5 resultados para Switching regression models
em Chinese Academy of Sciences Institutional Repositories Grid Portal
Resumo:
The fanning of Chinese mitten crab, a quality aquatic product in China and neighbouring Asian countries, has been developing rapidly in China since last decade. It reached a total yield of 3.4 X 10(5) tonnes in 2002. Due to the successive over-stocking year after year, many lakes in the mid-lower Yangtze Basin, the main farming area, are under deterioration, leading to a reduction of crab yield and quality, and, subsequently, a loss of fanning profits. Aiming at a normal development of crab culture and the sustainable use of lakes, an annual investigation dealing with lake environmental factors in relation to stocked crab populations was carried out at 20 farms in 4 lakes. The results show that the submersed macrophyte biomass (B-Mac) is the key factor affecting annual crab yield (CY). Using the ratio of Secchi depth to mean depth (Z(SD)/Z(M)), an easily measured parameter closely correlated to BMac, as driving variable, 10 regression models of maximal crab yields were generated (r(2) ranging 0.49-0.81). Based on the theory of MSY (Maximum Sustainable Yield), in combination with body-weight (BW) and recapture rate (RR) of adult crabs, a general optimal stocking model was eventually formulated. All models are simple and easy to operate. Comments on their applications and prospects are given in brief. (c) 2006 Elsevier B.V. All rights reserved.
Resumo:
In this paper, we introduce the method of leaps and bounds regression which can be used to select variables quickly and obtain the best regression models. These models contain one variable, two variables, three variables and so on. The results obtained by using leaps and bounds regression were compared with those achieved by using stepwise regression to lead to the conclusion that leaps and bounds regression is an effective method.
Resumo:
Resting metabolism was measured in immature mandarin fish Siniperca chuatsi weighing 42.1-510.2 g and Chinese snakehead Channa argus weighing 41.5-510.3 g at 10, 15, 20, 25, 30 and 35 degreesC. Heat increment of feeding was measured in mandarin fish weighing 202.0 (+/-14.0) g and snakehead weighing 200.8 (+/-19.3) g fed swamp leach Misgurnus anguillicaudatus at 1% body weight per day at 28 degreesC. In both species, weight exponent in the power relationship between resting metabolism and body weight was not affected by temperature. The relationship between resting metabolism and temperature could be described by a power function. The temperature exponent was 1.39 in mandarin fish and 2.10 in snakehead (P < 0.05), indicating that resting metabolism in snakehead increased with temperature at a faster rate than in mandarin fish. Multiple regression models were used to describe the effects of body weight (W, g) and temperature (T, C) on the resting metabolism (R-s, mg O-2/h): In R-s = - 5.343 + 0.772 In W + 1.387 In T for the mandarin fish and In R-s = -7.863 + 0.801 ln W + 2.104 In T for the Chinese snakehead. The proportion of food energy channelled to heat increment was 8.7% in mandarin fish and 6.8% in snakehead. (C) 2000 Elsevier Science Inc. All rights reserved.
Resumo:
The soil respiration and net ecosystem productivity of Kobresia littledalei meadow ecosystem was investigated at Dangxiong grassland station, one grassland field station of Lhasa Plateau Ecosystem Research Station. Soil respiration and soil heterotrophic respiration were measured at the same time by using Li6400-09 chamber in growing season of year 2004. The response of soil respiration and its components, i.e. microbial heterotrophic respiration and root respiration to biotic and abiotic factors were addressed. We studied the daily and seasonal variation on Net Ecosystem carbon Exchange (NEE) measured by eddy covariance equipments and then the regression models between the NEE and the soil temperature. Based on the researches, we analyzed the seasonal variation in grass biomass and estimated NEE combined the Net Ecosystem Productivity with heterogeneous respiration and then assessed the whether the area is carbon source or carbon sink. 1.Above-ground biomass was accumulated since the grass growth started from May; On early September the biomass reached maximum and then decreased. The aboveground net primary production (ANPP) was 150.88 g m~" in 2004. The under-ground biomass reached maximum when the aboveground start to die back. Over 80% of the grass root distributed at the soil depth from 0 to 20cm. The underground NPP was 1235.04 g m"2.. Therefore annual NPP wasl.385X103kg ha"1, i.e.6236.6 kg C ha"1. 2. The daily variation of soil respiration showed single peak curve with maximum mostly at noon and minimum 4:00-6:00 am. Daily variations were greater in June, July and August than those in September and October. Soil respiration had strong correlation with soil temperature at 5cm depth while had weaker correlation with soil moisture, air temperature, surface soil temperature, and so on. But since early September the soil respiration had a obviously correlation with soil moisture at 5cm depth. Biomass had a obviously linearity correlation with soil respiration at 30th June, 20th August, and the daytime of 27th September except at 23lh October and at nighttime of 27th September. We established the soil respiration responding to the soil temperature and to estimate the respiration variation during monsoon season (from June through August) and dry season (May, September and October). The regression between soil respiration and 5cm soil temperature were: monsoon season (June through August), Y=0.592expfl()932\ By estimating , the soil daily respiration in monsoon season is 7.798gCO2m"2 and total soil respiration is 717.44 gCC^m" , and the value of Cho is 2.54; dry season (May, September and October), Y=0.34exp°'085\ the soil daily respiration is 3.355gCO2m~2 and total soil respiration is 308.61 gCC^m", and the value of Cho is 2.34. So the total soil respiration in the grown season (From May to October) is 1026.1 g CO2IT1"2. 