In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→...In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→∞)x′(t)e^(t)=0,where t_(0) and ψ_(0) are real constants,φ(s)=s/√1−s^(2),s∈R with s∈(−1,1),f:[t_(0),∞)×R→R satisfies the Lipschitz or Osgood-type conditions.展开更多
Cloud data sharing is an important issue in modern times.To maintain the privacy and confidentiality of data stored in the cloud,encryption is an inevitable process before uploading the data.However,the centralized ma...Cloud data sharing is an important issue in modern times.To maintain the privacy and confidentiality of data stored in the cloud,encryption is an inevitable process before uploading the data.However,the centralized management and transmission latency of the cloud makes it difficult to support real-time processing and distributed access structures.As a result,fog computing and the Internet of Things(IoT)have emerged as crucial applications.Fog-assisted proxy re-encryption is a commonly adopted technique for sharing cloud ciphertexts.It allows a semitrusted proxy to transforma data owner’s ciphertext into another re-encrypted ciphertext intended for a data requester,without compromising any information about the original ciphertext.Yet,the user revocation and cloud ciphertext renewal problems still lack effective and secure mechanisms.Motivated by it,we propose a revocable conditional proxy re-encryption scheme offering ciphertext evolution(R-CPRE-CE).In particular,a periodically updated time key is used to revoke the user’s access privileges while an access condition prevents a malicious proxy from reencrypting unauthorized ciphertext.We also demonstrate that our scheme is provably secure under the notion of indistinguishability against adaptively chosen identity and chosen ciphertext attacks in the random oracle model.Performance analysis shows that our scheme reduces the computation time for a complete data access cycle from an initial query to the final decryption by approximately 47.05%compared to related schemes.展开更多
The carbonylation of amines offers a promising route for synthesizing N-substituted carbamates with high atom economy.However,conventional catalysts exhibit limited catalytic efficiency,and the underlying proton trans...The carbonylation of amines offers a promising route for synthesizing N-substituted carbamates with high atom economy.However,conventional catalysts exhibit limited catalytic efficiency,and the underlying proton transfer mechanism remains elusive.Herein,we reported a metal-free,room-temperature strategy utilizing 1,5,7-triazabicyclo[4.4.0]dec-5-ene(TBD)as a dual hydrogen bond catalyst to synergistically activate propylamine(PA)and dimethyl carbonate(DMC).This green catalytic system achieves a 10-fold acceleration in reaction rate compared to other hydrogen bonding catalysts under mild conditions.This is enabled by dual hydrogen bonding of TBD with PA and DMC,which facilitates rapid proton transfer and stabilizes tetrahedral intermediates.Theoretical calculations confirm that the dual hydrogen bond system significantly lowers activation energy compared to single hydrogen bond analogs.Furthermore,it was revealed that the hydrogen bonding network within the product is the primary factor responsible for the sluggish reaction rate.This study demonstrates the effectiveness of a dual hydrogen bond system in accelerating the carbonylation of amines and provides a green route to access carbamates.展开更多
The dynamic characteristics of the track system can directly affect its service performance and failure process.To explore the load characteristics and dynamic response of the track system under the dynamic loads from...The dynamic characteristics of the track system can directly affect its service performance and failure process.To explore the load characteristics and dynamic response of the track system under the dynamic loads from the rack vehicle in traction conditions,a systematic test of the track subsystem was carried out on a large-slope test line.In the test,the bending stress of the rack teeth,the wheel-rail forces,and the acceleration of crucial components in the track system were measured.Subsequently,a detailed analysis was conducted on the tested signals of the rack railway track system in the time domain and the time-frequency domains.The test results indicate that the traction force significantly affects the rack tooth bending stress and the wheel-rail forces.The vibrations of the track system under the traction conditions are mainly caused by the impacts generated from the gear-rack engagement,which are then transferred to the sleepers,the rails,and the ballast beds.Furthermore,both the maximum stress on the racks and the wheel-rail forces measured on the rails remain below their allowable values.This experimental study evaluates the load characteristics and reveals the vibration characteristics of the rack railway track system under the vehicle’s ultimate load,which is very important for the load-strengthening design of the key components such as racks and the vibration and noise reduction of the track system.展开更多
Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the ...Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the post-earthquake period. Therefore, establishing a calculation method for the post-earthquake train speed threshold that considers the influence of different site characteristics is of great engineering significance. Taking the CRTS Ⅲ slab track as the research object, this study is based on the track irregularity root mean square rate(TRR), which the authors proposed earlier to quantify the track regularity level. Using the nonlinear least squares fitting method, the mapping relationship between the TRR and the postearthquake train running performance indicators on bridges is established. Furthermore, the influence of laws governing site categories and train speeds on post-earthquake train running performance on bridges is analyzed, and a train speed threshold for bridges based on running performance under random site conditions is proposed. The research results indicate that all train running performance indicators increase significantly with the increase of train operating speed;different site categories have a significant impact on post-earthquake track residual deformation and train running stability. The greater the amplitude of postearthquake track alignment residual deformation, the lower the threshold for the stable running speed of trains after the earthquake, with the speed threshold decreasing by up to 20%. The research outcomes can provide technical references for the post-earthquake safe operation and maintenance of high-speed railway bridges under complex site conditions, as well as the formulation of targeted train speed control schemes.展开更多
In this paper,we study the asymptotic behavior of the micropolar fluid flow through a thin domain,assuming zero Dirichlet boundary condition on the top boundary,which is rapidly oscillating,and non-standard boundary c...In this paper,we study the asymptotic behavior of the micropolar fluid flow through a thin domain,assuming zero Dirichlet boundary condition on the top boundary,which is rapidly oscillating,and non-standard boundary conditions on the flat bottom.Assuming“Reynolds roughness regime”,in which the thickness of the domain is very small compared to the wavelength of the roughness(i.e.a very slight roughness),we rigorously derive a generalized Reynolds equation for pressure,clearly showing the roughness-induced effects.Moreover,we give expressions for the average velocity and microrotation.展开更多
The main purpose of using geothermal energy piles(GEPs)is to enable the exploitation of geothermal energy for meeting the heating/cooling demands of buildings efficiently.However,the installation process of convention...The main purpose of using geothermal energy piles(GEPs)is to enable the exploitation of geothermal energy for meeting the heating/cooling demands of buildings efficiently.However,the installation process of conventional GEPs is inconvenient compared with that of traditional foundation piles.The pre-bored grouted planted geothermal energy pile(PGP GEP)is an innovative technology to simplify the installation process.Most investigations of in-situ experiments for conventional GEPs have focused on summer conditions.An in-situ test for a PGP GEP was conducted to analyze the temperature changes and thermo-mechanical characteristics under winter conditions.The results show that the average temperature of the pile decreased by 5.1℃,and the pile exhibited a general trend of high temperatures at both ends and low temperatures in the middle.In mechanics,strong pile end restraints resulted in smaller observed axial strain and higher axial thermal-induced force in the pile ends than at the middle of the pile.展开更多
To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervis...To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.展开更多
Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of...Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.展开更多
BEIJING,Feb.25(Xinhua)-In a territory more than twice the size of the European Union and where per capita GDP varies up to fourfold across provincia level regions,the challenge of modernizing China with the right solu...BEIJING,Feb.25(Xinhua)-In a territory more than twice the size of the European Union and where per capita GDP varies up to fourfold across provincia level regions,the challenge of modernizing China with the right solutions for diverse localities has become a test of governance wisdom.展开更多
Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC rec...Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.展开更多
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of...Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.展开更多
Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual pat...Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual patient responses towards different drugs.This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations.Methods:Tumor and adjacent tissues from female breast cancer patients were collected during surgery.Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models.The obtained patient-derived conditional reprogramming breast cancer(CRBC)cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres to form 3D culture models.Comparisons between 2D and 3D models were made using immunohistochemistry(tumor markers),MTS assays(cell viability),flow cytometry(apoptosis),transwell assays(migration),and Western blotting(protein expression).Drug sensitivity tests were conducted to evaluate patient-specific responses to anti-cancer agents.Results:2D and 3D culture models were successfully established using samples from eight patients.The 3D models retained histological and marker characteristics of the original tumors.Compared to 2D cultures,3D models exhibited increased apoptosis,enhanced drug resistance,elevated stem cell marker expression,and greater migration ability—features more reflective of in vivo tumor behavior.Conclusion:Patient-derived 3D CRBC models effectively mimic the in vivo tumor microenvironment and demonstrate stronger resistance to anti-cancer drugs than 2D models.These hydrogel-based models offer a cost-effective and clinically relevant platform for drug screening and personalized breast cancer treatment.展开更多
