Important Impact Factors Research Articles

Effect of vascular changes on prognosis after induced chemotherapy for advanced hypopharyngeal carcinoma

Objective: To analyze the clinical characteristics of two groups(vascular classification declines or not in narrow band imaging (NBI) of patients with advanced hypopharyngeal carcinoma after induced chemotherapy, to follow-up and compare the survival differences between the two groups, and to explore the effect of vascular changes on clinical prognosis after induced chemotherapy in patients with advanced hypopharyngeal carcinoma. Methods: Clinical data of 56 patients with advanced hypopharyngeal carcinoma from August 2014 to September 2016 in Beijing Tongren Hospital, Capital Medical University were collected. The patients were divided into two groups according to NBI vascular classification declines or not after induced chemotherapy. The survival of patients and the impact of different factors on the prognosis were retrospectively analyzed. SPSS 24.0 statistical software was used for analysis. Frequency data were compared between the two groups using χ(2) test. Kaplan-Meier method and Cox regression analysis were employed for survival analysis and Log-Rank test was used for inter-group comparison, P<0.05 was statistically significant. Results: There was significant difference in overall survival rate(OS) between two groups of patients with advanced hypopharyngeal carcinoma after induced chemotherapy (P<0.05). Multivariate analysis showed that NBI vascular classification changes after induced chemotherapy was the impact factor for prognosis of advanced hypopharyngeal carcinoma after induced chemotherapy. Conclusion: In addition to recurrence and metastasis, NBI vascular classification changes is the important impact factor for prognosis of advanced hypopharyngeal carcinoma after induced chemotherapy. Patients with NBI vascular classification declines have significant survival benefit. The patients with advanced hypopharyngeal carcinoma should be checked with NBI examination before and after induced chemotherapy. NBI should be included in the routine screening indicators for prognosis of advanced hypopharyngeal carcinoma.

Black carbon radiative forcing in south Mexico City, 2015

Black carbon (BC) is a strong radiative forcer. Because of its multiple effects on climate change, BC has been located as the second important impact factor of climate change only after carbon dioxide. Sources of BC include mainly diesel vehicles and biomass burning. Mexico’s pledges before the Paris Agreement are, between others, the reduction of BC emissions to up to 51% by 2030 compared with those in 2000. In order to know the exact contribution of BC to the emission inventory of Mexico it is necessary to estimate several BC properties, such as its radiative forcing and its effects on the radiative heating of the atmosphere, among others. In this work, a technique based on the available remote-sensing and ground-based data along with the Optical Properties of Aerosols and Clouds (OPAC) and the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) algorithms were used to estimate black carbon radiative forcing in the south of Mexico City during 2015. Land-based measurements were taken from a recently created monitoring network, the Aerosol Robotic Network (AERONET), and satellite measurements were obtained from the Moderate Resolution Imaging Spectroradiometer) (MODIS). Black carbon monthly concentrations along 2015 were between 1.9 and 4.1 μg/m 3 . Results show that monthly average radiative forcing on the top of the atmosphere over south Mexico City during 2015 was +30.2 ± 6.2 W/m 2 . November, December and January presented the highest radiative forcing values (+34.9, +46.9, +34.0, respectively). In addition, estimates of atmospheric heating show an average annual value of 0.85 ± 0.22 W/m 2 . Values of Angstrom > 1, as obtained in this work, indicate that aerosols are of the urban type and freshly emitted. Also, low single scattering albedo values in increasing wavelengths show that aerosols are mainly from urban-industrial aerosols.

