Data-limited Conditions Research Articles

Believing is Seeing: A Perspective on Perceiving Images of Objects on the Shroud of Turin

For many years, the Shroud of Turin has been famous for images of a body and face which many believe were formed during The Resurrection. More recently, however, claims have been made that the Shroud also contains evidence of other objects, and these claims have been used to support the view that the Shroud is the burial cloth of Jesus. However, these claims are based on marks that are barely visible and the psychological processes known to be involved in perceiving objects under data-limited conditions have been largely ignored. Here, we consider these processes and assess the claims that objects can be seen on the Shroud. We conclude that the viewing conditions provided by images of the Shroud are likely to lead to the illusory perception of objects, and knowing the psychological processes underlying these perceptions is crucial for accurately determining the provenance of the Shroud and other material artefacts.

The Correlation Between Statistically Downscaled Precipitation Data and Groundwater Level Records in North-Western Turkey

Downscaling of atmospheric climate parameters is a sophisticated tool to develop statistical relationships between large-scale atmospheric variables and local-scale meteorological variables. In this study, the variables selected from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data set were used as predictors for the downscaling of monthly precipitation in a watershed located in north-western Turkey where station records terminated two decades ago. An Artificial Neural Network (ANN) based approach was used to downscale global climate predictors that are positively correlated to the existing time frame of precipitation data in the basin. The downscaled precipitation information were used to extend the non-existing data from the meteorological station, which were later correlated with groundwater level data obtained from automatic pressure transducers that continuously record depth to groundwater. The results of the study showed that, among a large set of NCEP/NCAR parameters, surface precipitation data recorded at the meteorological station was strongly correlated with precipitation rate, air temperature and relative humidity at surface and air temperature at 850, 500, and 200 hPa pressure levels, and geopotential heights at 850 and 200 hPa pressure levels. The gaps in station data were then filled with the correlations obtained from NCEP/NCAR parameters and a complete precipitation data set was obtained that extended to current time line. This extended precipitation time series was later correlated with the existing groundwater level data from an alluvial plain in order to develop a general relationship that can be used in basin-wide water budget estimations. The proposed methodology is believed to serve the needs of engineers and basin planners who try to create a link between related hydrological variables under data-limited conditions.

Effort Allocation in Rural Road Safety Analysis under Data-Limited Conditions

Traffic safety policy defines plans that are expressed using numerical values for the planned level of improvement. The directing or apportioning of efforts represents the initial step of planned improvements. If a road is observed as a system of sections, the sections should be prioritized, selected, and investigated according to precise enhancement requests. A temporal approach to road safety analysis enables the application of reliability reallocation theory. The individual application of certain reliability reallocation methods may yield results that are unusable for a road authority in some situations. This paper describes a method that is based on a judicious combination of acceptable features of two reliability reallocation methods [the aeronautical radio incorporated (ARINC) and the minimum effort algorithm] in different iterations. This method enables the possibility of setting a precisely expressed goal with a minimal set of input values to obtain quality and applicable results for a decision maker. The presented approach represents an improvement in the field of road safety decision-making support and is transferable to other areas of transportation engineering and effort allocation. Language: en

Multivariate probability distribution for sewer system vulnerability assessment under data-limited conditions

The lack of geometrical and hydraulic information about sewer networks often excludes the adoption of in-deep modeling tools to obtain prioritization strategies for funds management. The present paper describes a novel statistical procedure for defining the prioritization scheme for preventive maintenance strategies based on a small sample of failure data collected by the Sewer Office of the Municipality of Naples (IT). Novelty issues involve, among others, considering sewer parameters as continuous statistical variables and accounting for their interdependences. After a statistical analysis of maintenance interventions, the most important available factors affecting the process are selected and their mutual correlations identified. Then, after a Box-Cox transformation of the original variables, a methodology is provided for the evaluation of a vulnerability map of the sewer network by adopting a joint multivariate normal distribution with different parameter sets. The goodness-of-fit is eventually tested for each distribution by means of a multivariate plotting position. The developed methodology is expected to assist municipal engineers in identifying critical sewers, prioritizing sewer inspections in order to fulfill rehabilitation requirements.

