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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Crystal structure of a glutamate-1-semialdehyde-aminomutase from Pseudomonas aeruginosa PAO1

The C5 pathway in bacteria is responsible for the synthesis of 5-aminolevulinic acid, which forms the core skeleton of cofactors required for metabolism. One of the key actors in this pathway is a pyridoxamine-5′-phosphate (PMP)/pyridoxal-5′-phosphate (PLP) dependent enzyme called glutamate-1-semialdehyde aminomutase (GSAM). In this study, we crystallized the expression product of the uncharacterized pa4088 gene from the opportunistic pathogen Pseudomonas aeruginosa PAO1. The resulting high-resolution structure confirms it to be a member of the GSAM family. Continuous electron density indicates the presence of a PLP cofactor with a Schiff base linkage between the PLP cofactor and the ε-amino group of Lys286. A crystal structure of a K286A mutant in complex with PMP is also reported. As GSAM enzymes are not present in mammalian cells, this work provides a starting point for the investigation of GSAM as a target for drug development against P. aeruginosa infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Stigmatellin Probes the Electrostatic Potential in the QB Site of the Photosynthetic Reaction Center

The electrostatic potential in the secondary quinone (QB) binding site of the reaction center (RC) of the photosynthetic bacterium Rhodobacter sphaeroides determines the rate and free energy change (driving force) of electron transfer to QB. It is controlled by the ionization states of residues in a strongly interacting cluster around the QB site. Reduction of the QB induces change of the ionization states of residues and binding of protons from the bulk. Stigmatellin, an inhibitor of the mitochondrial and photosynthetic respiratory chain, has been proven to be a unique voltage probe of the QB binding pocket. It binds to the QB site with high affinity, and the pK value of its phenolic group monitors the local electrostatic potential with high sensitivity. Investigations with different types of detergent as a model system of isolated RC revealed that the pK of stigmatellin was controlled overwhelmingly by electrostatic and slightly by hydrophobic interactions. Measurements showed a high pK value (>11) of stigmatellin in the QB pocket of the dark-state wild-type RC, indicating substantial negative potential. When the local electrostatics of the QB site was modulated by a single mutation, L213Asp/Ala, or double mutations, L213Asp-L212Glu/Ala-Ala (AA), the pK of stigmatellin dropped to 7.5 and 7.4, respectively, which corresponds to a >210 mV increase in the electrostatic potential relative to the wild-type RC. This significant pK drop (DpK > 3.5) decreased dramatically to (DpK > 0.75) in the RC of the compensatory mutant (AAþM44Asn/AAþM44Asp). Our results indicate that the L213Asp is the most important actor in the control of the electrostatic potential in the QB site of the dark-state wild-type RC, in good accordance with conclusions of former studies using theoretical calculations or light-induced charge recombination assay.

Gerencsér, László↗
DOE OSTI2023

Bayesian sequential optimal experimental design for nonlinear models using policy gradient reinforcement learning

We present a mathematical framework and computational methods for optimally designing a finite sequence of experiments. This sequential optimal experimental design (sOED) problem is formulated as a finite-horizon partially observable Markov decision process (POMDP) under a Bayesian setting and with information-theoretic utilities. The formulation is general and may accommodate continuous random variables, non-Gaussian posteriors, and nonlinear forward models. The sOED design policy incorporates elements of feedback and lookahead simultaneously, and we show it to generalize the commonly-used batch and greedy design strategies. We solve for the sOED policy using the policy gradient (PG) method from reinforcement learning, and provide a derivation for the PG expression in the sOED context. Adopting an actor-critic approach, the policy and value functions are parameterized using deep neural networks and improved via PG estimates produced from simulated episodes of designs and observations. The new PG-sOED algorithm is first validated on a linear-Gaussian benchmark, and then compared against other design baselines on a sensor movement problem for contaminant source inversion in a convection-diffusion field. As a result, we provide explanation for the policy behaviors using knowledge of the underlying physical process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Deep reinforcement learning control of hydraulic fracturing

Hydraulic fracturing is a technique to extract oil and gas from shale formations, and obtaining a uniform proppant concentration along the fracture is key to its productivity. Recently, various model predictive control schemes have been proposed to achieve this objective. But such controllers require an accurate and computationally efficient model which is difficult to obtain given the complexity of the process and uncertainties in the rock formation properties. In this article, we design a model-free data-based reinforcement learning controller which learns an optimal control policy through interactions with the process. Deep reinforcement learning (DRL) controller is based on the Deep Deterministic Policy Gradient algorithm that combines Deep-Q-network with actor-critic framework. In addition, we utilize dimensionality reduction and transfer learning to quicken the learning process. We show that the controller learns an optimal policy to obtain uniform proppant concentration despite the complex nature of the process while satisfying various input constraints.

