| 1. |
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The Seventeenth Data Release of the Sloan Digital Sky Surveys : Complete Release of MaNGA, MaStar, and APOGEE-2 Data
- 2022
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Ingår i: Astrophysical Journal Supplement Series. - : Institute of Physics (IOP). - 0067-0049 .- 1538-4365. ; 259:2
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Tidskriftsartikel (refereegranskat)abstract
- This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.
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| 2. |
- 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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| 3. |
- 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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| 4. |
- Araújo, Mário J, et al.
(författare)
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Proteomics reveals multiple effects of titanium dioxide and silver nanoparticles in the metabolism of turbot, Scophthalmus maximus
- 2022
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Ingår i: Chemosphere. - : Pergamon-Elsevier Science Ltd. - 0045-6535 .- 1879-1298. ; 308
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Tidskriftsartikel (refereegranskat)abstract
- Titanium dioxide (TiO2) and silver (Ag) NPs are among the most used engineered inorganic nanoparticles (NPs); however, their potential effects to marine demersal fish species, are not fully understood. Therefore, this study aimed to assess the proteomic alterations induced by sub-lethal concentrations citrate-coated 25 nm ("P25") TiO2 or polyvinylpyrrolidone (PVP) coated 15 nm Ag NPs to turbot, Scophthalmus maximus. Juvenile fish were exposed to the NPs through daily feeding for 14 days. The tested concentrations were 0, 0.75 or 1.5 mg of each NPs per kg of fish per day. The determination of NPs, Titanium and Ag levels (sp-ICP-MS/ICP-MS) and histological alterations (Transmission Electron Microscopy) supported proteomic analysis performed in the liver and kidney. Proteomic sample preparation procedure (SP3) was followed by LC-MS/MS. Label-free MS quantification methods were employed to assess differences in protein expression. Functional analysis was performed using STRING web-tool. KEGG Gene Ontology suggested terms were discussed and potential biomarkers of exposure were proposed. Overall, data shows that liver accumulated more elements than kidney, presented more histological alterations (lipid droplets counts and size) and proteomic alterations. The Differentially Expressed Proteins (DEPs) were higher in Ag NPs trial. The functional analysis revealed that both NPs caused enrichment of proteins related to generic processes (metabolic pathways). Ag NPs also affected protein synthesis and nucleic acid transcription, among other processes. Proteins related to thyroid hormone transport (Serpina7) and calcium ion binding (FAT2) were suggested as biomarkers of TiO2 NPs in liver. For Ag NPs, in kidney (and at a lower degree in liver) proteins related with metabolic activity, metabolism of exogenous substances and oxidative stress (e.g.: NADH dehydrogenase and Cytochrome P450) were suggested as potential biomarkers. Data suggests adverse effects in turbot after medium/long-term exposures and the need for additional studies to validate specific biological applications of these NPs.
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| 5. |
- Barrera Diaz, Carlos Alberto, 1987-, et al.
(författare)
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A Study of Discrete Event Simulation Project Data and Provenance Information Management in an Automotive Manufacturing Plant
- 2017
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Ingår i: Proceedings of the 2017 Winter Simulation Conference. - : IEEE. - 9781538634288 - 9781538634295 - 9781538634301 ; , s. 4012-4023
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Konferensbidrag (refereegranskat)abstract
- Discrete Event Simulation (DES) project data management is a complex and important engineering activity which impacts on an organization’s efficiency. This efficiency could be decreased by the lack of provenance information or the unreliability of existing information regarding previous simulation projects, all of which complicates the reusability of the existing data. This study presents an analysis of the management of simulation projects and their provenance data, according to the different types of scenarios usually found at a manufacturing plant. A survey based on simulation projects at an automotive manufacturing plant was conducted, in order to categorize the information regarding the studied projects, map the available provenance data and standardize its management. This study also introduces an approach that demonstrates how a structured framework based on the specific data involved in the different types of scenarios could allow an improvement of the management of DES projects.
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| 6. |
- Barrera Diaz, Carlos Alberto, 1987-, et al.
(författare)
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An Enhanced Simulation-Based Multi-Objective Optimization Approach with Knowledge Discovery for Reconfigurable Manufacturing Systems
- 2023
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Ingår i: Mathematics. - : MDPI. - 2227-7390. ; 11:6
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Tidskriftsartikel (refereegranskat)abstract
- In today’s uncertain and competitive market, where manufacturing enterprises are subjected to increasingly shortened product lifecycles and frequent volume changes, reconfigurable manufacturing system (RMS) applications play significant roles in the success of the manufacturing industry. Despite the advantages offered by RMSs, achieving high efficiency constitutes a challenging task for stakeholders and decision makers when they face the trade-off decisions inherent in these complex systems. This study addresses work task and resource allocations to workstations together with buffer capacity allocation in an RMS. The aim is to simultaneously maximize throughput and to minimize total buffer capacity under fluctuating production volumes and capacity changes while considering the stochastic behavior of the system. An enhanced simulation-based multi-objective optimization (SMO) approach with customized simulation and optimization components is proposed to address the abovementioned challenges. Apart from presenting the optimal solutions subject to volume and capacity changes, the proposed approach supports decision makers with knowledge discovery to further understand RMS design. In particular, this study presents a customized SMO approach combined with a novel flexible pattern mining method for optimizing an RMS and conducts post-optimal analyses. To this extent, this study demonstrates the benefits of applying SMO and knowledge discovery methods for fast decision support and production planning of an RMS.
