Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

Rate-limiting factors in hydrate decomposition through depressurization across various scales:A mini-review

Natural gas hydrate is an energy resource for methane that has a carbon quantity twice more than all traditional fossil fuels combined.However,their practical application in the field has been limited due to the challenges of long-term preparation,high costs and associated risks.Experimental studies,on the other hand,offer a safe and cost-effective means of exploring the mechanisms of hydrate dissociation and optimizing exploitation conditions.Gas hydrate decomposition is a complicated process along with intrinsic kinetics,mass transfer and heat transfer,which are the influencing factors for hydrate decomposition rate.The identification of the rate-limiting factor for hydrate dissociation during depressurization varies with the scale of the reservoir,making it challenging to extrapolate findings from laboratory experiments to the actual exploitation.This review aims to summarize current knowledge of investigations on hydrate decomposition on the subject of the research scale(core scale,middle scale,large scale and field tests)and to analyze determining factors for decomposition rate,considering the various research scales and their associated influencing factors.

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

Multi-scale design of silicon/carbon composite anode materials for lithium-ion batteries:A review

Silicon/carbon composites,which integrate the high lithium storage performance of silicon with the exceptional mechanical strength and conductivity of carbon,will replace the traditional graphite electrodes for high-energy lithium-ion batteries.Various strategies have been designed to synthesize silicon/carbon composites for tackling the issues of anode pulverization and poor stability in the anodes,thereby improving the lithium storage ability.The effect of the regulation method at each scale on the final negative electrode performance remains unclear.However,it has not been fully clarified how the regulation methods at each scale influence the final anode performance.This review will categorize the materials structure into three scales:molecular scale,nanoscale,and microscale.First,the review will examine modification methods at the molecular scale,focusing on the interfacial bonding force between silicon and carbon.Next,it will summarize various nanostructures and special shapes in the nanoscale to explore the construction of silicon/carbon composites.Lastly,the review will provide an analysis of microscale control approaches,focusing on the formation of composite particle with micron size and the utilization of micro-Si.This review provides a comprehensive overview of the multi-scale design of silicon/carbon composite anode materials and their optimization strategies to enhance the performance of lithium-ion batteries.

A real-time performance improvement method for composite time scale

The composite time scale(CTS)provides a stable,accurate,and reliable time scale for modern society.The improvement of CTS’s real-time performance will improve its stability,which strengths related applications’performance.Aiming at this goal,a method achieved by determining the optimal calculation interval and accelerating adjustment stage is proposed in this paper.The determinants of the CTS’s calculation interval(characteristics of the clock ensemble,the measurement noise,the time and frequency synchronization system’s noise and the auxiliary output generator noise floor)are studied and the optimal calculation interval is obtained.We also investigate the effect of ensemble algorithm’s initial parameters on the CTS’s adjustment stage.A strategy to get the reasonable initial parameters of ensemble algorithm is designed.The results show that the adjustment stage can be finished rapidly or even can be shorten to zero with reasonable initial parameters.On this basis,we experimentally generate a distributed CTS with a calculation interval of 500 s and its stability outperforms those of the member clocks when the averaging time is longer than1700 s.The experimental result proves that the CTS’s real-time performance is significantly improved.

Scale effect removal and range migration correction for hypersonic target coherent detection

The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar condition.However,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual application.Thus,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration performance.To eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation angle.Compared to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation capabilities.At last,this paper gives several simulations to assess the viability of ScLRT.

High Sensitivity Submicron Scale Temperature Sensor Based on Perovskite Nanoplatelet Lasers

Submicron scale temperature sensors are crucial for a range of applications,particularly in micro and na-noscale environments.One promising solution involves the use of active whispering gallery mode(WGM)microresonators.These resonators can be remotely excited and read out using free-space structures,simplifying the process of sensing.In this study,we present a submicron-scale temperature sensor with a remarkable sensitivity up to 185 pm/℃based on a trian-gular MAPbI3 nanoplatelet(NPL)laser.Notably,as temperature changes,the peak wavelength of the laser line shifts lin-early.This unique characteristic allows for precise temperature sensing by tracking the peak wavelength of the NPL laser.The optical modes are confined within the perovskite NPL,which measures just 85 nm in height,due to total internal reflec-tion.Our NPL laser boasts several key features,including a high Q of~2610 and a low laser threshold of about 19.8μJ·cm^(−2).The combination of exceptional sensitivity and ultra-small size makes our WGM device an ideal candidate for integration into systems that demand compact temperature sensors.This advancement paves the way for significant prog-ress in the development of ultrasmall temperature sensors,opening new possibilities across various fields.

