Generalized Hamming Weights of Irreducible Cyclic Codes

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F q Set of q Alphabets

F q Set of q Alphabets
α Sk β Sk
: : : : : : : : : : : : : : : : : : : : : : : : : : : :
ˆk Generator matrix of S r th -order Reed M¨ uller Code Binary nonlinear Preparata Code Binary nonlinear Kerdock Code max{M | there exists a binary (n, M, dH ) code } Gray map {φ(c) : c ∈ C} : Gray image of C Irreducible polynomial over Z2 such that it divides xn − 1 over Z2 Hensel uplift of h2 (x) over Z4 p-basis of C p-dimension of C Generalized gray map Generalized gray image of C Generalized gray image of C in 2-basis form Binary residue code of C Binary torsion code of C Correlation of c ∈ C Simplex Code of type α Simplex Code of type β
Synopsis
Name of the student: Manish Kumar Gupta Degree for which submitted: Ph.D. Thesis Title: On Some Linear Codes over Z2s Name of the Thesis Supervisors: Prof. M. C. Bhandari & Prof. A. K. Lal Month and Year of Thesis Submission: December, 1999 Roll No.: 9310863 Department: Mathematics

Asymptotic Weight Distributions of Irregular Repeat-Accumulate Codes

Asymptotic Weight Distributions of Irregular Repeat-Accumulate Codes

Abstract— In this paper, the average input-parity weight enumerator (AIPWE) of regular/irregular repeat-accumulate (RA) ensembles is derived, by viewing an RA code as a serial concatenation of an outer low-density generator matrix (LDGM) code and an inner accumulator. The exact average weight distribution (AWD) of the systematic and nonsystematic versions of the RA ensembles are then obtained from their AIPWE’s. We further derive the asymptotic growth exponent of the AWD’s, which are then used to bound the ensemble performance under maximum likelihood (ML) decoding. It is shown that simple nonsystematic regular RA ensembles outperform systematic regular RA and regular low-density parity-check (LDPC) ensembles and have distance spectrum which closely resembles that of the random ensemble.

中国教育优缺点英语作文

中国教育优缺点英语作文

中国教育优缺点英语作文The Pros and Cons of Education in ChinaEducation, being the backbone of any society, plays a pivotal role in shaping the future of its youth. China, with its rich cultural heritage and historical context, has a unique education system that has both distinct advantages and some notable challenges.Advantages of Chinese Education:1.Emphasis on Basics:Chinese education systems, especially at the primary andsecondary levels,focus heavily on fundamental skills such as mathematics, science,and language arts.This ensures a solid foundation for students, preparing them well for further academic and professional pursuits.2.Cultural Preservation:Chinese education strongly values the preservation andpromotion of its rich cultural heritage.This is evident in the integration of traditional subjects like Chinese literature and history, which foster a sense of cultural pride and identity among students.3.Discipline and Structure:Chinese schools are known for their strict disciplineand well-structured curricula. This structured approach helps students develop good habits, time management skills, and a sense of responsibility.4.High Standards:The education system in China aims to maintain high standardsof academic excellence. This is reflected in the rigorous exams and assessments that students undergo, ensuring they are constantly challenged and pushed to excel.Challenges of Chinese Education:1.Heavy Focus on Exams:While exams serve as a metric to evaluate studentperformance, the overemphasis on them can lead to a narrow focus on exam-related content, neglecting other important areas of education like creativity, critical thinking, and practical skills.ck of Diversity:The one-size-fits-all approach to education in China can limitthe opportunities for students to explore their interests and talents.The standardized curriculum and exams do not always cater to the diverse needs and abilities of students.3.Stress and Burnout:The intense focus on exams and high standards can createimmense pressure on students, leading to stress, anxiety, and even burnout.This can have negative impacts on their mental health and well-being.4.Limited Autonomy:The strict structure and discipline in Chinese schools cansometimes limit students' autonomy and agency. Students may feel constrained in terms of exploring their own interests and taking initiative in their learning.In conclusion,while the Chinese education system has several strengths that prepare students well for academic and professional success, it also faces some challenges that need to be addressed. Balancing the focus on fundamentals with the promotion of creativity and diversity,as well as prioritizing student well-being,are crucial in creating a more comprehensive and inclusive education system.。

初始计量英语

初始计量英语

IntroductionIn the globalized landscape where competition is fierce and quality standards are continuously escalating, understanding the multi-dimensional aspects of high-quality and high-standard metrics becomes paramount. These metrics are not just numerical indicators; they embody a comprehensive framework that reflects excellence in various domains, including but not limited to manufacturing processes, service delivery, product design, education, and policy implementation. This essay aims to delve into the intricacies of high-quality and high-standard metrics from multiple perspectives.First Dimension: Precision and AccuracyHigh-quality and high-standard metrics often begin with precision and accuracy. In any field, whether it's scientific research or industrial production, these terms represent the degree to which measurements or outcomes correspond to their true values. Precision refers to the consistency of repeated measurements while accuracy concerns how close those measurements are to the actual value. For instance, in manufacturing, high-quality products adhere strictly to precise specifications and tolerances, ensuring consistent performance and longevity. Similarly, in academic research, studies that employ highly accurate and precise data collection methods contribute significantly to the validity and reliability of results.Second Dimension: Efficiency and EffectivenessAnother critical aspect of high-quality and high-standard metrics involves efficiency and effectiveness. Efficiency pertains to achieving maximum output with minimum input, whereas effectiveness is about doing the right things to achieve intended goals. A high-quality service, for example, might be one that minimizes customer wait times (efficiency) while maximizing customer satisfaction (effectiveness). In project management, a high-standard metric could be measured by the timely completion of milestones within budget, coupled with meeting or exceeding client expectations.Third Dimension: Adaptability and InnovationIn today's fast-paced world, adaptability and innovation have become key components of high-quality and high-standard metrics. An adaptable system can respond effectively to change and improve over time, while innovative approaches lead to breakthroughs and competitive advantages. High-quality software development, for instance, demands not only error-free coding but also the ability to integrate new features and updates quickly. Educational institutions that foster innovation and adaptability in their curriculum design and teaching methodologies can ensure that students are equipped with skills relevant to a rapidly evolving job market.Fourth Dimension: Sustainability and ResponsibilityA fourth dimension in assessing high-quality and high-standard metrics is sustainability and responsibility. Products, services, and policies should meet present needs without compromising future generations' ability to meet theirs. This includes environmental stewardship, social equity, and economic viability. For example, a construction company adhering to high-quality standards may use eco-friendly materials and efficient energy systems, thereby reducing its carbon footprint. Similarly, corporate governance practices that incorporate ethical decision-making and social responsibility form part of high-standard business operations.Fifth Dimension: User Experience and Customer SatisfactionLastly, user experience and customer satisfaction are pivotal dimensions in defining high-quality and high-standard metrics. A superior product or service must offer an intuitive, seamless, and enjoyable experience to users, alongside fulfilling their requirements. The measurement of customer satisfaction through feedback mechanisms, surveys, and reviews provides valuable insights into areas that need improvement and serves as a testament to the quality of the offering.ConclusionIn summary, high-quality and high-standard metrics encompass a broad spectrum of characteristics that transcend mere technical specifications orquantitative assessments. They require a holistic approach that takes into account precision and accuracy, efficiency and effectiveness, adaptability and innovation, sustainability and responsibility, and user experience and customer satisfaction. By rigorously applying these multi-faceted metrics across all sectors and industries, organizations can not only maintain but also enhance their competitive edge and foster a culture of continuous improvement and excellence. This underscores the importance of developing and maintaining high-quality and high-standard benchmarks in every facet of human endeavor.While this analysis has touched upon several core elements, it's essential to note that the definition and application of high-quality and high-standard metrics can vary widely depending on the specific context and industry. Regardless, the pursuit of these metrics remains a cornerstone for progress and success in the 21st century.Word count: 649 words (excluding title)。

名词解释(谢哲宇修改

名词解释(谢哲宇修改

Chapter 1Statistics(统计学):研究数据资料的收集、整理、分析和解释(interpretation)的科学。

Biostatistics(生物统计学):统计学应用于生物科学Variable(变量):指某种特征,它的表现在不同个体间或不同组间存在变异性。

Observation(观测值):指对变量的表现进行观察或测量所获得的数值,有时也被称为变数(variate)Population(总体):又叫“统计总体”,是指一个统计问题研究对象的全体,它是具有某种(或某些)共同特征的元素的集合。

Individual(个体):总体中每一个研究对象称作个体。

Sample(样本):从总体中按一定方法抽取部分具有代表性的个体,这部分个体称为样本。

Parameter(参数):描述总体特征的数,如总体平均数、总体方差等。

Statistic(统计量):描述样本特征的量,如样本平均数、样本方差、样本相关系数等。

Accuracy(准确性):指观测值或估计值与真值的接近程度。

Precision(精确性):对同一物体的重复观察值或估计值彼此之间的接近程度。

Chapter 2Raw data(直接数据):数据调查与实验未经处理的数据;Continuous data(连续性数据):指在一定范围内可取任何实数值的数据。

Discrete data(离散性数据):在一定范围内只能取有限种可能值的数据。

Count data(计数数据):用计数的方式得到的数据资料,必须用整数来表示。

Classification data(分类资料):可自然的或人为的分为2个或多个不同类别的资料。

例如:男生记做1 女生记做2频数(率)分布(frequency distribution);;下四分位数(lower quartile);中位数(median);上四分位数(upper quartile);条形图(bar chart);直方图(histogram);饼图(pie chart);散点图(scatter plot),组间距(interval)Percentile(百分位数):一组n个观测值按数值大小排列,小于某数值的数据个数占全体个数的x%,则为x%分位数。

上大学的重要性英语作文

上大学的重要性英语作文

Attending university is a significant milestone in an individuals life,offering a multitude of benefits that extend beyond academic learning.Here are some key points that highlight the importance of pursuing higher education:1.Academic Excellence:Universities provide a comprehensive curriculum that allows students to delve deeper into their chosen field of study.This academic depth is crucial for understanding complex concepts and theories that form the foundation of various professions.2.Skill Development:Beyond the classroom,universities offer opportunities to develop a range of skills.These include critical thinking,problemsolving,communication,and teamwork,which are essential for success in the workplace and in life.working Opportunities:University life exposes students to a diverse community of individuals from different backgrounds and cultures.This environment is conducive to building a professional network that can be invaluable for future career opportunities.4.Research and Innovation:Universities are hubs for research and innovation.Students have the opportunity to participate in cuttingedge research projects,which can lead to groundbreaking discoveries and advancements in various fields.5.Personal Growth:Living away from home and managing ones own affairs can significantly contribute to personal growth.University life encourages independence, selfreliance,and maturity.6.Career Preparation:A university degree is often a prerequisite for many professional careers.Higher education equips students with the necessary qualifications and credentials that employers seek.7.Cultural Exposure:Universities often host cultural events,guest lectures,and international exchange programs,providing students with a broader understanding of the world and its diverse cultures.8.Access to Resources:Universities provide access to stateoftheart facilities,including libraries,laboratories,and technological resources that are essential for academic and research pursuits.9.Career Services:Most universities have dedicated career services that assist students in finding internships,parttime jobs,and fulltime employment upon graduation,easing the transition from academia to the professional world.10.Lifelong Learning:The habit of lifelong learning is often instilled during university years.This mindset is crucial in todays rapidly changing world,where continuous learning is necessary to stay relevant and competitive.In conclusion,attending university is not just about obtaining a degree it is a transformative experience that shapes an individuals intellectual,professional,and personal development.It opens doors to a world of opportunities and equips students with the tools necessary to navigate and succeed in an everevolving global landscape.。

