On the use of possibility theory in uncertainty analysis of life cycle inventory

Purpose  

The purpose of this paper is to enhance the mathematical and physical understanding of practitioners of uncertainty analysis of life cycle inventory (LCI), on the application of possibility theory. The main questions dealt with are (1) clear definition of the terms—“necessity–possibility,” “probability,” “belief–plausibility,” and of their mutual relationships; (2) what justifies the substitution of classical probability for possibility; (3) mutual comparison of, and transformations in both senses between probability and possibility uncertainty measures; (4) how to construct meaningful input possibility measures from available probabilistic/statistic information; and (5) comparative analysis of the solutions of the problem of data uncertainty propagation in LCI, afforded, respectively, by probabilistic Monte Carlo simulation and possibilistic fuzzy interval arithmetic.     

The Use of Probabilistic Analysis to Improve Decision-Making in Environmental Regulation in a Developing Context: The Case of Arsenic Regulation in Chile

Using probabilistic analysis may be very useful for risk management in developing countries, where information, resources, and technical expertise are often scarce. Currently, most regulatory agencies recommend using deterministic approaches for the analysis of problems relating to decision-making. However, this approach does not incorporate uncertainty in the variables, nor the propagation of uncertainty through the different processes in which they are involved. The complexity of the problem is therefore arbitrarily reduced, and valuable information that could be useful for proposing realistic policies is not considered. This article compares the results of a deterministic analysis with those of a probabilistic one for regulating arsenic in Chile, and differences are established for public policy as a result of building uncertainty into the analysis. It is concluded that the use of a deterministic approach can lead to higher risks than necessary and that probabilistic results can help the regulator negotiate stricter standards. Alternatively, the regulator may end up imposing much higher costs to sources than originally expected as these will be forced to use expensive technology to comply consistently with a given standard.     

Stress,Uncertainty and Decision Confidence

We successfully manipulated decision confidence in a probabilistic prediction task by means of stress as induced by excessive cognitive demands. In particular, our results indicate that decisions (based on high and low, but not intermediate levels of uncertainty) made under stress (confirmed by skin conductance measures) are associated with increased confidence when outcome probabilities are incompletely known (20% residual uncertainty). A different pattern was found when outcome probabilities were completely known (0% residual uncertainty). Here, stress led to decreased decision confidence when decisions were associated with intermediate levels of uncertainty but had no effect in case of high and low levels of uncertainty. In addition we provide evidence for ambiguity—(understood as implicit-risk) assessment being impaired under stress conditions.     

SPIDE: sybil-proof,incentivized data exchange

Cluster Computing - Decentralized, open-access blockchain systems opened up new, exciting possibilities—all without reliance on trusted third parties. Regardless of the employed consensus...     

Integrating life cycle cost analysis and LCA

The private sector decision making situations which LCA addresses mustalso eventually take theeconomic consequences of alternative products or product designs into account. However, neither the internal nor external economic aspects of the decisions are within the scope of developed LCA methodology, nor are they properly addressed by existing LCA tools. This traditional separation of life cycle environmental assessment from economic analysis has limited the influence and relevance of LCA for decision-making, and left uncharacterized the important relationships and trade-offs between the economic and life cycle environmental performance of alternative product design decision scenarios. Still standard methods of LCA can and have been tightly, logically, and practically integrated with standard methods for cost accounting, life cycle cost analysis, and scenario-based economic risk modeling. The result is an ability to take both economic and environmental performance — and their tradeoff relationships — into account in product/process design decision making.     

A Reflective Lens: Applying Critical Systems Thinking and Visual Methods to Ecohealth Research

Critical systems methodology has been advocated as an effective and ethical way to engage with the uncertainty and conflicting values common to ecohealth problems. We use two contrasting case studies, coral reef management in the Philippines and national park management in Australia, to illustrate the value of critical systems approaches in exploring how people respond to environmental threats to their physical and spiritual well-being. In both cases, we used visual methods—participatory modeling and rich picturing, respectively. The critical systems methodology, with its emphasis on reflection, guided an appraisal of the research process. A discussion of these two case studies suggests that visual methods can be usefully applied within a critical systems framework to offer new insights into ecohealth issues across a diverse range of socio-political contexts. With this article, we hope to open up a conversation with other practitioners to expand the use of visual methods in integrated research.     

