9,239 research outputs found
TOWARDS AN UNDERSTANDING OF EFFORTFUL FUNDRAISING EXPERIENCES: USING INTERPRETATIVE PHENOMENOLOGICAL ANALYSIS IN FUNDRAISING RESEARCH
Physical-activity oriented community fundraising has experienced an exponential growth in popularity over the past 15 years. The aim of this study was to explore the value of effortful fundraising experiences, from the point of view of participants, and explore the impact that these experiences have on peopleâs lives. This study used an IPA approach to interview 23 individuals, recognising the role of participants as proxy (nonprofessional) fundraisers for charitable organisations, and the unique organisation donor dynamic that this creates. It also bought together relevant psychological theory related to physical activity fundraising experiences (through a narrative literature review) and used primary interview data to substantiate these. Effortful fundraising experiences are examined in detail to understand their significance to participants, and how such experiences influence their connection with a charity or cause. This was done with an idiographic focus at first, before examining convergences and divergences across the sample. This study found that effortful fundraising experiences can have a profound positive impact upon community fundraisers in both the short and the long term. Additionally, it found that these experiences can be opportunities for charitable organisations to create lasting meaningful relationships with participants, and foster mutually beneficial lifetime relationships with them. Further research is needed to test specific psychological theory in this context, including self-esteem theory, self determination theory, and the martyrdom effect (among others)
The Adirondack Chronology
The Adirondack Chronology is intended to be a useful resource for researchers and others interested in the Adirondacks and Adirondack history.https://digitalworks.union.edu/arlpublications/1000/thumbnail.jp
Digital asset management via distributed ledgers
Distributed ledgers rose to prominence with the advent of Bitcoin, the first provably secure protocol to solve consensus in an open-participation setting. Following, active research and engineering efforts have proposed a multitude of applications and alternative designs, the most prominent being Proof-of-Stake (PoS). This thesis expands the scope of secure and efficient asset management over a distributed ledger around three axes: i) cryptography; ii) distributed systems; iii) game theory and economics. First, we analyze the security of various wallets. We start with a formal model of hardware wallets, followed by an analytical framework of PoS wallets, each outlining the unique properties of Proof-of-Work (PoW) and PoS respectively. The latter also provides a rigorous design to form collaborative participating entities, called stake pools. We then propose Conclave, a stake pool design which enables a group of parties to participate in a PoS system in a collaborative manner, without a central operator. Second, we focus on efficiency. Decentralized systems are aimed at thousands of users across the globe, so a rigorous design for minimizing memory and storage consumption is a prerequisite for scalability. To that end, we frame ledger maintenance as an optimization problem and design a multi-tier framework for designing wallets which ensure that updates increase the ledgerâs global state only to a minimal extent, while preserving the security guarantees outlined in the security analysis. Third, we explore incentive-compatibility and analyze blockchain systems from a micro and a macroeconomic perspective. We enrich our cryptographic and systems' results by analyzing the incentives of collective pools and designing a state efficient Bitcoin fee function. We then analyze the Nash dynamics of distributed ledgers, introducing a formal model that evaluates whether rational, utility-maximizing participants are disincentivized from exhibiting undesirable infractions, and highlighting the differences between PoW and PoS-based ledgers, both in a standalone setting and under external parameters, like market price fluctuations. We conclude by introducing a macroeconomic principle, cryptocurrency egalitarianism, and then describing two mechanisms for enabling taxation in blockchain-based currency systems
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Mixture Models in Machine Learning
Modeling with mixtures is a powerful method in the statistical toolkit that can be used for representing the presence of sub-populations within an overall population. In many applications ranging from financial models to genetics, a mixture model is used to fit the data. The primary difficulty in learning mixture models is that the observed data set does not identify the sub-population to which an individual observation belongs. Despite being studied for more than a century, the theoretical guarantees of mixture models remain unknown for several important settings.
In this thesis, we look at three groups of problems. The first part is aimed at estimating the parameters of a mixture of simple distributions. We ask the following question: How many samples are necessary and sufficient to learn the latent parameters? We propose several approaches for this problem that include complex analytic tools to connect statistical distances between pairs of mixtures with the characteristic function. We show sufficient sample complexity guarantees for mixtures of popular distributions (including Gaussian, Poisson and Geometric). For many distributions, our results provide the first sample complexity guarantees for parameter estimation in the corresponding mixture. Using these techniques, we also provide improved lower bounds on the Total Variation distance between Gaussian mixtures with two components and demonstrate new results in some sequence reconstruction problems.
