Predictive feedback control and Fitts' law

Fitts’ law is a well established empirical formula, known for encapsulating the “speed-accuracy trade-off”. For discrete, manual movements from a starting location to a target, Fitts’ law relates movement duration to the distance moved and target size. The widespread empirical success of the formula is suggestive of underlying principles of human movement control. There have been previous attempts to relate Fitts’ law to engineering-type control hypotheses and it has been shown that the law is exactly consistent with the closed-loop step-response of a time-delayed, first-order system. Assuming only the operation of closed-loop feedback, either continuous or intermittent, this paper asks whether such feedback should be predictive or not predictive to be consistent with Fitts law. Since Fitts’ law is equivalent to a time delay separated from a first-order system, known control theory implies that the controller must be predictive. A predictive controller moves the time-delay outside the feedback loop such that the closed-loop response can be separated into a time delay and rational function whereas a non- predictive controller retains a state delay within feedback loop which is not consistent with Fitts’ law. Using sufficient parameters, a high-order non-predictive controller could approximately reproduce Fitts’ law. However, such high-order, “non-parametric” controllers are essentially empirical in nature, without physical meaning, and therefore are conceptually inferior to the predictive controller. It is a new insight that using closed-loop feedback, prediction is required to physically explain Fitts’ law. The implication is that prediction is an inherent part of the “speed-accuracy trade-off”

Calcitization of aragonitic bryozoans in Cenozoic tropical carbonates from East Kalimantan, Indonesia

© The Author(s) 2016. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The file attached is the published version of the article

Change and Aging Senescence as an adaptation

Understanding why we age is a long-lived open problem in evolutionary biology. Aging is prejudicial to the individual and evolutionary forces should prevent it, but many species show signs of senescence as individuals age. Here, I will propose a model for aging based on assumptions that are compatible with evolutionary theory: i) competition is between individuals; ii) there is some degree of locality, so quite often competition will between parents and their progeny; iii) optimal conditions are not stationary, mutation helps each species to keep competitive. When conditions change, a senescent species can drive immortal competitors to extinction. This counter-intuitive result arises from the pruning caused by the death of elder individuals. When there is change and mutation, each generation is slightly better adapted to the new conditions, but some older individuals survive by random chance. Senescence can eliminate those from the genetic pool. Even though individual selection forces always win over group selection ones, it is not exactly the individual that is selected, but its lineage. While senescence damages the individuals and has an evolutionary cost, it has a benefit of its own. It allows each lineage to adapt faster to changing conditions. We age because the world changes.Comment: 19 pages, 4 figure

Essential elements of an early intervention service for psychosis: the opinions of expert clinicians

BACKGROUND: Early intervention teams attempt to improve outcome in schizophrenia through earlier detection and the provision of phase-specific treatments. Whilst the number of early intervention teams is growing, there is a lack of clarity over their essential structural and functional elements. METHODS: A 'Delphi' exercise was carried out to identify how far there was consensus on the essential elements of early intervention teams in a group of 21 UK expert clinicians. Using published guidelines, an initial list was constructed containing 151 elements from ten categories of team structure and function. RESULTS: Overall there was expert consensus on the importance of 136 (90%) of these elements. Of the items on which there was consensus, 106 (70.2%) were rated essential, meaning that in their absence the functioning of the team would be severely impaired. CONCLUSION: This degree of consensus over essential elements suggests that it is reasonable to define a model for UK early intervention teams, from which a measure of fidelity could be derived

Using Simulation Models to Evaluate Ape Nest Survey Techniques

BACKGROUND: Conservationists frequently use nest count surveys to estimate great ape population densities, yet the accuracy and precision of the resulting estimates are difficult to assess. METHODOLOGY/PRINCIPAL FINDINGS: We used mathematical simulations to model nest building behavior in an orangutan population to compare the quality of the population size estimates produced by two of the commonly used nest count methods, the 'marked recount method' and the 'matrix method.' We found that when observers missed even small proportions of nests in the first survey, the marked recount method produced large overestimates of the population size. Regardless of observer reliability, the matrix method produced substantial overestimates of the population size when surveying effort was low. With high observer reliability, both methods required surveying approximately 0.26% of the study area (0.26 km(2) out of 100 km(2) in this simulation) to achieve an accurate estimate of population size; at or above this sampling effort both methods produced estimates within 33% of the true population size 50% of the time. Both methods showed diminishing returns at survey efforts above 0.26% of the study area. The use of published nest decay estimates derived from other sites resulted in widely varying population size estimates that spanned nearly an entire order of magnitude. The marked recount method proved much better at detecting population declines, detecting 5% declines nearly 80% of the time even in the first year of decline. CONCLUSIONS/SIGNIFICANCE: These results highlight the fact that neither nest surveying method produces highly reliable population size estimates with any reasonable surveying effort, though either method could be used to obtain a gross population size estimate in an area. Conservation managers should determine if the quality of these estimates are worth the money and effort required to produce them, and should generally limit surveying effort to 0.26% of the study area, unless specific management goals require more intensive sampling. Using site- and time- specific nest decay rates (or the marked recount method) are essential for accurate population size estimation. Marked recount survey methods with sufficient sampling effort hold promise for detecting population declines

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

7-Substituted 2-Nitro-5,6-dihydroimidazo[2,1-b][1,3]oxazines: Novel Antitubercular Agents Lead to a New Preclinical Candidate for Visceral Leishmaniasis.

Within a backup program for the clinical investigational agent pretomanid (PA-824), scaffold hopping from delamanid inspired the discovery of a novel class of potent antitubercular agents that unexpectedly possessed notable utility against the kinetoplastid disease visceral leishmaniasis (VL). Following the identification of delamanid analogue DNDI-VL-2098 as a VL preclinical candidate, this structurally related 7-substituted 2-nitro-5,6-dihydroimidazo[2,1-b][1,3]oxazine class was further explored, seeking efficacious backup compounds with improved solubility and safety. Commencing with a biphenyl lead, bioisosteres formed by replacing one phenyl by pyridine or pyrimidine showed improved solubility and potency, whereas more hydrophilic side chains reduced VL activity. In a Leishmania donovani mouse model, two racemic phenylpyridines (71 and 93) were superior, with the former providing >99% inhibition at 12.5 mg/kg (b.i.d., orally) in the Leishmania infantum hamster model. Overall, the 7R enantiomer of 71 (79) displayed more optimal efficacy, pharmacokinetics, and safety, leading to its selection as the preferred development candidate

Leadership and decision-making practices in public versus private universities in Pakistan

The goal of this study is to examine differences in leadership and decision-making practices in public and private universities in Pakistan, with a focus on transformational leadership (TL) and participative decision-making (PDM). We conducted semi-structured interviews with 46 deans and heads of department from two public and two private universities in Pakistan. Our findings indicate that leadership and decision-making practices are different in public and private universities. While differences were observed in all six types of TL-behaviour, the following three approaches emerged to be crucial in both public and private universities: (1) articulating a vision, (2) fostering the acceptance of group goals, and (3) high-performance expectations. In terms of PDM, deans and heads of department in public and private universities adopt a collaborative approach. However, on a practical level this approach is limited to teacher- and student-related matters. Overall, our findings suggest that the leadership and decision-making practices in Pakistani public and private universities are transformational and participative in nature