| 1. |
- Abolfathi, Bela, et al.
(författare)
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The Fourteenth Data Release of the Sloan Digital Sky Survey : First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment
- 2018
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Ingår i: Astrophysical Journal Supplement Series. - : IOP Publishing Ltd. - 0067-0049 .- 1538-4365. ; 235:2
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Tidskriftsartikel (refereegranskat)abstract
- The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014-2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V.
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| 2. |
- Blanton, Michael R., et al.
(författare)
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Sloan Digital Sky Survey IV : Mapping the Milky Way, Nearby Galaxies, and the Distant Universe
- 2017
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Ingår i: Astronomical Journal. - : IOP Publishing Ltd. - 0004-6256 .- 1538-3881. ; 154:1
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Tidskriftsartikel (refereegranskat)abstract
- We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and. high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z similar to 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z similar to 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs. and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the. Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July.
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| 3. |
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| 4. |
- Guo, Jinan, et al.
(författare)
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A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis
- 2024
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Ingår i: Prostate Cancer and Prostatic Diseases. - : Nature Publishing Group. - 1365-7852 .- 1476-5608.
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Tidskriftsartikel (refereegranskat)abstract
- Background: Prostate cancer patients with pelvic lymph node metastasis (PLNM) have poor prognosis. Based on EAU guidelines, patients with >5% risk of PLNM by nomograms often receive pelvic lymph node dissection (PLND) during prostatectomy. However, nomograms have limited accuracy, so large numbers of false positive patients receive unnecessary surgery with potentially serious side effects. It is important to accurately identify PLNM, yet current tests, including imaging tools are inaccurate. Therefore, we intended to develop a gene expression-based algorithm for detecting PLNM. Methods: An advanced random forest machine learning algorithm screening was conducted to develop a classifier for identifying PLNM using urine samples collected from a multi-center retrospective cohort (n = 413) as training set and validated in an independent multi-center prospective cohort (n = 243). Univariate and multivariate discriminant analyses were performed to measure the ability of the algorithm classifier to detect PLNM and compare it with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram score. Results: An algorithm named 25 G PLNM-Score was developed and found to accurately distinguish PLNM and non-PLNM with AUC of 0.93 (95% CI: 0.85-1.01) and 0.93 (95% CI: 0.87-0.99) in the retrospective and prospective urine cohorts respectively. Kaplan-Meier plots showed large and significant difference in biochemical recurrence-free survival and distant metastasis-free survival in the patients stratified by the 25 G PLNM-Score (log rank P < 0.001 and P < 0.0001, respectively). It spared 96% and 80% of unnecessary PLND with only 0.51% and 1% of PLNM missing in the retrospective and prospective cohorts respectively. In contrast, the MSKCC score only spared 15% of PLND with 0% of PLNM missing. Conclusions: The novel 25 G PLNM-Score is the first highly accurate and non-invasive machine learning algorithm-based urine test to identify PLNM before PLND, with potential clinical benefits of avoiding unnecessary PLND and improving treatment decision-making.
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| 5. |
- Guo, Jinan, et al.
(författare)
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Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients
- 2021
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Ingår i: Frontiers in Medicine. - : Frontiers Media S.A.. - 2296-858X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available.Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups.Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892-0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935-0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1-3 cancer subgroups.Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.
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| 6. |
- Huang, Haiping, et al.
(författare)
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An Efficient Signature Scheme Based on Mobile Edge Computing in the NDN-IoT Environment
- 2021
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Ingår i: IEEE Transactions on Computational Social Systems. - : IEEE. - 2329-924X. ; 8:5, s. 1108-1120
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Tidskriftsartikel (refereegranskat)abstract
- Named data networking (NDN) is an emerging information-centric networking paradigm, in which the Internet of Things (IoT) achieves excellent scalability. Recent literature proposes the concept of NDN-IoT, which maximizes the expansion of IoT applications by deploying NDN in the IoT. In the NDN, the security is built into the network by embedding a public signature in each data package to verify the authenticity and integrity of the content. However, signature schemes in the NDN-IoT environment are facing several challenges, such as signing security challenge for resource-constrained IoT end devices (EDs) and verification efficiency challenge for NDN routers. This article mainly studies the data package authentication scheme in the package-level security mechanism. Based on mobile edge computing (MEC), an efficient certificateless group signature scheme featured with anonymity, unforgeability, traceability, and key escrow resilience is proposed. The regional and edge architecture is utilized to solve the device management problem of IoT, reducing the risks of content pollution attacks from the data source. By offloading signature pressure to MEC servers, the contradiction between heavy overhead and shortage of ED resources is avoided. Moreover, the verification efficiency in NDN router is much improved via batch verification in the proposed scheme. Both security analysis and experimental simulations show that the proposed MEC-based certificateless group signature scheme is provably secure and practical.