Climate sensitivity of soil water regime of different Hungarian Chernozem soil subtypes

In this study the possible effects of two predicted climate change scenarios on soil water regime of Hungarian Calcic Chernozem soils has been investigated. Soil profiles classified as Calcic Chernozem — in total 49 — were selected from the MARTHA soil physical database that incorporates soil data at national scale. These profiles were subdivided into three groups (sandy loam, loam and clayey loam) in accordance with their mechanical composition. Soil water retention curves were scaled separately for each of the three textural groups, using similar media scaling in order to represent the variability of soil hydrophysical data with one parameter, the scaling factor (SF). Reference soil profiles were chosen according to the cumulative distribution function of the scaling factor, six for each textural group. Daily downscaled meteorological data from A2 and B2 climate scenarios of the Hadley Centre (2070–2100) and data from a reference period (RF, 1961–1990) were used in this study to characterize different climatic situations. Nine representative years were selected in case of all the three scenarios, using the cumulative probability function of the annual precipitation sum. Scenario analyses were performed, validating the SWAP soil water balance simulation model for the 18 reference soil profiles and 27 representative years in order to evaluate the expected changes in soil water regime under different from the present (RF) climatic conditions (A2 and B2 scenarios). Our results show that the scaling factor could be used as a climate sensitivity indicator of soil water regime. The large climate sensitivity of the majority of Chernozem soil subtypes water regime has been proven.     

Horse breed discrimination using machine learning methods

Genetic relationships and population structure of 8 horse breeds in the Czech and Slovak Republics were investigated using classification methods for breed discrimination. To demonstrate genetic differences among these breeds, we used genetic information — genotype data of microsatellite markers and classification algorithms — to perform a probabilistic prediction of an individual’s breed. In total, 932 unrelated animals were genotyped for 17 microsatellite markers recommended by the ISAG for parentage testing (AHT4, AHT5, ASB2, HMS3, HMS6, HMS7, HTG4, HTG10, VHL20, HTG6, HMS2, HTG7, ASB17, ASB23, CA425, HMS1, LEX3). Algorithms of classification methods — J48 (decision trees); Naive Bayes, Bayes Net (probability predictors); IB1, IB5 (instance-based machine learning methods); and JRip (decision rules) — were used for analysis of their classification performance and of results of classification on this genotype dataset. Selected classification methods (Naive Bayes, Bayes Net, IB1), based on machine learning and principles of artificial intelligence, appear usable for these tasks.     

Human mate choice and the wedding ring effect

Individuals are often restricted to indirect cues when assessing the mate value of a potential partner. Females of some species have been shown to copy each other’s choice; in other words, the probability of a female choosing a particular male increases if he has already been chosen by other females. Recently it has been suggested that mate-choice copying could be an important aspect of human mate choice as well. We tested one of the hypotheses, the so-called wedding ring effect—that women would prefer men who are already engaged or married—in a series of live interactions between men and women. The results show that women do not find men signaling engagement, or being perceived as having a partner, more attractive or higher in socioeconomic status. Furthermore, signs of engagement did not influence the women’s reported willingness to engage in short-term or long-term relationships with the men. Thus, this study casts doubt on some simplified theories of human mate-choice copying, and alternative, more complex scenarios are outlined and discussed. Tobias Uller works on broad issues in evolutionary biology, such as life-history evolution and evolutionary genetics. Christoffer Johansson recently received his Ph.D. with a dissertation on biomechanics of swimming birds. Their collaborative work on humans is focused on mate choice.     

