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In the chemical flooding process, the premature breakthrough of chemical agents in production wells results in a large waste of chemical agents and increases the volume and processing difficulty of the produced fluids. The early warning method of chemical agent channeling can predict the strength of agent channeling in advance. The practice of chemical flooding shows that the production performance can be used for early warning of chemical agent channeling. In this paper, we analyze the relationship between cumulative oil production and cumulative polymer production of production wells in polymer–surfactant flooding. Three types of curves according to the enhanced oil production characteristics of chemical flooding, including convex type, S‐type, and concave type. We use the drop speed of the water–oil ratio and the rapid‐decline speed of water cut as early warning indicators to predict the channeling coefficient. A Latin hypercube experimental design method is used to design a polymer–surfactant flooding scheme with the main control factors of the channeling coefficient and early warning indicators. Numerical simulation is used to calculate samples of the channeling coefficient and early warning indicators under various conditions. The drop speed of the water–oil ratio reference value model and the rapid‐decline speed of the water cut reference value model are determined with a multiple regression method. A prediction model for the chemical agent channeling coefficient is established using the deviation coefficient of an early warning index. The method is applied in the Ng54‐61 polymer–surfactant flooding pilot area in the west of the Gudong Seventh District, Shengli Oilfield, China, and the error between the predicted result and the actual value is less than 10%. This research is helpful in taking effective antichanneling measures and improving the oil recovery degree of chemical flooding reservoirs. [ABSTRACT FROM AUTHOR]

During the process of determining carbon emissions from coal using the emission factor method, third-party organizations in China are responsible for verifying the accuracy of the carbon emission data. However, these verifiers face challenges in efficiently handling large quantities of data. Therefore, this study proposed a fast screening method that utilizes multiple linear regression (MLR), in combination with the stepwise backward regression method, to identify problematic carbon emission data for the lower calorific value (LCV) and carbon content (C) of coal. The results demonstrated the effectiveness of the proposed method. The regression models for LCV and C exhibited high R-squared (R2) values of 0.9784 and 0.9762, respectively, and the root mean square error (RMSE) values of the validation set were 0.32 MJ/kg and 0.80% for LCV and C, respectively, indicating strong predictive capabilities. By analyzing the obtained results, the study established the optional error threshold interval for the LCV and C of coal as 2RMSE–3RMSE. This interval can be utilized as a reliable criterion for judging the quality and reliability of carbon emission data during the verification process. Overall, the proposed screening method can serve as a valuable tool for verifiers in assessing the quality and reliability of carbon emission data in various regions. [ABSTRACT FROM AUTHOR]

Background: Most previous studies on women of childbearing age have focused on reproductive health and fertility intentions, and evidence regarding the comprehensive health status of women of childbearing age is limited. This study aimed to comprehensively examine the health status of women of childbearing age through a multi-method and multi-indicator evaluation, analyze the factors that influence their overall health, and provide sound recommendations for the improvement and promotion of healthy behaviors. Methods: Data on women of childbearing age living in Shanxi Province were collected between September 2021 and January 2022 through online and offline surveys. The k-means algorithm was used to assess health-related patterns in women, and multivariate nonconditional logistic regression was used to assess the influencing factors of women's overall health. Results: In total, 1,258 of 2,925 (43%) participants were classified as having a good health status in all five domains of the three health dimensions: quality of life, mental health, and illness. Multivariate logistic regression showed that education level, gynecological examination status, health status of family members, access to medical treatment, age, cooking preferences, diet, social support, hand washing habits, attitude toward breast cancer prevention, and awareness of reproductive health were significantly associated with different health patterns. Conclusions: The comprehensive health status of women of childbearing age in Shanxi Province is generally good; however, a large proportion of women with deficiencies in some dimensions remains. Since lifestyle greatly impacts women's health, health education on lifestyle and health-related issues should be strengthened. [ABSTRACT FROM AUTHOR]

This study seeks to compare the impact of the Subindices of the Global competitiveness index on the global competitiveness index of India, Pakistan and China during the period of 2008 to 2017. The study uses multiple regression equations to examine the impact of sub-indices of GCI on the GCI of India, Pakistan and China. It uses comparative analysis to find out the result. The global competitiveness index ranks a country based on its competitiveness capacity. This index is released every year by the World Economic Forum to measure competitiveness among countries. The study first tests the normality of the data by using the Jacque-Bera test. The stationarity of the data is checked by using the unit root test. The study examines multicollinearity, autocorrelation, and heteroscedasticity in the regression model. The study uses a residuals test to check the validity of the regression model. The study applies BDS (Brock-Dechert-Scheinkman) independence test to examine the non-linear pattern of the residuals distribution. It is found that series are not independently identically distributed. And it is observed that variables are stationary at the first difference, and there is a significant impact of sub-indices of GCI ON the GCI of India, Pakistan and China. [ABSTRACT FROM AUTHOR]

