Organic Matter Accumulation in the Upper Permian Dalong Formation from the Lower Yangtze Region,South China

The Late Permian was marked by a series of important geological events and widespread organic-rich black shale depositions,acting as important unconventional hydrocarbon source rocks.However,the mechanism of organic matter(OM)enrichment throughout this period is still controversial.Based on geochemical data,the marine redox conditions,paleogeographic and hydrographic environment,primary productivity,volcanism,and terrigenous input during the Late Permian in the Lower Yangtze region have been studied from the Putaoling section,Chaohu,to provide new insights into OM accumulation.Five Phases are distinguished based on the TOC and environmental variations.In Phase I,anoxic conditions driven by water restriction enhanced OM preservation.In Phase II,euxinic and cycling hydrological environments were the two most substantial controlling factors for the massive OM deposition.During Phase III,intensified terrestrial input potentially diluted the OM in sediment and the presence of oxygen in bottom water weakened the preservation condition.Phase IV was characterized by a relatively higher abundance of mercury(Hg)and TOC(peak at 16.98 wt%),indicating that enhanced volcanism potentially stimulated higher productivity and a euxinic environment.In Phase V,extremely lean OM was preserved as a result of terrestrial dilutions and decreasing primary productivity.Phases I,II and IV are characterized as the most prominent OM-rich zones due to the effective interactions of the controlling factors,namely paleogeographic,hydrographic environment,volcanism,and redox conditions.

Genesis of LCT Pegmatites during Early Paleozoic Orogeny of the North Qinling Orogenic Belt,China:Emplacement Conditions and Structural Control

The Guanpo pegmatite field in the North Qinling orogenic belt(NQB),China,hosts the most abundant LCT pegmatites.However,their emplacement conditions and structural control remain unexplored.In this contribution,we investigated it combining pegmatite orientation measurement with oxygen isotope geothermometry and fluid inclusion study.The orientations of type A1 pegmatites(P_(f)<σ_(2))are predominantly influenced by P-and T-fractures due to simple shearing in Shiziping dextral thrust shear zone during D_(2)deformation,whereas type A2 pegmatites(contemporaneous with D_(4))are governed by hydraulic fractures aligned with S_(0)and S_(0+1)stemming from fluid pressure(P_(f)<σ_(2)).Additionally,type B pegmatites(P_(f)≤σ_(2))exhibit orientations shaped by en echelon extensional fractures in local ductile shear zones(contemporaneous with D_(3)).The albite-quartz oxygen isotope geothermometry and microthermometric analysis of fluid inclusions in elbaites from the latest pegmatites(including types B and A2)suggest that the crystallization P-T for late magmatic and hydrothermal stages are 527.5-559.2℃,320℃,3.1-3.6 kbar and 2.0 kbar,respectively.Our observations along with previous studies suggest that the genesis of the LCT pegmatites was a long-term,multi-stage event during early Paleozoic orogeny(including the collision stage)of the NQB,and was facilitated by various local fractures.

Ambient-Condition Strategy for Production of Hollow Ga_(2)O_(3)@rGO Crystalline Nanostructures Toward Efficient Lithium Storage

Crystallineγ-Ga_(2)O_(3)@rGO core-shell nanostructures are synthesized in gram scale,which are accomplished by a facile sonochemical strategy under ambient condition.They are composed of uniformγ-Ga_(2)O_(3)nanospheres encapsulated by reduced graphene oxide(rGO)nanolayers,and their formation is mainly attributed to the existed opposite zeta potential between the Ga_(2)O_(3)and rGO.The as-constructed lithium-ion batteries(LIBs)based on as-fabricatedγ-Ga_(2)O_(3)@rGO nanostructures deliver an initial discharge capacity of 1000 mAh g^(-1)at 100 mA g^(-1)and reversible capacity of 600 mAh g^(-1)under 500 mA g^(-1)after 1000 cycles,respectively,which are remarkably higher than those of pristineγ-Ga_(2)O_(3)with a much reduced lifetime of 100 cycles and much lower capacity.Ex situ XRD and XPS analyses demonstrate that the reversible LIBs storage is dominant by a conversion reaction and alloying mechanism,where the discharged product of liquid metal Ga exhibits self-healing ability,thus preventing the destroy of electrodes.Additionally,the rGO shell could act robustly as conductive network of the electrode for significantly improved conductivity,endowing the efficient Li storage behaviors.This work might provide some insight on mass production of advanced electrode materials under mild condition for energy storage and conversion applications.

