196 research outputs found
The rate of beneficial mutations surfing on the wave of a range expansion
No full textMany theoretical and experimental studies suggest that range expansions can have severe consequences for the gene pool
of the expanding population. Due to strongly enhanced genetic drift at the advancing frontier, neutral and weakly
deleterious mutations can reach large frequencies in the newly colonized regions, as if they were surfing the front of the
range expansion. These findings raise the question of how frequently beneficial mutations successfully surf at shifting range
margins, thereby promoting adaptation towards a range-expansion phenotype. Here, we use individual-based simulations
to study the surfing statistics of recurrent beneficial mutations on wave-like range expansions in linear habitats. We show
that the rate of surfing depends on two strongly antagonistic factors, the probability of surfing given the spatial location of
a novel mutation and the rate of occurrence of mutations at that location. The surfing probability strongly increases towards
the tip of the wave. Novel mutations are unlikely to surf unless they enjoy a spatial head start compared to the bulk of the
population. The needed head start is shown to be proportional to the inverse fitness of the mutant type, and only weakly
dependent on the carrying capacity. The precise location dependence of surfing probabilities is derived from the nonextinction
probability of a branching process within a moving field of growth rates. The second factor is the mutation
occurrence which strongly decreases towards the tip of the wave. Thus, most successful mutations arise at an intermediate
position in the front of the wave. We present an analytic theory for the tradeoff between these factors that allows to predict
how frequently substitutions by beneficial mutations occur at invasion fronts. We find that small amounts of genetic drift
increase the fixation rate of beneficial mutations at the advancing front, and thus could be important for adaptation during
species invasions
Art of Analysis
No full textArt of Analysis (AoA) is a nationally-recognized partnership between the Columbus Museum of Art (CMA) and the Ohio State University Medicine and the Arts (Ohio State M&A) initiative. AoA uses art as a catalyst for conversation and collaboration, fostering a range of skills essential for student wellness, quality medical care, and resilience in a high burnout field. The session takes AoA as a case study to explore what makes a meaningful, sustainable partnership for wellness and growth. Presenters will 1) recreate a portion of the AoA experience; 2) highlight key aspects of wellness fostered through the experience; 3) identify elements that support success and present challenges; and 4) support participants to generate ideas for taking these lesson to their own contexts. Art of Analysis brings students and faculty from medical sciences across Ohio State to CMA for an evening of in-gallery, facilitated discussion. Participants practice critical and creative thinking habits, including careful observation, questioning assumptions, collaborative thinking, reasoning with evidence, and adopting multiple perspectives. AoA began in 2010 as an approach to fostering observation skills and comfort with ambiguity – both crucial skillsets for diagnosis and treatment, and both identified as growth areas for medical students by the then-dean of the College of Medicine. Evaluations revealed participant perception that AoA supported their observation skills and shifted their thinking about the role of ambiguity/developing and reasoning through multiple interpretations. Evaluations also surfaced emergent, highly-valuable outcomes: students reported: feeling compassion for subjects of works of art, valuing the exploration of points of view different from their own, gaining appreciation for peers' perspectives, and cherishing the time to slow down. In other words, the experience created the opportunity to build empathetic behaviors necessary for the human work of medicine, and provided participants with self-care strategies to support resilience as students and medical professionals. Based on these findings, AoA has evolved to explicitly support a broader range of critical, creative and empathetic dispositions. The session advocates that these dispositions are essential for individual and community wellness, and supports attendees to think in fresh ways about deeply-meaningful partnerships for their own contexts. AoA is the subject of an article in the Journal of Learning Through the Arts. Session presenters Jennifer Lehe (manager of strategic partnerships, CMA) and Dr. Linda Stone, MD (special assistant to the dean for humanism and professionalism, Ohio State COM) presented AoA at a national convening of medical school-art museum partnerships (Art of Examination, 2016 MoMA). Art of Analysis is part of Ohio State's Medicine and the Arts Initiative, for which Dr. Stone was awarded the 2017 Governor's Awards for the Arts for Community Development and Participation.AUTHOR AFFILIATION: Jennifer Lehe, Manager of Strategic Partnerships, Columbus Museum of Art, Ohio State Medicine and the Arts Board, [email protected] (Corresponding Author); Linda Stone, MD, Special Assistant to the Dean for Humanism and Professionalism, Ohio State College of Medicine, Ohio State Medicine and the Arts Board, Ohio State Medical Humanities.Art of Analysis (AoA) is a nationally-recognized partnership between the Columbus Museum of Art (CMA) and The Ohio State University Medicine and the Arts (OSU M&A). Attendees will explore the partnership, which brings students and faculty from Ohio State medical sciences to CMA for an evening of facilitated discussion with art. AoA participants practice critical, creative, and empathetic thinking, including close observation, questioning assumptions and adopting multiple perspectives. Learn how presenters co-created and evolved a program to support wellness and learning for students by capitalizing on the expertise of art museum educators and emergent outcomes. The presenters advocate that the dispositions fostered in AoA are essential for indivi-dual and community wellness, while supporting participants to think in fresh ways about deeply meaningful partnerships. Attendees will have time to generate and receive input on ideas for their own contexts
Tasuta lehe kontseptsioon ja ärimudel. Tasuta lehe ärimudeli toimimine Eestis
No full textThe present study tries to analyze in the discourse of media economics the area not
studied in Estonia yet – the conception and business model of free papers.
