Three-dimensional computer-assisted design of craniofacial surgical procedures: optimization and interaction with cephalometric and CT-based models

A computer program is described which aids the clinician in planning craniofacial surgical procedures. It operates on a three-dimensional landmark data base derived by combining posteroanterior and lateral cephalograms from the patient and from the Bolton normative standards. A three-dimensional surgical simulation program based on computerized tomographic (CT) data is also described which can be linked to the cephalometrically based program. After the clinician has selected the number and type of osteotomies to be performed on the patient, an automated optimization program computes the postoperative positions of these fragments which best fit the appropriate normal cephalometric form. The clinician then interactively modifies the design to account for such variables as bone-graft resorption, relapse tendency, occlusal disparities, and the condition of the overlying soft-tissue matrix. Osteotomy movement specifications are easily transferred between the CT-based and the cephalometrically based surgical simulation programs. This allows the automated positioning step to be performed on the cephalometrically based model while the interactive step is performed using the superior image provided by the CT-based model.     

The development of tool manufacture in humans: what helps young children make innovative tools?

We know that even young children are proficient tool users, but until recently, little was known about how they make tools. Here, we will explore the concepts underlying tool making, and the kinds of information and putative cognitive abilities required for children to manufacture novel tools. We will review the evidence for novel tool manufacture from the comparative literature and present a growing body of data from children suggesting that innovation of the solution to a problem by making a tool is a much more challenging task than previously thought. Children''s difficulty with these kinds of tasks does not seem to be explained by perseveration with unmodified tools, difficulty with switching to alternative strategies, task pragmatics or issues with permission. Rather, making novel tools (without having seen an example of the required tool within the context of the task) appears to be hard, because it is an example of an ‘ill-structured problem’. In this type of ill-structured problem, the starting conditions and end goal are known, but the transformations and/or actions required to get from one to the other are not specified. We will discuss the implications of these findings for understanding the development of problem-solving in humans and other animals.     

Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible.     

Longitudinal Stability in Reading Comprehension Is Largely Heritable from Grades 1 to 6

Reading comprehension is a foundational academic skill and significant attention has focused on reading development. This report is the first to examine the stability and change in genetic and environmental influences on reading comprehension across Grades 1 to 6. This developmental range is particularly important because it encompasses the timespan in which most children move from learning how to read to using reading for learning. Longitudinal simplex models were fitted separately for two independent twin samples (N = 706; N = 976). Results suggested that the shared environment contributed to variance in early but not later reading. Instead, stability in reading development was largely mediated by continuous genetic influences. Thus, although reading is clearly a learned skill and the environment remains important for reading development, individual differences in reading comprehension appear to be also influenced by a core of genetic stability that persists through the developmental course of reading.     

The relationship between sea surface temperature and population change of Great Cormorants Phalacrocorax carbo breeding near Disko Bay,Greenland

Arctic seas have warmed and sea ice has retreated. This has resulted in range contraction and population declines in some species, but it could potentially be a boon for others. Great Cormorants Phalacrocorax carbo have a partially wettable plumage and seem poorly suited to foraging in Arctic waters. We show that rates of population change of Cormorant colonies around Disko Bay, Greenland, are positively correlated with sea surface temperature, suggesting that they may benefit from a warming Arctic. However, although Cormorant populations may increase in response to Arctic warming, the extent of expansion of their winter range may ultimately be limited by other factors, such as sensory constraints on foraging behaviour during long Arctic nights.     

Future climate‐driven shifts in distribution of Calanus finmarchicus

Calanus finmarchicus is a key‐structural species of the North Atlantic polar biome. The species plays an important trophic role in subpolar and polar ecosystems as a grazer of phytoplankton and as a prey for higher trophic levels such as the larval stages of many fish species. Here, we used a recently developed ecological niche model to assess the ecological niche (sensu Hutchinson) of C. finmarchicus and characterize its spatial distribution. This model explained about 65% of the total variance of the observed spatial distribution inferred from an independent dataset (data of the continuous plankton recorder survey). Comparisons with other types of models (structured population and ecophysiological models) revealed a clear similarity between modeled spatial distributions at the scale of the North Atlantic. Contemporary models coupled with future projections indicated a progressive reduction of the spatial habitat of the species at the southern edge and a more pronounced one in the Georges Bank, the Scotian Shelf and the North Sea and a potential increase in abundance at the northern edge of its spatial distribution, especially in the Barents Sea. These major changes will probably lead to a major alteration of the trophodynamics of North Atlantic ecosystems affecting the trophodynamics and the biological carbon pump.