Crop model usefulness in drylands of southern Africa: an application of DSSAT

Crop models are useful tools for simulating impacts of climate and agricultural practices on crops. Models have to demonstrate the ability to simulate actual crop growth response in particular environments before application. Data limitations in southern Africa frequently hinder adequate assessment of crop models before application. The DSSAT model was used to test the usefulness of crop models under data-limited dryland conditions of southern Africa by validation using data from experimental trial reports and district-wide crop yield estimates. Two crops each were selected in three locations to represent varying cropping and physical conditions in southern Africa, i.e. maize and sorghum (Mohale's Hoek, Lesotho and Big Bend, Swaziland) and maize and groundnut (Lilongwe, Malawi). DSSAT performs well in simulating crop yields obtained from experimental trials. District-wide simulated mean crop yields were acceptable (relative difference ranged from −12.2% to +2.36%). However, the model's capture of seasonal yield variation for some locations and crops was uncertain due to climate extremes. It was concluded that satisfactory crop model testing before application is possible and that DSSAT crop models are useful even under data-limited conditions.

Stock assessment of the Spanish mackerel (Scomberomorus commerson) in Saudi waters of the Arabian Gulf with generalized depletion models under data-limited conditions

A multi-annual and multi-fleet version of a generalized depletion model is developed and applied to the Spanish mackerel (Scomberomorus commerson) stock in Saudi waters of the Arabian Gulf under data-limited conditions. The fishing operational data are the official monthly records of estimated catch biomass and exact nominal effort of two artisanal fleets from 1995 to 2012. To transform catch in biomass to catch in numbers, a monthly trend in mean weight is estimated from biological compositional data from 2002, 2013 and used to produce predictions of mean weight for every month between 1995 and 2012. Estimates of natural mortality and initial abundance, thirty six fleet-specific abundance parameters, and six fleet-specific fishing operational parameters, are obtained by maximum likelihood. Thirty six additional timing parameters are fixed by graphical display of catch spikes, a convenient statistic defined here, and by maximum likelihood. The reconstructed history of the stock shows that the catch varies in direct relation to the magnitude of recruitment pulses, while nominal effort has been stable. The annual exploitation rate was estimated at approximately 10%, which implies that fishing is occurring at sustainable levels, although these results are conditional on a well-behaved mean monthly weight in the catch and simplified statistical models.

Spatial working memory load impairs signal enhancement, not attentional orienting

The current study examined the effect of spatial working memory load on spatial cuing effect. It is well known that spatial working memory and spatial attention functionally overlap or share a common resource. Awh et al. (1998) showed visual selection played a critical role in the maintenance of spatial information. Based upon this finding, we expected that the improvement in behavioral performance by attention would interact with spatial working memory. Two experiments were conducted to test this hypothesis. Participants were given a transient cue predicting the location of a relevant item and they had to perform a visual discrimination task with or without maintaining four locations in working memory. Cuing effect measured by reaction time did not differ either in the presence or in the absence of spatial working memory load. However, spatial working memory load reduced cuing effect in accuracy. This discrepancy can be explained by distinction between channel selection and channel enhancement by attention (Prinzmetal et al., 2005). The benefit in RT by attention shows prioritization of the attended location (channel selection), whereas the improvement in accuracy under data-limited conditions reflects the enhancement of perceptual representation on the attended location (channel enhancement). Given the fact that spatial working memory load reduced only the attentional advantage in accuracy, we conclude that spatial working memory load impairs signal enhancement on the attended location, but seems to be irrelevant with attentional orienting per se.

The processing locus of interference from salient singleton distractors

Numerous studies have demonstrated that target processing is slowed in the presence of an irrelevant singleton element. One hypothesis is that these slowed responses are due to disruptions in the early sensory processing of the targets. We replicated this effect in a resource-limited procedure. However, under data-limited conditions (e.g., brief exposure durations and backward masking), the same singleton distractor did not interfere with performance. Following previous suggestions that data-limited procedures should be sensitive to disruptions in early visual processing (Santee & Egeth, 1982), we conclude that slowed response times in the presence of salient singleton distractors may be due to disruptions in a postperceptual stage of processing such as response selection.

The Bahamas’ Nassau grouper ( Epinephelus striatus) fishery – two assessment methods applied to a data – deficient coastal population

The Nassau grouper is an important fish species in the reef ecosystem of the Bahamas. It is subjected to intense exploitation by small-scale fisheries and is harvested with different fishing gears, primarily during the winter spawning season. The piecemeal nature of the fishing operations precludes an economically feasible way to compile data to assess the status of exploitation of the resource. There is public and governmental concern regarding over-exploitation of the Nassau grouper due to the numerous extinctions of spawning aggregations in the greater Caribbean. Due to the large size of the Bahamas archipelago, where many Nassau grouper spawning aggregations still occur, the collection of appropriate data for stock assessments is very difficult. In addition, stock assessment algorithms that are applicable to tropical, seasonally aggregating species are noticeably lacking. In this paper we present applications of analytical and hydroacoustic assessment algorithms to the Nassau grouper fishery in the Bahamas that could be implemented under data-limited conditions. The results of the analyses indicate that the methods generate consistent abundance and mortality rate estimates that are commensurable with a stock subjected to full exploitation.

