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Project-based Temporary Organizing and Routine Dynamics
Projects are forms of organizing that have become increasingly common in the past decades. The ad-hoc and temporary nature of projects seemingly poses significant challenges to the patterning of activities into organizational routines. Yet, considerable research in routine dynamics has been carried out in project contexts. In this chapter, we show that projects and routines share some common characteristics and that acknowledging the project nature of routines as well as the organizational routine nature of projects offers significant opportunities for the advancement of routine dynamics research
Parallel Search with no Coordination
We consider a parallel version of a classical Bayesian search problem.
agents are looking for a treasure that is placed in one of the boxes indexed by
according to a known distribution . The aim is to minimize
the expected time until the first agent finds it. Searchers run in parallel
where at each time step each searcher can "peek" into a box. A basic family of
algorithms which are inherently robust is \emph{non-coordinating} algorithms.
Such algorithms act independently at each searcher, differing only by their
probabilistic choices. We are interested in the price incurred by employing
such algorithms when compared with the case of full coordination. We first show
that there exists a non-coordination algorithm, that knowing only the relative
likelihood of boxes according to , has expected running time of at most
, where is the expected running time of the best
fully coordinated algorithm. This result is obtained by applying a refined
version of the main algorithm suggested by Fraigniaud, Korman and Rodeh in
STOC'16, which was designed for the context of linear parallel search.We then
describe an optimal non-coordinating algorithm for the case where the
distribution is known. The running time of this algorithm is difficult to
analyse in general, but we calculate it for several examples. In the case where
is uniform over a finite set of boxes, then the algorithm just checks boxes
uniformly at random among all non-checked boxes and is essentially times
worse than the coordinating algorithm.We also show simple algorithms for Pareto
distributions over boxes. That is, in the case where for
, we suggest the following algorithm: at step choose uniformly
from the boxes unchecked in ,
where . It turns out this algorithm is asymptotically
optimal, and runs about times worse than the case of full coordination
Linear Time Distributed Swap Edge Algorithms
In this paper, we consider the all best swap edges problem in
a distributed environment. We are given a 2-edge connected positively weighted network X, where all communication is routed through a rooted spanning tree T of X. If one tree edge e = {x, y} fails, the communication network will be disconnected. However, since X is 2-edge connected,
communication can be restored by replacing e by non-tree edge e′, called a swap edge of e, whose ends lie in different components of T − e. Of all possible swap edges of e, we would like to choose the best, as defined by the application. The all best swap edges problem is to identify the
best swap edge for every tree edge, so that in case of any edge failure, the best swap edge can be activated quickly. There are solutions to this problem for a number of cases in the literature. A major concern for all these solutions is to minimize the number of messages. However, especially in fault-transient environments, time is a crucial factor. In this
paper we present a novel technique that addresses this problem from a time perspective; in fact, we present a distributed solution that works in linear time with respect to the height h of T for a number of differentcriteria, while retaining the optimal number of messages. To the best of
our knowledge, all previous solutions solve the problem in O(h^2) time in the cases we consider
Asynchronous Silent Programmable Matter Achieves Leader Election and Compaction
We study models and algorithms for Programmable Matter (PM), that is matter with the ability to change its physical properties (e.g., shape or optical properties) in a programmable fashion. PM can be implemented by assembling a system of weak self-organizing computational elements, called particles, that can be programmed via distributed algorithms to collectively achieve some global task. Recent advances in the production of nanotechnologies have rendered such systems increasingly possible in practice, thus triggering research interests from many areas of computer science. The most established models for PM assume that particles: are modeled as finite state automata; are all identical, executing the same algorithm based on local observation of the surroundings; live and operate in the cells of a hexagonal grid; can move from one cell to another by repeatedly alternating between a contracted state (a particle occupies one cell) and an expanded state (a particle occupies two neighboring cells). Given these elementary features, it is rather hard to design distributed algorithms even for basic tasks and, in fact, all existing solutions to solve fundamental problems via PM have resorted to endowing PM systems with various capabilities to overcome such hardness, thus assuming quite unrealistic features. In this paper, we move toward more realistic computational models for PM. Specifically, we first introduce, a new modeling approach that relaxes several assumptions used in previous ones. Second, we present a distributed algorithm to solve, in the model, a foundational primitive for PM, namely Leader Election. This algorithm works in O(n) rounds for all initial configurations of n particles that are both connected (i.e. particles induce a connected graph) and compact (i.e. without holes, that is no empty cells surrounded by particles occur). As usual in asynchronous contexts, a round is intended as the time within which all particles have been activated at least once. Third, we show that, if the initial configuration admits holes, it is impossible to achieve leader election while preserving connectivity. Finally, by slightly empowering the robots, we design an algorithm to handle initial configurations admitting holes that in O(n2) rounds solves the leader election problem while obtaining also compaction
Neutralization of IFN-γ reverts clinical and laboratory features in a mouse model of macrophage activation syndrome.
