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.

Method based on fuzzy linguistic scale and FIOWGA operator for decision-making problems

In this paper, we present a fuzzy linguistic scale, which is characterized by triangular fuzzy numbers on [1/9, 9], for the comparison between two alternatives, and introduce a possibility degree formula for comparing triangular fuzzy numbers. We utilize the fuzzy linguistic scale to construct a linguistic preference matrix, and propose a fuzzy induced ordered weighted geometric averaging (FIOWGA) operator to aggregate linguistic preference information. A method based on the fuzzy linguistic scale and FIOWGA operator for decision-making problems is presented. Finally, an illustrative example is given to verify the developed method and to demonstrate its feasibility and effectiveness.

Analysis and forecasts of investment scale and structure in upstream sector for oil companies based on system dynamics

Oil and gas exploration and production is the most important and key segment in the whole business chain of the petroleum industry.Therefore,oil companies always put much emphasis on making scientific and reasonable decisions about investment scale and structure in the upstream sector,so that they can minimise business risks and obtain high returns.According to the system dynamics theories and methods and based on the actual results from an oil company＇s practice in China,a system dynamics model is built in this paper for analyzing and forecasting the upstream investment scale and structure for an oil company.This model was used to analyze the investment effect of a large oil company in China, and the results showed that the total upstream investment scale will decline slowly in a short period and the investment proportion of different parts should be adjusted if some influencing factors are taken into account.This application practice was compared with the actual data and indicated that the system dynamics（SD） model presented in this paper is a useful tool for analyzing and forecasting of upstream investment scale and structure of oil companies in their investment decisions.

A skew–normal mixture of joint location, scale and skewness models

Normal mixture regression models are one of the most important statistical data analysis tools in a heterogeneous population. When the data set under consideration involves asymmetric outcomes, in the last two decades, the skew normal distribution has been shown beneficial in dealing with asymmetric data in various theoretic and applied problems. In this paper, we propose and study a novel class of models： a skew-normal mixture of joint location, scale and skewness models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population. The issues of maximum likelihood estimation are addressed. In particular, an Expectation-Maximization （EM） algorithm for estimating the model parameters is developed. Properties of the estimators of the regression coefficients are evaluated through Monte Carlo experiments. Results from the analysis of a real data set from the Body Mass Index （BMI） data are presented.

Glasgow coma scale and APACHE-II scores affect the liver transplantation outcomes in patients with acute liver failure

BACKGROUND:The timing and selection of patients for liver transplantation in acute liver failure are great challenges.This study aimed to investigate the effect of Glasgow coma scale(GCS)and APACHE-II scores on liver transplantation outcomes in patients with acute liver failure.METHOD:A total of 25 patients with acute liver failure were retrospectively analyzed according to age,etiology,time to transplantation,coma scores,complications and mortality.RESULTS:Eighteen patients received transplants from live donors and 7 had cadaveric whole liver transplants.The mean duration of follow-up after liver transplantation was 39.86±40.23 months.Seven patients died within the perioperative period and the 1-,3-,5-year survival rates of the patients were72%,72%and 60%,respectively.The parameters evaluated for the perioperative deaths versus alive were as follows:the mean age of the patients was 33.71 vs 28 years,MELD score was 40 vs32.66,GCS was 5.57 vs 10.16,APACHE-II score was 23 vs 18.11,serum sodium level was 138.57 vs 138.44 mmol/L,mean waiting time before the operation was 12 vs 5.16 days.Low GCS,high APACHE-II score and longer waiting time before the operation(P【0.01)were found as statistically significant factors for perioperative mortality.CONCLUSION:Lower GCS and higher APACHE-II scores are related to poor outcomes in patients with acute liver failure after liver transplantation.

