How Sense of Ritual in Tourism Impacts Tourists’Co-Creation of Tourism Experience Values:A Study Based on the Theory of Value Co-Creation

Establishing a sense of ritual within tourism consumption scenarios offers tourists the opportunity for interactive engagement.Drawing upon the value co-creation theory,this study constructed an influence mechanism model to examine tourists'active engagement in the process of co-creating tourism experience values.It employed Partial Least Squares Structural Equation Modeling(PLS-SEM)to empirically test the proposed hypotheses.The findings demonstrate that the model constructed in the present study exhibits robust reliability,validity,and explanatory power.The perception of the sense of ritual in tourism exerts a significant positive influence on tourists’co-creation of tourism experience values,thereby significantly enhancing both the communitas and flow experienced by tourists during their travels.Moreover,such communitas and flow can mediate the influence of the sense of ritual in tourism on tourists’co-creation of tourism experience values.This study contributes to advancing the current research on tourists’co-creation of tourism experience values and the sense of ritual in tourism,thereby providing theoretical foundations for cultivating a sense of ritual within tourism consumption scenarios.

Remote sensing of air pollution incorporating integrated-path differential-absorption and coherent-Doppler lidar

An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber laser.By combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric pollution.Extensive static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 km.Flight experiments is conducted with the helicopter.Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 s.The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety.

Characterization and spatial analysis of coseismic landslides triggered by the Luding Ms 6.8 earthquake in the Xianshuihe fault zone, Southwest China

On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km^(2). The coseismic landslides primarily consisted of medium and small-sized landslides, characterized by shallow surface sliding. Some exhibited characteristics of high-position initiation resulted in the obstruction or partial obstruction of rivers, leading to the formation of dammed lakes. Our research found that the coseismic landslides were predominantly observed on slopes ranging from 30° to 50°, occurring at between 1000 m and 2500 m, with slope aspects varying from 90° to 180°. Landslides were also highly developed in granitic bodies that had experienced structural fracturing and strong-tomoderate weathering. Coseismic landslides concentrated within a 6 km range on both sides of the Xianshuihe and Daduhe fault zones. The area and number of coseismic landslides exhibited a negative correlation with the distance to fault lines, road networks, and river systems, as they were influenced by fault activity, road excavation, and river erosion. The coseismic landslides were mainly distributed in the southeastern region of the epicenter, exhibiting relatively concentrated patterns within the IX-degree zones such as Moxi Town, Wandong River basin, Detuo Town to Wanggangping Township. Our research findings provide important data on the coseismic landslides triggered by the Luding Ms 6.8 earthquake and reveal the spatial distribution patterns of these landslides. These findings can serve as important references for risk mitigation, reconstruction planning, and regional earthquake disaster research in the earthquake-affected area.

Variation in the surface heat flux on the north and south slopes of Mount Qomolangma

The distinctive conditions present on the north and south slopes of Mount Qomolangma,along with the intricate variations in the underlying surfaces,result in notable variations in the surface energy flux patterns of the two slopes.In this paper,data from TESEBS(Topographical Enhanced Surface Energy Balance System),remote sensing data from eight cloud-free scenarios,and observational data from nine stations are utilized to examine the fluctuations in the surface heat flux on both slopes.The inclusion of MCD43A3 satellite data enhances the surface albedo,contributing to more accurate simulation outcomes.The model results are validated using observational data.The RMSEs of the net radiation,ground heat,sensible heat,and latent heat flux are 40.73,17.09,33.26,and 30.91 W m^(−2),respectively.The net radiation flux is greater on the south slope and exhibits a rapid decline from summer to autumn.Due to the influence of the monsoon,on the north slope,the maximum sensible heat flux occurs in the pre-monsoon period in summer and the maximum latent heat flux occurs during the monsoon.The south slope experiences the highest latent heat flux in summer.The dominant flux on the north slope is sensible heat,while it is latent heat on the south slope.The seasonal variations in the ground heat flux are more pronounced on the south slope than on the north slope.Except in summer,the ground heat flux on the north slope surpasses that on the south slope.