Mass balance modelling of contaminants in river basins: Application of the flexible matrix approach

It is useful to have available a variety of catchment-scale water quality models that range in complexity, spatial resolution and data requirements. In a previous paper [Warren, C., Mackay, D., Whelan, M., Fox, K., 2005. Mass balance modelling of contaminants in river basins: a flexible matrix approach. Chemosphere 61, 1458-1467] a series of simple to intermediately complex mass balance models was presented which can be used for tiered exposure assessments in river basins. The connectivity of the segments is expressed using a matrix that permits flexibility in application, enabling the model to be re-segmented and applied to different catchments as required. In this paper, the intermediate models, QWASI matrix-rate constant (QMX-R) and QWASI matrix-fugacity (QMX-F) are used to estimate concentrations of linear alkylbenzene sulfonates (LAS) in the rivers Aire and Calder, UK, and of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in the Fraser River basin, Canada. The results compare satisfactorily with monitoring data, suggesting that these QWASI-based models for exposure and risk assessment may be applicable under data-limited conditions. The use of QWASI-based models for regulatory purposes in an evaluative river system is also discussed with reference to assessments of para-dichlorobenzene (pDCB), trichloroethylene (TCE), bis(2-ethylhexyl) phthalate (DEHP) and toluene. It is shown that multi-media QWASI model predictions can be usefully depicted graphically on chemical space diagrams and used to highlight regions in which advection, partitioning to sediments and volatilization may be important determinants of chemical fate in river systems.

The Terrestrial Water Cycle: Modeling and Data Assimilation across Catchment Scales

Hydrologic science is currently undergoing a revolution in which the field is being transformed by the multitude of available new data streams. Historically, hydrologic models that have been developed to answer basic questions about rainfall–runoff relationships, surface water and groundwater storage and fluxes, land– atmosphere interactions, and so forth, have been optimized for previously data-limited conditions. However, with the advent of remote sensing technologies and increased computational resources, the environment for water cycle researchers has fundamentally changed to one where there is now a flood of spatially distributed and time-dependent data. This transition from a “data poor” to a “data rich” environment has allowed for an increase in the scope and scale of research questions and practical problems that can be addressed, but also requires that we fundamentally change our approaches to solving these problems. Largely due to a lack of historical data, the mean states and fluxes in the terrestrial water cycle remain poorly characterized. Development of diagnostic and predictive frameworks for characterizing the mean states and their natural variability is a crucial first step in understanding how they may be altered under anthropogenic climate change. The buildup of greenhouse gases during the past century is postulated to be responsible for global warming through increased radiative forcing of the earth system. Changes in the energy balance of earth are likely to affect other climatic factors besides temperature, including the components of the terrestrial water cycle. For example, atmospheric moisture amounts (and thus precipitable water) in the Northern Hemisphere are generally observed to have increased since 1973 (Ross and Elliott 2001). An increase of a few percent in atmospheric moisture is expected to lead to stronger rainfall rates (Trenberth et al. 2003). In terms of evaporation, even though a very robust finding in all climate models with global warming is for an increase in potential evapotranspiration (IPCC 2001), recent studies (e.g., Peterson et al. 1995; Brutsaert and Parlange 1998; Ohmura and Wild 2002; Roderick and Farquhar 2002) indicate there is still a debate about whether land evaporation will increase or decrease under a warming climate. In any case, a reduction in or an augmentation of the global terrestrial evaporation, combined with the increasing trend in global precipitation, will have to be balanced by changes in runoff and soil moisture, and this will effectively spin down or accelerate the hydrological cycle (Ramanathan et al. 2001). Milly et al. (2002) investigated the changes in risk of large floods using both streamflow observations and numerical simulations of anthropogenic climate change. They found that the frequency of large floods increased substantially during the twentieth century, and that this trend would continue into the twenty-first century. However, the frequency of floods with shorter return periods did not increase significantly. Therefore, evidence would seem to indicate that a potential consequence of global warming is the acceleration of the hydrological cycle. The ability to detect * Organizers of the International Workshop on Terrestrial Water Cycle.

Evidence for an Activation Locus of the Word-Frequency Effect in Lexical Decision.

