Soil conditioners improve Cd-contaminated farmland soil microbial communities to inhibit Cd accumulation in rice

The addition of silicon(Si)and organic fertilizers to soil conditioners can inhibit the transfer of heavy metal ions from soil to crops.However,it is not clear how Si and organic fertilizers affect soil properties and the micro-ecological environment and thereby reduce cadmium(Cd)accumulation in rice.In this study,the effects of L-type soil conditioners containing Si and organic fertilizers on bacterial and fungal community diversity,soil pH,organic matter,and available Si were analyzed with field experiments at two sites in Liuzhou City and Hezhou City,respectively,in Guangxi,China.With the increase of Si and organic fertilizer content in soil conditioner,rice yield respectively increased by 16.8–25.8 and 6.8–13.1%,and rice Cd content decreased significantly by 8.2–21.1 and 10.8–40.6%,respectively,at the two experimental sites.Soil microbiome analysis showed that the increase in abundance of Firmicutes and Actinobacteriota bacteria associated with Cd adsorption and sequestration,and Basidiomycota fungal populations associated with degradation of macromolecules favored the inhibition of soil Cd activity(soil exchangeable Cd decreased by 14.4–14.8 and 18.1–20.6%).This was associated with an increase in organic matter and Si content caused by applying soil conditioners.In conclusion,L-type soil conditioners,rich in Si and organic fertilizer,can reduce soil Cd bioavailability by regulating the dominant Cd passivating flora in the soil and ultimately reduce Cd accumulation in rice.

Effects of Combined Application of Biochar-based Organic Fertilizer and Reduced Nitrogen Fertilizer on Soil Enzyme Activity and Yield of Purple Cabbage(Brassica oleracea var.capita rubra)in Yuanmou County

[Objectives]In response to the issue of soil improvement in Yuanmou County,the effects of combined application of biochar-based organic fertilizer and reduced nitrogen fertilizer on soil nutrients,soil enzyme activity,and yield of purple cabbage(Brassica oleracea var.capita rubra)were investigated in the field base of Institute of Thermal Zone Ecological Agriculture,Yunnan Academy of Agricultural Sciences in Yuanmou County.[Methods]A total of 13 treatments were set up by applying biochar-based organic fertilizer at three levels of 15,30 and 45 t/hm^(2)(T_(1),T_(2),T_(3)),combined with top application of nitrogen fertilizer(urea)at four levels:375(N_1),300(N_(2)),225(N_(3))and 0 kg/hm^(2),with non-fertilizing treatment as control check(CK),in order to explore the optimal ratio for the combined application of biochar-based organic fertilizer with nitrogen fertilizer.[Results]The application of biochar-based organic fertilizer could significantly improve soil nutrients,enzyme activity,and purple cabbage yield.The improvement effect of combined application with nitrogen fertilizer was higher than that of single application of biochar-based organic fertilizer,and the improvement effect was enhanced with the application amount of biochar-based organic fertilizer increasing.The contents of organic matter and total nitrogen were the highest in treatment T_(3)N_(3),of which the values increased by 81.39%and 56.09%compared with the CK,respectively.The contents of soil hydrolyzable nitrogen,available phosphorus,and available potassium were all the highest under treatment T_(3)N_(2),with increases of 92.76%,171.01%and 235.50%,respectively.There was a significant positive correlation between the activity of soil catalase,urease,and sucrase and organic matter,total nitrogen,and available nutrients.The overall soil enzyme activity was relatively higher in treatment T_(3)N_(2).The yield of purple cabbage treated with biochar-based organic fertilizer combined with nitrogen fertilizer could reach 85750 kg/hm^(2),which was 94.78%higher than that treated with biochar-based organic fertilizer alone.Based on comprehensive analysis,the optimal combination ratio was 45 t/hm^(2)of biochar-based organic fertilizer and 300 kg/hm^(2)of urea(T_(3)N_(2)).[Conclusions]This study provides data support for the promotion of biochar-based organic fertilizers and reduced fertilizer in agricultural soil in the Dam area of Yuanmou County.

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.

Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system(DGs)that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner(UPQC).In addition to supplying active power to the utility grid,the system of hybrid wind photovoltaic functions as a UPQC,compensating reactive power and suppressing the harmonic load currents.Additionally,the load is supplied with harmonic-free,balanced and regulated output voltages.Since PVWind-UPQC is established on a dual compensation scheme,the series inverter works like a sinusoidal current source,while the parallel inverter works like a sinusoidal voltage source.Consequently,a smooth alteration from interconnected operating modes to island operating modes and vice versa can be achieved without load voltage transients.Since PV-Wind-UPQC inverters handle the energy generated through the hybrid wind photovoltaic system and the energy demanded through the load,the converters should be sized cautiously.A detailed study of the flow of power via the PV-Wind-UPQC is imperative to gain a complete understanding of the system operation and the proper design of the converters.Thus,curves that allow the sizing of the power converters according to the power flow via the converters are presented and discussed.Simulation results are presented to assess both steady state and dynamic performances of the grid connected hybrid system of PV-Wind-UPQC.This investigation is verified by simulating and analyzing the results with Matlab/Simulink.

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.

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.

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.

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.

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.

Intelligent pavement condition survey:Overview of current researches and practices

Automated pavement condition survey is of critical importance to road network management.There are three primary tasks involved in pavement condition surveys,namely data collection,data processing and condition evaluation.Artificial intelligence(AI)has achieved many breakthroughs in almost every aspect of modern technology over the past decade,and undoubtedly offers a more robust approach to automated pavement condition survey.This article aims to provide a comprehensive review on data collection systems,data processing algorithms and condition evaluation methods proposed between 2010 and 2023 for intelligent pavement condition survey.In particular,the data collection system includes AI-driven hardware devices and automated pavement data collection vehicles.The AI-driven hardware devices including right-of-way(ROW)cameras,ground penetrating radar(GPR)devices,light detection and ranging(LiDAR)devices,and advanced laser imaging systems,etc.These different hardware components can be selectively mounted on a vehicle to simultaneously collect multimedia information about the pavement.In addition,this article pays close attention to the application of artificial intelligence methods in detecting pavement distresses,measuring pavement roughness,identifying pavement rutting,analyzing skid resistance and evaluating structural strength of pavements.Based upon the analysis of a variety of the state-of-the-art artificial intelligence methodologies,remaining challenges and future needs with respect to intelligent pavement condition survey are discussed eventually.

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.

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.

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.

Condition indices for rigid pavements: A comparative analysis of state DOTs using Michigan PMS data

Pavement infrastructure is vital in providing services and links between various sectors of society. Therefore, thepreservation and maintenance of these roads are critical to attaining a pavement network in good conditionthroughout its service life. Various performance indicators like the international roughness index (IRI), pavementcondition index (PCI), and present serviceability rating (PSR) have been used by the state department of transportation (DOT) and highway agencies for evaluating pavement surface conditions and planning future maintenance strategies. Limited data availability, multiple distresses depending on region, lack of correlation of thesecondition indices to maintenance strategies, and data collection limitations pose a challenge for applying theseindices to local conditions. This paper compares condition indices of different states for rigid pavements. Further,using a specific condition index for local conditions is also highlighted. For this purpose, five states and theircorresponding condition indices were evaluated and compared to the Michigan DOT distress index (DI). Thesestates include Virginia, Minnesota, North Dakota, Louisiana, and Oregon. The corresponding distresses of eachcondition index were converted to make them compatible with the MDOT DI. This study used the MDOT'spavement management system (PMS) database to evaluate each condition index for 433 rigid pavement sections.Each distress index was plotted against MDOT DI and compared using a paired t-test. Results show that thecondition indices of Virginia and Minnesota are comparable to DI in terms of the Spearman correlation value. Thet-test results show that except for Virgina, condition indices from other states statistically differ from DI.Therefore, one can't use those directly for local conditions in Michigan. This paper presents the evaluation anddata requirements for each condition index and its impact on selecting a maintenance treatment.