Developing higher resolution climate change scenarios for agricultural risk assessment: progress,challenges and prospects

Climate change presents perhaps the greatest economic and environmental challenge we have ever faced. Climate change and its associated impacts, adaptation and vulnerability have become the focus of current policy, business and research. This paper provides invaluable information for those interested in climate change and its impacts. This paper comprehensively reviews the advances made in the development of regional climate change scenarios and their application in agricultural impact, adaptation and vulnerability assessment. Construction of regional climate change scenarios evolved from the application of arbitrary scenarios to the application of scenarios based on general circulation models (GCMs). GCM-based climate change scenarios progressed from equilibrium climate change scenarios to transient climate change scenarios; from the use of direct GCM outputs to the use of downscaled GCM outputs; from the use of single scenarios to the use of probabilistic climate change scenarios; and from the application of mean climate change scenarios to the application of integrated climate change scenarios considering changes in both mean climate and climate variability.     

Propagating uncertainty in microarray data analysis

Microarray technology is associated with many sources of experimentaluncertainty. In this review we discuss a number of approachesfor dealing with this uncertainty in the processing of datafrom microarray experiments. We focus here on the analysis ofhigh-density oligonucleotide arrays, such as the popular AffymetrixGeneChip® array, which contain multiple probes for eachtarget. This set of probes can be used to determine an estimatefor the target concentration and can also be used to determinethe experimental uncertainty associated with this measurement.This measurement uncertainty can then be propagated throughthe downstream analysis using probabilistic methods. We giveexamples showing how these credibility intervals can be usedto help identify differential expression, to combine informationfrom replicated experiments and to improve the performance ofprincipal component analysis.      

A reexamination of Gilligan’s analysis of the female moral system

Gilligan’s (1982) refinement of Kohlberg’s theory on moral development operates on two theses: (1) females, more so than males, reach moral decisions based on the personalities of the relevant individuals; and (2) female behaviors stemming from moral decisions are based upon “care” and “responsibility for others.” This article accepts the first thesis but argues that the second is incorrect. That is, self-interest—i.e., aiding “blood” kin and/or carefully monitoring reciprocity—rather than “altruism” is argued to be the operant dynamic in forging distaff morality and resultant behavior. Six empirical examples are presented as contraindicative of Gilligan’s second thesis. Finally, it is suggested that selection for the psychological traits of independence and the mastery of subtle social chess yielded ancestral females who had more descendants—us—than did females with alternative profiles. Nancy S. Coney is a professor at Western Illinois University and is interested in both clinical and nonclinical aspects of women’s psychology. Wade C. Mackey is interested in biocultural anthropology and has authored two books on fathering:Fathering Behaviors (Plenum, 1995) andThe American Father (Plenum, 1996).     

Possibility Theory: A New Approach to Uncertainty Analysis? (3 pp)

Background, Aims and Scope The problem of the evaluation of practitioner's belief and belief-related uncertainties on LCA results obtained from different methodological choices has been addressed so far by scenario modeling, Cultural Theory perspectives and probabilistic simulation. The direct evaluation of belief and related uncertainties could be of interest, e.g. when the information available (resulting from classical uncertainty analysis or the application of the precautionary principle) do not allow one to choose between methodological alternatives leading to different LCA results and conclusions. The difficulty of modeling belief arises from the additive nature of classical measures, e.g. probabilities. Since the 1960s, non-additive measures (e.g. possibilities) have been developed and applied to model belief in real world problems. The aim of this paper is to discuss the application of possibility measures in LCA for uncertainty analysis in complement to classical approaches. Methods The nature and the meaning of possibilities are briefly introduced by comparison with probabilities (subjective or not) in order to enlighten strengths, drawbacks and complementarities. A tentative possibilistic approach based on the evaluation of a posteriori possibilities of final LCA results depending on a priori possibilities of the methodological choices behind the calculations is described, also by means of an application example. Results and Outlook. A new approach for the modeling of practitioner's belief and belief-related uncertainties in complement of classical methods of uncertainty analysis has been proposed for discussion. Uncertainty can be characterized by confidence intervals and indexes that could help practitioners in making methodological choices and could improve the interpretation and reliability of LCA results, still increasing its sophistication.     

