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06美国大学生建模C

06美国大学生建模C
06美国大学生建模C

ICM: Trade-offs in the fight against HIV/AIDS

As the HIV/AIDS pandemic enters its 25th year, both the number of infections and number of deaths due to the disease continue to rise. Despite an enormous amount of effort, our global society remains uncertain on how to most effectively allocate resources to fight this epidemic.

You are a team of analysts advising the United Nations (UN) on how to manage the available resources for addressing HIV/AIDS. Your job is to model several scenarios of interest and to use your models to recommend the allocation of financial resources. The narrative below provides some background information, and outlines specific tasks.

Task #1: For each of the continents (Africa, Asia, Europe, North America, Australia, and South America), choose the country you believe to be most critical in terms of HIV/AIDS. Build a model to approximate the expected rate of change in the number of HIV/AIDS infections for these countries from 2006 to 2050, in the absence of any additional interventions. Fully explain your model and the assumptions that underlie your model. In addition, explain how you selected the countries to model.

Use as a list of countries for inclusion in your analysis the countries included in the attached spreadsheet, which include all member states of the World Health Organization (WHO) as of 2003.

Data: “list_WHO_member_states.xls”

Reliable data on HIV prevalence rates by county are generally difficult to obtain. The attached spreadsheet includes several worksheets of data which you may use in your analysis.

Data: “hiv_aids_data.xls”

a.“Global HIV- AIDS cases, 1999”: These data come from UNAIDS (the Joint United

Nations Programme on HIV/AIDS) and report the estimated number of HIV positive 0 to

49 year olds by country at the end of 1999.

b.“HIV- AIDS in Africa over time”: These data come from the US government and give

some piecemeal time series data on measured HIV prevalence rates among women of

childbearing age, in urban areas, over time for some African countries.

c.“HIV- AIDS subtypes”: These data come from UNAIDS and give the geographic

distribution of HIV-1 subtypes by country.

Also attached, for your use, are some basic population and demographic data.

Data:

(1)“fertility_data.xls”: These data come from the UN and give age-specific fertility rates by major

area, region, and country, 1995-2050 (births per thousand women)

a.Estimates for 1995-2005

b.Projections (under the assumption of medium fertility levels) for 2005-2050

(2)“population_data.xls”: These data come from the UN and give total population (both sexes

combined) by major area, region, and country, annually for 1950-2050 (thousands).

a.Estimates for 1950-2005

b.Projections (under the assumption of medium fertility levels) for 2006-2050

(3)“age_data.xls”: These data come from the UN and give population (for both sexes, and by

gender) by five-year age groups, major area, region, and country, 1950-2050 (thousands).

a.Estimates, 1950-2005

b.Projections (under the assumption of medium fertility levels) for 2010-2050

(4)“birth_rate_data.xls”: These data come from the UN and give crude birth rates by major area,

region, and country, 1950-2050 (births per thousand population).

a.Estimates, 1950-2005

b.Projections (under the assumption of medium fertility levels) for 2005-2050

(5)“life_expectancy_0_data.xls”: These data come from the UN and give life expectancy at

birth (by sex and both sexes combined) by major area, region, and country, 1950-2050 (years).

a.Estimates, 1950-2005

b.Projections (under the assumption of medium fertility levels) for 2005-2050

There are a number of interventions that HIV/AIDS funding could be directed towards -- including prevention interventions (voluntary counseling and testing, condom social marketing, school-based AIDS education, medicines to prevent mother-to-child transmission, etc.) and care interventions (treating other untreated sexually transmitted diseases, treating opportunistic infections, etc.). You should focus on only two potential interventions: provision of antiretroviral (ARV) drug therapies, and provision of a hypothetical HIV/AIDS preventative vaccine.

Task #2: First, estimate the level of financial resources from foreign aid donors that you realistically expect to be available to address HIV/AIDS, by year, from 2006 to 2050, for the countries you selected in Task #1. Then use the model you developed in Task #1 and these estimates of financial resources to estimate the expected rate of change in the number of HIV/AIDS infections for your selected countries from 2006 to 2050 under realistic assumptions for the following three scenarios:

(1)Antiretroviral (ARV) drug therapy

(2)A preventative HIV/AIDS vaccine

(3)Both ARV provision and a preventative HIV/AIDS vaccine

Assume in these scenarios that there is no risk of emergence of drug-resistant strains of HIV (you will examine this issue in Task #3).

