愿景与格局的落差——论张翎的小说《归海》兼及其他小说

《归海》以近百年来中国天翻地覆的历史为背景,从第三代女性的中加跨国视角,表现中国三代女性的悲欢离合,并通过作者擅长的绝境书写,增加小说的戏剧化效果,加深人性拷问的深度,让作者独特的“女性如水”的创作理念呈现出前所未有的宏大愿景。但《归海》在延续“战争的孩子”的写作思路时,也沿袭了旧作的桥段、手法、修辞等等,作者惯常的绝境书写和女性意识使《归海》难以突破以往的小说格局。

海外华文小说中传统意象资源的转化:以张翎《归海》为例

张翎的长篇小说新作《归海》主要包括三个不同层面的叙事主题,分别指向书写母亲、自我疗愈及回望故土。同时,作家援引、激活传统意象符号,建构起以“归海”为核心的雨/水、龙、凤意象体系,紧密贴合小说叙事且与之形成互补关系,深化了作品的叙事美学内涵。意象的选择与运用,不仅体现出张翎在跨文化语境中汲取、转化汉语文学传统的叙事自觉,也示范了一种将海外生命体验与民族精神进行融合性书写的独特路径。

战争女性的精神创伤——论张翎《归海》

在《归海》中,张翎持续了其一直以来对于战争、创伤、疗愈的思考。战争后遗症的描写、女性生命力量的礼赞、人性的幽微叩问,以及母女情深的叙述,小说从寓居加拿大的袁凤视角出发,讲述了其母袁春雨跌宕起伏的一生。从故土到他乡,再从他乡回归故土,母亲的生命河流千回百转,终于归入大海。作品不仅以惨痛的笔触讲述了战争中女性的精神创伤故事,而且还凭借着母女情深的真切书写完成了某种难能可贵的精神救赎。

到阴曹地府走一遭——论张翎的《归海》

“战争的孩子”三部曲之二《归海》是女儿对于母亲、生者对于死者生平隐秘的一次追忆和探访。正是死亡把一个平淡无奇的女人转换成一道谜,一个宝藏,里面藏着人性的珍珠。剖蚌取珠式的写作存在一种困境:人都是拒绝靠近、刻画的。张翎的解决方法是,杀了她,让她敞开,再拼接遗存的碎片,让她复活。就在拼接、复活的过程中,人性的珍珠熠熠生辉。珍珠绝不是爱,爱在张翎那里不具备优先性,甚至是被狐疑、打击的;而女性像春雨、泥土一样“宁静而持久的耐力”,她们靠着耐力熬过苦难,熬过苦难的她们就是“苦难的英雄”。张翎的苦难书写的意义在于:书写、阅读苦难,可以让我们汲取对抗苦难的力量,如果苦难不会消失,苦难书写的光彩就不会衰竭。

创伤记忆和战争的孩子——论《归海》

加拿大著名华人作家张翎的长篇近作《归海》形象而又深刻地揭櫫了战争对人性的摧残和给人类带来的灾难和创痛。从后记忆的角度分析《归海》的叙述结构,尝试阐述作家如何在文化范畴内揭示人物心理创伤形成轨迹,探索创伤的后续和跨代影响,即对创伤经历者与他们后代关系的影响。其次,从性别角度讨论作家在描述人物的创伤历史时所体现出的一种深刻的现代观念,即对性别主体性作为身份标志的强烈关注,可见它从性别的视角展现性强暴对女性生理和精神上的创伤,实质是对女性的“自我”主体的侵犯。最后,尝试分析在《归海》中表现出来的作家跨语言和跨文化的双语创作实践的意义。

A second modified normalized difference water index(SMNDWI) in the case of extracting the shoreline

Due to the fast development of industrialization and urbanization, shorelineextraction is necessary for the sustainable development and environment protection inmany countries. This study focused on the accurate methods of extracting theinstantaneous waterline —shoreline obtained as the same instant as the satellite imageis acquired. Based on NDWI (Normalized Difference Water Index) and MNDWI(Modified Normalized Difference Water Index), the study changed the bandcombination and proposed a second modified normalized water index (SMNDWI) toextract the waterline. And, this new index is applied to three types of coast to evaluatethe performance of this method with traditional ones. Results show that SNDWI isbetter than NDWI and suitable for applying to the waterline extraction.

Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data

This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution.

Preliminary Studies on Predicting the Tropical Indian Ocean Sea Surface Temperature through Combined Statistical Methods and Dynamic ENSO Prediction

The sea surface temperature （SST） in the In- dian Ocean affects the regional climate over the Asian continent mostly through a modulation of the monsoon system. It is still difficult to provide an a priori indication of the seasonal variability over the Indian Ocean. It is widely recognized that the warm and cold events of SST over the tropical Indian Ocean are strongly linked to those of the equatorial eastern Pacific. In this study, a statistical prediction model has been developed to predict the monthly SST over the tropical Indian Ocean. This model is a linear regression model based on the lag relationship between the SST over the tropical Indian Ocean and the Nino3.4 （5°S-5°N, 170°W-120°W） SST Index. The pre- dictor （i.e., Nino3.4 SST Index） has been operationally predicted by a large size ensemble E1 Nifio and the Southern Oscillation （ENSO） forecast system with cou- pled data assimilation （Leefs_CDA）, which achieves a high predictive skill of up to a 24-month lead time for the equatorial eastern Pacific SST. As a result, the prediction skill of the present statistical model over the tropical In- dian Ocean is better than that of persistence prediction for January 1982 through December 2009.

Agricultural Extension in Balochistan, Pakistan:Date Palm Farmers' Access and Satisfaction

This study analyzed information gathered from 200 date palm households in the mountainous Panjgur District of Balochistan in Pakistan with the aim of determining date farmers＇ access to and satisfaction with agricultural extension services. Information was collected through a structured questionnaire survey, group discussions and semi- structured personal interviews. The findings of the analysis revealed very poor access to extension services. The results of logistic regression analysis identified five variables out of six which significantly influence date farmers＇ access to extension services： household bead＇s age, household bead＇s literacy, number of date palm trees owned, mostly inherited date palm trees, and percentage of dead date palm trees. The overwhelming majority of farmers were dissatisfied with all three main types of extension services being provided by public extension officials. Explanations for this as well as for associations between access to extension services and the six independent variables are provided. Important policy conclusions are drawn based on the findings.

Living alone, health and preventive care use among the elderly in Shanghai, China

Objective:The purpose of the study was to compare the preventive care use and health between the elderly living alone and living with other individuals and identify strategies to improve the preventive care use among the elderly living alone.Methods:A questionnaire including socioeconomic characteristics,preventive care use,health status and Social Support Rate Scale was administered to 240 elderly living alone and 244 elderly living with other individuals in Shanghai,China.Logistic regression analysis was used to examine the predictors of preventive care use.Results:The elderly living alone were more likely to be single(never married,divorced,separated and widowed),have lower social support and income,utilize less routine physical check-up and blood glucose screenings,have worse self-reported health and have limitations in IADL compared to the elderly living with other individuals.Women,old age,high education,income and social support and close to medical institutions were positively associated with routine physical check-up among the elderly.Conclusion:Living alone was associated with less preventive care use and worse health.It was important to provide more social support and economic support for the elderly living alone to increase their preventive health care service utilization and improve their health status.

