Economic Exit, Interdependence, and Conflict

This article examines the question of whether economic interdependence constrains or motivates interstate conflict. The theoretical model predicts when and how interdependence influences conflict, using exit costs to separate economic interdependence from less binding economic interaction. Analysis of the model suggests that when exit costs exceed an endurance threshold for at least one state, the threat of exit becomes a viable but limited bargaining tool. Exceeding this threshold increases low-level conflict as states use economic and diplomatic tools to resolve demands, but it decreases high-level conflict because states take advantage of more efficient means of dispute resolution. If the stakes are too high, however, exit costs fail to check conflict, and the economic relationship becomes an ineffective bargaining arena. Empirical analysis provides support for the hypotheses derived from the model

State-Sponsored Crime: The Futility of the Economic Espionage Act

The United States is facing an international challenge: economic espionage, the theft of our intellectual assets and proprietary information. The events of September 11, 2001, pushed the seriousness of this activity to the far recesses of the public’s consciousness. While this threat to our national security lacks the visceral impact of September 11, the long-term national security implications (a decline in economic competitiveness) stemming from the systemic theft of intellectual property has consequences no less serious than a real-world terrorist attack. Espionage targeting intellectual assets and proprietary information is driven by the international competition characterizing a global economy. Americans have long ignored the preeminent rule of international economic competition: “Expediency outgrosses morality.” The success or failure of our ability to compete will determine U.S. economic well-being and, ultimately, our national security. The global economy that emerged after the Cold War is replete with strong, independent, predatory competitors, a state of affairs that can be attributed largely to U.S. economic globalism and the showcasing of American technology. The desire for American technology is the primary motivation for the continuing economic espionage activities undertaken by a multitude of foreign countries. It has been obvious for over a decade that economic espionage is a serious problem. Appreciating the seriousness of this threat, Congress passed the Economic Espionage Act of 1996; the President signed the Act into law on October 11, 1996. The Economic Espionage Act (EEA) took a traditional approach to the activity at issue by treating the misappropriation of proprietary economic information as theft and criminalizing it. Congress believed that by prosecuting and sanctioning those who unlawfully appropriate proprietary information, we can deter others from engaging in such conduct. Prosecution and punishment can contribute to preventing economic espionage, but they, alone, cannot accomplish this, for reasons we explain below. Our purpose in writing this article is to point out the danger of relying on traditional solutions in a nontraditional era; reacting to completed acts of economic espionage by sanctioning the perpetrator(s) is an effective strategy only if they can be identified, located, and apprehended. Part II explains what economic espionage is and why it is a serious problem. Part III reviews the provisions and enforcement of the Economic Espionage Act and explains why it is not a viable approach to economic espionage in the twenty-first century. Part IV considers how we can more effectively address economic espionage

Pole Dancing: 3D Morphs for Tree Drawings

We study the question whether a crossing-free 3D morph between two straight-line drawings of an $n$-vertex tree can be constructed consisting of a small number of linear morphing steps. We look both at the case in which the two given drawings are two-dimensional and at the one in which they are three-dimensional. In the former setting we prove that a crossing-free 3D morph always exists with $O(\log n)$ steps, while for the latter $\Theta(n)$ steps are always sufficient and sometimes necessary.Comment: Appears in the Proceedings of the 26th International Symposium on Graph Drawing and Network Visualization (GD 2018

Detection rate of FNA cytology in medullary thyroid carcinoma. a meta-analysis

Background: The early detection of medullary thyroid carcinoma (MTC) can improve patient prognosis, because histological stage and patient age at diagnosis are highly relevant prognostic factors. As a consequence, delay in the diagnosis and/or incomplete surgical treatment should correlate with a poorer prognosis for patients. Few papers have evaluated the specific capability of fine-needle aspiration cytology (FNAC) to detect MTC, and small series have been reported. This study conducts a meta-analysis of published data on the diagnostic performance of FNAC in MTC to provide more robust estimates. Research Design and Methods: A comprehensive computer literature search of the PubMed/MEDLINE, Embase and Scopus databases was conducted by searching for the terms 'medullary thyroid' AND 'cytology', 'FNA', 'FNAB', 'FNAC', 'fine needle' or 'fine-needle'. The search was updated until 21 March 2014, and no language restrictions were used. Results: Fifteen relevant studies and 641 MTC lesions that had undergone FNAC were included. The detection rate (DR) of FNAC in patients with MTC (diagnosed as 'MTC' or 'suspicious for MTC') on a per lesion-based analysis ranged from 12·5% to 88·2%, with a pooled estimate of 56·4% (95% CI: 52·6-60·1%). The included studies were statistically heterogeneous in their estimates of DR (I-square >50%). Egger's regression intercept for DR pooling was 0·03 (95% CI: -3·1 to 3·2, P = 0·9). The study that reported the largest MTC series had a DR of 45%. Data on immunohistochemistry for calcitonin in diagnosing MTC were inconsistent for the meta-analysis. Conclusions: The presented meta-analysis demonstrates that FNAC is able to detect approximately one-half of MTC lesions. These findings suggest that other techniques may be needed in combination with FNAC to diagnose MTC and avoid false negative results. © 2014 John Wiley & Sons Ltd