Estimating the properties of foam-conditioned clay soils is important for both conditioning and recycling goals in earth pressure balance(EPB)shield tunneling.In this study,the vacuum dewatering behaviors of foam-cond...Estimating the properties of foam-conditioned clay soils is important for both conditioning and recycling goals in earth pressure balance(EPB)shield tunneling.In this study,the vacuum dewatering behaviors of foam-conditioned clay soils were investigated,with their potential use as an alternative means to assess foam optimization being examined.A series of laboratory and fieldtests was conducted,including vacuum dewatering tests that considered the effects of filtrationtime and pressure,vane shear tests,and improved cone pullout tests under different gravimetric water content(w)and foam injection ratio(FIR)conditions.It was found that the filtrate loss(FL),which characterizes dewaterability,was increased by extended vacuum filtrationtime and elevated pressure.While increases in w and FIR enhanced FL,reductions were observed in the undrained shear strength(cu),tangential adhesion stress(Fs),and normal adhesion stress(Fn).Furthermore,a linear decrease in FL with increasing mechanical indices(cu,Fs,and Fn)was demonstrated by both laboratory and fielddata fittingresults,regardless of w,FIR,and dewatering conditions.This study provides novel insights into the understanding of vacuum dewatering mechanisms in foam-conditioned clay soils,while a simple approach is proposed for evaluating foam conditioning effectiveness in EPB shield tunneling applications.展开更多
It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typica...It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.展开更多
The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To...The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To develop an efficient flow field reconstruction model for this,we present an Improved Conditional Denoising Diffusion Generative Adversarial Network(ICDDGAN),which integrates Conditional Denoising Diffusion Probabilistic Models(CDDPMs)with Style GAN,and introduce a reconstruction discrimination mechanism and dynamic loss weight learning strategy.We establish the Mach number flow field dataset by numerical simulation at various backpressures for the mode transition process from turbine mode to ejector ramjet mode at Mach number 2.5.The proposed ICDDGAN model,given only sparse parameter information,can rapidly generate high-quality Mach number flow fields without a large number of samples for training.The results show that ICDDGAN is superior to CDDGAN in terms of training convergence and stability.Moreover,the interpolation and extrapolation test results during backpressure conditions show that ICDDGAN can accurately and quickly reconstruct Mach number fields at various tunnel slice shapes,with a Structural Similarity Index Measure(SSIM)of over 0.96 and a Mean-Square Error(MSE)of 0.035%to actual flow fields,reducing time costs by 7-8 orders of magnitude compared to Computational Fluid Dynamics(CFD)calculations.This can provide an efficient means for rapid computation of complex flow fields.展开更多
In the present study,a combination of pulsed discharge plasma and TiO2（plasma/TiO2）has been developed in order to study the activity of TiO2by varying the discharge conditions of pulsed voltage,discharge mode,air fl...In the present study,a combination of pulsed discharge plasma and TiO2（plasma/TiO2）has been developed in order to study the activity of TiO2by varying the discharge conditions of pulsed voltage,discharge mode,air flow rate and solution conductivity.Phenol was used as the chemical probe to characterize the activity of TiO2in a pulsed discharge system.The experimental results showed that the phenol removal efficiency could be improved by about 10%by increasing the applied voltage.The phenol removal efficiency for three discharge modes in the plasma-discharge-alone system was found to be highest in the spark mode,followed by the spark–streamer mode and finally the streamer mode.In the plasma/TiO2system,the highest catalytic effect of TiO2was observed in the spark–streamer discharge mode,which may be attributed to the favorable chemical and physical effects from the spark–streamer discharge mode,such as ultraviolet light,O3,H2O2,pyrolysis,shockwaves and high-energy electrons.Meanwhile,the optimal flow rate and conductivity were 0.05 m^3l^（-1）and 10μS cm^（-1）,respectively.The main phenolic intermediates were hydroquinone,catechol,and p-benzoquinone during the discharge treatment process.A different phenol degradation pathway was observed in the plasma/TiO2system as compared to plasma alone.Analysis of the reaction intermediates demonstrated that p-benzoquinone reduction was selectively catalyzed on the TiO2surface.The effective decomposition of phenol constant（De）increased from 74.11%to 79.16%when TiO2was added,indicating that higher phenol mineralization was achieved in the plasma/TiO2system.展开更多
Numerical simulation based on computational fluid dynamics （CFD） is a useful approach for quantitatively investigating the underlying thermal-mechanical conditions during FSW, such as temperature field and material ...Numerical simulation based on computational fluid dynamics （CFD） is a useful approach for quantitatively investigating the underlying thermal-mechanical conditions during FSW, such as temperature field and material deformation field. One of the critical issues in CFD simulation of FSW is the use of the frictional boundary condition, which represents the friction between the welding tool and the workpiece in the numerical models. In this study, three-dimensional numerical simulation is conducted to analyze the heat transfer and plastic deformation behaviors during the FSW of AA2024. For comparison purposes, both the boundary velocity （BV） models and the boundary shear stress （BSS） models are employed in order to assess their performances in predicting the temperature and material deformation in FSW. It is interesting to note that different boundary conditions yield similar predictions on temperature, but quite different predictions on material deformation. The numerical predictions are compared with the experimental results. The predicted deformation zone geometry by the BSS model is consistent with the experimental results while there is large difference between the predictions by the BV models and the experimental measurements. The fact that the BSS model yields more reasonable predictions on the deformation zone geometry is attributed to its capacity to automatically adjust the contact state at the tool/workpiece interface. Based on the favorable predictions on both the temperature field and the material deformation field, the BSS model is suggested to have a better performance in numerical simulation of FSW than the BV model.展开更多
Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources.The wind turbine is an essential system used to change kinetic energy into electrical e...Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources.The wind turbine is an essential system used to change kinetic energy into electrical energy.Wind turbine blades,in particular,require a competitive condition inspection approach as it is a significant component of the wind turbine system that costs around 20-25 percent of the total turbine cost.The main objective of this study is to differentiate between various blade faults which affect the wind turbine blade under operating conditions using a machine learning approach through histogram features.In this study,blade bend,hub-blade loose connection,blade erosion,pitch angle twist,and blade cracks were simulated on the blade.This problem is formulated as a machine learning problem which consists of three phases,namely feature extraction,feature selection and feature classification.Histogram features are extracted from vibration signals and feature selection was carried out using the J48 decision tree algorithm.Feature classification was performed using 15 tree classifiers.The results of the machine learning classifiers were compared with respect to their accuracy percentage and a better model is suggested for real-time monitoring of a wind turbine blade.展开更多
This article investigates the comparative analysis of the facility present condition (FPC) of selected health and educational buildings in Rivers State. State funded hospitals and schools (14 functional out of 23 gene...This article investigates the comparative analysis of the facility present condition (FPC) of selected health and educational buildings in Rivers State. State funded hospitals and schools (14 functional out of 23 general hospitals and 2 out of 3 tertiary schools) were selected for the study. The general hospital is a secondary health facility designed to bring health care services close to citizens especially those in rural communities. These facilities were inherited from the colonial masters in 1960. An assessment visit in2016 found the 23 general hospitals completely dilapidated and abandoned. However, rehabilitation intervention was carried out by the government in 2020. This scenario was quite different with the schools. Thus, this study is to increase the awareness of facility operators on building maintenance. A purposive sampling technique was used in selecting the hospitals and schools, while simple random sampling was adopted for questionnaire distribution to 300 respondents. The instrument reliability and validity were ascertained using Cronbach Alpha and face validity. The instrument obtained information about the status of the facility present condition. SPSS and Microsoft Xlstat were used to obtain the mean and frequency distribution of the responses. Comparative analysis was conducted to understand the FPC of the schools and hospitals. Z-test was deployed to ascertain if there was a significant difference in the FPC between the two institutions. Checklist was adopted to confirm the findings. The result from the survey showed that schools have better FPC than hospitals.展开更多
基金Supported by the National Natural Science Foundation of China(Grant Nos.12361040,12061064)the National Science Foundation of Gansu Province(Grant No.22JR5RA264)State Scholarship Fund(Grant No.20230862021).
文摘In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→∞)x′(t)e^(t)=0,where t_(0) and ψ_(0) are real constants,φ(s)=s/√1−s^(2),s∈R with s∈(−1,1),f:[t_(0),∞)×R→R satisfies the Lipschitz or Osgood-type conditions.
基金supported in part by the National Science and Technology Council of Republic of China under the contract numbers NSTC 114-2221-E-019-055-MY2NSTC 114-2221-E-019-069.
文摘Cloud data sharing is an important issue in modern times.To maintain the privacy and confidentiality of data stored in the cloud,encryption is an inevitable process before uploading the data.However,the centralized management and transmission latency of the cloud makes it difficult to support real-time processing and distributed access structures.As a result,fog computing and the Internet of Things(IoT)have emerged as crucial applications.Fog-assisted proxy re-encryption is a commonly adopted technique for sharing cloud ciphertexts.It allows a semitrusted proxy to transforma data owner’s ciphertext into another re-encrypted ciphertext intended for a data requester,without compromising any information about the original ciphertext.Yet,the user revocation and cloud ciphertext renewal problems still lack effective and secure mechanisms.Motivated by it,we propose a revocable conditional proxy re-encryption scheme offering ciphertext evolution(R-CPRE-CE).In particular,a periodically updated time key is used to revoke the user’s access privileges while an access condition prevents a malicious proxy from reencrypting unauthorized ciphertext.We also demonstrate that our scheme is provably secure under the notion of indistinguishability against adaptively chosen identity and chosen ciphertext attacks in the random oracle model.Performance analysis shows that our scheme reduces the computation time for a complete data access cycle from an initial query to the final decryption by approximately 47.05%compared to related schemes.