Be sure to carefully describe the assumptions that underlie your model.

You can choose whether these scenarios should be implemented for all of the countries you selected in Task #1, or for certain subsets of countries based on income cut-offs, disease burden, etc. Available for use if you wish is a spreadsheet of country-level income data.

Data: “income_data.xls”: These data are from the World Bank (2002) and give per-capita gross national product (GNP) data as well as broad income classifications that you are free to use in your analysis if you wish.

ARV drug therapies can have tremendous benefits in terms of prolonging the lives of individuals infected with HIV/AIDS. ARVs are keeping a high proportion of HIV/AIDS-infected individuals in rich countries alive, and policy makers and international institutions are facing tremendous political pressure to increase access to ARVs for individuals in poor countries. Health budgets in low-income countries are very limited, and it seems unlikely that poor countries will be able to successfully expand these programs to the majority of their populations using their own resources. Appendix 1 presents country-specific data from UNAIDS on current access to ARVs for a number of countries.

The efficacy of ARVs depends in large part on adherence to the treatment regimen and to proper monitoring. The most favorable conditions for ARVs are structured programs with extensive counseling and physician care, as well as regular testing to monitor for disease progression and the onset of opportunistic infections. Non-adherence or inadequate treatment carries with it two very serious consequences. First, the treatment may not be effective for the individual undergoing treatment. Second, partial or inadequate treatments are thought to directly lead to the emergence of drug-resistant strains of HIV.

The price of the drugs initially used to treat patients has come down to several hundred dollars a year per patient, but delivering them and providing the necessary accompanying medical care and further treatment is the key administrative and financial challenge. It is estimated that purchasing and delivering antiretrovirals using the clinically-recommended approach (DOTS, or directly observed short course treatments) which is intended to minimize the emergence of drug-resistant strains would cost less than $1,100 per person per year. (Adams, Gregor et al. [2001]. “Consensus Statement on Antiretroviral Treatment for AIDS in Poor Countries,”

https://www.wendangku.net/doc/088449731.html,/bioethics/pdf/consensus_aids_therapy.pdf )

For a preventative HIV vaccine, make assumptions you feel are reasonable about the following (in addition to other factors you may choose to include in your model):

(1)The year in which an HIV/AIDS preventative vaccine might be available

(2)How quickly vaccination rates might reach the following steady-state levels of vaccination:

a.If you wish to immunize new cohorts (infants), assume the steady-state level for new

cohorts of the country-by-country immunization rates for the third dose of the

diphtheria-pertussis-tetanus vaccine (DTP3), as reported by the WHO (2002)

i.Data: “vaccination_rate_data.xls”

b.If you wish to immunize adults (any group over age 5), assume the steady-state level for

older cohorts is the second dose of the tetanus toxoid (TT2) rate, as reported by the WHO

(2002)

i.Data: “vaccination_rate_data.xls”

(3)The efficacy and duration of protection of the vaccine

(4)Whether there would be epidemiological externalities from vaccination

(5)Assume the vaccine is a three-dose vaccine, and can be added to the standard package of vaccines

delivered under the WHO’s Expanded Programme on Immunization (EPI) at an incremental cost of addition of $0.75

Task #3: Re-formulate the three models developed in Task #2, taking into consideration the following assumptions about the development of ARV-resistant disease strains. Current estimates suggest that patients falling below 90-95 percent adherence to ARV treatment are at a “substantial risk” of producing drug resistant strains. Use as an assumption for your analysis that a person receiving ARV treatment with adherence below 90 percent has a 5 percent chance of producing a strain of HIV/AIDS which is resistant to standard first-line drug treatments.

Second- and third-line ARV drug therapies are available, but assume for your analysis that these drugs are prohibitively expensive to implement in countries outside of Europe, Japan, and the United States.

Task #4: Write a white paper to the United Nations providing your team’s recommendations on the following:

(1)Your recommendations for allocation of the resources available for HIV/AIDS

among ARV provision and a preventative HIV vaccine

(2)Your argument for how to weigh the importance of HIV/AIDS as an

international concern relative to other foreign policy priorities

(3)Your recommendations for how to coordinate donor involvement for HIV/AIDS

For (1): assume that between now and 2010 the available financial resources could be allocated so as the speed the development of a preventative HIV vaccine – through directly-financing vaccine research and development (R&D), or through other mechanisms. Any gains from such spending would move the date of development you assumed in Task #2 to some earlier date.