The combination of technology and finance has a great potential impact on regional social and economic development, and strategic emerging industries are the convergence of technological innovation and financial support, the development of which have great significance for industrial structure adjustment and industrial quality improvement. The geographical distribution of emerging strategic industries in China is uneven. We selected 18 provinces with relatively concentrated emerging industries. 206 STI board enterprises in 2020 were collected. A three-stage DEA model was used to measure the input--output efficiency of the integrated development of science and technology finance. Also, we used a regression model to examine the path of integrated development of science and technology innovation and financial support. The research finds that the development of strategic emerging industries has a large demand for financial support and obvious regional differences, and the government plays a strong guiding role in their development as well. At the end of the research, countermeasures and suggestions for the development of strategic emerging industries are given. [ABSTRACT FROM AUTHOR]

Within urban green spaces, tree species diversity is believed to correlate with aboveground biomass, though there is some disagreement within the literature on the strength and directionality of the relationship. Therefore, we assessed the relationship between the biodiversity of woody species and the aboveground biomass of woody plant species in the tropical, coastal city of Haikou in southern China. To accomplish this, we obtained comprehensive tree and site data through field sampling of 190 urban functional units (UFUs, or work units) corresponding to six types of land uses governmental‐institutional, industrial‐commercial, park‐recreational, residential, transport infrastructure, and undeveloped area. Based on our field data, we investigated the relationship between tree species diversity and aboveground biomass using multiple regression, which revealed significant relationships across all five types of land uses. Aboveground biomass in green spaces was also correlated with anthropogenic factors, especially time since urban development, or site age, annual maintenance frequency by human caretakers, and human population density. Among these factors, maintenance is the strongest predictor of aboveground biomass in urban green space. Therefore, this study highlights the critical role of maintenance of urban green space in promoting both aboveground biomass and woody biodiversity in urban ecosystems and, consequently, on urban ecosystem services. Our findings contribute to a deeper understanding of the ecosystem services provided by communities of woody plant species in urban areas. [ABSTRACT FROM AUTHOR]

• Models for household recycling behaviour in high-rise buildings were evaluated. • The used of recycling facilities can be predicted by physical setting. • The use of informal recycling sectors can be predicted by housing type. • Implications for public design in high-density residential areas are provided. • It provides insights into public design in high-rise residential areas. Recycling strategies and waste management for the source separation of recyclables are still in their infancy in China and many other developing countries. Unlike formal recycling systems with strictly regulated management in high-income countries, waste management and recycling activities in low-income and middle-income countries are predominantly informal. Formal recycling systems often have very small amounts of recyclables in comparison to informal recycling systems. Considering the Chinese case of urban Guangzhou, where formal and informal recycling systems coexist, this study investigated household recycling behaviour and explored the sociodemographic and contextual factors that affect this behaviour. Based on data collected through questionnaire surveys and interviews, a model of the use of public recycling facilities (UPRF) and a model of the use of informal recycling sectors (UIRS) were evaluated using correlations and multiple regression analyses. The findings indicated that the use of public recycling facilities can be significantly predicted by the launch of a source separation scheme, the physical setting and satisfaction with public recycling facilities. The sociodemographic variables did not significantly predict the use of public recycling facilities but did significantly predict the use of informal recycling sectors. This study's findings have implications for researchers and policymakers and shed light on public designs for sustainability. [ABSTRACT FROM AUTHOR]

As one part of the 'Three Norths' forest protection system, dense farmland shelterbelt networks in northeastern China could greatly modify water and sediment flows. In this paper, catchment soil erosion rate and sediment yield (SY) that are impacted by farmland shelterbelts were estimated using WaTEM/SEDEM model. The shelterbelts reduced catchment soil erosion and SY to some extent. The mean soil erosion rate and specific sediment yield (SSY; defined as the ratio of SY to catchment area; t km−2 yr−1) of the 25 reservoir catchments decreased from 351.6 and 93.9 t km−2 yr−1 under the supposed scenario without shelterbelts to 331.1 t km−2 yr−1 and 86.3% t km−2 yr−1 under the current situation with shelterbelts. The sediment trap efficiencies (STEs) varied from 0.01% to 23.6% with an average value of 7.6%. The STEs were significantly correlated with shelterbelt density, catchment perimeter, topographic factors, RUSLEP‐factor and land use patterns including patch density (PD), patch cohesion index (COHESION), Shannon's diversity index (SHDI) and aggregation index (AI). The multiple regression equation involving factors of catchment's topography and morphology and land use pattern has a satisfactory performance, and mean slope gradient (MSG) and AI explained most of the variability of shelterbelts' STE. This information can help land managers to better design shelterbelts and to reduce water‐derived soil loss at catchment scale. [ABSTRACT FROM AUTHOR]