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| 7. |
- Johnson, Heather, et al.
(författare)
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Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up
- 2020
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Ingår i: BMC Medicine. - : BioMed Central. - 1741-7015. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. Methods: Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRTPCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. Results: The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963–0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929–0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956–0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980–0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947–0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. Conclusions: The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.
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| 8. |
- Lederman, Judith S., et al.
(författare)
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Completing the progression establishing an international baseline of primary, middle and secondary students’ views of scientific inquiry
- 2023
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Ingår i: International Journal of Science Education. - : Routledge. - 0950-0693 .- 1464-5289.
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge of scientific inquiry (SI) is considered essential to the development of an individual's Scientific Literacy (SL) and therefore, SI is included in many international science education reform documents. Two previous large scale international studies assessed the SI understandings of students entering middle school and secondary students at the end of their formal K-12 science education. The purpose of this international project was to use the VASI-E to collect data on what primary level students have learned about SI in their first few years of school. This study adds to previous research to bridge the landscape of SI understandings now with representation from primary, middle and high school samples. A total of 4,238 students from 35 countries/regions spanning six continents participated in the study. The results show that globally, primary students are not adequately informed about SI for their age group. However, when compared with the students in the previous international studies (grades seven and 12), the primary students' understandings were surprisingly closer to the levels of understanding of SI of the secondary school students than those in the seventh grade study.
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| 9. |
- Liu, Yongshuang, et al.
(författare)
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Classification and recognition of encrypted EEG data based on neural network
- 2020
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Ingår i: Journal of Information Security and Applications. - : Elsevier. - 2214-2134 .- 2214-2126. ; 54
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Tidskriftsartikel (refereegranskat)abstract
- With the rapid development of Machine Learning technology applied in electroencephalography (EEG) signals, Brain-Computer Interface (BCI) has emerged as a novel and convenient human-computer interaction for smart home, intelligent medical and other Internet of Things (IoT) scenarios. However, security issues such as sensitive information disclosure and unauthorized operations have not received sufficient concerns. There are still some defects with the existing solutions to encrypted EEG data such as low accuracy, high time complexity or slow processing speed. For this reason, a classification and recognition method of encrypted EEG data based on neural network is proposed, which adopts Paillier encryption algorithm to encrypt EEG data and meanwhile resolves the problem of floating point operations. In addition, it improves traditional feed-forward neural network (FNN) by using the approximate function instead of activation function and realizes multi-classification of encrypted EEG data. Extensive experiments are conducted to explore the effect of several metrics (such as the hidden neuron size and the learning rate updated by improved simulated annealing algorithm) on the recognition results. Followed by security and time cost analysis, the proposed model and approach are validated and evaluated on public EEG datasets provided by PhysioNet, BCI Competition IV and EPILEPSIAE. The experimental results show that our proposal has the satisfactory accuracy, efficiency and feasibility compared with other solutions. (C) 2020 Elsevier Ltd. All rights reserved.
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| 10. |
- Wang, Kai, et al.
(författare)
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EXTENDED RELATIVISTIC CONFIGURATION INTERACTION AND MANY-BODY PERTURBATION CALCULATIONS OF SPECTROSCOPIC DATA FOR THE N 6 CONFIGURATIONS IN Ne-LIKE IONS BETWEEN Cr XV AND Kr XXVII
- 2016
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Ingår i: Astrophysical Journal Supplement Series. - : American Astronomical Society. - 0067-0049 .- 1538-4365. ; 226:2
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Tidskriftsartikel (refereegranskat)abstract
- Level energies, wavelengths, electric dipole, magnetic dipole, electric quadrupole, and magnetic quadrupole transition rates, oscillator strengths, and line strengths from combined relativistic con guration interaction and many-body perturbation calculations are reported for the 201 ne-structure states of the 2s22p6, 2s22p53l, 2s2p63l, 2s22p54l, 2s2p64l, 2s22p55l, and 2s22p56l con gurations in all Ne-like ions between Cr XV and Kr XXVII. Calculated level energies and transition data are compared with experiments from the National Institute of Standards and Technology (NIST) and CHIANTI databases, and other recent benchmark calculations. The mean energy difference with the NIST experiments is only 0.05%. The present calculations signi cantly increase the amount of accurate spectroscopic data for the n > 3 states in a number of Ne-like ions of astrophysical interest. A complete data set should be helpful for analyzing new observations from solar and other astrophysical sources, and is also likely to be useful for modeling and diagnosing a variety of plasmas, including astronomical and fusion plasma.
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