6,935 research outputs found
Manganese abundances in mercury-manganese stars
We use exact curve-of-growth analysis and spectral synthesis to deduce the abundance of Mn from high signal-to-noise ratio visible-region echelle spectra of selected Mn i and MnII lines in 24 HgMn stars. The results are compared with the Mn abundances derived from UV resonance lines by Smith & Dworetsky. We find excellent agreement for several unblended Mn lines and confirm the temperature dependence of the Mn abundance found by Smith & Dworetsky. The MnII lines at λλ 4206 and 4326 are much stronger than one would predict from the mean Mn abundances. The lack of agreement is greatest for stars with the strongest MnII lines. Using ad hoc multicomponent fits to the profiles of sharp-lined stars, we show that most of the discrepancies can be explained by hyperfine structure that desaturates the lines, with full widths of the order of 0.06--0.09 Å
Options for managing human threats to high seas biodiversity
Areas beyond national jurisdiction (ABNJ) constitute 61% of the world's oceans and are collectively managed by countries under the United Nations Convention on the Law of the Sea (UNCLOS). Growing concern regarding the deteriorating state of the oceans and ineffective management of ABNJ has resulted in negotiations to develop an international legally binding instrument (ILBI) for the conservation and sustainable use of biodiversity beyond national jurisdiction under UNCLOS. To inform these negotiations, we identified existing and emerging human activities and influences that affect ABNJ and evaluated management options available to mitigate the most pervasive, with highest potential for impact and probability of emergence. The highest-ranking activities and influences that affect ABNJ were fishing/hunting, maritime shipping, climate change and its associated effects, land-based pollution and mineral exploitation. Management options are diverse and available through a variety of actors, although their actions are not always effective. Area-based management tools (ABMTs), including marine protected areas (MPAs), were the only consistently effective option to mitigate impacts across high-ranked activities and influences. However, addressing land-based pollution will require national action to prevent this at its source, and MPAs offer only a partial solution for climate change. A new ABNJ ILBI could help unify management options and actors to conserve marine biodiversity and ensure sustainable use. Incorporating a mechanism to establish effective ABMTs into the ILBI will help deliver multiple objectives based on the ecosystem approach
Quantum Common Causes and Quantum Causal Models
Reichenbach’s principle asserts that if two observed variables are found to be correlated, then there should be a causal explanation of these correlations. Furthermore, if the explanation is in terms of a common cause, then the conditional probability distribution over the variables given the complete common cause should factorize. The principle is generalized by the formalism of causal models, in which the causal relationships among variables constrain the form of their joint probability distribution. In the quantum case, however, the observed correlations in Bell experiments cannot be explained in the manner Reichenbach’s principle would seem to demand. Motivated by this, we introduce a quantum counterpart to the principle. We demonstrate that under the assumption that quantum dynamics is fundamentally unitary, if a quantum channel with input
A
and outputs
B
and
C
is compatible with
A
being a complete common cause of
B
and
C
, then it must factorize in a particular way. Finally, we show how to generalize our quantum version of Reichenbach’s principle to a formalism for quantum causal models and provide examples of how the formalism works
The role of mentorship in protege performance
The role of mentorship on protege performance is a matter of importance to
academic, business, and governmental organizations. While the benefits of
mentorship for proteges, mentors and their organizations are apparent, the
extent to which proteges mimic their mentors' career choices and acquire their
mentorship skills is unclear. Here, we investigate one aspect of mentor
emulation by studying mentorship fecundity---the number of proteges a mentor
trains---with data from the Mathematics Genealogy Project, which tracks the
mentorship record of thousands of mathematicians over several centuries. We
demonstrate that fecundity among academic mathematicians is correlated with
other measures of academic success. We also find that the average fecundity of
mentors remains stable over 60 years of recorded mentorship. We further uncover