42 ENGINEERING↗
DOE OSTI2025

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2010

Food for thought: Conditions for discourse reflection in the light of environmental assessment

People tend to take notice of what is happening around them selectively. Discourses-frames through which actors give meaning to aspects of the world-act as built-in filters that distinguish relevant from irrelevant data. Use of knowledge generated by environmental assessments (EAs) in decision-making may be understood from this perspective. Environmental knowledge that is inconsistent with dominant discourses runs the risk of being ignored. Discourses on the value of EA as a tool for decision-making may have a similar effect. Stimulating decision-makers and stakeholders to critically reflect on and reconsider their discourses in the light of EAs-also known as frame reflection or policy learning-may enhance the probability that these assessments and the knowledge that they generate impact upon decision-making. Up to now little has been written about how discourse reflection in the context of EA can be promoted. Valuable inputs are fragmented over different bodies of literature. In this paper we draw from these bodies to identify favourable conditions for discourse reflection.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2010

Contested environmental policy infrastructure: Socio-political acceptance of renewable energy, water, and waste facilities

The construction of new infrastructure is hotly contested. This paper presents a comparative study on three environmental policy domains in the Netherlands that all deal with legitimising building and locating infrastructure facilities. Such infrastructure is usually declared essential to environmental policy and claimed to serve sustainability goals. They are considered to serve (proclaimed) public interests, while the adverse impact or risk that mainly concerns environmental values as well is concentrated at a smaller scale, for example in local communities. The social acceptance of environmental policy infrastructure is institutionally determined. The institutional capacity for learning in infrastructure decision-making processes in the following three domains is compared: 1.The implementation of wind power as a renewable energy innovation; 2.The policy on space-water adaptation, with its claim to implement a new style of management replacing the current practice of focusing on control and 'hard' infrastructure; 3.Waste policy with a focus on sound waste management and disposal, claiming a preference for waste minimization (the 'waste management hierarchy'). All three cases show a large variety of social acceptance issues, where the appraisal of the impact of siting the facilities is confronted with the desirability of the policies. In dealing with environmental conflict, the environmental capacity of the Netherlands appears to be low. The policies are frequently hotly contested within the process of infrastructure decision-making. Decision-making on infrastructure is often framed as if consensus about the objectives of environmental policies exists. These claims are not justified, and therefore stimulating the emergence of environmental conflicts that discourage social acceptance of the policies. Authorities are frequently involved in planning infrastructure that conflicts with their officially proclaimed policy objectives. In these circumstances, they are often confronted with local actors who support alternatives that are in fact better in tune with the new policy paradigm.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

A Strategic Project Appraisal framework for ecologically sustainable urban infrastructure

Actors in the built environment are progressively considering environmental and social issues alongside functional and economic aspects of development projects. Infrastructure projects represent major investment and construction initiatives with attendant environmental, economic and societal impacts across multiple scales. To date, while sustainability strategies and frameworks have focused on wider national aspirations and strategic objectives, they are noticeably weak in addressing micro-level integrated decision making in the built environment, particularly for infrastructure projects. The proposed approach of this paper is based on the principal that early intervention is the most cost-effective and efficient means of mitigating the environmental effects of development projects, particularly macro infrastructure developments. A strategic overview of the various project alternatives, taking account for stakeholder and expert input, could effectively reduce project impacts/risks at low cost to the project developers but provide significant benefit to wider communities, including communities of future stakeholders. This paper is the first exploratory step in developing a more systematic framework for evaluating strategic alternatives for major metropolitan infrastructure projects, based on key sustainability principles. The developed Strategic Project Appraisal (SPA) framework, grounded in the theory of Strategic Environmental Assessment (SEA), provides a means of practically appraising project impacts and alternatives in terms of quantified ecological limits; addresses the neglected topic of metropolitan infrastructure as a means of delivering sustainability outcomes in the urban context and more broadly, seeks to open a debate on the potential for SEA methodology to be more extensively applied to address sustainability challenges in the built environment. Practically applied and timed appropriately, the SPA framework can enable better decision-making and more efficient resource allocation ensuring low impact infrastructure development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

An investigation of environmental and sustainability discourses associated with the substantive purposes of environmental assessment