In the second part, we study Mixtures of Sparse Linear Regressions where the goal is to learn the best set of linear relationships between the scalar responses (i.e., labels) and the explanatory variables (i.e., features). We focus on a scenario where a learner is able to choose the features to get the labels. To tackle the high dimensionality of data, we further assume that the linear maps are also sparse , i.e., have only few prominent features among many. For this setting, we devise algorithms with sub-linear (as a function of the dimension) sample complexity guarantees that are also robust to noise.
In the final part, we study Mixtures of Sparse Linear Classifiers in the same setting as above. Given a set of features and the binary labels, the objective of this task is to find a set of hyperplanes in the space of features such that for any (feature, label) pair, there exists a hyperplane in the set that justifies the mapping. We devise efficient algorithms with sub-linear sample complexity guarantees for learning the unknown hyperplanes under similar sparsity assumptions as above. To that end, we propose several novel techniques that include tensor decomposition methods and combinatorial designs
Karttatypografia: luettavuuden parantaminen kirjainmuotoilun keinoin topografisissa kartoissa
This thesis examines the legibility of type on maps and aims to find out ways to improve it through type design. As type often is an integral part of maps â something that helps the map user navigate, understand, and perceive a wide range of information in an effective way â type design and legibility must be regarded as important design elements. However, even though cartography and typography have extensive theoretical bases, the subject of legibility has not been comprehensively researched in cartographic context. Thus, by combining type design theory and scientific legibility studies with cartographic theory, the legibility of type on maps could be improved.
The topic is first studied by an extensive literature review to cover existing concepts and theories of cartography, cartographic typography, and typography. After a competent knowledge basis of these concepts and theories is acquired, the findings are utilised in the design component. The design component is a type family designed specifically to be used with topographic maps: it consists of two elements, a project description that follows the design process of the type family, relating design choices to the theoretical findings and perspectives presented in the literary review, and the finished type family. In conclusion of the design component, several visual studies are made both to compare the design component (type family) to other relevant typefaces, and to validate the possible functionality of the design component in the chosen cartographic application (topographic map).
A broad understanding of the topics of the literature review was formed. Cartographic theory observed the overall nature of maps and specified the various map elements and their intended uses. Cartographic typography deepened the understanding of type on maps â it highlighted the specific needs that must be taken into consideration, demonstrated the diversity of typographic situations that might occur, and presented a large set of guidelines to help the mapmaker to achieve better results. Typography and type design focused on the micro-level of type: how the minor design choices affect the whole, and furthermore, through legibility studies, validated certain views and brought new topics into consideration. By combining theoretical literature from these domains, this thesis helped to form a foundation for an improved framework for type de-sign for (topographic) maps. Furthermore, the domains of cartographic typography and typography and type design gave clear suggestions on how the legibility of type on topographic maps can be improved: legibility of type in this context constitutes from multiple components that must be both taken into consideration and be applied to processes of mapmaking and type design.TĂ€ssĂ€ opinnĂ€ytetyössĂ€ tutkitaan karttatypografiaa ja pyritÀÀn löytĂ€mÀÀn keinoja parantaa luettavuutta kirjainmuotoilun keinoin. Teksti on usein elimellinen osa karttoja: se helpottaa kartan kĂ€yttĂ€jÀÀ navigoimaan ja sisĂ€istĂ€mÀÀn suuren mÀÀrĂ€n informaatiota tehokkaasti. SiispĂ€ kirjainmuotoilua ja luettavuutta tulee pitÀÀ tĂ€rkeinĂ€ karttasuunnittelun työkaluina. Vaikka sekĂ€ kartografiassa ettĂ€ typografiassa on olemassa laajat teoreettiset perustat, luettavuutta ei ole kattavasti tutkittu kartografisessa kontekstissa. YhdistĂ€mĂ€llĂ€ kirjainmuotoilun ja tieteelliset luettavuustutkimukset kartografiseen teoriaan, karttatekstien luettavuutta voidaan parantaa.
