A Generalization of Otsu's Method and Minimum Error Thresholding

We present Generalized Histogram Thresholding (GHT), a simple, fast, and effective technique for histogram-based image thresholding. GHT works by performing approximate maximum a posteriori estimation of a mixture of Gaussians with appropriate priors. We demonstrate that GHT subsumes three classic thresholding techniques as special cases: Otsu's method, Minimum Error Thresholding (MET), and weighted percentile thresholding. GHT thereby enables the continuous interpolation between those three algorithms, which allows thresholding accuracy to be improved significantly. GHT also provides a clarifying interpretation of the common practice of coarsening a histogram's bin width during thresholding. We show that GHT outperforms or matches the performance of all algorithms on a recent challenge for handwritten document image binarization (including deep neural networks trained to produce per-pixel binarizations), and can be implemented in a dozen lines of code or as a trivial modification to Otsu's method or MET.Comment: ECCV 202

“Publish or perish”—presentations at annual national orthopaedic meetings and their correlation with subsequent publication

BACKGROUND: Presentation of research at annual national orthopaedic conferences not only serves as a forum for the dissemination of knowledge but is also often a requirement of orthopaedic training programmes. The expected outcome is publication in a peer-reviewed journal. However, publication rates vary for a variety of reasons. The objective of this study was to determine publication rates of presentations from our local Singapore Orthopaedic Association (SOA) annual scientific meeting (ASM) and some of the potential associated factors. We also compared our findings to equivalent meetings worldwide to assess value of scientific content of various orthopaedic conferences. METHODS: All presentations of six SOA ASMs were entered into a database. Using presentation titles, author names and keywords in PubMed and Google Scholar, we determined how many presentations progressed to publication in a peer-reviewed journal. Various comparisons were made to determine factors that could influence publication rates. A comparison with national orthopaedic meetings of America, United Kingdom, Ireland, Australia, Germany, Turkey and Brazil was also conducted. RESULTS: Excluding the ASMs with less than 4 years of follow-up, the publication rate was 35.8%. Both podium and international presenters were found to have significantly higher publication rates than poster and local presenters, respectively, while basic science and clinical research were found to have equivalent rates. Publication rates from other countries’ national conferences ranged between 26.6% and 58.1%. CONCLUSIONS: We suggest that the quality of a presentation is related to its subsequent publication in a peer-reviewed journal. Our findings support the general consensus that the annual meeting of the American Academy of Orthopaedic Surgeons (AAOS) is the gold standard for the dissemination of orthopaedic knowledge updates and advancements in our specialty. Each national orthopaedic association could determine the ratio of “presentations at ASM” to “publication within five years of presentation” and use this as a measure of their annual conference’s impact on the addition and advancement to the orthopaedic literature. This tool may in turn assist clinicians in determining which meetings to attend

Treatment options for patients with triple-negative breast cancer

Breast cancer is a heterogeneous disease composed of different subtypes, characterized by their different clinicopathological characteristics, prognoses and responses to treatment. In the past decade, significant advances have been made in the treatment of breast cancer sensitive to hormonal treatments, as well as in patients whose malignant cells overexpress or amplify HER2. In contrast, mainly due to the lack of molecular targets, little progress has been made in the treatment of patients with triple-negative breast cancer. Recent improved understanding of the natural history, pathophysiology, and molecular features of triple-negative breast cancers have provided new insights into management and therapeutic strategies for women affected with this entity. Ongoing and planned translational clinical trials are likely to optimize and improve treatment of women with this disease

Reclaiming the child left behind: the case for corporate cultural responsibility

Although a reasonable understanding of corporate social responsibility (CSR) exists, one dimension remains largely ignored. That is, the cultural impacts of corporations, or the bearing, at various levels of their business models, activities, and outcomes on the value systems and enduring beliefs of affected people. We introduce the notion of corporate cultural responsibility (CCR). The way corporations address CCR concerns can be reflected according to three stances: cultural destructiveness, cultural carelessness, and cultural prowess. Taken sequentially, they reflect a growing comprehension and increasingly active consideration of CCR concerns by corporations. In turn, we explicitly address issues related to the complex question of determining the cultural responsibilities of corporate actors; specify key CCR-related conceptualizations; and lay a foundation for discussions, debates, and research efforts centered on CCR concerns and rationales

Estrogen mediated-activation of miR-191/425 cluster modulates tumorigenicity of breast cancer cells depending on estrogen receptor status.

MicroRNAs (miRNAs), single-stranded non-coding RNAs, influence myriad biological processes that can contribute to cancer. Although tumor-suppressive and oncogenic functions have been characterized for some miRNAs, the majority of microRNAs have not been investigated for their ability to promote and modulate tumorigenesis. Here, we established that the miR-191/425 cluster is transcriptionally dependent on the host gene, DALRD3, and that the hormone 17β-estradiol (estrogen or E2) controls expression of both miR-191/425 and DALRD3. MiR-191/425 locus characterization revealed that the recruitment of estrogen receptor α (ERα) to the regulatory region of the miR-191/425-DALRD3 unit resulted in the accumulation of miR-191 and miR-425 and subsequent decrease in DALRD3 expression levels. We demonstrated that miR-191 protects ERα positive breast cancer cells from hormone starvation-induced apoptosis through the suppression of tumor-suppressor EGR1. Furthermore, enforced expression of the miR-191/425 cluster in aggressive breast cancer cells altered global gene expression profiles and enabled us to identify important tumor promoting genes, including SATB1, CCND2, and FSCN1, as targets of miR-191 and miR-425. Finally, in vitro and in vivo experiments demonstrated that miR-191 and miR-425 reduced proliferation, impaired tumorigenesis and metastasis, and increased expression of epithelial markers in aggressive breast cancer cells. Our data provide compelling evidence for the transcriptional regulation of the miR-191/425 cluster and for its context-specific biological determinants in breast cancers. Importantly, we demonstrated that the miR-191/425 cluster, by reducing the expression of an extensive network of genes, has a fundamental impact on cancer initiation and progression of breast cancer cells

Histogram partitioning algorithms for adaptive and autonomous threshold estimation in cognitive radio–based industrial wireless sensor networks

Modern energy detectors typically use adaptive threshold estimation algorithms to improve signal detection in cognitive radio–based industrial wireless sensor networks (CR‐IWSNs). However, a number of adaptive threshold estimation algorithms often perform poorly under noise uncertainty conditions since they are typically unable to auto‐adapt their parameter values per changing spectra conditions. Consequently, in this paper, we have developed two new algorithms to accurately and autonomously estimate threshold values in CR‐IWSNs under dynamic spectra conditions. The first algorithm is a parametric‐based technique termed the histogram partitioning algorithm, whereas the second algorithm is a fully autonomous variant termed the mean‐based histogram partitioning algorithm. We have evaluated and compared both algorithms with some well‐known methods under different CR sensing conditions. Our findings indicate that both algorithms maintained over 90% probability of detection in both narrow and wideband sensing conditions and less than 10% probability of false alarm under noise‐only conditions. Both algorithms are quick and highly scalable with a time complexity of O(V), where V is the total number of input samples. The simplicity, effectiveness, and viability of both algorithms make them typically suited for use in CR‐IWSN applications.http://wileyonlinelibrary.com/journal/ett2020-10-01hj2019Electrical, Electronic and Computer Engineerin