THE EFFECT OF MICROECONOMIC FACTORS ON BUSINESS MODELS IN FINTECH INDUSTRY

The variety of financial technology (FinTech) companies and their activities poses heterogeneity in the business models of them. Not only the business environment has been changing rapidly, the financial services sector influences and triggers changes as well. And it is hard to determine whether and which changes influence the business model disruptively and which evolutionary. To enable management decision making easier, methodology for identification of possible microeconomic risks and their influence on the current activity and the whole business model of the company has to be shaped accordingly. The aim of this research is to find out what and how microeconomic factors affect business modelling of the FinTech companies. In this research the authors used a continuous comparative analysis method as well as content analysis method [1]. In interviews, experts were asked to assess the significance of specific microeconomic factors by using the Likert's scale. As a result of the research, the difference of the influence as well as their dependencies and modifications on business modelling was determined. This result forms the basis for conclusions about the most important microeconomic impact factors, the areas of their influence and possible consequences that affect business modelling of the FinTech company.

Dietary nitrate protects skin flap against ischemia injury in rats via enhancing blood perfusion

Insufficient blood supply is associated with high levels of necrosis in reconstructive surgery. Restoring blood flow to undersupplied ischemic tissue is the most important impact factor determining skin flap viability. Dietary nitrate, a significant source of nitric oxide, has multiple physiological functions, including regulator of blood flow, angiogenesis, and vasodilatation. However, the effects of dietary nitrate on ischemic skin flap remain unknown. The present study evaluated whether dietary nitrate supplementation altered blood flow of ischemic skin flap in rats. Our results showed that nitrate treatment significantly enhanced ischemic tissue survival. Mechanistically, nitrate therapy significantly increased serum nitrate and nitrite levels, blood perfusion, and angiogenesis. In addition, the circulating levels of Inflammatory mediators were decreased by nitrate supplementation. In conclusion, we demonstrated that dietary nitrate supplementation protected ischemic skin flap by enhancing ischemia-induced revascularization.

Simulation of soil water dynamics and water productivity of apple trees in different areas of Shaanxi Province, China

Using WinEPIC and partial least squares regression model, we compared the driving factors of water productivity and soil moisture dynamics of several mature apple plantations in Shaanxi from 1981 to 2016. For the hilly and gully region of northern Shaanxi, the residual loess platform region in Weibei, and Guanzhong Plain, the average annual yield of mature apple forests was 16.94, 22.62 and 25.70 t·hm-2, the annual average evapotranspiration was 511.2, 614.9 and 889.88 mm, and the water productivity was 3.81, 3.82 and 3.24 kg·m-3, respectively. In northern Shaanxi and Weibei regions, water stress was the most serious, with the average annual stress days being 54.89 and 28.38 d, respectively. The N-level stress in Guanzhong region was severe, with an average annual stress day of 25.87 d. The largest factor affecting the yield of apple plantations in the northern Shaanxi and northern Weibei regions was the precipitation. The standardized regression coefficients were 0.274 and 0.235, respectively, the amount of N applied had a significant impact on the yield, with regression coefficients of 0.224 and 0.232, respectively. The maximum impact factor in Guanzhong region was the amount of N applied, with a regression coefficient of 0.335, followed by the amount of water supplied and the amount of applied P. The regression coefficients were 0.154 and 0.147, respectively. The dominant factor affecting the water productivity of apple plantations in northern Shaanxi and Weibei was precipitation, and the standardized regression coefficients were 0.238 and 0.194, respectively. The most important impact factors in Guanzhong region were the amount of N applied and the amount of water supplied, and the regression coefficients were 0.182 and 0.178, respectively. During the simulation period, the total water consumption of apple plantations in the northern Shaanxi, Weibei and Guanzhong regions was 1152.17, 1342.95 and 1372.42 mm, respectively. The effective water content decline rates of 2-15 m soil layers were 63.44, 57.08 and 51.41 mm·a-1, respectively. The dry layer of deep soil appeared after 8, 13 and 17 years, and the dry layer was stable to 11 m deep for 18, 21 and 26 years, respectively, suggesting the drying status was severe. The management focus of apple plantations in different regions should be determined by the dominant factors of water productivity.

