Neurobiological model of visuo-spatial cognition in young Williams Syndrome children: measures of dorsal-stream and frontal function

We examine hypotheses for the neural basis of the profile of visual cognition in young children with Williams syndrome (WS). These are: (a) that it is a consequence of anomalies in sensory visual processing; (b) that it is a deficit of the dorsal relative to the ventral cortical stream; (c) that it reflects deficit of frontal function, in particular of fronto-parietal interaction; (d) that it is related to impaired function in the right hemisphere relative to the left. The tests reported here are particularly relevant to (b) and (c). They form part of a more extensive programme of investigating visual, visuospatial, and cognitive function in large group of children with WS children, aged 8 months to 15 years. To compare performance across tests, avoiding floor and ceiling effects, we have measured performance in children with WS in terms of the ‘age equivalence’ for typically developing children. In this paper the relation between dorsal and ventral function was tested by motion and form coherence thresholds respectively. We confirm the presence of a subgroup of children with WS who perform particularly poorly on the motion (dorsal) task. However, such performance is also characteristic of normally developingchildren up to 5 years: thus the WS performance may reflect an overall persisting immaturity of visuospatial processing which is particularly evident in the dorsal stream. Looking at the performance on the global coherence tasks of the entire WS group, we find that there is also a subgroup who have both high form and motion coherence thresholds, relative to the performance of children of the same chronological age and verbal age on the BPVS, suggesting a more general global processing deficit. Frontal function was tested by a counterpointing task, ability to retrieve a ball from a ‘detour box’, and the Stroop-like ‘day-night’ task, all of which require inhibition of a familiar response. When considered in relation to overall development as indexed by vocabulary, the day-night task shows little specific impairment, the detour box shows a significant delay relative to controls, and the counterpointing task shows a marked and persistent deficit in many children. We conclude that frontal control processes show most impairment in WS when they are associated with spatially directed responses, reflecting a deficit of fronto-parietal processing. However, children with WS may successfully reduce the effect of this impairment by verbally mediated strategies. On all these tasks we find a range of difficulties across individual children and a small subset of WS who show very good performance, equivalent to chronological age norms of typically developing children. Neurobiological models of visuo-spatial cognition in children with WS p.4 Overall, we conclude that children with WS have specific processing difficulties with tasks involving frontoparietal circuits within the spatial domain. However, some children with WS can achieve similar performance to typically developing children on some tasks involving the dorsal stream, although the strategies and processing may be different in the two groups.

Chironomid-based reconstructions of summer air temperature from lake deposits in Lyndon Stream, New Zealand spanning the MIS 3/2 transition

We present chironomid-based temperature reconstructions from lake sediments deposited between ca 26,600 cal yr BP and 24,500 cal yr BP from Lyndon Stream, South Island, New Zealand. Summer (February mean) temperatures averaged 1 1C cooler, with a maximum inferred cooling of 3.7 1C. These estimates corroborate macrofossil and beetle-based temperature inferences from the same site and suggest climate amelioration (an interstadial) at this time. Other records from the New Zealand region also show a large degree of variability during the late Otiran glacial sequence (34,000–18,000 cal yr BP) including a phase of warming at the MIS 2/3 transition and a maximum cooling that did not occur until the global LGM (ca 20,000 cal yr BP). The very moderate cooling identified here at the MIS 2/3 transition confirms and enhances the long-standing discrepancy in New Zealand records between pollen and other proxies. Low abundances (o20%) of canopy tree pollen in records from late MIS 3 to the end of MIS 2 cannot be explained by the minor (o5 1C) cooling inferred from this and other studies unless other environmental parameters are considered. Further work is required to address this critical issue.

Palaeoclimate change recorded in Upper Cretaceous (Albian-Cenomanian) Kazhdumi Formation Borehole spectral Gamma-Ray Logs, South Pars Gas field, Persian Gulf

Th/U and Th/K data from spectral gamma-ray logs obtained from outcrop successions have been used as a rapid and inexpensive proxy for determining possible episodes of humid-arid palaeoclimate change. Such outcrop-based measurements have never been tested using spectral gamma-ray data obtained from wireline logs in subsurface boreholes. Th/K and Th/U ratios have traditionally been used to decipher sequence stratigraphic patterns, at outcrop and in borehole. The possible influence of palaeoclimate on such ratio changes has yet to be proven, especially from borehole data. In this work, we compare borehole-derived Th/K (and to a lesser extent Th/U) to palaeoenvironmental changes inferred from palynology and deduce that both sea level and changing hinterland weathering regimes caused discrete fluctuations observed in the spectral gamma-ray logs. This is the first time such subsurface information has been used in this way. Interpretation of wireline logs in terms of palaeoclimate as well as sea level may now be considered, and the use of such logs in palaeoclimate reconstruction is strengthened.

The use of short time-on-stream in situ spectroscopic transient kinetic isotope techniques to investigate the mechanism of hydrocarbon selective catalytic reduction (HC-SCR) of NOx at low temperatures

The problem of differentiating between active and spectator species that have similar infrared spectra has been addressed by developing short time-on-stream in situ spectroscopic transient isotope experimental techniques (STOS-SSITKA). The techniques have been used to investigate the reaction mechanism for the reduction of nitrogen oxides (NOx) by hydrocarbons under lean-burn (excess oxygen) conditions on a silver catalyst. Although a nitrate-type species tracks the formation of isotopically labeled dinitrogen, the results show that this is misleading because a nitrate-type species has the same response to an isotopic switch even under conditions where no dinitrogen is produced. In the case of cyanide and isocyanate species, the results show that it is possible to differentiate between slowly reacting spectator isocyanate species, probably adsorbed on the oxide support, and reactive isocyanate species, possibly on or close to the active silver phase. The reactive isocyanate species responds to an isotope switch at a rate that matches that of the rate of formation of the main product, dinitrogen. It is concluded that these reactive isocyanates could potentially be involved in the reduction of NOx whereas there is no evidence to support the involvement of nitrate-type species that are observable by infrared spectroscopy.

Incremental learning from stream data

Recent years have witnessed an incredibly increasing interest in the topic of incremental learning. Unlike conventional machine learning situations, data flow targeted by incremental learning becomes available continuously over time. Accordingly, it is desirable to be able to abandon the traditional assumption of the availability of representative training data during the training period to develop decision boundaries. Under scenarios of continuous data flow, the challenge is how to transform the vast amount of stream raw data into information and knowledge representation, and accumulate experience over time to support future decision-making process. In this paper, we propose a general adaptive incremental learning framework named ADAIN that is capable of learning from continuous raw data, accumulating experience over time, and using such knowledge to improve future learning and prediction performance. Detailed system level architecture and design strategies are presented in this paper. Simulation results over several real-world data sets are used to validate the effectiveness of this method.