Quantifying the Mean Sea Level Change at the Gulf of Finland Coast Caused by the Realistic Portion of the Global Warming Forcing

Quantifying the coastal mean sea level change causing by the winter positive phase of the North Atlantic oscillation index NAO＋ at the Gulf of Finland coast is of high priority for detecting and predicting the global warming impact in this region. Both boreal winter months and season of three long-term data station series of the coastal mean sea levels and the NAO indices were linked for two cases, i.e.： different periods and the 1977-1994 period. This study is dedicated to： （1） Detecting the exclusive impacts of the NAO＋; （2） Estimating the significant standard bivariate linear regression models; （3） Calculating the climatic linear trend coefficient by using three methods （OLS, GLS, Theil-Sen）; （4） Correcting the mean sea level series anomalies by using the significant linear regression equations as a function of NAO＋ anomalies, over the period 1977-1994; （5） Calculating the realistic linear trend caused as a function of NAO＋ for period 1977-1994 in the context of the realistic portion of the global warming. The results reveal that, the NAO＋ manifests their impacts on the coastal mean sea levels and its contribution in the configured linear trends. The realistic linear changes have detected and predicted. The Gulf of Finland coast showed the wannest regions in the context of the realistic portion of the global warming during the winters of the period 1977-1994.

Kinetics of Atmospheric Corrosion of Mild Steel in Marine and Rural Environments

In continuation of the extensive studies carried out to update the corrosion map of India, in this study, the degradation of mild steel by air pollutants was studied at 16 different locations from Nagore to Ammanichatram along the east coast of Tamilnadu, India over a period of two years. The weight loss study showed that the mild steel corrosion was more at Nagapattinam site, when compared to Ammanichatram and Maravakadu sites. A linear regression analysis of the experimental data was attempted to predict the mechanism of the corrosion. The composition of the corrosion products formed on the mild steel surfaces was identified by XRD technique. The corrosion rate values obtained are discussed in the light of the weathering parameters, atmospheric pollutants such as salt content ＆ SO2 levels in the atmosphere, corrosion products formed on the mild steel surfaces.

Beak Measurements of Octopus (Octopus variabilis) in Jiaozhou Bay and Their Use in Size and Biomass Estimation

Cephalopods play key roles in global marine ecosystems as both predators and preys.Regressive estimation of original size and weight of cephalopod from beak measurements is a powerful tool of interrogating the feeding ecology of predators at higher trophic levels.In this study,regressive relationships among beak measurements and body length and weight were determined for an octopus species(Octopus variabilis),an important endemic cephalopod species in the northwest Pacific Ocean.A total of 193 individuals(63 males and 130 females) were collected at a monthly interval from Jiaozhou Bay,China.Regressive relationships among 6 beak measurements(upper hood length,UHL;upper crest length,UCL;lower hood length,LHL;lower crest length,LCL;and upper and lower beak weights) and mantle length(ML),total length(TL) and body weight(W) were determined.Results showed that the relationships between beak size and TL and beak size and ML were linearly regressive,while those between beak size and W fitted a power function model.LHL and UCL were the most useful measurements for estimating the size and biomass of O.variabilis.The relationships among beak measurements and body length(either ML or TL) were not significantly different between two sexes;while those among several beak measurements(UHL,LHL and LBW) and body weight(W) were sexually different.Since male individuals of this species have a slightly greater body weight distribution than female individuals,the body weight was not an appropriate measurement for estimating size and biomass,especially when the sex of individuals in the stomachs of predators was unknown.These relationships provided essential information for future use in size and biomass estimation of O.variabilis,as well as the estimation of predator/prey size ratios in the diet of top predators.

The Modeling of Weather Conditions and Wind Power in Cities of Western Black Sea Region by Using Linear Regression Method

In this study, weather condition data such as the monthly average temperature, relative moisture, wind speed, pressure and the calculated wind power values of Zonguldak, Sinop, Dtizce, Bartm, Kastamonu, Bolu and Karabi^k cities located in western Black Sea region were examined for 10 year period （2001-2011）. In the modeling of the weather conditions, linear regression analysis was used and the effect of temperature, relative moisture and pressure on wind speed was researched by non-linear regression method. Besides, in this study, the effect of roughness coefficient in cities of western Black Sea region was also taken into consideration and the wind power potentials in 10 m, 25 m and 50 m altitude were researched in detail with the help of WASP （Wind Atlas Analysis and Application） program. In the light of the values obtained by developed models and weather condition data, it was observed that some cities in the western Black Sea region have wind power potential with their effects on environment and energy.