微尺度下城市公园人造绿地土壤水分的时空分异格局及其驱动机制

PDF HTML阅读 XML下载 导出引用 引用提醒 微尺度下城市公园人造绿地土壤水分的时空分异格局及其驱动机制 DOI: 10.5846/stxb201807061479 作者: 作者单位: 中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院大学,中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室,中国科学院生态环境研究中心城市与区域生态国家重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41571482，71734006）；国家重点研发计划重点专项（2016YFC0502804） Pattern and mechanism of microscale spatial-temporal variation in soil moisture at an artificial grassland in an urban park Author: Affiliation: State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences,,,,State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:水是生态系统的基本非生物组成要素，土壤水分对生态系统结构和功能有重要影响。微地形改造被证明能有效涵养水源、防止水土流失，并被广泛应用在生态恢复工程中。然而，在微尺度下人造生态系统土壤水分的时空分异格局及其驱动机制仍不明确。选择北京奥林匹克森林公园一处集合了4种不同地形的草地作为研究对象，对表层（0-10 cm）和深层（10-25 cm）土壤水分开展了长期的研究工作。研究结果表明，不同地形上土壤水分的季节变化特征没有显著差异，土壤温度是影响土壤水分季节变化的主要因素。在植被覆盖均匀的条件下，微地形对土壤表层水分的空间分布格局有显著影响，除洼地和冲沟两种特殊地形外，坡度决定的生态水文过程是主要的驱动机制；土壤深层水分没有明显的空间分布格局。研究结果说明在微尺度下，微地形通过影响土壤水分的空间分布格局，可能会对生态系统结构和功能产生潜在影响，应当在景观改造和生态恢复相关研究和工程应用中给予更多的关注。 Abstract:Water is the most basic element of ecosystem and is crucial to ecosystem structure and function. The transformation of microtopography has been widely used in ecological restoration to conserve soil water. However, the pattern and mechanisms of spatial-temporal variation in soil moisture at the micro-scale remain unclear. In this study, both topsoil (0-10 cm) and subsoil (10-25 cm) water content of four microtopographic types, which were located on an artificial grassland inside Beijing Olympic forest park, were monitored for one year. Only the topsoil water content was significantly affected by microtopography. Through eco-hydrological processes, slope gradient was an important impact factor for the spatial distribution of soil moisture. However, temporal variation in soil moisture showed no response to microtopography and was significantly affected by soil temperature. Therefore, further study is needed to reveal the potential effects of artificial microtopography on ecosystem structure and function, especially in the field of landscape transformation and ecological restoration. 参考文献 相似文献 引证文献

Mapping and evaluating cultivated land fallow in Southwest China using multisource data

Accurately and effectively mapping and evaluating cultivated land fallow has already become an important issue that has received much attention in China. However, systematically analysing regional cultivated land fallow remains inadequate because current studies have mainly focused on quantifying cultivated land fallow using statistical data based on administrative units or a single aspect of cultivated land fallow using high or medium spatial resolution images at the local or regional scales. Against the existing shortcomings, this study first developed an integrated index of cultivated land fallow (ILF) for mapping and evaluating cultivated land fallow in Southwest China using multisource spatial data. The performance of the ILF was validated by comparing its results with Google Earth images and ecological carrying capacity of cultivated land (TEC). And the spatial distribution of cultivated land fallow in Southwest China was evaluated at the regional, provincial and metropolitan scales. The results revealed that the ILF provided a reliable evaluation of cultivated land fallow in Southwest China. Compared to the Google earth images, the pixel with the high ILF value was the cultivated land that was found to prioritize fallow. There was also a significant correlation between ILF and TEC at the prefectural level in Sichuan, with an R2 value >0.65. In Southwest China, the cultivated land related to highly appropriate fallow (HAF) accounted for 5.73% of the total cultivated land in 2010. The cultivated land related to inappropriate fallow (IF) accounted for 53.26% and 37.36% in Sichuan and Chongqing but only comprised 22.90% and 19.72% in Yunnan and Guizhou, respectively. Special attention needs to be paid to Guiyang and Kunming, where the HAF made up 25.38% and 17.48% of their total cultivated land, respectively. Human activities have been found to already become the most important impact factors for cultivated land fallow in Southwest China. This study is especially valuable for providing a scientific basis for policy-making on viable cultivated land fallow policy in Southwest China.

