Nanoscale deformation of GaAs affected by silicon doping

Effect of silicon doping on the elastic–plastic transition of GaAs crystal is demonstrated by results of nanoindentations and ab initio simulations. The performed experiments show that an increase of silicon concentration causes a decrease of the contact pressure at the onset of permanent nanodeformation of GaAs crystal. Ab initio calculations demonstrate that presence of Si atoms in the crystal lattice suppresses the shear modulus as well as the pressure of equilibrium between zinc-blende and rock-salt phases of GaAs. Furthermore, it is argued that the effect of dislocations pinning to Si dopants is essential for clarification of GaAs yielding

La metacognición y el mejoramiento de la enseñanza de química universitaria

En este trabajo, que es parte de una investigación más extensa, sobre mejoramiento de la enseñanza de química universitaria, se presentan algunos resultados obtenidos luego de aplicar una nueva propuesta de enseñanza, destinada a la comprensión y resolución de problemas sobre el tema «Soluciones». Con el objeto de facilitar el aprendizaje significativo, la propuesta de trabajo incluye el uso de las denominadas herramientas metacognitivas que permitan aplicar metodologías conducentes al logro de dichos aprendizajes por parte de los estudiantes. Luego de aplicar las mencionadas herramientas, se procedió a realizar la evaluación de los estudiantes participantes para obtener datos sobre los logros alcanzados y sus aprendizajes. El análisis de los resultados muestra que el uso del nuevo enfoque instruccional ayuda a los estudiantes en sus procesos de aprendizaje, en la medida que se vayan haciendo conscientes de los mecanismos que se utilizan para obtener aprendizaje significativo.This work, which is part of a more extensive research project on the improvement of Chemistry teaching at university level, presents the results obtained by applying an innovative teaching methodology. This methodology was designed with the objective of helping students to better understand and solve problems regarding the topic "Solutions". In order to facilitate learning, the proposed methodology includes the use of metacognitive tools (concept maps, Gowin's Vee and clinical interviews), which allows the students to apply significant learning methodologies. After applying these tools, we evaluated the students in order to measure their achievements and their learning. The analysis of the results shows that the use of this new instructional approach helps the students in their learning process because they become aware of the mechanism they use to achieve significant learning

An Improved Bound for First-Fit on Posets Without Two Long Incomparable Chains

It is known that the First-Fit algorithm for partitioning a poset P into chains uses relatively few chains when P does not have two incomparable chains each of size k. In particular, if P has width w then Bosek, Krawczyk, and Szczypka (SIAM J. Discrete Math., 23(4):1992--1999, 2010) proved an upper bound of ckw^{2} on the number of chains used by First-Fit for some constant c, while Joret and Milans (Order, 28(3):455--464, 2011) gave one of ck^{2}w. In this paper we prove an upper bound of the form ckw. This is best possible up to the value of c.Comment: v3: referees' comments incorporate

Incremental Medians via Online Bidding

In the k-median problem we are given sets of facilities and customers, and distances between them. For a given set F of facilities, the cost of serving a customer u is the minimum distance between u and a facility in F. The goal is to find a set F of k facilities that minimizes the sum, over all customers, of their service costs. Following Mettu and Plaxton, we study the incremental medians problem, where k is not known in advance, and the algorithm produces a nested sequence of facility sets where the kth set has size k. The algorithm is c-cost-competitive if the cost of each set is at most c times the cost of the optimum set of size k. We give improved incremental algorithms for the metric version: an 8-cost-competitive deterministic algorithm, a 2e ~ 5.44-cost-competitive randomized algorithm, a (24+epsilon)-cost-competitive, poly-time deterministic algorithm, and a (6e+epsilon ~ .31)-cost-competitive, poly-time randomized algorithm. The algorithm is s-size-competitive if the cost of the kth set is at most the minimum cost of any set of size k, and has size at most s k. The optimal size-competitive ratios for this problem are 4 (deterministic) and e (randomized). We present the first poly-time O(log m)-size-approximation algorithm for the offline problem and first poly-time O(log m)-size-competitive algorithm for the incremental problem. Our proofs reduce incremental medians to the following online bidding problem: faced with an unknown threshold T, an algorithm submits "bids" until it submits a bid that is at least the threshold. It pays the sum of all its bids. We prove that folklore algorithms for online bidding are optimally competitive.Comment: conference version appeared in LATIN 2006 as "Oblivious Medians via Online Bidding