Preventing Health Anxiety:The Role of Self-Evaluation,Sense of Coherence,Self-Rated Health and Perceived Social Support

Background:Components of Self,completed with the perceived social support determine the individual differences in theevaluation of a stressor and the behavioral responses toward it,such as health-related anxiety.The study set as a goal theanalysis of associations between the components of Self,such as self-evaluation,sense of coherence,perceived social support,and reported health-related anxiety in an adult sample.Methods:147 adults from the 18–73 age group(mean age 37.5)voluntarily completed the questionnaire through Qualtrics online platform containing the Short Health Anxiety Inventory,Core Self-Evaluation Scale,Social Support Assessing Scale,and one Health Self-Evaluation Item.Results:ANOVA foundrelevant differences in total scores and subscales’scores of the health anxiety scale depending on the positive self-evaluation.Linear regression shows that the analyzed variables were responsible for the prediction of a higher value on the“Perceivedprobability of becoming ill”subscale in a proportion of 45.6%and for the“Perceived consequence of illness”subscale in aproportion of 20.2%The predictive value of the linear regression model for the total score on the health anxiety scale was46.3%.Our findings show that negative Core Self-Evaluation is linked with perceived health anxiety.Conclusions:Selfevaluation,sense of coherence and perceived social support influence the perceived health and can explain the differences inthe reported health-related anxiety.

Comparative study of self-compassion and sense of coherence in nurses of psychiatric hospitals

Objective:Nurses,due to the nature of their job,are subjected to various forms of stress and physical and psychological injuries.Self-compassion and a sense of coherence have attracted much attention in research in recent years as having high potential for improving the health and performance of people in the workplace.The present study aimed to compare self-compassion and the sense of coherence in nurses working in psychiatric hospitals and other hospitals of Kerman University of Medical Sciences.Methods:The present study was a descriptive-comparative study of applied type conducted on 100 nurses of Shahid Beheshti Psychiatric Hospital in Kerman by the census method and 100 nurses of other hospitals of Kerman University of Medical Sciences by the stratified random sampling method.The instruments included the self-compassion questionnaire and the sense of coherence questionnaire.Data were analyzed using the Statistical Package for Social Sciences software.Results:The results of the present study showed that self-compassion and sense of coherence were higher in psychiatric nurses(39.35±7.7 and 53.02±8.01)than among other nurses(36.03±5.81 and 49.76±6.30).There was a direct and moderate relationship between a sense of coherence and self-compassion(P-value<0.005).The higher the score of compassion for oneself,the higher was the score of sense of coherence.Furthermore,the sense of coherence had a direct and weak relationship with all dimensions of self-compassion,except for the extreme imitation dimension,which showed a direct and moderate relationship to other dimensions(P-value<0.001).Conclusions:Self-compassion and a sense of coherence,as a form of self-communication,increase nurses’satisfaction and reduce nurses’job stress and,as a result,job performance is improved.

Fracture network characterisation of the Balmuccia peridotite using drone-based photogrammetry,implications for active-seismic site survey for scientific drilling

The presence of discontinuities(e.g.faults,fractures,veins,layering)in crystalline rocks can be challenging for seismic interpretations because the wide range of their size,orientation,and intensity,which controls the mechanical properties of the rock and elastic wave propagation,resulting in equally varying seismic responses at different scales.The geometrical characterisation of adjacent outcrop discontinuity networks allows a better understanding of the nature of the subsurface rocks and aids seismic interpretation.In this study,we characterise the discontinuity network of the Balmuccia peridotite(BP)in the IvreaeVerbano Zone(IVZ),northwestern Italy.This geological body is the focus of the Drilling the Ivrea eVerbano zonE(DIVE),an international continental scientific drilling project,and two active seismic surveys,SEismic imaging of the Ivrea ZonE(SEIZE)and high-resolution SEIZE(Hi-SEIZE),which aim to resolve the subsurface structure of the DIVE drilling target through high-resolution seismic imaging.For fracture characterisation,we developed two drone-based digital outcrop models(DOMs)at two different resolutions(10^(-3)-10 m and 10^(-1)-10^(3)m),which allowed us to quantitatively characterise the orientation,size,and intensity of the main rock discontinuities.These properties affect the seismic velocity and consequently the interpretation of the seismic data.We found that(i)the outcropping BP discontinuity network is represented by three more sets of fractures with respect to those reported in the literature;(ii)the discontinuity sizes follow a power-law distribution,indicating similarity across scales,and(iii)discontinuity intensity is not uniformly distributed along the outcrop.Our results help to explain the seismic behaviour of the BP detected by the SEIZE survey,suggesting that the low P-wave velocities observed can be related to the discontinuity network,and provide the basic topological parameters(orientation,density,distribution,and aperture)of the fracture network unique to the BP.These,in turn,can be used for interpretation of the Hi-SEIZE seismic survey and forward modelling of the seismic response.