基金financially supported by the National Key R&D Program of China(2023YFC3905400)the Clean Combustion and Low-carbon Utilization of Coal,Strategic Priority Research Program of the Chinese Academy of Sciences,Grant No.XDA 29000000.
文摘The carbonylation of amines offers a promising route for synthesizing N-substituted carbamates with high atom economy.However,conventional catalysts exhibit limited catalytic efficiency,and the underlying proton transfer mechanism remains elusive.Herein,we reported a metal-free,room-temperature strategy utilizing 1,5,7-triazabicyclo[4.4.0]dec-5-ene(TBD)as a dual hydrogen bond catalyst to synergistically activate propylamine(PA)and dimethyl carbonate(DMC).This green catalytic system achieves a 10-fold acceleration in reaction rate compared to other hydrogen bonding catalysts under mild conditions.This is enabled by dual hydrogen bonding of TBD with PA and DMC,which facilitates rapid proton transfer and stabilizes tetrahedral intermediates.Theoretical calculations confirm that the dual hydrogen bond system significantly lowers activation energy compared to single hydrogen bond analogs.Furthermore,it was revealed that the hydrogen bonding network within the product is the primary factor responsible for the sluggish reaction rate.This study demonstrates the effectiveness of a dual hydrogen bond system in accelerating the carbonylation of amines and provides a green route to access carbamates.
基金supported by the National Natural Science Foundation of China(No.52388102)the Sichuan Science and Technology Program(No.2024NSFTD0011)the Fundamental Research Funds for the State Key Laboratory of Rail Transit Vehicle System of Southwest Jiaotong University(No.2023TPL-T11).
文摘The dynamic characteristics of the track system can directly affect its service performance and failure process.To explore the load characteristics and dynamic response of the track system under the dynamic loads from the rack vehicle in traction conditions,a systematic test of the track subsystem was carried out on a large-slope test line.In the test,the bending stress of the rack teeth,the wheel-rail forces,and the acceleration of crucial components in the track system were measured.Subsequently,a detailed analysis was conducted on the tested signals of the rack railway track system in the time domain and the time-frequency domains.The test results indicate that the traction force significantly affects the rack tooth bending stress and the wheel-rail forces.The vibrations of the track system under the traction conditions are mainly caused by the impacts generated from the gear-rack engagement,which are then transferred to the sleepers,the rails,and the ballast beds.Furthermore,both the maximum stress on the racks and the wheel-rail forces measured on the rails remain below their allowable values.This experimental study evaluates the load characteristics and reveals the vibration characteristics of the rack railway track system under the vehicle’s ultimate load,which is very important for the load-strengthening design of the key components such as racks and the vibration and noise reduction of the track system.
基金supported by the Science and Technology Research and Development Program Project of China Railway Group Limited (Grant No.2022-Major-17)the National Natural Science Foundation of China (Grant Nos.52578619,52178180)+2 种基金the National Key Research and Development Program of China (Grant No.2022YFC3004304)the Frontier Cross Research Project of Central South University (Grant No.2023QYJC006)the Natural Science Foundation of Hunan Province Funding Project (Grant No.2023JJ40724)。
文摘Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the post-earthquake period. Therefore, establishing a calculation method for the post-earthquake train speed threshold that considers the influence of different site characteristics is of great engineering significance. Taking the CRTS Ⅲ slab track as the research object, this study is based on the track irregularity root mean square rate(TRR), which the authors proposed earlier to quantify the track regularity level. Using the nonlinear least squares fitting method, the mapping relationship between the TRR and the postearthquake train running performance indicators on bridges is established. Furthermore, the influence of laws governing site categories and train speeds on post-earthquake train running performance on bridges is analyzed, and a train speed threshold for bridges based on running performance under random site conditions is proposed. The research results indicate that all train running performance indicators increase significantly with the increase of train operating speed;different site categories have a significant impact on post-earthquake track residual deformation and train running stability. The greater the amplitude of postearthquake track alignment residual deformation, the lower the threshold for the stable running speed of trains after the earthquake, with the speed threshold decreasing by up to 20%. The research outcomes can provide technical references for the post-earthquake safe operation and maintenance of high-speed railway bridges under complex site conditions, as well as the formulation of targeted train speed control schemes.