This paper investigates the discursive construction of the substantive purposes of environmental assessment (EA). It addresses these purposes by exploring the complex and often multifaceted linkages between political factors and plural views of democracy, public participation, and the role of science that are embedded in environmental and sustainability discourses. The interaction between policy-making and public actors leads to the formulation of divergent and potentially competing rationales for public participation, and for social appraisal more generally. Participatory approaches have also given impetus to the development of several interpretations on the role of science in assessment procedures. Science is important in mediating public participation and the two are therefore reciprocally linked. This leads to discourses that become manifest in the construction of substantive purposes. Discourse analysis in EA is a relevant method for examining trends and patterns in sustainable development. It is argued that public participation is an important, if not decisive, variable in the articulation and civil legitimacy of certain purposes. A general proposition that results from this paper is that EA, although typically presented as an objective scientific tool, is an intrinsically normative process. Enhanced knowledge on the construction, and reconstruction over time, of substantive purposes is required if environmental and sustainability discourses are to be used and understood as meaningful analytical instruments to assess the socio-political implications of EA. - Highlights: Black-Right-Pointing-Pointer Substantive purposes related to environmental assessment may be best analyzed through discourse analysis. Black-Right-Pointing-Pointer Environmental and sustainability discourses are contingent on the level of participatory democracy and civic science. Black-Right-Pointing-Pointer Public participation is a decisive variable in the construction of the substantive purpose of environmental assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Knowledge brokerage - potential for increased capacities and shared power in impact assessment

Constructive and collaborative planning theory has exposed the perceived limitations of public participation in impact assessment. At strategic levels of assessment the established norm can be misleading and practice is illusive. For example, debates on SEA effectiveness recognize insufficiencies, but are often based on questionable premises. The authors of this paper argue that public participation in strategic assessment requires new forms of information and engagement, consistent with the complexity of the issues at these levels and that strategic assessments can act as knowledge brokerage instruments with the potential to generate more participative environments and attitudes. The paper explores barriers and limitations, as well as the role of knowledge brokerage in stimulating the engagement of the public, through learning-oriented processes and responsibility sharing in more participative models of governance. The paper concludes with a discussion on building and inter-change of knowledge, towards creative solutions to identified problems, stimulating learning processes, largely beyond simple information transfer mechanisms through consultative processes. The paper argues fundamentally for the need to conceive strategic assessments as learning platforms and design knowledge brokerage opportunities explicitly as a means to enhance learning processes and power sharing in IA. - Highlights: Black-Right-Pointing-Pointer Debates on SEA recognize insufficiencies on public participation Black-Right-Pointing-Pointer We propose new forms of engagement consistent with complex situations at strategic levels of decision-making Black-Right-Pointing-Pointer Constructive and collaborative planning theories help explain how different actors acquire knowledge and the value of knowledge exchange Black-Right-Pointing-Pointer Strategic assessments can act as knowledge brokerage instruments Black-Right-Pointing-Pointer The paper argues for strategic assessments as learning platforms as a means to enhance learning processes and power sharing in IA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Improving the effectiveness of impact assessment pertaining to Indigenous peoples in the Brazilian environmental licensing procedure

The number of environmental licence applications for projects affecting Indigenous peoples in Brazil has increased since the implementation of a major infrastructure program (Programa de Aceleração do Crescimento) in 2007. This increase has caused problems for Brazilian agencies involved in environmental licensing procedures (IBAMA, FUNAI and others). We analyze the Brazilian environmental licensing procedure for situations involving Indigenous peoples, Maroons (Quilombolas) or other traditional communities in order to identify potential improvements for Brazil and potentially other countries. Although Brazilian procedures are consistent with international best practice in environmental licensing, in practice social impacts are inadequately addressed, mitigation measures are poorly implemented, and there is a lack of enforcement and compliance. The paper is based on document analysis and interviews with key actors in governmental and non-governmental organizations and Indigenous leaders. We suggest that Free, Prior and Informed Consent (FPIC) processes need to be conducted at the earliest stages of project planning, and that Indigenous peoples should actively participate in impact assessment, monitoring and evaluation processes. In order to achieve a social licence to operate, there needs to be full recognition of traditional knowledge and acceptance of Indigenous values and concepts. We also recommend increased involvement of social experts and mediators as well as improved accountability, enforcement and grievance mechanisms in the licensing process. - Highlights: • The Brazilian environmental licensing system needs to address social impacts better. • Communities need to be consulted at the earliest stage possible. • Indigenous peoples need to be invited to participate in impact assessment teams. • Independent Indigenous committees to monitor implementation of mitigation measures. • Accountability, enforcement and grievance mechanisms need to be improved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Knowledge brokering on emissions modelling in Strategic Environmental Assessment of Estonian energy policy with special reference to the LEAP model

