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Article: How We Come to Value Nature? - A Pragmatist Perspective

Peltola, Taru / Isabelle Arpin

Ecological economics. 2017 Dec., v. 142

2017

Abstract: Valuation studies have been mobilized to demonstrate the importance of nature to society and to incorporate concerns about nature into decision making. Although increasingly popular in ecosystem service research, such studies have also been criticized. ... ...

Abstract	Valuation studies have been mobilized to demonstrate the importance of nature to society and to incorporate concerns about nature into decision making. Although increasingly popular in ecosystem service research, such studies have also been criticized. In particular, tensions between the assumptions of valuation methods and the real-life processes of valuing have been identified. This article argues that a process-based, pragmatist approach to valuing helps to evaluate the relevance of valuation studies results. Pragmatism proposes a focus on activities through which people come to value natural elements in their everyday life rather than on the outcomes of valuing processes. Using this approach we examine three empirical cases: 1) restoration of natural springs in Finland; 2) protection of the bearded vulture in the French Alps; and 3) management of urban biodiversity in the City of Grenoble, France. Through these cases we demonstrate how nature's value to people emerges from commonplace ways of engaging with natural elements, such as domestication, inheriting and community building. We conclude by discussing the usefulness of acknowledging this kind of processes in nature conservation.
Keywords	biodiversity ; decision making ; domestication ; ecosystem services ; natural resources conservation ; people ; society ; springs (water) ; Alps region ; Finland ; France
Language	English
Dates of publication	2017-12
Size	p. 12-20.
Publishing place	Elsevier B.V.
Document type	Article
ISSN	0921-8009
DOI	10.1016/j.ecolecon.2017.06.009
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Phenotype-driven identification of epithelial signalling clusters.

Marques, Elsa / Peltola, Tomi / Kaski, Samuel / Klefström, Juha

Scientific reports

2018 Volume 8, Issue 1, Page(s) 4034

Abstract: In metazoans, epithelial architecture provides a context that dynamically modulates most if not all epithelial cell responses to intrinsic and extrinsic signals, including growth or survival signalling and transforming oncogene action. Three-dimensional ( ...

Abstract	In metazoans, epithelial architecture provides a context that dynamically modulates most if not all epithelial cell responses to intrinsic and extrinsic signals, including growth or survival signalling and transforming oncogene action. Three-dimensional (3D) epithelial culture systems provide tractable models to interrogate the function of human genetic determinants in establishment of context-dependency. We performed an arrayed genetic shRNA screen in mammary epithelial 3D cultures to identify new determinants of epithelial architecture, finding that the key phenotype impacting shRNAs altered not only the data population average but even more noticeably the population distribution. The broad distributions were attributable to sporadic gene silencing actions by shRNA in unselected populations. We employed Maximum Mean Discrepancy concept to capture similar population distribution patterns and demonstrate here the feasibility of the test in identifying an impact of shRNA in populations of 3D structures. Integration of the clustered morphometric data with protein-protein interactions data enabled hypothesis generation of novel biological pathways underlying similar 3D phenotype alterations. The results present a new strategy for 3D phenotype-driven pathway analysis, which is expected to accelerate discovery of context-dependent gene functions in epithelial biology and tumorigenesis.
MeSH term(s)	Cell Line ; Cell Transformation, Neoplastic ; Epithelial Cells/metabolism ; Humans ; Phenotype ; Signal Transduction
Language	English
Publishing date	2018-03-05
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-018-22293-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Re-inventing forestry expertise: Strategies for coping with biodiversity protection in Finland

Peltola, Taru / Johanna Tuomisaari

Forest policy and economics. 2016 Jan., v. 62

2016

Abstract: Tackling biodiversity loss requires new forms of expertise in forestry. Drawing on a case study in Finland, the paper analyses how professional foresters are invited to protect the heterogeneity of forest ecosystems while they simultaneously work to ... ...

