Bird's‐Eye ‐ Large‐Scale Visual Analytics of City Dynamics using Social Location Data

The analysis of behavioral city dynamics, such as temporal patterns of visited places and citizens' mobility routines, is an essential task for urban and transportation planning. Social media applications such as Foursquare and Twitter provide access to large‐scale and up‐to‐date dynamic movement data that not only help to understand the social life and pulse of a city but also to maintain and improve urban infrastructure. However, the fast growth rate of this data poses challenges for conventional methods to provide up‐to‐date, flexible analysis. Therefore, planning authorities barely consider it. We present a system and design study to leverage social media data that assist urban and transportation planners to achieve better monitoring and analysis of city dynamics such as visited places and mobility patterns in large metropolitan areas. We conducted a goal‐and‐task analysis with urban planning experts. To address these goals, we designed a system with a scalable data monitoring back‐end and an interactive visual analytics interface. The monitoring component uses intelligent pre‐aggregation to allow dynamic queries in near real‐time. The visual analytics interface leverages unsupervised learning to reveal clusters, routines, and unusual behavior in massive data, allowing to understand patterns in time and space. We evaluated our approach based on a qualitative user study with urban planning experts which demonstrates that intuitive integration of advanced analytical tools with visual interfaces is pivotal in making behavioral city dynamics accessible to practitioners. Our interviews also revealed areas for future research.     

The molecular basis for A-site mutations conferring aminoglycoside resistance: relationship between ribosomal susceptibility and X-ray crystal structures

Aminoglycoside antibiotics target the 16S ribosomal RNA (rRNA) bacterial A site and induce misreading of the genetic code. Point mutations of the ribosomal A site may confer resistance to aminoglycoside antibiotics. The influence of bacterial mutations (introduced by site-directed mutagenesis) on ribosomal drug susceptibility was investigated in vivo by determination of minimal inhibitory concentrations. To determine the origin of the various resistance phenotypes at a molecular level, the in vivo results were compared with the previously published crystal structures of paromomycin, tobramycin, and geneticin bound to oligonucleotides containing the minimal A site. Two regions appear crucial for binding in the A site: the single adenine residue at position 1408 and the non-Watson-Crick U1406.U1495 pair. The effects of mutations at those positions are modulated by the nature of the substituent at position 6' (either hydroxy or ammonium group) on ring I, by the number of positive charges on the antibiotic, and by the linkage between rings I and III (either 4,5 or 4,6). In particular, the analysis demonstrates: 1) that the C1409-G1491 to A1409-U1491 polymorphism (observed in 15 % of bacteria) is not associated with resistance, which indicates that it does not affect the stacking of ring I on residue 1491, 2) that the high-level resistance to 6'-NH3+ aminoglycosides exhibited by the A1408G mutation most probably results from the inability of ring I forming a pseudo base pair with G1408, which prevents its insertion inside the A site helix, and 3) that mutations of the uracil residues forming the U1406.U1495 pair either to cytosine or to adenine residues mostly confer low to moderate levels of drug resistance, whereas the U1406C/U1495A double mutation confers high-level resistance (except for neomycin), which suggests that aminoglycoside binding to the wild-type A site and its functional consequences strongly depend on a particular geometry of the U1406.U1495 pair. The relationships between the resistance phenotypes observed in vivo and the interactions described at the molecular level define the biological importance of the different structural interactions observed by X-ray crystallography studies.     

Capacity-achieving ensembles for the binary erasure channel with bounded complexity

We present two sequences of ensembles of nonsystematic irregular repeat-accumulate (IRA) codes which asymptotically (as their block length tends to infinity) achieve capacity on the binary erasure channel (BEC) with bounded complexity per information bit. This is in contrast to all previous constructions of capacity-achieving sequences of ensembles whose complexity grows at least like the log of the inverse of the gap (in rate) to capacity. The new bounded complexity result is achieved by puncturing bits, and allowing in this way a sufficient number of state nodes in the Tanner graph representing the codes. We derive an information-theoretic lower bound on the decoding complexity of randomly punctured codes on graphs. The bound holds for every memoryless binary-input output-symmetric (MBIOS) channel and is refined for the binary erasure channel.     

Photoelectronic Properties of Disordered Organic Solids: Molecularly-Doped Polymers

Currently there is intense scientific and technological interest in molecular materials as diverse as quasi-one-dimensional organic crystals [1] and amorphous organic polymers [2, 3]. Despite this diversity they pose several common scientific issues that indicate potentially useful and important technological properties. They also offer opportunities for studying scientific questions characteristic of their particular genre. Through this predictive understanding, the possibility of marrying the best features of each is a strong motivator for the intense activity in these fields. A particularly interesting combination of such features exists in disordered organic solids to which the large and important class, polymers, belongs.     

