Acyclic 4-coloring of planar graphs without 4- and 5-cycles

Every planar graph is known to be acyclically 5-colorable (O.V.Borodin, 1976). Some sufficient conditions are also obtained for a planar graph to be acyclically 4- and 3-colorable. In particular, the acyclic 4-colorability was proved for the following planar graphs: without 3- and 4-cycles (O.V.Borodin, A.V. Kostochka, and D.R.Woodall, 1999), without 4-, 5-, and 6-cycles, or without 4-, 5-, and 7-cycles, or without 4-, 5-, and intersecting 3-cycles (M. Montassier, A.Raspaud andW.Wang, 2006), and without 4-, 5-, and 8-cycles (M. Chen and A.Raspaud, 2009). The purpose of this paper is to prove that each planar graph without 4- and 5-cycles is acyclically 4-colorable.     

Foreword to the Special Focus on Mathematics,Data and Knowledge

There is a growing interest in applying mathematical theories and methods from topology, computational geometry, differential equations, fluid dynamics, quantum statistics, etc. to describe and to analyze scientific regularities of diverse, massive, complex, nonlinear, and fast changing data accumulated continuously around the world and in discovering and revealing valid, insightful, and valuable knowledge that data imply. With increasingly solid mathematical foundations, various methods and techniques have been studied and developed for data mining, modeling, and processing, and knowledge representation, organization, and verification; different systems and mechanisms have been designed to perform data-intensive tasks in many application fields for classification, predication, recommendation, ranking, filtering, etc. This special focus of Mathematics in Computer Science is organized to stimulate original research on the interaction of mathematics with data and knowledge, in particular the exploration of new mathematical theories and methodologies for data modeling and analysis and knowledge discovery and management, the study of mathematical models of big data and complex knowledge, and the development of novel solutions and strategies to enhance the performance of existing systems and mechanisms for data and knowledge processing. The present foreword provides a short review of some key ideas and techniques on how mathematics interacts with data and knowledge, together with a few selected research directions and problems and a brief introduction to the four papers published in the focus.     

RUMINATIONS ON THE DEVELOPMENT AND FUTURE OF POPULATION DYNAMICS MODELS IN FISHERIES

ABSTRACT. I trace the development of fisheries models (i.e., fish population dynamics models of species subject to fisheries) to the 21st century. The first real efforts occurred in the period 1900 1920 with the work of Baranov (the “Grandfather” of fisheries population dynamics) and the formation of the International Council for the Exploration of the Sea (ICES). The establishment of the science occurred between 1920 1960 with multi‐species modeling, age‐ and size‐structure dynamics, and production models. Fundamental work during this time was done by Ricker (the “Father” of fisheries population dynamics), Beverton and Holt (the “Prophets” of fisheries population dynamics), Chapman, Dickie, DeLury, Graham, Gulland, Leslie, Lotka and Volterra, Russell, Schaefer, and Thompson. During this time, most of the workwas deterministic and mathematical. Between 1960 and 1980, statistical methodology evolved greatly but was separate from mathematical advances for the most part. The development of statistical principles for the estimation of animal abundance was further enhanced by Arnason, Buckland, Burnham and Anderson and White, Cormack, Eberhardt, Jolly, Manly, Pollock, Ricker, Robson, and Seber, among others. Fisheries models evolved in a deterministic setting, with advances in age‐structured models (Gulland, Pope, Doubleday), surplus production models (Pella, Tomlin‐son, Schnute, Fletcher, Hilborn), growth models, bioeconomic models (C. Clark) and management control models (Hilborn, Walters). The period 1980 2000 was the Golden Age. The integration between mathematics and statistics occurred when likelihood and least squares techniques were formally combined with mathematical models of population change. The number of fisheries modelers grew exponentially during this time, resulting in a concomitant increase in publications. A major advance in the 1990s has been the development of Bayesian and time series methods, which have allowed explicit specification of uncertainty. Currently, theory allows realistic modeling of age‐ and size‐structured populations, migratory populations and harvesting strategies. These models routinely incorporate measurement error, process error (stochasticity) and time variation. But data needs often overwhelm the performance of models, and greater demands are being placed on models to answer complex questions. There has been poor communication between fisheries and ecological modelers, between fisheries researchers and statisticians, and among fisheries researchers in different geographic locales. Future models will need to deal better with habitat and spatial concerns, genetics, multispecies interactions, environmental factors, effects of harvesting on the ecosystem, model misspecification and so‐cioeconomic concerns. Meta‐analysis, retrospective analysis and operating models are some modern approaches for dealing with uncertainty and providing for sustainable fisheries. However, I fear that current attacks on single‐species models and management may result in rejection of these advances and an attempt to substitute a less scientific approach.     