Abstract	Tackling biodiversity loss requires new forms of expertise in forestry. Drawing on a case study in Finland, the paper analyses how professional foresters are invited to protect the heterogeneity of forest ecosystems while they simultaneously work to homogenise these habitats for improved productivity. To understand how formerly irrelevant biological knowledge, and related skills and expertise gain credibility in forestry decision-making in such a complex policy context, the paper adopts a two-fold theoretical approach. On one hand, it focuses on the tools and techniques which redirect expert practice, introducing new rationalities, roles and routines for professional foresters. On the other hand, it seeks to view foresters as complex sociological actors who reinvent themselves as biodiversity experts by strategically mobilising various kinds of resources to negotiate their role and status as experts. This two-fold analysis addresses how the status of biological knowledge is determined by the tension between formally configured expert rationalities and expert identities and roles mobilised through informal interactions. Three expert strategies in engaging with biodiversity are identified based on the personal histories, motivations and identities of the foresters: the ambassador, navigator and bolshie. Through these strategies professional foresters interact with each other and with landowners while implementing biodiversity policies, hence influencing the policy outcomes.
Keywords	biodiversity ; case studies ; coping strategies ; decision making ; experts ; forest ecosystems ; foresters ; forestry ; habitats ; issues and policy ; landowners ; motivation ; Finland
Language	English
Dates of publication	2016-01
Size	p. 11-18.
Publishing place	Elsevier B.V.
Document type	Article
ISSN	1389-9341
DOI	10.1016/j.forpol.2015.10.005
Database	NAL-Catalogue (AGRICOLA)

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Article: Value capture in business ecosystems for municipal solid waste management: Comparison between two local environments

Peltola, T / E. Viana / L. Aarikka-Stenroos / S. Mäkinen

Journal of cleaner production. 2016 Nov. 20, v. 137

2016

Abstract: The increasing amount of global waste reflects the social, environmental, and economic trajectories of the local environment. This study addresses this multifaceted problem that requires a holistic view with an ecosystem-level perspective on waste. The ... ...

Abstract	The increasing amount of global waste reflects the social, environmental, and economic trajectories of the local environment. This study addresses this multifaceted problem that requires a holistic view with an ecosystem-level perspective on waste. The research objective is to analyze how the waste business ecosystem enables value capture and creation. Thus, this study contributes to the literature by using a business ecosystem approach that acknowledges several stakeholders, value networks, and the social and environmental issues of the local environment. We qualitatively examine the structure and process of value capture in the waste business ecosystem in two different environments, Finland and Sao Paulo metropolitan area, Brazil. We identify the key stakeholders and their roles, as well as contrast the waste business ecosystem between a developing country and a developed country to unveil differences in value networks. The comparative qualitative case study described relies on the interview and observation of multiple stakeholders. Theoretically, this research builds on the business ecosystem literature, value capture and creation literature, and the extant literature on waste business management. As its key result, the study maps two different ecosystems and their value creation and value capture mechanisms. The findings show that notwithstanding the strong role of regulators in both local environments and their business ecosystems, some private companies engage in value capture. However, the process and structure of the value capture differ in the two case studies. We also found that the stakeholders and their roles in the value capture structure and process vary between these two local environments and with regard to collaboration for value creation. In Finland, ecosystem-level value creation is not rare, but in the Sao Paulo metropolitan area, business models are typically single-firm-centric in terms of value creation and capture. The results presented in this paper delineate and structure the waste business ecosystems in both local environments and provide implications for stakeholders by suggesting the value capture trajectories that can be reached. Finally, fruitful avenues for further research are discussed.
Keywords	business management ; case studies ; developed countries ; developing countries ; ecosystems ; models ; municipal solid waste ; private enterprises ; stakeholders ; waste management ; Brazil ; Finland
Language	English
Dates of publication	2016-1120
Size	p. 1270-1279.
Publishing place	Elsevier Ltd
Document type	Article
ISSN	0959-6526
DOI	10.1016/j.jclepro.2016.07.168
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets

Afrabandpey, Homayun / Peltola, Tomi / Kaski, Samuel

2019

Abstract: Learning predictive models from small high-dimensional data sets is a key problem in high-dimensional statistics. Expert knowledge elicitation can help, and a strong line of work focuses on directly eliciting informative prior distributions for ... ...

