130,393 research outputs found
POSCA: Path Optimization for Solar Cover Amelioration in Urban Air Mobility
No full textUrban Air Mobility (UAM) encompasses both piloted and autonomous aerial vehicles, spanning from small unmanned aerial vehicles (UAVs) like drones to passenger-carrying personal air vehicles (PAVs), to revolutionize smart transportation in congested urban areas. This emerging paradigm is anticipated to offer disruptive solutions to the mobility challenges in congested cities. In this context, a pivotal concern centers on the sustainability of transitioning to this mode of transportation, especially with the focus on incorporating clean technology into developing innovative solutions from the ground up. Recent studies highlight that a significant portion of the total energy consumption in UAM can be attributed to the flight operations of the aircraft. To address this challenge, this paper introduces a framework POSCA aimed at meeting the energy requirements of UAM flights. It delves into a complex and dynamic route-planning problem. It introduces a novel concept called the Phototropic Index, calculated by considering the traversal distance and solar coverage along the route. To solve the path planning problem, we propose two solutions, S-POSCA and D-POSCA, catering to static and dynamic setups. Simulation results confirm an average increase of 8.81% in static conditions and 10.64% in the dynamic condition for the cumulative Global Horizontal Irradiance (GHI) compared to the baseline approaches
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
ANALISI DELLA MUTAZIONE V599E DI BRAF NEI TUMORI TIROIDEI MEDIANTE MUTANT ALLELE SPECIFIC AMPLIFICATION (MASA)
No full textGoing Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far
Deep Proteomics of Breast Cancer Cells Reveals that Metformin Rewires Signaling Networks Away from a Pro-growth State.
No full textMetformin is the most frequently prescribed drug for type 2 diabetes. In addition to its hypoglycemic effects, metformin also lowers cancer incidence. This anti-cancer activity is incompletely understood. Here, we profiled the metformin-dependent changes in the proteome and phosphoproteome of breast cancer cells using high-resolution mass spectrometry. Intotal, we quantified changes of 7,875 proteins and 15,813 phosphosites after metformin changes. To interpret these datasets, we developed a generally applicable strategy that overlays metformin-dependent changes in the proteome and phosphoproteome onto a literature-derived network. This approach suggested that metformin treatment makes cancer cells more sensitive to apoptotic stimuli and less sensitive to pro-growth stimuli. These hypotheses were tested invivo; as a proof-of-principle, we demonstrated that metformin inhibits the p70S6K-rpS6 axis in a PP2A-phosphatase dependent manner. In conclusion, analysis of deep proteomics reveals both detailed and global mechanisms that contribute to the anti-cancer activity of metformin
Metformin Induces Apoptosis and Downregulates Pyruvate Kinase M2 in Breast Cancer Cells Only When Grown in Nutrient-Poor Conditions
No full text, in addition to inhibiting cancer cell proliferation, metformin can also induce apoptosis. The molecular mechanism underlying this second effect is still poorly characterized and published data are often contrasting. We investigated how nutrient availability can modulate metformin-induced apoptosis in three breast cancer cell lines.MCF7, SKBR3 and MDA-MB-231 cells were plated in MEM medium supplemented with increasing glucose concentrations or in DMEM medium and treated with 10 mM metformin. Cell viability was monitored by Trypan Blue assay and treatment effects on Akt/mTOR pathway and on apoptosis were analysed by Western Blot. Moreover, we determined the level of expression of pyruvate kinase M2 (PKM2), a well-known glycolytic enzyme expressed in cancer cells.Our results showed that metformin can induce apoptosis in breast cancer cells when cultured at physiological glucose concentrations and that the pro-apoptotic effect was completely abolished when cells were grown in high glucose/high amino acid medium. Induction of apoptosis was found to be dependent on AMPK activation but, at least partially, independent of TORC1 inactivation. Finally, we showed that, in nutrient-poor conditions, metformin was able to modulate the intracellular glycolytic equilibrium by downregulating PKM2 expression and that this mechanism was mediated by AMPK activation.We demonstrated that metformin induces breast cancer cell apoptosis and PKM2 downregulation only in nutrient-poor conditions. Not only glucose levels but also amino acid concentration can influence the observed metformin inhibitory effect on the mTOR pathway as well as its pro-apoptotic effect. These data demonstrate that the reduction of nutrient supply in tumors can increase metformin efficacy and that modulation of PKM2 expression/activity could be a promising strategy to boost metformin anti-cancer effect
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