非酒精性脂肪性肝病高危人群监测与防治

非酒精性脂肪性肝病高危人群监测与防治

∗基金项目:科技部病毒性肝炎及艾滋病等传染病重大专项(编号:2018ZX10723203);珠江人才计划本土创新团队项目(编号: 2017BT01S131)作者单位:511340广州市南方医科大学南方医院增城分院(李俊缨,陈金军);南方医院(周玲)第一作者:李俊缨:女,27岁,南方医科大学传染病学硕士㊂主要从事非酒精性脂肪性肝病诊断和微创减重手术治疗临床研究㊂E-mail:2292921780@通讯作者:陈金军,E-mail:chjj@ ㊃专家论坛㊃非酒精性脂肪性肝病高危人群:监测与防治∗李俊缨,周玲,陈金军㊀㊀ʌ关键词ɔ㊀非酒精性脂肪性肝病;高危人群;防治㊀㊀DOI:10.3969/j.issn.1672-5069.2020.05.002㊀㊀Surveillance and management of individuals with high risk of NAFLD㊀Li Junying,Zhou Ling,Chen Jinjun.Department of Liver Diseases,Zengcheng Branch,Nanfang Hospital,Guangzhou510515,Guangdong Province,China㊀㊀ʌKey wordsɔ㊀Non-alcoholic fatty liver diseases;High risk;Surveillance and management㊀㊀非酒精性脂肪性肝病(NAFLD)已成为全球性最主要的肝病㊂儿童和成人可能有不同的发病机制,儿童更易受遗传和环境因素的影响㊂除基因外,高龄㊁男性或绝经期女性㊁2型糖尿病㊁肥胖㊁饮酒和肌肉衰减为成人罹患NAFLD及疾病进展的高危因素㊂本文尝试总结成人NAFLD发病的高危因素及相应的监测和干预措施㊂1㊀主要高危因素1.1遗传易感性㊀多个层面的遗传异常影响单纯性非酒精性脂肪肝(NAFL)的罹患风险,以及疾病进展,包括非酒精性脂肪性肝炎(NASH)㊁肝纤维化㊁肝硬化和肝细胞癌,包括PNPLA3I148M突变增加NAFLD罹患及疾病进展(肝纤维化和肝细胞癌)的风险;TM6SF2E167K突变则是NAFLD更易发生肝病事件而心脑血管事件减少的 分流信号 [1]㊂在大队列真实世界研究中发现,NAFLD并不增加急性心肌梗死或中风的发病率[2]㊂以遗传特征将NAFLD 分层管理可能是将来个体化监测和干预NAFLD的方向㊂1.2老年与衰老㊀儿童和成人NAFLD的肝组织学特征和疾病早期表现不同,提示年龄的影响不仅是环境和遗传因素的积累,在发病机制上也不尽相同,需要更多的研究阐明㊂男性NAFLD的年龄分布呈U 型,即50~60岁开始下降[3]㊂绝经前妇女则罹患NAFLD较少,绝经后增加明显;绝经期女性需要更多的关注㊂1.3肥胖㊀肥胖是重要的代谢异常组分,与罹患NAFLD密切相关㊂重复肝脏活检的队列研究证实,肥胖是NAFLD肝纤维化快速进展的危险因素[4]㊂超重,尤其是肥胖是NAFLD相关肝细胞癌发生的独立危险因素,男性肥胖患者患病风险更高㊂非肥胖者罹患NAFLD的高危因素包括中心性肥胖㊁胰岛素抵抗㊁体质量快速增加和遗传危险因素,例如PNPLA3多态性㊂关于肥胖NAFLD人群的研究较多,而非肥胖型NAFLD已经受到了重视[5]㊂肥胖,或者是内脏肥胖时的炎症细胞,尤其是巨噬细胞,在脂肪组织和肝组织中的功能表型转化㊁细胞迁移和信号传递可能在肥胖导致的NAFLD进展过程中起重要作用[6]㊂1.42型糖尿病(T2DM)㊀我国T2DM的流行率持续升高,其合并的NAFLD问题日渐突出㊂T2DM也是NAFLD肝纤维化快速进展的独立危险因素[4]㊂以无创筛查手段发现T2DM患者中进展性肝纤维化比例>10%,50%左右NAFLD相关肝硬化患者合并2型糖尿病㊂胰岛素抵抗和高胰岛素血症是两者的共同疾病基础㊂部分治疗2型糖尿病的药物可缓解NAFLD相关的肝脏问题,包括肝脏脂肪变性㊁炎症,甚至肝纤维化[7]㊂有关处置糖尿病的专业群体,包括但不限于医疗㊁护理㊁诊断㊁康复等人员,应高度重视2型糖尿病的肝脏并发症,即NAFLD及其肝病疾病谱㊂1.5饮酒㊀虽然临床诊断的标准和流程会将酒精性㊃216㊃实用肝脏病杂志2020年9月第23卷第5期㊀J Prac Hepatol,Septemper.2020.Vol.23No.5肝病与NAFLD鉴别开,但两者常常同时存在,尤其是肥胖患者㊂饮酒是NAFLD进展为NASH的危险因素㊂空腹中等饮酒量也可使得肥胖相关肝脏脂肪变性进展为脂肪性肝炎㊂最近的前瞻性研究证实,NAFLD患者即便非过量饮酒也会导致NAFLD肝纤维化进展㊂在NAFLD患者中,没有安全的饮酒量[8]㊂酒精性肝病与NAFLD在细胞等多个层面上具有共同的发病机制,可能都有乙醇的作用,其差别在于乙醇的来源㊂阐明肠道微生态相关的内源性乙醇的产生机制有助于制定两种不同临床表型的肝脏疾病的监测和干预策略㊂1.6肌肉衰减㊀肌肉衰减与年龄㊁饮食㊁运动和遗传相关㊂一般是由于年龄增长和衰老所致,而在年轻人群中运动和饮食是肌肉衰减的主要影响因素㊂大规模的队列研究大部分来自韩国,其结果表明肌肉衰减与NAFLD发生率增高直接相关㊂肌肉衰减也是导致NAFLD患者肝内炎症㊁纤维化和长期病死率增高的风险因素[9,10]㊂1.7高危因素的相互作用㊀罹患NAFLD和疾病进展受遗传因素和环境因素的综合影响㊂具有多重高危因素的患者群体最需要关注㊂目前,多以遗传因素进行分组后进行互作分析㊂较新的研究数据提示,胰岛素抵抗或高胰岛素血症加重具有遗传易感性群体的肝脂肪变[11],而年龄相关的肌肉衰减并不会恶化PNPLA3I148M携带者肝脂肪变或肝纤维化的级别[12]㊂最新的尝试发现,可将NAFLD分为遗传型(genetic NAFLD)和代谢型(metabolic NAFLD),更有助于理解常见高危因素与NAFLD的相互因果关系㊂很多队列研究采用多因素综合分析法㊂在单纯肝脏脂肪变转变为NASH的高危因素上,短期内(6个月内)体质量增加超过5kg,体质指数㊁胰岛素抵抗评分㊁血胆固醇㊁甘油三酯㊁瘦素水平升高的人群更容易使得NAFL进展为NASH[13]㊂队列研究证实,高龄㊁肥胖㊁T2DM㊁PNPLA3和rs738409SNP基因是NASH相关肝纤维化进展的独立危险因素[14]㊂重复肝脏活检的队列研究证实,T2DM和肥胖是NAFLD肝纤维化快速进展的独立危险因素,也有队列研究证实,2型糖尿病和肥胖是NASH相关HCC 发病的危险因素[15]㊂2 高危人群的筛查与诊断结合部分高危因素,如肥胖人群和T2DM等重要高危因素的人口比例及部分发表数据,多国研究者利用数学模型推算,2016年我国大陆有2.43亿NAFLD人群,NAFLD相关肝硬化达110万,而2030年将分别达到3.14亿和230万[16]㊂针对NAFLD的相关医学筛查,定义高危人群并制定相关筛查和诊断策略,将最大程度地利用有限的医疗资源,发现和管理NAFLD,尤其是较易进展为脂肪性肝炎㊁进展性肝纤维化/肝硬化㊁肝细胞癌的人群,可以做到早发现㊁早干预,降低未来我国肝病负担,将是健康中国的重要部分㊂针对NAFLD人群的筛查,采用简便㊁易行㊁低价㊁敏感㊁无创方法和手段进行比较适宜㊂关于肝脏脂肪变性的筛查和诊断手段,常用腹部超声,已发表的大部分NAFLD流行率的横断面数据也是采用腹部超声检查㊂考虑到操作简便性和可靠性,未来将会普及使用肝脏瞬时弹性成像的脂肪衰减等技术㊂目前,已有不少类似设备上市,但各设备诊断界值各异,需要进一步确认㊂磁共振脂肪定量成像(MRI-PDFF)可用于NAFL和NASH的肝脏脂肪含量的定性和定量诊断[17],但部分极高体质量者无法进行相关的检查和诊断㊂建议对超重或肥胖及T2DM患者进行常规筛查肝脏脂肪变性,尤其是绝经期妇女㊁老年且出现肌肉衰减者等亚群体㊂脂肪性肝炎的筛查主要依赖谷丙转氨酶的反复测量㊂目前,尚缺乏更佳的血清生物标记物准确筛查NASH,需要更多研究㊂建议针对肥胖或超重㊁T2DM等人群定期检测谷丙转氨酶(3~6个月),尤其是体质量迅速增加(5kg/6个月)㊁饮酒㊁肌肉衰减等高危群体㊂肝脏纤维化程度是影响NAFLD发生临床显性肝病事件的最主要的决定因素,筛查NAFLD高危人群肝纤维化更重要㊂针对NASH肝纤维化相关生物标志物较多,包括透明质酸㊁IV型7S胶原㊁III前胶原肽和花紫藤凝集素阳性mac2结合蛋白(WFA-M2BP)㊂血小板计数是预测NAFLD患者晚期肝纤维化最简单的指标㊂欧洲多个相关协会的联合指导意见建议对合并肥胖或任何代谢综合征(MS)的患者应该接受超声和脂肪变性生物标记和血清肝酶水平检查,以鉴别诊断NAFL和NASH[18]㊂所有NAFLD患者均需进行肝脏纤维化程度的评估㊂NASH相关肝硬化病例逐渐增多,但大部分肝病相关专业医疗人员仍然未对其给予足够的重视,尤其是在与隐源性肝硬化的鉴别诊断的情形下㊂NASH肝硬化的诊断主要元素包括:病史上有肝脏脂肪变性,或者至少1个异常组分;肝组织学或其他影像学证实存在肝硬化或者门静脉高压等证据,初步排除常见慢性肝病病因,如病毒性肝炎㊁酒精性肝㊃316㊃实用肝脏病杂志2020年9月第23卷第5期㊀J Prac Hepatol,Septemper.2020.Vol.23No.5病㊁自身免疫性肝病㊁肝豆状核变性等,即可初步诊断[19]㊂建议按照代谢性脂肪性肝病的概念重新审视NASH相关肝硬化的诊断流程,尤其是在隐源性肝硬化的鉴别诊断㊂NASH肝硬化患者需要筛查门静脉高压的相关高危临床事件风险,胃食管静脉曲张㊁腹水㊁HCC等㊂针对NASH相关HCC,筛查以甲胎蛋白和腹部超声为基础,以每6个月进行筛查㊂但近期研究证实甲胎蛋白缺乏有效监测的特异性和灵敏性㊂HCC的诊断以影像学和组织学为证据[20]㊂肝脏病理是诊断NAFLD的 金标准 ㊂在成人型NASH(1型),炎症和胶原沉积发生在肝小叶3区窦状旁窦,并与小叶炎症㊁肝细胞气球样变和马洛里小体相关,而儿童型NASH(2型)表现为1区炎症㊁主要是门脉-窦周纤维化而缺乏明显的气球样变㊂很大比例的儿童患者具有1型和2型NASH的重叠特征[21]㊂3 干预治疗3.1生活方式干预㊀生活方式干预是治疗NAFLD的一线和基础性治疗㊂针对NAFLD而言,体质量减少5%可以减少肝脂肪变性,减重10%可改善肝坏死炎症和纤维化[22]㊂但临床实践常忽略的问题是,生活方式干预有效率较低,超过70%患者并不能达到减重的目的,需要更多的手段,包括严密的生活方式监督㊁改善认知和行为模式等综合运用㊂3.2药物治疗㊀目前,尚无国家管理部门批准用于NAFLD的治疗药物[23]㊂针对NAFL患者,初步证据表明胰高血糖素样肽-1激动剂,如依塞那肽和利拉格肽,能改善肝脂肪变性,但减轻体质量的效果不明确[24]㊂针对NASH患者,多个队列研究均证实维生素E㊁吡格列酮㊁胆汁酸衍生物6-乙基和Resmetirom 是对经组织学证实的NASH患者短期内最有效的药物㊂依折麦布作为降低肠道胆固醇摄取的降脂药可改善NAFLD的肝组织学损伤[23]㊂针对NASH相关肝硬化,肾素血管紧张素醛固酮系统抑制剂被证实能改善肝纤维化程度[23]㊂针对NASH相关HCC,研究证实对合并T2DM的NASH相关早期肝硬化患者长期使用二甲双胍显著降低了失代偿肝硬化和HCC 的发生㊁发展及死亡[25]㊂他汀类药物的使用可能与HCC的风险降低有关[26]㊂3.3减肥手术㊀有效的减肥手术将显著改善/逆转NAFLD的所有肝组织学特征,特别是包括严重肥胖患者的纤维化㊂针对病态肥胖NASH早期肝硬化患者,研究证实胃袖状切除术除了减重之外可逆转肝硬化[27]㊂胃左动脉栓塞术也开始用于肥胖患者的减重治疗,但目前对于NAFLD治疗效果尚不明确㊂ʌ参考文献ɔ[1]CarlssonB,Lindén D,Brolén G,et al.The emerging role of genet-ics in precision medicine for patients with non-alcoholic steatohepa-titis.Aliment Pharmacol Ther,2020,51(12):1305-1320. [2]AlexanderM,Loomis AK,Lei J,et al.Non-alcoholic fatty liverdisease and risk of incident acute myocardial infarction and stroke: findings from matched cohort study of18million European adults.BMJ,2019,367:l5367.[3]Lonardo A,Bellentani S,KArgo C,et al.Epidemiologicalmodifiers of non-alcoholic fatty liver disease:focus on high-risk groups.Dig Liver Dis,2015,47(12):997-1006.[4]Singh S,Allen AM,Wang Z,et al.Fibrosis progression in nonal-coholic fatty liver vs nonalcoholic steatohepatitis:a systematic review and meta-analysis of paired-biopsy studies.Clin Gastroen-terol Hepatol,2015,13(4):643-654.[5]Cowman mentary on forensic and non-forensic psychiatricnursing skills and competencies for psychopathic and personality dis-ordered patients.J Clin Nurs,2014,23(7-8):1170-1171. [6]Lebeau PF,Byun JH,Platko K,et al.Pcsk9knockout exacerbatesdiet-induced non-alcoholic steatohepatitis,fibrosis and liver injury in mice.JHEP Rep,2019,1(6):418-429.[7]Younossi ZM,Golabi P,de Avila L,et al.The global epidemiologyof NAFLD and NASH in patients with type2diabetes:a systematic review and meta-analysis.J Hepatol,2019,71(4):793-801.[8]Chang Y,Cho YK,Kim Y,et al.Nonheavy drinking andworsening of noninvasive fibrosis markers in nonalcoholic fatty liver disease:a cohort study.Hepatology,2019,69(1):64-75. [9]Bhanji RA,Narayanan P,Allen AM,et al.Sarcopenia in hiding:the risk and consequence of underestimating muscle dysfunction in nonalcoholic steatohepatitis.Hepatology,2017,66(6):2055 -2065.[10]Kim JA,Choi KM.Sarcopenia and fatty liver disease.Hepatol Int,2019,13(6):674-687.[11]Barata L,Feitosa MF,Bielak LF,et al.Insulin resistance exacer-bates genetic predisposition to nonalcoholic fatty liver disease in in-dividuals without diabetes.Hepatol Commun,2019,3(7):894 -907.[12]Xia MF,Chen LY,Wu L,et al.The PNPLA3rs738409C>G va-riant influences the association between low skeletal muscle mass and NAFLD:The Shanghai Changfeng study.Aliment Pharmacol T-her,2019,50(6):684-695.[13]Zelber-Sagi S,Lotan R,Shlomai A,et al.Predictors for incidenceand remission of NAFLD in the general population during a seven-year prospective follow-up.J Hepatol,2012,56(5):1145-1151.[14]Koo BK,Joo SK,Kim D,et al.Additive effects of PNPLA3andTM6SF2on the histological severity of non-alcoholic fatty liver dis-ease.J Gastroenterol Hepatol,2018,33(6):1277-1285. [15]Turati F,Talamini R,Pelucchi C,et al.Metabolic syndrome andhepatocellular carcinoma risk.Br J Cancer,2013,108:222-228.㊃416㊃实用肝脏病杂志2020年9月第23卷第5期㊀J Prac Hepatol,Septemper.2020.Vol.23No.5㊀㊀∗基金项目:国家自然科学基金资助项目(编号:81870404/81670518/81170392)作者单位:510080广州市中山大学附属第一医院消化内科第一作者:叶俊钊,男,31岁,医学博士㊂主要从事非酒精性脂肪性肝病的基础和临床研究通讯作者:钟碧慧,E-mail:sophiazhong@[16]Estes C,Anstee QM,Arias-Loste MT,et al.Modeling NAFLDdisease burden in China,France,Germany,Italy,Japan,Spain, United Kingdom,and United States for theperiod2016-2030.J Hepatol,2018,69(4):896-904.[17]Hannah WN Jr,Harrison SA.Noninvasive imaging methods to de-termine severity of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis.Hepatology,2016,64(6):2234-2243. [18]Yoneda M,Imajo K,Takahashi H,et al.Clinical strategy of diag-nosing and following patients with nonalcoholic fatty liver disease based on invasive and noninvasive methods.J Gastroenterol.2018, 53(2):181-196.[19]李俊缨,熊鸣,张继平,等.非酒精性脂肪性肝炎相关肝硬化的诊断和治疗进展.肝脏.2019,24(10):1008-1704. [20]Bruix J,Sherman M.Management of hepatocellular carcinoma:anupdate.Hepatology,2011,53:1020-1022.[21]Goldner D,Lavine JE.NAFLD in children:unique considerationsand challenges.Gastroenterology,2020,158(7):1967-1983.[22]Zelber-Sagi S,Lotan R,Shlomai A,et al.Predictors for incidenceand remission of NAFLD in the general population during a seven-year prospective follow-up.J Hepatol,2012,56:1145-1151.[23]Diehl AM,Day C.Cause,pathogenesis,and treatment of nonalco-holic steatohepatitis.N Engl J Med,2017,377(21):2063-2072.[24]Vilar-Gomez E,Calzadilla-Bertot L,Wai-Sun Wong V,et al.Type2diabetes and metformin use associate with outcomes of pa-tients with non-alcoholic steatohepatitis-related,Child-Pugh A cirrhosis.Clin Gastroenterol Hepatol,2020,S1542-3565(20) 30633-30639.[25]Margini C,Dufour JF.The story of HCC in NAFLD:from epidemi-ology,across pathogenesis,to prevention and treatment.Liver Int, 2016,36:317-324.[26]Wong VW,Chan RS,Wong GL,et munity-based lifestylemodification programme for non-alcoholic fatty liver disease:a ran-domized controlled trial.J Hepatol,2013,59:536-542. [27]Weiss CR,Abiola GO,Fischman AM,et al.Bariatric embolizationof arteries for the treatment of obesity(BEAT obesity)trial:results at1Year.Radiology,2019,291(3):792-800.(收稿:2020-07-06)(本文编辑:陈从新)㊃专家论坛㊃非酒精性脂肪性肝病合并代谢并发症患者规范治疗与管理∗叶俊钊,钟碧慧㊀㊀ʌ关键词ɔ㊀非酒精性脂肪性肝病;高血脂;高血糖;高尿酸;高血压;管理㊀㊀DOI:10.3969/j.issn.1672-5069.2020.05.003㊀㊀Standardized treatment and management ofpatients with metabolic complications and nonalcoholic fatty liver disease㊀Ye Junzhao,Zhong Bihui.Department of Gastroenterology,First Affiliated Hospital,Sun Yat-sen University,Guangzhou510080, Guangdong Provinnce,China㊀㊀非酒精性脂肪性肝病(nonalcoholic fatty liver disease,NAFLD),现有更名为代谢相关脂肪性肝病(metabolic associated fatty liver disease,MAFLD)[1],是我国乃至世界最主要的慢性肝脏疾病,累及超过全球26%以上的总人口[2,3]㊂大数据显示MAFLD 患病率仍处于持续上升阶段,并且年轻化㊁大众化趋势日益显著[3]㊂MAFLD不仅导致肝脏炎症㊁肝硬化和肝癌[2],还与糖脂代谢紊乱互为因果,引发一系列代谢合并症,包括高血糖㊁高尿酸㊁高血压和高血脂等[4],而这些合并症是驱动2型糖尿病㊁痛风和动脉粥样硬化性心脑血管疾病发生的高危因素,为患者和社会带来了巨大的负担[2]㊂纠正MAFLD合并的代谢异常对于疾病控制和降低远期严重并发症极其关键,但由于其涉及的代谢合并症多且往往相互重叠,如何针对性选用兼顾不同合并症情况下的最佳治疗,往往需要临床医师综合参照多个专科指南才㊃516㊃实用肝脏病杂志2020年9月第23卷第5期㊀J Prac Hepatol,Septemper.2020.Vol.23No.5。