Appendix 1.

Percentage of adults with advanced HIV infection receiving antiretroviral treatment

Country

% of adults with

advanced HIV infection

receiving ARVs Source of information

Sub-Saharan Africa

Angola < 1 WHO 2002

Benin 2.5

AAI

2002 Botswana 7.9 (2780) UNGASS CR 2003

Burkina Faso 1.4 (675) UNGASS CR 2003

Burundi 1.9

AAI

2002 Cameroon 1.5 National Target 2002

Central African Rep < 1 National Target 2002

C?te d'Ivoire 2.7 UNGASS CR 2003

Democratic Rep. of Congo 0 AAI 2002

Equatorial Guinea 6.8 WHO 2002

Eritrea < 1 WHO 2002

Ethiopia < 1 WHO 2002

Gambia 6.3

WHO

2002 Ghana 1.8

WHO

2002 Lesotho < 1 WHO 2002

Malawi 1.8 UNGASS CR 2003

Mali 2.5

WHO

2003 Mauritius* 100 UNGASS CR 2003

Mozambique 0

WHO

2002 Namibia 0

WHO

2002 Nigeria 1.5 (8,100) UNGASS CR 2003

Kenya 3 UNGASS CR 2003

Rwanda < 1 (1,500) UNGASS CR 2003

Senegal < 1 AAI 2002

Seychelles* 68.2 UNGASS CR 2003

Sierra Leone 0 WHO 2002

South Africa 0 WHO 2002

Swaziland 1.7 (450) UNGASS CR 2003

Uganda 6.3 (10,000) UNGASS CR 2003

United Republic of Tanzania < 1 UNGASS CR 2003

Zambia 0

WHO

2002 Zimbabwe 0

WHO

2002

South & South-East Asia

Afghanistan* 0 WHO country office

Bangladesh* 0

WHO

2002 Cambodia 3

NCHADS

2002 India 2 UNGASS CR 2003

Indonesia* 2.7

WHO

2002

Iran* 100 WHO 2002

Myanmar* < 1 UNGASS CR 2003

Pakistan* 2.2 WHO 2002

Philippines* 3.5

WHO

2002

Sri Lanka* 2 National Target 2002

Singapore* 0

MoH

Thailand 4

NACP

2003 Viet Nam* 1 UNGASS CR 2003

East Asia & Pacific

China* 5 National Target 2002

Hong Kong* 100 WHO 2002

Papa New Guinea* 0 WHO 2002

Samoa* 100

MoH

2002 Tonga* 0

NACP

2003

Caribbean & Latin America

Argentina* 91.2

(23253) UNGASS CR 2003

Bahamas* < 1 WHO 2002

Belize 7.7 (29) UNGASS CR 2003

Bolivia* < 1 WHO 2002

Brazil* 100 (119,500) UNGASS CR 2003

Dominican Republic 0 National Target 2002

Guatemala 46 UNGASS CR 2003

WHO

2002 Guyana 0

Honduras < 1 WHO 2002

Jamaica < 1 AAI 2002

Mexico* 92 UNGASS CR 2003

2002 Nicaragua* 0

WHO Paraguay* 50 (300) UNGASS CR 2003

2002

NACP Peru* 19.2

Trinidad & Tobago < 1 AAI 2002

2002

NACP Uruguay* 50.5

Eastern Europe & Central Asia

Albania* 0 WHO EURO Survey of ARV access 2003 Armenia* 0 WHO EURO Survey of ARV access 2003 Azerbaijan* 0 WHO EURO Survey of ARV access 2003

Belarus* < 1 UNGASS CR 2003

Bosnia & Herzegovina* 10 WHO EURO Survey of ARV access 2003 Bulgaria* 44.5 WHO EURO Survey of ARV access 2003

Croatia* 98.7 WHO EURO Survey of ARV access 2003

Cyprus* 100 Dept Medical and Health Services

Estonia* 32 WHO EURO Survey of ARV access 2003

Georgia* 8 WHO EURO Survey of ARV access 2003 Hungary* 97 WHO EURO Survey of ARV access 2003 Kazakhstan* 1 UNGASS CR 2003

