonging to at least 13 compound classes,with organometallic compounds,lipids and lipid-like molecules,phenylpropanoids and polyketides,and benzenoids as major types.To date,this is the first record of the characterization of P.clipeus in samples from Chinese waters.Our results support the wide distribution of epibenthic Prorocentrum species.

Three-dimensional constrained gravity inversion of Moho depth and crustal structural characteristics at Mozambique continental margin

Mozambique's continental margin in East Africa was formed during the break-off stage of the east and west Gondwana lands. Studying the geological structure and division of continent-ocean boundary(COB) in Mozambique's continental margin is considered of great significance to rebuild Gondwana land and understand its movement mode. Along these lines, in this work, the initial Moho was fit using the known Moho depth from reflection seismic profiles, and a 3D multi-point constrained gravity inversion was carried out. Thus, highaccuracy Moho depth and crustal thickness in the study area were acquired. According to the crustal structure distribution based on the inversion results, the continental crust at the narrowest position of the Mozambique Channel was detected. According to the analysis of the crustal thickness, the Mozambique ridge is generally oceanic crust and the COB of the whole Mozambique continental margin is divided.

Effects of nutrient limitations on the sinking velocity of Thalassiosira weissflogii

The sinking of diatoms is critic al to the formation of oceanic biological pumps and coastal hypoxic zones.However,little is known about the effects of different nutrient restrictions on diatom sinking.In this study,we measured the sinking velocity(SV) of Thalassiosira weissflogii using a new phytoplankton video observation instrument and analyzed major biochemical components under varying nutrient conditions.Our results showed that the SV of T.weissflogii under different nutrient limitation conditions varied substantially.The highest SV of(1.77±0.02) m/d was obtained under nitrate limitation,signific antly surpassing that under phosphate limitation at(0.98±0.13) m/d.As the nutrient limitation was released,the SV steadily decreased to(0.32±0.03) m/d and(0.15±0.05) m/d,respectively.Notably;under conditions with limited nitrate and phosphate concentrations,the SV values of T.weissflogii significantly positively correlated with the lipid content(P <0.001),with R^(2) values of 0.86 and 0.69,respectively.The change of the phytoplankton SV was primarily related to the intracellular compo sition,which is controlled by nutrient conditions but did not significantly correlate with transparent extracellular polymer and biosilica contents.The results of this study help to understand the regulation of the vertical sinking process of diatoms by nutrient restriction and provide new insights into phytoplankton dynamics and their relationship with the marine nutrient structure.

Machine Learning for Signal Demodulation in Underwater Wireless Optical Communications

The underwater wireless optical communication(UWOC)system has gradually become essential to underwater wireless communication technology.Unlike other existing works on UWOC systems,this paper evaluates the proposed machine learningbased signal demodulation methods through the selfbuilt experimental platform.Based on such a platform,we first construct a real signal dataset with ten modulation methods.Then,we propose a deep belief network(DBN)-based demodulator for feature extraction and multi-class feature classification.We also design an adaptive boosting(Ada Boost)demodulator as an alternative scheme without feature filtering for multiple modulated signals.Finally,it is demonstrated by extensive experimental results that the Ada Boost demodulator significantly outperforms the other algorithms.It also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power.A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio(SNR)is higher.

Observer-Based Adaptive Robust Precision Motion Control of a Multi-Joint Hydraulic Manipulator

Hydraulic manipulators are usually applied in heavy-load and harsh operation tasks.However,when faced with a complex operation,the traditional proportional-integral-derivative(PID)control may not meet requirements for high control performance.Model-based full-state-feedback control is an effective alternative,but the states of a hydraulic manipulator are not always available and reliable in practical applications,particularly the joint angular velocity measurement.Considering that it is not suitable to obtain the velocity signal directly from differentiating of position measurement,the low-pass filtering is commonly used,but it will definitely restrict the closed-loop bandwidth of the whole system.To avoid this problem and realize better control performance,this paper proposes a novel observerbased adaptive robust controller(obARC)for a multi-joint hydraulic manipulator subjected to both parametric uncertainties and the lack of accurate velocity measurement.Specifically,a nonlinear adaptive observer is first designed to handle the lack of velocity measurement with the consideration of parametric uncertainties.Then,the adaptive robust control is developed to compensate for the dynamic uncertainties,and the close-loop system robust stability is theoretically proved under the observation and control errors.Finally,comparative experiments are carried out to show that the designed controller can achieve a performance improvement over the traditional methods,specifically yielding better control accuracy owing to the closed-loop bandwidth breakthrough,which is limited by low-pass filtering in fullstate-feedback control.