Travel burden on rural residents is an important theme in transport geography. However, the empirical evidence for this remains scarce. This paper aims to shed light on rural travel burden by examining the relationship between the rural built environment and villagers' travel burden, as measured by the time and money spent on essential and regional trips. A national survey of rural residents in 287 villages across China is analysed. The results show that residents living in rural areas are more likely to be faced with travel burden than are urban residents when accessing livelihood opportunities in local rural settlements and regional urban centres. The built environment attributes are significantly correlated with residents' travel burden. Specifically, the distance from the village to the destination has the strongest relationship with essential trips compared with other built environment variables. Villagers tend to incur higher time costs for an essential or regional trip when paved roads, bus stations and high-quality roads are less accessible. Bus transfer times from the village to the town centre, the population density, and the accessibility of local facilities also show significantly correlation with villagers' travel cost. Moreover, those residents who are elderly, low-income, or have a physical disability are more likely to suffer from high travel burden. The findings will enhance our understanding of the role of land use and transport policies in releasing villagers' travel burden to achieve sustainable transport development in rural contexts. [ABSTRACT FROM AUTHOR]

A field survey was conducted to investigate the concentrations of chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb) in vegetables, corresponding cultivated soils and irrigation waters from 36 open sites in high natural background area of Wuzhou, South China. Redundancy analysis, Spearman’s rho correlation analysis and multiple regression analysis were adopted to evaluate the contributions of impacting factors on metal contents in the edible parts of vegetables. This study concluded that leafy and root vegetables had relatively higher metal concentrations and adjusted transfer factor values compared to fruiting vegetables according to nonparametric tests. Plant species, total soil metal content and soil pH value were affirmed as three critical factors with the highest contribution rate among all the influencing factors. The bivariate curve equation models for heavy metals in the edible vegetable tissues were well fitted to predict the metal concentrations in vegetables. The results from this case study also suggested that it could be one of efficient strategies for clean agricultural production and food safety in high natural background area to breed vegetable varieties with low heavy metal accumulation and to enlarge planting scale of these varieties. [ABSTRACT FROM AUTHOR]

Vocal disorders are very common occupation-related disease in teachers, though it has never been given enough attention in China. As a result, the occupational health care of professional voice users is surprisingly undeveloped compared to the attention given to occupational hearing disorders or many other occupational symptoms. The aim of the present study was to assess the prevalence of voice problems in the general population of Chinese university teachers, and explore whether their voice problems affected their daily life, their social life and their work. A voice strain and voice handicap index questionnaire was administered to university instructors of English (N = 156) in six Chinese universities. Results indicated that voice strain is prevalent among Chinese university instructors. The respondents' self-perceptions revealed that voice strain was significantly correlated with theirjob and their daily activities. [ABSTRACT FROM AUTHOR]

Source apportionment is crucial to the prevention and control of heavy metals in the soil. The major methods focus on the identification of soil heavy metals from different pollution sources. However, they are unsuited to the source apportionment at a regional scale due to ignoring the spatial heterogeneity of heavy metal content caused by soil formation. Thus, we built a source apportionment model by introducing the weathering and leaching coefficients as the key parameters of soil-forming processes. In this study, we selected Liaohe Plain in China as the study area, which was the starting point of China's industrial development, with dense industrial areas and high levels of heavy-metal emission. Heavy metals concentrations in surface and deep soil of reference and grid points were collected as model data. The results showed that the average contribution rates of soil-forming process to Cd, Hg, As, and Pb were 82.7%, 85.2%, 88.6%, and 91.7%, respectively, and those of anthropogenic activities were 17.3%, 14.8%, 11.4%, and 8.3%, respectively. Spatial distribution of contribution rates showed the superposition of soil environmental background and pollution sources. This study provides a feasible method to quantify heavy metals contents from natural and anthropogenic sources at a regional scale. [Display omitted] • Source apportionment was built for heavy metal of surface soil at regional scale. • Data contained heavy metals in surface and deep soil of reference and grid point. • Nature source content was estimated by weathering and leaching of reference point. • Anthropogenic content was calculated by regression coefficient and grid point value. [ABSTRACT FROM AUTHOR]

• Energy benchmarking models were developed based on simulation and regression. • Reasonable VAC energy consumption were proposed for different climates in China. • Impacts of service-related variables on VAC energy use were quantitively analyzed. The energy consumption of Ventilation and Air Conditioning (VAC) systems in subway stations has attracted much attention, aiming to figure out energy-saving potentials and improve energy efficiency. Benchmarking is a useful method to evaluate energy performance of VAC systems during the operational stage. This study describes the development of an energy benchmarking model for the analysis of VAC energy consumption in subway stations with platform screen door systems in a variety of climate regions in China. Firstly, the Constraint Value (CV) and Leading Value (LV) of VAC energy use were simulated using a validated theoretical energy model, which represent the "general" and "superior" level of the VAC energy use, respectively. Results show that, for the 2,520 simulated cases, CV ranges from 184 to 859 × 103 kWh/year and LV ranges from 178 to 529 × 103 kWh/year, with different ranges for cold, hot-summer cold-winter, and hot-summer warm-winter region. Next, the simulated values of CV and LV were applied to establish an energy benchmarking model using the ordinary least square approach. For each climate region, the regressive energy benchmarking models for CV and LV were established and validated by cross-validation. Results show that R2 are 0.753–0.903 and MBE of the test set are 2.1–7.1%, indicating a good fit for the regressive benchmarking models. In order to further test their application, the regressive models were then applied to existing subway stations. Finally, the impacts of service-related variables, i.e. number of passengers, train departure density, and tunnel length, on the CV and LV were discussed. The proposed energy benchmarking model and analysis provide a convenient and effective tool for operators and managers to evaluate VAC energy consumption status and assess energy-saving potentials for subway stations. [ABSTRACT FROM AUTHOR]