Kyrgyzstan* 0 EURO survey 2002

Latvia* 51 WHO EURO Survey of ARV access 2003 Lithuania* 55 WHO EURO Survey of ARV access 2003 Macedonia* 20 WHO EURO Survey of ARV access 2003 Moldova Republic* 8.3 WHO 2002

Poland* 92.9 WHO EURO Survey of ARV access 2003 Romania* 64.4 WHO EURO Survey of ARV access 2003 Russian Federation* 83.3 WHO 2002

Serbia & Montenegro* 26.4 WHO EURO Survey of ARV access 2003 Slovakia* 95 WHO EURO Survey of ARV access 2003 Slovenia* 96.3 WHO EURO Survey of ARV access 2003 Tajikistan* 0 UNGASS CR 2003

Ukraine < 1 MoH and WHO 2002

Uzbekistan* 0 WHO EURO Survey of ARV access 2003

North Africa & Middle East

Djibouti* 1.8 MoH, WHO 2002

Jordan* 21.3 UNGASS CR 2003

2003

NACP Lebanon* 100

Morocco* 20.7 UNGASS CR 2003

Qatar* 64.9 HIV registry 2002

Sudan < 1 WHO 2002

High-income OECD

Australia* 53.2 Annual Surveillance Report

Austria* 92.6 WHO EURO Survey of ARV access 2003 Belgium* 93.8 WHO EURO Survey of ARV access 2003 Denmark* 90.9 WHO EURO Survey of ARV access 2003

Finland* 94.6 WHO EURO Survey of ARV access 2003 Germany* 94.7 WHO EURO Survey of ARV access 2003

Iceland* 87.5 WHO EURO Survey of ARV access 2003

Italy* 72.7 WHO EURO Survey of ARV access 2003 Luxembourg* 96.9 WHO EURO Survey of ARV access 2003

Malta* 94.3 WHO EURO Survey of ARV access 2003 Netherlands* 96 WHO EURO Survey of ARV access 2003

Norway* 89.6 WHO EURO Survey of ARV access 2003

Spain* 92.3 WHO EURO Survey of ARV access 2003 Sweden* 95 WHO EURO Survey of ARV access 2003 Switzerland* 95 WHO EURO Survey of ARV access 2003

United Kingdom* 92.1 WHO EURO Survey of ARV access 2003

Notes: * := Countries with low prevalence/concentrated epidemics; AAI := Accelerated Access Initiative; UNGASS CR 2003 := program monitoring data from UNGASS (United Nations General Assembly Special Session) country reports 2003; WHO 2002 := 2002 program monitoring data through WHO (World Health Organization) country offices; MoH := Ministry of Health; NACP := National AIDS Control Programme; NCHADS := National Centre for HIV/AIDS, Dermatology and STIs (sexually transmitted infections).

美国数学建模大赛比赛规则

数学中国MCM/ICM参赛指南翻译(2014版) MCM:The Mathematical Contest in Modeling MCM:数学建模竞赛 ICM:The InterdisciplinaryContest in Modeling ICM:交叉学科建模竞赛ContestRules, Registration and Instructions 比赛规则,比赛注册方式和参赛指南 (All rules and instructions apply to both ICM and MCMcontests, except where otherwisenoted.)(所有MCM的说明和规则除特别说明以外都适用于 ICM) 每个MCM的参赛队需有一名所在单位的指导教师负责。 指导老师:请认真阅读这些说明,确保完成了所有相关的步骤。每位指导教师的责任包括确保每个参赛队正确注册并正确完成参加MCM/ ICM所要求的相关步骤。请在比赛前做一份《参赛指南》的拷贝,以便在竞赛时和结束后作为参考。 组委会很高兴宣布一个新的补充赛事(针对MCM/ICM 比赛的视频录制比赛)。点击这里阅读详情! 1.竞赛前

A.注册 B.选好参赛队成员 2.竞赛开始之后 A.通过竞赛的网址查看题目 B.选题 C.参赛队准备解决方案 D.打印摘要和控制页面 3.竞赛结束之前 A.发送电子版论文。 4.竞赛结束的时候, A. 准备论文邮包 B.邮寄论文 5.竞赛结束之后 A. 确认论文收到 B.核实竞赛结果 C.发证书 D.颁奖 I. BEFORE THE CONTEST BEGINS:(竞赛前)A.注册 所有的参赛队必须在美国东部时间2014年2月6号(星期四)下午2点前完成注册。届时,注册系统将会自动关闭,不再接受新的注册。任何未在规定时间