I Just Don't Trust Them: The Development and Validation of an Assessment Instrument to Measure Trust in Science and Scientists

Trust in science and scientists can greatly influence consideration of scientific developments and activities. Yet, trust is a nebulous construct based on emotions, knowledge, beliefs, and relationships. As we explored the literature regarding trust in science and scientists we discovered that no instruments were available to assess the construct, and therefore, we developed one. Using a process of data collection from science faculty members and undergraduate students, field testing, expert feedback, and an iterative process of design, we developed, validated, and established the reliability of the Trust in Science and Scientist Inventory. Our 21‐item instrument has a reliability of Cronbach's alpha of .86, and we have successfully field‐tested it with a range of undergraduate college students. We discuss implications and possible applications of the instrument, and include it in the appendix.     

环境治理政策的减排、增效与结构优化效果动态评价

为测度环境治理政策波动对产出、减排、要素配置、消费与产业结构的影响及其传导机制,将异质性消费偏好、产出差异性、环境效用和环境损失函数引入E-DSGE模型。政策强度分析发现,技术进步、排污税和消费税政策效果较强,环境控制和治污支出冲击效果较弱。政策效应分析发现,技术进步政策效应最优,能实现增产和减排双重目标,促进要素配置和居民消费、产出与消费结构改进;排污税和政府治污支出政策次优,能实现增产和减排的双赢目标,促进要素供给和产出结构清洁化,不利于消费提升和消费结构优化;环境控制与消费税政策效果最差,以牺牲产出实现减排,不利于要素配置,产出与消费结构改进效果较弱,消费税会抑制居民消费,但消费税政策效果随环境友好型家庭比例提升而加强。     

PROMETHEE: A comprehensive literature review on methodologies and applications

In recent decades, several Multi-Criteria Decision Aid (MCDA) methods have been proposed to help in selecting the best compromise alternatives. In the meantime, the PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) family of outranking methods and their applications has attracted much attention from academics and practitioners. In this paper, a classification scheme and a comprehensive literature review are presented in order to uncover, classify, and interpret the current research on PROMETHEE methodologies and applications. Based on the scheme, 217 scholarly papers from 100 journals are categorized into application areas and non-application papers. The application areas include the papers on the topics of Environment Management, Hydrology and Water Management, Business and Financial Management, Chemistry, Logistics and Transportation, Manufacturing and Assembly, Energy Management, Social, and Other Topics. The last area covers the papers published in several fields: Medicine, Agriculture, Education, Design, Government and Sports. The scholarly papers are also classified by (1) year of publication, (2) journal of publication, (3) authors’ nationality, (4) PROMETHEE as applied with other MCDA methods, and (5) PROMETHEE as applied with GAIA (Geometrical Analysis for Interactive Aid) plane. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of PROMETHEE methodologies and applications, and hence promote the future of PROMETHEE research.     

Academic operations research programs structured on a user command language

Twelve deterministic and probabilistic Operations Research BASIC computer programs, useful in academic and research environments, are described. All accept identical conversational instructions in a unified user command language. Each program has help and examples messages, and built-in sets of data useful for illustration. It accepts commands for retrieving, displaying, changing, and saving the data, and for computing and optimization. Three programs also accept simulation commands. The availability of the source code and detailed documentation allows users to modify the programs, delete or add algorithms, change dimensions, and to translate the programs into other languages.     

基于ISM的地震灾后恢复重建影响因素分析

地震灾后恢复重建是地震灾害受灾国的一项艰巨而繁重的工作任务.地震灾害的破坏性使恢复重建具有复杂性、不确定性和开放性的特点,因此地震灾后恢复重建影响因素不但具有复杂性,而且影响范围和程度也各不相同.引入ISM模型解决了地震灾后恢复重建影响因素多而杂的问题,在文献资料统计基础上构建地震灾后恢复重建影响因子解析结构模型.通过分析确定地震灾后恢复重建关键影响区素共16个:重建主体、重建经验、施工条件、物价、资金、工程成本、建材质量、施工工期、标准施工、检验维修、工程利用、公共服务、自然环境、运行经费、社会饵障、居民激励.该结论为政府优化地震灾后恢复重建工作,保证重建效果具有重要意义.     

On the integral cohomology of a sylow subgroup of the symmetric group

Projectivity classes, which dualize injectivity classes (cf.[ll]), are introduced and some examples are given. Characterizations of hereditary rings, semisimple rings, Noetherian rings, (semi-)perfect rings, quasi-perfect rings, semiregular rings, semiregular modules and F- semiperfect modules using projectivity classes are given. Finally, for a projectivity class P, P-projective covers are defined and similar results with “quasi-projective cover” substituted by “T-projective cover” will still hold. Our results unify and generalize several well known results by Golan, Huynh and Smith, Rangaswamy and Vanaja, Tiwary and Pandeya, and Xue.     