计量经济学英汉术语名词对照及解释

计量经济学英汉术语名词对照及解释

计量经济学英汉术语名词对照及解释A校正R2(Adjusted R-Squared):多元回归分析中拟合优度的量度,在估计误差的方差时对添加的解释变量用一个自由度来调整。

对立假设(Alternative Hypothesis):检验虚拟假设时的相对假设。

AR(1)序列相关(AR(1) Serial Correlation):时间序列回归模型中的误差遵循AR (1)模型。

渐近置信区间(Asymptotic Confidence Interval):大样本容量下近似成立的置信区间。

渐近正态性(Asymptotic Normality):适当正态化后样本分布收敛到标准正态分布的估计量。

渐近性质(Asymptotic Properties):当样本容量无限增长时适用的估计量和检验统计量性质。

渐近标准误(Asymptotic Standard Error):大样本下生效的标准误。

渐近t 统计量(Asymptotic t Statistic):大样本下近似服从标准正态分布的t统计量。

渐近方差(Asymptotic Variance):为了获得渐近标准正态分布,我们必须用以除估计量的平方值。

渐近有效(Asymptotically Effcient):对于服从渐近正态分布的一致性估计量,有最小渐近方差的估计量。

渐近不相关(Asymptotically Uncorrelated):时间序列过程中,随着两个时点上的随机变量的时间间隔增加,它们之间的相关趋于零。

衰减偏误(Attenuation Bias):总是朝向零的估计量偏误,因而有衰减偏误的估计量的期望值小于参数的绝对值。

自回归条件异方差性(Autoregressive Conditional Heteroskedasticity, ARCH):动态异方差性模型,即给定过去信息,误差项的方差线性依赖于过去的误差的平方。

一阶自回归过程[AR(1)](Autoregressive Process of Order One [AR(1)]):一个时间序列模型,其当前值线性依赖于最近的值加上一个无法预测的扰动。

CFS效应下中英双语者语言与自尊的相关关系研究

CFS效应下中英双语者语言与自尊的相关关系研究

入点。以语 言作为 C S效应的刺激源最能够反映该文化的特 点。本研 究力 图探 讨在 C S效应基 础上双语 者的语 F F 言与个体 自尊 的相关关 系。采 用单 因素双水平的重复测量 实验 设计 , 结果发现 , 本科 生组被 试在转换 中英双语过
程 中自尊 变化显著 , 自尊的变化会随着效应的消失而恢 复到原有水 平; 但 而研 究生组被试 则在 两种语 言情境 下都 保持 高的 自尊水平并无明显 变化。
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由语言学家洪堡 ( od u) 出来了。将语言决定论 推向高 H n bt提
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各国对数学的看法英语作文

各国对数学的看法英语作文

Mathematics is a universal language that transcends cultural and geographical boundaries.However,the perception and approach to mathematics vary significantly among different countries around the world.Here is an exploration of how various nations view and engage with the subject of mathematics.China:Mastery and ExcellenceIn China,mathematics is highly valued as a subject that requires mastery and precision. The Chinese education system places a strong emphasis on math,with students expected to achieve high proficiency levels.The country is known for its rigorous curriculum and competitive exams,such as the Gaokao,where math scores play a crucial role in determining university admissions.India:A Tradition of Mathematical GeniusIndia has a rich history of mathematical innovation,dating back to ancient times.The country is renowned for its mathematical prodigies and has made significant contributions to the field.In contemporary times,Indian students are encouraged to excel in mathematics,with the subject being a core part of the education system.The competitive nature of Indian education fosters a deep understanding and appreciation for the subject.United States:A Mixed BagThe United States has a diverse approach to mathematics education.While some students excel and pursue advanced studies in the field,others struggle with basic concepts.The cation system has been criticized for not providing equal opportunities for all students to develop strong math skills.However,there is a growing emphasis on improving math education and fostering a love for the subject.Russia:Deep Understanding and ApplicationRussian education is known for its focus on developing a deep understanding of mathematical concepts.The curriculum is designed to challenge students to think critically and apply mathematical knowledge to realworld problems.Russian students often excel in international math competitions,reflecting the countrys commitment to highquality math education.France:A Strong Emphasis on TheoryIn France,mathematics is approached with a strong emphasis on theory and abstract thinking.French students are encouraged to explore the beauty and logic of mathematical concepts.The French education system is known for its rigorous training in theoretical mathematics,which has produced many renowned mathematicians.Japan:A Balance of Theory and Practical ApplicationJapanese education seeks to balance the theoretical understanding of mathematics with practical application.The curriculum is designed to be comprehensive,covering a wide range of topics and ensuring that students have a solid foundation in the subject.Japanese students are known for their strong problemsolving skills and ability to apply mathematical concepts to various situations.Germany:A Focus on Logical Thinking and PrecisionGermanys approach to mathematics education emphasizes logical thinking and precision. The curriculum is structured to develop students analytical skills and their ability to solve complex problems.German students are encouraged to explore the subject in depth,with a focus on understanding the underlying principles and concepts.ConclusionWhile the approach to mathematics education varies from country to country,the subject remains a critical component of the global educational landscape.Each nations unique perspective on mathematics contributes to the rich tapestry of global mathematical knowledge and innovation.Regardless of cultural differences,the pursuit of mathematical excellence remains a shared goal across the world.。