Influence of Weather and Climate on Malaria Occurrence Based on Human-Biometeorological Methods in Ondo State, Nigeria

This study focuses on the influence of weather and climate on malaria occurrence based on human-biometeorological methods was carried out in Ondo State, Nigeria using meteorological and malaria dataset in the state for the period from 1998 to 2008. In addition, sea surface temperatures （SSTs） over equatorial Pacific Ocean were integrated in the analysis. The association between each of the meteorological-biometeorological parameters and clinical-reported malaria cases was examined by using Poisson distribution and log as link function between the two categories of dataset. The next step was the building of a model by using Poisson multiple regression models （GLMs） in order to know the weather variables that lead to statistically changes in clinical-reported malaria cases. The study revealed that an increase of I m.s1 of wind speed can lead to an increase of about 164% and 171% in the monthly occurrence of malaria at 95% confidence interval in derived savanna and humid forest zone respectively. Also, an increase of I ℃ in air temperature and sea surface temperature is associated with 53.4% and 29% increase in monthly malaria occurrence （CI： 95%） in derived savanna while an increase of 1 ℃ in air temperature and sea surface temperature is associated with 56.4% and 15.4% increase in monthly malaria occurrence at 95% confidence interval in humid forest zone of Ondo State

Correlation and path analysis of morphological and weight traits in marine gastropod Glossaulax reiniana

Using correlation and path analysis, the genetic correlation between weight traits and morphological traits was determined in the marine gastropod Glossaulax reiniana. A total of 100 G. reiniana individuals from a wild population were used. Shell width （X1）, shell height （X2）, umbo-callus height （X3）, body width （X4）, operculum length （X5）, operculum width （X6）, body weight （Y1） and soft-tissue weight （Y2） were measured, and the correlation coefficient matrix calculated. Morphological traits were used as independent variables and weight traits as dependent variables for path coefficient analysis. Path coefficients, correlation indices and determination coefficients were also determined. Results indicate that the correlation coefficients associated with each morphological and weight trait were all highly significant （P〈0.01）. After deleting redundant independent variables, the following optimum multiple regression equations were obtained using stepwise multiple regression analysis： Y1=-29.317＋0.362X2＋0.349X4＋ 1.190）（5 for body weight; and Y2=-17.292＋0.166X1＋0.171X2＋0.703X5, for soft-tissue weight. Operculum height had the highest positive direct correlation with both body weight and soft-tissue weight, which was in accordance with the test results obtained from determinate coefficient analysis. The indication of high genetic correlations between weight traits and morphological traits will provide valuable information for G. reiniana breeding programs.

Influence of the Pacific Decadal Oscillation on regional sea level rise in the Pacific Ocean from 1993 to 2012

The rate of regional sea level rise （SLR） provides important information about the impact of human activities on climate change. However, accurate estimation of regional SLR can be severely affected by sea surface height （SSH） change caused by the Pacific Decadal Oscillation （PDO-SSH）. Here, the PDO- SSH signal is extracted from satellite altimeter data by multi-variable linear regression, and regional SLR in the altimeter era is calculated, before and after removing that signal. The results show that PDO-SSH trends are rising in the western Pacific and falling in the eastern Pacific, with the strongest signal confined to the tropical and North Pacific. Over the past 20 years, the PDO-SSH accounts for about 30%/-400% of altimeter-observed SLR in the regions 8° 15°N, 130°-160°E and 30°-40°N, 170°-220°E. Along the coast ＆North America, the PDO-SSH signal dramatically offsets the coastal SLR, as the sea level trends change sign from falling to rising.