Aero-Hydro-Elastic-Servo Modeling and Dynamic Response Analysis of A Monopile Offshore Wind Turbine Under Different Operating Scenarios

This paper constructs a coupled aero-hydro-elastic-servo simulation framework for a monopile offshore wind turbine(OWT).In this framework,a detailed multi-body dynamics model of the monopile OWT including the gearbox,blades,tower and other components(nacelle,hub,bedplate,etc.)has been explicitly established.The effects of pile−soil interaction,controller and operational conditions on the turbine dynamic responses are studied systematically in time domain and frequency domain.The results show that(1)a comprehensive drivetrain model has the capability to provide a more precise representation of the complex dynamic characteristics exhibited by drivetrain components,which can be used as the basis for further study on the dynamic characteristics of the drivetrain.(2)The pile−soil interaction can influence the wind turbine dynamic responses,particularly under the parked condition.(3)The effect of the pile−soil interaction on tower responses is more significant than that on blade responses.(4)The use of the controller can substantially affect the rotor characteristics,which in turn influences the turbine dynamic responses.(5)The tower and blade displacements under the operational condition are much larger than those under the parked condition.The model and methodology presented in this study demonstrate potential for examining complex dynamic behaviors of the monopile OWTs.To ensure accuracy and precision,it is imperative to construct a detailed model of the wind turbine system,while also taking into account simulation efficiency.

Role of outdoor trees on pedestrian wind and thermal conditions around a pre-education building for sustainable energy management

Finding sustainable energy resources is essential to face the increasing energy demand.Trees are an important part of ancient architecture but are becoming rare in urban areas.Trees can control and tune the pedestrian-level wind velocity and thermal condition.In this study,a numerical investigation is employed to assess the role of trees planted in the windward direction of the building complex on the thermal and pedestrian wind velocity conditions around/inside a pre-education building located in the center of the complex.Compared to the previous studies(which considered only outside buildings),this work considers the effects of trees on microclimate change both inside/outside buildings.Effects of different parameters including the leaf area density and number of trees,number of rows,far-field velocity magnitude,and thermal condition around the main building are assessed.The results show that the flow velocity in the spacing between the first-row buildings is reduced by 30%-40% when the one-row trees with 2 m height are planted 15 m farther than the buildings.Furthermore,two rows of trees are more effective in higher velocities and reduce the maximum velocity by about 50%.The investigation shows that trees also could reduce the temperature by about 1℃around the building.

Autophagy and mitophagy as potential therapeutic targets in diabetic heart condition:Harnessing the power of nanotheranostics

Autophagy and mitophagy pose unresolved challenges in understanding the pathology of diabetic heart condition(DHC),which encompasses a complex range of cardiovascular issues linked to diabetes and associated cardiomyopathies.Despite significant progress in reducing mortality rates from cardiovascular diseases(CVDs),heart failure remains a major cause of increased morbidity among diabetic patients.These cellular processes are essential for maintaining cellular balance and removing damaged or dysfunctional components,and their involvement in the development of diabetic heart disease makes them attractive targets for diagnosis and treatment.While a variety of conventional diagnostic and therapeutic strategies are available,DHC continues to present a significant challenge.Point-of-care diagnostics,supported by nanobiosensing techniques,offer a promising alternative for these complex scenarios.Although conventional medications have been widely used in DHC patients,they raise several concerns regarding various physiological aspects.Modern medicine places great emphasis on the application of nanotechnology to target autophagy and mitophagy in DHC,offering a promising approach to deliver drugs beyond the limitations of traditional therapies.This article aims to explore the potential connections between autophagy,mitophagy and DHC,while also discussing the promise of nanotechnology-based theranostic interventions that specifically target these molecular pathways.