Aluksi tutustutaan olemassa oleviin konsepteihin ja kartografisiin teorioihin kattavan kirjallisuuskatsauksen avulla. Kun tarpeellinen tietopohja on rakennettu, saavutettua tietÀmystÀ hyödynnetÀÀn opinnÀytetyön projektiosassa, joka tÀssÀ tapauksessa on topografisten karttojen yhteydessÀ kÀytettÀvÀ kirjainperhe. Projektiosio on kaksijakoinen ja pitÀÀ sisÀllÀÀn sekÀ valmiin kirjainperheen, ettÀ projektikuvauksen. Projektikuvaus seuraa suunnitteluprosessia ja peilaa tehtyjÀ valintoja kirjallisuuskatsauksessa esiteltyihin löydöksiin. Projektiosion pÀÀtelmÀssÀ tutkitaan visuaalisesti kirjainperheen toimintaa ja kÀyttökelpoisuutta topografisessa karttaympÀristössÀ, sekÀ verrataan kirjainperheen toimivuutta suhteessa muihin kirjaintyyppeihin.
Tutkimuksen perusteella muodostuu laaja ymmĂ€rrys aiheesta. Kartografinen teoria valottaa yleisesti karttojen olemusta ja toimintaa, sekĂ€ esittelee erilaisia karttalementtejĂ€ ja niiden toimintatapoja. Karttatypografian teoria syventÀÀ ymmĂ€rrystĂ€ tekstin kĂ€yttĂ€ytymisestĂ€ karttaympĂ€ristössĂ€, esittelee karttatypografian erityispiirteitĂ€, ja tarjoaa laajan karttatypografisen ohjeiston. Typografian ja kirjainmuotoilun teoria keskittyy mikrotason aiheisiin: kuinka vĂ€hĂ€pĂ€töisiltĂ€ vaikuttavat suunnitteluvalinnat vaikuttavat kokonaisuuteen, ja kuinka luettavuustutkimukset auttavat nĂ€kemÀÀn asioita uudessa valossa. TĂ€mĂ€ opinnĂ€ytetyö auttaa parantamaan kirjainmuotoilua (topografisessa) karttaympĂ€ristössĂ€ yhdistĂ€mĂ€llĂ€ edellĂ€ mainittujen alojen teorioita keskenÀÀn ja pohjustamalla paranneltuja suunniteluvalintoja. Yhdistetty teoria viittaa selkeĂ€sti siihen, ettĂ€ luettavuus karttaympĂ€ristössĂ€ koostuu lukuisista osatekijöistĂ€ â nĂ€mĂ€ osatekijĂ€t tulee ymmĂ€rtÀÀ, ottaa huomioon, ja soveltaa sekĂ€ karttojen ettĂ€ niille suunniteltujen kirjaintyyppien suunnitteluprosesseissa
BECOMEBECOME - A TRANSDISCIPLINARY METHODOLOGY BASED ON INFORMATION ABOUT THE OBSERVER
ABSTRACT
Andrea T. R. Traldi
BECOMEBECOME
A Transdisciplinary Methodology Based on Information about the Observer
The present research dissertation has been developed with the intention to provide practical strategies and discover new intellectual operations which can be used to generate Transdisciplinary insight. For this reason, this thesis creates access to new knowledge at different scales.
Firstly, as it pertains to the scale of new knowledge generated by those who attend Becomebecome events. The open-source nature of the Becomebecome methodology makes it possible for participants in Becomebecome workshops, training programmes and residencies to generate new insight about the specific project they are working on, which then reinforce and expand the foundational principles of the theoretical background.
Secondly, as it pertains to the scale of the Becomebecome framework, which remains independent of location and moment in time. The method proposed to access Transdisciplinary knowledge constitutes new knowledge in itself because the sequence of activities, described as physical and mental procedures and listed as essential criteria, have never been found organised
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in such a specific order before. It is indeed the order in time, i.e. the sequence of the ideas and activities proposed, which allows one to transform Disciplinary knowledge via a new Transdisciplinary frame of reference.
Lastly, new knowledge about Transdisciplinarity as a field of study is created as a consequence of the heretofore listed two processes.
The first part of the thesis is designated âBecomebecome Theoryâ and focuses on the theoretical background and the intellectual operations necessary to support the creation of new Transdisciplinary knowledge. The second part of the thesis is designated âBecomebecome Practiceâ and provides practical examples of the application of such operations. Crucially, the theoretical model described as the foundation for the Becomebecome methodology (Becomebecome Theory) is process-based and constantly checked against the insight generated through Becomebecome Practice.
