Behavioural simulation of biological neuron systems using VHDL and VHDL-AMS

The investigation of neuron structures is an incredibly difficult and complex task that yields relatively low rewards in terms of information from biological forms (either animals or tissue). The structures and connectivity of even the simplest invertebrates are almost impossible to establish with standard laboratory techniques, and even when this is possible it is generally time consuming, complex and expensive. Recent work has shown how a simplified behavioural approach to modelling neurons can allow “virtual” experiments to be carried out that map the behaviour of a simulated structure onto a hypothetical biological one, with correlation of behaviour rather than underlying connectivity. The problems with such approaches are numerous. The first is the difficulty of simulating realistic aggregates efficiently, the second is making sense of the results and finally, it would be helpful to have an implementation that could be synthesised to hardware for acceleration. In this paper we present a VHDL implementation of Neuron models that allow large aggregates to be simulated. The models are demonstrated using a system level VHDL and VHDL-AMS model of the C. Elegans locomotory system

Upgrading the Employment Scene in Chicago

Appalled at the degree to which employment interviews at the annual AACTE convention too often seem cold, aloof, and negative, educators Bailey and Wilson offer suggestions to help rehumanize the process

Allele frequency misspecification: effect on power and Type I error of model-dependent linkage analysis of quantitative traits under random ascertainment

BACKGROUND: Studies of model-based linkage analysis show that trait or marker model misspecification leads to decreasing power or increasing Type I error rate. An increase in Type I error rate is seen when marker related parameters (e.g., allele frequencies) are misspecified and ascertainment is through the trait, but lod-score methods are expected to be robust when ascertainment is random (as is often the case in linkage studies of quantitative traits). In previous studies, the power of lod-score linkage analysis using the "correct" generating model for the trait was found to increase when the marker allele frequencies were misspecified and parental data were missing. An investigation of Type I error rates, conducted in the absence of parental genotype data and with misspecification of marker allele frequencies, showed that an inflation in Type I error rate was the cause of at least part of this apparent increased power. To investigate whether the observed inflation in Type I error rate in model-based LOD score linkage was due to sampling variation, the trait model was estimated from each sample using REGCHUNT, an automated segregation analysis program used to fit models by maximum likelihood using many different sets of initial parameter estimates. RESULTS: The Type I error rates observed using the trait models generated by REGCHUNT were usually closer to the nominal levels than those obtained when assuming the generating trait model. CONCLUSION: This suggests that the observed inflation of Type I error upon misspecification of marker allele frequencies is at least partially due to sampling variation. Thus, with missing parental genotype data, lod-score linkage is not as robust to misspecification of marker allele frequencies as has been commonly thought

Differences in the nutritional quality of improved finger millet genotypes in Ethiopia

Improved crop genotypes are constantly introduced. However, information on their nutritional quality is generally limited. The present study reports the proximate composition and the concentration and relative bioavailability of minerals of improved finger millets of different genotypes. Grains of finger millet genotypes (n = 15) grown in research station during 2019 and 2020 in Ethiopia, and replicated three times in a randomized complete block design, were analysed for proximate composition, mineral concentration (iron, zinc, calcium, selenium), and antinutritional factors (phytate, tannin and oxalate). Moreover, the antinutritional factors to mineral molar ratio method was used to estimate mineral bioavailability. The result shows a significant genotypic variation in protein, fat and fibre level, ranging from 10% to 14.6%, 1.0 to 3.8%, and 1.4 to 4.6%, respectively. Similarly, different finger millets genotypes had significantly different mineral concentrations ranging from 3762 ± 332 to 5893 ± 353 mg kg−1 for Ca, 19.9 ± 1.6 to 26.2 ± 2.7 mg kg−1 for Zn, 36.3 ± 4.6 to 52.9 ± 9.1 mg kg−1 for Fe and 36.6 ± 11 to 60.9 ± 22 µg kg−1 for Se. Phytate (308–360 µg g−1), tannin (0.15–0.51 mg g−1) and oxalate (1.26–4.41 mg g−1) concentrations were also influenced by genotype. Antinutritional factors to minerals molar ratio were also significantly different by genotypes but were below the threshold for low mineral bioavailability. Genotype significantly influenced mineral and antinutritional concentrations of finger millet grains. In addition, all finger millet genotypes possess good mineral bioavailability. Especially, the high Ca concentration in finger millet, compared to in other cereals, could play a vital role to combating Ca deficiency. The result suggests the different finger millet genotypes possess good nutrient content and may contribute to the nutrition security of the local people

Composition profiles of InAs–GaAs quantum dots determined by medium-energy ion scattering

The composition profile along the [001] growth direction of low-growth-rate InAs–GaAs quantum dots (QDs) has been determined using medium-energy ion scattering (MEIS). A linear profile of In concentration from 100% In at the top of the QDs to 20% at their base provides the best fit to MEIS energy spectra

Risk estimation using probability machines

BACKGROUND: Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. RESULTS: We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. CONCLUSIONS: The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from

The Music Therapist in School as Outsider

This essay examines the institutional commonalities among several schools in which I have worked as a music therapist, illustrating how thinking about my role as an outsider has informed my therapeutic approach. I refer to the broader concept of the outsider as it relates to both fictional and historical figures and in particular to Sherly Williams's article 'The Therapist as Outsider: The Truth of the Stranger' (1999) in which she compares the therapist to the archetypal figures of the fool and the seer. Finally, I link these ideas to Winnicott's concept of play, presenting the music therapist's role in school as that of an advocate for fostering creative impulses, which can at times be at odds with (or perhaps complementary to) the central educational aims of the school