Processing speed, executive function, and age differences in remembering and knowing.

A group of young (n = 52, M = 23.27 years) and old (n = 52, M = 68.62 years) adults studied two lists of semantically unrelated nouns. For one list a time of 2 s was allowed for encoding, and for the other, 5 s. A recognition test followed where participants classified their responses according to Gardiner's (1988) remember-know procedure. Age differences for remembering and knowing were minimal in the faster 2-s encoding condition. However, in the longer 5-s encoding condition, younger persons produced significantly more remember responses, and older adults a greater number of know responses. This dissociation suggests that in the longer encoding condition, younger adults utilized a greater level of elaborative rehearsal governed by executive processes, whereas older persons employed maintenance rehearsal involving short-term memory. Statistical control procedures, however, found that independent measures of processing speed accounted for age differences in remembering and knowing and that independent measures of executive control had little influence. The findings are discussed in the light of contrasting theoretical accounts of recollective experience in old age

The Use of Loglinear Models for Assessing Differential Item Functioning Across Manifest and Latent Examinee Groups

Loglinear latent class models are used to detect differential item functioning (DIF). These models are formulated in such a manner that the attribute to be assessed may be continuous, as in a Rasch model, or categorical, as in Latent Class Mastery models. Further, an item may exhibit DIF with respect to a manifest grouping variable, a latent grouping variable, or both. Likelihood-ratio tests for assessing the presence of various types of DIF are described, and these methods are illustrated through the analysis of a "real world" data set

Image recognition with an adiabatic quantum computer I. Mapping to quadratic unconstrained binary optimization

Many artificial intelligence (AI) problems naturally map to NP-hard optimization problems. This has the interesting consequence that enabling human-level capability in machines often requires systems that can handle formally intractable problems. This issue can sometimes (but possibly not always) be resolved by building special-purpose heuristic algorithms, tailored to the problem in question. Because of the continued difficulties in automating certain tasks that are natural for humans, there remains a strong motivation for AI researchers to investigate and apply new algorithms and techniques to hard AI problems. Recently a novel class of relevant algorithms that require quantum mechanical hardware have been proposed. These algorithms, referred to as quantum adiabatic algorithms, represent a new approach to designing both complete and heuristic solvers for NP-hard optimization problems. In this work we describe how to formulate image recognition, which is a canonical NP-hard AI problem, as a Quadratic Unconstrained Binary Optimization (QUBO) problem. The QUBO format corresponds to the input format required for D-Wave superconducting adiabatic quantum computing (AQC) processors.Comment: 7 pages, 3 figure

The impact of climate change on the archaeology of New Zealand’s coastline

Abstract: With rising sea levels, changes in precipitation patterns and an increased incidence of severe weather events being predicted as a result of global climate change, the Department of Conservation commissioned a study to determine the potential impacts of these effects on New Zealand’s archaeological sites, which are mostly located near the coast. A Geographic Information System (GIS)-based case study examined the distribution of archaeological sites in the Whangarei District and assessed the risk to the archaeological resource primarily from sea level rise associated with future climate change.The results of the analysis are fairly conclusive. Currently, the major threats to archaeological sites in coastal areas are erosion, flooding and ground instability, and some sites are at risk from more than one of these threats. Approximately one-third of the recorded site locations in the Whangarei District are potentially threatened by these hazards, regardless of any future climate change effects. Climate change will exacerbate existing coastal hazards, and increase the likelihood and severity of impacts on archaeological sites. An additional 2.5–10% of archaeological sites might be affected by increased threats due to predicted changes in climate, including rising sea levels. The types of sites that are most likely to be affected in the Whangarei District are coastal midden and small habitation sites relating to Māori occupation. Although these could be affected by all three of the major hazards identified, they are particularly susceptible to coastal erosion. Land stability issues and flooding are likely to affect a greater range of sites, including larger sites such as pā and sites relating to early European settlement. It is not possible to quantify the risk to sites from increased land instability as a result of global climate change, but it is noted that any increase in extreme weather events would not be confined to coastal areas. These sites potentially hold significant information relating to the history of both the district and New Zealand. The implications of the study are that coastal sites are already under considerable threat, and that important archaeological information is being lost at a rate that may increase significantly in the future. Action is needed now to protect or retrieve the information from significant sites under threat in coastal areas before these sites disappear completely

Defining small catchment runoff responses using hillslope hydrological process observations.

Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2000.The Umzimvubu catchment on the eastern coastal escarpment of South Africa is sensitive to anthropogenic influences,with commercial and subsistence agriculture, irrigation, domestic and rural settlements and forestry compete for water use. An adequate supply of water to the region is seen as imperative in the light of the recent establishment of forest cultivation. In order to provide a sound assessment of the impacts of afforestation on the catchment, the subsurface hydrological processes of hillslopes on the Molteno sedimentary formations of the region must be clearly understood. Since the runoff hydrograph is, to a large degree, dependent on the subsurface processes, a number of models that simulate small catchment runoff have been developed. However, recent successful application of tracer techniques to hydrological modelling has shown that the subsurface processes are still not fully understood (Schultz, 1999), and whether or not the subsurface processes are modelled adequately is most often not verified, since there is a lack of relevant data. It is, therefore imperative that the subsurface component of these small catchment runoff models be improved. This can be achieved by first observing detailed subsurface water dynamics and assessing these against the catchment runoff response. In this dissertation, results from a detailed experiment that was initiated in a 1.5 km2 catchment in the northern East Cape Province are shown. Nests of automated tensiometers, groundwater level recorders and weather stations have been placed at critical points around the catchment, and these , together with soil hydraulic and physical characteristics are used to define and identify the dominant hillslope processes. Two crump weirs record runoff from these hillslopes. The results of this subsurface study highlight the dynamics of surface and subsurface water in the hillslope transects. It is evident that the subsurface processes are strongly influenced by the -bedrock topography as well as the soil characteristics, such as macropore flow and deep percolation. Using the monitored data and 2-D vadose zone modelling, the dominant hillslope processes have been defined and are used to aid in the selection of critical parameters to be used in estimating the catchment runoff. Results show that a clear understanding of the subsurface dynamics can lead to a realistic estimation of catchment scale runoff response