Jorge Luis Borges and the Nothingness of the Self

In this paper I discuss how Borges uses his ideas on selfhood to explore the “central problem of literature” that Andre Maurois highlighted and how in the process projects to the reader his idea of reality. I argue also that the self that Borges tries to present in his work may nevertheless not be always congruent with the self he may have wanted to convey. This is because his quest is influenced by a number of factors, not least the fact that the self-creation process is affected by our interplay with the external world

Literature and the construction of reality

In this article I consider the idea that Glasersfeld’s “radical constructivism” offers an ideal framework for putting in place such a reality of the best fit for us. Along with this, I examine also the fundamental biological and epistemological limitations that we are faced with when trying to fathom objective reality and, secondly, the inescapable gap between language – which we use as a primary cognitive tool in our attempt to comprehend the world. The paper then show that literature – especially fiction – best meets the criteria for addressing these gaps and constructing such a model of reality in line with what radical constructivism proposes

Bacterial Resistance and the Optimal Use of Antibiotics

The increasing resistance of harmful biological organisms (bacteria, parasites, and pests) to selection pressure from the widespread use of control agents such as antibiotics, antimalarials, and pesticides is a serious problem in both medicine and agriculture. Modeling resistance —or, conversely, the effectiveness of these control agents as a biological resource—yields insights into how these agents should be optimally managed to maximize their economic benefit to society. This paper uses a model of evolution of bacterial resistance to antibiotics—in which resistance places an evolutionary disadvantage on the resistant organism—to develop a simple sequential algorithm of optimal antibiotic use. Although the solution to this problem follows the well-recognized rule of using resources in the order of increasing marginal cost, the unique ways in which these economic costs arise from differing biological traits distinguishes this problem from others in the natural resources arena. This paper also examines the option of periodically rotating between two or more antibiotics and characterizes the economic and biological criteria under which a cycling strategy is superior to simultaneous use of two or more antibiotics.antibiotic resistance, natural resource, optimization.

ACT Now or Later: The Economics of Malaria Resistance

In the past, malaria control efforts in sub-Saharan Africa have relied on a combination of vector control and effective treatment using chloroquine. With increasing resistance to chloroquine, attention has now turned to alternative treatment strategies to replace this failing drug. Although there are strong theoretical arguments in favor of switching to more expensive artemisinin-based combination treatments (ACTs), the validity of these arguments in the face of financial constraints has not been previously analyzed. In this paper, we use a bioeconomic model of malaria transmission and evolution of drug resistance to examine questions of optimal treatment strategy and coverage when drug resistance places an additional constraint on choices available to the policymaker. Our main finding is that introducing ACTs sooner is more economically efficient if the planner had a relatively longer time horizon. However, for shorter planning horizons, delaying the introduction of ACTs is preferable.Malaria; mathematical models; drug resistance; bioeconomics

Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussians

Convolutional neural nets (CNNs) have demonstrated remarkable performance in recent history. Such approaches tend to work in a unidirectional bottom-up feed-forward fashion. However, practical experience and biological evidence tells us that feedback plays a crucial role, particularly for detailed spatial understanding tasks. This work explores bidirectional architectures that also reason with top-down feedback: neural units are influenced by both lower and higher-level units. We do so by treating units as rectified latent variables in a quadratic energy function, which can be seen as a hierarchical Rectified Gaussian model (RGs). We show that RGs can be optimized with a quadratic program (QP), that can in turn be optimized with a recurrent neural network (with rectified linear units). This allows RGs to be trained with GPU-optimized gradient descent. From a theoretical perspective, RGs help establish a connection between CNNs and hierarchical probabilistic models. From a practical perspective, RGs are well suited for detailed spatial tasks that can benefit from top-down reasoning. We illustrate them on the challenging task of keypoint localization under occlusions, where local bottom-up evidence may be misleading. We demonstrate state-of-the-art results on challenging benchmarks.Comment: To appear in CVPR 201

Asymptotic approximations for stationary distributions of many-server queues with abandonment

A many-server queueing system is considered in which customers arrive according to a renewal process and have service and patience times that are drawn from two independent sequences of independent, identically distributed random variables. Customers enter service in the order of arrival and are assumed to abandon the queue if the waiting time in queue exceeds the patience time. The state of the system with $N$ servers is represented by a four-component process that consists of the forward recurrence time of the arrival process, a pair of measure-valued processes, one that keeps track of the waiting times of customers in queue and the other that keeps track of the amounts of time customers present in the system have been in service and a real-valued process that represents the total number of customers in the system. Under general assumptions, it is shown that the state process is a Feller process, admits a stationary distribution and is ergodic. It is also shown that the associated sequence of scaled stationary distributions is tight, and that any subsequence converges to an invariant state for the fluid limit. In particular, this implies that when the associated fluid limit has a unique invariant state, then the sequence of stationary distributions converges, as $N\rightarrow \infty$, to the invariant state. In addition, a simple example is given to illustrate that, both in the presence and absence of abandonments, the $N\rightarrow \infty$ and $t\rightarrow \infty$ limits cannot always be interchanged.Comment: Published in at http://dx.doi.org/10.1214/10-AAP738 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Fluid limits of many-server queues with reneging

This work considers a many-server queueing system in which impatient customers with i.i.d., generally distributed service times and i.i.d., generally distributed patience times enter service in the order of arrival and abandon the queue if the time before possible entry into service exceeds the patience time. The dynamics of the system is represented in terms of a pair of measure-valued processes, one that keeps track of the waiting times of the customers in queue and the other that keeps track of the amounts of time each customer being served has been in service. Under mild assumptions, essentially only requiring that the service and reneging distributions have densities, as both the arrival rate and the number of servers go to infinity, a law of large numbers (or fluid) limit is established for this pair of processes. The limit is shown to be the unique solution of a coupled pair of deterministic integral equations that admits an explicit representation. In addition, a fluid limit for the virtual waiting time process is also established. This paper extends previous work by Kaspi and Ramanan, which analyzed the model in the absence of reneging. A strong motivation for understanding performance in the presence of reneging arises from models of call centers.Comment: Published in at http://dx.doi.org/10.1214/10-AAP683 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org