文摘In this paper,we study the asymptotic behavior of the micropolar fluid flow through a thin domain,assuming zero Dirichlet boundary condition on the top boundary,which is rapidly oscillating,and non-standard boundary conditions on the flat bottom.Assuming“Reynolds roughness regime”,in which the thickness of the domain is very small compared to the wavelength of the roughness(i.e.a very slight roughness),we rigorously derive a generalized Reynolds equation for pressure,clearly showing the roughness-induced effects.Moreover,we give expressions for the average velocity and microrotation.
文摘The main purpose of using geothermal energy piles(GEPs)is to enable the exploitation of geothermal energy for meeting the heating/cooling demands of buildings efficiently.However,the installation process of conventional GEPs is inconvenient compared with that of traditional foundation piles.The pre-bored grouted planted geothermal energy pile(PGP GEP)is an innovative technology to simplify the installation process.Most investigations of in-situ experiments for conventional GEPs have focused on summer conditions.An in-situ test for a PGP GEP was conducted to analyze the temperature changes and thermo-mechanical characteristics under winter conditions.The results show that the average temperature of the pile decreased by 5.1℃,and the pile exhibited a general trend of high temperatures at both ends and low temperatures in the middle.In mechanics,strong pile end restraints resulted in smaller observed axial strain and higher axial thermal-induced force in the pile ends than at the middle of the pile.
基金supported by the National Natural Science Foundation of China Funded Project(Project Name:Research on Robust Adaptive Allocation Mechanism of Human Machine Co-Driving System Based on NMS Features,Project Approval Number:52172381).
文摘To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.
基金supported by the Chung-Ang University Research Grants in 2023.Alsothe work is supported by the ELLIIT Excellence Center at Linköping–Lund in Information Technology in Sweden.
文摘Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.
文摘BEIJING,Feb.25(Xinhua)-In a territory more than twice the size of the European Union and where per capita GDP varies up to fourfold across provincia level regions,the challenge of modernizing China with the right solutions for diverse localities has become a test of governance wisdom.
基金supported by the National Natural Science Foundation of China(Grant Nos.42077242 and 42171407)the Graduate Innovation Fund of Jilin University.
文摘Accurate and rapid recognition of weathering degree(WD)and groundwater condition(GC)is essential for evaluating rock mass quality and conducting stability analyses in underground engineering.Conventional WD and GC recognition methods often rely on subjective evaluation by field experts,supplemented by field sampling and laboratory testing.These methods are frequently complex and timeconsuming,making it challenging to meet the rapidly evolving demands of underground engineering.Therefore,this study proposes a rock non-geometric parameter classification network(RNPC-net)to rapidly achieve the recognition and mapping ofWD and GC of tunnel faces.The hybrid feature extraction module(HFEM)in RNPC-net can fully extract,fuse,and utilize multi-scale features of images,enhancing the network's classification performance.Moreover,the designed adaptive weighting auxiliary classifier(AC)helps the network learn features more efficiently.Experimental results show that RNPC-net achieved classification accuracies of 0.8756 and 0.8710 for WD and GC,respectively,representing an improvement of approximately 2%e10%compared to other methods.Both quantitative and qualitative experiments confirm the effectiveness and superiority of RNPC-net.Furthermore,for WD and GC mapping,RNPC-net outperformed other methods by achieving the highest mean intersection over union(mIOU)across most tunnel faces.The mapping results closely align with measurements provided by field experts.The application of WD and GC mapping results to the rock mass rating(RMR)system achieved a transition from conventional qualitative to quantitative evaluation.This advancement enables more accurate and reliable rock mass quality evaluations,particularly under critical conditions of RMR.
基金supported by Supported by the Scientific Research Foundation for High-Level Talents of Zhoukou Normal University(ZKNUC2024018).
文摘Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.
基金supported by the Natural Science Foundation of Guangdong Province(No.2021B1515120053)Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515140166).