Abstract	Learning predictive models from small high-dimensional data sets is a key problem in high-dimensional statistics. Expert knowledge elicitation can help, and a strong line of work focuses on directly eliciting informative prior distributions for parameters. This either requires considerable statistical expertise or is laborious, as the emphasis has been on accuracy and not on efficiency of the process. Another line of work queries about importance of features one at a time, assuming them to be independent and hence missing covariance information. In contrast, we propose eliciting expert knowledge about pairwise feature similarities, to borrow statistical strength in the predictions, and using sequential decision making techniques to minimize the effort of the expert. Empirical results demonstrate improvement in predictive performance on both simulated and real data, in high-dimensional linear regression tasks, where we learn the covariance structure with a Gaussian process, based on sequential elicitation.
Keywords	Computer Science - Machine Learning ; Computer Science - Human-Computer Interaction ; Statistics - Machine Learning
Subject code	004
Publishing date	2019-02-26
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Probabilistic Formulation of the Take The Best Heuristic

Peltola, Tomi / Jokinen, Jussi / Kaski, Samuel

2019

Abstract: The framework of cognitively bounded rationality treats problem solving as fundamentally rational, but emphasises that it is constrained by cognitive architecture and the task environment. This paper investigates a simple decision making heuristic, Take ... ...

Abstract	The framework of cognitively bounded rationality treats problem solving as fundamentally rational, but emphasises that it is constrained by cognitive architecture and the task environment. This paper investigates a simple decision making heuristic, Take The Best (TTB), within that framework. We formulate TTB as a likelihood-based probabilistic model, where the decision strategy arises by probabilistic inference based on the training data and the model constraints. The strengths of the probabilistic formulation, in addition to providing a bounded rational account of the learning of the heuristic, include natural extensibility with additional cognitively plausible constraints and prior information, and the possibility to embed the heuristic as a subpart of a larger probabilistic model. We extend the model to learn cue discrimination thresholds for continuous-valued cues and experiment with using the model to account for biased preference feedback from a boundedly rational agent in a simulated interactive machine learning task. Comment: Annual Meeting of the Cognitive Science Society, CogSci 2018 Proceedings
Keywords	Statistics - Applications ; Computer Science - Artificial Intelligence
Subject code	006
Publishing date	2019-11-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Adipokines played a limited role in predicting temporary growth differences between very low birthweight infants with and without bronchopulmonary dysplasia.

Lehtinen, A / Korhonen, P / Hyödynmaa, E / Koivisto, A M / Peltola, T / Hämäläinen, M / Moilanen, E / Tammela, O

Acta paediatrica (Oslo, Norway : 1992)

2017 Volume 106, Issue 10, Page(s) 1583–1588

Abstract: Aims: This study explored whether growth was poorer among very low birthweight (VLBW) infants with bronchopulmonary dysplasia (BPD) and assessed adipokine levels as predictors of early growth.: Methods: We studied 53 VLBW infants born in Tampere ... ...

Abstract	Aims: This study explored whether growth was poorer among very low birthweight (VLBW) infants with bronchopulmonary dysplasia (BPD) and assessed adipokine levels as predictors of early growth. Methods: We studied 53 VLBW infants born in Tampere University Hospital up to 12 months of corrected age (CA). The median gestational age of the 21 infants with BPD and 32 infants without BPD was 29 weeks, and the median birthweights were 930 (635-1470) and 1185 (650-1470) grams. Growth parameters, macronutrients intake and plasma levels of adipokines were measured. Results: Bronchopulmonary dysplasia infants were lighter than controls until 36 weeks of CA, with catch-up growth achieved by three months of CA. Adipsin levels were lower in BPD infants at 28 days of postnatal age. High leptin levels seemed protective for low weight for height at nine months of CA. The duration of ventilator therapy predicted low weight for height, length for age and body mass index and BPD predicted low length for age at 12 months of CA. Conclusions: Catch-up growth in VLBW infants with BPD was achieved by three months of CA, but adipokines played a limited role in predicting growth. Shortening ventilator therapy could help growth in VLBW infants.
Language	English
Publishing date	2017-10
Publishing country	Norway
Document type	Journal Article
ZDB-ID	203487-6
ISSN	1651-2227 ; 0365-1436 ; 0803-5253
ISSN (online)	1651-2227
ISSN	0365-1436 ; 0803-5253
DOI	10.1111/apa.13942
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Emergent publics and affects in environmental governance

Peltola, Taru / Jarkko Bamberg / Maria Åkerman / Outi Ratamäki / Pauliina Lehtonen

Journal of environmental policy & planning. 2018 Mar. 4, v. 20, no. 2

2018

Abstract: Drawing on the wide social scientific literature on emotions and affects, we highlight the value and potential contribution of the affect theory for understanding public engagement in environmental policy and planning. We suggest that such theorization ... ...

