Regulation of Imports and Foregn Investment in the United States on National Security Grounds

Traditionally, concerns over the effects of trade and investment on national security have centered upon the transfer of products and technologies with potential military uses. However, national security concerns also arise with respect to the economic and military impact of imports and of foreign acquisition of domestic assets. The United States has a longstanding statute, section 232 of the Trade Expansion Act of 1962, that allows the President to restrict imports of goods on national security grounds. More recently, another statute, popularly referred to as the Exon-Florio Act, provides the President with authority to bar the acquisition of United States companies or businesses by foreign persons on national security grounds. Thus, United States law provides for the regulation of inward flows of both goods and capital for reasons of national security. This article will examine the substance, interpretation, and application of these laws, and comment upon possible future developments in light of evolving trends in the global economy

Local modularity measure for network clusterizations

Many complex networks have an underlying modular structure, i.e., structural subunits (communities or clusters) characterized by highly interconnected nodes. The modularity $Q$ has been introduced as a measure to assess the quality of clusterizations. $Q$ has a global view, while in many real-world networks clusters are linked mainly \emph{locally} among each other (\emph{local cluster-connectivity}). Here, we introduce a new measure, localized modularity $LQ$, which reflects local cluster structure. Optimization of $Q$ and $LQ$ on the clusterization of two biological networks shows that the localized modularity identifies more cohesive clusters, yielding a complementary view of higher granularity.Comment: 5 pages, 4 figures, RevTex4; Changed conten

HIV and Hepatitis C-Coinfected Patients Have Lower Low-Density Lipoprotein Cholesterol Despite Higher Proprotein Convertase Subtilisin Kexin 9 (PCSK9): An Apparent "PCSK9-Lipid Paradox".

BackgroundProprotein convertase subtilisin kexin 9 (PCSK9) inhibitors reduce low-density lipoprotein cholesterol (LDL-C) and improve outcomes in the general population. HIV-infected individuals are at increased risk for cardiovascular events and have high rates of dyslipidemia and hepatitis C virus (HCV) coinfection, making PCSK9 inhibition a potentially attractive therapy.Methods and resultsWe studied 567 participants from a clinic-based cohort to compare PCSK9 levels in patients with HIV/HCV coinfection (n=110) with those with HIV infection alone (n=385) and with uninfected controls (n=72). The mean age was 49 years, and the median LDL-C level was 100 mg/dL (IQR 77-124 mg/dL); 21% were taking statins. The 3 groups had similar rates of traditional risk factors. Total cholesterol, LDL-C, and high-density lipoprotein cholesterol levels were lower in coinfected patients compared with controls (P<0.001). PCSK9 was 21% higher in HIV/HCV-coinfected patients versus controls (95% CI 9-34%, P<0.001) and 11% higher in coinfected individuals versus those with HIV infection alone (95% CI 3-20%, P=0.008). After adjustment for cardiovascular risk factors, HIV/HCV coinfection remained significantly associated with 20% higher PCSK9 levels versus controls (95% CI 8-33%, P=0.001). Interleukin-6 levels increased in a stepwise fashion from controls (lowest) to HIV-infected to HIV/HCV-coinfected individuals (highest) and correlated with PCSK9 (r=0.11, P=0.018).ConclusionsDespite having lower LDL-C, circulating PCSK9 levels were increased in patients coinfected with HIV and HCV in parallel with elevations in the inflammatory, proatherogenic cytokine interleukin-6. Clinical trials should be conducted to determine the efficacy of targeted PCSK9 inhibition in the setting of HIV/HCV coinfection

Generalizations of the clustering coefficient to weighted complex networks

The recent high level of interest in weighted complex networks gives rise to a need to develop new measures and to generalize existing ones to take the weights of links into account. Here we focus on various generalizations of the clustering coefficient, which is one of the central characteristics in the complex network theory. We present a comparative study of the several suggestions introduced in the literature, and point out their advantages and limitations. The concepts are illustrated by simple examples as well as by empirical data of the world trade and weighted coauthorship networks.Comment: 4 pages, 1 table, 3 figures; revised versio

