Sustainability Assessment and Indicator Development: the Electricity System in Dalian, China
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Annual Report 年報 2015 Contents
Annual Report 年報 2015 Contents General Information on the Company 2 Chairman’s Statement 8 Financial Highlights 10 Management Discussion and Analysis 11 Directors’ Report 48 Corporate Governance Report 60 Profiles of Directors, Supervisors and Senior Management 72 Independent Auditor’s Report 76 Consolidated Balance Sheet 77 Consolidated Income Statement 79 Consolidated Cash Flows Statement 80 Consolidated Statement of Changes in Shareholders’ Equity 82 Company Balance Sheet 83 Company Income Statement 85 Company Cash Flow Statement 86 Company Statement of Changes in Shareholders’ Equity 88 Notes to the Financial Statements 89 Supplementary Information to the Financial Statements 228 Financial Highlights for the Past Five Financial Years 230 General Information on the Company 1) Company Profile Dalian Port (PDA) Company Limited (the “Company”) was established in Dalian City, Liaoning Province, the People’s Republic of China (the “PRC”) on 16 November 2005. The Company was successfully listed on the Main Board of the Stock Exchange of Hong Kong Limited with stock code of 2880 and Shanghai Stock Exchange with stock code of 601880 on 28 April 2006 and 6 December 2010, respectively. The Company is the first port company listed in both the stock exchanges of Hong Kong and Shanghai. Located at the entrance of Bohai Bay, with its proximity to major international shipping routes as compared to other ports in Bohai Bay and with deep water and ice-free port conditions, Dalian port is able to operate its terminals throughout the year. As the consolidated operational platform for port and logistics services in Dalian port, the Company and its subsidiaries (collectively, the “Group”) are the biggest comprehensive port operator in the Three Northeastern Provinces of China (collectively, Heilongjiang Province, Jilin Province and Liaoning Province). -
Summary on Marine and Coastal Protected Areas in NOWPAP Region
Summary on Marine and Coastal Protected Areas in NOWPAP Region (NOWPAP DINRAC, March 2010) 1. Overview This summary is based on the Database on Coastal and Marine Nature Reserves in the Northwest Pacific Region (NowpapNatureReserve, http://dinrac.nowpap.org/NowpapNatureReserve.php) which is developed and maintained by NOWPAP DINRAC. The data was collected and provided by the National Focal Points of DINRAC started from 2006 and updated periodically. The WDPA (World database of protected areas, http://www.wdpa-marine.org), and the Ramsar Sites Database (http://ramsar.wetlands.org) were also taken as reference. The summary intends to give an overview and understanding on current situation of marine and coastal protected areas (MPAs) in NOWPAP region. The MPAs - marine and coastal protected areas comprise the nature reserves, national parks, wetland protected areas (Ramsar Sites) in NOWPAP Region. The sea area mainly covers the Yellow Sea and Eastern Area of NOWPAP region. Based on the existing data, there are total 87 MPAs in NOWPAP region covers an area of 4,090,046ha (Table 1 to Table 3). The earliest MPA was established in October 1916 and the latest was in August 2007 (Table 4). The smallest area is 10ha in Japan and largest area is 909,000ha in China (Table 5). Statistics tables and figures below are conducted on number, area, protected level, protected type and protected objectives (species) for MPAs in NOWPAP (Table 6 and Fig.1 to Fig.5). The list (List 1) and the location of the MPAs (Map 1) are listed individually. 2. Statistics Table 1. Number of MPAs in NOWPAP Region by Country Level Protected Type Country Total Wild Municipal/ Natural Nature Number National Provincial animal and County ecosystem heritage plant China 20 9 5 6 15 17 17 Japan 31 17 14 0 31 31 20 Korea 22 22 0 0 22 20 13 Russia 14 7 7 0 14 14 7 Region 87 55 26 6 82 82 57 1 Table 2. -
Table of Codes for Each Court of Each Level