Least Square Finite Element Model for Analysis of Multilayered Composite Plates under Arbitrary Boundary Conditions

Laminated composites are widely used in many engineering industries such as aircraft, spacecraft, boat hulls, racing car bodies, and storage tanks. We analyze the 3D deformations of a multilayered, linear elastic, anisotropic rectangular plate subjected to arbitrary boundary conditions on one edge and simply supported on other edge. The rectangular laminate consists of anisotropic and homogeneous laminae of arbitrary thicknesses. This study presents the elastic analysis of laminated composite plates subjected to sinusoidal mechanical loading under arbitrary boundary conditions. Least square finite element solutions for displacements and stresses are investigated using a mathematical model, called a state-space model, which allows us to simultaneously solve for these field variables in the composite structure’s domain and ensure that continuity conditions are satisfied at layer interfaces. The governing equations are derived from this model using a numerical technique called the least-squares finite element method (LSFEM). These LSFEMs seek to minimize the squares of the governing equations and the associated side conditions residuals over the computational domain. The model is comprised of layerwise variables such as displacements, out-of-plane stresses, and in- plane strains, treated as independent variables. Numerical results are presented to demonstrate the response of the laminated composite plates under various arbitrary boundary conditions using LSFEM and compared with the 3D elasticity solution available in the literature.

Statistical Models for Condition Monitoring and State of Health Estimation of Lithium-Ion Batteries for Ships

Battery systems are increasingly being used for powering ocean going ships,and the number of fully electric or hybrid ships relying on battery power for propulsion is growing.To ensure the safety of such ships,it is important to monitor the available energy that can be stored in the batteries,and classification societies typically require the state of health(SOH)to be verified by independent tests.This paper addresses statistical modeling of SOH for maritime lithium-ion batteries based on operational sensor data.Various methods for sensor-based,data-driven degradation monitoring will be presented,and advantages and challenges with the different approaches will be discussed.The different approaches include cumulative degradation models and snapshot models,models that need to be trained and models that need no prior training,and pure data-driven models and physics-informed models.Some of the methods only rely on measured data,such as current,voltage,and temperature,whereas others rely on derived quantities such as state of charge.Models include simple statistical models and more complicated machine learning techniques.Insight from this exploration will be important in establishing a framework for data-driven diagnostics and prognostics of maritime battery systems within the scope of classification societies.

Absorbing Boundary Conditions for Simulating Water Waves Near Solid Bodies

The objective of this paper is to present a new method for designing absorbing or non-reflective boundary conditions (ABC) or (NRBC), illustrated by the case study of the modelling of a solid body in water, specifically the capillary gravity waves generated by its motion at the surface. The study analyses the flow of an inviscid, barotropic, and compressible fluid around the stationary solid body. The dynamic behaviour of the fluid is analysed using a two-dimensional coupled Neumann-Kelvin model extended with capillarity and inertia terms. For computational purposes, it is necessary to truncate the unbounded spatial domain with artificial boundaries and then introduce appropriate absorbing boundary conditions. The propagation of short wavelength waves in a convective fluid medium with significant differences in properties between the interior and the surface of the fluid presents a number of difficulties in the design of these conditions. The results are illustrated numerically and commented upon.

Existence of Entropy Solution for Degenerate Parabolic-Hyperbolic Problem Involving p(x)-Laplacian with Neumann Boundary Condition

We consider a strongly non-linear degenerate parabolic-hyperbolic problem with p(x)-Laplacian diffusion flux function. We propose an entropy formulation and prove the existence of an entropy solution.

Temporally Preserving Latent Variable Models:Offline and Online Training for Reconstruction and Interpretation of Fault Data for Gearbox Condition Monitoring

Latent variable models can effectively determine the condition of essential rotating machinery without needing labeled data.These models analyze vibration data via an unsupervised learning strategy.Temporal preservation is necessary to obtain an informative latent manifold for the fault diagnosis task.In a temporalpreserving context,two approaches exist to develop a condition-monitoring methodology:offline and online.For latent variable models,the available training modes are not different.While many traditional methods use offline training,online training can dynamically adjust the latent manifold,possibly leading to better fault signature extraction from the vibration data.This study explores online training using temporal-preserving latent variable models.Within online training,there are two main methods:one focuses on reconstructing data and the other on interpreting the data components.Both are considered to evaluate how they diagnose faults over time.Using two experimental datasets,the study confirms that models from both training modes can detect changes in machinery health and identify faults even under varying conditions.Importantly,the complementarity of offline and online models is emphasized,reassuring their versatility in fault diagnostics.Understanding the implications of the training approach and the available model formulations is crucial for further research in latent variable modelbased fault diagnostics.