Strategic Environmental Assessment (SEA) serves as a platform for bringing together researchers, policy developers and other stakeholders to evaluate and communicate significant environmental and socio-economic effects of policies, plans and programmes. Quantitative computer models can facilitate knowledge exchange between various parties that strive to use scientific findings to guide policy-making decisions. The process of facilitating knowledge generation and exchange, i.e. knowledge brokerage, has been increasingly explored, but there is not much evidence in the literature on how knowledge brokerage activities are used in full cycles of SEAs which employ quantitative models. We report on the SEA process of the national energy plan with reflections on where and how the Long-range Energy Alternatives Planning (LEAP) model was used for knowledge brokerage on emissions modelling between researchers and policy developers. Our main suggestion is that applying a quantitative model not only in ex ante, but also ex post scenario modelling and associated impact assessment can facilitate systematic and inspiring knowledge exchange process on a policy problem and capacity building of participating actors. - Highlights: • We examine the knowledge brokering on emissions modelling between researchers and policy developers in a full cycle of SEA. • Knowledge exchange process can evolve at any modelling stage within SEA. • Ex post scenario modelling enables systematic knowledge exchange and learning on a policy problem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Proponent-Indigenous agreements and the implementation of the right to free, prior, and informed consent in Canada

Indigenous peoples have gained considerable agency in shaping decisions regarding resource development on their traditional lands. This growing agency is reflected in the emergence of the right to free, prior, and informed consent (FPIC) when Indigenous rights may be adversely affected by major resource development projects. While many governments remain non-committal toward FPIC, corporate actors are more proactive at engaging with Indigenous peoples in seeking their consent to resource extraction projects through negotiated Impact and Benefit Agreements. Focusing on the Canadian context, this article discusses the roots and implications of a proponent-driven model for seeking Indigenous consent to natural resource extraction on their traditional lands. Building on two case studies, the paper argues that negotiated consent through IBAs offers a truncated version of FPIC from the perspective of the communities involved. The deliberative ethic at the core of FPIC is often undermined in the negotiation process associated with proponent-led IBAs. - Highlights: • FPIC is becoming a norm for resource extraction projects on Indigenous lands. • Proponent-led IBAs have become the main instrument to establish FPIC in Canada. • Case studies show elite-driven IBA negotiations do not always create the conditions for FPIC. • We need to pay attention to community deliberations as an inherent aspect of FPIC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Streamlining or sidestepping? Political pressure to revise environmental licensing and EIA in Brazil

In the Anthropocene, governments are increasingly being forced to take action to minimize or reverse human impacts on the environment. One of the most widespread legal instruments to prevent negative impacts on the environment is Environmental Impact Assessment (EIA). Almost all countries have an EIA system in place aimed at mitigating the diverse impacts causing by development projects. A common drawback of such systems is that they are often ineffective and time-consuming, and are therefore frequently viewed by politicians as “in the way” of development. This is the case in Brazil, where EIA has had a very limited influence on decision-making and where environment reforms (e.g. the new Forest Code) have often been strongly influenced by powerful lobbies (e.g. agribusiness groups, industry actors, etc.) and conservative legislators. Continuing this trend, the most recent political developments have seen the proposal of a series of amendments aimed at “streamlining” the Brazilian EIA system. In this viewpoint, we provide an in depth analysis of the proposed changes, highlighting the serious consequences that would accompany the weakening of environmental licensing and EIA legislation in Brazil.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A reinforcement learning approach to long-horizon operations, health, and maintenance supervisory control of advanced energy systems

In this work, we develop a Reinforcement Learning (RL) approach to the supervisory control problem for advanced energy systems, such as novel nuclear reactors and other demand-driven, mission-critical, and component-health-sensitive energy plants. The inclusive problem landscape considered captures the stochastic confluence of plant performance, component health evolution, power demand from the grid, diverse maintenance actions, and operator-defined goals and constraints, all considered over meaningfully long-enough reasoning horizons. Key aspects of the proposed approach are a receding horizon control-inspired technique dictating time- or event-triggered supervisory policy (re-)constructions, as well as additional capability-enabling contributions such as timescale compression, to handle long reasoning horizons and uncertainty in parts of the problem, and practical yet demonstrably-effective handling of hybrid action spaces with continuous and discrete decision variables. The resulting algorithm consists of a simulation-based RL agent constructing stochastic supervisory control policies over nontrivial action spaces and for long horizons, applying the learned policy to the system for a much shorter interval, and perpetually repeating, to construct the next long-horizon policy. That next policy will only be applied, again, for a short interval, yet originally far-in-time events move progressively closer, their associated uncertainty decreases, and new events and aspects enter the reasoning horizon. The proposed methodology bridges fundamental receding horizon concepts with the unequivocally stronger and more scalable reasoning of contemporary RL. Numerical examples using Soft Actor–Critic Deep RL illustrate the operation and efficacy of the proposed technique for a power plant tasked with health-aware load following missions in a dynamic electricity market landscape.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Lessons from wind policy in Portugal