three significant correlations in mentorship fecundity. First, mentors with
small mentorship fecundity train proteges that go on to have a 37% larger than
expected mentorship fecundity. Second, in the first third of their career,
mentors with large fecundity train proteges that go on to have a 29% larger
than expected fecundity. Finally, in the last third of their career, mentors
with large fecundity train proteges that go on to have a 31% smaller than
expected fecundity.Comment: 23 pages double-spaced, 4 figure
Prostate Imaging Quality (PI-QUAL): A New Quality Control Scoring System for Multiparametric Magnetic Resonance Imaging of the Prostate from the PRECISION trial
The PRECISION trial was a multicentre randomised study that demonstrated that multiparametric magnetic resonance imaging (mpMRI)-targeted biopsy is superior to standard transrectal ultrasound-guided biopsy for the detection of prostate cancer. The outcomes of studies reporting mpMRI-targeted biopsies are dependent on the quality of the mpMRI but there are currently no scoring systems available for evaluating this. We introduced a novel scoring system, the Prostate Imaging Quality (PI-QUAL) score, to assess the quality of scans in the PRECISION trial. PI-QUAL is a score on a Likert scale from 1 to 5, where 1 means that no mpMRI sequences are of diagnostic quality and 5 implies that each sequence is independently of optimal diagnostic quality. Fifty-eight out of 252 (23%) mpMRI scans chosen at random from each of the 22 centres in this trial were evaluated by two experienced radiologists from the coordinating trial centre, in consensus, blinded to pathology results. Overall, the mpMRI quality in the centres participating in PRECISION was good. MpMRI quality was of sufficient diagnostic quality (PI-QUAL ≥3) for 55 scans (95%) and of good or optimal diagnostic quality (PI-QUAL ≥4) for 35 scans (60%). Fifty-five out of 58 (95%) scans were of diagnostic quality for T2WI, followed by DWI (46/58 scans; 79%), and DCE (38/58 scans; 66%). Further validation of this scoring system is warranted. PATIENT SUMMARY: In this study we developed a scoring system (PI-QUAL) to assess the quality of multiparametric magnetic resonance imaging (mpMRI) in prostate cancer detection. We used scans from 22 centres that participated in the PRECISION trial. Although there was room for improvement in images that used intravenous contrast, we found that mpMRI in the PRECISION trial was of sufficient diagnostic quality (PI-QUAL score ≥3) for 95% of the scans
Multiparametric prostate MRI quality assessment using a semi-automated PI-QUAL software program
The technical requirements for the acquisition of multiparametric magnetic resonance imaging (mpMRI) of the prostate have been clearly outlined in the Prostate Imaging Reporting and Data System (PI-RADS) guidelines, but there is still huge variability in image quality among centres across the world. It has been difficult to quantify what constitutes a good-quality image, and a first attempt to address this matter has been the publication of the Prostate Imaging Quality (PI-QUAL) score and its dedicated scoring sheet. This score includes the assessment of technical parameters that can be obtained from the DICOM files along with a visual evaluation of certain features on prostate MRI (e.g., anatomical structures). We retrospectively analysed the image quality of 10 scans from different vendors and magnets using a semiautomated dedicated PI-QUAL software program and compared the time needed for assessing image quality using two methods (semiautomated assessment versus manual filling of the scoring sheet). This semiautomated software is able to assess the technical parameters automatically, but the visual assessment is still performed by the radiologist. There was a significant reduction in the reporting time of prostate mpMRI quality according to PI-QUAL using the dedicated software program compared to manual filling (5'54″ versus 7'59″; p = 0.005). A semiautomated PI-QUAL software program allows the radiologist to assess the technical details related to the image quality of prostate mpMRI in a quick and reliable manner, allowing clinicians to have more confidence that the quality of mpMRI of the prostate is sufficient to determine patient care
Prostate MRI quality: a critical review of the last 5 years and the role of the PI-QUAL score