Effect of spatial scale and topography on spatial heterogeneity of soil seed banks under grazing disturbance in a sandy grassland of Horqin Sand Land, Northern China

Soil seed banks play an important role in the distribution and composition of plant communities in semiarid grassland ecosystems. However, information on how spatial scale influences the spatial heterogeneity of soil seed banks in a grassland under grazing disturbance is still lacking. Based on field sampling and greenhouse germination, we measured the species composition and seed density of soil seed banks at different spatial scales （30 mx30 m, 30 mx60 m and 30 mx90 m） along a topographical gradient in a sandy grassland in Horqin Sand Land, Northern China. By applying geostatistical methods, we examined how spatial scale and topography affected the spatial distribution of soil seed banks in the study area. Our results showed that the total number of species in soil seed banks, as well as the number of dominant annuals, increased with the increase of spatial scales. Seed density in soil seed banks decreased with the increase of spatial scales due to an increase in the slopes and relative heights of the sampling points. Geostatistical analysis showed that the relative structural variance （C/（C0＋C）） of seed density and species richness were over 65% for all spatial scales, indicating that these variables had an ob- vious spatial autocorrelation and the spatial structured variance accounted for the largest proportion of the total sample variance. Spatial autocorrelation of seed density in soil seed banks increased with the increase of measured scales, while that of species richness showed a reverse trend. These results suggest that the total number of spe- cies in soil seed banks is spatial scale dependent and lower topography may accommodate more seeds. Spatial distribution of seed density in soil seed banks is also scale dependent due to topographic variation. Grassland management, therefore, needs to consider local grazing disturbance regime, spatial scale and topography.

Preparation of MCM-41 in Industrial Scale and Its Application in Heavy Oil Processing

A series of MCM 41 molecular sieves have been prepared on an industrial scale, and the effect of preparation factors such as aging temperature, pH values on the structure and pore distribution of the MCM 41 product have been studied by using X ray diffraction(XRD), thermogravimetric(TG) and electron microscopy(TEM). It is shown that the pH values have a significant effect on the crystallinity of the synthesized product. Under proper conditions, the MCM 41 prepared on an industrial scale has the same performance as the samples prepared on an Lab scale. The prepared MCM 41 was used as a modifier of zeolite Y for fluid catalytic cracking(FCC) of residual oil. It is shown that the addition of the MCM 41 in the zeolite Y catalyst increases the pore size, and surface area of the catalysts, which helps to increase the yield of gasoline and diesel and decrease the production of gaseous product and carbon deposition in the catalyst. The better performance of the MCM 41 modified zeolite Y catalyst is believed to be due to its adjustment on the acidity and increase of the pore size.

HIGH TEMPERATURE OXIDATION AND STRUCTURE OF SCALE AND WHISKERS FOR Fe-Ni-Cr SEALING ALLOYS

The oxidation rate,the growth,morphology and structure of oxide scale and whiskers for Fe-Ni-Cr sealing alloys in H_2-H_2O atmosphere at high temperatures have been studied. The growth rate of scale is controlled by diffusion.The scale is composed of Cr_2O_3 and spinel(Fe,Mn)O·Cr_2O_3 and the oxide whisker,are spinel(Fe,Mn)O·Cr_2O_3.

Scale and scope economies in small household rice farming in Vietnam

The Vietnamese agricultural sector has experienced a dramatic structural change based on increased specialization in rice cultivation.However,small-scale rice-farmers have continued to grow multiple crops,especially in less developed provinces.While the literature advocates crop diversification for reasons of both economic and ecological sustainability,there lacks empirical evidence as to whether crop diversification brings efficiency and productivity gains to small farms.The present study is the first applications of the input-oriented stochastic distance function approach in estimating scale and scope economies using data of multi-crop farming households in Vietnam.We find strong evidence of product-specific economies of scale.Scope economies are also present for rice,vegetable,and other annual crop production.This suggests that crop diversification enhances efficiency and productivity.However,there still exists significant technical inefficiency in crop production,indicating opportunities to expand farm output at the existing level of inputs and technologies.More specifically,our empirical results indicate that it is desirable to expand vegetable and other annual crop production in mountainous areas while rice cultivation can be further expanded in delta and coastal regions.