Solid phase extraction coupled to liquid chromatography-tandem mass spectrometry analysis of sulfonamides, tetracyclines, analgesics and hormones in surface water and wastewater in Luxembourg

In the early 1990s different studies highlighted the relationship between pharmaceuticals, human health and the environment. Among the emerging contaminants, antibiotics are obviously of high concern, because of their potential for inducing antibiotic resistance. In addition, natural and synthetic hormones are relevant because of their potential endocrine-disrupting effects on wildlife. This investigation focuses on the analysis of four classes of veterinary and human pharmaceuticals (sulfonamides, tetracyclines, analgesics and hormones) in surface water and wastewater in Luxembourg. The selected eleven pharmaceuticals include four sulfonamides (sulfathiazole, sulfamethoxazole, sulfadimethoxine and sulfamethazine), two tetracyclines (tetracycline and oxytetracycline), two analgesics (ibuprofen and diclofenac), and three hormones (2 naturals, estrone and β-estradiol, and a synthetic one, 17-α-ethinyl estradiol). The most innovative parts of this study are the simultaneous extraction of the above-mentioned pharmaceuticals as well as tracking their behaviour during flood events in a small river catchment. The method includes pre-concentration by solid phase extraction using Oasis® HLB (Hydrophilic Lipophilic Balance) which gave superior results compared to Chromabond® C-18EC, Chromabond® EASY and Bond Elut® PLEXA cartridges, also evaluated in this investigation. The analysis of the investigated pharmaceutical compounds is carried out by high performance liquid chromatography coupled to a triple quadrupole mass spectrometer. The limits of quantification were 1 ng L^− 1, except for β-estradiol (2 ng L^− 1) and 17-α-ethinyl estradiol (6 ng L^− 1). Recovery rates range from 70 to 94%, with relative standard deviations between 4 and 19%. Application of this method to river concentration and flood events revealed high concentrations of ibuprofen (10-4000 ng L^− 1), with highest levels during flood events, while concentrations of estrogens (1-240 ng L^− 1) and sulfonamides (1-20 ng L^− 1) were comparatively low.     

The impact of goal focus, task type and group size on synchronous net-based collaborative learning discourses

Net-based collaborative learning discourses often suffer from deficiencies such as lack of coherence and coordination. It is suggested that the provision of two functionalities, referencing and typing, which learners may optionally use to ground their contributions during a chat-based discourse, can improve collaborative learning. In particular, we examined if goal focus, type of task and group size affect learning outcomes and the use of these functionalities. A chat-based system, called a learning protocol, implements these functionalities and serves as a net-based collaborative learning environment. Results suggest that a learning protocol is more beneficial for knowledge-acquisition tasks than for problem-solving tasks, and that the use of supporting functionalities increases when goal focus is on the group rather than on the individual. Also, there is a tendency that learning outcomes improve as group size increases. We propose that learning protocols provide potentially valuable design features that can promote net-based collaborative learning.     

Pathline: A Tool For Comparative Functional Genomics

Biologists pioneering the new field of comparative functional genomics attempt to infer the mechanisms of gene regulation by looking for similarities and differences of gene activity over time across multiple species. They use three kinds of data: functional data such as gene activity measurements, pathway data that represent a series of reactions within a cellular process, and phylogenetic relationship data that describe the relatedness of species. No existing visualization tool can visually encode the biologically interesting relationships between multiple pathways, multiple genes, and multiple species. We tackle the challenge of visualizing all aspects of this comparative functional genomics dataset with a new interactive tool called Pathline. In addition to the overall characterization of the problem and design of Pathline, our contributions include two new visual encoding techniques. One is a new method for linearizing metabolic pathways that provides appropriate topological information and supports the comparison of quantitative data along the pathway. The second is the curvemap view, a depiction of time series data for comparison of gene activity and metabolite levels across multiple species. Pathline was developed in close collaboration with a team of genomic scientists. We validate our approach with case studies of the biologists’ use of Pathline and report on how they use the tool to confirm existing findings and to discover new scientific insights.     

Volume MLS ray casting

The method of Moving Least Squares (MLS) is a popular framework for reconstructing continuous functions from scattered data due to its rich mathematical properties and well-understood theoretical foundations. This paper applies MLS to volume rendering, providing a unified mathematical framework for ray casting of scalar data stored over regular as well as irregular grids. We use the MLS reconstruction to render smooth isosurfaces and to compute accurate derivatives for high-quality shading effects. We also present a novel, adaptive preintegration scheme to improve the efficiency of the ray casting algorithm by reducing the overall number of function evaluations, and an efficient implementation of our framework exploiting modern graphics hardware. The resulting system enables high-quality volume integration and shaded isosurface rendering for regular and irregular volume data.