Vocal disorders are very common occupation-related disease in teachers, though it has never been given enough attention in China. As a result, the occupational health care of professional voice users is surprisingly undeveloped compared to the attention given to occupational hearing disorders or many other occupational symptoms. The aim of the present study was to assess the prevalence of voice problems in the general population of Chinese university teachers, and explore whether their voice problems affected their daily life, their social life and their work. A voice strain and voice handicap index questionnaire was administered to university instructors of English (N = 156) in six Chinese universities. Results indicated that voice strain is prevalent among Chinese university instructors. The respondents' self-perceptions revealed that voice strain was significantly correlated with theirjob and their daily activities. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the accuracy of Cameriere's methods on dental age estimation in the northern Chinese population. A sample of orthopantomographs of 785 healthy children (397 girls and 388 boys) aged between 5 and 15 years was collected. The seven left permanent mandibular teeth were evaluated with Cameriere's method. The sample was split into a training set to develop a Chinese-specific prediction formula and a test set to validate this novel developed formula. Following the training dataset study, the variables gender ( g), x (canine teeth), x (first premolar), x (second molar), N, and the first-order interaction between s and N contributed significantly to the fit, yielding the following linear regression formula: Age = 10.202 + 0.826 g − 4.068 x − 1.536 x − 1.959 x + 0.536 N − 0.219 s ⋅ N, where g is a variable, 1 for boys and 0 for girls. The equation explained 91.2 % ( R = 0.912) of the total deviance. By analyzing the test dataset, the accuracy of the European formula and Chinese formula was determined by the difference between the estimated dental age (DA) and chronological age (CA). The European formula verified on the collected Chinese children underestimated chronological age with a mean difference of around −0.23 year, while the Chinese formula underestimated the chronological age with a mean difference of −0.04 year. Significant differences in mean differences in years (DA − CA) and absolute difference (AD) between the Chinese-specific prediction formula and Cameriere's European formula were observed. In conclusion, a Chinese-specific prediction formula based on a large Chinese reference sample could ameliorate the age prediction accuracy in the age group of children. [ABSTRACT FROM AUTHOR]

Soil profiles from 0 to 90 cm depth were collected to investigate temporal dynamics and profile variations in soil urease activities in Carex meyeriana wetland and to capture the direct and indirect effects of soil nutrients on soil urease activities in the Changbai Mountain valley wetland of China during the periods from 2002 to 2003. Our results showed that soil urease activities decreased gradually with increasing depth along soil profiles with higher coefficients of variation in the upper soils, which were positively correlated with microorganism numbers. Soil urease activities during the growing season from May to September were higher than those in April. Path analysis showed that both NO3−-N and dissolved Mg (DMg) had direct positive effects on soil urease activities and they had the highest direct path coefficients and determination coefficients compared to other soil nutrients. Total contents of Cu and Fe showed direct and indirect positive effects on soil urease activities through NO3−-N, whereas they showed negative indirect effects through DMg. Despite that total Mg and dissolved K showed direct adverse effects on soil urease activities, the indirect effects through NO3−-N were much higher. In contrast, total Zn showed both direct and indirect adverse effects on this enzyme. However, the positive indirect effects of soil organic matter, total N, and total P on soil urease activities were more significant than their direct effects. The findings of this work had a potential important role in monitoring soil biological quality in N-limited mountain valley wetland ecosystems. [ABSTRACT FROM AUTHOR]

The Chinese hotel industry is undergoing brisk growth, particularly in the budget hotel segment. Thus, an exploratory study was conducted to determine the factors facilitating growth of the budget hotel market. A strengths, weaknesses, opportunities and threat analysis was undertaken to identify future trends and to assess market potential. Relevant implications and suggestions were made to the industry so as to remedy the identified weaknesses and overcome the threats. Some regression models about the expansion of different star-rated hotels in China were also developed. It was found that overall disposable income was the most significant factor in explaining and predicting the number of budget hotel rooms. [ABSTRACT FROM AUTHOR]

Abstract: An attempt was made to develop multiple regression models for office buildings in the five major climates in China – severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. A total of 12 key building design variables were identified through parametric and sensitivity analysis, and considered as inputs in the regression models. The coefficient of determination R 2 varies from 0.89 in Harbin to 0.97 in Kunming, indicating that 89–97% of the variations in annual building energy use can be explained by the changes in the 12 parameters. A pseudo-random number generator based on three simple multiplicative congruential generators was employed to generate random designs for evaluation of the regression models. The difference between regression-predicted and DOE-simulated annual building energy use are largely within 10%. It is envisaged that the regression models developed can be used to estimate the likely energy savings/penalty during the initial design stage when different building schemes and design concepts are being considered. [ABSTRACT FROM AUTHOR]