WHY PRACTICE MAKES PERFECT SENSE:THE PAST,PRESENT AND POTENTIAL FUTURE OF THE PPP PARADIGM IN LANGUAGE TEACHER EDUCATION

Introduction Among,the many lesson planning paradigms usedin English language teacher education over the last 40 years,PPP has proven to be one of the mostpopular and most durable(see Figure 1)despite regular criticism in literature emanating from the Anglophone,centre,of ELT theory.After presenting a brief history of the paradigm andoutlining the main criticisms directed at PPP,especially in the 1990s,I discuss some important rescarch findings from SLA studics sincc the turn of the century that lend support to PPP-typelesson structures.

Preparation of single atom catalysts for high sensitive gas sensing

Single atom catalysts(SACs)have garnered significant attention in the field of catalysis over the past decade due to their exceptional atom utilization efficiency and distinct physical and chemical properties.For the semiconductor-based electrical gas sensor,the core is the catalysis process of target gas molecules on the sensitive materials.In this context,the SACs offer great potential for highly sensitive and selective gas sensing,however,only some of the bubbles come to the surface.To facilitate practical applications,we present a comprehensive review of the preparation strategies for SACs,with a focus on overcoming the challenges of aggregation and low loading.Extensive research efforts have been devoted to investigating the gas sensing mechanism,exploring sensitive materials,optimizing device structures,and refining signal post-processing techniques.Finally,the challenges and future perspectives on the SACs based gas sensing are presented.

Microarrow sensor array with enhanced skin adhesion for transdermal continuous monitoring of glucose and reactive oxygen species

Conventional blood sampling for glucose detection is prone to cause pain and fails to continuously record glucose fluctuations in vivo.Continuous glucose monitoring based on implantable electrodes could induce pain and potential tissue inflammation,and the presence of reactive oxygen species(ROS)due to inflammationmay affect glucose detection.Microneedle technology is less invasive,yet microneedle adhesion with skin tissue is limited.In this work,we developed a microarrow sensor array(MASA),which provided enhanced skin surface adhesion and enabled simultaneous detection of glucose and H_(2)O_(2)(representative of ROS)in interstitial fluid in vivo.The microarrows fabricated via laser micromachining were modified with functional coating and integrated into a patch of a three-dimensional(3D)microneedle array.Due to the arrow tip mechanically interlocking with the tissue,the microarrow array could better adhere to the skin surface after penetration into skin.The MASA was demonstrated to provide continuous in vivo monitoring of glucose and H_(2)O_(2) concentrations,with the detection of H_(2)O_(2) providing a valuable reference for assessing the inflammation state.Finally,the MASA was integrated into a monitoring system using custom circuitry.This work provides a promising tool for the stable and reliable monitoring of blood glucose in diabetic patients.

Determining the planting year of navel orange trees in mountainous and hilly areas of southern China:a remote sensing based method

Remote sensing has demonstrated validity in determining the planting year of deciduous fruit trees;however,its effectiveness in ascertaining the planting year of evergreen fruit trees remains unverified.Furthermore,the sources of error associated with using remote sensing to determine the planting year of fruit trees remain unclear.This study investigates several cultivated sweet orange(Citrus sinensis)varieties,which are extensively cultivated throughout subtropical China.We analyzed Landsat time series data from 132 navel orange orchards in Gannan,covering the period from 1993 to 2021.For each orchard,Google Earth Engine was employed to extract three vegetation indices—Enhanced Vegetation Index(EVI),Normalized Difference Vegetation Index(NDVI),and Normalized Burn Ratio(NBR)—for each available date,thereby generating three distinct vegetation index time series.The planting year of navel orange trees was identified based on abrupt changes observed in these time series.The principal sources of error in determining the planting year were investigated using the Wilcoxon signed-rank test,Spearman's correlation analysis,and Kruskal-Wallis H test.Key findings include:(1)Following the planting of navel orange trees,EVI,NDVI,and NBR exhibited fluctuations and a gradual increase over time,peaking approximately 10 to 15 years later.(2)The vegetation index time series derived from Landsat imagery effectively determined the planting year of evergreen navel orange trees in orchards,even within highly fragmented landscapes.Among these indices,NDVI and NBR time series outperformed the EVI time series.Specifically,the average determination errors for EVI,NDVI,and NBR time series were 6.4,1.8,and 2.8 years,respectively.(3)Major sources of error included the methods used to construct the time series,the selection of vegetation indices,and the orchard management practices.Overall,this study provides a viable method for determining the planting year of evergreen navel orange trees in fragmented landscapes and offers insights into factors contributing to uncertainty in planting year determination.