Parameterizing by the Number of Numbers

The usefulness of parameterized algorithmics has often depended on what Niedermeier has called, "the art of problem parameterization". In this paper we introduce and explore a novel but general form of parameterization: the number of numbers. Several classic numerical problems, such as Subset Sum, Partition, 3-Partition, Numerical 3-Dimensional Matching, and Numerical Matching with Target Sums, have multisets of integers as input. We initiate the study of parameterizing these problems by the number of distinct integers in the input. We rely on an FPT result for ILPF to show that all the above-mentioned problems are fixed-parameter tractable when parameterized in this way. In various applied settings, problem inputs often consist in part of multisets of integers or multisets of weighted objects (such as edges in a graph, or jobs to be scheduled). Such number-of-numbers parameterized problems often reduce to subproblems about transition systems of various kinds, parameterized by the size of the system description. We consider several core problems of this kind relevant to number-of-numbers parameterization. Our main hardness result considers the problem: given a non-deterministic Mealy machine M (a finite state automaton outputting a letter on each transition), an input word x, and a census requirement c for the output word specifying how many times each letter of the output alphabet should be written, decide whether there exists a computation of M reading x that outputs a word y that meets the requirement c. We show that this problem is hard for W[1]. If the question is whether there exists an input word x such that a computation of M on x outputs a word that meets c, the problem becomes fixed-parameter tractable

Information Gathering in Ad-Hoc Radio Networks with Tree Topology

We study the problem of information gathering in ad-hoc radio networks without collision detection, focussing on the case when the network forms a tree, with edges directed towards the root. Initially, each node has a piece of information that we refer to as a rumor. Our goal is to design protocols that deliver all rumors to the root of the tree as quickly as possible. The protocol must complete this task within its allotted time even though the actual tree topology is unknown when the computation starts. In the deterministic case, assuming that the nodes are labeled with small integers, we give an O(n)-time protocol that uses unbounded messages, and an O(n log n)-time protocol using bounded messages, where any message can include only one rumor. We also consider fire-and-forward protocols, in which a node can only transmit its own rumor or the rumor received in the previous step. We give a deterministic fire-and- forward protocol with running time O(n^1.5), and we show that it is asymptotically optimal. We then study randomized algorithms where the nodes are not labelled. In this model, we give an O(n log n)-time protocol and we prove that this bound is asymptotically optimal

Time-Energy Tradeoffs for Evacuation by Two Robots in the Wireless Model

Two robots stand at the origin of the infinite line and are tasked with searching collaboratively for an exit at an unknown location on the line. They can travel at maximum speed $b$ and can change speed or direction at any time. The two robots can communicate with each other at any distance and at any time. The task is completed when the last robot arrives at the exit and evacuates. We study time-energy tradeoffs for the above evacuation problem. The evacuation time is the time it takes the last robot to reach the exit. The energy it takes for a robot to travel a distance $x$ at speed $s$ is measured as $xs^2$. The total and makespan evacuation energies are respectively the sum and maximum of the energy consumption of the two robots while executing the evacuation algorithm. Assuming that the maximum speed is $b$, and the evacuation time is at most $cd$, where $d$ is the distance of the exit from the origin, we study the problem of minimizing the total energy consumption of the robots. We prove that the problem is solvable only for $bc \geq 3$. For the case $bc=3$, we give an optimal algorithm, and give upper bounds on the energy for the case $bc>3$. We also consider the problem of minimizing the evacuation time when the available energy is bounded by $\Delta$. Surprisingly, when $\Delta$ is a constant, independent of the distance $d$ of the exit from the origin, we prove that evacuation is possible in time $O(d^{3/2}\log d)$, and this is optimal up to a logarithmic factor. When $\Delta$ is linear in $d$, we give upper bounds on the evacuation time.Comment: This is the full version of the paper with the same title which will appear in the proceedings of the 26th International Colloquium on Structural Information and Communication Complexity (SIROCCO'19) L'Aquila, Italy during July 1-4, 201

Elastic-plastic transition in MBE-grown GaSb semiconducting crystal examined by noindentation

The present paper concerns the elastic-plastic nanodeformation of Te-doped GaSb crystals grown by molecular beam epitaxy on the n-type of GaSb substrate. The conventional analysis of nanoindentation data obtained with sharp triangular (Berkovich) and spherical tip revealed the elastic modulus (E = 83:07 1:78 GPa), hardness (H = 5:19 0:25 GPa) and “true hardness” (HT = 5:73 0:04 GPa). The registered pop-in event which indicates the elastic–plastic transition in GaSb crystal points towards the corresponding yield strength ( Y = 3:8 0:1 GPa). The origin of incipient plasticity in GaSb crystal is discussed in terms of elastic-plastic deformation energy concept