文摘Background:Therapeutic responses of breast cancer vary among patients and lead to drug resistance and recurrence due to the heterogeneity.Current preclinical models,however,are inadequate for predicting individual patient responses towards different drugs.This study aimed to investigate the patient-derived breast cancer culture models for drug sensitivity evaluations.Methods:Tumor and adjacent tissues from female breast cancer patients were collected during surgery.Patient-derived breast cancer cells were cultured using the conditional reprogramming technique to establish 2D models.The obtained patient-derived conditional reprogramming breast cancer(CRBC)cells were subsequently embedded in alginate-gelatin methacryloyl hydrogel microspheres to form 3D culture models.Comparisons between 2D and 3D models were made using immunohistochemistry(tumor markers),MTS assays(cell viability),flow cytometry(apoptosis),transwell assays(migration),and Western blotting(protein expression).Drug sensitivity tests were conducted to evaluate patient-specific responses to anti-cancer agents.Results:2D and 3D culture models were successfully established using samples from eight patients.The 3D models retained histological and marker characteristics of the original tumors.Compared to 2D cultures,3D models exhibited increased apoptosis,enhanced drug resistance,elevated stem cell marker expression,and greater migration ability—features more reflective of in vivo tumor behavior.Conclusion:Patient-derived 3D CRBC models effectively mimic the in vivo tumor microenvironment and demonstrate stronger resistance to anti-cancer drugs than 2D models.These hydrogel-based models offer a cost-effective and clinically relevant platform for drug screening and personalized breast cancer treatment.
基金supported by the National Youth Top-notch Talent Support Program of China(Grant No.00389335)the National Natural Science Foundation of China(Grant No.52378392)the“Foal Eagle Program”Youth Top-notch Talent Project of Fujian Province(Grant No.00387088).
文摘Estimating the properties of foam-conditioned clay soils is important for both conditioning and recycling goals in earth pressure balance(EPB)shield tunneling.In this study,the vacuum dewatering behaviors of foam-conditioned clay soils were investigated,with their potential use as an alternative means to assess foam optimization being examined.A series of laboratory and fieldtests was conducted,including vacuum dewatering tests that considered the effects of filtrationtime and pressure,vane shear tests,and improved cone pullout tests under different gravimetric water content(w)and foam injection ratio(FIR)conditions.It was found that the filtrate loss(FL),which characterizes dewaterability,was increased by extended vacuum filtrationtime and elevated pressure.While increases in w and FIR enhanced FL,reductions were observed in the undrained shear strength(cu),tangential adhesion stress(Fs),and normal adhesion stress(Fn).Furthermore,a linear decrease in FL with increasing mechanical indices(cu,Fs,and Fn)was demonstrated by both laboratory and fielddata fittingresults,regardless of w,FIR,and dewatering conditions.This study provides novel insights into the understanding of vacuum dewatering mechanisms in foam-conditioned clay soils,while a simple approach is proposed for evaluating foam conditioning effectiveness in EPB shield tunneling applications.
基金the support from National Natural Science Foundation of China(No.52275153)the Frontier Technologies R&D Program of Jiangsu,China(No.BF2024068)+1 种基金The Fund of Prospective Layout of Scientific Research for Nanjing University of Aeronautics and Astronautics,ChinaResearch Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics),China(Nos.MCAS-I-0425K01,MCAS-I-0423G01)。
文摘It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.
文摘The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To develop an efficient flow field reconstruction model for this,we present an Improved Conditional Denoising Diffusion Generative Adversarial Network(ICDDGAN),which integrates Conditional Denoising Diffusion Probabilistic Models(CDDPMs)with Style GAN,and introduce a reconstruction discrimination mechanism and dynamic loss weight learning strategy.We establish the Mach number flow field dataset by numerical simulation at various backpressures for the mode transition process from turbine mode to ejector ramjet mode at Mach number 2.5.The proposed ICDDGAN model,given only sparse parameter information,can rapidly generate high-quality Mach number flow fields without a large number of samples for training.The results show that ICDDGAN is superior to CDDGAN in terms of training convergence and stability.Moreover,the interpolation and extrapolation test results during backpressure conditions show that ICDDGAN can accurately and quickly reconstruct Mach number fields at various tunnel slice shapes,with a Structural Similarity Index Measure(SSIM)of over 0.96 and a Mean-Square Error(MSE)of 0.035%to actual flow fields,reducing time costs by 7-8 orders of magnitude compared to Computational Fluid Dynamics(CFD)calculations.This can provide an efficient means for rapid computation of complex flow fields.