Scale offers the possibility of identifying adherence to lifestyle interventions in patients with non-alcoholic fatty liver disease

Nonalcoholic fatty liver disease(NAFLD)is the most common chronic liver disorder,and dietary and lifestyle interventions remain the mainstays of NAFLD therapy.Zeng et al established a prediction system to evaluate adherence to lifestyle interventions in patients with NAFLD and choose optimal management.Here,we discuss the application scenarios of the scale and the areas warranting further attention,aiming to provide a possible reference for clinical recommend-ations.

A sub-grid scale model for Burgers turbulence based on the artificial neural network method

The present study proposes a sub-grid scale model for the one-dimensional Burgers turbulence based on the neuralnetwork and deep learning method.The filtered data of the direct numerical simulation is used to establish thetraining data set,the validation data set,and the test data set.The artificial neural network(ANN)methodand Back Propagation method are employed to train parameters in the ANN.The developed ANN is applied toconstruct the sub-grid scale model for the large eddy simulation of the Burgers turbulence in the one-dimensionalspace.The proposed model well predicts the time correlation and the space correlation of the Burgers turbulence.

Scale dependence of forest fragmentation and its climate sensitivity in a semi-arid mountain:Comparing Landsat,Sentinel and Google Earth data

Landscape fragmentation is generally viewed as an indicator of environmental stresses or risks,but the fragmentation intensity assessment also depends on the scale of data and the definition of spatial unit.This study aimed to explore the scale-dependence of forest fragmentation intensity along a moisture gradient in Yinshan Mountain of North China,and to estimate environmental sensitivity of forest fragmentation in this semi-arid landscape.We developed an automatic classification algorithm using simple linear iterative clustering(SLIC)and Gaussian mixture model(GMM),and extracted tree canopy patches from Google Earth images(GEI),with an accuracy of 89.2%in the study area.Then we convert the tree canopy patches to forest category according to definition of forest that tree density greater than 10%,and compared it with forest categories from global land use datasets,FROM-GLC10 and GlobeLand30,with spatial resolutions of 10 m and 30 m,respectively.We found that the FROM-GLC10 and GlobeLand30 datasets underestimated the forest area in Yinshan Mountain by 16.88%and 21.06%,respectively;and the ratio of open forest(OF,10%<tree coverage<40%)to closed forest(CF,tree coverage>40%)areas in the underestimated part was 2:1.The underestimations concentrated in warmer and drier areas occupied mostly by large coverage of OFs with severely fragmented canopies.Fragmentation intensity of canopies positively correlated with spring temperature while negatively correlated with summer precipitation and terrain slope.When summer precipitation was less than 300 mm or spring temperature higher than 4℃,canopy fragmentation intensity rose drastically,while the forest area percentage kept stable.Our study suggested that the spatial configuration,e.g.,sparseness,is more sensitive to drought stress than area percentage.This highlights the importance of data resolution and proper fragmentation measurements for forest patterns and environmental interpretation,which is the base of reliable ecosystem predictions with regard to the future climate scenarios.

Flow and sound fields of scaled high-speed trains with different coach numbers running in long tunnel

Segregated incompressible large eddy simulation and acoustic perturbation equations were used to obtain the flow field and sound field of 1:25 scale trains with three,six and eight coaches in a long tunnel,and the aerodynamic results were verified by wind tunnel test with the same scale two-coach train model.Time-averaged drag coefficients of the head coach of three trains are similar,but at the tail coach of the multi-group trains it is much larger than that of the three-coach train.The eight-coach train presents the largest increment from the head coach to the tail coach in the standard deviation(STD)of aerodynamic force coefficients:0.0110 for drag coefficient(Cd),0.0198 for lift coefficient(Cl)and 0.0371 for side coef-ficient(Cs).Total sound pressure level at the bottom of multi-group trains presents a significant streamwise increase,which is different from the three-coach train.Tunnel walls affect the acoustic distribution at the bottom,only after the coach number reaches a certain value,and the streamwise increase in the sound pressure fluctuation of multi-group trains is strengthened by coach number.Fourier transform of the turbulent and sound pressures presents that coach number has little influence on the peak frequencies,but increases the sound pressure level values at the tail bogie cavities.Furthermore,different from the turbulent pressure,the first two sound pressure proper orthogonal decomposition(POD)modes in the bogie cavities contain 90%of the total energy,and the spatial distributions indicate that the acoustic distributions in the head and tail bogies are not related to coach number.