3. Soil heterogeneous respiration had a strong correlation with soil temperature especially with soil temperature at 5cm depth. The variation range in soil heterogeneous respiration was widely. The regression between soil heterogeneous respiration and 5cm soil temperature is: monsoon season, Y=0.106exp ' 3x; dry season, Y=0.18exp°"0833x.By estimating total soil heterotrophic respiration in monsoon season is 219.6 gCC^m"2, and the value of Cho is 3.78; While total soil heterogeneous respiration in dry season is 286.2 gCCbm"2, and the value of Cho is 2.3. The total soil heterotrophic respiration of the year is 1379.4kg C ha"1. 4. We estimated the root respiration through the balance between soil respiration and the soil heterotrophic respiration. The contribution of root respiration to total respiration was different during different period: re-greening period 48%; growing period 69%; die-back period 48%. 5. The Ecosystem respiration was relatively strong from May to October, and of which the proportion in total was 97.4%.The total respiration of Ecosystem was 369.6 g CO2 m" .we got the model of grass respiration respond to the soil temperature at 5cm depth and then estimated the daytime grass respiration, plus the nighttime NEE and daytime soil respiration. But when we estimated the grass respiration, we found the result was negative, so the estimating value in this way was not close. 6. The estimating of carbon pool or carbon sink. The NPP minus the soil heterogeneous respiration was the NEE, and it was 4857.3kg C o ha"1, which indicated that the area was the carbon sink.
Resumo:
Self-regulation has recently become an important topic in cognitive and developmental domain. According to previous theories and experimental studies, it is shown that self-regulation consist of both a personality (or social) aspect and a behavioral cognitive aspect of psychology. Self-regulation can be divided into self-regulation personality and self-regulation ability. In the present study researches have been carried out from two perspectives: child development and individual differences. We are eager to explore the characteristics of self-regulation in terms of human cognitive development. In the present study, we chose two groups of early adolescences one with high intelligence and the other with normal intelligence. In Study One Questionnaires were used to compare whether the highly intelligent group had had better self-regulation personality than the normal group. In Study Two experimental psychology tasks were used to compare whether highly intelligent children had had better self-regulation cognitive abilities than their normal peers. Finally, in Study Three we combined the results of Study One and Study Two to further explore the neural mechanisms for highly intelligent children with respect to their good self-regulation abilities. Some main results and conclusions are as follows: (1) Questionnaire results showed that highly intelligent children had better self-regulation personalities, and they got higher scores on the personalities related to self-regulation such as, self-reliance, stability, rule-consciousness. They also got higher scores on self-consciousness which meant that they could know their own self better than the normal children. (2) Among the three levels of cognitive difficulties in self-regulation abilities, the highly intelligent children had faster reaction speed than normal children in the primary self-regulation tasks. In the intermediate self-regulation tasks, highly intelligent children’s inhibition processing and executive processing were both better than their normal peers. In the advanced self-regulation tasks, highly intelligent children again had faster reaction speed and more reaction accuracy than their normal peers when facing with conflict and inconsistency experimental conditions,. Regression model’s results showed that primary and advanced self-regulation abilites had larger predictive power than intermediate self-regualation ability. (3) Our neural experiments showed that highly intelligent children had more efficient neural automatic processing ability than normal children. They also had better, faster and larger neural reaction to novel stimuli under pre-attentional condition which made good and firm neural basis for self-regualation. Highly intelligent children had more mature frontal lobe and pariental functions for inhibition processing and executive processing. P3 component in ERP was closely related to executive processing which mainly activated pariental function. There were two time-periods for inhibition processing—first it was the pariental function and later it was the coordination function of frontal and pariental lobes. While conflict control task had pariental N2 and frontal-pariental P3 neural sources, highly intelligent children had much smaller N2 and shorter P3 latency than normal children. Inconsistency conditions induced larger N2 than conditions without inconsistency, and conditions without inconsistency (or Conflict) induced higher P3 amplitudes than with Inconsistency (or Conflict) conditions. In conclusion, the healthy development of self-regulation was very important for children’s personality and cognition maturity, and self-regulation had its own specific characteristics in ways of presentation and ways of development. Better understanding of self-regulation can further help the exploration of the nature of human intelligence and consciousness.