The authors report a lexical decision experiment designed to determine whether activation is the locus of the word-frequency effect. K. R. Paap and L. S. Johansen (1994) reported that word frequency did not affect lexical decisions when exposure durations were brief; they accounted for this by proposing that data-limited conditions prevented late-occurring verification processes. Subsequently, P. A. Allen, A. F. Smith, M. Lien, T. A. Weber, and D. J. Madden (1997) and K. R. Paap, L. S. Johansen, E. Chun, and P. Vonnahme (2000) reported additional evidence that word-frequency effects do and do not have an activation locus, respectively. The authors further tested this issue in a lexical decision experiment using data-limited procedures--predicted by verification models to eliminate word-frequency effects. The authors observed word-frequency effects using individually determined exposure durations that were only 1 screen cycle longer than the exposure duration that yielded chance performance. Word-frequency effects persisted even when an adjusted measure of performance was used.

Age-related changes in selective attention and perceptual load during visual search.

Three visual search experiments were conducted to test the hypothesis that age differences in selective attention vary as a function of perceptual load (E. A. Maylor & N. Lavie, 1998). Under resource-limited conditions (Experiments 1 and 2), the distraction from irrelevant display items generally decreased as display size (perceptual load) increased. This perceptual load effect was similar for younger and older adults, contrary to the findings of Maylor and Lavie. Distraction at low perceptual loads appeared to reflect both general and specific inhibitory mechanisms. Under more data-limited conditions (Experiment 3), an age-related decline in selective attention was evident, but the age difference was not attributable to capacity limitations as predicted by the perceptual load theory.

Receiver operating characteristics in the lexical decision task: evidence for a simple signal-detection process simulated by the multiple read-out model.

This study provides further evidence for the hypothesis that performance in the lexical decision task is based on the output of a signal detection mechanism, as implemented by the multiple read-out model of word recognition (MROM; J. Grainger & A. M. Jacobs, 1996). We extend the MROM to allow predictions of receiver operating characteristics in a data-limited variant of the lexical decision task and show that the model provides accurate descriptions of the data. Our results challenge all models of word recognition that do not include a familiarity assessment mechanism. They also suggest that under data-limited conditions a deadline mechanism for generating "no" responses in the lexical decision task may not necessarily be functional.

Phonological Information Provides Early Sources of Constraint in the Processing of Letter Strings

Three experiments addressed the role of phonological information in visual word recognition using a letter search task. Subjects were presented with a target letter (e.g., "I") followed by a letter string (a word, a pseudohomophone, a pseudoword control, or a nonword). Their task was to indicate whether the target letter was present in the letter string. All experiments presented pseudohomophones (e.g., TAIP or BRANE) that either contained a letter (I) that was absent in their sound-alike word (TAPE) or were missing a letter (I) that was present in their sound-alike word (BRAIN). In Experiments 1 and 2, subjects made more miss errors under data-limited conditions when the letter string was a target-present pseudohomophone (TAIP) and more false alarm errors when the letter string was a target-absent pseudohomophone (BRANE). Experiment 2 controlled for a possible confound in the data in terms of word completion strategies. In Experiment 3, we replicated the pseudohomophone disadvantage using resource-limited conditions: detection times were longer for pseudohomophones. The existence of a pseudohomophone disadvantage in a supposedly graphemic task adds further support to the accumulating evidence that phonological information generated from the printed word is an early and major constraint in visual word recognition.

Effects of aging on priming and skill learning.

This study examined the effects of aging on 2 kinds of implicit memory; repetition priming and skill learning. In Experiment 1, older adults showed less improvement in the skill of reading inverted words than did young adults, but priming performance did not differ for the 2 age groups. Similarly, in Experiment 2, in a partial-word identification task, skill learning was observed only for young adults, whereas there was no age difference in priming. Experiments 1a and 2a, however, showed that when older adults were presented with more perceptual information than were young adults, the age deficit in skill learning was eliminated. These results indicate that skill learning is impaired under data-limited conditions, whereas priming is unaffected under these conditions. It is proposed that the age deficit in skill learning is related to a deficit in perceptual organization and reorganization.

Identification of Letters in the Predesignated Target Paradigm: A Word Superiority Effect for the Common Word the

The size of the perceptual unit used in reading was addressed using the predesignated target paradigm. Sixteen subjects viewed the following stimuli in random order: the words tee, the, tie, and toe; the nonwords eet, eht, eit, and eot; and the letters e, h, i, and o. Subjects fixated on the location of the center letter and identified the letter as e, h, i, or o, alternatives which were known to them at the onset. A word superiority effect was obtained for the common word the but not for the less common words tee, tie, and toe. The word superiority effect was attributable to bias rather than discriminability: Subjects exhibited a bias to perceive the words in this experiment as the (i.e., there was a bias to perceive h in the t e stimulus presentations). These results suggest that the common word the is processed in reading units that are larger than the letter, and that the system is biased to perceive common rather than uncommon words in data-limited conditions.