Irradiation and measurements of fluorinated ethylene-propylene-A on silicon solar cells in vacuum

Silicon monoxide (SiO) coated silicon solar cells covered with fluorinated ethylene-propylene-A (FEP-A) were irradiated by 1-MeV electrons in vacuum. The effect of irradiation on the light transmittance of FEP-A was checked by measuring the short-circuit current of the cells while in vacuum after each dose increment, immediately after the irradiation, and again after a minimum elapsed time of 16 hr. The results indicated no apparent loss in transmission due to irradiation of FEP-A and no delamination from the SiO surface while the cells were in vacuum, but embrittlement of FEP-A occurred at the accumulated dose

Ultraviolet irradiation at elevated temperatures and thermal cycling in vacuum of FEP-A covered silicon solar cells

Experiments were designed and performed on silicon solar cells covered with heat-bonded FEP-A in an effort to explain the rapid degeneration of open-circuit voltage and maximum power observered on cells of this type included in an experiment on the ATS-6 spacecraft. Solar cells were exposed to ultraviolet light in vacuum at temperatures ranging from 30 to 105 C. The samples were then subjected to thermal cycling from 130 to -130 C. Inspection following irradiation indicated that all the covers remained physically intact. However, during the temperature cycling heat-bonded covers showed cracking. The test showed that heat-bonded FEP-A covers embrittle during UV exposure and the embrittlement is dependent upon sample temperature during irradiation. The results of the experiment suggest a probable mechanism for the degradation of the FEP-A cells on ATS-6

Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing, expression profiles, proteomics, and electronic health records are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of distributions that commonly appear in the analysis of such data. These distributions present some interesting features: they are discontinuous in the rational numbers, but continuous in the irrational numbers, and possess a certain self-similar (fractal-like) structure. The first set of examples which we present here are drawn from a high-throughput sequencing experiment. Here, the self-similar distributions appear as part of the evaluation of the error rate of the sequencing technology and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in electronic clinical data. The distributions are also relevant to identification of subclonal populations in tumors and the study of the evolution of infectious diseases, and more precisely the study of quasi-species and intrahost diversity of viral populations

Off the Beaten Path: Let's Replace Term-Based Retrieval with k-NN Search

Retrieval pipelines commonly rely on a term-based search to obtain candidate records, which are subsequently re-ranked. Some candidates are missed by this approach, e.g., due to a vocabulary mismatch. We address this issue by replacing the term-based search with a generic k-NN retrieval algorithm, where a similarity function can take into account subtle term associations. While an exact brute-force k-NN search using this similarity function is slow, we demonstrate that an approximate algorithm can be nearly two orders of magnitude faster at the expense of only a small loss in accuracy. A retrieval pipeline using an approximate k-NN search can be more effective and efficient than the term-based pipeline. This opens up new possibilities for designing effective retrieval pipelines. Our software (including data-generating code) and derivative data based on the Stack Overflow collection is available online

You can't see what you can't see: Experimental evidence for how much relevant information may be missed due to Google's Web search personalisation

The influence of Web search personalisation on professional knowledge work is an understudied area. Here we investigate how public sector officials self-assess their dependency on the Google Web search engine, whether they are aware of the potential impact of algorithmic biases on their ability to retrieve all relevant information, and how much relevant information may actually be missed due to Web search personalisation. We find that the majority of participants in our experimental study are neither aware that there is a potential problem nor do they have a strategy to mitigate the risk of missing relevant information when performing online searches. Most significantly, we provide empirical evidence that up to 20% of relevant information may be missed due to Web search personalisation. This work has significant implications for Web research by public sector professionals, who should be provided with training about the potential algorithmic biases that may affect their judgments and decision making, as well as clear guidelines how to minimise the risk of missing relevant information.Comment: paper submitted to the 11th Intl. Conf. on Social Informatics; revision corrects error in interpretation of parameter Psi/p in RBO resulting from discrepancy between the documentation of the implementation in R (https://rdrr.io/bioc/gespeR/man/rbo.html) and the original definition (https://dl.acm.org/citation.cfm?id=1852106) as per 20/05/201

Giant strongly connected component of directed networks

We describe how to calculate the sizes of all giant connected components of a directed graph, including the {\em strongly} connected one. Just to the class of directed networks, in particular, belongs the World Wide Web. The results are obtained for graphs with statistically uncorrelated vertices and an arbitrary joint in,out-degree distribution $P(k_i,k_o)$. We show that if $P(k_i,k_o)$ does not factorize, the relative size of the giant strongly connected component deviates from the product of the relative sizes of the giant in- and out-components. The calculations of the relative sizes of all the giant components are demonstrated using the simplest examples. We explain that the giant strongly connected component may be less resilient to random damage than the giant weakly connected one.Comment: 4 pages revtex, 4 figure

Clustering and preferential attachment in growing networks

We study empirically the time evolution of scientific collaboration networks in physics and biology. In these networks, two scientists are considered connected if they have coauthored one or more papers together. We show that the probability of scientists collaborating increases with the number of other collaborators they have in common, and that the probability of a particular scientist acquiring new collaborators increases with the number of his or her past collaborators. These results provide experimental evidence in favor of previously conjectured mechanisms for clustering and power-law degree distributions in networks.Comment: 13 pages, 2 figure

The United States, PMSCs and the state monopoly on violence: Leading the way towards norm change

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2013 Sage.The proliferation of private military and security companies (PMSCs) in Iraq and Afghanistan has raised many questions regarding the use of armed force by private contractors. This article addresses the question of whether the increased acceptance of PMSCs indicates a transformation of the international norm regarding the state monopoly on the legitimate use of armed force. Drawing on theoretical approaches to the analysis of norm change, the article employs four measures to investigate possible changes in the strength and meaning of this norm: modifications in state behaviour, state responses to norm violation, the promulgation of varying interpretations of the norm in national and international laws and regulations, and changes in norm discourse. Based on an analysis of empirical evidence from the United States of America and its allies, the article concludes that these measures suggest that the USA is leading the way towards a transformation of the international norm of the state monopoly on violence, involving a revised meaning. Although this understanding has not yet been formally implemented in international law, it has allowed a growing number of countries to tolerate, accept or legalize the use of armed force by PMSCs in the international arena.The Alexander von Humboldt Foundation and the Peace Research Institute Frankfurt

Universal Behavior of Load Distribution in Scale-free Networks

We study a problem of data packet transport in scale-free networks whose degree distribution follows a power-law with the exponent $\gamma$. We define load at each vertex as the accumulated total number of data packets passing through that vertex when every pair of vertices send and receive a data packet along the shortest path connecting the pair. It is found that the load distribution follows a power-law with the exponent $\delta \approx 2.2(1)$, insensitive to different values of $\gamma$ in the range, $2 < \gamma \le 3$, and different mean degrees, which is valid for both undirected and directed cases. Thus, we conjecture that the load exponent is a universal quantity to characterize scale-free networks.Comment: 5 pages, 5 figures, revised versio