Методичні підходи до визначення модельних підприємств лісового господарства

Підприємства лісового господарства зазнають впливу не лише соціально-економічних, а й природно-кліматичних чинників. На сьогодні актуальним питанням для підприємств лісової галузі України є визначення нормативних (оптимальних) організаційно-економічних параметрів їх діяльності за регіонами та їх уповільнення до реальних економічних умов функціонування. Розглянуто методичний підхід до визначення за регіонами модельних лісогосподарських підприємств (лідерів). Запропонована методика спирається на сценарний підхід у методології управління господарською діяльністю підприємств галузі та використовує методи міжгосподарського порівняльного аналізу. Прогнозування параметрів діяльності лісогосподарських підприємств за регіонами здійснюється за достовірними багатофакторними моделями з шістьма групами найвагоміших факторів впливу. Запропоновані оптимальні багатофакторні моделі організаційно-економічної діяльності лісогосподарських підприємств містять такі параметри: ресурсно-виробничого потенціалу (потужності), еколого-економічної (лісівничо-екологічної та економічної складових) та соціально-економічної ефективності (соціальної значущості для власних працівників та економіки регіону) за шістьма групами критеріїв. Запропонований методичний підхід апробовано на лісогосподарських підприємствах чотирьох областей України (Вінницької, Сумської, Харківської та Чернігівської).

Influence Oil Price towards Economic Indicators in Russia

This paper examines the effect of oil price shocks on the Russian economic indicators using time series for the period 1991-2016 year to cover all of oil price shocks. We use the method of vector autoregressive (VAR) and the Dickey-Fuller test (ADF) were utilized to investigate the long-run and the short-run relationships between variables. From the results shows that one of the most important external impact factor is the world price of oil. This research work suggests a positive and significant long-term relationship between oil prices and Russian GDP dynamics. The study recommended a reducing the dependence of the Russian economy on energy resources, including oil, the transformation of the economy from industrial to innovative and improvement of the investment climate in the country for a foreign investor, the stabilization of foreign economic policy, which should lead to the abolition of anti-Russian sanctions. Apart from the fact that this will make the Russian economy more attractive for foreign investments, the opportunity will again become one of the main players in the oil market.

Long-Term Atmospheric Visibility Trends and Their Relations to Socioeconomic Factors in Xiamen City, China

Atmospheric visibility (AV), one of the most concerning environmental issues, has shown a continuous decline in China’s urban areas, especially in Southeastern China. Existing studies have shown that AV is affected by air pollutants and climate change, which are always caused by human activities that are linked to socioeconomic factors, such as urban size, residents’ activities, industrial activities, and urban greening. However, the contribution of socioeconomic factors to AV is still not well understood, especially from a long-term perspective, which sometimes leads to ineffective policies. In this study, we used the structural equation model (SEM) in order to quantify the contribution of socioeconomic factors on AV change in Xiamen City, China, between 1987–2016. The results showed that the annual average AV of Xiamen between 1987–2016 was 12.00 km, with a change rate of −0.315 km/year. Urban size, industrial activities, and residents’ activities were found to have a negative impact on AV, while the impact of urban greening on the AV was modest. Among all of the indicators, the number of resident’s vehicles, total retail sales of consumer goods, and household electricity consumption were found to have the highest negative direct impact on the AV. The resident population, urban built-up area, and secondary industry gross domestic product (GDP) were the most important indirect impact factors. Based on our results, we evaluated the existing environmental regulations and policies of Xiamen City.