Before starting with concrete Estonian cases the author considered it important to give
an overview of the conception and circulation strategies of free papers in the world,
first of all of the economically successful Metro.
The aim of the research is to study how structural changes in the Estonian media and
media use in the 1990s created favourable conditions for the emergence of free papers
in 1997. It appeared that free papers which emerged during the heavy competition
between the two media concerns fulfilled media political aim quite efficiently without
achieving the expected economic success.
To prove the above-mentioned facts, the author analyzes relying on certain economic
data the reasons of the economic failure of the free Tartu paper Tartu Börs. The
analysis revealed that business model of a certain channel contains so many factors,
that the model successfully functioning at one market does not function well in other
market conditions. The economic success of free papers in Estonia is opposed by the
small size of the market, absence of great travelling junctions and the factor that in
Estonia free papers emerged as a result of competition between media concerns.
The publishers of the free papers tried to follow the circulation and content
conception of the successful Metro but did not carry out fundamental analysis of the
situation on the advertising market, which is more important than barriers in entering the market. Another important obstacle was the fact, that free papers created an
unexpected inner competition with other publications on advertising market and the
publisher concentrated on ad sale.
From the point of view of academic discourse, the analysis of free papers as a case in
media economics, is limited from the one hand, as benefits and costs of a free paper as
a part of a media concern cannot be completely controlled. On the other hand, it is a
good case. For establishing the tradition of the analysis in media economics it is better
to start with a more simple case – free paper, the publishing expenses of which are
smaller compared to paid paper and the only source of income is the time and
attention of the reader materializing in advertizing profits.http://tartu.ester.ee/record=b1629952~S1*es
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Inclusionary Zoning in a Monocentric City
No full textTo show how inclusionary zoning alters development, the author finds the most profitable housing design to build on vacant lots at each location in a monocentric city under different regulatory regimes. Section 1 sets up the model by specifying renter's preferences, geography and building parameters. Section 2 solves the developer's profit-maximization problem at each location under each regime. Finally, in Section 3, a numerical simulation confirms the effects predicted by theory and gives a picture of their magnitude
Resource allocation and pricing under competition in shared mobility markets
No full textShared mobility services, such as those involving shared rides and shared cars/bikes, are becoming important components of urban transportation systems. There are various advantages of shared mobility, including: (i) significant societal benefit to our environment; for example, bikesharing is considered as a promising way to reduce traffic congestion, harmful gas emissions, and fuel consumption (Qiu and He, 2018); (ii) economic benefits to users, by reducing their travel costs especially those related to owning and maintaining a vehicle; (iii) increased accessibility of users, e.g., by bridging the spatiotemporal gaps in existing transportation service networks (Shaheen et al., 2016); and (iv) creation of new job opportunities; for example, in 2014, the Uber platform created 20,000 new jobs each month (Eadicicco, 2014).
Nevertheless, fierce competition and lack of strategic planning have led to repeated failures of shared mobility services in many cities. For example, oversupply and poor management of bikes – partly due to competition among bikesharing companies – have proven to be counter productive, causing huge wastes of resources and significant societal disbenefits in some countries. The service providers face lots of challenges in their daily operations. For example, in a ridesharing market, significant imbalance between spatiotemporal distributions of vehicle supply and travel demand mandates companies to allocate their resources (e.g., vehicles and drivers) and design pricing strategies optimally to incentivize demand and maximize their profits. It is even more challenging for the service providers to make optimal operation decisions when there are multiple companies in a shared mobility market. For example, in a bikesharing market, where the market share depends on how the competing companies deploy their bikes over time and space as well as how they make pricing decisions, each individual company needs to maximize its profit through optimal pricing, investment, and allocation/rebalancing strategies, in response to not only time-varying demand but also actions of the fellow competitors.
All the above challenges highlight the urgent needs for a systematic modeling framework to analyze the optimal investment, management, and pricing strategies for these companies under competition. This Ph.D. dissertation aims at investigating several important topics in competitive shared mobility markets (both ridesharing and vehicle sharing), including: (i) dynamic pricing and resource allocation in an on-demand ridesharing market; (ii) pricing and matching in a two-sided ridesharing market under competition; (iii) optimal investment and management of dockless shared bikes in a competitive market; and (iv) pricing and resource allocation in a docked bikesharing market under competition.