There is increasing interest in the use of multiparametric magnetic resonance imaging (mpMRI) in the prostate cancer pathway. The European Association of Urology (EAU) and the British Association of Urological Surgeons (BAUS) now advise mpMRI prior to biopsy, and the Prostate Imaging Reporting and Data System (PI-RADS) recommendations set out the minimal technical requirements for the acquisition of mpMRI of the prostate.The widespread and swift adoption of this technique has led to variability in image quality. Suboptimal image acquisition reduces the sensitivity and specificity of mpMRI for the detection and staging of clinically significant prostate cancer.This critical review outlines the studies aimed at improving prostate MR quality that have been published over the last 5 years. These span from the use of specific MR sequences, magnets and coils to patient preparation. The rates of adherence of prostate mpMRI to technical standards in different cohorts across the world are also discussed.Finally, we discuss the first standardised scoring system (i.e., Prostate Imaging Quality, PI-QUAL) that has been created to evaluate image quality, although further iterations of this score are expected in the future
Understanding PI-QUAL for prostate MRI quality: a practical primer for radiologists
Prostate magnetic resonance imaging (MRI) of high diagnostic quality is a key determinant for either detection or exclusion of prostate cancer. Adequate high spatial resolution on T2-weighted imaging, good diffusion-weighted imaging and dynamic contrast-enhanced sequences of high signal-to-noise ratio are the prerequisite for a high-quality MRI study of the prostate. The Prostate Imaging Quality (PI-QUAL) score was created to assess the diagnostic quality of a scan against a set of objective criteria as per Prostate Imaging-Reporting and Data System recommendations, together with criteria obtained from the image. The PI-QUAL score is a 1-to-5 scale where a score of 1 indicates that all MR sequences (T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced sequences) are below the minimum standard of diagnostic quality, a score of 3 means that the scan is of sufficient diagnostic quality, and a score of 5 implies that all three sequences are of optimal diagnostic quality. The purpose of this educational review is to provide a practical guide to assess the quality of prostate MRI using PI-QUAL and to familiarise the radiologist and all those involved in prostate MRI with this scoring system. A variety of images are also presented to demonstrate the difference between suboptimal and good prostate MR scans
Sequential prostate MRI reporting in men on active surveillance: initial experience of a dedicated PRECISE software program
BACKGROUND AND OBJECTIVES: There is interest in using sequential multiparametric magnetic resonance imaging (mpMRI) to assess men on active surveillance (AS) for prostate cancer. The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) recommendations propose standardised reporting mpMRI data for these men. This includes accurate size measurements of lesions over time, but such approach is time consuming for the radiologist and there is a strong need of dedicated tools to report serial scans in a systematic manner. We present the results from an initial validation cohort using dedicated PRECISE reporting software to allow automated comparison between sequential scans on AS. MATERIALS AND METHODS: We retrospectively analysed baseline and follow-up scans of 20 men randomised to 6 months of daily dutasteride (n = 10) or placebo (n = 10) from the MAPPED trial. Men underwent 3T mpMRI at baseline and after 6 months, and a dedicated radiologist reported the scans using both a widespread commercially-available platform (Osirix®) and a semi-automated dedicated PRECISE reporting tool (MIM®). Tumour volume by planimetry in all sequences and conspicuity on diffusion-weighted imaging were assessed. Reporting time was recorded, and we used the Wilcoxon test for statistical analysis. RESULTS: Median tumour volumes and conspicuity were similar using both approaches. The reporting time of the follow-up scan was quicker using the PRECISE reporting workflow both in the whole population (12'33″ vs 10'52″; p = 0.005) and in the dutasteride arm (15'50″ vs 12'59″; p = 0.01). A structured report including clinical and imaging data was generated according to the PRECISE recommendations and a comparison table between lesion characteristics at baseline and follow-up scans was also included. CONCLUSION: We conclude that a dedicated PRECISE reporting tool for sequential scans in men on AS results in a significant reduction in the reporting time and allows the radiologist to easily compare scans over time. This tool will help with our understanding of the natural history of mpMRI changes during AS
Follow-Up of Men With PI-RADS 4 or 5 Abnormality on Prostate MRI and Non-Malignant Pathologic Findings on Initial Targeted Prostate Biopsy
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