Establishing better nitrogen (N) management strategies is of great significance for sustaining crop production and reducing environmental pollution. However, there is limited knowledge about N fertilizer management practices with soil nutrient supply, N leaching, crop productivity and nutrient use efficiency (NUE) reaching the desired level simultaneously. In this study, pot experiment was conducted to evaluate the effects of N fertilizer and in combination with fulvic acid (FA) on NUE and nutrient supply in a moderate-salinized soil (with total salt content 3.30 g kg−1 and EC 1:5 1.18 dS m−1). Ten treatments were included: treatment without any addition (CK); 100%, 85% and 70% of the conventional inorganic N fertilizer addition rate (100% CF, 85% CF and 70% CF); 100% CF, 85% CF and 70% CF combined with 75 kg ha−1 FA (100% CF + F1, 85% CF + F1, and 70% CF + F1), respectively; and 100% CF, 85% CF and 70% CF combined with 150 kg ha−1 FA (100% CF + F2, 85% CF + F2, and 70% CF + F2), respectively. In order to further investigate the effects of combining N fertilizer and FA applications on soil N leaching losses, part of the fertilizer management practices were selected to conduct a soil leaching experiment. The results demonstrated that the Olsen-P for the upper 20 cm of soil was significantly affected by N fertilization (P ≤ 0.01). In the treatments with inorganic fertilization alone, the concentration of soil mineral N at 0–10 cm soil depth decreased with decreasing level of fertilizer N, while Olsen-P content and alkaline phosphatase activity decreased with increasing N fertilizer application rate. The application of FA significantly increased alkaline phosphatase activity. Overall, the total mineral N leaching losses increased exponentially with increasing annual fertilizer N application rates, while the addition of FA decreased the total mineral N leaching factor (TLF N). Furthermore, the results of multiple regression analysis revealed that wheat grain yield, plant P uptake, plant N uptake, harvest index of applied fertilizer N (HI N), partial factor productivity of applied fertilizer P (PFP P), recovery efficiency of P (RE P) and recovery efficiency of N (RE N) reached ≥85% of their maximum concurrently, when the application amounts of N fertilizer and FA varied from 300 to 370 kg ha−1 and from 164 to 250 kg ha−1, respectively. These results of this study provide a basis for appropriate nitrogen (N) management in salt-affected soils and for the improvement of the sustainability of agricultural development in China. • Olsen-P content decreased with increasing nitrogen (N) application rate. • Fulvic acid addition decreased the total mineral nitrogen leaching factor (TLF N). • Combined application of fulvic acid with optimum N fertilization could improve wheat grain yield and nutrient use efficiency. • The recommended application rates of N fertilizer and fulvic acid were 300–370 kg ha−1 and 164–250 kg ha−1, respectively. [ABSTRACT FROM AUTHOR]

Abstract: This article questions the effectiveness and viability of rural Tax-for-Fee reform (Fei Gai Shui) on water resources and agriculture production, taking the Zhanghe Irrigation System of China as a case study example. The Fei Gai Shui reform has been heralded as a possible solution for reducing the excessive fiscal burden on peasants. While the reform may achieve in relieving peasant burdens significantly, the initial impact of Fei Gai Shui on water resources and agricultural production indicate least satisfactory trends. The policy shows significant impact on rice yield and area. It might also have profound impact on cropping pattern but it has yet to be seen. Dependence on local water resources such as ponds show significant increase after Fei Gai Shui as it discouraged farmers to rely on regional water sources. Although the lower regional water use under Fei Gai Shui reduced the water charges paid by farmers, the savings were mostly offset by increasing pumping costs in accessing water from local ponds. Without any adjustments, the Fei Gai Shui is likely to cause serious predicament in agricultural sector. It is visioned that local water resources such as water ponds will continue to play an important role in sustaining agricultural production. [Copyright &y& Elsevier]

Accurate knowledge of the quality and environmental impact of the highway runoff in Pear River Delta, South China is required to assess this important non-point pollution source. This paper presents the quality characterization and environmental impact assessment of rainfall runoff from highways in urban and rural area of Guangzhou, the largest city of Pear River Delta over 1 year’s investigation. Multiple regression and Pearson correlation analysis were used to determine influence of the rainfall characteristics on water quality and correlations among the constituents in highway runoff. The results and analysis indicates that the runoff water is nearly neutral with low biodegradability. Oil and grease (O&G), suspended solids (SS) and heavy metals are the dominant pollutants in contrast to the low level of nutrient constituents in runoff. Quality of highway runoff at rural site is better than that of at urban site for most constituents. Depth and antecedent dry period are the main rainfall factors influencing quality of highway runoff. The correlation patterns among constituents in highway runoff at urban site are consistent with their dominant phases in water. Strong correlations ( r ≥ 0.80) are found among chemical oxygen demand (COD), total phosphorus, Cu and Zn as well as conductivity, nitrate nitrogen and total nitrogen. O&G, COD, SS and Pb in highway runoff at urban site substantially exceed their concentrations in receiving water of Pear River. The soil directly discharged by highway runoff at rural site has contaminated seriously by heavy metals in surface layer accompanying with pH conversion from original acidic to alkaline at present. [ABSTRACT FROM AUTHOR]