First, we propose a multi-period game-theoretic model that addresses dynamic pricing and idling vehicle dispatching problems in a one-sided ridesharing market (i.e., with fully compliant drivers/vehicles). A dynamic mathematical program with equilibrium constraints (MPEC) is formulated to capture the interdependent decision-making processes of the mobility service provider (e.g., regarding vehicle allocation) and travelers (e.g., regarding ridesharing and travel path options). An algorithm based on approximate dynamic programming (ADP), with customized subroutines for solving the MPEC, is developed to solve the overall problem. It is shown with numerical experiments that the proposed dynamic pricing and vehicle dispatching strategy can help ridesharing service providers achieve better system performance (as compared with myopic policies) while facing spatial and temporal variations in ridesharing demand.
Then we study the competition between two companies in a two-sided ridesharing market. The two companies share and compete for drivers and riders, and each company optimizes its pricing and driver-rider matching strategies to maximize its profit. The competition is modeled as a generalized Nash equilibrium problem (GNEP). We consider the independent decision-making process of drivers and riders, and show that the game is a potential game which can be solved by systematic approaches. We then investigate the impact of competition and draw managerial insights through a series of hypothetical numerical experiments.
Next, we shift our attention from ridersharing to bikesharing. We develop a game-theoretical framework to model the competition between two bikesharing companies in a dockless bikesharing market. A two-stage multi-period stochastic program is developed to model the decision process of each company regarding the number and spatiotemporal distribution of bikes in a city. The effects of demand elasticity and uncertainty are also discussed. We then show the existence of Nash equilibrium and analytical insights into the solution for several special cases. For general cases, an iterative algorithm is proposed to solve the Nash equilibrium. Numerical experiments are conducted to demonstrate the applicability of the proposed model and to draw insights into the impacts of market competition.
Finally, we consider the competition between two companies in a docked bikesharing market, where the additional decisions on dock-station installation and pricing decisions are also addressed. We model the competition as a GNEP, in which the users’ behaviors are modeled using a set of logical constraints. We then develop reformulation approaches to convert the nonlinear model into a linear one and show how the equilibrium of the GNEP can be obtained. We demonstrate the optimal decisions for the companies, and investigate the market property under competition through hypothetical and real-world case studies.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-08-01The student, Zhoutong Jiang, accepted the attached license on 2021-07-12 at 15:58.The student, Zhoutong Jiang, submitted this Dissertation for approval on 2021-07-12 at 18:56.This Dissertation was approved for publication on 2021-07-13 at 15:32.DSpace SAF Submission Ingestion Package generated from Vireo submission #16873 on 2022-01-12 at 12:54:38Made available in DSpace on 2022-01-12T22:35:11Z (GMT). No. of bitstreams: 2
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Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Onl
Polynomial approximations for fast predictive analysis of infrastructure systems: Applications to power and transportation systems
No full textThe student, Negin Alemazkoor, accepted the attached license on 2019-08-21 at 11:03.The student, Negin Alemazkoor, submitted this Dissertation for approval on 2019-08-21 at 11:17.This Dissertation was approved for publication on 2019-08-23 at 09:36.DSpace SAF Submission Ingestion Package generated from Vireo submission #14431 on 2020-02-28 at 17:35:12Made available in DSpace on 2020-03-02T22:38:34Z (GMT). No. of bitstreams: 2
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Previous issue date: 2019-08-23Embargo set by: Seth Robbins for item 113963
Lift date: 2022-03-02T22:39:04Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 113963 on 2022-03-03T10:15:27Z.Infrastructure systems are complex networks with inherent sources of uncertainty. Optimal operation of these systems directly affects the welfare of society. Accurate analysis and predictions for infrastructure systems are vital to achieve optimal management and operation. Data for predictive analysis can be from different sources, including computationally expensive system simulations or sensors placed within the system. For a reliable predictive analysis, it is necessary to (a) incorporate significant uncertainty in behavior of the system induced by inherent variability of system components, and (b) capture the changes within the system and adjust the predictions accordingly. This study aims to address some of the main challenges regarding these two pillars of a reliable predictive analysis for infrastructure systems.