Effect of the sheet size on the thermal stability of silicone rubber–reduced graphene oxide nanocomposites

AbstractThe structures of differently sized reduced graphene oxides (rGOs), the dispersion state, and the compatibility of rGO with silicone rubber (SR) are important impact factors on the properties of SR–rGO nanocomposites. To analyze the influence of the size of rGO on the properties of SR‐based nanocomposites, three differently sized rGO sheets were introduced into SR to fabricate a series of SR‐based nanocomposites. The SR–middle‐sized reduced graphene oxide (MrGO) nanocomposites showed the best mechanical and thermal properties. Compared with the blank sample, the SR–MrGO nanocomposites presented remarkable two‐fold and three‐fold increases in the tensile modulus and strength values. The initial degradation temperature increased nearly 40 °C. In this study, we investigated the size effect of graphene on the thermal stability by examining the thermal degradation mechanism of the different SR–rGO nanocomposites in detail. Ultimately, this research may suggest a facile approach for improving the thermal stability of SR. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47034.

A feature-based prediction method for energy consumption of machining process and its application

Energy consumption prediction for machining process is the basis of the study of energy performance and energy efficiency assessment in manufacturing systems. The existing energy consumption prediction methods for manufacturing process are mainly focused on processing equipment, processing parameters and material. However, part features are also important impact factors for energy consumption of manufacturing process, but these are not studied systematically. In this paper, an energy consumption prediction method based on part feature is proposed. Firstly, the energy consumption of a part feature was analyzed, and an energy consumption model was established based on part multi-features by using matter element theory. Then, a hybrid reasoning method considering case-based reasoning and rule reasoning was studied, and an energy consumption prediction method of manufacturing process was proposed. Finally, a case study of a shaft part was given to verify the effectiveness of the above methods.

Spatiotemporal Dynamics of CO2 Emissions in Chongqing: An Empirical Analysis at the County Level

China's CO2 emissions present obvious temporal and spatial distribution characteristics. Therefore, the study of spatiotemporal dynamics of CO2 emissions could provide useful information for the government and policy-makers on viable CO2 emissions mitigation in China. Using Chongqing as a case study, we investigated the spatiotemporal dynamics of CO2 emissions at the county level (38 counties) from 1997 to 2012.The mathematical statistical method, spatial autocorrelation, and rank size rule were employed to evaluate the CO2 emissions change in detail. The results showed that all of the counties in Chongqing have experienced a rapid growth of CO2 emissions, but the two dimensional structure of CO2 emissions has not changed. The Global Moran's I clearly decreases with a small fluctuation, and these values gradually decrease from 0.56 in 1997 to 0.40 in 2012.In addition, the HH clusters are concentrated in some counties in the downtown areas. Based on the rank size rule analysis, the slope values q decrease from -1.35 in 1997 to -0.88 in 2012, indicating a clear scattered pattern of CO2 emissions in Chongqing at the county level. It has also been proven that the proportion of second industries and the urbanization rate are more important impact factors for CO2 emissions than the population.

Controls of carbon flux in a semi-arid grassland ecosystem experiencing wetland loss: Vegetation patterns and environmental variables

Inner Mongolia, China, contains the world’s largest grassland ecosystem. This has many areas of wetland, which provide important ecological services, especially carbon sequestration in the semi-arid terrestrial ecosystems. However, the area of wetland has decreased sharply in the past two decades. This study examined ways to recognize and extract wetland from grassland to determine the difference among net ecosystem exchange (NEE), gross primary production (GPP) and ecosystem respiration (Reco) between wetland and grassland and to evaluate the influence of wetland loss on carbon sequestration in the grassland. The eddy covariance (EC) flux technique was coupled with the Vegetation Photosynthesis and Respiration Model (VPRM) to upscale the spatial patterns of carbon flux. The results showed that the region was a carbon source in 2016, probably caused by overharvesting and degradation of forests. The value of the NEE (average: 6.63 ± 3.50 g C m−2 d−1) in grassland was apparently higher than that in wetland (average: 0.86 ± 1.69 g C m−2 d−1), which suggested that the capability of carbon sequestration in wetland was still stronger than that in grassland even in carbon loss condition. The results showed a positive relationship between aboveground biomass (AGB) and ground-based daily GPP or Reco for both wetland and grassland and a negative relationship between AGB and NEE. The ground-based daily NEE was also significantly related to soil water content (SWC) but showed no relationship with daily precipitation (PRE), which suggested that SWC was a more important impact factor than precipitation on CO2 flux exchange in the study area. The change between wetland and grassland did not influence the positive relationship between AGB or SWC and CO2 flux. Our study provides a new way to determine the spatial CO2 flux exchange and its controlling factors (environmental variables and vegetation patterns) and to successfully analyze its differences in wetland and grassland.