英语硕士毕业论文高级词汇

英语硕士毕业论文高级词汇

英语硕士毕业论文高级词汇在英语硕士毕业论文中使用高级词汇可以提升论文的学术性和表达能力。

以下是一些适合论文写作的高级词汇,总计1200字:1. Significance (意义)2. Proponent (支持者)3. Advocate (提倡者)4. Undermine (削弱)5. Enhance (增强)6. Comprehend (理解)7. Assimilate (吸收,融入)8. Analyze (分析)9. Evaluate (评估)10. Distinguish (区分)11. Contradictory (矛盾的)12. Controversial (有争议的)13. Acquire (获得)14. Substantiate (证实)15. Fabricate (捏造)16. Validity (有效性)17. Reliability (可靠性)18. Inconclusive (无定论的)19. Conclusive (确定的)20. Prominent (突出的)21. Prevalent (普遍的)22. Pervasive (普及的)23. Ubiquitous (无处不在的)24. Discern (分辨)25. Evident (明显的)26. Profound (深刻的)27. Elaborate (详细阐述)28. Alleviate (减轻)29. Mitigate (缓解)30. Ameliorate (改善)31. Perceive (感知)32. Acknowledge (承认)33. Contend (主张,辩论)34. Advocate (主张)35. Efficacy (功效)36. Eminent (杰出的)37. Stagnant (停滞的)38. Pioneering (开拓性的)39. Culminate (达到顶点)40. Provoke (引发)41. Foster (培养)42. Impose (征收,强加)43. Implicate (牵连,涉及)44. Exemplify (举例说明)45. Exacerbate (加剧)46. Alleviate (缓解)47. Contribute (贡献)48. Substantiate (证明)49. Corroborate (证实)50. Uphold (支持)51. Inherently (固有地)52. Conducive (有助于)53. Hinder (阻碍)54. Facilitate (促进)55. Solicit (征求)56. Inhibit (抑制)57. Impede (妨碍)58. Elucidate (阐明)59. Integral (不可或缺的)60. Constitute (构成)61. Evolve (演变)62. Assess (评估)63. Propagate (传播)64. Imply (暗示)65. Correlate (相关联)66. Chronicle (记录)67. Advocate (倡导)68. Bolster (支持)69. Coincide (一致)70. Culminate (达到顶点)71. Illuminate (阐明)72. Innovate (创新)73. Disseminate (传播)74. Foster (培养)75. Clarify (澄清)76. Substantiate (证实)77. Postulate (假设)78. Elucidate (阐明)79. Deduce (推断)80. Propound (提出)81. Validate (验证)82. Attribute (归因于)83. Veracity (真实性)84. Intricate (复杂的)85. Entail (需要)86. Evoke (唤起)87. Delineate (描绘)88. Convey (传达)89. Contrive (策划)90. Culminate (达到高潮)91. Credible (可信的)92. Cynical (愤世嫉俗的)93. Connote (暗示)94. Ascribe (归因于)95. Appertain to (属于)96. Dissociate (分离)97. Fabricate (捏造)98. Elucidate (阐明)99. Dispense with (省去) 100. Attribute to (归因于) 101. Delineate (描述) 102. Advocate (主张) 103. Constitute (构成) 104. Corroborate (证实) 105. Refute (反驳)106. Merit (价值)107. Superficial (肤浅的) 108. Substantial (实质的) 109. Facilitate (促进) 110. Contend (主张) 111. Compensate for (补偿) 112. Deviate (偏离)113. Dissent (异议)114. Acumen (敏锐)115. Ambiguous (含糊不清的) 116. Validate (验证)117. Attribute to (归因于) 118. Manifest (显现)119. Substantiate (证实) 120. Curtail (削减)121. Paradoxical (矛盾的) 122. Incongruous (不协调的) 123. Clarity (清晰)124. Profound (深刻的) 125. Conjecture (推测) 126. Unveil (揭示)127. Illustrate (阐明)128. Demarcate (划界) 129. Promulgate (宣扬) 130. Mitigate (缓解)131. Provoke (激起)132. Fortify (加强)133. Elicit (引出)134. Brevity (简洁)135. Reminiscent (令人回忆起) 136. Evident (明显的)137. Plausible (合理的) 138. Endeavor (努力)139. Implicate (涉及)140. Indiscriminate (任意的) 141. Far-reaching (广泛的) 142. Inexplicable (难以解释的) 143. Articulate (表达清晰的) 144. Comprehensible (可理解的) 145. Pragmatic (实用的)146. Parity (平等)147. Inconsequential (不重要的) 148. Disparate (迥然不同的) 149. Amplify (扩大)150. Inhibit (阻止)。

2014年经济学年会论文

2014年经济学年会论文

以下为2014年第十四届中国经济学年会入选论文名单,公布表单中的作者信息为投稿系统直接导出(英文文章信息从邮箱所投稿件中摘录),若有需要更正之处,请您务必于10月28日之前将需要更正的个人信息、论文题目,所属领域发信致mail2cenet@。