Abstract	Drawing on the wide social scientific literature on emotions and affects, we highlight the value and potential contribution of the affect theory for understanding public engagement in environmental policy and planning. We suggest that such theorization complements political ontologies that envision concerned publics to arise as citizens are attached to objects and other beings in their everyday life. Focus on emotions and affects enables in-depth exploration of the corporeality of these attachments, increasing understanding about how affected publics get driven for action and how new sensibilities and horizons for action are created. Based on the discussion of affect theory and case examples, we argue that emotions and affects should be treated as crucial carriers of knowledge about transformation of political subjects and their concerns. They also direct analytic gaze beyond public participation procedures and encourage the development of novel, more inclusive settings for public engagement.
Keywords	citizen participation ; emotions ; environmental governance ; environmental policy ; planning ; politics
Language	English
Dates of publication	2018-0304
Size	p. 157-169.
Publishing place	Routledge
Document type	Article
ISSN	1522-7200
DOI	10.1080/1523908X.2017.1343135
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Interactive AI with a Theory of Mind

Çelikok, Mustafa Mert / Peltola, Tomi / Daee, Pedram / Kaski, Samuel

2019

Abstract: Understanding each other is the key to success in collaboration. For humans, attributing mental states to others, the theory of mind, provides the crucial advantage. We argue for formulating human--AI interaction as a multi-agent problem, endowing AI ... ...

Abstract	Understanding each other is the key to success in collaboration. For humans, attributing mental states to others, the theory of mind, provides the crucial advantage. We argue for formulating human--AI interaction as a multi-agent problem, endowing AI with a computational theory of mind to understand and anticipate the user. To differentiate the approach from previous work, we introduce a categorisation of user modelling approaches based on the level of agency learnt in the interaction. We describe our recent work in using nested multi-agent modelling to formulate user models for multi-armed bandit based interactive AI systems, including a proof-of-concept user study. Comment: This is a slightly updated version of a manuscript that appeared in ACM CHI 2019 Workshop: Computational Modeling in Human-Computer Interaction
Keywords	Computer Science - Human-Computer Interaction ; Computer Science - Artificial Intelligence
Publishing date	2019-12-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework

Afrabandpey, Homayun / Peltola, Tomi / Piironen, Juho / Vehtari, Aki / Kaski, Samuel

2019

Abstract: A salient approach to interpretable machine learning is to restrict modeling to simple models. In the Bayesian framework, this can be pursued by restricting the model structure and prior to favor interpretable models. Fundamentally, however, ... ...

Abstract	A salient approach to interpretable machine learning is to restrict modeling to simple models. In the Bayesian framework, this can be pursued by restricting the model structure and prior to favor interpretable models. Fundamentally, however, interpretability is about users' preferences, not the data generation mechanism; it is more natural to formulate interpretability as a utility function. In this work, we propose an interpretability utility, which explicates the trade-off between explanation fidelity and interpretability in the Bayesian framework. The method consists of two steps. First, a reference model, possibly a black-box Bayesian predictive model which does not compromise accuracy, is fitted to the training data. Second, a proxy model from an interpretable model family that best mimics the predictive behaviour of the reference model is found by optimizing the interpretability utility function. The approach is model agnostic -- neither the interpretable model nor the reference model are restricted to a certain class of models -- and the optimization problem can be solved using standard tools. Through experiments on real-word data sets, using decision trees as interpretable models and Bayesian additive regression models as reference models, we show that for the same level of interpretability, our approach generates more accurate models than the alternative of restricting the prior. We also propose a systematic way to measure stability of interpretabile models constructed by different interpretability approaches and show that our proposed approach generates more stable models. Comment: This version contains more experiments including a comparison with baseline methods from the literature and complemented some of the existing results in the previous version
Keywords	Computer Science - Machine Learning ; Computer Science - Artificial Intelligence ; Computer Science - Human-Computer Interaction ; Statistics - Machine Learning
Subject code	006
Publishing date	2019-10-21
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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