Simulating the effect of nepotism on political risk taking and social unrest

Nepotism has been the primary influence on political behavior throughout human history. Despite the spread of democracy in the 20th century, nepotistic regimes have hardly disappeared. Nepotism heavily influences political activity throughout the developing world, Middle East, and central Asia where family ties are essential for gaining access to power, state resources, and privileges. Rebelling against such nepotistic regimes is difficult and risky. RiskTaker is an agent-based model we developed for testing the influences of various social forces on risk taking behavior, including the formulation of rebellious coalitions. We use RiskTaker to examine the influence of nepotism on the distribution of wealth and social status. Nepotism heavily skews the distribution of wealth and status, leading to the formation of opposing coalitions and exacerbating social unrest.This paper was tied for Best Paper, NAACSOS (North American Association for Computational Social and Organizational Science) Annual Conference 2005, June 26–28, Notre Dame. Robert Sedlmeyer, Department of Computer Science, Indiana University – Purdue University, Fort Wayne provided programming for the RiskTaker model. Lawrence A. Kuznar is a professor of anthropology and director of the Decision Sciences and Theory Institute at Indiana University—Purdue University, Fort Wayne. He has conducted fieldwork among Aymara Indians in Andean Peru and the Navajo of the American southwest. His research interests include computer modeling, theories of risk taking and conflict, terrorism, social evolution, and scientific epistemology. He has authored articles in Ecological Economics (with W. Frederick), Current Anthropology, American Anthropologist, Mathematical Anthropology and Culture Theory and Journal of Anthropological Research, and published two books (Awatimarka Harcourt Brace, 1995 and Reclaiming a Scientific Anthropology Altamira Press, 1997) and two edited volumes. William Frederick has served as a faculty member in the departments of mathematical sciences and the department of computer sciences at Indiana University—Purdue University, Fort Wayne since 1979. His primary interests include mathematical modeling, game theory, and genetic algorithms.     

Relations among Besov-type spaces,Triebel–Lizorkin-type spaces and generalized Carleson measure spaces

In this article, the authors construct some counterexamples to show that the generalized Carleson measure space and the Triebel–Lizorkin-type space are not equivalent for certain parameters, which was claimed to be true in Lin and Wang [C.-C. Lin and K.Wang, Equivalency between the generalized Carleson measure spaces and Triebel–Lizorkin-type spaces, Taiwanese J. Math. 15 (2011), pp. 919–926]. Moreover, the authors show that for some special parameters, the generalized Carleson measure space, the Triebel–Lizorkin-type space and the Besov-type space coincide with certain Triebel–Lizorkin space, which answers a question posed in Remark 6.11(i) of Yuan et al. [W. Yuan, W. Sickel and D. Yang, Morrey and Campanato Meet Besov, Lizorkin and Triebel, Lecture Notes in Mathematics 2005, Springer-Verlag, Berlin, 2010]. In conclusion, the Triebel–Lizorkin-type space and the Besov-type space become the classical Besov spaces, when the fourth parameter is sufficiently large.     

Modelling and numerical approach to a class of metal‐forming problems—Quasi‐steady case

A class of quasi‐steady metal‐forming problems, with rigid‐plastic, incompressible, strain and strain‐rate dependent material model and with unilateral frictionless and nonlinear, nonlocal Coulomb's frictional contact conditions is considered. A coupled variational formulation, constituted of a variational inequality, with nonlinear and nondifferentiable terms, and a strain evolution equation, is derived and under a restriction on the material characteristics and using a variable stiffness parameters method with time retardation, existence, uniqueness and convergence results are obtained and presented. An algorithm, combining this method and the finite element method, is proposed and applied for solving an example strip drawing problem. Copyright © 2011 John Wiley & Sons, Ltd.     

基于人体营养健康角度的中国果蔬发展建模

我国食物生产在一定程度上依然不能适应营养需求,居民营养不足与过剩并存。为了解决这个问题,本文将数据范围定位在常见的果蔬品种上,对其所含营养成分进行主成分分析和聚类,选择主要的蔬菜水果。利用损耗率和马尔可夫链,用线性回归的方法,通过对以往数据的分析,构建模型预测果蔬的消费量。进一步地,构建线性最优化模型来确定不同经济区域、不同季度的主要蔬菜水果的最合理消费量和购买成本。基于居民人体的营养均衡、购买成本、种植者收益、进出口贸易以及土地面积等多方面因素的考虑,构建多目标规划模型,寻找最优的产量和消费量。从种植产量、价格、国民营养摄入等方面向有关部门提出合理化建议。     

小区域科技实力及其评估体系

科技实力是运作主体能够进行并完成科技活动的能力。科技实力是一个评估性概念，它反映了科学技术的创新，发展，转移，推广，储备条件以及管理，效果等不同层面的综合性的特征，科技实力由科技潜在能力（科技势能），科技显现能力（科技动能）构成，它包含了对科技资源及分布状态，科技资源保障能力，科技创新能力，科技开发能力，科技转移能力和科技活动运作能力的综合描述。     