Moderate scale and realization potential of new citrus-planting business entities in hilly and mountainous areas in China

The natural and economic conditions of agricultural resources vary greatly in China,especially in hilly and mountainous areas.The phenomenon of land fragmentation has become increasingly prominent,so that large-scale operations cannot be fully achieved in a short period of time,and the centralized and continuous scale of operations cannot be realized in China.In addition,with increasingly strict farmland protection and agricultural land use control systems,the issues of nongrain production and nonagricultural cultivated land use have become increasingly restricted.Thus,it is quite necessary to determine the appropriate scale of operations and the means to achieve moderately scaled operations for the new business entities.On the basis of microsurvey data for 108 new citrus-planting business entities in the modern agricultural park in the Chongqing's Jiangjin District,an area with long citrus-planting history,we measured the moderate scale of new citrus-planting business entities to maximize profit using a translog growth model.According to the projection pursuit model,we evaluated the suitability conditions of citrus planting in garden land,woodland,grassland,and general cultivated land in the study area.We then explored the potential for new moderate-scale business entities within different farming radii.The results showed that large-scale planting conditions of citrus in garden land,forest land,grassland,and general cultivated land in the study area were suitable,and the proportion of high-suitable and mediumsuitable land was 73.42%.Under the existing social and economic conditions,the moderate scale of new citrus-planting business entities in the study area was 1.8–2.7 hm^(2).In particular,its rankings from large to small were agricultural enterprises(17.19–25.78 hm^(2)),farmer cooperatives(16.88–25.33 hm^(2)),big growers and breeders(6.39–9.59 hm^(2)),and family farms(5.02–7.53 hm^(2)).In the sample of 108 households,only 47.22%of the entities achieved moderate-scale operation,of which 25%of the entities achieved a scale greater than moderate operation.However,52.78%of the entities achieved a scale of less than moderate operation.These entities would have to transfer the surrounding adjacent garden land,forest land,grassland,or general cultivated land to achieve largescale land management.The land area of the adjacent gardens in a 1000 m farming radius could meet the moderate-scale operation demand of the vast majority of new business entities.For the vast majority of new business entities,the land area of the adjacent woodland,grassland,and general cultivated land could supplement the garden land to achieve moderate-scale operation in a 500 m farming radius.If the land area with moderate suitability and high suitability is prioritized,the land area in the adjacent gardens in the 1000 m farming radius could meet the moderate-scale operation demand for the vast majority of new business entities.Within the 500 m farming radius,the vast majority of new business entities have achieved moderate-scale operations if the land area adjacent to forest land,grassland,and general arable land was supplemented by gardens;however,a few entities could not achieve moderate-scale operations.From the village perspective,gardens were prioritized.Sixteen villages had planting areas and planting suitability that exceeded the average level of the study area,accounting for 23.53%.If combined with the reserve potential of the garden land,eight villages could improve their potential,accounting for 11.76%.Therefore,the conditions of large-scale citrus planting in the study area should be further improved,and the scale expansion of new citrus-planting business entities should receive additional scientific guidance.

Development of the Japanese Medication Adherence Scale and Verification of Its Reliability and Validity in Hypertensive Patients

A 32-Item Japanese Medication Adherence Scale had been developed as a tool for evaluating the medication-taking behavior of hypertensive patients and predicting therapeutic efficacy, and an Internet survey of 990 hypertensive patients throughout Japan was performed. As a result, factor 1 “Expectation of pharmacological efficacy” (9 items), factor 2 “Motivation to be self-controlled in taking medication” (6 items), and factor 3 “Negative feelings about taking medication” (4 items) were identified, comprising a total of 19 items. The scale was highly reliable. Because it proved capable of discriminating between the 2 groups with different medication-taking status and blood pressure, its validity had also been confirmed.