Dynamic Vision-Based Machinery Fault Diagnosis With Cross-Modality Feature Alignment

Intelligent machinery fault diagnosis methods have been popularly and successfully developed in the past decades,and the vibration acceleration data collected by contact accelerometers have been widely investigated.In many industrial scenarios,contactless sensors are more preferred.The event camera is an emerging bio-inspired technology for vision sensing,which asynchronously records per-pixel brightness change polarity with high temporal resolution and low latency.It offers a promising tool for contactless machine vibration sensing and fault diagnosis.However,the dynamic vision-based methods suffer from variations of practical factors such as camera position,machine operating condition,etc.Furthermore,as a new sensing technology,the labeled dynamic vision data are limited,which generally cannot cover a wide range of machine fault modes.Aiming at these challenges,a novel dynamic vision-based machinery fault diagnosis method is proposed in this paper.It is motivated to explore the abundant vibration acceleration data for enhancing the dynamic vision-based model performance.A crossmodality feature alignment method is thus proposed with deep adversarial neural networks to achieve fault diagnosis knowledge transfer.An event erasing method is further proposed for improving model robustness against variations.The proposed method can effectively identify unseen fault mode with dynamic vision data.Experiments on two rotating machine monitoring datasets are carried out for validations,and the results suggest the proposed method is promising for generalized contactless machinery fault diagnosis.

Debaryomyces hansenii supplementation in low fish meal diets promotes growth,modulates microbiota and enhances intestinal condition in juvenile marine fish

Background The development of a sustainable business model with social acceptance,makes necessary to develop new strategies to guarantee the growth,health,and well-being of farmed animals.Debaryomyces hansenii is a yeast species that can be used as a probiotic in aquaculture due to its capacity to i)promote cell proliferation and differen-tiation,ii)have immunostimulatory effects,iii)modulate gut microbiota,and/or iv)enhance the digestive function.To provide inside into the effects of D.hansenii on juveniles of gilthead seabream(Sparus aurata)condition,we inte-grated the evaluation of the main key performance indicators coupled with the integrative analysis of the intestine condition,through histological and microbiota state,and its transcriptomic profiling.Results After 70 days of a nutritional trial in which a diet with low levels of fishmeal(7%)was supplemented with 1.1%of D.hansenii(17.2×10^(5) CFU),an increase of ca.12%in somatic growth was observed together with an improve-ment in feed conversion in fish fed a yeast-supplemented diet.In terms of intestinal condition,this probiotic modu-lated gut microbiota without affecting the intestine cell organization,whereas an increase in the staining intensity of mucins rich in carboxylated and weakly sulphated glycoconjugates coupled with changes in the affinity for certain lectins were noted in goblet cells.Changes in microbiota were characterized by the reduction in abundance of several groups of Proteobacteria,especially those characterized as opportunistic groups.The microarrays-based transcrip-tomic analysis found 232 differential expressed genes in the anterior-mid intestine of S.aurata,that were mostly related to metabolic,antioxidant,immune,and symbiotic processes.Conclusions Dietary administration of D.hansenii enhanced somatic growth and improved feed efficiency param-eters,results that were coupled to an improvement of intestinal condition as histochemical and transcriptomic tools indicated.This probiotic yeast stimulated host-microbiota interactions without altering the intestinal cell organization nor generating dysbiosis,which demonstrated its safety as a feed additive.At the transcriptomic level,D.hansenii pro-moted metabolic pathways,mainly protein-related,sphingolipid,and thymidylate pathways,in addition to enhance antioxidant-related intestinal mechanisms,and to regulate sentinel immune processes,potentiating the defensive capacity meanwhile maintaining the homeostatic status of the intestine.