The Effect of Sea Level Rise on Egyptian Economy

The vulnerability of Egypt to potential impacts of sea level rise has been considered. It was recognized that many locations in Egyptian Coast, on Mediterranean Sea （Mersa Matruh, Alexandria and Port Said） and on Red Sea （Hurghada）, are highly vulnerable to the potential impacts of sea level rise, salt water intrusion and increase of frequency and severity of storm surges. The aim of this study is to investigate the monthly average and the variations of sea level and meteorological conditions along the Egyptian Mediterranean and north Red Sea coasts. Monthly mean cycles and correlation coefficients between MSL （Mean Sea Level） and different meteorological parameters were also calculated. The analyzed data was from 2007 to 2009 covering 3 years of hourly recorded sea level and meteorological parameters were used except for Hurghada sea level was for 2007 and 2008. Sea level harmonic analyses were done by using TOGA （Tropical Ocean and Global Atmosphere） software. Sea level variations were also computed, and it was 20.1,20, 0.1 and 55.3 cm in Alexandria, Port Said, Mersa Matruh and Hurghada respectively. The annual of the tidal constituents were computed to determine the MSL. Surge calculations were done by using TOGA software and eliminating the predicted tide from the observed sea level. The average calculated surge was also analyzed that the highest surge happened during summer and the lowest during winter in Alexandria and Port Said, while the highest surge was during winter and the lowest during summer in Hurghada. The surge variation was very weak in Mersa Matruh. The result of multiple regression analysis is a statistically significant relationship between the variables at the 99% confidence level.

Prediction of Coastal Fecal Indicator Bacteria Concentrations Using Multivariate Data Analysis

The application of multivariate data analysis, a method for coping with multi-colinearity among independent variables in analyzing coastal water quality data, is presented. This study investigates the statistical regression modeling of FIB （fecal indicator bacteria） concentrations at the outlet of Talbert Marsh in Orange County, California. The multivariate data modeling utilized FIB and physical variables measurements （n = 5,580） collected during a series of longitudinal study of the Talbert Marsh. For the statistical prediction modeling in predicting the FIB concentrations at the outlet of the Talbert Marsh, multivariate analysis techniques such as PCR （principal components regression）, PLS （partial least-squares） regression and SVM （support vector machine） regression were adopted. Statistical modeling results suggest that the statistical modeling predictions are all fell within the reasonable range of actual measurement data. In addition, it is indicated that the accuracy of SVM regression for predicting FIB concentrations at the Talbert Marsh outlet is better than that of other models.

Statistical Downscaling of FGOALS-s2 Projected Precipitation in Eastern China

A statistical regression downscaling method was used to project future changes in precipitation over eastern China based on Phase 5 of the Coupled Model Intercomparison Project （CMIPS） the Representative Concentration Pathway （RCP） scenarios simulated by the second spectral version of the Flexible Global Ocean- Atmosphere-Land System （FGOALS-s2） model. Our val- idation results show that the downscaled time series agree well with the present observed precipitation in terms of both the annual mean and the seasonal cycle. The regres- sion models built from the historical data are then used to generate future projections. The results show that the en- hanced land-sea thermal contrast strengthens both the subtropical anticyclone over the western Pacific and the east Asian summer monsoon flow under both RCPs. However, the trend of precipitation in response to warming over the 21 st century are different across eastern Chi- na under different RCPs. The area to the north of 32°N is likely to experience an increase in annual mean precipitation, while for the area between 23°N and 32°N mean precipitation is projected to decrease slightly over this century under RCP8.5. The change difference between scenarios mainly exists in the middle and late century. The land-sea thermal contrast and the associated east Asian summer monsoon flow are stronger, such that precipitation increases more, at higher latitudes under RCP8.5 compared to under RCP4.5. For the region south of 32°N, rainfall is projected to increase slightly under RCP4.5 but decrease under RCP8.5 in the late century. At the high resolution of 5 km, our statistically downscaled results for projected precipitation can be used to force hydrological models to project hydrological processes, which will be of great benefit to regional water planning and management.