注:第14届中国经济学年会将于2014年12月13日-14日在深圳北京大学大学汇丰商学院召开,届时还将举办经济学年会人才招聘专场和经济学图书展。

敬请关注年会官方网站-中国经济学教育科研网()的最新消息。

中文入选文章稿件领域论文题目作者单位产业组织理论固定成本与中国制造业生产率分布王磊,夏纪军, 上海财经大学经济学院产业组织理论自然垄断的测度模型及其应用——以中国重化工业为例陈林,刘小玄, 暨南大学产业经济研究院,中国社会科学院经济研究所产业组织理论消费者理性预期与企业的动态研发策略分析张剑虎, 山东大学经济学院产业组织理论政策性负担、规制俘获与食品安全龚强,雷丽衡,袁燕, 西南财经大学统计学院产业组织理论自然灾害、社会信任与产业集群阮建青,张晓波, 浙江大学中国农村发展研究院发展经济学收入差距与炫耀性消费周广肃,樊纲,马光荣, 北京大学国家发展研究院发展经济学跳出―腐败陷阱‖:与经济效率激励相容的反腐败改革叶静怡,赵奎,方敏, 北京大学经济学院发展经济学距离、知识溢出与创新——基于城市群的实证分析叶静怡,林佳,姜蕴璐, 北京大学经济学院发展经济学政府补贴、所有权性质与企业研发决策王昀,孙晓华, 大连理工大学经济学院发展经济学中国GDP统计数据可信吗:来自外太空的证据陈丰龙,徐康宁,刘修岩, 东南大学发展经济学房价影响竞争力:2003年之后的土地政策如何推升了工资?陆铭,张航,梁文泉, 复旦大学经济学院发展经济学技术进步方向转变诱导劳动力结构优化了吗?董直庆,蔡啸, 华东师范大学商学院,吉林大学商学院发展经济学发展中国家的技术模仿、经济增长与就业秦永, 南京审计学院发展经济学中国消费结构升级对产业结构转型影响的实证研究王宇,干春晖,张亚军, 上海财经大学发展经济学要素市场扭曲、垄断势力与全要素生产率盖庆恩, 上海财经大学发展经济学中国各省域产业结构生态效率的实证比较吕明元,陈维宣, 天津商业大学经济学院发展经济学村干部素质、基层民主与农民收入增加赵仁杰,何爱平, 西北大学发展经济学经济发展与交通事故:斯密德―倒U型‖法则在中国成立吗?刘瑞明,佟欣, 西北大学经济管理学院发展经济学中国省域工业增长质量:态势评价与影响因素分析刚翠翠,任保平,李娟伟, 西北大学经济管理学院发展经济学劳动力市场分割、迁移成本和滞后城市化李勇,魏婕, 西南财经大学经济学院、西北大学经济管理学院发展经济学中国能源增长核算以及对TFP的再解释邹沛江,张大永, 西南财经大学经济与管理研究院发展经济学中国的贫困现状、特征与反贫困政策措施:基于等值规模调整宋扬,赵君, 中国人民大学经济学院后的再分析黄英伟, 中国社会科学院经济研究所发展经济学收入来源、收入平等与集体效率:对中国集体制农户收入流动性的考察发展经济学经济增长和产业结构变迁——后工业社会中的一种新解叶提芳,葛翔宇, 中南财经政法大学法律与经济学知识产权纠纷解决行政偏好与企业创新激励苗妙,魏建, 山东大学经济研究院公共经济学―营改增‖的收入分配效应研究——收入和消费的双重视角葛玉御,田志伟, 山东大学经济学院公共经济学新农保、宗族网络与农村家庭代际转移范辰辰,李文, 山东大学经济学院公共经济学全面直管还是省内单列:省直管县改革的扩权模式选择宫汝凯、姚东旻,荣建欣, 东华大学,中央财经大学,上海财经大学公共经济学节能一定会抑制经济增长吗?——基于不同节能政策实施效程时雄,柳剑平, 湖北大学商学院果的考察公共经济学税制结构、税收低估与居民的再分配需求徐建斌, 华中科技大学管理学院陈力朋,刘华,徐建斌, 华中科技大学管理学院公共经济学税收凸显性对居民消费行为的影响——以个人所得税、消费税为例的经验分析公共经济学经济集聚、税收竞争与中国地方政府的税收努力程度邓明, 厦门大学财政系公共经济学优质义务教育的支付意愿:基于住宅租售比的实证估计张牧扬,石薇,陈杰, 上海财经大学公共经济与管理学院公共经济学中国增值税与营业税对城镇居民收入分配影响演变的分析田志伟,胡怡建, 上海财经大学公共经济与管理学院公共经济学村庄直接民主与农村居民幸福感职嘉男,陈前恒, 中国农业大学经济管理学院公共经济学公共支出政策如何影响社会信任:中国的微观经验陈思霞, 中南财经政法大学财政税务学院公共经济学保障性住房建设困境与土地财政——对城市层面数据的实证谭锐, 华南理工大学公共政策研究院研究管理经济学吃喝腐败、寻租与政府补贴申宇,陈震, 复旦大学金融学中国财产保险公司效率研究:新的方法和假说检验孙祁祥,边文龙,王向楠, 北京大学,中国社会科学院金融研究所国际经济学人民币汇率变动如何影响员工收入?徐建炜,戴觅, 北京师范大学经济与工商管理学院国际经济学环境规制、外商直接投资与中国省级出口竞争力沈国兵,张鑫, 复旦大学经济学院国际经济学贸易网络地位、自主研发能力与高端制造业技术扩散——基孙天阳,许和连,吴钢, 湖南大学经济与贸易学院于复杂网络的研究国际经济学国外最终需求对我国碳排放诱发效应及SDA分解肖皓,陈娅妮,汪寿阳, 湖南大学经济与贸易学院国际经济学企业家精神的国际溢出——来自FDI渠道的证据刘鹏程, 南开大学国际经济研究所国际经济学全球价值链重构与世界经济再平衡——基于全球生产分工的谭人友,葛顺奇, 南开大学国际经济研究所视角国际经济学全球价值链分工如何改变了贸易利益?李宏艳, 天津财经大学国际经济学对冲、金融约束与出口汇率弹性赵仲匡,李殊琦,杨汝岱, 武汉理工大学管理学院国际经济学南-北国际分割生产效应的模型分析杨永华, 云南师范大学国际经济学人民币汇率的进口价格传递效应:来自微观面板数据的证据黄滕,金雪军, 浙江大学经济学院国际经济学金融发展、融资约束与企业出口的三元边际杨连星, 中国人民大学经济学院国际经济学出口经验、路径依赖与企业出口的地理广化陈勇兵,李梦珊,赵羊,李冬阳, 中南财经政法大学国际经济学多产品进口企业、进口产品转换与企业生产率陈勇兵,赵羊, 中南财经政法大学行为经济学群体分类能否解决公共合作的囚徒困境难题?——来自公共品连洪泉,周业安,陈叶烽,叶航, 华南师范大学经济与管理学院实验的证据宏观经济学利益冲突下时间不一致性政策的理论建模及应用路继业, 东北财经大学郭凯,孙音,邢天才东北财经大学金融学院宏观经济学逻辑平滑转移机制、非线性货币政策规则与不确定性:基于逆序构建的NLRE模型的实证研究宏观经济学财政政策、异质性企业与中国城镇居民就业郭长林, 东北财经大学经济学院宏观经济学中国减排政策的经济增长效应和最优碳排放量研究程时雄,柳剑平, 湖北大学宏观经济学金融抑制与劳动收入份额——基于发展战略的视角张建武,王茜,林志帆,赵秋运, 华南师范大学经济与管理学院,北京大学光华管理学院宏观经济学劳动力成本上升、资产泡沫与中国经济波动郭念枝,村瀬英彰, 闽江学院公共经济学与金融学系宏观经济学结构变迁中市场与政府的贡献水平测度——基于中国工业企李晶, 南昌大学中国中部经济社会发展研业面板数据的实证分析究中心宏观经济学债务视角下的经济危机龚刚,徐文舸,杨光, 云南财经大学金融研究院,南开大学经济学院宏观经济学中国罕见灾难冲击与财政货币政策效应及最优货币政策规则袁靖, 厦门大学、山东工商学院统计学院选择的实证分析——基于贝叶斯DSGE模型宏观经济学公众预期对房价及宏观经济的动态影响研究许志伟, 上海交通大学安泰经济与管理学院宏观经济学什么决定了技术进步的方向?黎德福, 同济大学经济与管理学院.经济与金融系万晓莉, 西南财经大学宏观经济学房价预期、房屋资产与中国居民消费——基于总体和调研数据的证据宏观经济学房价波动对我国不同收入等级的城镇居民消费的影响——基张笑, 西南民族大学于省际动态面板数据的研究宏观经济学中国土地政策与经济波动何怡瑶, 浙江大学经济学院宏观经济学存款利率开放、经济结构调整与货币政策转型李宏瑾,洪浩, 中国人民银行营业管理部宏观经济学央行沟通、实际干预与货币政策效果的频域异质性林建浩,赵文庆, 中山大学岭南学院金融学政策差异对小额贷款公司发展的影响梁巧慧,胡金焱, 山东大学经济学院陈兴,成福玲, 山东大学经济研究院金融学股权集中与信贷约束——来自世界银行2012年中国企业调查问卷的实证研究金融学创业板上市公司的资本结构与绩效:来自公司治理的影响茹璟,薛娇娇,Ting Ren, 北大汇丰商学院金融学投资效率、公司治理和高管变更岑维,童娜琼,王京, 北京大学汇丰商学院金融学―政商旋转门‖—独立董事政治联系、政府补贴和企业经济社童娜琼,岑维,沈若琳, 北京大学汇丰商学院会效益金融学新基金进入的竞争效应研究冯旭南, 北京大学经济学院金融学晋升激励、考核机制与国有企业研发投入俞鸿琳, 对外经济贸易大学金融学融资流动性与系统性风险——来自中国银行业的经验吴卫星,蒋涛,吴锟, 对外经济贸易大学金融学院及应用金融研究中心金融学银行能够实施有效监督吗?——基于大股东掏空行为的研究张光利,刘轶,戚俊峰, 湖南大学金融与统计学院金融学经济周期、融资约束与资本结构非线性调整潜力,胡援成, 华东交通大学产业与金融研究院,江西财经大学金融发展与风险防范研究中心&金融管理国际研究院金融学利率市场化改革对企业借款价格的影响:趋势、效率和政策含钱雪松,杜立, 华中科技大学经济学院义金融学人民币安全溢价测算:2004-2012 范小云,郭步超,袁梦怡, 南开大学金融系金融学资本市场错误定价对我国上市公司并购活动的影响分析王璐清,何婧, 南开大学经济学院刘航,王勇, 清华大学社会科学学院金融学道德风险与银行再融资选择:为何资产证券化可以作为一种激励工具?金融学地区政治能量、地方IPO热潮与公司业绩逆转蔡庆丰,张浩,郭俊峰,郝凯, 厦门大学金融系何彦林,刘莉亚, 上海财经大学金融学院金融学生产潜力、市场择时、外国竞争与企业并购——基于中国企业国内并购与跨境并购的比较研究金融学早年灾害经历与金融风险态度异质性黄枫,孙世龙, 上海财经大学徐晓萍,张顺晨,敬静, 上海财经大学经济学院金融学院金融学同城VC可以更好地监督企业开展创新投入吗?——来自我国中小板上市公司的证据金融学企业创业板上市前为何引入私募股权投资者——基于发行成本及核准上市之间权衡的视角张子炜,李曜, 上海对外经贸大学金融管理学院金融学询价阶段机构投资者报价策略实证分析胡志强,姜雨杉, 武汉大学经济与管理学院金融学非线性相依结构、动态系统性风险测度与后验分析王锦阳,刘锡良,杜在超, 西南财经大学金融学一股独大不利于公司治理吗?——基于持股模式和两类治理成本的经验证据黄建欢,肖敏,尹筑嘉,湖南大学经济与贸易学院,长沙理工大学经济与管理学院金融学金融危机时期中国上市公司投资行为研究张小茜, 浙江大学金融学中国信贷供给周期的实际效果:基于公司层面的经验证据王义中,陈丽芳,宋敏, 浙江大学经济学院金融学担保公司与中小企业贷款—银行视角下的合谋还是合作?马松,潘珊,贾春新, 西南财经大学博士后科研流动站&中共成都市委政策研究室、北京大学光华管理学院经济学博士金融学中小企业主政治背景对担保费率及银行贷款条件的影响分析马松,潘珊,姚长辉, 西南财经大学博士后科研流动站&中共成都市委政策研究室、北京大学光华管理学院经济学博士徐欣, 中南财经政法大学金融学企业自主研发、IPO折价与创新能力的信号效应——基于中国创业板上市公司的实证研究金融学官员变更与资本市场发展罗党论,佘国满, 中山大学岭南学院金融学我国要素市场发展差异、企业性质与异地并购绩效姚益龙,刘巨松,刘冬妍, 中山大学岭南学院金融学企业创新来源:信贷市场还是股票市场?刘培森,尹希果,李后建, 重庆大学经济史战争的遗产:太平天国战争对近代人力资本影响的实证研究李楠,林矗, 上海财经大学经济史学系经济史历史冲击与发展:太平天国战争对经济发展长期影响李楠,林矗, 上海财经大学经济学院经济史学系经济学教育匿名审稿制度推动了中国的经济学进步吗?——基于双重差刘瑞明,赵仁杰, 西北大学经济管理学院分方法的研究劳动、人口经济学高校扩招如何影响教育溢价?马光荣,纪洋,徐建炜, 北京大学国家发展研究院劳动、人口经济学最低工资标准与农民工收入不平等叶静怡,杨洋, 北京大学经济学院劳动、人口经济学我国遗产继承与财产不平等分析詹鹏,吴珊珊, 北京师范大学经济与工商管理学院劳动、人口经济学金融知识、创业决策和创业动机尹志超,宋全云,吴雨,彭嫦燕, 成都西南财经大学经济与管理研究院劳动、人口经济学中国代际教育流动性的水平与趋势:基于多种方法的测度潘春阳,吴柏均, 华东理工大学商学院劳动、人口经济学政府干预、投资品相对价格与劳动收入份额——基于徐蔓华,赖艳,赵秋运, 华南师范大学, 北京大学光华管理1993-2012年省级面板数据的实证分析学院劳动、人口经济学融资约束、企业储蓄和劳动收入份额:基于中国经济转型的发现赵秋运,魏下海,马晶,林志帆, 北京大学光华管理学院、华南师范大学经济与管理学院劳动、人口经济学社会关系网、朋友圈效应与农民工收入王春超,张呈磊,周先波, 暨南大学经济学院,中山大学岭南学院劳动、人口经济学自我雇佣有利于农村外出劳动力市民化吗?—来自RUMiCI2009的证据宁光杰, 南开大学经济学系劳动、人口经济学动态死亡率模糊性对生育决策的影响研究汪丽萍,朱文革, 上海财经大学劳动、人口经济学外出务工,心理健康及自选择性--基于反事实分布的分析傅伟, 上海财经大学经济学院劳动、人口经济学高校扩招降低了大学教育回报率了吗蔡海静,马汴京, 浙江财经大学劳动、人口经济学子女性别和父母幸福感刘国恩,陆方文, 中国人民大学大学劳动、人口经济学计划生育损害中国的企业家精神么?孙文凯, 中国人民大学经济学院劳动、人口经济学―人的城镇化‖:文化距离与社会融合徐现祥,刘毓芸,肖泽凯, 中山大学岭南(大学)学院农业经济学要素丰裕度、技术进步偏向性与中国农业部门劳动收入份额王林辉,袁礼,国胜铁, 华东师范大学商学院,东北师范大学经济学院农业经济学农地流转、土地规模与农户信贷约束——来自江苏的经验证据黄惠春, 南京农业大学金融学院农业经济学关税减让、汇率升值与农户福利——价格传导视角张腾飞,朱晶, 南京农业大学经济管理学院农业经济学―一家两制‖:对农户模型理论的拓展于泽洋,周立, 香港科技大学社会科学部农业经济学农户土地承包经营权抵押及贷款可得性研究余新平,熊德平, 浙江大学中国农村发展研究院,宁波大学商学院农业经济学农户参保行为的影响因素研究——以玉米种植户为例张崇尚,吕开宇, 中国农业科学院农业经济与发展研究所肖卫东, 山东师范大学公共管理学院农业经济学中国农业地理集聚的影响因素:一个理论框架及其空间计量经济分析农业经济学资源禀赋、结构差异与中国农产品贸易的决定乔长涛,王丹, 中南财经政法大学工商管理学院,碳排放权交易湖北省协同创新中心区域经济学集聚经济是工资差距的来源吗?——基于制造业企业的实证吴晓怡,邵军, 东南大学经济管理学院研究区域经济学从外太空看中国省区经济趋同王贤彬,黄亮雄,徐现祥, 广东外语外贸大学国际经济贸易学院区域经济学城市规模、中间产品与异质厂商生产率赵曜,柯善咨, 湖南大学经济与贸易学院区域经济学知识产权保护、人力资本结构与企业自主创新强度张望, 南京农业大学经济管理学院区域经济学实际政治权力结构与地方经济增长:中国革命战争的长期影响李飞跃,张冬,刘明兴, 南开大学经济学院国经系区域经济学边界效应、国内市场一体化与区域壁垒何雄浪, 西南民族大学区域经济学价格差异、市场分割与中国省际边界效应—基于断点回归方法的实证分析黄新飞,陈珊珊,世界经济研究中国出口增长实现以质取胜了吗?刘瑶, 东北财经大学数理经济与计量经济学空间面板数据模型Bootstrap LM-Error检验研究任通先,龙志和,陈青青,林光平,华南理工大学经济与贸易学院数理经济与计量经济学住宅投资、要素投入与区域经济增长:半参数非线性空间计量分析吴玉鸣,微观经济学距离、信息和贷款定价--基于中国上市公司委托贷款公告数据钱雪松,金芳吉, 华中科技大学经济学院的经验分析张博,胡金焱,范辰辰, 山东大学经济学院微观经济学社会网络、信息获取与家庭创业收入——基于中国城乡差异视角的实证研究顾海,马超,宋泽, 东南大学公共卫生学院卫生经济学医保统筹制度对促进城乡居民医疗服务利用和健康实质公平的探讨卫生经济学住房拥挤、小孩健康和学习成绩温兴祥, 西南财经大学经济与管理研究院政治经济学市场、社会行动与最低工资制度:基于新政治经济学的视角叶静怡,赵奎,方敏, 北京大学经济学院政治经济学过度自信、官员异质性与地方经济增长万欣,张克中,马媛媛, 华中科技大学管理学院政治经济学作为社会契约的合作社:应用Ramsay模型理解合作社原则许建明, 厦门大学经济研究所制度经济学制度结构变迁的内生性理论黄少安,韦倩,杨友才, 山东大学经济研究院制度经济学国家结构、特授权力与中国转型韩忠亮, 北京大学经济学院制度经济学双重金融压制、外源融资错位与企业技术创新*——为什么我国金融系统存在创新产出的低效率?刘政, 昆明理工大学管理与经济学院制度经济学异质性文化资本、适度规模与创新效率李娟伟,任保平,刚翠翠, 陕西师范大学国际商学院中国经济改革城镇化模式选择、生产性服务业集聚与居民消费汤向俊, 江苏科技大学发展经济学中国产业的结构调整与劳动力配置--基于比较利益相等的理论解释江永基,蔡继明, 厦门大学经济学院,清华大学政治经济学研究中心资源与环境经济学转型期间中国电力体制改革的绩效评估:1999-2010 宫汝凯,王大中, 东华大学,上海财经大学资源与环境经济学FDI提升还是降低了中国环境规制?——―污染天堂‖假说的新李子豪,陈鑫, 河南财经政法大学国际经济与贸易检验学院,湖南大学经济与贸易学院资源与环境经济学中国工业废气污染物影子价格测度及影响因素分析程时雄,柳剑平, 湖北大学商学院刘建民,陈霞, 湖南大学资源与环境经济学财政分权对环境污染的非线性效应——基于中国272个地级市PSTR模型分析资源与环境经济学政府鼓励企业节能的最优激励契约及其政策传导机制甘兴,张汉江,赖明勇, 湖南大学经济与贸易学院资源与环境经济学城市经济结构、技术外部性与土地集约利用彭冲,金培振,李玉双, 湖南大学经济与贸易学院资源与环境经济学环境政策激励和技术进步方向转变李多,董直庆, 吉林大学商学院资源与环境经济学低碳技术下边际减排成本与工业经济的双赢杜敏哲,王兵, 暨南大学经济学院资源与环境经济学分权、寻租与―资源诅咒‖——理论分析与中国省际地区的经验邓明, 厦门大学财政系依据*资源与环境经济学过犹不及的资源―红利‖:资源依赖对经济增长的门槛效应邵帅,杨莉莉, 上海财经大学资源与环境经济学我国环境规制改革缓解了省际边界污染问题吗?林立国,孙韦, 上海财经大学经济学院资源与环境经济学资本深化、经济结构变迁与二氧化碳排放黄晓芬, 上海市发展改革研究院资源与环境经济学中国产业结构变迁对能源效率影响的实证分析吕明元,陈维宣, 天津商业大学经济学院周晨,李国平, 西安交通大学经济与金融学院资源与环境经济学流域生态补偿中的居民支付意愿及其影响因素分析——以南水北调中线工程为例资源与环境经济学流域生态补偿中的农户受偿意愿研究——以南水北调中线工周晨,丁晓辉,李国平, 西安交通大学经济与金融学院程陕南水源区为例资源与环境经济学我国环境规制对技术进步的影响:基于工业行业的实证检验师美妮,岳利萍, 西北大学经济管理学院资源与环境经济学中国工业碳排放效率评估:基于物质平衡原则袁鹏, 西南财经大学工商管理学院。