Gate-to-Gate Energy Consumption in Chemical Batch Plants: Statistical Models Based on Reaction Synthesis Type

Energy consumption in the chemical industry is an important operating cost and environmental impact factor and reducing it is also explicitly mentioned as one of the key principles of green chemistry. Energy consumption has thus been included in diverse process design and evaluation tools as a key metric. However, measurements of energy consumption at the process equipment level are scarce, especially in fine chemical production typically performed in multiproduct and multipurpose batch plants. In this work, we present a shortcut approach based on statistical models, such as probability density functions (PDF) and classification trees, for estimating steam consumption which typically represents the highest energy utility consumption in batch plants. The output of these models is in the form of intervals derived from PDF interquartile ranges and as classes derived from the classification trees, respectively. The validation results (i.e., goodness of fit, cross validation, and case studies) show that the mo...

Retrieval of time series three-dimensional landslide surface displacements from multi-angular SAR observations

A major limitation for wide application of Synthetic Aperture Radar (SAR) remote sensing in mapping landslide surface displacements is the intrinsic gap between the ultimate objective of measuring three-dimensional displacements and the limited capability of detecting only one or two-dimensional displacements by repeat-pass SAR observations of identical imaging geometries. Although multi-orbit SAR observations of dissimilar viewing geometries can be jointly analyzed to inverse the three-dimensional displacements, the reliability of inversion results might be highly questionable in case of continuous motion because of the usually asynchronous acquisitions of multi-orbit SAR datasets. Aiming at this problem, we proposed an approach of retrieving time series three-dimensional displacements from multi-angular SAR datasets for step-like landslides in the Three Gorges area in this article. Firstly, time series displacements of a common ground target in the azimuth and line-of-sight (LOS) direction can be estimated using traditional methods of SAR interferometry (InSAR) and SAR pixel offset tracking (POT), respectively. Then, a spline fitting and interpolation procedure was employed to parameterize the displacement history in the sliding/dormant periods of step-like landslides and estimate displacements from multi-angular observations for identical date series. Finally, three-dimensional displacements can be inverted from these synchronized multi-angular measured displacements in traditional ways. As a case study, the proposed method was applied to retrieve the three-dimensional displacements history of the Shuping landslide in the Three Gorges area, China. Comparisons between SAR-measured displacements and measurements of global positioning system (GPS) showed good agreement. Furthermore, temporal correlation analyses suggest that reservoir water level fluctuation and rainfall are the two most important impact factors for the Shuping landslide stability.

Exploring spatiotemporal patterns of electric power consumption in countries along the Belt and Road

Fully understanding spatiotemporal patterns of electric power consumption (EPC) is one of the key questions related to sustainable socioeconomic and environmental development in countries along the Silk Road Economic Belt and the 21st-Century Maritime Silk Road (hereinafter referred to as the Belt and Road countries). However, studies about spatiotemporal patterns of EPC in the Belt and Road countries are still scarce due to the lack of reliable data. This study attempted to investigate spatiotemporal patterns of EPC in the Belt and Road countries from multiple perspectives. Firstly, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime stable light data were used to estimate EPC from 1992 to 2013. Subsequently, the mathematical statistic method, standard deviational ellipse, rank size rule, and correlation analysis were employed to evaluate the EPC change in detail. The results reveal that the EPC growth mainly occurs in the developing countries, especially in China. The geographical distribution of EPC in the Belt and Road countries is oriented in the Northwest-Southeast direction between 1992 and 2013. Based on the rank size rule analysis, the slope values of q are −2.392 and −2.175 between 1992 and 2013, with an average R2 value of 0.664, indicating a clear clustering pattern of EPC. It is also proved that GDP is a more important impact factor to EPC than the population. Our findings can offer an effective way to understand spatiotemporal evolution characteristics of EPC in the Belt and Road countries, and provide references for regional socioeconomic development and cooperation.