A review of extreme condition effects on solder joint reliability:Understanding failure mechanisms

Solder joint,crucial component in electronic systems,face significant challenges when exposed to extreme conditions during applications.The solder joint reliability involving microstructure and mechanical properties will be affected by extreme conditions.Understanding the behaviour of solder joints under extreme conditions is vital to determine the durability and reliability of solder joint.This review paper aims to comprehensively explore the underlying failure mechanism affecting solder joint reliability under extreme conditions.This study covers an in-depth analysis of effect extreme temperature,mechanical stress,and radiation conditions towards solder joint.Impact of each condition to the microstructure including solder matrix and intermetallic compound layer,and mechanical properties such as fatigue,shear strength,creep,and hardness was thoroughly discussed.The failure mechanisms were illustrated in graphical diagrams to ensure clarity and understanding.Furthermore,the paper highlighted mitigation strategies that enhancing solder joint reliability under challenging operating conditions.The findings offer valuable guidance for researchers,engineers,and practitioners involved in electronics,engineering,and related fields,fostering advancements in solder joint reliability and performance.

Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

A Dual-Task Learning Approach for Bearing Anomaly Detection and State Evaluation of Safe Region

Predictive maintenance has emerged as an effective tool for curbing maintenance costs,yet prevailing research predominantly concentrates on the abnormal phases.Within the ostensibly stable healthy phase,the reliance on anomaly detection to preempt equipment malfunctions faces the challenge of sudden anomaly discernment.To address this challenge,this paper proposes a dual-task learning approach for bearing anomaly detection and state evaluation of safe regions.The proposed method transforms the execution of the two tasks into an optimization issue of the hypersphere center.By leveraging the monotonicity and distinguishability pertinent to the tasks as the foundation for optimization,it reconstructs the SVDD model to ensure equilibrium in the model’s performance across the two tasks.Subsequent experiments verify the proposed method’s effectiveness,which is interpreted from the perspectives of parameter adjustment and enveloping trade-offs.In the meantime,experimental results also show two deficiencies in anomaly detection accuracy and state evaluation metrics.Their theoretical analysis inspires us to focus on feature extraction and data collection to achieve improvements.The proposed method lays the foundation for realizing predictive maintenance in a healthy stage by improving condition awareness in safe regions.

Shear strength degradation of gas hydrate-bearing sediment due to partial hydrate dissociation

Extraction of methane hydrate from subseafloor reservoir may potentially trigger seabed slides and induce subsidence.To address the problems,it is crucial to properly characterize the phase equilibrium condition of pore hydrate and the shear strength of the soil.As one of the key constitutive components,the phase equilibrium condition enforces a constraint over pore gas pressure,temperature and unhydrated water content.Such a constraint,however,has been traditionally ignored in analyzing the mechanical behavior of hydrate-bearing soil.In this paper,a series of stepwise hydrate dissociation tests was performed,and the phase equilibrium condition of pore hydrate was determined,providing an effective way to evaluate the unhydrated water content during hydrate dissociation.Meanwhile,a series of direct shear tests was also conducted to explore the shear strength characteristics of the soil.It is shown that the shear strength of the hydrate-bearing soil can be significantly influenced by pore gas pressure,unhydrated water content,hydrate saturation and several other factors.In particular,the measured shear strength depends upon the initial water content of the sample,pointing to a potential problem that the shear strength could be wrongly determined if not properly interpreted.A shear strength criterion,which enforces the equilibrium condition of pore hydrate,is developed for hydrate-bearing soil,establishing a link between the equilibrium condition and the shear strength.The proposed equation describes well the shear strength characteristics of hydrate-bearing soils,remarkably unifying the effects of pore pressure,temperature,water content and hydrate saturation.

INCOMPRESSIBLE LIMIT OF IDEAL MAGNETOHYDRODYNAMICS IN A DOMAIN WITH BOUNDARIES

We study the incompressible limit of classical solutions to compressible ideal magneto-hydrodynamics in a domain with a flat boundary.The boundary condition is characteristic and the initial data is general.We first establish the uniform existence of classical solutions with respect to the Mach number.Then,we prove that the solutions converge to the solution of the incompressible MHD system.In particular,we obtain a stronger convergence result by using the dispersion of acoustic waves in the half space.