Under the current taxi licensing system in Hong Kong, holders of taxi licenses are given perpetual operating right in the taxi business. Since 1995, the government has not issued any new taxi licenses. Against this background, the freely traded taxi licenses are often held as an investment asset. When there are active speculative activities, the taxi license premium may be affected more by the general economic conditions than the demand for taxi services and/or changes in the levels of taxi services. In this paper, we use the backward and forward multiple regression methods to develop the level-of-taxi-services (LOTS) and economy-wide (EW) models for understanding fluctuations in the premiums of urban and New Territories (NT) taxis from 1986 to 2002. The results suggest that variations of both urban and NT taxi license premiums can be better accounted for by factors of the EW than the LOTS models. When the policymakers review policy with regard to the taxi license, it is important for them to take a closer look not only at taxi-related factors but also at the economy-wide factors. [ABSTRACT FROM AUTHOR]

Estimating the amount of irrigation water is challenging at the catchment scale because of the difficulties in direct measurement and interactions between the flow components. The objectives of the study were to characterize the catchment flows in an agricultural catchment with an irrigation system in subtropical China and to estimate catchment irrigation flow using hydrograph analysis methods. A weighting model and multiple regression models were established to estimate catchment irrigation outflow according to the hydrographs of the inflows and outflows of the catchment. The multiple regression models took into consideration the drainage time of base flow, resulting in better estimation on an event and annual basis. Using the MR-6d method, the estimated irrigation outflows amounted to 3700 mm, 2600 mm and 2760 mm during 2001, 2002 and 2003 respectively, which covered 70%, 60% and 64% respectively of the total catchment outflows in the corresponding years. [ABSTRACT FROM AUTHOR]

Large-scale infrastructural developments in rural areas often impose significant direct and indirect impacts on environment and people. The Three Gorges Project to dam the Yangtze River in China will create a huge reservoir, inundate farmlands and villages, and incur large-scale resettlement. The concurrent de-farming program to reforest marginal farmlands on steep slopes imposes additional stresses on local people. This study evaluates the ecological and economic adjustments in rural areas affected by both projects, and explores villagers’ knowledge, attitudes, perceptions, and expectations vis-à-vis the drastic changes. Eleven villages in Yunyang County in Sichuan Province, stratified into three zones based on topography and agriculture, were assessed by field studies, questionnaire surveys, maps, satellite imagery, and census and government reports. Multiple regressions identified predictors for 17 dependent variables. Spatial variations in the difficult terrain imposed zone-differentiated agricultural constraints, ecological impacts, and human responses. The dominant farming population—mainly young adults working as migrant laborers in cities—has adopted some nonagricultural work to supplement incomes. Expected per-capita standardized farmland (SF) exceeded threshold SF, which surpasses existing SF. Motivations to reclaim more farmlands, de-farm marginal lands, and become migrant laborers were explained by different multiple-regression predictors. Reduction in farmland stock by inundation and de-farming, aggravated by unwillingness towards nonlocal resettlement, would impose ecological pressures and stimulate demands for nonfarming incomes. Common anticipation of better future income and occupation has been subdued by unfavorable feedbacks from early relocatees. Future environmental and landscape changes are hinged upon changing human responses. Government policies could be informed by research findings to match economic, ecological, and social realities. [ABSTRACT FROM AUTHOR]

Abstract: This study uses statistical modeling techniques to develop a desertification risk index (RI) for Minqin County, Gansu Province, China. Twenty socio-economic factors were selected and compared with the RI results to explore the spatial and temporal variability of desertification risk in the study area and to identify possible local driving forces behind desertification risk. The explanatory factors were different in 1988, 1992 and 1997, possibly reflecting the role of temporal variation as a contributor to desertification. The average number of sheep per-household was found to be an important indicator of change in desertification risk, while changes in ridge crop planting area explained the distribution of the rate of change in desertification risk in 1988–1992. The results suggests that the RI was useful in expanding the understanding of spatial temporal desertification issues in Minqin County, as well as identifying a current set of agricultural activities related to desertification risk. Further, given the limited nature of consistent data and observations for the area, development of the RI also served to establish a baseline for future investigations into desertification change and the risks such change might pose for the region. [Copyright &y& Elsevier]