计量经济学中英文词汇对照

计量经济学中英文词汇对照

Common variance Common variation Communality variance Comparability Comparison of bathes Comparison value Compartment model Compassion Complement of an event Complete association Complete dissociation Complete statistics Completely randomized design Composite event Composite events Concavity Conditional expectation Conditional likelihood Conditional probability Conditionally linear Confidence interval Confidence limit Confidence lower limit Confidence upper limit Confirmatory Factor Analysis Confirmatory research Confounding factor Conjoint Consistency Consistency check Consistent asymptotically normal estimate Consistent estimate Constrained nonlinear regression Constraint Contaminated distribution Contaminated Gausssian Contaminated normal distribution Contamination Contamination model Contingency table Contour Contribution rate Control

汉语国际教育专业英文术语

汉语国际教育专业英文术语

汉语国际教育专业英文术语The field of Chinese international education has seen a significant growth in recent years, with the increasing global demand for the Chinese language and culture. As the world becomes more interconnected, the need for effective communication and understanding across cultures has become increasingly important. This has led to the development of a specialized vocabulary, or terminology, that is essential for professionals working in the field of Chinese international education.One of the key terms in this field is "Mandarin Chinese," which refers to the standard form of the Chinese language. Mandarin Chinese is the most widely spoken language in China and is also the official language of the country. It is a tonal language, meaning that the same sequence of sounds can have different meanings depending on the tone used. This can be a challenge for non-native speakers, who must learn to recognize and reproduce the correct tones in order to communicate effectively.Another important term in Chinese international education is "Chinese as a Foreign Language (CFL)." This refers to the teaching and learning of the Chinese language by individuals whose nativelanguage is not Chinese. CFL programs are designed to help non-native speakers develop proficiency in the language, with a focus on practical communication skills. These programs often include instruction in Chinese grammar, vocabulary, and cultural norms, as well as opportunities for students to practice their language skills through activities and interactions.The term "Chinese as a Second Language (CSL)" is also commonly used in the field of Chinese international education. This term refers to the teaching and learning of Chinese by individuals who already have a primary or native language. CSL programs are often designed for individuals who need to learn Chinese for professional or academic purposes, such as students studying in China or business professionals working with Chinese companies.Another key term in Chinese international education is "Chinese Language Proficiency Test (HSK)." The HSK is a standardized Chinese language proficiency test that is administered by the Chinese government. The test is designed to assess an individual's ability to use the Chinese language in a variety of contexts, and it is widely recognized as a measure of language proficiency both within China and internationally.In addition to these core terms, there are also a number of other specialized terms and concepts that are important in the field ofChinese international education. These include "Chinese cultural studies," which refers to the study of Chinese history, literature, art, and other aspects of Chinese culture; "Chinese language pedagogy," which focuses on the methods and approaches used to teach the Chinese language; and "Chinese language teacher training," which encompasses the education and professional development of individuals who teach Chinese as a foreign or second language.Overall, the field of Chinese international education is a dynamic and evolving field that requires a deep understanding of the language, culture, and educational systems of China. The specialized terminology used in this field reflects the complexity and diversity of the subject matter, and it is essential for professionals working in this field to be familiar with these terms in order to effectively communicate and collaborate with their colleagues and students.。

上大学的好处 英语作文

上大学的好处 英语作文

Attending university is a significant milestone in many individuals lives,offering a wealth of opportunities and experiences that can shape ones future.Here are some of the key benefits of pursuing higher education:1.Academic Growth:University provides a platform for deep academic exploration. Students have the chance to specialize in a field of interest,gaining a comprehensive understanding of their chosen subject through rigorous coursework and research.2.Skill Development:Beyond book knowledge,universities equip students with critical thinking,problemsolving,and communication skills.These are essential competencies in the modern workforce and are often honed through group projects,presentations,and discussions.working Opportunities:The university environment is a melting pot of diverse individuals from various backgrounds.This diversity fosters a rich networking experience,allowing students to build relationships that can be beneficial for future career prospects and personal growth.4.Cultural Exposure:Universities often host international students and faculty,providinga window into different cultures and perspectives.This exposure can broaden ones worldview and foster a greater appreciation for diversity.5.Personal Development:The university years are a time of selfdiscovery and personal growth.Living away from home,managing finances,and making independent decisions are all part of the university experience that contribute to a students maturity and selfreliance.6.Career Advancement:A university degree is often a stepping stone to a successful career.It can open doors to job opportunities that may not be accessible without higher education.Additionally,many industries require specialized knowledge that can only be obtained through university study.7.Research Opportunities:For those interested in academia or research,universities offer unparalleled access to resources and mentorship.Engaging in research projects can lead to a deeper understanding of a subject and can be a stepping stone to a career in academia or research and development.8.Financial Benefits:While the initial cost of university education can be high,the longterm financial benefits often outweigh the costs.Higher education is associated with higher lifetime earnings and increased job security.9.Lifelong Learning:The pursuit of a university degree instills a habit of lifelong learning.The skills and knowledge gained at university can be continuously applied and expanded upon throughout ones career.10.Social Impact:Many university graduates go on to make significant contributions to society,whether through their professional work,community service,or by becoming leaders in their fields.In conclusion,the benefits of attending university extend far beyond the academic realm. They encompass personal growth,career opportunities,and the chance to make a meaningful impact on the world.For many,the university experience is a transformative journey that sets the foundation for a fulfilling life and career.。

硕士学位论文-中英立法语言中模糊限制语的对比研究

硕士学位论文-中英立法语言中模糊限制语的对比研究

A Contrastive Analysis of HedgesIn Chinese and English Legislative Languages 中英立法语言中模糊限制语的对比研究By Hao ChangxiaUnder the Supervision ofProfessor Zhang YimingA Thesis Submitted to the College of Foreign Languages ofShanghai Maritime UniversityIn Partial Fulfillment ofThe Requirements for the MA DegreeShanghai Maritime UniversityMay 10th, 2009AcknowledgementsFirst, I would like to thank my supervisor, Professor Zhang Yiming in Shanghai Maritime University, who inspired and encouraged me throughout the writing of the present thesis. The completion of the thesis could never have been possible without his precious guidance and constructive suggestions.Second, I would also like to express my deepest gratitude to my boyfriend, who was always ready to give me his opinions and support. He taught me how to make good use of the computer software tools with great patience, which was a very great help for me, especially when making the quantitative analysis of the data during the research of the present thesis.Last but not least, I would like to thank all my roommates, with whom I share the pain and pleasure of writing the thesis. It helped me ease the stress during the writing and keep a good mood so as to finish the present thesis smoothly.ABSTRACTAccuracy and preciseness is always regarded as the soul of the legislative language and people believes that legislative language is clear and precise all the time. While research findings after the birth of fuzzy linguistics show that, vague words or phrases could also be found in this kind of language. This paper is written exactly based on such findings.Since vague language is a big family. This paper chooses hedges, a member of the vague language family, as the research focus to make a contrastive analysis on how they are used in both the English and Chinese legislative languages. And the corpora in English and Chinese are Labor Regulation of Washington State and Labor Law of PRC respectively.This paper consists of three parts. Chapters one to three is the first part, which gives a brief view of the whole thesis, reviews the past researches on hedges both at home and abroad, and presents the theoretic framework for analysis.Chapters four to five is the second part, which first studies what kind of hedges are used in the corpora and their distribution based on Prince et al‟s taxonomy, then researches the various linguistic realizations of hedges by means of Channel‟s categories of approximators and the pragmatic functions through the Cooperative Principle of Grice, and finally carries out a contrastive analysis of hedges used in the English and Chinese legislative language in order to find and conclude some similarities as well as differences.And chapter six is the third part, which summarizes the whole thesis, shows the limitations and also presents suggestions for further studies.Keyword: Hedges, Legislative language, Contrastive Analysis摘要清晰准确一直被视为立法语言的灵魂,人们历来认为立法语言应当准确明了地表达事物。

英汉对照计量经济学术语

英汉对照计量经济学术语

英汉对照计量经济学术语A校正R2〔Adjusted R-Squared〕:多元回归剖析中拟合优度的量度,在估量误差的方差时对添加的解释变量用一个自在度来调整。

统一假定〔Alternative Hypothesis〕:检验虚拟假定时的相对假定。

AR〔1〕序列相关〔AR(1) Serial Correlation〕:时间序列回归模型中的误差遵照AR〔1〕模型。

渐近置信区间〔Asymptotic Confidence Interval〕:大样本容量下近似成立的置信区间。

渐近正态性〔Asymptotic Normality〕:适当正态化后样本散布收敛到规范正态散布的估量量。

渐近性质〔Asymptotic Properties〕:当样本容量有限增长时适用的估量量和检验统计量性质。

渐近规范误〔Asymptotic Standard Error〕:大样本下失效的规范误。

渐近t 统计量〔Asymptotic t Statistic〕:大样本下近似听从规范正态散布的t 统计量。

渐近方差〔Asymptotic Variance〕:为了取得渐近规范正态散布,我们必需用以除估量量的平方值。

渐近有效〔Asymptotically Efficient〕:关于听从渐近正态散布的分歧性估量量,有最小渐近方差的估计量。

渐近不相关〔Asymptotically Uncorrelated〕:时间序列进程中,随着两个时点上的随机变量的时间距离添加,它们之间的相关趋于零。

衰减偏误〔Attenuation Bias〕:总是朝向零的估量量偏误,因此有衰减偏误的估量量的希冀值小于参数的相对值。

自回归条件异方差性〔Autoregressive Conditional Heteroskedasticity, ARCH〕:静态异方差性模型,即给定过去信息,误差项的方差线性依赖于过去的误差的平方。

一阶自回归进程[AR〔1〕]〔Autoregressive Process of Order One [AR(1)]〕:一个时间序列模型,其以后值线性依赖于最近的值加上一个无法预测的扰动。

上大学的优点英语作文

上大学的优点英语作文

上大学的优点英语作文Attending university offers a multitude of benefits that can significantly impact an individuals personal and professional life. Here are some of the key advantages of pursuing higher education1. Academic Growth University education provides a comprehensive and indepth understanding of a chosen field. It allows students to specialize in their area of interest and gain expertise through rigorous academic training.2. Critical Thinking and Problem Solving Higher education encourages students to think critically and analytically. It equips them with the skills to approach problems from multiple perspectives and develop innovative solutions.3. Access to Resources Universities are hubs of knowledge offering access to extensive libraries research facilities and technological resources that can enhance learning and research capabilities.4. Networking Opportunities Attending university provides the chance to meet and interact with a diverse group of individuals including fellow students professors and industry professionals. These connections can be invaluable for future collaborations and career opportunities.5. Personal Development Living away from home and being part of a university community can foster independence and personal growth. Students learn to manage their time finances and responsibilities which are crucial life skills.6. Career Advancement A university degree is often a prerequisite for many professional positions. Higher education can open doors to better job prospects and higher earning potential.7. Cultural Exposure Universities often host cultural events guest lectures and international exchange programs providing students with a broader understanding of the world and its diverse cultures.8. Research Opportunities For those interested in academia or research universities offer the chance to participate in cuttingedge research projects which can lead to significant contributions to their field.9. Skill Development Beyond the classroom universities offer various extracurricular activities and clubs that can help students develop a range of skills such as leadership teamwork and public speaking.10. Lifelong Learning The pursuit of higher education instills a habit of lifelong learning. Graduates are more likely to continue seeking knowledge and adapting to new information throughout their careers.In conclusion attending university is not just about obtaining a degree its an investment in ones intellectual and personal development. It provides a solid foundation for a successful career and a fulfilling life.。

