Fabrication and Room-Temperature Single-Charging Behavior of Self-Aligned Single-Dot Memory Devices

Self-aligned single-dot memory devices and arrays were fabricated based on arsenic-assisted etching and oxidation effects. The resulting device has a floating gate of about 5-10 nm, presenting single-electron memory operation at room temperature. In order to realize the final single-electron memory circuit, this paper investigates process repeatability, device uniformity in single-dot memory arrays, device scalability, and process transferability to an industrial application     

Protein folding transition states: elicitation of Hammond effects by 2,2,2-trifluoroethanol

Adaptation of the techniques of classical physical-organic chemistry to the study of protein folding has led to our current detailed understanding of the transition states. Here, we have applied a series of structure--activity relationships to analyse the effects on protein folding transition states of 2,2,2-trifluoroethanol (TFE), a reagent that is usually assumed to act by stabilising secondary structure. The folding and unfolding of the highly alpha-helical tetramerisation domain of p53 provides a useful paradigm for analysing its effects on kinetics: The first step of its folding consists of an association reaction with little, if any, formation of secondary structure in the transition state; and the final step of the folding reaction involves just the formation of bonds at subunit interfaces, with the alpha-helical structure being completely formed. We have systematically measured the effects of TFE on two sets of structure--activity relationships. The first is for Phi values, which measure the degree of non-covalent bond formation at nearly every position in the transition state. The second is for relative effects of the denaturant, guanidinium chloride, on kinetics and equilibria, which measure the gross position of the transition state on the reaction co-ordinate. We find that TFE modulated the kinetics by a variety of effects other than that on secondary structure. In particular, there were Hammond effects, movement of the position of the transition state along the reaction co-ordinate, which either significantly speeded up or slowed down protein unfolding, depending on the particular mutant examined. The gross effects of TFE on protein folding kinetics are thus not a reliable guide to the structures of transition states.     

On the hardness of solving edge matching puzzles as SAT or CSP problems

Edge matching puzzles have been amongst us for a long time now and traditionally they have been considered, both, a children’s game and an interesting mathematical divertimento. Their main characteristics have already been studied, and their worst-case complexity has been properly classified as a NP-complete problem. It is in recent times, specially after being used as the problem behind a money-prized contest, with a prize of 2US$ million for the first solver, that edge matching puzzles have attracted mainstream attention from wider audiences, including, of course, computer science people working on solving hard problems. We consider these competitions as an interesting opportunity to showcase SAT/CSP solving techniques when confronted to a real world problem to a broad audience, a part of the intrinsic, i.e. monetary, interest of such a contest. This article studies the NP-complete problem known as edge matching puzzle using SAT and CSP approaches for solving it. We will focus on providing, first and foremost, a theoretical framework, including a generalized definition of the problem. We will design and show algorithms for easy and fast problem instances generation, generators with easily tunable hardness. Afterwards we will provide with SAT and CSP models for the problems and we will study problem complexity, both typical case and worst-case complexity. We will also provide some specially crafted heuristics that result in a boost in solving time and study which is the effect of such heuristics.     

Solving weighted CSPs with meta-constraints by reformulation into satisfiability modulo theories

We introduce WSimply, a new framework for modelling and solving Weighted Constraint Satisfaction Problems (WCSP) using Satisfiability Modulo Theories (SMT) technology. In contrast to other well-known approaches designed for extensional representation of goods or no-goods, and with few declarative facilities, our approach aims to follow an intensional and declarative syntax style. In addition, our language has built-in support for some meta-constraints, such as priority and homogeneity, which allows the user to easily specify rich requirements on the desired solutions, such as preferences and fairness. We propose two alternative strategies for solving these WCSP instances using SMT. The first is the reformulation into Weighted SMT (WSMT) and the application of satisfiability test based algorithms from recent contributions in the Weighted Maximum Satisfiability field. The second one is the reformulation into an operation research-like style which involves an optimisation variable or objective function and the application of optimisation SMT solvers. We present experimental results of two well-known problems: the Nurse Rostering Problem (NRP) and a variant of the Balanced Academic Curriculum Problem (BACP), and provide some insights into the impact of the addition of meta-constraints on the quality of the solutions and the solving time.     

An ant colony optimization algorithm for DNA sequencing by hybridization

The reconstruction of DNA sequences from DNA fragments is one of the most challenging problems in computational biology. In recent years the specific problem of DNA sequencing by hybridization has attracted quite a lot of interest in the optimization community. Several metaheuristics such as tabu search and evolutionary algorithms have been applied to this problem. However, the performance of existing metaheuristics is often inferior to the performance of recently proposed constructive heuristics. On the basis of these new heuristics we develop an ant colony optimization algorithm for DNA sequencing by hybridization. An important feature of this algorithm is the implementation in a so-called multi-level framework. The computational results show that our algorithm is currently a state-of-the-art method for the tackled problem.     

Real-time Light Animation

Light source animation is a particularly hard field of real‐time global illumination algorithms since moving light sources result in drastic illumination changes and make coherence techniques less effective. However, the animation of small (point‐like) light sources represents a special but practically very important case, for which the reuse of the results of other frames is possible. This paper presents a fast light source animation algorithm based on the virtual light sources illumination method. The speed up is close to the length of the animation, and is due to reusing paths in all frames and not only in the frame where they were obtained. The possible applications of this algorithm are the lighting design and systems to convey shape and features with relighting.     

STATISTICAL LINGUISTIC LAWS IN ECOLOGICAL MODELS

This paper gives the theoretical setup so that an ecological model, as a particular mathematical model, can be considered a text written in a formal language (mathematics), and therefore, statistical linguistic laws can be applied to obtain information parameters in different semantic levels of the same model. The statistical laws will be useful to: a) compare semantic levels, submodels, and different models mutually; b) prove that information temperature parameter is an indirect measure of meaning: the significance or semantic component of information, opposed to significant, or comprehension, on the part of the observer (modeller) of the model text. We will apply these ideas in two practical examples.     

Trading genes along the silk road: mtDNA sequences and the origin of central Asian populations

Central Asia is a vast region at the crossroads of different habitats, cultures, and trade routes. Little is known about the genetics and the history of the population of this region. We present the analysis of mtDNA control-region sequences in samples of the Kazakh, the Uighurs, the lowland Kirghiz, and the highland Kirghiz, which we have used to address both the population history of the region and the possible selective pressures that high altitude has on mtDNA genes. Central Asian mtDNA sequences present features intermediate between European and eastern Asian sequences, in several parameters-such as the frequencies of certain nucleotides, the levels of nucleotide diversity, mean pairwise differences, and genetic distances. Several hypotheses could explain the intermediate position of central Asia between Europe and eastern Asia, but the most plausible would involve extensive levels of admixture between Europeans and eastern Asians in central Asia, possibly enhanced during the Silk Road trade and clearly after the eastern and western Eurasian human groups had diverged. Lowland and highland Kirghiz mtDNA sequences are very similar, and the analysis of molecular variance has revealed that the fraction of mitochondrial genetic variance due to altitude is not significantly different from zero. Thus, it seems unlikely that altitude has exerted a major selective pressure on mitochondrial genes in central Asian populations.