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| 7. |
- Barrera Diaz, Carlos Alberto, 1987-, et al.
(författare)
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Availability Analysis of Reconfigurable Manufacturing System Using Simulation-Based Multi-Objective Optimization
- 2022
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Ingår i: SPS2022. - Amsterdam; Berlin; Washington, DC : IOS Press. - 9781643682686 - 9781643682693 ; , s. 369-379
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Konferensbidrag (refereegranskat)abstract
- Nowadays, manufacturing companies face an increasing number of challenges that can cause unpredictable market changes. These challenges are derived from a fiercely competitive market. These challenges create unforeseen variations and uncertainties, including new regional requirements or regulations, new technologies and materials, new market segments, increasing demand for new product features, etc. To cope with the challenges above, companies must reinvent themselves and design manufacturing systems that seek to produce quality products while responding to the changes faced. These capabilities are encompassed in Reconfigurable Manufacturing Systems (RMS), capable of dealing with uncertainties quickly and economically. The availability of RMS is a crucial factor in establishing the production capacity of a system that considers all events that could interrupt the planned production. The impact of the availability in RMS is influenced by the configuration of the systems, including the number of resources used. This paper presents a case study in which a simulation-based multi-objective optimization (SMO) method is used to find machines’ optimal task allocation and assignment to workstations under different scenarios of availability. It has been shown that considering the availability of the machines affects the optimal configuration, including the number of resources needed, such as machines and buffers. This study demonstrates the importance of the availability consideration during the design of RMS.
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| 8. |
- Barrera Diaz, Carlos Alberto, 1987-, et al.
(författare)
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Discrete Event Simulation Output Data-Handling System in an Automotive Manufacturing Plant
- 2018
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Ingår i: Procedia Manufacturing. - : Elsevier. - 2351-9789. ; 25, s. 23-30
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Tidskriftsartikel (refereegranskat)abstract
- Discrete Event Simulation is a comprehensive tool for the analysis and design of manufacturing systems. Over the years, considerable efforts to improve simulation processes have been made. One step in these efforts is the standardisation of the output data through the development of an appropriate system which presents the results in a standardised way. This paper presents the results of a survey based on simulation projects undertaken in the automotive industry. In addition, it presents the implementation of an automated output data-handling system which aims to simplify the project’s documentation task for the simulation engineers and make the results more accessible for other stakeholders.
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| 9. |
- Barrera Diaz, Carlos Alberto, 1987-, et al.
(författare)
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Enabling Knowledge Discovery from Simulation-Based Multi-Objective Optimization in Reconfigurable Manufacturing Systems
- 2022
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Ingår i: Proceedings of the 2022 Winter Simulation Conference. - : IEEE. - 9781665476614 - 9781665476621 ; , s. 1794-1805
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Konferensbidrag (refereegranskat)abstract
- Due to the nature of today's manufacturing industry, where enterprises are subjected to frequent changes and volatile markets, reconfigurable manufacturing systems (RMS) are crucial when addressing ramp-up and ramp-down scenarios derived from, among other challenges, increasingly shortened product lifecycles. Applying simulation-based optimization techniques to their designs under different production volume scenarios has become valuable when RMS becomes more complex. Apart from proposing the optimal solutions subject to various production volume changes, decision-makers can extract propositional knowledge to better understand the RMS design and support their decision-making through a knowledge discovery method by combining simulation-based optimization and data mining techniques. In particular, this study applies a novel flexible pattern mining algorithm to conduct post-optimality analysis on multi-dimensional, multi-objective optimization datasets from an industrial-inspired application to discover the rules regarding how the tasks are assigned to the workstations constitute reasonable solutions for scalable RMS.
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| 10. |
- Barrera Diaz, Carlos Alberto, 1987-, et al.
(författare)
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Optimizing reconfigurable manufacturing systems : A Simulation-based Multi-objective Optimization approach
- 2021
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Ingår i: Procedia CIRP. - : Elsevier. - 2212-8271. ; 104, s. 1837-1842
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Tidskriftsartikel (refereegranskat)abstract
- Application of reconfigurable manufacturing systems (RMS) plays a significant role in manufacturing companies’ success in the current fiercely competitive market. Despite the RMS’s advantages, designing these systems to achieve a high-efficiency level is a complex and challenging task that requires the use of optimization techniques. This study proposes a simulation-based optimization approach for optimal allocation of work tasks and resources (i.e., machines) to workstations. Three conflictive objectives, namely maximizing the throughput, minimizing the buffers’ capacity, and minimizing the number of machines, are optimized simultaneously while considering the system’s stochastic behavior to achieve the desired system’s configuration.
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