A VGGNet-based correction for satellite altimetry-derived gravity anomalies to improve the accuracy of bathymetry to depths of 6500 m

Understanding the topographic patterns of the seafloor is a very important part of understanding our planet.Although the science involved in bathymetric surveying has advanced much over the decades,less than 20%of the seafloor has been precisely modeled to date,and there is an urgent need to improve the accuracy and reduce the uncertainty of underwater survey data.In this study,we introduce a pretrained visual geometry group network(VGGNet)method based on deep learning.To apply this method,we input gravity anomaly data derived from ship measurements and satellite altimetry into the model and correct the latter,which has a larger spatial coverage,based on the former,which is considered the true value and is more accurate.After obtaining the corrected high-precision gravity model,it is inverted to the corresponding bathymetric model by applying the gravity-depth correlation.We choose four data pairs collected from different environments,i.e.,the Southern Ocean,Pacific Ocean,Atlantic Ocean and Caribbean Sea,to evaluate the topographic correction results of the model.The experiments show that the coefficient of determination(R~2)reaches 0.834 among the results of the four experimental groups,signifying a high correlation.The standard deviation and normalized root mean square error are also evaluated,and the accuracy of their performance improved by up to 24.2%compared with similar research done in recent years.The evaluation of the R^(2) values at different water depths shows that our model can achieve performance results above 0.90 at certain water depths and can also significantly improve results from mid-water depths when compared to previous research.Finally,the bathymetry corrected by our model is able to show an accuracy improvement level of more than 21%within 1%of the total water depths,which is sufficient to prove that the VGGNet-based method has the ability to perform a gravity-bathymetry correction and achieve outstanding results.

Spatiotemporal characteristics of water exchange between the Andaman Sea and the Bay of Bengal

A high-resolution customized numerical model is used to analyze the water transport in the three major water passages between the Andaman Sea(AS)and the Bay of Bengal,i.e.,the Preparis Channel(PC),the Ten Degree Channel(TDC),and the Great Channel(GC),based on the daily averaged simulation results ranging from 2010 to 2019.Spectral analysis and Empirical Orthogonal Function(EOF)methods are employed to investigate the spatiotemporal variability of the water exchange and controlling mechanisms.The results of model simulation indicate that the net average transports of the PC and GC,as well as their linear trend,are opposite to that of the TDC.This indicates that the PC and the GC are the main inflow channels of the AS,while the TDC is the main outflow channel of the AS.The transport variability is most pronounced at surface levels and between 100 m and 200 m depth,likely affected by monsoons and circulation.A 182.4-d semiannual variability is consistently seen in all three channels,which is also evident in their second principal components.Based on sea level anomalies and EOF analysis results,this is primarily due to equatorial winds during the monsoon transition period,causing eastward movement of Kelvin waves along the AS coast,thereby affecting the spatiotemporal characteristics of the flow in the AS.The first EOF of the PC flow field section shows a split at 100 m deep,likely due to topography.The first EOF of the TDC flow field section is steady but has potent seasonal oscillations in its time series.Meanwhile,the first EOF of the GC flow field section indicates a stable surface inflow,probably influenced by the equatorial Indian Ocean’s eastward current.

Provenance of colorless and brown volcanic glass in late Pleistocene tephra layers in the Western Philippine Sea

Tephra layers in the western Philippine Sea,characterized by abundant volcanic glass shards,may provide crucial evidence on the eruption history of volcanoes and tectonic evolution of the western Pacific.A 220-ka sediment core from the Benham Rise in the western Philippine Sea offers new insights into the provenance of four intercalated tephra layers(T1–T4,in chronological order)containing either colorless or brown glass shards.Relative to primitive mantle,all glass shards are enriched in large-ion lithophile elements,such as Rb,Cs,and Pb,and depleted in high field-strength elements,such as Th,Nb,and Ta,indicating a subduction-related origin.The colorless glass shards are characterized by high SiO_(2)(>78%)and light rare earth element(LREE)contents as well as high La/Sm ratios(>9),low FeO and MgO contents(<1%),low Sr/Y(<15)and high Ba/Th ratios(>100),pointing to a rhyolitic composition and a medium-K calc-alkaline serial affinity.In contrast,the brown glass shards are characterized by lower SiO_(2)(<63%)and LREE contents,higher FeO,MgO,and CaO contents,lower La/Sm(<6)and Ba/Th(<75),and similar Sr/Y ratios(<15),indicating derivation from medium to high-K calc-alkaline andesite magma.Brown glass shards from layers T3(152 ka)and T4(172 ka)were correlated with volcanic deposits from the Taal and Laguna Caldera in the Maccolod Corridor,respectively,while the colorless glass shards from layers T1(36.5 ka)and T2(61.2 ka)were likely sourced from the Irosin Caldera in the Bicol Arc.Establishing the provenance of late Pleistocene tephra layers in the western Philippine Sea is helpful to complement a Philippine volcanic history and establish a regional tephrochronostratigraphy.