基于深度学习的交通运输业能耗预测——以“一带一路”主要经济体为例

为合理规划一次能源使用,深入推进节能减排,需对交通运输能耗进行预测.使用灰色综合关联度模型筛选出客运、货运和经济发展水平三个方面共八个影响因素作为模型输入,提出了主要由LSTM层、Dropout层和Bi-LSTM层构成的深度学习模型,并使用天牛群优化算法精调模型超参数,在此基础上对2019至2025年中国、印度、东南亚和巴基斯坦四个"一带一路"沿线经济体交通运输能耗进行预测.研究结果表明:首先,BSO-LSTM模型较GA-BPNN、GA-SVR、GA-LSTM和PSO-LSTM模型具有最高的预测精度.其次,2019-2025年,中、印、东、巴交通运输业能耗总体上在波动中上升,年均增长率分别为2.92%、5.64%、3.05%和4.88%.再次,2024年中、印、东、巴交通运输业单位GDP能耗分别为29.41、37.41、46.67和83.12,除巴基斯坦外,较2018年均有所下降.最后,中国、东南亚2018-2024年交通运输业能源消费弹性系数较2012-2018年有所下降,而印度、巴基斯坦仍保持上升趋势.     

EM 2000 Mathématiques, quel avenir?

Delivered as the closing session, this talk was supposed to be an opening towards the future, both of children and humankind. There will be problems and challenges. How is math involved? Math has permanent values, recognized by other scientists, and also stable notions, some of them going back to the ancient Greeks. However math is in a perpetual motion. Old notions get a new look, new notions appear, as well as new relations with other sciences, international relations, including developing countries, new trends and a new conception of mathematical sciences. Math teaching should express both permanence and mobility of the subject, utility and beauty. Informatics, probability and statistics, geometry and all kinds of computing are subjects of reports under preparation, for a long term view of math education.     

Computational and mathematical organization theory: Perspective and directions

Computational and mathematical organization theory is an interdisciplinary scientific area whose research members focus on developing and testing organizational theory using formal models. The community shares a theoretical view of organizations as collections of processes and intelligent adaptive agents that are task oriented, socially situated, technologically bound, and continuously changing. Behavior within the organization is seen to affect and be affected by the organization's, position in the external environment. The community also shares a methodological orientation toward the use of formal models for developing and testing theory. These models are both computational (e.g., simulation, emulation, expert systems, computer-assisted numerical analysis) and mathematical (e.g., formal logic, matrix algebra, network analysis, discrete and continuous equations). Much of the research in this area falls into four areas: organizational design, organizational learning, organizations and information technology, and organizational evolution and change. Historically, much of the work in this area has been focused on the issue how should organizations be designed. The work in this subarea is cumulative and tied to other subfields within organization theory more generally. The second most developed area is organizational learning. This research, however, is more tied to the work in psychology, cognitive science, and artificial intelligence than to general organization theory. Currently there is increased activity in the subareas of organizations and information technology and organizational evolution and change. Advances in these areas may be made possible by combining network analysis techniques with an information processing approach to organizations. Formal approaches are particularly valuable to all of these areas given the complex adaptive nature of the organizational agents and the complex dynamic nature of the environment faced by these agents and the organizations.This paper was previously presented at the 1995 Informs meeting in Los Angeles, CA.     

On a relation between the domination number and a strongly connected bidirection of an undirected graph

As a generalization of directed and undirected graphs, Edmonds and Johnson [J. Edmonds, E.L. Johnson, Matching: A well-solved class of linear programs, in: R. Guy, H. Hanani, N. Sauer, J. Schönheim (Eds.), Combinatorial Structures and their Applications, Gordon and Breach, New York, 1970, pp. 88-92] introduced bidirected graphs. A bidirected graph is a graph each arc of which has either two positive end-vertices (tails), two negative end-vertices (heads), or one positive end-vertex (tail) and one negative end-vertex (head). We extend the notion of directed paths, distance, diameter and strong connectivity from directed to bidirected graphs and characterize those undirected graphs that allow a strongly connected bidirection. Considering the problem of finding the minimum diameter of all strongly connected bidirections of a given undirected graph, we generalize a result of Fomin et al. [F.V. Fomin, M. Matamala, E. Prisner, I. Rapaport, Bilateral orientations in graphs: Domination and AT-free classes, in: Proceedings of the Brazilian Symposium on Graphs, Algorithms and Combinatorics, GRACO 2001, in: Electronics Notes in Discrete Mathematics, vol. 7, Elsevier Science Publishers, 2001] about directed graphs and obtain an upper bound for the minimum diameter which depends on the minimum size of a dominating set and the number of bridges in the undirected graph.