To this effect, âinformation about the observerâ is proposed as a key notion which binds together Transdisciplinary resources from several studies in the hard sciences and humanities. It is a concept that enables understanding about why and how information that is generated through Becomebecome Practice is considered of paramount importance for establishing the reference parameters necessary to access Transdisciplinary insight which is meaningful to a specific project, a specific person, or a specific moment in time
Multi-parametric Analysis for Mixed Integer Linear Programming: An Application to Transmission Planning and Congestion Control
Enhancing existing transmission lines is a useful tool to combat transmission
congestion and guarantee transmission security with increasing demand and
boosting the renewable energy source. This study concerns the selection of
lines whose capacity should be expanded and by how much from the perspective of
independent system operator (ISO) to minimize the system cost with the
consideration of transmission line constraints and electricity generation and
demand balance conditions, and incorporating ramp-up and startup ramp rates,
shutdown ramp rates, ramp-down rate limits and minimum up and minimum down
times. For that purpose, we develop the ISO unit commitment and economic
dispatch model and show it as a right-hand side uncertainty multiple parametric
analysis for the mixed integer linear programming (MILP) problem. We first
relax the binary variable to continuous variables and employ the Lagrange
method and Karush-Kuhn-Tucker conditions to obtain optimal solutions (optimal
decision variables and objective function) and critical regions associated with
active and inactive constraints. Further, we extend the traditional branch and
bound method for the large-scale MILP problem by determining the upper bound of
the problem at each node, then comparing the difference between the upper and
lower bounds and reaching the approximate optimal solution within the decision
makers' tolerated error range. In additional, the objective function's first
derivative on the parameters of each line is used to inform the selection of
lines to ease congestion and maximize social welfare. Finally, the amount of
capacity upgrade will be chosen by balancing the cost-reduction rate of the
objective function on parameters and the cost of the line upgrade. Our findings
are supported by numerical simulation and provide transmission line planners
with decision-making guidance
Investigation of cytotoxic properties of some heterocyclic derivatives by molecular modeling
Currently, many technologies have been adopted to boost the efficiency of drugdevelopment and overcome obstacles in the drug discovery pipeline. The application of these approaches spans a wide range, from bioactivity predictions, de novo compound synthesis, target identification to hit discovery, and lead optimization. This dissertation comprises two studies. First, we proposed an original approach based on statistical consideration dedicated to k-means clustering analysis in order to define a set of rules for structural features that would help in designing novel anti-cancer drug candidates. It has been applied successfully to classify 500 cytotoxic compounds with 21 molecular descriptors into distinct clusters. The percentage of molecules in each cluster is 50%, 24.88%, and 25.12% for cluster 1, cluster 2, and cluster 3, respectively. Each cluster groups a homogeneous class of molecules with respect to their molecular descriptors. Silhouette analysis, used as a cluster validation approach proves that the molecules are very well clustered, and there are no molecules placed in the wrong cluster. In silico screening of pharmacological properties ADME and evaluation of drug-likeness were performed for all molecules. The quantitative analysis of molecular electrostatic potential was performed to identify the nucleophilic and electrophilic sites in the representative molecule of each cluster. In addition, a molecular docking study was carried
out to investigate the interactions of the paragon molecules with the active binding sites of six different targets. Our findings provide a guide to assist the chemist in selecting and testing only the potential molecules with good pharmacokinetic profiles to improve the clinical outcomes of drug therapies.
Second, a simulation-based investigation was conducted to examine the CHK1 inhibitory activity of cytotoxic xanthone derivatives using a hierarchical workflow for molecular docking, MD simulation, ADME-TOX prediction, and MEP analysis. A molecular docking study was conducted for the forty-three xanthone derivatives along with standard Prexasertib into the selected CHK1 protein structures 7AKM and 7AKO. Furthermore, MD studies support molecular docking results and validate the stability of studied complexes in physiological conditions. Moreover, in silico ADME-TOX studies are used to predict the
pharmacokinetic, pharmacodynamic, and toxicological properties of the selected eight
xanthones and the standard Prexasertib. The quantitative analysis of electrostatic potential was performed for the lead compound L36 to identify the reactive sites and possible noncovalent interactions. Our study provides new unexplored insights into xanthones as CHK1 inhibitors and identified L36 as a potential drug candidate that could undergo further in vivo assays and optimization, laying a solid foundation for the development of CHK1 inhibitors and cancer drug discovery. To the best of our knowledge, this is the first time such a study was conducted for the xanthones with CHK1 by using a computational based approach
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