Specifically, consider power transmission or distribution systems, where computationally expensive power flow simulations must be run to evaluate the future state of the system. Conventionally, uncertain variables, such as power consumption, are treated as deterministic variables. This can result in unreliable predictions and consequently suboptimal decisions. On the other hand, quantifying the uncertainty in the system's state using sampling approaches may require thousands of simulations and can be computationally intractable. To reduce the computational burden, full scale simulations should be replaced with analytical surrogates such as polynomial functions, radial basis functions, and Gaussian processes. Accuracy of these surrogates directly affects the accuracy of system analysis and the optimality of the decisions made based on the analysis. In this dissertation, we focus on polynomial surrogates and develop innovative methodologies to improve the accuracy of the polynomial surrogates. We use several numerical examples to validate the efficiency and accuracy of the proposed methodologies. Also, as demonstration on the application side, we apply the developed methodologies to a power distribution system with various uncertainty, such as power generation and consumption uncertainty. The results demonstrate that our proposed approaches substantially reduce the computational cost associated with probabilistic power flow analysis and probabilistic system control.
Additionally, for the cases that data is constantly streaming from the sensors within the system, a computationally fast online predictive model is introduced, that is capable of adjusting the predictions once system faces significant disruptions. The efficiency and accuracy of the proposed approach is demonstrated using a real-world extreme scenario, namely the Woolsey wildfire in California, following which traffic patterns significantly changed. Specifically, we study traffic conditions in locations close to the wildfire and show that the proposed approach can capture and accurately predict the post-disaster changes.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-12-0
The Growth and Phenology of Curly Birch (Betula pendula var. carelica) Clones
No full textUurimistöö viidi läbi Järvselja õppe- ja katsemetskonna territooriumile 2012. sügisel
rajatud maarjakase (Betula pendula var. carelica) geograafilisel katsealal.
Katsekultuuri pindala on 0,36 hektarit ja kuhu on kultiveeritud kaheksa erineva Soome
maarjakase klooni taimi.
Magistritöö eesmärgiks on analüüsida erinevate kloontaimede kasvu, arengut ning
fenoloogiat, milleks mõõdeti ja analüüsiti erinevate kloonide takseertunnuseid (kõrgus,
kahe aasta kõrguse juurdekasvud, juurekaela diameeter), fotosünteesi aktiivsust
iseloomustavad parameetreid (netoassimilatsioon, õhulõhede juhtuvus ja
süsihappegaasi kontsentratsiooni muutus), lehe anatoomiat (lehe pindala, õhulõhede
tihedus) ja võra haabitust. Saadud tulemuste põhjal anti soovitused Eesti kliimasse
sobilike maarjakase kloontaimede kasutamiseks maarjakasekultuuride rajamisel.
Töö tulemusena selgus, et pärilikkusel on oluline mõju taimede kasvule. Samuti olid
erinevate kloonide fotosünteesi parameetrid ja lehtede mõõtmed ning õhulõhede
tihedus erinevad. Ladvavõrsel asuvate lehtede fotosünteesi aktiivsus oli kõrgem kui
külgvõrsel asuvatel lehtedel. Laasitud puude netoassimilatsioonimäär ja süsihappegaasi
kontsentratsiooni muutus olid suuremad kui laasimata puudel. Õhulõhede juhtivuses
aga laasitud ja laasimata puudel erinevusi ei esinenud. Kloonide lõikes olid erinevad ka
keskmised lehtede pindalad, õhulõhede tihedus ja õhulõhede arv. Samuti selgus, et
ladvavõrse lehed olid suuremad kui külgvõrse lehed. Õhulõhede tihedus ei sõltunud
lehe asukohast võrsel.
Saadud tulemuste põhjal võib väita, et Eesti kliimasse sobib kõige paremini Soome
maarjakase kloon Pertunmaa (E-10524), samuti on heade kasvuparameetritega ka
kloon Kerimäki (E-8306).The research was carried through at a comparative experimental plot of curly birches at
Järvselja. The comparitive experimental plots area is 0.36 hectars and 360 trees were
planted there, cloned from 8 different mother trees.
The purpose of this masters thesis is to compare plants height, diameter photosythesis
parameters(netassimilation ratio, stomatal conductance and carbon dioxide
concentration change), leaf anatomy(area and stomatal density) and crown shape are
analysed. The author gives a recommendation by using the analysis’ results about
which curly birch clones are suitable for growing in the Estonian climate and which are
not.
The results of the analysis were that heredity has an important influence on the plants
growth. The growth, photosynthesis parameters, leaf areas and stomatal density of
different clones were different. The leaves from the treetop shoots had a higher
photosynthesis activity than the rest of the leaves. The net assimilation ratio and carbon
dioxide concentration change was bigger for pruned trees than non-pruned trees. The
stomatal conductance was not different for pruned and non-pruned trees. The leaf area,
stomatal density and stomatal count per leaf is different for separate clones. It was also
found that the treetop leaves were bigger. The stomatal density didn’t depend on the
leaves location.
The author claimes, by different compared parameters, that the clone Pertunmaa (E-
10524) is the the best for the Estonian climate and the clone Kerimäki (E-8306) has
good parameters as well
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