Structure of resorcinol,phenol, and furan resins by MALDI‐TOF mass spectrometry and 13C NMR

The structure of traditional, linear phenol–resorcinol–formaldehyde (PRF) resins, urea‐branched PRF resins, and phenol–resorcinol–furfural (PRFuran) resins has been investigated in depth by both matrix‐assisted laser desorption/ionization time of flight (MALDI‐TOF) mass spectroscopy and ¹³C NMR. The structure of a variety of oligomers has been obtained, and the structures present in each of the three types of resins related to the very different percentages of resorcinol needed for their equal performance as adhesives. The oligomers type and species distribution appeared very different for each case. PRF resins performance is improved by maximizing either the proportion of resorcinol‐containing oligomers or methylol‐groups containing oligomers, even without any resorcinol, or both. It is equally obtained by the minimization of the relative proportion of the low reactivity Phenol (CH₂ Phenol) species in which resorcinol is not present, this being the most important parameter. This can be obtained by more effective use of the resorcinol by just modifying the resin manufacturing procedure. This parameter instead does not appear to be determinant in PRFuran resins. In these, it is the higher molecular weight of furfural in relation to formaldehyde that engenders for the same manufacturing procedure a correspondingly lower proportion of resorcinol in the resin. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 2665–2674, 2004     

The structure and content of programming knowledge: Disentangling training and language effects in theories of skill development

This article reviews the extensive literature emerging from studies concerned with skill acquisition and the development of knowledge representation in programming. In particular, it focuses upon theories of program comprehension that suggest programming knowledge can be described in terms of stereotypical knowledge structures that can in some way capture programming expertise independently of the programming language used and in isolation from a programmer's specific training experience. An attempt is made to demonstrate why existing views are inappropriate. On the one hand, programs are represented in terms of a variety of formal notations ranging from the quasi‐mathematical to the near textual. It is argued that different languages may lead to different forms of knowledge representation, perhaps emphasizing certain structures at the expense of others or facilitating particular strategies. On the other hand, programmers are typically taught problem‐solving techniques that suggest a strict approach to problem decomposition. Hence, it seems likely that another factor that may mediate the development of knowledge representation, and that has not received significant attention elsewhere, is related to the training experience that programmers typically encounter. In this article, recent empirical studies that have addressed these issues are reviewed, and the implications of these studies for theories of skill acquisition and for knowledge representation are discussed. In conclusion, a more extensive account of knowledge representation in programming is presented that emphasizes training effects and the role played by specific language features in the development of knowledge representation within the programming domain.     

Re-examining the causal structure of information technology impact research

About 20 years ago, Markus and Robey noted that most research on IT impacts had been guided by deterministic perspectives and had neglected to use an emergent perspective, which could account for contradictory findings. They further observed that most research in this area had been carried out using variance theories at the expense of process theories. Finally, they suggested that more emphasis on multilevel theory building would likely improve empirical reliability. In this paper, we reiterate the observations and suggestions made by Markus and Robey on the causal structure of IT impact theories and carry out an analysis of empirical research published in four major IS journals, Management Information Systems Quarterly (MISQ), Information Systems Research (ISR), the European Journal of Information Systems (EJIS), and Information and Organization (I&O), to assess compliance with those recommendations. Our final sample consisted of 161 theory-driven articles, accounting for approximately 21% of all the empirical articles published in these journals. Our results first reveal that 91% of the studies in MISQ, ISR, and EJIS focused on deterministic theories, while 63% of those in I&O adopted an emergent perspective. Furthermore, 91% of the articles in MISQ, ISR, and EJIS adopted a variance model; this compares with 71% from I&O that applied a process model. Lastly, mixed levels of analysis were found in 14% of all the surveyed articles. Implications of these findings for future research are discussed.     

Practical Interdomain Routing Security

This article reviews risks and vulnerabilities in interdomain routing and best practices that can have near-term benefits for routing security. It includes examples of routing failures and common attacks on routers, and countermeasures to reduce router vulnerabilities.     

Distribution-preserving statistical disclosure limitation

One approach to limiting disclosure risk in public-use microdata is to release multiply-imputed, partially synthetic data sets. These are data on actual respondents, but with confidential data replaced by multiply-imputed synthetic values. A mis-specified imputation model can invalidate inferences based on the partially synthetic data, because the imputation model determines the distribution of synthetic values. We present a practical method to generate synthetic values when the imputer has only limited information about the true data generating process. We combine a simple imputation model (such as regression) with density-based transformations that preserve the distribution of the confidential data, up to sampling error, on specified subdomains. We demonstrate through simulations and a large scale application that our approach preserves important statistical properties of the confidential data, including higher moments, with low disclosure risk.     

Sentinel-1-based flood mapping: a fully automated processing chain

This article presents an automated Sentinel-1-based processing chain designed for flood detection and monitoring in near-real-time (NRT). Since no user intervention is required at any stage of the flood mapping procedure, the processing chain allows deriving time-critical disaster information in less than 45 min after a new data set is available on the Sentinel Data Hub of the European Space Agency (ESA). Due to the systematic acquisition strategy and high repetition rate of Sentinel-1, the processing chain can be set up as a web-based service that regularly informs users about the current flood conditions in a given area of interest. The thematic accuracy of the thematic processor has been assessed for two test sites of a flood situation at the border between Greece and Turkey with encouraging overall accuracies between 94.0% and 96.1% and Cohen’s kappa coefficients (κ) ranging from 0.879 to 0.910. The accuracy assessment, which was performed separately for the standard polarizations (VV/VH) of the interferometric wide swath (IW) mode of Sentinel-1, further indicates that under calm wind conditions, slightly higher thematic accuracies can be achieved by using VV instead of VH polarization data.