Comprehensive analysis of glacier recession(2000-2020)in the Nun-Kun Group of Glaciers,Northwestern Himalaya

Himalayan glaciers are shrinking rapidly,especially after 2000.Glacier shrinkage,however,shows a differential pattern in space and time,emphasizing the need to monitor and assess glacier changes at a larger scale.In this study,changes of 48 glaciers situated around the twin peaks of the Nun and Kun mountains in the northwestern Himalaya,hereafter referred to as Nun-Kun Group of Glaciers(NKGG),were investigated using Landsat satellite data during 2000-2020.Changes in glacier area,snout position,Equilibrium Line Altitude(ELA),surface thickness and glacier velocity were assessed using remote sensing data supplemented by field observations.The study revealed that the NKGG glaciers have experienced a recession of 4.5%±3.4%and their snouts have retreated at the rate of 6.4±1.6 m·a^(-1).Additionally,there was a 41%increase observed in the debris cover area during the observation period.Using the geodetic approach,an average glacier elevation change of-1.4±0.4 m·a^(-1)was observed between 2000 and 2012.The observed mass loss of the NKGG has resulted in the deceleration of glacier velocity from 27.0±3.7 m·a^(-1)in 2000 to 21.2±2.2 m·a^(-1)in 2020.The ELA has shifted upwards by 83.0±22 m during the period.Glacier morphological and topographic factors showed a strong influence on glacier recession.Furthermore,a higher recession of 12.9%±3.2%was observed in small glaciers,compared to 2.7%±3.1%in larger glaciers.The debris-covered glaciers showed lower shrinkage(2.8%±1.1%)compared to the clean glaciers(9.3%±5%).The glacier depletion recorded in the NKGG during the last two decades,if continued,would severely diminish glacial volume and capacity to store water,thus jeopardizing the sustainability of water resources in the basin.

Automatic recognition of landslides based on YOLOv7 and attention mechanism

Landslide disasters comprise the majority of geological incidents on slopes,posing severe threats to the safety of human lives and property while exerting a significant impact on the geological environment.The rapid identification of landslides is important for disaster prevention and control;however,currently,landslide identification relies mainly on the manual interpretation of remote sensing images.Manual interpretation and feature recognition methods are time-consuming,labor-intensive,and challenging when confronted with complex scenarios.Consequently,automatic landslide recognition has emerged as a pivotal avenue for future development.In this study,a dataset comprising 2000 landslide images was constructed using open-source remote sensing images and datasets.The YOLOv7 model was enhanced using data augmentation algorithms and attention mechanisms.Three optimization models were formulated to realize automatic landslide recognition.The findings demonstrate the commendable performance of the optimized model in automatic landslide recognition,achieving a peak accuracy of 95.92%.Subsequently,the optimized model was applied to regional landslide identification,co-seismic landslide identification,and landslide recognition at various scales,all of which showed robust recognition capabilities.Nevertheless,the model exhibits limitations in detecting small targets,indicating areas for refining the deep-learning algorithms.The results of this research offer valuable technical support for the swift identification,prevention,and mitigation of landslide disasters.

Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this paper.Here,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its performance.Then,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation platforms.Subsequently,it is used toward secure communication application scenarios.Taking it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)model.Eventually,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

Aging Mongolian pine plantations face high risks of drought-induced growth decline:evidence from both individual tree and forest stand measurements

Discerning vulnerability differences among different aged trees to drought-driven growth decline or to mortality is critical to implement age-specific countermeasures for forest management in water-limited areas.An important species for afforestation in dry environments of northern China,Mongolian pine(Pinus sylvestris var.mongolica Litv.)has recently exhibited growth decline and dieback on many sites,particularly pronounced in old-growth plantations.However,changes in response to drought stress by this species with age as well as the underlying mechanisms are poorly understood.In this study,tree-ring data and remotely sensed vegetation data were combined to investigate variations in growth at individual tree and stand scales for young(9-13 years)and aging(35-52 years)plantations of Mongolian pine in a water-limited area of northern China.A recent decline in tree-ring width in the older plantation also had lower values in satellited-derived normalized difference vegetation indices and normalized difference water indices relative to the younger plantations.In addition,all measured growth-related metrics were strongly correlated with the self-calibrating Palmer drought severity index during the growing season in the older plantation.Sensitivity of growth to drought of the older plantation might be attributed to more severe hydraulic limitations,as reflected by their lower sapwood-and leaf-specific hydraulic conductivities.Our study presents a comprehensive view on changes of growth with age by integrating multiple methods and provides an explanation from the perspective of plant hydraulics for growth decline with age.The results indicate that old-growth Mongolian pine plantations in water-limited environments may face increased growth declines under the context of climate warming and drying.