Thiosulfate oxidation and autotrophy potential by marine prevalent heterotrophic bacteria of genus Marinobacter

The genus Marinobacter is very broadly distributed in global environments and is considered as aerobic heterotroph.In this study,six Marinobacter strains were identified with autotrophic thiosulfate oxidation capacity.These strains,namely Marinobacter guineae M3B^(T),Marinobacter aromaticivorans D15-8PT,Marinobacter vulgaris F01^(T),Marinobacter profundi PWS21^(T),Marinobacter denitrificans JB02H27T,and Marinobacter sp.ST-1M(with a 99.93%similarity to the 16S rDNA sequences of Marinobacter salsuginis SD-14B^(T)),were screened out of 32 Marinobacter strains by autotrophic thiosulfate oxidization medium.The population of cells grew in a chemolithotrophic medium,increasing from 105 cells/mL to 10^(7) cells/mL within 5 d.This growth was accompanied by the consumption of thiosulfate 3.59 mmol/L to 9.64 mmol/L and the accumulation of sulfate up to 0.96 mmol/L,and occasionally produced sulfur containing complex particles.Among these Marinobacter strains,it was also found their capability of oxidizing thiosulfate to sulfate in a heterotrophic medium.Notably,M.vulgaris F01^(T)and M.antarcticus ZS2-30^(T)showed highly significant production of sulfate at 9.45 mmol/L and 3.10 mmol/L.Genome annotation indicated that these Marinobacter strains possess a complete Sox cluster for thiosulfate oxidation.Further phylogenetic analysis of the soxB gene revealed that six Marinobacter strains formed a separate lineage within Gammaproteobacteria and close to obligate chemolithoautotroph Thiomicrorhabdus arctica.The results indicated that thiosulfate oxidizing and chemolithoautotrophic potential in Marinobacter genus,which may contribute to the widespread of Marinobacter in the global ocean.

Effects of phosphorus limitation on sinking velocities of phytoplankton during summer in the Changjiang River Estuary

The sinking of phytoplankton is critical to organic matter transportation in the ocean and it is an essential process for the formation of coastal hypoxic zones.This study was based on a field investigation conducted during the summer of 2022 in the Changjiang River(Yangtze River) Estuary(CJE) and its adjacent waters.The settling column method was employed to measure the sinking velocity(SV) of different size fractions of phytoplankton at the surface of the sea and to analyze their environmental control mechanisms.The findings reveal significant spatial variation in phytoplankton SV(-0.55-2.41 m/d) within the CJE.High-speed sinking was predominantly observed in phosphate-depleted regions beyond the CJE front.At the same time,an upward trend was more commonly observed in the phosphate-rich regions near the CJE mouth.The SV ranges for different sizefractionated phytoplankton,including micro-(>20 μm),nano-(2-20 μm),and picophytoplankton(0.7-2 μm),were-0.50-4.74 m/d,-1.04-1.59 m/d,and-1.24-1.65 m/d,respectively.Correlation analysis revealed a significant negative correlation between SV and dissolved inorganic phosphorus(DIP),implying that the influence of DIP contributes to SV.The variations in phytoplankton alkaline phosphatase activity suggested a significant increase in SV across all size fractions in the event of phosphorus limitation.Phytoplankton communities with limited photo synthetic capacity(maximum photochemical efficience,Fv/Fm <0.3) were found to have higher SV than that of communities with strong capacity,suggesting a link between sinking and alterations in physiological conditions due to phosphate depletion.The findings from the in situ phosphate enrichment experiments confirmed a marked decrease in SV following phosphate supplementation.These findings suggest that phosphorus limitation is the primary driver of elevated SV in the CJE.This study enhances the comprehension of the potential mechanisms underlying hypoxic zone formation in the CJE,providing novel insights into how nearshore eutrophication influences organic carbon migration.

基于全局响应面算法的Q235B钢的Johnson-Cook模型参数最优

This study investigates the mechanical properties of Q235B steel through quasi-static tests at both room temperature and elevated temperature.The initial values of the Johnson-Cook model parameters are determined using a fitting method.The global response surface algorithm is employed to optimize and calibrate the Johnson-Cook model parameters for Q235B steel under both room temperature and elevated temperature conditions.A simulation model is established at room temperature,and the simulated mechanical performance curves for displacement and stress are monitored.Multiple optimization algorithms are applied to optimize and calibrate the model parameters at room temperature.The global response surface algorithm is identified as the most suitable algorithm for this optimization problem.Sensitivity analysis is conducted to explore the impact of model parameters on the objective function.The analysis indicates that the optimized material model better fits the experimental values,aligning more closely with the actual test results of material strain mechanisms over a wide temperature range.

Identification and analysis of immunological activity of two isoforms of tropomyosin in Alectryonella plicatula

Oyster,as a common aquatic food,play an important role in shellfish allergy.In this study,2 tropomyosin(TM)isoforms TM-αand TM-β(TM-α/-β)in Alectryonella plicatula were identified.The sequences of 852 bp encoding 284 amino acids of TM-α/-βand 2 recombinant proteins were obtained,respectively.There were 12 amino acid differences between TM-α/-β.The results of immunological experiments indicated that TM-βhad stronger immunobinding activity and immunoreactivity than those of TM-α.Structural analysis showed that TM-βhad moreα-helix and higher surface hydrophobicity than TM-α.Sequences and epitopes alignment with shellfish TMs revealed that amino acids of TM-βwere more frequently recognized as IgE epitopes in other shellfish TMs than TM-α.Differences in structure and sequence account for the higher immunological activity of TM-βcompared to TM-α.These findings provide a theoretical basis for enriching the understanding of shellfish TM and accurate diagnosis of allergic components.