Prospects for the Future: A Framework and Discussion of Directions for the Next Generation of International Large-Scale Assessments

2012 ◽  
pp. 149-160 ◽  
Author(s):  
Henry Braun
Keyword(s):  
Large Scale ◽  
Next Generation ◽  
The Future ◽  
Large Scale Assessments

scholarly journals The GRAPE project: Current Status and Future Outlook

2003 ◽  
Vol 208 ◽  
pp. 13-24
Author(s):  
Junichiro Makino
Keyword(s):  
Present Status ◽  
Large Scale ◽  
Parallel Architecture ◽  
Current Status ◽  
Next Generation ◽  
Future Outlook ◽  
The Future ◽  
Peak Speed

I'll briefly overview the present status and the future of the GRAPE project. GRAPE (GRAvity PiPE) project is a project to design, develop and use special-purpose computers for astrophysical N-body simulations to do large-scale N-body simulations. Our first machine, GRAPE-1 was completed in 1989 and offered the speed of 240 Mflops. Since then, we have continued to develop newer and faster machines, and the newest machine, the GRAPE-6, has achieved the peak speed of 32 Tflops. I'll briefly discuss GRAPE-6 and its parallel architecture, and then discuss the possible form of GRAPE-7, the next generation machines.

Next-Generation Sequencing: An Emerging Tool for Drug Designing

2019 ◽  
Vol 25 (31) ◽  
pp. 3350-3357 ◽  
Author(s):  
Pooja Tripathi ◽  
Jyotsna Singh ◽  
Jonathan A. Lal ◽  
Vijay Tripathi
Keyword(s):  
Next Generation Sequencing ◽  
High Throughput ◽  
Large Scale ◽  
Massively Parallel Sequencing ◽  
Genomic Research ◽  
Biological Research ◽  
Next Generation ◽  
Human Welfare ◽  
Drug Designing ◽  
Generation Sequencing

Background: With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production. Method: In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques. Discussions: The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day. Conclusion: Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.

scholarly journals Using Participatory Spatial Tools to Unravel Community Perceptions of Land-Use Dynamics in a Mine-Expanding Landscape in Ghana

2021 ◽  
Author(s):  
Jane J. Aggrey ◽  
Mirjam A. F. Ros-Tonen ◽  
Kwabena O. Asubonteng
Keyword(s):  
Land Use ◽  
Adverse Effects ◽  
Large Scale ◽  
Sub Saharan Africa ◽  
Small Scale ◽  
Eastern Region ◽  
Food Crop ◽  
Mosaic Landscape ◽  
Rural Landscapes ◽  
The Future

AbstractArtisanal and small-scale mining (ASM) in sub-Saharan Africa creates considerable dynamics in rural landscapes. Many studies addressed the adverse effects of mining, but few studies use participatory spatial tools to assess the effects on land use. Hence, this paper takes an actor perspective to analyze how communities in a mixed farming-mining area in Ghana’s Eastern Region perceive the spatial dynamics of ASM and its effects on land for farming and food production from past (1986) to present (2018) and toward the future (2035). Participatory maps show how participants visualize the transformation of food-crop areas into small- and large-scale mining, tree crops, and settlement in all the communities between 1986 and 2018 and foresee these trends to continue in the future (2035). Participants also observe how a mosaic landscape shifts toward a segregated landscape, with simultaneous fragmentation of their farming land due to ASM. Further segregation is expected in the future, with attribution to the expansion of settlements being an unexpected outcome. Although participants expect adverse effects on the future availability of food-crop land, no firm conclusions can be drawn about the anticipated effect on food availability. The paper argues that, if responsibly applied and used to reveal community perspectives and concerns about landscape dynamics, participatory mapping can help raise awareness of the need for collective action and contribute to more inclusive landscape governance. These findings contribute to debates on the operationalization of integrated and inclusive landscape approaches and governance, particularly in areas with pervasive impacts of ASM.

scholarly journals Why ability point estimates can be pointless: a primer on using skill measures from large-scale assessments in secondary analyses

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Clemens M. Lechner ◽  
Nivedita Bhaktha ◽  
Katharina Groskurth ◽  
Matthias Bluemke
Keyword(s):  
Measurement Error ◽  
Statistical Models ◽  
Test Scores ◽  
Large Scale ◽  
Equation Modeling ◽  
Model Parameters ◽  
Advantages And Disadvantages ◽  
Point Estimates ◽  
Secondary Analyses ◽  
Large Scale Assessments