Oscillation properties of eigenfunctions for Sturm-Liouville problems with interface conditions via Prufer transformation

A class of Sturm-Liouville problems with discontinuity is studied in this paper.The oscillation properties of eigenfunctions for Sturm-Liouville problems with interface conditions are obtained.The main method used in this paper is based on Prufer transformation,which is different from the classical ones.Moreover,we give two examples to verify our main results.

Effect of Low pH on Forming Process of Desulfurization Gypsum Composite Boards Strengthened by Melamine-formaldehyde Resin

Through exploring the effects of low pH on the composite system of desulfurization gypsum(DG)enhanced by melamine-formaldehyde resin(MF),it is found that the inducing of sulfate-ion,in contrast to chloride and oxalate ions,favors the longitudinal growth of the crystalline form of the hydration product,which was relatively simple and had the highest length to width(L/D)ratio.At the same time,MF can also improve L/D ratio of gypsum hydration products,which favors the formation of hydrated whiskers.Finally,in a composite system composed of hemihydrate gypsum,MF,and glass fibers,when dilute sulfuric acid was used to regulate pH=3-4,the tight binding formed among the components of the composite system compared to pH=5-6.The hydration product of gypsum adheres tightly to glass fiber surface and produces a good cross-linking and binding effect with MF.The flexural strength,compressive strength,elastic modulus,and water absorption of the desulphurized gypsum composite board is 22.7 MPa,39.8 MPa,5608 MPa,and 1.8%,respectively.

Improving autoencoder-based unsupervised damage detection in uncontrolled structural health monitoring under noisy conditions

Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enhance the performance of guided wave damage detection in noisy environments is crucial.This paper introduces a local temporal principal component analysis(PCA)reconstruction approach for denoising guided waves prior to implementing unsupervised damage detection,achieved through novel autoencoder-based reconstruction.Experimental results demonstrate that the proposed denoising method significantly enhances damage detection performance when guided waves are contaminated by noise,with SNR values ranging from 10 to-5 dB.Following the implementation of the proposed denoising approach,the AUC score can elevate from 0.65 to 0.96 when dealing with guided waves corrputed by noise at a level of-5 dB.Additionally,the paper provides guidance on selecting the appropriate number of components used in the denoising PCA reconstruction,aiding in the optimization of the damage detection in noisy conditions.

Numerical investigation of geostress influence on the grouting reinforcement effectiveness of tunnel surrounding rock mass in fault fracture zones

Grouting is a widely used approach to reinforce broken surrounding rock mass during the construction of underground tunnels in fault fracture zones,and its reinforcement effectiveness is highly affected by geostress.In this study,a numerical manifold method(NMM)based simulator has been developed to examine the impact of geostress conditions on grouting reinforcement during tunnel excavation.To develop this simulator,a detection technique for identifying slurry migration channels and an improved fluid-solid coupling(FeS)framework,which considers the influence of fracture properties and geostress states,is developed and incorporated into a zero-thickness cohesive element(ZE)based NMM(Co-NMM)for simulating tunnel excavation.Additionally,to simulate coagulation of injected slurry,a bonding repair algorithm is further proposed based on the ZE model.To verify the accuracy of the proposed simulator,a series of simulations about slurry migration in single fractures and fracture networks are numerically reproduced,and the results align well with analytical and laboratory test results.Furthermore,these numerical results show that neglecting the influence of geostress condition can lead to a serious over-estimation of slurry migration range and reinforcement effectiveness.After validations,a series of simulations about tunnel grouting reinforcement and tunnel excavation in fault fracture zones with varying fracture densities under different geostress conditions are conducted.Based on these simula-tions,the influence of geostress conditions and the optimization of grouting schemes are discussed.