Cluster-based industrialization in China Financing and performance

Cluster-based industrialization in China Financing and performance

Cluster-based industrialization in China:Financing and performanceCheryl Long a ,Xiaobo Zhang b ,⁎a Colgate University,United StatesbInternational Food Policy Research Institute,Development Strategy and Governance Division,United Statesa b s t r a c ta r t i c l e i n f o Article history:Received 31January 2010Received in revised form 25February 2011Accepted 1March 2011Available online 6March 2011JEL classi fication:D24G10L11O14O16Keywords:ClusteringIndustrialization Finance ExportProductivity ChinaChina's rapid industrialization despite the lack of a well developed financial system seems to defy the conventional thinking on the role of finance in development.This paper tries to explain the puzzle from the clustering point of view.Based on firm-level data from two recent censuses,we find that within industrial clusters:finer division of labor lowers the capital barriers to entry;closer proximity makes the provision of trade credit among firms easier.With less reliance on external financing,more small firms emerge within clusters,leading to higher levels of export and total factor productivity thanks to the resultant more fierce competition.©2011Elsevier B.V.All rights reserved.1.IntroductionMany have argued that a well-developed financial system is a key prerequisite for industrial development,as it can help pool disparate savings to finance large lump-sum investments in machinery and factory buildings (Goldsmith,1969;McKinnon,1973;King and Levine,1993;Rajan and Zingales,1998).However,China's rapid industrialization over the past three decades seems to defy the conventional wisdom.At the incipient stage of reform in the late 1970s,China's financial system was far from developed by any existing standards (Allen et al.,2005).In particular,the vast number of privately-owned small and medium enterprises (SMEs)had little access to formal credit from state-owned banks (Lin and Li,2001).Despite the initial lack of financial development,China has achieved in three decades the same degree of industrialization that took two centuries to occur in Europe (Summers,2007).And the rapid growth in the private sector has been a de fining feature of China's growth patterns (Song et al.,2011).How was the vast number of SMEs able to emerge and quickly grow in such a credit-constrained environment?Without denying the importance of formal financing and informal mechanisms of alternative financing (as pointed out in Allen et al.,2005;Fisman and Love,2003)in overcoming credit constraints,we argue herein that the cost of investment in production technologies may not be as prohibitive as suggested in the literature thanks to the clustering mode of production.By dividing an integrated production process into many incremental steps,clustering can lower capital entry barriers,thereby enabling more entrepreneurs to participate in nonfarm production.The closer proximity of firms in a cluster also allows more inter-firm trade credit and thus reduces the need for working capital.As has been reported in the media,China's rapid industrialization in the past several decades has been accompanied by the emergence of numerous “specialty cities ”of a particular kind,where thousands of firms,large and small,each specializing in a finely de fined production step,are lumped together in a densely populated region to churn out some particular manufactured consumer good by the millions (if not billions)annually.1Despite the numerous popular media reports of this phenomenon,few studies have been performed to rigorously establish patterns usingJournal of International Economics 84(2011)112–123⁎Corresponding author.E-mail addresses:Cxlong@ (C.Long),X.Zhang@ (X.Zhang).1For example,see /2004/12/24/business/worldbusiness/24china.html for a New York Times report.Many formerly rural towns in the coastal areas have become so specialized that they boast of themselves as the world's Socks City,Sweater City,Kid's Clothing City,Footwear Capital,and soon.0022-1996/$–see front matter ©2011Elsevier B.V.All rights reserved.doi:10.1016/j.jinteco.2011.03.002Contents lists available at ScienceDirectJournal of International Economicsj ou r n a l h o m e pa ge :ww w.e l s ev i e r.c o m/l o c a t e /j i edata covering a large sample and a long time period.2Toward this end, we use completefirm-level data from the China Industrial Census1995 (China,National Bureau of Statistics,1995)and the China Economic Census2004(China,National Bureau of Statistics,2004)to compute measures of clustering.We use industry proximity measure to explore howfirms interact with one another,which is a key feature of clustering as highlighted by Porter(1998,2000).Our results suggest that China's rapid industrialization during this time period was marked by increased clustering—closer interactions amongfirms within the same region.We then examine the role of clustering onfirmfinancing.At the county level,we calculate both clustering measures and the minimum asset level among allfirms andfind that clustering is associated with lower minimum capital requirements for industrial investment.Next, based on a panel dataset at thefirm level from the two censuses in 1995and2004,we document that clustering is accompanied by a more prevalent use of trade credit amongfirms,thus reducing their reliance on externalfinancing for working capital.We further show that that clustering would help create more new establishments and result in extensive industrial growth.The emergence of domestic non-state establishments in a location is found to be highly associated with the degree of local industrial clustering.As a placebo test,the number of state-owned enterprises (SOEs),which are notfinancially constrained and thus should not be affected by clustering,is not related to the degree of clustering at all.Finally,wefind that clustering also boosts intensive growth—improvingfirm productivity through increased competition among similarfirms.Domestic non-statefirms in more clustered regions have higher export and total factor productivity(TFP)levels,while clustering has little to do with the performance of SOEs.The study of China's industrialization may also be useful for the research on industrialization in general.China's miraculously rapid industrialization provides a unique laboratory enabling us to observe and understand the process of industrialization.While industrialization in Western Europe and North America at the early stages of the Industrial Revolution can now be studied only through the relatively dim mirror of history,industrialization can be viewed directly in the ongoing economic revolution in China.China's experience may be relevant to other developing countries characterized by a high population density and a low capital-to-labor ratio.A clearer understanding of the industrializa-tion processes in China will be of great value in helping propagate these processes to the world's less fortunate regions.2.Literature review on clustering,finance,and industrial developmentOur study is closely related to two threads of literature.Thefirst relevant body of literature is onfinance and industrial growth. Because of the high cost to build up a factory and purchase machinery, in the absence of a well developed capital market,it would be hard for many potential entrepreneurs with limitedfinancial resources to start their own businesses(Banerjee and Newman,1993).Therefore,financial development is regarded as havingfirst-order importance in promoting economic growth(King and Levine,1993).In an influential empirical paper,Rajan and Zingales(1998)show thatfirms in industrial sectors relying heavily on externalfinance grow faster in countries with more developedfinancial markets, suggesting thatfinancial development can help reducefirms'costs of externalfinance.However,the lack of a well-functioning capital market is common in developing countries.In the case of China,Allen et al.(2005)has suggested the reliance on informalfinancing–such as borrowing from family members,relatives, and friends–as the main solution.However,considering that at the onset of China's reform a large proportion of rural people were poor (Ravallion and Chen,2007),the amount of local savings available for informalfinancing would have been rather limited.Another alternative is forfirms to rely on suppliers in the form of trade credit as an alternative source of funds(Fisman and Love,2003).Yet despite the positive role of trade credit in easing working capital constraints,it alone does not explain how capital entry barriers can be overcome because many entrepreneurs also lack starting capital to set up their businesses.Our study is also related to the literature on industrial clustering. Industrialization is often accompanied by clustering(or spatial agglomeration)of industrial activities.3Italy,Japan,and other East Asian countries and regions have all experienced a path of spatial clustering during the course of industrialization,which was led by small and medium enterprises(SMEs).One noted example is the popular putting-out system in the U.K.prior to its Industrial Revolution,in which a merchant obtained market orders and subcontracted the production to nearby farmers or skilled workers, who usuallyfinished the work in their homes or family workshops (Hounshell,1984).Outsourcing(or subcontracting),the modern variant of the traditional putting-out system,remains a major feature of industrial production organization in contemporary Japan and Taiwan(Sonobe and Otsuka,2006).Industrial districts in which different workshops and factories clustered together were ubiquitous in France and Italy until the mid-twentieth century and are still viable in some regions of Italy(Piore and Sabel,1984;Porter,1998).The literature on clustering has highlighted at least three key positive externalities of industrial clusters:better access to the market and suppliers,labor pooling,and easyflow of technology know-how (Marshall,1920).Glaeser and Gottlieb(2009)emphasize the role of agglomeration in speeding theflow of ideas.With these positive externalities,Porter(1998)argues that clustering is an important way forfirms to fulfill their competitive advantage.Ciccone and Hall (1996)and Ciccone(2002)have empirically shown that agglomer-ation is positively associated with productivity at the local geograph-ical level in the US and Europe.We argue in this paper that another main advantage of clustering in developing countries with limitedfinancial development is in helping firms alleviatefinancial constraints,a point that has not been previously discussed except in several case studies.One key feature of industrial clustering observed in China is that an integrated production process is disaggregated into many small steps that are performed by a large number of smallfirms.By dividing a production process into incremental stages,a large lump-sum investment can be transformed into many small steps(Schmitz,1995).Based on a case study on cashmere sweater cluster,Ruan and Zhang(2009)empirically show that clustering enables many farmers with entrepreneurial talents to move into industrial production by lowering capital entry barriers. Furthermore,as an integrated production is split up among manyfirms in a narrow geographic area,thesefirms have to interact repeatedly on a regular basis.Over time,firms build up trust with their customers and suppliers within the cluster,which in turn lowers transaction costs of extending and receiving trade credit amongfirms,easing their burden of financing for working capital.Huang et al.(2008)and Ruan and Zhang (2009)provide supporting evidence that trade credit is indeed prevalent in footwear and cashmere clusters in China.To test whether thefinancing effects of clustering described in these case studies still hold up in a broader context,we will resort to a more rigorous analysis using a large sample in this paper.By linking the literature onfinance and growth and on clustering,our paper also attempts to offer an explanation to China's growth puzzle.2Lu and Tao(2009)found a clear trend of industrial agglomeration during the period of1998–2005.But their sample includes only largefirms and does not capture the large number of small and mediumfirms prevalent in these“specialty cities”.3In the literature,various terms for the phenomenon of clustering abound, including spatial agglomeration,industrial district,cluster,industrial concentration,and so on.In this paper,we prefer to use cluster,as it better captures the interconnected-ness amongfirms in a narrowly concentrated location.113C.Long,X.Zhang/Journal of International Economics84(2011)112–1233.Data,proximity measure,and patterns of China's industrializationWe utilizefirm-level data from the China Industrial Census1995 and China Economic Census2004for analysis in this pared to datasets used in previous studies on China's industrialization patterns(Young,2000;Bai et al.,2004;Wen,2004;Zhang and Tan, 2007;Lu and Tao,2009),our datasets have more comprehensive coverage in both time and the number offirms—spanning a time period of10years and including industrialfirms of all sizes(not only those above a certain scale).Conventional measures of industrial agglomeration are based on regional specialization or industrial concentration.The market share of a certain number of the largest,say,threefirms,in an industry or region is often used as a concentration measure.The advantage of this measure is that it is easy to calculate and interpret,but when the distribution offirms is relatively spread out,it may miss thosefirms below the cut-off lines.To overcome this problem,the Gini coefficient is often used to calculate the regional variation of output or employment shares for all thefirms in an industry.Krugman(1991) modifies the Gini coefficient by accounting for the discrepancy between a region's share of output/employment in a certain industry and its share in all manufacturing industries in calculating the Gini coefficient.However,these concentration measures do not distinguish between the following two kinds of“agglomeration”:one in which a small number of largefirms with minimum inter-firm connections are located,versus the other in which a large number of variously sizedfirms congregate and interact closely with one another.While thefirst type of agglomeration characterizes cities such as Detroit,the second type of agglomeration seems to betterfit the patterns observed in coastal China,where thousands offirms of all sizes are densely populated in a small region,closely intertwined with one another throughout the production processes,all the while churning out thousands of products with breathtaking efficiency.The second type of agglomerationfits very well into the definition of clusters given by Porter,whose concept of an industrial cluster is summarized as“a geographically proximate group of inter-connected companies(and associated institutions)in a particularfield”(Porter, 2000,page16).Although the concept is intuitive and extremely easy to understand,the measurement of interconnectedness seems more elusive.To our knowledge,no previous studies have directly measured it except in case studies in whichfirms can provide detailed information on how they interact with otherfirms.Such detailed information is necessarily absent for large-scale studies like ours.In the absence of thefirst-best information,we analyze Porter's concept of clustering more carefully to explore alternative ways of measuring interconnectedness amongfirms. When delineating the main actors within a cluster,Porter states,“They include,for example,suppliers of specialized inputs such as components,machinery,and services as well as providers of specialized infrastructure.Clusters also often extend downstream to channels or customers and laterally to manufacturers of complementary products or companies related by skills,technologies,or common inputs”(Porter, 2000,16–17,italics added by authors).In addition,Porter emphasizes that one main benefit derived from geographically concentrated clusters is that industries in the same cluster share common technologies,skills,knowledge,inputs,and institutions.Previous work has also shown that technology linkages among related industries are an important engine for innovation(Scherer,1982; Feldman and Audresch,1999).The works cited above suggest one way to measure interconnec-tedness as envisioned in the cluster concept by Porter.If industries andfirms produce similar goods,then they are more likely to use similar combinations of inputs in their production processes,and more likely to rely on the same set of suppliers and clients,and thus are more likely to be interconnected through skills,technologies,and other common inputs.The similarity among products of industries can thus be used as a measure for clustering,as defined by Porter.New results obtained by Hausmann and Klinger(2006)allow us to implement the above measure of interconnectedness among indus-tries(and participatingfirms)in a cluster.Hausmann and Klinger (2006)constructed a proximity matrix for all four-digit SITC products, in which the proximity between any two goods captures their similarity in the following sense:if the two goods need the same combination of inputs(or endowments and capabilities)to produce, then there is a higher probability that a country has a comparative advantage in both,and the two products are more likely to be both exported.In other words,the proximity between each pair of goods can be computed as the probability that a country has net exports in both(averaged over all countries in the world).4It follows thatfirms and industries that produce products with a higher proximity are more likely to interact with one another in various ways,including dependence on similar inputs(be they raw materials,labor,or machinery),reliance on similar technologies and research and development,and even dependence on the same supply or marketing facilities.Thus,those industries producing commodities that are more proximate in the Hausmann–Klinger space are likely to be more interconnected in the Porter sense.As a result,this proximity measure can be used to provide a gage for how closely interconnected industries and their participatingfirms are within a specific region.To implement the idea of measuring interconnectedness among firms using product proximity,we follow the procedures below5:(1) Aggregatefirm level output,asset,and employment to the cell level, where the cell is defined as a combination of county and a four-digit CIC industry.(2)Convert the CICfirst to ISIC and then to SITC based on the manuals obtained from China's National Bureau of Statistics as well as correspondence tables from Eurostat and the United Nations.(3)For each industry in a cell,calculate its average proximity to all industries located in the same region,using the Hausmann–Klinger product proximity matrix,which gives the proximity(or the inverse distance)between each pair of products(and between each pair of industries through the conversion procedures in(2)above).The average proximity for each industry(for a certain region)is computed as a weighted average using the size of the other industry in each pair as the weight.(4)Finally,the average industry proximity for each region is computed as the average of the proximities of all the industries in that region,weighted by the size of each industry.The proximity measure can be based on assets,employment,or output,as the weights discussed above that are used to adjust for the size of each industry can be assets,employment,or output.We use all these measures,as they reflect different kinds of interconnectedness and thus measure different effects of clustering.Although likely to contribute to all three of these advantages as outlined by Marshall, output-weighted proximity is probably more conducive to techno-logical spillovers,since the output can be used as input in the production of other industries in the same region,while employment-weighted proximity implies more labor-market pooling,and asset-weighted proximity implies more specialized supplies,especially in capital goods.All these effects of agglomeration will lead to higher productivity at thefirm level.In addition,we emphasize in this paper another effect of agglom-eration that has not drawn enough attention previously,namely,its impact onfirmfinances.Asfinancial transactions permeate the whole production process,including labor hiring,asset purchasing,and product sales,we expect all three measures of proximity to play a role in helping overcomefirms'financial constraints.4For a more detailed discussion on how the Hausmann–Klinger proximity matrix is constructed and what advantages it has in measuring industry clustering,see Long and Zhang(2010).5For more details on constructing these measures,see Long and Zhang(2010).114 C.Long,X.Zhang/Journal of International Economics84(2011)112–123Using the proximity measures described above,we found that clustering among Chinese industries increased signi ficantly between 1995and 2004.6Table 1presents the industry proximity measures in 1995and 2004weighted by asset,employment and output at the county level,showing that the measures have increased signi ficantly during this period.7The measures constructed at the prefecture and the provincial levels give the same pattern of higher average industry proximity in each region in the latter year (Long and Zhang,2010).Finally,compared to the conventional measures,the proximity measures fare much better in accurately re flecting the clustering patterns observed in reality.By 2004,the coastal regions were boasting of some well-known industrial clusters in China.Examples include Shanghai (with clusters in re fined steel,petroleum,general and special purpose equipment,and automobile),Zhejiang (with clusters in textile,shoes,apparel,electrical appliances,and electronic and telecommunications equipment),and Guangdong (with clusters in textile,apparel,electronics,and computers and related products).Consistent with this pattern,Li and Fung Research Center (2006)report 23well known industrial clusters at the prefecture level in China,all located in the Coast.We thus divide Chinese prefectures into two groups —the prefectures with well known industrial clusters reported by Li and Fung Research Center (2006)and those without the above mentioned industrial clusters.On average,the proximity measure (be it weighted by output,asset,or employment)is signi ficantly higher for the prefectures with industrial clusters than that for prefectures without clusters.In contrast,when the conven-tional measures (the concentration ratio,the Gini Coef ficient,or the Krugman –Gini-Coef ficient)are used,the value for the clustering group is either statistically indifferent from or smaller than that for the non-clustering group.In summary,proximity measures seem superior to the conventional measures in evaluating the degree of industrial clusters in China.For detailed results,see Table A in the Appendix A .4.Clustering,firm financing,and number of firms:county level evidenceWe now turn to explore the effects of such increased industry clustering within geographical regions.Through two channels,the greater degree of clustering has helped alleviate the dif ficulty in firms'access to external finances:the finer division of labor within industrial clusters reduces the level of capital requirement,and the greater availability of trade credit among firms within the clusters helps satisfy working capital requirement.With financial constraints eased,the number of firms increases,and thus the degree of competition.In turn,we expect to observe better firm performance.To study the potential effects of clustering on firm finances,firm entry,and firm performance outlined above,we utilize data at two levels of aggregation.County-level data will be used to explore the impact of clustering on the minimal capital requirement and the number of firms;while firm level data will be analyzed to study how clustering relates to the amount of trade credit among firms,the export performance of firms,and their productivity.Table 1provides summary statistics of variables used in the county-level analysis,where two patterns are worth noting.First of all,the minimum level of assets at the county level has dropped between 1995and 2004,in stark contrast to the tremendous growth in the size of the overall Chinese economy.This result is consistent with the second pattern:The total number of firms has risen substantially from 1995to 2004,indicating an increase in competition over time.In particular,the number of domestic non-state firms has risen faster than the total number of firms,while the number of state owned enterprises (SOEs)has shrunk over time,consistent with the privatization process in China during this time period.Finally,the level of financial inef ficiency has fallen slightly during this time period,although the change is not statistically signi ficant.To explore the effect of clustering on firms'capital requirements,it is crucial that our sample does not exclude firms due to their small size.The 1995and 2004censuses that include all industrial firms provide the ideal data for computing the minimum level of assets for each county and testing the hypothesis.Table 2shows results from the following regression:log min asset c ;2004 =α+β1Ãlog min asset c ;1995 +β2ÃP c ;1995+β3ÃF c ;1995+ε;ð1Þwhere c indicates county,min(asset c,2004)is the minimum level of assets among all firms located in the county in 2004,min(asset c,1995)is the minimum level of assets in 1995,P c,1995is the industry proximity in 1995,F c,1995measures the degree of financial inef ficiency in 1995,8and εis the random error term.Therefore,the coef ficient β2shows the effect of industry proximity in a region on the minimum requirement of capital for firms located in that region.Columns 1–3in the top panel of Table 2suggest that greater financial inef ficiency is associated with a higher level of minimum assets in a region,implying higher capital entry barriers in regions with less financial development.The finding is consistent with the mainstream literature that finance plays a role in economic development.Yet the6Interestingly,we find similar results using other conventional concentration measures,including the Hirfendahl index and Gini coef ficient.See Long and Zhang (2010)for details.7The exception is employment weighted proximity,which did not change signi ficantly.This most likely re flects the fact that SOEs laid off massive number of workers as part of the restructuring reform in the middle and late 1990s.Table 1Summary statistics of county-level variables used in regressions.VariableMean SD Min Max N Proximity 2004(w =asset)0.2260.0350.0910.3972833Proximity 2004(w =employment)0.2200.0320.0000.4032834Proximity 2004(w =output)0.2260.0380.0000.6312833Proximity 1995(w =asset)0.2180.0310.0000.4952765Proximity 1995(w =employment)0.2220.0370.0000.4952756Proximity 1995(w =output)0.2170.0300.0000.4952764Log(minimum asset 2004)(in millions) 3.061 1.4550.00010.4042761Log(minimum asset 1995)(in millions) 3.540 1.2640.00010.0752761Log(5th percentile asset 2004)(in millions) 4.8520.8750.00010.4042761Log(5th percentile asset 1995)(in millions) 4.7390.9770.00010.0752761Log(10th percentile asset 2004)(in millions) 5.3990.7880.00010.4042761Log(10th percentile asset 1995)(in millions) 5.2420.9310.00010.0752761Log(total number of firms 2004) 5.289 1.3530.4059.8352761Log(total number of firms 1995)4.684 1.0400.6937.6762761Log(number of non-state firms 2004)5.180 1.46709.8332761Log(number of non-state firms 1995) 4.117 1.35707.6282761Log(number of SOEs 2004)0.2940.4130 3.1772761Log(number of SOEs 1995) 1.7380.7340 4.8032761Financial inef ficiency 2004 1.1160.3070.023 3.8502761Financial inef ficiency 19951.1450.2060.0362.5762754Calculated by authors based on China Industrial Census 1995and China EconomicCensus 2004.Following Zhang and Tan (2007)and Hsieh and Klenow (2009),we use the variation in marginal product of capital to measure the degree of financial inef ficiency.See footnote 9for details.8In an ideal world with perfect capital markets,the marginal product of capital should be equal across firms and regions.Based on this insight,Zhang and Tan (2007)and Hsieh and Klenow (2009)propose to use the variation in marginal product of capital to measure the degree of financial inef ficiency.For a production function with constant returns to scale,the marginal product of capital is proportional to average product of capital.Therefore,the variation in the log(marginal product of capital)=variation in the log(average product of capital).In this paper,we compute the standard deviation of logarithm of the value added/total asset ratio at the county level as a measure of financial inef ficiency.It would be ideal to find information on formal financial development.However,such data are not systemically available at the county level for a long period.115C.Long,X.Zhang /Journal of International Economics 84(2011)112–123。