AbstractMeasures of cognitive or socio-emotional skills from large-scale assessments surveys (LSAS) are often based on advanced statistical models and scoring techniques unfamiliar to applied researchers. Consequently, applied researchers working with data from LSAS may be uncertain about the assumptions and computational details of these statistical models and scoring techniques and about how to best incorporate the resulting skill measures in secondary analyses. The present paper is intended as a primer for applied researchers. After a brief introduction to the key properties of skill assessments, we give an overview over the three principal methods with which secondary analysts can incorporate skill measures from LSAS in their analyses: (1) as test scores (i.e., point estimates of individual ability), (2) through structural equation modeling (SEM), and (3) in the form of plausible values (PVs). We discuss the advantages and disadvantages of each method based on three criteria: fallibility (i.e., control for measurement error and unbiasedness), usability (i.e., ease of use in secondary analyses), and immutability (i.e., consistency of test scores, PVs, or measurement model parameters across different analyses and analysts). We show that although none of the methods are optimal under all criteria, methods that result in a single point estimate of each respondent’s ability (i.e., all types of “test scores”) are rarely optimal for research purposes. Instead, approaches that avoid or correct for measurement error—especially PV methodology—stand out as the method of choice. We conclude with practical recommendations for secondary analysts and data-producing organizations.

Technical perspective: The future of large-scale embedded sensing

2020 ◽  
Vol 63 (12) ◽  
pp. 91-91
Author(s):  
Joseph A. Paradiso
Keyword(s):  
Large Scale ◽  
Embedded Sensing ◽  
The Future

scholarly journals Transcriptomic resources for prairie grass (Bromus catharticus): expressed transcripts, tissue-specific genes, and identification and validation of EST-SSR markers

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ming Sun ◽  
Zhixiao Dong ◽  
Jian Yang ◽  
Wendan Wu ◽  
Chenglin Zhang ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Ssr Markers ◽  
Large Scale ◽  
Genetic Research ◽  
High Yield ◽  
Yield Strain ◽  
Tissue Samples ◽  
Prairie Grass ◽  
The Future ◽  
Genomic Resource

Abstract Background Prairie grass (Bromus catharticus) is a typical cool-season forage crop with high biomass production and fast growth rate during winter and spring. However, its genetic research and breeding has remained stagnant due to limited available genomic resources. The aim of this study was to generate large-scale genomic data using high-throughput transcriptome sequencing, and perform a preliminary validation of EST-SSR markers of B. catharticus. Results Eleven tissue samples including seeds, leaves, and stems were collected from a new high-yield strain of prairie grass BCS1103. A total of 257,773 unigenes were obtained, of which 193,082 (74.90%) were annotated. Comparison analysis between tissues identified 1803, 3030, and 1570 genes specifically and highly expressed in seed, leaf, and stem, respectively. A total of 37,288 EST-SSRs were identified from unigene sequences, and more than 80,000 primer pairs were designed. We synthesized 420 primer pairs and selected 52 ones with high polymorphisms to estimate genetic diversity and population structure in 24 B. catharticus accessions worldwide. Despite low diversity indicated by an average genetic distance of 0.364, the accessions from South America and Asia and wild accessions showed higher genetic diversity. Moreover, South American accessions showed a pure ancestry, while Asian accessions demonstrated mixed internal relationships, which indicated a different probability of gene flow. Phylogenetic analysis clustered the studied accessions into four clades, being consistent with phenotypic clustering results. Finally, Mantel analysis suggested the total phenotypic variation was mostly contributed by genetic component. Stem diameter, plant height, leaf width, and biomass yield were significantly correlated with genetic data (r > 0.6, P < 0.001), and might be used in the future selection and breeding. Conclusion A genomic resource was generated that could benefit genetic and taxonomic studies, as well as molecular breeding for B. catharticus and its relatives in the future.

scholarly journals China’s Investments in Germany and the Impact of the COVID-19 Pandemic

2021 ◽  
Vol 56 (2) ◽  
pp. 113-119
Author(s):  
Xinming Xia ◽  
Wan-Hsin Liu
Keyword(s):  
Large Scale ◽  
Know How ◽  
Advanced Technologies ◽  
The Future ◽  
Potential Impact ◽  
Chinese State ◽  
The Impact ◽  
Gain Access ◽  
Over Time

AbstractThis paper analyses how China’s investments in Germany have developed over time and the potential impact of the COVID-19 pandemic in this regard, based on four different datasets, including our own survey in mid-2020. Our analysis shows that Germany is currently one of the most attractive investment destinations for Chinese investors. Chinese state-owned enterprises have played an important role as investors in Germany — particularly in large-scale projects. The COVID-19 pandemic has had some negative but rather temporary effects on Chinese investments in Germany. Germany is expected to stay attractive to Chinese investors who seek to gain access to advanced technologies and know-how in the future.

THE FUTURE IS HERE: APPRECIATING AND DEVELOPING THE NEXT GENERATION OF LEADERS

2021 ◽  
Vol 2021 (100) ◽  
pp. 6-9
Author(s):  
Julia M. Santucci
Keyword(s):  
Next Generation ◽  
The Future
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