In this article we report a method to fabricate 2D TiO2–WO3 composite inverse opal films via a mechanical co-assembly route with a template of polystyrene spheres. Upon repeating the experiments described, we found that this was not an effective method for forming the films; often the film was broken or did not form at all.
The note also explains why the experiment didn’t work:
A paper on 3-D printing has been pulled because it “inadvertently” included some sensitive material.
We’re not sure which parts of the paper were the specific problem. But the sensitive material may have something with how to improve the surfaces of 3-D printed products, which is the subject of “Feasibility of using Copper(II)Oxide for additive manufacturing.”
Here’s what the paper, published in the International Journal of Precision Engineering and Manufacturing contains,according to the abstract:
Additive manufacturing, in spite of its ever wider application range, is still plagued by issues ranging from accuracy to surface finish. In this study, to address the latter issue, the feasibility of using Copper(II)Oxide powder with a polymer binder deposited through a Fused Deposition Modeling (FDM) 3D printing technique is explored.
Two journals published by Elsevier are retracting a pair of material science papers that appear to share figures.
The papers — in Materials Letters and Optics Communications — discuss photonic crystals, a kind of material used to manipulate light. They share the same first author, Zheng-qi Liu at Jiangxi Normal University and Nanjing University in China, as well as six other authors. Each paper presents one of the duplicated figures as a slightly different material.
One of the duplicated figures is a a picture of a photonic crystal taken with a scanning electron microscope that gives detail at the level of a few micrometers (it looks like a honeycomb, but it’s composed of tiny spheres). It’s Figure 1a in both papers:
An incorrect proof has felled a math paper. There’s not too much to say in a straightforward situation like this one, which we’ve seen before — the result of honest errors, not any malfeasance.
In this paper, we give an affirmative answer to Mbekhta’s conjecture (Mbekhta, 1990) about the pseudo Fredholm operators in Hilbert space. As a consequence, we characterize pseudo Fredholm operators and we prove that the generalized Kato spectrum satisfies the spectral mapping theorem in the Hilbert spaces setting.
The paper — published in the Journal of Mathematical Analysis and Applications — has been cited twice, according to Thomson Scientific’s Web of Knowledge.
An astrophysics journal is retracting a paper on black holes whose first author is a teenager about to earn his PhD, after learning the paper “draws extensively” from a book chapter by the last author.
Many papers are pulled for duplication, but few get a news release from the publisher about it. In a move that we approve of, the editors of The Astrophysical Journal announced the forthcoming retraction on the American Astronomical Society (AAS) website.
The paper‘s first author Song Yoo-Geun who turns 18 this month, and is on track to earn his doctorate next year from the University of Science and Technology in South Korea. According to the news release, the paper borrows heavily from a book chapter published in 2002 by his adviser and co-author, Seok Jae Park at the Korea Astronomy and Space Science Institute.
AAS is handling this very quickly. The paper was published in October, someone alerted the journal to the duplication on November 14, and the announcement of the retraction went up on the AAS website just ten days later.
The editor and author of most of the papers in a special issue of a math journal told us he is withdrawing the entire issue following revelations that he had coordinated the peer-review process.
The articles, published online earlier this year, recently received an expression of concern after the journal realized the guest editor David Gao, at the Federation University Australia, had coordinated the peer-review process. This was a major no-no, since Gao was also an author of 11 of the 13 papers. Mathematics and Mechanics of Solids slated the articles to be peer reviewed again, by reviewers not chosen by Gao.
Gao told us what happened next, from his perspective — he changed his mind about publishing the papers in MMS:
Did you recently log onto your favorite journal’s website and see this? (For anyone who doesn’t want to bother clicking, it’s the video from Rick Astley’s “Never Gonna Give You Up.”) If so, your favorite journal was hijacked.
We’re pleased to present a guest post from Michèle B. Nuijten, a PhD student at Tilburg University who helped develop a program called “statcheck,” which automatically spots statistical mistakes in psychology papers, making it significantly easier to find flaws. Nuijten writes about how such a program came about, and its implications for other fields.
Readers of Retraction Watch know that the literature contains way too many errors – to a great extent, as some research suggests, in my field of psychology. And there is evidence that problem is only likely to get worse.
To reliably investigate these claims, we wanted to study reporting inconsistencies at a large scale. However, extracting statistical results from papers and recalculating the p-values is not only very tedious, it also takes a LOT of time.
So we created a program known as “statcheck” to do the checking for us, by automatically extracting statistics from papers and recalculating p-values. Unfortunately, we recently found that our suspicions were correct: Half of the papers in psychology contain at least one statistical reporting inconsistency, and one in eight papers contain an inconsistency that might have affected the statistical conclusion.
A group of computer scientists has a pair of retractions for duplicating “substantial parts” of other articles written by different authors. Both papers, published in Neural Computing and Applications, are on ways to screen for breast cancer more effectively.
According to the abstract of “An improved data mining technique for classification and detection of breast cancer from mammograms,” computers make the process of identifying cancer in lesions detected by mammograms faster and more accurate:
Although general rules for the differentiation between benign and malignant breast lesion exist, only 15–30% of masses referred for surgical biopsy are actually malignant. Physician experience of detecting breast cancer can be assisted by using some computerized feature extraction and classification algorithms. Computer-aided classification system was used to help in diagnosing abnormalities faster than traditional screening program without the drawback attribute to human factors.
The article has been cited four times, according to Thomson Scientific’s Web of Knowledge. The retraction note reveals where “substantial parts” of the article came from:
This version of Hurricane Isaac — 