The stable isotopic composition of materials such as glacial ice, tree rings, lake sediments, and speleothems from low-to-mid latitudes contains information about past changes in temperature (T) and precipitation amount (P). However, the transfer functions which link δ18Op to changes in T or P, dδ18Op/dT and dδ18Op/dP, can exhibit significant temporal and spatial variability in these regions. In areas affected by the Southeast Asian monsoon, past variations in δ18O and δD of precipitation have been attributed to variations in monsoon intensity, storm tracks, and/or variations in temperature. Proper interpretation of past δ18Op variations here requires an understanding of these complicated stable isotope systematics. Since temperature and precipitation are positively correlated in China and have opposite effects on δ18Op, it is necessary to determine which of these effects is dominant for a specific region in order to perform even qualitative paleoclimate reconstructions. Here, we evaluate the value of the transfer functions in modern precipitation to more accurately interpret the paleorecord. The strength of these transfer functions in China is investigated using multiple regression analysis of data from 10 sites within the Global Network for Isotopes in Precipitation (GNIP). δ18Op is modeled as a function of both temperature and precipitation. The magnitude and signs of the transfer functions at any given site are closely related to the degree of summer monsoon influence. δ18Op values at sites with intense summer monsoon precipitation are more dependent on the amount of precipitation than on temperature, and therefore exhibit more negative values in the summer. In contrast, δ18Op values at sites that are unaffected by summer monsoon precipitation exhibit strong relationships between δ18Op and temperature. The sites that are near the northern limit of the summer monsoon exhibit dependence on both temperature and amount of precipitation. Comparison with simple linear models (δ18Op as a function of T or P) and a geographic model (δ18Op as a function of latitude and altitude) shows that the multiple regression model is more successful at reproducing δ18Op values at sites that are strongly influenced by the summer monsoon. The fact that the transfer function values are highly spatially variable and closely related to the degree of summer monsoon influence suggests that these values may also vary temporally. Since the Southeast Asian monsoon intensity is known to exhibit large variations on a number of timescales (annual to glacial–interglacial), and the magnitude and sign of the transfer functions is related to monsoon intensity, we suggest that as monsoon intensity changes, the magnitude and possibly even the sign of the transfer functions may vary. Therefore, quantitative paleoclimate reconstructions based on δ18Op variations may not be valid. [Copyright &y& Elsevier]

Artificial neural network analysis is found to be far superior to multiple regression when applied to the evaluation of trap quality in the Northern Kuqa Depression, a gas-rich depression of Tarim Basin in western China. This is because this technique can correlate the complex and non-linear relationship between trap quality and related geological factors, whereas multiple regression can only describe a linear relationship. However, multiple regression can work as an auxiliary tool, as it is suited to high-speed calculations and can indicate the degree of dependence between the trap quality and its related geological factors which artificial neural network analysis cannot.For illustration, we have investigated 30 traps in the Northern Kuqa Depression. For each of the traps, the values of 14 selected geological factors were all known. While geologists were also able to assign individual trap quality values to 27 traps, they were less certain about the values for the other three traps. Multiple regression and artificial neural network analysis were, therefore, respectively used to ascertain these values. Data for the 27 traps were used as known sample data, while the three traps were used as prediction candidates. Predictions from artificial neural network analysis are found to agree with exploration results: where simulation predicted high trap quality, commercial quality flows were afterwards found, and where low trap quality is indicated, no such discoveries have yet been made. On the other hand, multiple regression results indicate the order of dependence of the trap quality on geological factors, which reconciles with what geologists have commonly recognized. We can conclude, therefore, that the application of artificial neural network analysis with the aid of multiple regression to trap evaluation in the Northern Kuqa Depression has been quite successful. To ensure the precision of the above mentioned geological factors and their related parameters for each trap, a study of the petroleum system in Kuqa Depression was conducted, which included the partitioning and mechanisms of the Kuqa petroleum system. Three migration models are presented. [Copyright &y& Elsevier]

The depletion of traditional energy sources and severe environmental pollution are hindrances in meeting the increasing energy demands of the growing global population. Solar photovoltaic (PV) technology has been widely applied in China to replace traditional energy. The factors that affect the development of the PV industry in China are complex. This research sheds light on the development process of the PV industry in China by considering the PV installed capacity as an indicator of industrial development. A quantitative evaluation method was established to assess the PV industry and its influencing factors by developing a driving force model. This model combines the methods of factor quantification and multiple regression analysis by considering demand, market, policy, technology, and enterprise factors. The results show that from 2006 to 2008, policy factors played the most important role accounting for about 50% of the total impact, and since 2009, the impacts of technology and demand factors are more significant in the PV industry from the aspects of supply and demand accounting for 36% and 32%, respectively. The future trends of PV industry are predicted based on the evolution of the influencing factors. If guided by existing policies, the PV installed capacity will stabilize at 403 GW in 2025. The emphasis on energy storage technology in the future will also significantly promote the PV industry enabling it to reach 773 GW, and thereby, reduce about 0.87 billion tonnes of carbon dioxide emissions in that year compared to that with coal-based thermal power generation. This study provides a theoretical basis for multiple factor analysis in the photovoltaic industry and a deeper understanding for policy makers to coordinate the structure of energy generation in China in the future. • A driving force model of China's photovoltaic industry is established. • Factors influencing the annual photovoltaic install capacity and their contributions are determined. • Photovoltaic industry is a good form of industrial development. • Future trends in photovoltaic industry in different scenarios are explored. • Practical policy recommendations are proposed based on factor and trend analysis. [ABSTRACT FROM AUTHOR]