Table of Codes for Each Court of Each Level Corresponding Type Chinese Court Region Court Name Administrative Name Code Code Area Supreme People’s Court 最高人民法院 最高法 Higher People's Court of 北京市高级人民 Beijing 京 110000 1 Beijing Municipality 法院 Municipality No. 1 Intermediate People's 北京市第一中级 京 01 2 Court of Beijing Municipality 人民法院 Shijingshan Shijingshan District People’s 北京市石景山区 京 0107 110107 District of Beijing 1 Court of Beijing Municipality 人民法院 Municipality Haidian District of Haidian District People’s 北京市海淀区人 京 0108 110108 Beijing 1 Court of Beijing Municipality 民法院 Municipality Mentougou Mentougou District People’s 北京市门头沟区 京 0109 110109 District of Beijing 1 Court of Beijing Municipality 人民法院 Municipality Changping Changping District People’s 北京市昌平区人 京 0114 110114 District of Beijing 1 Court of Beijing Municipality 民法院 Municipality Yanqing County People’s 延庆县人民法院 京 0229 110229 Yanqing County 1 Court No. 2 Intermediate People's 北京市第二中级 京 02 2 Court of Beijing Municipality 人民法院 Dongcheng Dongcheng District People’s 北京市东城区人 京 0101 110101 District of Beijing 1 Court of Beijing Municipality 民法院 Municipality Xicheng District Xicheng District People’s 北京市西城区人 京 0102 110102 of Beijing 1 Court of Beijing Municipality 民法院 Municipality Fengtai District of Fengtai District People’s 北京市丰台区人 京 0106 110106 Beijing 1 Court of Beijing Municipality 民法院 Municipality 1 Fangshan District Fangshan District People’s 北京市房山区人 京 0111 110111 of Beijing 1 Court of Beijing Municipality 民法院 Municipality Daxing District of Daxing District People’s 北京市大兴区人 京 0115 -
Basic Characteristics and Spatial Patterns of Pseudo-Settlements—Taking Dalian As an Example
International Journal of Environmental Research and Public Health Article Basic Characteristics and Spatial Patterns of Pseudo-Settlements—Taking Dalian as An Example Jiaji Gao 1,2,3,†, Yingjia Zhang 1,3,† and Xueming Li 1,3,* Received: 30 July 2015; Accepted: 22 December 2015; Published: 20 January 2016 Academic Editor: Paul B. Tchounwou 1 School of Urban and Environmental Sciences, Liaoning Normal University, Dalian 116029, China; [email protected] (J.G.); [email protected] (Y.Z.) 2 Applied Technology College of Dalian Ocean University, Dalian 116300, China 3 The Research Center of Human Settlements, Liaoning Normal University, Dalian 116029, China * Correspondence: [email protected]; Tel.: +86-0411-8215-8258 † These authors contributed equally to this work. Abstract: A person’s living behavior patterns are closely related to three types of settlements: real-life settlements, imagined settlements, and pseudo-settlements. The term “pseudo-settlement” (PS) refers to the places that are selectively recorded and represented after the mass media chose and restructure the residence information. As the mass media rapidly develops and people’s way of obtaining information gradually change, PS has already become one of the main ways for people to recognize and understand real-life settlements, as well as describe their impressions of imagined settlements. PS also has a profound impact on tourism, employment, investment, migration, real estate development, etc. Thus, the study of PSs has important theoretical and practical significance. This paper proposes to put forward residential quarters where the mass media is displayed as the object of study and establishes the pseudo-settlement index system of Dalian in and elaborate analysis of the concept of PSs. -
Proteomics Reveals the Preliminary Physiological States of the Spotted
www.nature.com/scientificreports OPEN Proteomics reveals the preliminary physiological states of the spotted seal (Phoca largha) pups Jiashen Tian1, Jing Du1, Jiabo Han1, Xiangbo Bao1, Xinran Song2 & Zhichuang Lu1* Spotted seal (Phoca largha) is a critically endangered pinniped in China and South Korea. The conventional method to protect and maintain the P. largha population is to keep them captive in artifcially controlled environments. However, little is known about the physiological diferences between wild and captive P. largha. To generate a preliminary protein expression profle for P. largha, whole blood from wild and captive pups were subjected to a label-free comparative proteomic analysis. According to the results, 972 proteins were identifed and predicted to perform functions related to various metabolic, immune, and cellular processes. Among the identifed proteins, the expression level of 51 were signifcantly diferent between wild and captive P. large pups. These diferentially expressed proteins were enriched in a wide range