THE STABLE RECONSTRUCTION OF STRONGLY-DECAYING BLOCK SPARSE SIGNALS

In this paper,we reconstruct strongly-decaying block sparse signals by the block generalized orthogonal matching pursuit(BgOMP)algorithm in the l2-bounded noise case.Under some restraints on the minimum magnitude of the nonzero elements of the strongly-decaying block sparse signal,if the sensing matrix satisfies the the block restricted isometry property(block-RIP),then arbitrary strongly-decaying block sparse signals can be accurately and steadily reconstructed by the BgOMP algorithm in iterations.Furthermore,we conjecture that this condition is sharp.

Mapping lineaments using Landsat 8 OLI and SRTM data;a case study of the eastern part of the Ouarzazate Basin,Morocco

The integration of remote sensing and geographic information system(GIS)was employed in this study to delineate the structural lineaments within the eastern section of the Ouarzazate Basin,situated between the southern front of the Central High Atlas and the northern slopes of the Eastern Anti-Atlas(also known as the Saghro Massif).To achieve this objective,Landsat 8 Operational Land Imager(OLI)and Shuttle Radar Topography Mission(SRTM)data were used.Principal Component Analysis(PCA)was computed and a directional filter was applied to the first PCA and the panchromatic band(B8).Additionally,shading was applied to the SRTM data in four directions;N0°,N45°,N90°,N135°.After removing of the non-geological linear structures,the results obtained,using the automatic extraction method,allowed us to produce a synthetic map that included 1251 lineaments with an average length of 1331 m and was dominated by NE-SW,ENE-WSW and E-W directions,respectively.However,the high lineament density is clearly noted in the Anti-Atlas(Saghro Massif)and at the level of the northern part,extending from the Ait Ibrirne to Arg-Ali Oubourk villages.High lineament density can always be found around the major faults affecting this area.The data collected during the field investigations and from geological maps show that the major direction of the faults and structural accidents range mostly between N45°,N70°and N75°.The correlation of remote sensing results with those collected in the field shows a similarity and coincidence with each other.From these results,it is possible to consider the automatic extraction method as a supplementary kind that can serve classical geology by quickly enriching it with additional data.As shown in this work,this method provides more information when applied in arid areas where the fields are well outcropped.

Remote sensing of quality traits in cereal and arable production systems:A review

Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and categorised storage for enterprises,future trading prices,and policy planning.The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits.Many studies have also proposed models and methods for predicting such traits based on multiplatform remote sensing data.In this paper,the key quality traits that are of interest to producers and consumers are introduced.The literature related to grain quality prediction was analyzed in detail,and a review was conducted on remote sensing platforms,commonly used methods,potential gaps,and future trends in crop quality prediction.This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data.

Joint Design of ISAC Waveform Under PAPR Constraints

In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication multi-user interference(MUI)and the gap between dual-use waveform and ideal radar waveform is minimized with peak-toaverage power ratio(PAPR)constraints.We propose an efficient algorithm based on alternating direction method of multipliers(ADMM),which is able to decouple multiple variables and provide a closed-form solution for each subproblem.In addition,to improve the sensing performance in both spatial and temporal domains,we propose a new criteria to design the ideal radar waveform,in which the beam pattern is made similar to the ideal one and the integrated sidelobe level of the ambiguity function in each target direction is minimized in the region of interest.The limited memory Broyden-Fletcher-Goldfarb-Shanno(LBFGS)algorithm is applied to the design of the ideal radar waveform which works as a reference in the design of the dual-function waveform.Numerical results indicate that the designed dual-function waveform is capable of offering good communication quality of service(QoS)and sensing performance.

Landsat Image-Based Spatiotemporal Variation Analysis of Erosion and Deposition off the Qingshuigou of the Yellow River Delta from 1984 to 2021

Owing to climate change and human activity,the Qingshuigou of the Yellow River Delta(YRD)has undergone dynamic changes in erosion and deposition.Therefore,studying these changes is important to ensure ecological protection and sustainable development.In this study,the trend of erosion-deposition evolution in the Qingshuigou was investigated based on 38 coastline phases extracted from Landsat series images of the YRD at one-year intervals from 1984 to 2021.The periodicity of the scouring and deposition evolution was also analyzed using wavelet analysis.Results showed that the total area of the Qingshuigou was affected by deposition and erosion and that the fluctuation first increased and then decreased.The total area reached a maximum in 1993.The depositional area first increased and then decreased,whereas the overall erosion area decreased.Deposition and erosion areas showed periodic changes to some extent;however,the periodic signal intensity decreased.Furthermore,factors including channel morphological evolution and variations in water and sediment discharge affect the spatiotemporal dynamics of erosion and deposition processes.The application of nonconsistency tests finally revealed that deposition area and flushing magnitude exhibited non-stationarities,which are potentially attributed to impacts from climatic change drivers.