Cophylogeny reconstruction via an approximate bayesian computation

Despite an increasingly vast literature on cophylogenetic reconstructions for studying host-parasite associations, understanding the common evolutionary history of such systems remains a problem that is far from being solved. Most algorithms for host-parasite reconciliation use an event-based model, where the events include in general (a subset of) cospeciation, duplication, loss, and host switch. All known parsimonious event-based methods then assign a cost to each type of event in order to find a reconstruction of minimum cost. The main problem with this approach is that the cost of the events strongly influences the reconciliation obtained. Some earlier approaches attempt to avoid this problem by finding a Pareto set of solutions and hence by considering event costs under some minimization constraints. To deal with this problem, we developed an algorithm, called Coala, for estimating the frequency of the events based on an approximate Bayesian computation approach. The benefits of this method are 2-fold: (i) it provides more confidence in the set of costs to be used in a reconciliation, and (ii) it allows estimation of the frequency of the events in cases where the data set consists of trees with a large number of taxa. We evaluate our method on simulated and on biological data sets. We show that in both cases, for the same pair of host and parasite trees, different sets of frequencies for the events lead to equally probable solutions. Moreover, often these solutions differ greatly in terms of the number of inferred events. It appears crucial to take this into account before attempting any further biological interpretation of such reconciliations. More generally, we also show that the set of frequencies can vary widely depending on the input host and parasite trees. Indiscriminately applying a standard vector of costs may thus not be a good strategy

Dynamical structure factor of a nonlinear Klein-Gordon lattice

The quantum modes of a nonlinear Klein-Gordon lattice have been computed numerically [L. Proville, Phys. Rev. B 71, 104306 (2005)]. The on-site nonlinearity has been found to lead to phonon bound states. In the present paper, we compute numerically the dynamical structure factor so as to simulate the coherent scattering cross section at low temperature. The inelastic contribution is studied as a function of the on-site anharmonicity. Interestingly, our numerical method is not limited to the weak anharmonicity and permits one to study thoroughly the spectra of nonlinear phonons

Public libraries and social inclusion: how empathic are we?

Abstract. An IP router must forward packets at gigabit speed in order to guarantee a good QoS. Two important factors make this task a challenging problem: (i) for each packet, the longest matching prefix in the forwarding table must be computed; (ii) the routing tables contain several thousands of entries and their size grows significantlyeveryyear. Because of this, parallel routers have been developed which use several processors to forward packets. In this work, we present a novel algorithmic technique which, for the first time, exploits the parallelism of the router to also reduce the size of the routing table. Our method is scalable and requires onlya minimal additional hardware. Indeed, we prove that anyIP routing table T can be split into two subtables T1 and T2 such that: (a) |T1 | can be anypositive integer k ≤|T | and |T2 | ≤|T |−k; (b) the two routing tables can be used separatelybytwo processors so that the IP lookup on T is obtained bysimplyXOR-ing the IP lookup on the two tables. Our method is independent on the data structure used to implement the lookup search and it allows for a better use of the processors L2 cache. For real routers routing tables, we also show how to achieve simultaneously: (a) |T1 | is roughly7 % of the original table T; (b) the lookup on table T2 does not require the best matching prefix computation.

On the construction of model Hamiltonians for adiabatic quantum computation and its application to finding low energy conformations of lattice protein models

In this report, we explore the use of a quantum optimization algorithm for obtaining low energy conformations of protein models. We discuss mappings between protein models and optimization variables, which are in turn mapped to a system of coupled quantum bits. General strategies are given for constructing Hamiltonians to be used to solve optimization problems of physical/chemical/biological interest via quantum computation by adiabatic evolution. As an example, we implement the Hamiltonian corresponding to the Hydrophobic-Polar (HP) model for protein folding. Furthermore, we present an approach to reduce the resulting Hamiltonian to two-body terms gearing towards an experimental realization.Comment: 35 pages, 8 figure