Passengers’ intentions to use low-cost carriers: An extended theory of planned behavior model

The purpose of this paper is to develop and test an extended research model based on the theory of planned behavior (TPB) that identifies factors influencing the intention to use low-cost carriers (LCCs) in China. A survey of 596 passengers was conducted in two major airports in China, and a structural equation modeling method was used to test the hypotheses. The results indicate that attitudes, subjective norms, price, service quality, access, uncertainty avoidance, and technology self-efficacy significantly influence passenger decisions to travel by LCCs, while perceived behavioral control (PBC) and frequency are not considered important impact factors. Price is the strongest determinant of the intention to use LCCs, followed by service quality. The findings enhance the understanding of LCC passenger motivation from psychological, service, and cultural perspectives, providing useful implications for LCCs in improving marketing strategies and customer services.

How Does Suppliers’ Fairness Affect the Relationship Quality of Agricultural Product Supply Chains?

Although many studies have suggested that the relationship between different supply chain members significantly affects agricultural product quality, suppliers’ perceptions of fairness, which greatly influence their decisions on building the relationship quality, are often overlooked. Particularly, the empirical evidence to investigate the impacts of suppliers’ fairness on the relationship quality and the factors that affect the suppliers’ fairness is missing, and therefore this knowledge gap needs to be filled by new research. Herein, we conducted a survey of 450 agricultural product suppliers and systemically analyzed the impact of antecedents on fairness perception and the impact of fairness perception on relationship quality. In addition, we developed a structural equation model and found that information sharing and price satisfaction had significantly positive effects on procedural fairness and distributive fairness, respectively. Furthermore, our studies demonstrated that procedural fairness is more important in improving the relationship quality than distributive fairness. However, supplier dependence is another important impact factor, and it greatly decreases the positive effects of suppliers’ fairness on relationship quality. In summary, the study results provide several managerial implications and extend our understanding of the importance of suppliers’ fairness in the relationship quality, which involves product development with respect to the supplier’s performance.

FACTORS AFFECTING THE PATTERN OF VEGETATION CARBON DENSITY IN A KARST REGION IN NORTHWEST GUANGXI, CHINA

The changing characteristics of vegetation carbon patterns in the karst region of northwest Guangxi, China and their impact factors were analyzed on the basis of vegetation inventory data from 2005 to 2010. A radial basis function network model (RBFN) was constructed using data from 1377 samples and 13 environmental factors. The results for the 5-year study period were as follows: (1) The total carbon storage of vegetation had increased with an annual growth rate of 1.84% and the carbon density of vegetation increased from 29.04 t hm-2 to 29.57 t hm-2. The carbon density in the west (>40 t hm-2) was greater than that in the Middle East (<25 t hm-2). Hot spot analysis revealed a random distribution of vegetation carbon density in 2005, but a highly aggregated distribution in 2010. (2) The four most important impact factors on spatial distribution of vegetation carbon density in this area were land type, forest type, forest category, and vegetation type (significance <50%). The least important factors were location, slope, aspect, and elevation (significance of 2 11%). Vegetation carbon density increased significantly with the implementation of rocky desertification control measures. Factors changed by human activities had much greater impacts than topographic factors on the spatial distribution of vegetation carbon density. Therefore, the Ecological Immigration Program, returning farmland to forests, and rocky desertification control measures had an important effect on the pattern of vegetation carbon density. Key words: Guangxi China, impact factors, karst, northwest, pattern characteristic, radial basis function network (RBFN), vegetation carbon