Wind capacity and generation grew rapidly in several European countries, such as Portugal. Wind power adoption in Portugal began in the early 2000s, incentivized by a continuous feed-in tariff policy mechanism, coupled with public tenders for connection licenses in 2001, 2002, and 2005. These policies led to an enormous success in terms of having a large share of renewables providing electricity services: wind alone accounts today for ~23.5% of electricity demand in Portugal. We explain the reasons wind power became a key part of Portugal's strategy to comply with European Commission climate and energy goals, and provide a detailed review of the wind feed-in tariff mechanism. We describe the actors involved in wind power production growth. We estimate the environmental and energy dependency gains achieved through wind power generation, and highlight the correlation between wind electricity generation and electricity exports. Finally, we compare the Portuguese wind policies with others countries' policy designs and discuss the relevance of a feed-in tariff reform for subsequent wind power additions.

17 WIND ENERGY↗
DOE OSTI2017

Estimating the implied cost of carbon in future scenarios using a CGE model: The Case of Colorado

We develop a state-level computable general equilibrium (CGE) model that reflects the roles of coal, natural gas, wind, solar, and hydroelectricity in supplying electricity, using Colorado as a case study. Also, we focus on the economic impact of implementing Colorado's existing Renewable Portfolio Standard, updated in 2013. This requires that 25% of state generation come from qualifying renewable sources by 2020. We evaluate the policy under a variety of assumptions regarding wind integration costs and assumptions on the persistence of federal subsidies for wind. Specifically, we estimate the implied price of carbon as the carbon price at which a state-level policy would pass a state-level cost-benefit analysis, taking account of estimated greenhouse gas emission reductions and ancillary benefits from corresponding reductions in criteria pollutants. Our findings suggest that without the Production Tax Credit (federal aid), the state policy of mandating renewable power generation (RPS) is costly to state actors, with an implied cost of carbon of about $17 per ton of CO 2 with a 3% discount rate. Federal aid makes the decision between natural gas and wind nearly cost neutral for Colorado.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Pesticide risk perceptions and the differences between farmers and extensionists: Towards a knowledge-in-context model

A growing body of literature analyzes farmer perceptions of pesticide risk, but much less attention has been given to differences in risk perception between farmers and technical experts. Furthermore, inconsistencies in knowledge have too easily been explained in terms of lack of knowledge rather than exploring the underlying reasons for particular forms of thinking about pesticide risks. By doing this, the division between expert and lay knowledge has been deepened rather than transcended. Objective: This study aims to understand differences and similarities among the perceptions of pesticide risks of farmers, farm workers, and technical experts such as extensionists, by applying a social science approach towards knowledge and risk attitudes. Methods: Semi-structured interviews and field observations were conducted to smallholders, farm workers, extensionists, health professionals and scientists involved in the use and handling of pesticides. Subsequently, a survey was carried out to quantify the farmers and extensionists' acceptance or rejection of typical assertions expressed previously in the semi-structured interviews. Results: Smallholders showed to gain knowledge from their own experiences and to adapt pesticides practices, which is a potential basis for transforming notions of pesticide safety and risk reduction strategies. Though extensionists have received formal education, they sometimes develop ideas deviating from the technical perspective. The risk perception of the studied actors appeared to vary according to their role in the agricultural labor process; they varied much less than expected according to their schooling level. Conclusions: Commitment to the technical perspective is not dramatically different for extensionists on the one hand and farmers as well as farm workers on the other hand. Ideas about a supposed lack of knowledge by farmers and the need of formal training are too much driven by a deficit model of knowledge. Further research on risk perceptions of pesticides and training of rural people will benefit from the development of a knowledge-in-context model. -- Highlights: • Researching perceptions of farmers' extensionists and other professionals. • Experts as well as farmers deviate from the technical perspective. • Blaming who is responsible for pesticide problems creates expert-lay division. • Qualitative and quantitative methods, not as complementary but integrated. • Knowledge-in-context model as an alternative to the knowledge-deficit model.

60 APPLIED LIFE SCIENCES↗