In the IP of the Beholder: Strategies for Active IPv6 Topology Discovery

Existing methods for active topology discovery within the IPv6 Internet largely mirror those of IPv4. In light of the large and sparsely populated address space, in conjunction with aggressive ICMPv6 rate limiting by routers, this work develops a different approach to Internet-wide IPv6 topology mapping. We adopt randomized probing techniques in order to distribute probing load, minimize the effects of rate limiting, and probe at higher rates. Second, we extensively analyze the efficiency and efficacy of various IPv6 hitlists and target generation methods when used for topology discovery, and synthesize new target lists based on our empirical results to provide both breadth (coverage across networks) and depth (to find potential subnetting). Employing our probing strategy, we discover more than 1.3M IPv6 router interface addresses from a single vantage point. Finally, we share our prober implementation, synthesized target lists, and discovered IPv6 topology results

Size-resolved aerosol emission factors and new particle formation/growth activity occurring in Mexico City during the MILAGRO 2006 Campaign

Measurements of the aerosol size distribution from 11 nm to 2.5 microns were made in Mexico City in March 2006, during the MILAGRO (Megacity Initiative: Local and Global Research Observations) field campaign. Observations at the urban supersite, referred to as T0, could often be characterized by morning conditions with high particle mass concentrations, low mixing heights, and highly correlated particle number and CO<sub>2</sub> concentrations, indicative that particle number is controlled by primary emissions. Average size-resolved and total number- and volume-based emission factors for combustion sources impacting T0 have been determined using a comparison of peak sizes in particle number and CO<sub>2</sub> concentration. Peaks are determined by subtracting the measured concentration from a calculated baseline concentration time series. The number emission and volume emission factors for particles from 11 nm to 494 nm are 1.56 × 10<sup>15</sup> particles, and 9.48 × 10<sup>11</sup> cubic microns per kg of carbon, respectively. The uncertainty of the number emission factor is approximately plus or minus 50 %. The mode of the number emission factor was between 25 and 32 nm, while the mode of the volume factor was between 0.25 and 0.32 microns. These emission factors are reported as log normal model parameters and are compared with multiple emission factors from the literature. In Mexico City in the afternoon, the CO<sub>2</sub> concentration drops during ventilation of the polluted layer, and the coupling between CO<sub>2</sub> and particle number breaks down, especially during new particle formation events when particle number is no longer controlled by primary emissions. Using measurements of particle number and CO<sub>2</sub> taken aboard the NASA DC-8, the determined primary emission factor was applied to the Mexico City Metropolitan Area (MCMA) plume to quantify the degree of secondary particle formation in the plume; the primary emission factor accounts for less than 50 % of the total particle number and the surplus particle count is not correlated with photochemical age. Primary particle volume and number in the size range 0.1–2 μm are similarly too low to explain the observed volume distribution. Contrary to the case for number, the apparent secondary volume increases with photochemical age. The size distribution of the apparent increase, with a mode at ~250 nm, is reported

Feedback-Driven Radiology Exam Report Retrieval with Semantics

Clinical documents are vital resources for radiologists to have a better understanding of patient history. The use of clinical documents can complement the often brief reasons for exams that are provided by physicians in order to perform more informed diagnoses. With the large number of study exams that radiologists have to perform on a daily basis, it becomes too time-consuming for radiologists to sift through each patient\u27s clinical documents. It is therefore important to provide a capability that can present contextually relevant clinical documents, and at the same time satisfy the diverse information needs among radiologists from different specialties. In this work, we propose a knowledge-based semantic similarity approach that uses domain-specific relationships such as part-of along with taxonomic relationships such as is-a to identify relevant radiology exam records. Our approach also incorporates explicit relevance feedback to personalize radiologists information needs. We evaluated our approach on a corpus of 6,265 radiology exam reports through study sessions with radiologists and demonstrated that the retrieval performance of our approach yields an improvement of 5% over the baseline. We further performed intra-class and inter-class similarities using a subset of 2,384 reports spanning across 10 exam codes. Our result shows that intra-class similarities are always higher than the inter-class similarities and our approach was able to obtain 6% percent improvement in intra-class similarities against the baseline. Our results suggest that the use of domain-specific relationships together with relevance feedback provides a significant value to improve the accuracy of the retrieval of radiology exam reports

How to Train a Cell–Cutting-Edge Molecular Tools

In biological systems, the formation of molecular complexes is the currency for all cellular processes. Traditionally, functional experimentation was targeted to single molecular players in order to understand its effects in a cell or animal phenotype. In the last few years, we have been experiencing rapid progress in the development of ground-breaking molecular biology tools that affect the metabolic, structural, morphological, and (epi) genetic instructions of cells by chemical, optical (optogenetic) and mechanical inputs. Such precise dissection of cellular processes is not only essential for a better understanding of biological systems, but will also allow us to better diagnose and fix common dysfunctions. Here, we present several of these emerging and innovative techniques by providing the reader with elegant examples on how these tools have been implemented in cells, and, in some cases, organisms, to unravel molecular processes in minute detail. We also discuss their advantages and disadvantages with particular focus on their translation to multicellular organisms for in vivo spatiotemporal regulation. We envision that further developments of these tools will not only help solve the processes of life, but will give rise to novel clinical and industrial applications

Biotransformation patterns of 2,4,6-trinitrotoluene by aerobic bacteria

2,4,6-Trinitrotoluene (TNT), a toxic nitroaromatic explosive, accumulates in the environment, making necessary the remediation of contaminated areas and unused materials. Although bioremediation has been utilized to detoxify TNT, the metabolic process involved in the metabolism of TNT have proven to be complex. The three aerobic bacterial strains reported here (Pseudomonas aeruginosa, Bacillus sp., and Staphylococcus sp.) differ in their ability to biotransform TNT and in their growth characteristics in the presence of TNT. In addition, enzymatic activities have been identified that differ in the reduction of nitro groups, cofactor preferences, and the ability to eliminate-NO2 from the ring. The Bacillus sp. has the most diverse bioremediation potential owing to its growth in the presence of TNT, high level of reductive ability, and capability of removing-NO2 from the nitroaromatic ring