of cellular functions, including cytoskeleton, phagocytosis, proteolysis, the regulation of gene expression, and carbohydrate metabolism. The abundances of proteins involved in phagocytosis and ubiquitin-mediated proteolysis were signifcantly higher in the whole blood of wild P. largha pups than in captive individuals. In addition, heat shock protein 90-beta, were determined as the key protein associated with the diferences in the wild and captive P. largha pups due to the most interactions of it with various diferentially expressed proteins. Moreover, wild P. largha pups could be more nutritionally stressed and have more powerful immune capacities than captive pups. This study provides the frst data on the protein composition of P. -
Research on Development Countermeasures of Marine Cultural Industry in Dalian City
Journal of Literature and Art Studies, June 2018, Vol. 8, No. 6, 906-911 doi: 10.17265/2159-5836/2018.06.009 D DAVID PUBLISHING Research on Development Countermeasures of Marine Cultural Industry in Dalian City ZHU Hui, YANG Si-ting Law School and Coast Guard School, Dalian Ocean University, Dalian, 116023, China Nowadays, culture, as a kind of soft power, has become the worldwide force that has an influence on the future world. The competition in the future world will also be the competition of culture and cultural productivity. The consciousness of cultural construction and cultural development has become the consensus of all countries in the world. Dalian is an important city in terms of opening to and cooperation in Northeast Asia. The development of marine culture and marine cultural industry is of great significance on promoting the growth of Dalian’s marine economy and the revitalization of the old industrial bases in northeast, which is also beneficial to the development of Liaoning coastal economic belt, the economic circle around the Bohai Sea and the construction strategy of the “Belt and Road initiative”. This paper takes the development countermeasures of marine cultural industry in Dalian city as the research subject. Based on the detailed analysis of the status and insufficiency, putting forward several specific development countermeasures of marine cultural industry in Dalian city. Keywords: marine cultural industry, development countermeasures, Dalian Introduction In order to meet the challenges of the development of the global marine competition, China has established the marine power as the national development strategy, and the report of the 18th National Congress of the Communist Party of China clearly put forward the construction of the marine power, which accurately grasps the characteristics of the times and the world trend. -
Monitoring Changes of Ecosystem Services Supply and Demand Pattern in Central and Southern Liaoning Urban Agglomerations, China Using Landsat Images
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3, 2018 ISPRS TC III Mid-term Symposium “Developments, Technologies and Applications in Remote Sensing”, 7–10 May, Beijing, China MONITORING CHANGES OF ECOSYSTEM SERVICES SUPPLY AND DEMAND PATTERN IN CENTRAL AND SOUTHERN LIAONING URBAN AGGLOMERATIONS, CHINA USING LANDSAT IMAGES B. Li, F.Huang*, S. Chang, H. Qi, H.Zhai School of Geographical Sciences, Northeast Normal University, Renmin Street, Changchun, China - (lib250, huangf835, changs164, qih102, zhaih669)@nenu.edu.cn Commission III, WG III /10 KEY WORDS: Multiple-ecosystem Services, Landsat, Socioeconomic factors, Driving Forces, Regression Analysis, Central and Southern Liaoning Urban Agglomerations, China ABSTRACT: Indentifying the spatio-temporal patterns of ecosystem services supply and demand and the driving forces is of great significance to the regional ecological security and sustainable socio-economic development. Due to long term and high-intensity development, the ecological environment in central and southern Liaoning urban agglomerations has been greatly destroyed thereafter has restricted sustainable development in this region. Based on Landsat ETM and OLI images, land use of this urban agglomeration in 2005, 2010 and 2015 was extracted. The integrative index of multiple-ecosystem services (IMES) was used to quantify the supply (IMESs), demand (IMESd) and balance (IMESb) of multiple-ecosystem services, The spatial patterns of ecosystem services and its dynamics for the period of 2005-2015 were revealed. The multiple regression and stepwise regression analysis were used to explore relationships between ecosystem services and socioeconomic factors. The results showed that the IMESs of the region increased by 2.93%, whereas IMESd dropped 38%. -