Validity,Reliability,and Measurement Invariance of the Thai Smartphone Application-Based Addiction Scale and Bergen Social Media Addiction Scale

Background:In recent years,there has been increased research interest in both smartphone addiction and social media addiction as well as the development of psychometric instruments to assess these constructs.However,there is a lack of psychometric evaluation for instruments assessing smartphone addiction and social media addiction in Thailand.The present study evaluated the psychometric properties and gender measurement invariance of the Thai version of the Smartphone Application-Based Addiction Scale(SABAS)and Bergen Social Media Addiction Scale(BSMAS).Method:A total of 801 Thai university students participated in an online survey from January 2022 to July 2022 which included demographic information,SABAS,BSMAS,and the Internet Gaming Disorder Scale-Short Form(IGDS9-SF).Results:Confirmatory Factor Analyses(CFAs)found that both the SABAS and BSMAS had a one-factor structure.Findings demonstrated adequate psychometric properties of both instruments and also supported measurement invariance across genders.Moreover,scores on the SABAS and BSMAS were correlated with scores on the IGDS9-SF.Conclusion:The results indicated that the SABAS and BSMAS are useful psychometric instruments for assessing the risk of smartphone addiction and social media addiction among Thai young adults.

Optimal Multi-Timescale Scheduling of Integrated Energy Systems with Hybrid Energy Storage System Based on Lyapunov Optimization

The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To this end,this paper investigates the multi-timescale rolling opti-mization problem for IES integrated with HESS.Firstly,the architecture of IES with HESS is established,a comparative analysis is conducted to evaluate the advantages of the HESS over a single energy storage system(SESS)in stabilizing power fluctuations.Secondly,the dayahead and real-time scheduling cost functions of IES are established,the day-ahead scheduling mainly depends on operation costs of the components in IES,the real-time optimal scheduling adopts the Lya-punov optimization method to schedule the battery and hydrogen energy storage in each time slot,so as to minimize the real-time average scheduling operation cost,and the problem of day-ahead and real-time scheduling error,which caused by the uncertainty of the energy storage is solved by online optimization.Finally,the proposed model is verified to reduce the scheduling operation cost and the dispatching error by performing an arithmetic example analysis of the IES in Shanghai,which provides a reference for the safe and stable operation of the IES.

Research on Developing an Assessment Scale for Tourism Experience Elements of Ancient Shu Road Heritage Trail

Cultural ancient roads,known in Chinese as gudao,serve as heritage trails that carry historical exchanges across various regions in China.Due to their extensive preservation,wide geographical distribution,diverse thematic variations,and considerable tourist appeal,these paths have emerged as representative heritage trails,increasingly transforming into a novel tourism product experience that is highly favored by tourists and recognized by government authorities.However,research on ancient roads for tourism in China currently lacks a systematic theoretical framework,as well as relevant policies,regulations,and standards to guide their practical development.Therefore,there is a pressing need to draw upon international best practices and conduct foundational research to develop an experience element system that aligns with the perceptions,behaviors,and consumption characteristics of Chinese tourists,thereby advancing theoretical exploration in this field.This study focuses on the representative Ancient Shu Road as a case study and employs a mixed-method approach that integrates qualitative and quantitative research.It aims to construct a tourist-centric scale for the experience elements of ancient road tourism while analyzing the interactive relationship between these experience elements and tourist needs.This study addresses a significant gap in the development of indicator systems for domestic studies of ancient road tourism experiences.Ultimately,the study establishes a comprehensive scale that encompasses three core categories—trail resources and environment,facilities and services,and modes of tourism activities—along with eight primary dimensions:core resources,surrounding cultural environment,surrounding natural environment,tourism reception facilities and services,infrastructure and support services,information facilities and information services,and outdoor and recreational activities.This scale consists of thirty-two specific items,providing a robust reference for future research endeavors.Additionally,the study proposes specific development strategies related to key mechanisms,spatial configuration,and facility construction to enhance the overall development of ancient road tourism.

Performance Improvement of Kenaf/Glass Polymer Hybrid Composites by Effective Application of Fish Scale Powder as Filler:A Novel Approach

Modern technology for developing new items made from renewable resources is becoming more and more popular as a result of rising environmental concern.Recently,contemporary polymer composites have included the hybridization of natural fibers with synthetic ones,along with the inclusion of a variety of biowaste filler for developing sustainable goods.In this work,the kenaf/glass hybrid polyester composites are strengthened by the addition of fish scale(FS),which is taken from the fishs outermost layer of skin.Five different stacked-order laminates,such as KKKK,KGKG,GKKG,KGGK,and GGGG,are fabricated by using the hand lay-up method with four different weight concentrations of filler content:0%,5%,10%,and 15%.Mechanical possessions such as tensile,flexural,impact strength and micro-hardness have been evaluated through experimentation in accordance with ASTM standards.The experimental findings revealed that,the tensile strength and micro-hardness value of KGKG laminates with 15wt% of FS filler are found to be maximum of 118.72 MPa and 17.82 HV respectively which are 39.67%and 26.11%greater than that of KGKG laminates without FS filler.However,the flexural and impact strength of same laminates with 10 wt% FS filler exhibited a maximum value of 142.77 MPa and 62.08 kJ/m^(2).In order to corroborate its applicability for structural and building materials in open environment,the dimensional stability of the composite has been studied through moisture absorption test.The influences of FS filler loading on dimensional stability and resistance to moisture absorption capacity of laminates are also investigated.The experimental results reflected that the addition of FS-filler has significantly improved the dimensional stability of the laminates in moist environment by reducing the moisture absorption tendency.To further support the mode of failures,a fractography investigation of fractured surfaces was conducted.