Spectral centrality measures in complex networks

Complex networks are characterized by heterogeneous distributions of the degree of nodes, which produce a large diversification of the roles of the nodes within the network. Several centrality measures have been introduced to rank nodes based on their topological importance within a graph. Here we review and compare centrality measures based on spectral properties of graph matrices. We shall focus on PageRank, eigenvector centrality and the hub/authority scores of HITS. We derive simple relations between the measures and the (in)degree of the nodes, in some limits. We also compare the rankings obtained with different centrality measures.Comment: 11 pages, 10 figures, 5 tables. Final version published in Physical Review

Finding local community structure in networks

Although the inference of global community structure in networks has recently become a topic of great interest in the physics community, all such algorithms require that the graph be completely known. Here, we define both a measure of local community structure and an algorithm that infers the hierarchy of communities that enclose a given vertex by exploring the graph one vertex at a time. This algorithm runs in time O(d*k^2) for general graphs when $d$ is the mean degree and k is the number of vertices to be explored. For graphs where exploring a new vertex is time-consuming, the running time is linear, O(k). We show that on computer-generated graphs this technique compares favorably to algorithms that require global knowledge. We also use this algorithm to extract meaningful local clustering information in the large recommender network of an online retailer and show the existence of mesoscopic structure.Comment: 7 pages, 6 figure

Clustering in Complex Directed Networks

Many empirical networks display an inherent tendency to cluster, i.e. to form circles of connected nodes. This feature is typically measured by the clustering coefficient (CC). The CC, originally introduced for binary, undirected graphs, has been recently generalized to weighted, undirected networks. Here we extend the CC to the case of (binary and weighted) directed networks and we compute its expected value for random graphs. We distinguish between CCs that count all directed triangles in the graph (independently of the direction of their edges) and CCs that only consider particular types of directed triangles (e.g., cycles). The main concepts are illustrated by employing empirical data on world-trade flows

Soft power, hard news:How journalists at state-funded transnational media legitimize their work

How do journalists working for different state-funded international news organizations legitimize their relationship to the governments which support them? In what circumstances might such journalists resist the diplomatic strategies of their funding states? We address these questions through a comparative study of journalists working for international news organizations funded by the Chinese, US, UK and Qatari governments. Using 52 interviews with journalists covering humanitarian issues, we explain how they minimized tensions between their diplomatic role and dominant norms of journalistic autonomy by drawing on three – broadly shared – legitimizing narratives, involving different kinds of boundary-work. In, the first ‘exclusionary’ narrative, journalists differentiated their ‘truthful’ news reporting from the ‘false’ state ‘propaganda’ of a common Other, the Russian-funded network, RT. In the second ‘fuzzifying’ narrative, journalists deployed the ambiguous notion of ‘soft power’ as an ambivalent ‘boundary concept’, to defuse conflicts between journalistic and diplomatic agendas. In the final ‘inversion’ narrative, journalists argued that, paradoxically, their dependence on funding states gave them greater ‘operational autonomy’. Even when journalists did resist their funding states, this was hidden or partial, and prompted less by journalists’ concerns about the political effects of their work, than by serious threats to their personal cultural capital

High-speed multiple-mode mass-sensing resolves dynamic nanoscale mass distributions

Simultaneously measuring multiple eigenmode frequencies of nanomechanical resonators can determine the position and mass of surface-adsorbed proteins, and could ultimately reveal the mass tomography of nanoscale analytes. However, existing measurement techniques are slow (<1 Hz bandwidth), limiting throughput and preventing use with resonators generating fast transient signals. Here we develop a general platform for independently and simultaneously oscillating multiple modes of mechanical resonators, enabling frequency measurements that can precisely track fast transient signals within a user-defined bandwidth that exceeds 500 Hz. We use this enhanced bandwidth to resolve signals from multiple nanoparticles flowing simultaneously through a suspended nanochannel resonator and show that four resonant modes are sufficient for determining their individual position and mass with an accuracy near 150 nm and 40 attograms throughout their 150-ms transit. We envision that our method can be readily extended to other systems to increase bandwidth, number of modes, or number of resonators.United States. Army Research Office (Grant W911NF-09-0001)Center for Integration of Medicine and Innovative Technology (Contract 09-440)National Science Foundation (U.S.) (Grant 1129359