5,954 research outputs found
Diversity and Adaptation in Large Population Games
We consider a version of large population games whose players compete for
resources using strategies with adaptable preferences. The system efficiency is
measured by the variance of the decisions. In the regime where the system can
be plagued by the maladaptive behavior of the players, we find that diversity
among the players improves the system efficiency, though it slows the
convergence to the steady state. Diversity causes a mild spread of resources at
the transient state, but reduces the uneven distribution of resources in the
steady state.Comment: 8 pages, 3 figure
Models of Financial Markets with Extensive Participation Incentives
We consider models of financial markets in which all parties involved find
incentives to participate. Strategies are evaluated directly by their virtual
wealths. By tuning the price sensitivity and market impact, a phase diagram
with several attractor behaviors resembling those of real markets emerge,
reflecting the roles played by the arbitrageurs and trendsetters, and including
a phase with irregular price trends and positive sums. The positive-sumness of
the players' wealths provides participation incentives for them. Evolution and
the bid-ask spread provide mechanisms for the gain in wealth of both the
players and market-makers. New players survive in the market if the
evolutionary rate is sufficiently slow. We test the applicability of the model
on real Hang Seng Index data over 20 years. Comparisons with other models show
that our model has a superior average performance when applied to real
financial data.Comment: 17 pages, 16 figure
Inference and Optimization of Real Edges on Sparse Graphs - A Statistical Physics Perspective
Inference and optimization of real-value edge variables in sparse graphs are
studied using the Bethe approximation and replica method of statistical
physics. Equilibrium states of general energy functions involving a large set
of real edge-variables that interact at the network nodes are obtained in
various cases. When applied to the representative problem of network resource
allocation, efficient distributed algorithms are also devised. Scaling
properties with respect to the network connectivity and the resource
availability are found, and links to probabilistic Bayesian approximation
methods are established. Different cost measures are considered and algorithmic
solutions in the various cases are devised and examined numerically. Simulation
results are in full agreement with the theory.Comment: 21 pages, 10 figures, major changes: Sections IV to VII updated,
Figs. 1 to 3 replace
Hyperglycemia and Insulin Management in Critically Ill Patients
Hyperglycemia is a leading cause of increased morbidity and mortality in critically ill diabetic and nondiabetic patients in the ICU. Stricter control should be implemented in this setting in order to reduce mortality as well as other complications caused by hyperglycemia. Because hypoglycemia is associated with an increased risk of adverse effects, the optimal intensity of glucose control has been extensively investigated. Hyperglycemia is better controlled through continuous glucose infusions than with intermittent injections or IV infusions because it is easier to titrate the concentration of insulin to achieve a target glucose range. Pharmacists in acute-care and ambulatory-care settings are able to adjust insulin therapy and educate patients about hypoglycemia or hyperglycemia in order to optimize patient outcomes
PalProtect: A Collaborative Security Approach to Comment Spam
Collaborative security is a promising solution to many types of security problems. Organizations and individuals often have a limited amount of resources to detect and respond to the threat of automated attacks. Enabling them to take advantage of the resources of their peers by sharing information related to such threats is a major step towards automating defense systems. In particular, comment spam posted on blogs as a way for attackers to do Search Engine Optimization (SEO) is a major annoyance. Many measures have been proposed to thwart such spam, but all such measures are currently enacted and operate within one administrative domain. We propose and implement a system for cross-domain information sharing to improve the quality and speed of defense against such spam
Dynamical and Stationary Properties of On-line Learning from Finite Training Sets
The dynamical and stationary properties of on-line learning from finite
training sets are analysed using the cavity method. For large input dimensions,
we derive equations for the macroscopic parameters, namely, the student-teacher
correlation, the student-student autocorrelation and the learning force
uctuation. This enables us to provide analytical solutions to Adaline learning
as a benchmark. Theoretical predictions of training errors in transient and
stationary states are obtained by a Monte Carlo sampling procedure.