美国大学生数学建模竞赛组队和比赛流程

数学模型的组队非常重要,三个人的团队一定要有分工明确而且互有合作,三个人都有其各自的特长,这样在某方面的问题的处理上才会保持高效率。 三个人的分工可以分为这几个方面: 数学员:学习过很多数模相关的方法、知识,无论是对实际问题还是数学理论都有着比较敏感的思维能力,知道一个问题该怎样一步步经过化简而变为数学问题,而在数学上又有哪些相关的方法能够求解,他可以不能熟练地编程,但是要精通算法,能够一定程度上帮助程序员想算法,总之,数学员要做到的是能够把一个问题清晰地用数学关系定义,然后给出求解的方向; 程序员:负责实现数学员的想法,因为作为数学员,要完成大部分的模型建立工作,因此调试程序这类工作就必须交给程序员来分担了,一些程序细节程序员必须非常明白,需要出图,出数据的地方必须能够非常迅速地给出;ACM的参赛选手是个不错的选择,他们的程序调试能力能够节约大量的时间,提高在有限时间内工作的工作效率; 写手:在全文的写作中,数学员负责搭建模型的框架结构,程序员负责计算结果并与数学员讨论,进而形成模型部分的全部内容,而写手要做的。就是在此基础之上,将所有的图表,文字以一定的结构形式予以表达,注意写手时刻要从评委,也就是论文阅读者的角度考虑问题,在全文中形成一个完整地逻辑框架。同时要做好排版的工作,最终能够把数学员建立的模型和程序员算出的结果以最清晰的方式体现在论文中。一个好的写手能够清晰地分辨出模型中重要和次要的部分,这样对成文是有非常大的意义的。因为论文是评委能够唯一看到的成果,所以写手的水平直接决定了获奖的高低,重要性也不言而喻了。 三个人至少都能够擅长一方面的工作,同时相互之间也有交叉,这样,不至于在任何一个环节卡壳而没有人能够解决。因为每一项工作的工作量都比较庞大,因此,在准备的过程中就应该按照这个分工去准备而不要想着通吃。这样才真正达到了团队协作的效果。 比赛流程:对于比赛流程,在三天的国赛里,我们应该用这样一种安排方式:第一天:定题+资

2010年美国大学生数学建模竞赛B题一等奖

Summary Faced with serial crimes,we usually estimate the possible location of next crime by narrowing search area.We build three models to determine the geographical profile of a suspected serial criminal based on the locations of the existing crimes.Model One assumes that the crime site only depends on the average distance between the anchor point and the crime site.To ground this model in reality,we incorporate the geographic features G,the decay function D and a normalization factor N.Then we can get the geographical profile by calculating the probability density.Model Two is Based on the assumption that the choice of crime site depends on ten factors which is specifically described in Table5in this paper.By using analytic hierarchy process (AHP)to generate the geographical profile.Take into account these two geographical profiles and the two most likely future crime sites.By using mathematical dynamic programming method,we further estimate the possible location of next crime to narrow the search area.To demonstrate how our model works,we apply it to Peter's case and make a prediction about some uncertainties which will affect the sensitivity of the program.Both Model One and Model Two have their own strengths and weaknesses.The former is quite rigorous while it lacks considerations of practical factors.The latter takes these into account while it is too subjective in application. Combined these two models with further analysis and actual conditions,our last method has both good precision and operability.We show that this strategy is not optimal but can be improved by finding out more links between Model One and Model Two to get a more comprehensive result with smaller deviation. Key words:geographic profiling,the probability density,anchor point, expected utility

3分钟完整了解·HiMCM美国高中生数学建模竞赛

眼看一年一度的美国高中生数学建模竞赛就要到来了,聪明机智的你准备好了吗? 今年和码趣学院一起去参加吧! 什么是HiMCM HiMCM(High School Mathematical Contest in Modeling)美国高中生数学建模竞赛,是美国数学及其应用联合会(COMAP)主办的活动,面向全球高中生开放。 竞赛始于1999年,大赛组委将现实生活中的各种问题作为赛题,通过比赛来考验学生的综合素质。