Liaoning WLAN Hotspots
Liaoning WLAN hotspots NO. SSID Location_Name Location_Type Location_Address City Province High-tech park apartment CITY- 1 ChinaNet Office Building\Others Dalian Shahekou District Huangpu Road Dalian Liaoning ONE 2 ChinaNet GiaHui Building Business Building Dalian public fate Street 58 Dalian Liaoning Development Zone KaiLun 3 ChinaNet Hotels Dalian JinMa road No. 186 Dalian Liaoning Hotel 4 ChinaNet Damti coffee Entertainment bars(café\tea) Dalian Shahekou District Joint Road No. 187 Dalian Liaoning Wa Fang Dian Ge Lan West 5 ChinaNet entertainment bars(café\tea) Dalian Wafangdian DaKuan 3 Broad Street 93 Dalian Liaoning Food 6 ChinaNet Technology Square Office Building Dalian Shahekou District Home Street 419 Dalian Liaoning 7 ChinaNet Building hope Office Building Dalian Zhongshan District Zhongshan Road No. 136 Dalian Liaoning 8 ChinaNet Ou LI Jiar hotel Hotels Dalian Shahekou District Zhongshan Road No. 418 Dalian Liaoning 9 ChinaNet Dalian Telecom Office Office Building Dalian City Zhongshan Road No. 167 Dalian Liaoning 10 ChinaNet Jinhai Hotel Hotels Zhongshan District Jiefang Road No. 655 Dalian Liaoning Development Zone YingFang Dalian Economic and Technological Development Zone gold road No. 11 ChinaNet Hotels Dalian Liaoning Hotel 135 12 ChinaNet LangDi Cafe Entertainment bars(café\tea) Dalian Xigang District Wusi Road No. 80 Dalian Liaoning 13 ChinaNet LiYue Bay Hotel Hotels Dalian Zhongshan District ZhiFu Road 26 Dalian Liaoning 14 ChinaNet Software Park Building 8 Office Building Dalian Software Park Dalian Liaoning 15 ChinaNet -
Urban Climate 28 (2019) 100458
Urban Climate 28 (2019) 100458 Contents lists available at ScienceDirect Urban Climate journal homepage: www.elsevier.com/locate/uclim Spatial differentiation of urban wind and thermal environment in different grid sizes T ⁎ ⁎⁎ Jun Yanga,b, , Yichen Wanga, Xiangming Xiaoc,d, , Cui Jina, Jianhong (Cecilia) Xiae, Xueming Lia a Human Settlements Research Center, Liaoning Normal University, Dalian 116029, China b Jangho Architecture College, Northeastern University, Shenyang 110169, China c Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA d Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China e School of Earth and Planetary Sciences, Curtin University, Perth 65630, Australia ARTICLE INFO ABSTRACT Keywords: Due to rapid urbanization, China's urban morphology has undergone tremendous changes, re- Frontal area index sulting in an increased urban heat island (UHI) effect and negative impact of thermal environ- Urban thermal environment ment, especially in summer. Studying the scale effect between urban wind and thermal en- Grid size vironment can provide the best scale for the wind environment planning on mitigating UHI Maximum mutual information effect. Taking Dalian as an example, using multi-source data, a nonlinear correlation analysis was Dalian city used to analyze the correlation between the frontal area index (FAI) and land 77uuyyhsurface temperature (LST) under different grids. The results show that first, FAI is sensitive to grid-size changes. When the grid size increases from 25 × 25 m to 150 × 150 m with a step size of 25 m, in July, the numbers of grids with FAI > 1 are 19,992, 1538, 153, 20, 4, and 0 (0%) accounting for 2.106%, 0.645%, 0.081%, 0.019%, 0.006%, and 0% of the total, respectively. -
Economics and Transportation Linkages Dalian Loop