Purpose: Provide new methods to predict the number of hospital blood collections., Methods: The registered outpatients and blood collection patients in a large hospital in China in the period from March 2018 to April 2019 were enrolled in the study. Firstly, we analyzed the time series characteristics of the daily blood collection patients and their correlation with the number of daily outpatients. Then, we used the time series ARIMA and linear regression methods to build the periodic trend model of the blood collections number prediction and the regression prediction model with the number of registered outpatients as an independent variable. Finally, we built a combined prediction model considering mixed time series to predict the number of blood collections in the hospital., Results: The combined prediction model has a higher accuracy and can better explore the characteristics of the number of blood collections compared with other models. It can also give some suggestions for a reasonable blood collection management., Conclusion: The combined prediction model of mixed time series can reflect the change in the blood collections number due to the influence of internal and external factors and can realize the blood collection prediction with a higher accuracy providing a new method for the prediction of the blood collections number., (© 2021 John Wiley & Sons Ltd.)

Objective: To analyze the epidemiological characteristics of hand, foot and mouth disease (HFMD) in Sichuan Province from 2013 to 2019. To study the correlation between meteorological factors and the incidence of HFMD and construct a prediction model., Methods: The HMFD surveillance data and meteorological data from 2013 to 2019 in Sichuan Province were collected through the Chinese Center for Disease Control and Prevention and the China Meteorological data Network. Spearman correlation was used to analyze the relationship between HFMD incidence and meteorological factors. Multiple regression model and support vector regression (SVR) model were used to construct HFMD incidence prediction models respectively., Results: A total of 615 840 cases of HFMD and 81 deaths were reported from 2013 to 2019. The average annual incidence rate was 107.31/10 5 , and the mortality rate was 0.16/10 6 . Spearman correlation analysis showed that the monthly incidence rate of HFMD was correlated with monthly average relative humidity ( r =0.342), monthly average temperature ( r =0.284), monthly average water vapor pressure ( r =0.304) and monthly average days of precipitation ( r =0.259). The prediction effect of the SVR model ( R =0.836) was better than the multiple regression model ( 2 =0.836) was better than the multiple regression model ( R 2 =0.375). The SVR model provided a good fit to the monthly incidence of HFMD from 2013 to 2018, and can predict the peak incidence of HFMD in 2019., Conclusion: Relative humidity has the greatest influence on the incidence of HFMD. The fitting value of SVR model is in good agreement with the actual value, which is valuable in predicting the incidence of HFMD in Sichuan Province., (Copyright© by Editorial Board of Journal of Sichuan University (Medical Science Edition).)

Both environmental and geographic factors interact to structure the metacommunities in river networks, but the importance of these factors is difficult to distinguish. We used six aquatic taxonomic groups to test the relationship between environmental and geographic factors and their effect on species turnover patterns in an agriculturally dominated river (Chaohu Lake Basin, China). The relationships between three dissimilarity indices and geographic distance were assessed using the Mantel test while considering the differences in environmental factors between sites. Then, we employed a variation partitioning method to distinguish the isolated and combined effects of environmental and geographic distance on species turnover. There were significant relationships between environmental distance and species turnover in all groups. All organisms except periphytic diatoms were significantly correlated with two geographic (Euclidean and network) distances when the Chao dissimilarity index was considered. The results suggest that the strength of the correlations changed with environmental and geographic distances and with the aquatic community. The communities displayed more complex relationships with the distance measures when different dissimilarity (Jaccard, Chao, and Bray-Curtis dissimilarity) indices were considered. Nevertheless, aquatic communities are strongly influenced by both environmental and geographic distance, and the former has a stronger effect than the latter. [ABSTRACT FROM AUTHOR]

While the economy and society of China are developing rapidly, various ecological and environmental problems continue to emerge. The problem of air pollution is becoming an issue of increasing concern. Since 2013, Beijing, Tianjin, and Hebei Provinces have collaborated to control air pollution and have achieved certain success. However, the air pollution problem in the capital, Beijing, remains severe. In this study, a quantitative evaluation and analysis method is established for assessing urban air quality and its influencing factors by developing a driving force model. The model combines multiple regression and principal component analysis to account for social, economic, meteorological, and regional factors. The influencing factors with the highest contributions are regional transmission, energy consumption, and industrial structure. This model is used to project the future trend of the air quality in Beijing based on the evolution of the influencing factors, aimed to provide a theoretical basis for policies improving Beijing's air quality., (Copyright © 2019. Published by Elsevier Ltd.)