Genetic analysis of short term callus culture and morphogenesis in pearl millet,Pennisetum glaucum

Genetic analysis of five in vitro characters was made through a 5 × 5 diallel analysis using callus derived from immature inflorescence segments of pearl millet (Pennisetum glaucum). The characters studied were: — volume of total callus, — frequency of embryogenic calli, — embryogenic callus volume, — growth rate in terms of increase in fresh weight, and — frequency of regeneration. High heritability values and heterosis were noticed for all these characters except for E callus frequency. Additive gene action was predominant for callus growth rate and frequency of regeneration. Of the five inbreds, IP 1346 (= P5) was found to be the best genetic background for embryogenic callus volume, embryogenic growth rate and frequency of regeneration. This revised version was published online in June 2006 with corrections to the Cover Date.     

The PSI formal document process and its implementation on the PSI website

The Human Proteome Organisation's Proteomics Standards Initiative (HUPO-PSI) has recently developed formal document processes for reviewing MIAPE documents, specifications, community practice and informational documents. These document workflows rely on community participation as well as more traditional expert review. We here present the web interface used to support these document processes, and explain briefly how interested parties can participate in the review process. The HUPO-PSI website can be found at http://www.psidev.info.     

Automobile air conditioning: A case study of CFC replacements part II

Global warming impact (GW) of automobile air-conditioners using two refrigerants — a hydrocarbon blend and HFC-134a -were estimated and compared. The HFC-134a system showed a GW 20–90% greater than that of the hydrocarbon system. Volatile organic compounds (VOC) emissions of the air-conditioners were near to equal, in the basecase scenario slightly higher for HFC-134a, in some scenarios slightly higher for the hydrocarbon.     

Consciousness is Cheap, Even if Symbols are Expensive; Metabolism and the Brain’s Dark Energy

Use of symbols, the key to the biosemiotics field as to many others, required bigger brains which implied a promissory note for greater energy consumption; symbols are obviously expensive. A score years before the current estimate of 18–20% for the human brain’s metabolic demand on the organism, it was known that neural tissue is metabolically dear. This paper first discusses two evolutionary responses to this demand, on both of which there is some consensus. The first, assigning care of altricial infants with burgeoning brains (and in human infants the metabolic demand peaks at 65% of the total) to “allomothers” is not unique to humans. The second, using relatively small neurons as primates do, risks misfires past a certain minimal value. Moreover, in apparent paradox, there is an increasing consensus that large “Von Economo” neurons are critical for communication. This paper’s main contribution is the discussion of two further evolutionary tricks. The first is the use of self-similarity in the cortex, both in structure and process, to allow the cortex readily—and in energetic terms, parsimoniously—to shift between states in a high-dimensional space. This leads to discussion of the kind of formalism appropriate to model these shifts, a formalism which—it is tentatively suggested—may do double duty for the modeling of symbolic thought. The second trick is the superimposition on the background “white noise” of neural firing of EEG-detected waves like gamma. The paper describes a method, using the Hilbert transform, of calculating the dips in energy consumption as the brain is transitioned by gamma waves. It is hypothesized that consciousness may be a spandrel, the incidental result of a neurodynamic imperative that the brain enter a maximally sensitive (in sensory terms) “zero power” state a few times a second. If that is the case, then there are obvious benefits for health in meditation, which can be viewed as a state of consciousness extended over time by limiting afferent stimuli.     

New constructions of one- and two-stage pooling designs.

The study of gene functions requires a DNA library of high quality, such a library is obtained from a large mount of testing and screening. Pooling design is a very helpful tool for reducing the number of tests for DNA library screening. In this paper, we present new one- and two-stage pooling designs, together with new probabilistic pooling designs. The approach in this paper works for both error-free and error-tolerance scenarios.