基金funded by the Fundamental Research Funds for the Central Universities under Grant(DUT 15QY17)National Natural Science Foundation of China(Project Nos.51477025 and U1462105)
文摘In the present study,a combination of pulsed discharge plasma and TiO2（plasma/TiO2）has been developed in order to study the activity of TiO2by varying the discharge conditions of pulsed voltage,discharge mode,air flow rate and solution conductivity.Phenol was used as the chemical probe to characterize the activity of TiO2in a pulsed discharge system.The experimental results showed that the phenol removal efficiency could be improved by about 10%by increasing the applied voltage.The phenol removal efficiency for three discharge modes in the plasma-discharge-alone system was found to be highest in the spark mode,followed by the spark–streamer mode and finally the streamer mode.In the plasma/TiO2system,the highest catalytic effect of TiO2was observed in the spark–streamer discharge mode,which may be attributed to the favorable chemical and physical effects from the spark–streamer discharge mode,such as ultraviolet light,O3,H2O2,pyrolysis,shockwaves and high-energy electrons.Meanwhile,the optimal flow rate and conductivity were 0.05 m^3l^（-1）and 10μS cm^（-1）,respectively.The main phenolic intermediates were hydroquinone,catechol,and p-benzoquinone during the discharge treatment process.A different phenol degradation pathway was observed in the plasma/TiO2system as compared to plasma alone.Analysis of the reaction intermediates demonstrated that p-benzoquinone reduction was selectively catalyzed on the TiO2surface.The effective decomposition of phenol constant（De）increased from 74.11%to 79.16%when TiO2was added,indicating that higher phenol mineralization was achieved in the plasma/TiO2system.
基金supported by the National Natural Science Foundation of China(Grant No.51375259 and Grant No.51705280)the Ministry of Science and Technology of China(Grant No.2012ZX04012-011)+1 种基金Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund(the second phase,Grant No.U1501501)the Tsinghua National Laboratory for Information Science and Technology
文摘Numerical simulation based on computational fluid dynamics （CFD） is a useful approach for quantitatively investigating the underlying thermal-mechanical conditions during FSW, such as temperature field and material deformation field. One of the critical issues in CFD simulation of FSW is the use of the frictional boundary condition, which represents the friction between the welding tool and the workpiece in the numerical models. In this study, three-dimensional numerical simulation is conducted to analyze the heat transfer and plastic deformation behaviors during the FSW of AA2024. For comparison purposes, both the boundary velocity （BV） models and the boundary shear stress （BSS） models are employed in order to assess their performances in predicting the temperature and material deformation in FSW. It is interesting to note that different boundary conditions yield similar predictions on temperature, but quite different predictions on material deformation. The numerical predictions are compared with the experimental results. The predicted deformation zone geometry by the BSS model is consistent with the experimental results while there is large difference between the predictions by the BV models and the experimental measurements. The fact that the BSS model yields more reasonable predictions on the deformation zone geometry is attributed to its capacity to automatically adjust the contact state at the tool/workpiece interface. Based on the favorable predictions on both the temperature field and the material deformation field, the BSS model is suggested to have a better performance in numerical simulation of FSW than the BV model.
文摘Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources.The wind turbine is an essential system used to change kinetic energy into electrical energy.Wind turbine blades,in particular,require a competitive condition inspection approach as it is a significant component of the wind turbine system that costs around 20-25 percent of the total turbine cost.The main objective of this study is to differentiate between various blade faults which affect the wind turbine blade under operating conditions using a machine learning approach through histogram features.In this study,blade bend,hub-blade loose connection,blade erosion,pitch angle twist,and blade cracks were simulated on the blade.This problem is formulated as a machine learning problem which consists of three phases,namely feature extraction,feature selection and feature classification.Histogram features are extracted from vibration signals and feature selection was carried out using the J48 decision tree algorithm.Feature classification was performed using 15 tree classifiers.The results of the machine learning classifiers were compared with respect to their accuracy percentage and a better model is suggested for real-time monitoring of a wind turbine blade.
文摘This article investigates the comparative analysis of the facility present condition (FPC) of selected health and educational buildings in Rivers State. State funded hospitals and schools (14 functional out of 23 general hospitals and 2 out of 3 tertiary schools) were selected for the study. The general hospital is a secondary health facility designed to bring health care services close to citizens especially those in rural communities. These facilities were inherited from the colonial masters in 1960. An assessment visit in2016 found the 23 general hospitals completely dilapidated and abandoned. However, rehabilitation intervention was carried out by the government in 2020. This scenario was quite different with the schools. Thus, this study is to increase the awareness of facility operators on building maintenance. A purposive sampling technique was used in selecting the hospitals and schools, while simple random sampling was adopted for questionnaire distribution to 300 respondents. The instrument reliability and validity were ascertained using Cronbach Alpha and face validity. The instrument obtained information about the status of the facility present condition. SPSS and Microsoft Xlstat were used to obtain the mean and frequency distribution of the responses. Comparative analysis was conducted to understand the FPC of the schools and hospitals. Z-test was deployed to ascertain if there was a significant difference in the FPC between the two institutions. Checklist was adopted to confirm the findings. The result from the survey showed that schools have better FPC than hospitals.