BACKGROUND: The pathogenesis of macrophage activation syndrome (MAS) is not clearly understood: a large body of evidence supports the involvement of mechanisms similar to those implicated in the setting of primary hemophagocytic lymphohistiocytosis.
OBJECTIVE: We sought to investigate the pathogenic role of IFN-γ and the therapeutic efficacy of IFN-γ neutralization in an animal model of MAS.
METHODS: We used an MAS model established in mice transgenic for human IL-6 (IL-6TG mice) challenged with LPS (MAS mice). Levels of IFN-γ and IFN-γ-inducible chemokines were evaluated by using real-time PCR in the liver and spleen and by means of ELISA in plasma. IFN-γ neutralization was achieved by using the anti-IFN-γ antibody XMG1.2 in vivo.
RESULTS: Mice with MAS showed a significant upregulation of the IFN-γ pathway, as demonstrated by increased mRNA levels of Ifng and higher levels of phospho-signal transducer and activator of transcription 1 in the liver and spleen and increased expression of the IFN-γ-inducible chemokines Cxcl9 and Cxcl10 in the liver and spleen, as well as in plasma. A marked increase in Il12a and Il12b expression was also found in livers and spleens of mice with MAS. In addition, mice with MAS had a significant increase in numbers of liver CD68+ macrophages. Mice with MAS treated with an anti-IFN-γ antibody showed a significant improvement in survival and body weight recovery associated with a significant amelioration of ferritin, fibrinogen, and alanine aminotransferase levels. In mice with MAS, treatment with the anti-IFN-γ antibody significantly decreased circulating levels of CXCL9, CXCL10, and downstream proinflammatory cytokines. The decrease in CXCL9 and CXCL10 levels paralleled the decrease in serum levels of proinflammatory cytokines and ferritin.
CONCLUSION: These results provide evidence for a pathogenic role of IFN-γ in the setting of MAS
A Rupestrian Algorithm
Deciphering recently discovered cave paintings by the Astracinca, an egalitarian leaderless society flourishing in the 3rd millennium BCE, we present and analyze their shamanic ritual for forming new colonies. This ritual can actually be used by systems of anonymous mobile finite-state computational entities located and operating in a grid to solve the line recovery problem, a task that has both self-assembly and flocking requirements. The protocol is totally decentralized, fully concurrent, provably correct, and time optimal
Observation of the Decay B^-→D_s^((*)+)K^-ℓ^-ν̅ _ℓ
We report the observation of the decay B^- → D_s^((*)+)K^-ℓ^-ν̅ _ℓ based on 342  fb^(-1) of data collected at the Υ(4S) resonance with the BABAR detector at the PEP-II e^+e^- storage rings at SLAC. A simultaneous fit to three D_s^+ decay chains is performed to extract the signal yield from measurements of the squared missing mass in the B meson decay. We observe the decay B^- → D_s^((*)+)K^-ℓ^-ν̅ _ℓ with a significance greater than 5 standard deviations (including systematic uncertainties) and measure its branching fraction to be B(B^- → D_s^((*)+)K^-ℓ^-ν̅ _ℓ)=[6.13_(-1.03)^(+1.04)(stat)±0.43(syst)±0.51(B(D_s))]×10^(-4), where the last error reflects the limited knowledge of the D_s branching fractions
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