Generalization and training errors are found to agree with simulations. The
physical origin of the critical learning rate is presented. Comparison with
batch learning is discussed throughout the paper.Comment: 30 pages, 4 figure
A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks
Understanding how the dynamics of a neural network is shaped by the network
structure, and consequently how the network structure facilitates the functions
implemented by the neural system, is at the core of using mathematical models
to elucidate brain functions. This study investigates the tracking dynamics of
continuous attractor neural networks (CANNs). Due to the translational
invariance of neuronal recurrent interactions, CANNs can hold a continuous
family of stationary states. They form a continuous manifold in which the
neural system is neutrally stable. We systematically explore how this property
facilitates the tracking performance of a CANN, which is believed to have clear
correspondence with brain functions. By using the wave functions of the quantum
harmonic oscillator as the basis, we demonstrate how the dynamics of a CANN is
decomposed into different motion modes, corresponding to distortions in the
amplitude, position, width or skewness of the network state. We then develop a
perturbative approach that utilizes the dominating movement of the network's
stationary states in the state space. This method allows us to approximate the
network dynamics up to an arbitrary accuracy depending on the order of
perturbation used. We quantify the distortions of a Gaussian bump during
tracking, and study their effects on the tracking performance. Results are
obtained on the maximum speed for a moving stimulus to be trackable and the
reaction time for the network to catch up with an abrupt change in the
stimulus.Comment: 43 pages, 10 figure
Aryl Phosphoramidates of 5-Phospho Erythronohydroxamic Acid, A New Class of Potent Trypanocidal Compounds
RNAi and enzymatic studies have shown the importance of 6-phosphogluconate dehydrogenase (6-PGDH) in Trypanosoma brucei for the parasite survival and make it an attractive drug target for the development of new treatments against human African trypanosomiasis. 2,3-O-Isopropylidene-4-erythrono hydroxamate is a potent inhibitor of parasite Trypanosoma brucei 6-phosphogluconate dehydrogenase (6-PGDH), the third enzyme of the pentose phosphate pathway. However, this compound does not have trypanocidal activity due to its poor membrane permeability. Consequently, we have previously reported a prodrug approach to improve the antiparasitic activity of this inhibitor by converting the phosphate group into a less charged phosphate prodrug. The activity of prodrugs appeared to be dependent on their stability in phosphate buffer. Here we have successfully further extended the development of the aryl phosphoramidate prodrugs of 2,3-O-isopropylidene-4-erythrono hydroxamate by synthesizing a small library of phosphoramidates and evaluating their biological activity and stability in a variety of assays. Some of the compounds showed high trypanocidal activity and good correlation of activity with their stability in fresh mouse blood
Strategic sensemaking by social entrepreneurs:Creating strategies for social innovation
Purpose: This study explores how a small minority of social entrepreneurs break free from third sector constraints to conceive, create and grow non-profit organisations that generate social value at scale in new and innovative ways. Design/methodology/approach: Six narrative case histories of innovative social enterprises were developed based on documents and semi-structured interviews with founders and long serving executives. Data were coded “chrono-processually”, which involves locating thoughts, events and actions in distinct time periods (temporal bracketing) and identifying the processes at work in establishing new social ventures. Findings: This study presents two core findings. First, the paper demonstrates how successful social entrepreneurs draw on their lived experiences, private and professional, in driving the development and implementation of social innovations, which are realised through application of their capabilities as analysts, strategists and resources mobilisers. These capabilities are bolstered by personal legitimacy and by their abilities as storytellers and rhetoricians. Second, the study unravels the complex processes of social entrepreneurship by revealing how sensemaking, theorising, strategizing and sensegiving underpin the core processes of problem specification, the formulation of theories of change, development of new business models and the implementation of social innovations. Originality/value: The study demonstrates how social entrepreneurs use sensemaking and sensegiving strategies to understand and address complex social problems, revealing how successful social entrepreneurs devise and disseminate social innovations that substantially add value to society and bring about beneficial social change. A novel process-outcome model of social innovation is presented illustrating the interconnections between entrepreneurial cognition and strategic action.</p
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