Estimation of Dynamic VaR in Chinese Stock Markets Based on Time Scale and Extreme Value Theory

The accuracy and time scale invariance of value-at-risk （VaR） measurement methods for different stock indices and at different confidence levels are tested. Extreme value theory （EVT） is applied to model the extreme tail of standardized residual series of daily/weekly indices losses, and parametric and nonparametric methods are used to estimate parameters of the general Pareto distribution （GPD）, and dynamic VaR for indices of three stock markets in China. The accuracy and time scale invariance of risk measurement methods through back-testing approach are also examined. Results show that not all the indices accept time scale invariance; there are some differences in accuracy between different indices at various confidence levels. The most powerful dynamic VaR estimation methods are EVT-GJR-Hill at 97.5% level for weekly loss to Shanghai stock market, and EVT-GARCH-MLE （Hill） at 99.0% level for weekly loss to Taiwan and Hong Kong stock markets, respectively.

Rovai＇s Classroom Community Scale and Its Application in Chinese College English Class

The purpose of this study is to introduce the CCS （Classroom Community Scale） established by Rovai （2002） and its application among freshmen in China with regard to how well their college English class builds a sense of classroom community. In addition, the reliability of CCS as applied in face-to-face classroom setting and the influence of gender and graduating high school of students on their perceptions of classroom community are also examined.

Reduction of NO_(x)emission based on optimized proportions of mill scale and coke breeze in sintering process

Reducing NO_(x) emission of iron ore sintering process in a cost effective manner is a challenge for the iron and steel industry at present.Effects of the proportion of mill scale and coke breeze on the NO_(x) emission,strength of sinter,and sinter indexes were studied by com-bustion and sinter pot tests.Results showed that the peak value of NO concentration,total of NO emission,and fuel-N conversion rate gradu-ally decreased as the proportions of the mill scale increased because NO was reduced to N_(2) by Fe_(3)O_(4),FeO,and Fe in the mill scale.The strength of sinter reached the highest value at 8.0wt%mill scale due to the formation of minerals with low melting point.The fuel-N conver-sion rate slightly fluctuated and total NO_(x) emission significantly decreased with the decreased proportions of coke breeze because CO forma-tion and content of N element in the sintered mixture decreased.However,the sinter strength also decreased due to the decrease in the amount of the melting minerals.Furthermore,results of the sinter pot tests indicated that NO_(x) emission decreased.The sinter indexes performed well when the proportions of mill scale and coke breeze were 8.0wt%and 3.70wt%respectively in the sintered mixture.

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.

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.

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.

Scale effect of coastal landscape pattern stability and driving forces:a case study of Guangdong Province,China

The long-term dynamic evolution and underlying mechanisms of coastal landscape pattern stability,driven by strong anthropogenic interference and consequently climate change,are topics of major interest in national and international scientific research.Guangdong Province,located in southeastern China,has been undergoing rapid urbanization over several decades.In this study,we quantitatively determined the scale threshold characteristics of coastal landscape pattern stability in Guangdong Province,from the dual perspective of spatial heterogeneity and spatial autocorrelation.An analysis of the spatiotemporal evolution of the coastal landscape was conducted after the optical scale was determined.Then,we applied the geodetector statistical method to quantitatively explore the mechanisms underlying coastal landscape pattern stability.Based on the inflection point of landscape metrics and the maximum value of the MoranⅠindex,the optimal scale for analyzing coastal landscape pattern stability in Guangdong Province was 240 m×240 m.Within the past several decades,coastal landscape pattern stability increased slightly and then decreased,with a turning point around 2005.The most significant variations in coastal landscape pattern stability were observed in the transition zone of rural-urban expansion.A q-statistics analysis showed that the explanatory power of paired factors was greater than that of a single driving factor;the paired factors with the greatest impact on coastal landscape pattern stability in Guangdong Province were the change in gross industrial output and change in average annual precipitation from 2010 to 2015,based on a q value of 0.604.These results will contribute to future efforts to achieve sustainable coastal development and provide a scientific basis and technical support for the rational planning and utilization of resources in large estuarine areas,including marine disaster prevention and seawall ecological restoration.

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.