HiMCM不仅需要选手具备编程技巧,更强调数学,逻辑思维和论文写作能力。这项竞赛是借鉴了美国大学生数学建模竞赛的模式,结合中学生的特点进行设计的。 为什么要参加HiMCM 数学逻辑思维是众多学科的基础,在申请高中或大学专业的时候(如数学,经济学,计算机等),参加了优质的数学竞赛的经历都会大大提升申请者的学术背景。除了AMC这种书面数学竞赛,在某种程度上数学建模更能体现学生用数学知识解决各种问题的能力。

比赛形式 注意:HiMCM比赛可远程参加,无规定的比赛地点,无需提交纸质版论文。重要的是参赛者应注重解决方案的设计性,表述的清晰性。 1.参赛队伍在指定17天中,选择连续的36小时参加比赛。 2.比赛开始后,指导教师可登陆相应的网址查看赛题,从A题或B题中任选其一。 3.在选定的36小时之内,可以使用书本、计算机和网络,但不能和团队以外的任何人 员交流(包括本队指导老师) 比赛题目 1.比赛题目来自现实生活中的两个真实的问题,参赛队伍从两个选题中任选一个。比赛 题目为开放性的,没有唯一的解决方案。 2.赛事组委会的评审感兴趣的是参赛队伍解决问题的方法,所以不太完整的解决方案也 能提交。 3.参赛队伍必须将问题的解决方案整理成31页内的学术论文(包括一页摘要),学术 论文中可以用图表,数据等形式,支撑问题的解决方案 4.赛后,参赛队伍向COMPA递交学术论文,最终成果以英文报告的方式,通过电子 邮件上传。 表彰及奖励 参赛队伍的解决方案由COMPA组织专家评阅,最后评出: 特等奖(National Outstanding) 特等奖提名奖(National Finalist or Finalist) 一等奖(Meritorious)

美国数学建模比赛题目及翻译

PROBLEM A: The Ultimate Brownie Pan When baking in a rectangular pan heat is concentrated in the 4 corners and the product gets overcooked at the corners (and to a lesser extent at the edges). In a round pan the heat is distributed evenly over the entire outer edge and the product is not overcooked at the edges. However, since most ovens are rectangular in shape using round pans is not efficient with respect to using the space in an oven. Develop a model to show the distribution of heat across the outer edge of a pan for pans of different shapes - rectangular to circular and other shapes in between. Assume 1. A width to length ratio of W/L for the oven which is rectangular in shape. 2. Each pan must have an area of A. 3. Initially two racks in the oven, evenly spaced. Develop a model that can be used to select the best type of pan (shape) under the following conditions: 1. Maximize number of pans that can fit in the oven (N)

美国数学建模竞赛要求

2.竞赛开始之后 A.通过竞赛的网址查看题目 B.选题 C.参赛队准备解决方案 D.打印摘要和控制页面 3.竞赛结束之前 A.发送电子版论文。 4.竞赛结束的时候, A. 准备论文邮包 B.邮寄论文 5.竞赛结束之后 A. 确认论文收到 B.核实竞赛结果 C.发证书 D.颁奖 1.您必须在在美国东部时间2014年2月6日(星期四)晚上8点大赛开始以前选择好您的参赛队的队员。一旦比赛开始,您将不能增加或是改变任何一个参赛队队员(但是如果参赛队员本人决定不参加比赛,您可以把他/她从队员名单中删除)。 2.每个参赛队最多都只能由3名学生组成。 3.一个学生最多只能参加一个参赛队。 4.在比赛时间段内,参赛队成员必须是在校学生,但可以不是全日制学生。参赛队成员和指导教师必须来自同一所学校。 2.竞赛开始之后 A.通过网站的得到赛题 ! 美国东部时间2014年2月6日(星期四)晚上8点竞赛开始时,可以通过竞赛网站得到题目。 1.赛题会于美国东部时间2014年2月6日(星期四)晚上8点公布:所有的参赛队员可以通过访问https://www.wendangku.net/doc/088449731.html,/undergraduate/contests/mcm.得到赛题。无须任何密码,仅通过网页链接就可以得到赛题。 2、美国东部时间2014年2月6日晚7点50分,比赛题目也会同步发布于一下镜像网站:

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