Completeness for sequential sampling plans

In the sequential multinomial sampling case,a sufficient condition for a non-randomized sequential procedure to be complete is given,and also a necessary and sufficient condition for a randomized sequential procedure to be complete is obtained

Methodological framework for projecting the potential loss of intraspecific genetic diversity due to global climate change

Background: While research on the impact of global climate change (GCC) on ecosystems and species is flourishing, a fundamental component of biodiversity -- molecular variation -- has not yet received its due attention in such studies. Here we present a methodological framework for projecting the loss of intraspecific genetic diversity due to GCC. Methods: The framework consists of multiple steps that and combines 1) hierarchical genetic clustering methods to define comparable units of inference, 2) species accumulation curves (SAC) to infer sampling completeness, and 3) species distribution modelling (SDM) to project the genetic diversity loss under GCC. We suggest procedures for existing data sets as well as specifically designed studies. We illustrate the approach with two worked examples from a land snail (Trochulus villosus) and a caddisfly (Smicridea (S.) mucronata). Results: Sampling completeness was diagnosed on the third most coarse haplotype clade level for T. villosus and the second most coarse for S. mucronata. For both species, a substantial species range loss was projected under the chosen climate scenario. However, despite substantial differences in data set quality concerning spatial sampling and sampling depth, no loss of haplotype clades due to GCC was predicted for either species. Conclusions: The suggested approach presents a feasible method to tap the rich resources of existing phylogeographic data sets and guide the design and analysis of studies explicitly designed to estimate the impact of GCC on a currently still neglected level of biodiversity

Completeness of Randomized Kinodynamic Planners with State-based Steering

Probabilistic completeness is an important property in motion planning. Although it has been established with clear assumptions for geometric planners, the panorama of completeness results for kinodynamic planners is still incomplete, as most existing proofs rely on strong assumptions that are difficult, if not impossible, to verify on practical systems. In this paper, we focus on an important class of kinodynamic planners, namely those that interpolate trajectories in the state space. We provide a proof of probabilistic completeness for these planners under assumptions that can be readily verified from the system's equations of motion and the user-defined interpolation function. Our proof relies crucially on a property of interpolated trajectories, termed second-order continuity (SOC), which we show is tightly related to the ability of a planner to benefit from denser sampling. We analyze the impact of this property in simulations on a low-torque pendulum. Our results show that a simple RRT using a second-order continuous interpolation swiftly finds solution, while it is impossible for the same planner using standard Bezier curves (which are not SOC) to find any solution.Comment: 21 pages, 5 figure

Unfolding Hidden Barriers by Active Enhanced Sampling

Collective variable (CV) or order parameter based enhanced sampling algorithms have achieved great success due to their ability to efficiently explore the rough potential energy landscapes of complex systems. However, the degeneracy of microscopic configurations, originating from the orthogonal space perpendicular to the CVs, is likely to shadow "hidden barriers" and greatly reduce the efficiency of CV-based sampling. Here we demonstrate that systematic machine learning CV, through enhanced sampling, can iteratively lift such degeneracies on the fly. We introduce an active learning scheme that consists of a parametric CV learner based on deep neural network and a CV-based enhanced sampler. Our active enhanced sampling (AES) algorithm is capable of identifying the least informative regions based on a historical sample, forming a positive feedback loop between the CV learner and sampler. This approach is able to globally preserve kinetic characteristics by incrementally enhancing both sample completeness and CV quality.Comment: 5 pages, 3 figure

Total energy differences between SiC polytypes revisited

The total energy differences between various SiC polytypes (3C, 6H, 4H, 2H, 15R and 9R) were calculated using the full-potential linear muffin-tin orbital method using the Perdew-Wang-(91) generalized gradient approximation to the exchange-correlation functional in the density functional method. Numerical convergence versus k-point sampling and basis set completeness are demonstrated to be better than 1 meV/atom. The parameters of several generalized anisotropic next-nearest-neighbor Ising models are extracted and their significance and consequences for epitaxial growth are discussed.Comment: 8 pages, 3 figures, Latex, uses epsfig and revte

COMPLETENESS OF COMPUTER LABORATORY FACILITIES AND THE INFLUENCE OF LEARNING MOTIVATION FOR ACHIEVEMENT KKPI SUBJECT TENTH GRADE STUDENTS SMK NEGERI 5 YOGYAKARTA

The purpose of this research is to find out (1) completeness of computer laboratory facilities, (2) learning motivation, (3) academic achievement, (4) the influence of learning motivation with academic achievement for KKPI subject tenth grade students in SMK N 5 Yogyakarta. This research is a descriptive correlational Expost Facto research with quantitative approach. The population of this research are tenth grade students of KKPI subject with data collection techniques using Proporsional Random Sampling. Data collection methods for Completeness of Computer Laboratory facilities and learning motivation variable using a questionnaire with Likert scale model, while for the academic achievement variable using documentation score of the practice exams in KKPI subject. The validity of the research instrument was tested by three experts (expert judgment) calculated with the Pearson Product Moment Correlation formula. Reliability of the instrument was calculated using Alpha Cronbach formula. Data analysis techniques for the formulation of the problem 1, 2, and 3 using descriptive analysis, while the formulation of the problem 4 or hypothesis 1 using simple regression analysis. The results showed that the Completeness of Computer Laboratory Facilities for KKPI subjects tenth grade students in SMK N 5 Yogyakarta that qualified with Permendiknas No. 40 of 2008 are the teacher's desk, teacher's chair, whiteboard, LCD, printers, scanners, access points, indoor air , contact boxes, bins, size whiteboard, application software and textbooks. While the things that not not fulfilled are computer, stabilizier, student desks, student chairs, the number of LAN and clocks. Learning motivation of tenth grade students of SMK N 5 Yogyakarta in the medium category at 52.99%, lower category at 27.19%, higher category at 19.82%. Learning Achievement tenth grades students of SMK N 5 Yogyakarta in the medium category at 46.54%, lower by 36.87% category, higher category at 16.59%. There is a positive and significant association between the Achievement Motivation KKPI subjects of the tenth grade students are indicated by the price of the correlation coefficient (R) 0.958 and the coefficient of determination (R2) of 0.918. Keywords: Completeness of Computer Laboratory Facilities, Learning Motivation, Achievemen