Group 1 Economics and Transportation Linkages Dalian Loop Bai Jinyu China Ling Li China Reto Nebel Switzerland Vladimir Savcic Serbia/Spain Sebastian Seelig Germany Wita Simatupang Indonesia Coordinator Elien Wierenga The Netherlands 1 | ISOCARP – Young Planning Professionals’ Workshop 2008, Dalian, PR China Group 1 Introduction Dalian - an important port city of industry, trade and tourism in Northeast China – is located on the southern tip of the Liaodong Peninsula, on the West shore of the Pacific Ocean. It is neighboured by the Yellow Sea at the East and the Bohai Sea at the West. This makes Dalian to have a superb geographical location. It also serves as a gateway to Beijing and Tianjin; but also to Liaoning, Jilin and Heilongjiang and to part of the Inner Mongolia Autonomous Region. Dalian City has the jurisdiction over six districts, three county-level cities and a county, with a total population of 5.85 million people on an area of 13,566 sqkmi - please refer to table below. Target (million) Upper Limit (million) Name of Jurisdiction Urban Agricultural Total Urban Agricultural Total Population Population Population Population Population Population Central City 4.5 0.3 4.8 6 0.4 6.4 Main City 2.8 0.1 2.9 3.3 0.1 3.4 New City 1.7 0.2 1.9 2.7 0.3 3 Zhuanghe City 0.75 0.3 1.05 0.8 0.35 1.15 Wafangdian City 0.8 0.3 1.1 0.85 0.35 1.2 Pulandian City 0.65 0.25 0.9 0.75 0.35 1.1 Changhai Town 0.1 0.05 0.15 0.1 0.05 0.15 Total 6.8 1.2 8 8.5 1.5 10 Table 1. -
Minimum Wage Standards in China August 11, 2020
Minimum Wage Standards in China August 11, 2020 Contents Heilongjiang ................................................................................................................................................. 3 Jilin ............................................................................................................................................................... 3 Liaoning ........................................................................................................................................................ 4 Inner Mongolia Autonomous Region ........................................................................................................... 7 Beijing......................................................................................................................................................... 10 Hebei ........................................................................................................................................................... 11 Henan .......................................................................................................................................................... 13 Shandong .................................................................................................................................................... 14 Shanxi ......................................................................................................................................................... 16 Shaanxi ...................................................................................................................................................... -
Area Comprehensive Score 1990 2000 2010 Heping District 0.307
Comprehensive score of aging level in 1990, 2000 and 2010 Comprehensive score Area 1990 2000 2010 Heping District 0.307 0.572 0.792 Shenhe District 0.319 0.554 0.774 Dadong District 0.275 0.558 0.803 Huanggu District 0.262 0.542 0.777 Tiexi District (Shenyang) 0.252 0.611 0.800 Sujiatun District 0.202 0.409 0.699 Dongling District 0.202 0.370 0.512 Shenbei New District 0.196 0.388 0.534 Yuhong District 0.197 0.364 0.593 Liaozhong County 0.187 0.351 0.627 Kangping County 0.165 0.318 0.604 Faku County 0.195 0.354 0.653 Xinmin City 0.177 0.351 0.627 Zhongshan District 0.336 0.592 0.888 Xigang District 0.327 0.605 0.860 Shahekou District 0.284 0.534 0.770 Ganjingzi District 0.242 0.381 0.557 Lushunkou District 0.302 0.427 0.668 Jinzhou District 0.267 0.360 0.531 Changhai County 0.215 0.314 0.638 Wafangdian City 0.218 0.431 0.799 Pulandian City 0.243 0.440 0.812 Zhuanghe City 0.224 0.460 0.778 Tiedong District 0.230 0.541 0.831 Tiexi District (Anshan) 0.234 0.514 0.896 Lishan District 0.198 0.540 0.950 Qianshan District 0.215 0.399 0.721 Tai'an County 0.187 0.355 0.613 Xiuyan Manchu Autonomous County 0.171 0.349 0.620 Haicheng City 0.191 0.321 0.573 Xinfu District 0.245 0.517 0.853 Dongzhou District 0.230 0.551 1.000 Wanghua District 0.206 0.464 0.814 Shuncheng District 0.195 0.479 0.819 Fushun County 0.256 0.401 0.701 Xinbin Manchu Autonomous County 0.110 0.298 0.615 Qingyuan Manchu Autonomous County 0.124 0.318 0.618 Pingshan District 0.208 0.475 0.778 Xihu District 0.217 0.497 0.829 Mingshan District 0.186 0.440 0.743 Nanfen District 0.196