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study of 18 leading mobile sites, and our most recent large-scale eye-tracking study of checkouts, have all confirmed the same thing: checkout processes and long sign-up forms need to mark both the required and optional fields explicitly.

On the sites that didn’t explicitly denote both field types (i.e. optional and required) the test subjects spent longer time filling out the fields and more frequently ran into entirely preventable “Field is required” validation errors. In fact, when testing mobile checkouts, 75% of the test subjects experienced severe form usability issues on sites that failed to mark both required and optional fields clearly.

explicitly denote

Which fields are required and which are optional? Is ‘Apt. or Suite #’ required? How about ‘Contact Phone’? Some sites require a phone number while other sites don’t – alas, the user has no way of knowing without proper indicators for required and optional fields.

The most common mistake – made by 63% of the top 100 e-commerce checkouts – is to only denote one of the types – i.e. either only denoting required fields or the optional ones (the latter has the most severe usability consequences). Another common issue was observed on checkout steps where all the fields were required (this is often the case at the ‘Payment’ step), where some sites neglect to explicitly mark any of the fields as being required – leading to unnecessary form errors and confusion.

only denoting

The fix is easy: explicitly mark each and every field as optional / required (denoting both types throughout the form). Yet, when benchmarking the top 100 US checkout processes, only 9% of the sites explicitly marked both field types. In this article we’ll therefore share our research findings on why:

only 9%

We’ll end the article with a couple of “best practice” examples from sites that do denote both field types to remove any uncertainty and improve form completion times.

“best practice” examples

Note: the findings shared in this article relate to checkout forms and long account creation forms. Other forms, in particular short sign-up and contact forms, don’t seem to be affected anywhere nearly as much by the issues described and may therefore employ alternative designs.

From 2005 to 2013, the total amount awarded grew from about €50k to €90k, with a record 279 awards being allocated to support attendance to the 2014 General Assembly. For the 2015 General Assembly, the EGU has allocated €110k to financially support scientists who wish to attend the meeting. About 80-90% of the funds are reserved to assist young scientists in attending the conference, whilst the remaining funds will be allocated to established scientists.

Financial support includes a waiver of the registration fee and a refund of the Abstract Processing Charge (relating to the abstract for which support was requested). Additionally, the grant may include support for travel expenditures, at the discretion of the Support Selection Committee, to a maximum of €300. The EGU currently runs two different financial support schemes; you will be able to find more details about each of these awards on theSupport Distinctionsection on the EGU 2015 website. You will also find details on who is eligible for the awards on the website.

Scientists who wish to apply for financial support should submit an abstract, on which they are first authors, by 28 November 2014 . Late applications, or applications where the scientist is not the main author, will not be considered. The EGU Support Selection Committee will make its decision to support individual contributions by 31 December 2014. All applicants will be informed after the decision via email early in the new year. Only the granted amount mentioned in the financial support email will be paid out to the supported contact author, in person, during the EGU General Assembly 2015.

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Research Article SOCIAL SCIENCES
Trends and fluctuations in the severity of interstate wars

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21 Feb 2018: Vol. 4, no. 2, eaao3580 DOI: 10.1126/sciadv.aao3580
Aaron Clauset
Department of Computer Science, University of Colorado, Boulder, CO 80309, USA. BioFrontiers Institute, University of Colorado, Boulder, CO 80303, USA. Santa Fe Institute, Santa Fe, NM 87501, USA.

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Abstract

Since 1945, there have been relatively few large interstate wars, especially compared to the preceding 30 years, which included both World Wars. This pattern, sometimes called the long peace, is highly controversial. Does it represent an enduring trend caused by a genuine change in the underlying conflict-generating processes? Or is it consistent with a highly variable but otherwise stable system of conflict? Using the empirical distributions of interstate war sizes and onset times from 1823 to 2003, we parameterize stationary models of conflict generation that can distinguish trends from statistical fluctuations in the statistics of war. These models indicate that both the long peace and the period of great violence that preceded it are not statistically uncommon patterns in realistic but stationary conflict time series. This fact does not detract from the importance of the long peace or the proposed mechanisms that explain it. However, the models indicate that the postwar pattern of peace would need to endure at least another 100 to 140 years to become a statistically significant trend. This fact places an implicit upper bound on the magnitude of any change in the true likelihood of a large war after the end of the Second World War. The historical patterns of war thus seem to imply that the long peace may be substantially more fragile than proponents believe, despite recent efforts to identify mechanisms that reduce the likelihood of interstate wars.

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

Science Advances

Vol 4, No. 202 February 2018

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Trends and fluctuations in the severity of interstate wars

By Aaron Clauset

We have conducted the first large-scale assessment of repeat masking strategy and genome alignment parameters using real genomes - producing a practical guide to alignment parameters. We have tested a sufficient number of parameter combinations and genome pairs so that our results will be relevant to most genome alignment tasks. With our results, researchers will not only be able to produce more accurate alignments than with previous standard practice, but they will also have a much better idea of the reliability they can expect from such alignments.

The following genome versions were obtained from UCSC Mens Franklin and Marshall Orange Franklin Tshirt River Island Outlet Footlocker Discount Pictures 2018 Online XRMbL
: hg18, galGal3, fr2, gasAcu1, ce6, caePb2 [ 7 ]. The remaining genomes were obtained from RefSeq [ 47 ]. : NC_000913.2. : NC_000964.2. : NC_001326.1, NC_003421.2, NC_003423.3, NC_003424.3. : NC_003074.5, NC_003071.4, NC_003070.6, NC_003075.4, NC_003076.5. : NC_008394.1, NC_008395.1, NC_008396.1, NC_008397.1, NC_008398.1, NC_008399.1, NC_008400.1, NC_008401.1, NC_008402.1, NC_008403.1, NC_008404.1, NC_008405.1. : NC_001133.7, NC_001134.7, NC_001135.4, NC_001136.8, NC_001137.2, NC_001138.4, NC_001139.8, NC_001140.5, NC_001141.1, NC_001142.7, NC_001143.7, NC_001144.4, NC_001145.2, NC_001146.6, NC_001147.5, NC_001148.3, NC_001224.1. For the chaining evaluation, we obtained human and mouse CD4 regions from GenBank: U47924.1 and AC002397.1.

E-values are related to alignment scores by the following equation: E-value = 2 mnK * exp(-λ * score) [ 9 ]. Here, m and n are the lengths of the two genomes, and the factor of 2 appears because we compare both strands. We defined genome length as the total count of A, C, G, and T (i.e. ambiguous bases aren't counted) before any repeat-masking. The parameters λ and K depend on the scoring matrix, gap costs, and base abundances. We calculated them using ALP 1.1 http://www.ncbi.nlm.nih.gov/CBBresearch/Spouge/html.ncbi/index/software.html with options: -eps_lambda 0.01 -eps_K 0.05 -max_time 600 -max_mem 2000 [ 38 ]. For the base abundances, we used the average of the two genomes (i.e. we obtained the percentages for each genome separately, and then averaged those percentages).

For all alignments, any repeat masking was applied equally to both genomes. We ran Tandem Repeats Finder 4.04 with these options: match = 2 mismatch = 5 delta = 5 PM = 80 PI = 10 minscore = 30 maxperiod = 200 -R . For "TRFs" (Figure 1 ), we used: match = 2 mismatch = 7 delta = 7 PM = 80 PI = 10 minscore = 50 maxperiod = 2000 . For DustMasker, we used the option " -level 16 ", which increases the amount of masking. Runnseg has trouble with large runs of "N" in sequences: so we split sequences at runs of 100 or more "N"s, applied runnseg to the fragments, and then re-joined them.

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