BILL Strategy:Points to Consider During the Performance and Interpretation of Critical Care Echocardiography

The growing utilization of critical care echocardiography(CCE) by clinicians necessitates a meticulous review of clinical conditions in critically ill patients, both before and during the examination. The reviewing process of clinical conditions minimizes the risk of overlooking or misinterpreting crucial findings. This article proposes a comprehensive strategy, namely BILL strategy, to integrate into the CCE protocol, where "B" represents baseline respiratory and hemodynamic support, "I" signifies information gleaned from invasive monitoring, including central venous pressure and thermodilution-derived cardiac output, the first "L" denotes laboratory results such as central venous oxygen saturation, troponin, and brain natriuretic peptide, and the second "L" refers to lung ultrasound data. Combining the BILL strategy with CCE can enhance comprehensive understanding of critical conditions, potentially leading to improved diagnostic accuracy and patient outcomes.

The deterministic condition for the ground reaction force acting point on the combined knee valgus and tibial internal rotation moments in early phase of cutting maneuvers in female athletes

Background:Combined knee valgus and tibial internal rotation(VL+IR)moments have been shown to stress the anterior cruciate ligament(ACL)in several in vitro cadaveric studies.To utilize this knowledge for non-contact ACL injury prevention in sports,it is necessary to elucidate how the ground reaction force(GRF)acting point(center of pressure(CoP))in the stance foot produces combined knee VL+IR moments in risky maneuvers,such as cuttings.However,the effects of the GRF acting point on the development of the combined knee VL+IR moment in cutting are still unknown.Methods:We first established the deterministic mechanical condition that the CoP position relative to the tibial rotational axis differentiates the GRF vector’s directional probability for developing the combined knee VL+IR moment,and theoretically predicted that when the CoP is posterior to the tibial rotational axis,the GRF vector is more likely to produce the combined knee VL+IR moment than when the CoP is anterior to the tibial rotational axis.Then,we tested a stochastic aspect of our theory in a lab-controlled in vivo experiment.Fourteen females performed 60˚cutting under forefoot/rearfoot strike conditions(10 trials each).The positions of lower limb markers and GRF data were measured,and the knee moment due to GRF vector was calculated.The trials were divided into anterior-and posterior-CoP groups depending on the CoP position relative to the tibial rotational axis at each 10 ms interval from 0 to 100 ms after foot strike,and the occurrence rate of the combined knee VL+IR moment was compared between trial groups.Results:The posterior-CoP group showed significantly higher occurrence rates of the combined knee VL+IR moment(maximum of 82.8%)at every time point than those of the anterior-CoP trials,as theoretically predicted by the deterministic mechanical condition.Conclusion:The rearfoot strikes inducing the posterior CoP should be avoided to reduce the risk of non-contact ACL injury associated with the combined knee VL+IR stress.

A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders

Wayside monitoring is a promising cost-effective alternative to predict damage in the rolling stock. The main goal of this work is to present an unsupervised methodology to identify out-of-roundness(OOR) damage wheels, such as wheel flats and polygonal wheels. This automatic damage identification algorithm is based on the vertical acceleration evaluated on the rails using a virtual wayside monitoring system and involves the application of a two-step procedure. The first step aims to define a confidence boundary by using(healthy) measurements evaluated on the rail constituting a baseline. The second step of the procedure involves classifying damage of predefined scenarios with different levels of severities. The proposed procedure is based on a machine learning methodology and includes the following stages:(1) data collection,(2) damage-sensitive feature extraction from the acquired responses using a neural network model, i.e., the sparse autoencoder(SAE),(3) data fusion based on the Mahalanobis distance, and(4) unsupervised feature classification by implementing outlier and cluster analysis. This procedure considers baseline responses at different speeds and rail irregularities to train the SAE model. Then, the trained SAE is capable to reconstruct test responses(not trained) allowing to compute the accumulative difference between original and reconstructed signals. The results prove the efficiency of the proposed approach in identifying the two most common types of OOR in railway wheels.