Study of the intensive care unit activity scale in the early rehabilitation of patients after direct cardiac surgery

BACKGROUND Direct cardiac surgery often necessitates intensive post-operative care,and the intensive care unit(ICU)activity scale represents a crucial metric in assessing and guiding early rehabilitation efforts to enhance patient recovery.AIM To clarify the clinical application value of the ICU activity scale in the early recovery of patients after cardiac surgery.METHODS One hundred and twenty patients who underwent cardiac surgery between September 2020 and October 2021 were selected and divided into two groups using the random number table method.The observation group was rated using the ICU activity scale and the corresponding graded rehabilitation interventions were conducted based on the ICU activity scale.The control group was assessed in accordance with the routine rehabilitation activities,and the postoperative rehabilitation indexes of the patients in both groups were compared(time of tracheal intubation,time of ICU admission,occurrence of complications,and activity scores before ICU transfer).The two groups were compared according to postoperative rehabilitation indicators(time of tracheal intubation,length of ICU stay,and occurrence of complications)and activity scores before ICU transfer.RESULTS In the observation group,tracheal intubation time lasted for 18.30±3.28 h and ICU admission time was 4.04±0.83 d,which were significantly shorter than the control group(t-values:2.97 and 2.038,respectively,P<0.05).The observation group also had a significantly lower number of complications and adverse events compared to the control group(P<0.05).Before ICU transfer,the observation group(6.7%)had few complications and adverse events than the control group(30.0%),and this difference was statistically significant(P<0.05).Additionally,the activity score was significantly higher in the observation(26.89±0.97)compared to the control groups(22.63±1.12 points)(t-value;-17.83,P<0.05).CONCLUSION Implementation of early goal-directed activities in patients who underwent cardiac surgery using the ICU activity scale can promote the recovery of cardiac function.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

Small-scale fire tests in the underwater tunnel section model with new sidewall smoke extraction

The Shenzhen–Zhongshan Bridge is a 24‐km‐long bridge and tunnel system,including a 6.8-km-long super cross section subsea tunnel.To solve the smoke exhaust problem of a super large cross-section subsea tunnel,the tunnel has a new smoke exhaust system that combines a horizontal smoke exhaust cross section at the top and sidewall smoke exhaust holes.In order to evaluate the potential fire hazards of this type of tunnel,a 1:30 tunnel model was established and 140 smallscale experiments on underwater tunnel fires were conducted.By changing the fire power,fire location,and fan operation mode,different scenarios of submarine immersed tunnel fire were simulated and the related key parameters such as fire smoke diffusion behavior and smoke temperature distribution were studied.On this basis,the optimal smoke control strategy was proposed for different fire scenarios.The research results indicate that the new smoke exhaust system can fully utilize the smoke flow characteristics,significantly improve smoke exhaust efficiency,and increase available evacuation time,thus further enhancing the fire safety of super large cross-section subsea tunnels.

Data Scale, Data Scope and Platform Enterprise Performance: Insights from Digital Platform M&As

Data is a key asset for digital platforms,and mergers and acquisitions(M&As)are an important way for platform enterprises to acquire it.The types of data obtained from intra-industry and cross-sector M&As differ,as does the extent to which they interact within or between platforms.The impact of such data on corporate market performance is an important question to consider when selecting strategies for digital platform M&As.Based on our research on advertising-driven platforms,we developed a two-stage Hotelling game model for comparing the market performance effects of intra-industry M&As and cross-sector M&As for digital platforms.We carried out an empirical test using relevant data from advertising-driven digital platforms between 2009 and 2021,as well as a case study on Baidu’s M&A activities.Our research discovered that intra-industry M&As driven by“data economies of scale”and cross-sector M&As driven by“data economies of scope”are both beneficial to the market performance of platform enterprises.Intra-industry M&As have a more significant positive effect on the market performance of platform enterprises because the same types of data are easier to integrate and develop the“network effect of data scale”.From a data factor perspective,this paper reveals the inherent economic logic by which different types of M&As influence the market performance of digital platforms,as well as policymaking recommendations for all digital platforms to select M&A strategies based on data scale,data scope,and the network effect of data.