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x∈F∗ q
(x ∈ Fq )
χ(x)λ(x) ∈ Z [ζp(q−1) ]. 2
Lemma 2.1: (1) (trivial cases) q − 1, if χ = 1(= ψ 0 ) and λ = 1(= λ0 ) G(χ, λ) = Gq (χ, λ) = −1, if χ = 1 and λ = 1 0, if χ = 1 and λ = 1. (2) For b ∈ F∗ q (namely, λb = 1) G(χ, λb ) = χ(b)G(χ), G(χ) = χ(−1)G(χ), where χ is the conjugate character of χ and G(χ) = G(χ, λ1 ) =
2Hale Waihona Puke 2.1Preliminaries
Gauss sums
We introduce several basic facts on Gauss sums used in this paper. For more details on Gauss sums we refer the book [3]. Let q = pl where p is a prime number and l ≥ 1, θ be a primitive element of the √ 2π −1 ∗ finite field Fq , namely Fq = θ . Let ζm = e m for any positive integer m. The group of additive characters of Fq is ˆq = {λb : b ∈ Fq }, F where
(3) If χ = 1, then
Lemma 2.3: (semiprimitive case, [3, Theorem 11.6.3]) Let p be a prime number, e ≥ 3. Suppose that there exists a positive integer t such that pt ≡ −1 (mod e). Let t be the smallest positive integer satisfying pt ≡ −1 (mod e)(so that the multiplicative ∗ order of p in Ze is 2t). For l = 2ts (s ≥ 1), q = pl and a multiplicative character χ of Fq with order e, we have Gq (χ) = √ √ q (−1)s−1 , q (−1) if p = 2
[22,24]) and the weight hierarchy is totally determined in several cases. The bounds, asymptotic behaviour and duality of GHWs have been found [1,11,17,20,23]. But in general speaking, to determine the weight hierarchy is a difficult problem. In this paper we deal with GHWs of q -ary irreducible cyclic codes. For binary case (q = 2) there exist several results in [14,20,21]. We consider the general case where q is any power of a prime number. We firstly present two general formulas on dr (C ) ((3.3) and (3.4) in Theorem 3.2) which involves Gauss sums and character sum β ∈H \{0} ϕ(β ), where ϕ is a multiplicative character of FQ (Q = q k ) and H is a Fq -subspace of FQ with dimension r or k − r . When involved Gauss sums can be calculated and have the same values, the character sum is reduced to be the size of ′ ′ H θe , where θe is a subgroup of F∗ Q = θ . Then we can determine dr (C ) for smaller r by (3.3) and larger r by (3.4). And the weight hierarch {dr (C ) : 1 ≤ r ≤ k } can be totally determined in several cases. The paper is organized as follows. In Section 2 we introduce several basic facts on Gauss sums and previously known results on GHWs. Then we present two general formulas on dr (C ) and their direct consequences in Section 3. In Section 4 we obtain more results on dr (C ) for several particular cases. Section 5 is conclusion.
T (bx) λb (x) = ζp
and T is the trace mapping from Fq to Fp . The group of multiplicative characters of Fq is ˆ∗ = {ψ i : 0 ≤ i ≤ q − 2} = ψ F q where ψ is defined by ψ (θ) = ζq−1. ˆ∗ and λ ∈ F ˆq we define the Gauss sum on Fq by For each χ ∈ F q G(χ, λ) =
Generalized Hamming Weights of Irreducible Cyclic Codes
Minghui Yang, Jin Li, Keqin Feng, Dongdai Lin
arXiv:1410.2702v1 [cs.IT] 10 Oct 2014
Abstract-The generalized Hamming weight (GHW) dr (C ) of linear codes C is a natural generalization of the minimum Hamming distance d(C )(= d1 (C )) and has become one of important research objects in coding theory since Wei’s originary work [23] in 1991. In this paper two general formulas on dr (C ) for irreducible cyclic codes are presented by using Gauss sums and the weight hierarchy {d1 (C ), d2 (C ), . . . , dk (C )} (k = dim C ) are completely determined for several cases. keywords-generalized Hamming weight, irreducible cyclic code, Gauss sum.
q
and {d1 (C ), d2 (C ), . . . , dk (C )} is called the weight hierarchy of C (d0 (C ) = 0). It is obvious that d1 (C ) is just the minimun Hamming distance d(C ). The concept on GHW has appeared as early as in 1970’s ([12,17]) and has become an important research object in coding theory after Wei’s paper [23] in 1991, where Wei gives a series of beautiful results on GHW and indicates that it completely characterizes the performance of a linear code when it is used on wire-tap channel of type II which has connection with cryptography. GHW is also used to deal with t-resilient functions and trellis or branch complexity of linear codes [20]. In past two decades the value of GHWs has been determined or estimated for many series of linear codes (RM codes [10,23], BCH codes [4,8,9], trace codes [19], cyclic codes [6,16], AG codes [2,5,7,15,18,25,26], binary Kasami codes [13] and other codes 1
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