101,954 research outputs found
Surrogate modeling application for process system emissions assessment: improving computational performances for plantwide estimations
No full textDuring the last decade, data driven modeling has gained a role of major interest all over the engineering fields mainly due to the need of higher computational power or, inversely, less computational demanding models for applications such as optimization, simulation, scheduling and control. Relevant contributions of process systems surrogate modeling as a support for operation optimization were already proved in literature with a reduction of the overall computational time by two orders of magnitude with respect to conventional simulations. In this research work a biogas-to-methanol plant case study is used to assess the total energy consumption and estimate the related emissions. Therefore, a modeling phase carried out via Response Surface Methodology is set up in order to obtain the analytical function that allows to estimate the equivalent CO2 emissions over an extended range of operating conditions representing a wide interval of biomass feed composition. The study has been performed over a wide independent variables domain as well as for different sample sizes in order to compare the computational performances and the accuracy of the obtained models accordingly. The computational time was reduced by two orders of magnitude with a mean relative error lower than 1%. Given the quality of the results, this approach could be further exploited for other system variables and processes including highly non-ideal behaviour of mixtures to be treated. Furthermore, more complex sampling and different surrogate modeling strategies could be tested in order to check if even higher computational effectiveness and model accuracy could be obtained in the process systems domain
JunB transcription factor maintains skeletal muscle mass and promotes hypertrophy
No full textThe size of skeletal muscle cells is precisely regulated by intracellular signaling networks that determine the balance between overall rates of protein synthesis and degradation. Myofiber growth and protein synthesis are stimulated by the IGF-1/Akt/mammalian target of rapamycin (mTOR) pathway. In this study, we show that the transcription factor JunB is also a major determinant of whether adult muscles grow or atrophy. We found that in atrophying myotubes, JunB is excluded from the nucleus and that decreasing JunB expression by RNA interference in adult muscles causes atrophy. Furthermore, JunB overexpression induces hypertrophy without affecting satellite cell proliferation and stimulated protein synthesis independently of the Akt/mTOR pathway. When JunB is transfected into denervated muscles, fiber atrophy is prevented. JunB blocks FoxO3 binding to atrogin-1 and MuRF-1 promoters and thus reduces protein breakdown. Therefore, JunB is important not only in dividing populations but also in adult muscle, where it is required for the maintenance of muscle size and can induce rapid hypertrophy and block atrophy
Machine-learning certification of multipartite entanglement for noisy quantum hardware
No full textEntanglement is a fundamental aspect of quantum physics, both conceptually and for its many applications. Classifying an arbitrary multipartite state as entangled or separable-a task referred to as the separability problem-poses a significant challenge, since a state can be entangled with respect to many different of its partitions. We develop a certification pipeline that feeds the statistics of random local measurements into a non-linear dimensionality reduction algorithm, to determine with respect to which partitions a given quantum state is entangled. After training a model on randomly generated quantum states, entangled in different partitions and of varying purity, we verify the accuracy of its predictions on simulated test data, and finally apply it to states prepared on IBM quantum computing hardware.
Bibliographie Hilarion G. Petzold 1958 – 2009 mit Anhang als Einführung
No full textDieses Archiv enthält die Gesamtbibliographie der Werke des Autors nebst einiger Texte „Über H. G. Petzold“ im Schlussteil der Bibliographie sowie einen Anhang mit einer Einführung in die Architektur des Werkes in seinem wissenslogischen Aufbau als Ausarbeitung seines „Tree of Science Modells“ (2007).This archive contains the complete bibliography of the author and some texts about H. G. Petzold, moreover an epilogue with an introduction to the architecture of the works in its epistemological structure and composition and as an elaborations of Petzold’s „Tree of Science Modell (2007).https://www.fpi-publikation.de/polyloge/01-2009-petzold-h-g-gesamtbibliographie-h-g-petzold-1958-2009-updating-november2009/peerReviewedpublishedVersio
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
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3346: Samuel G. Freedman, author, 2013
No full textPhotograph of author Samuel G. Freedman, at NT Daily Slash meeting in the Mayborn School of Journalism at UNT
The Right to Strike under the United States Constitution: Theory, Practice, and Possible Implications for Canada
No full textAnswering critics of the Canadian Supreme Court's judgment in B.C. Health, the author argues that the Court laid the foundation for a principled and durable doctrine protecting constitutional labour rights, one that goes directly to the heart of the matter — the inequality of workers’ power in the employment relation. In the author’s view, two paths could lead from B.C. Health to the recognition of Charter protec- tion for a right to strike: one that treats the right as an accessory to col- lective bargaining, and one that upholds the right directly on the basis of the Charter values of equality and participation. The author supports the latter approach, contending that constitutional rights should be defined in relation to fundamental values, in a way that is not contingent on time-bound or fact-sensitive assessments about the role of strikes within a particular collective bargaining regime. Although a Charter right to strike may involve the courts in difficult choices about when to defer to legislative policy decisions, and courts may lack the institutional capac- ity to deal effectively with labour law issues, the author points out that judges can look to ILO standards for expert guidance. Noting that the U.S. experience in this area might be of considerable use to Canadians, the author concludes by providing an overview of American case law concerning a constitutional right to strike.Peer reviewe
G-Rank: Unsupervised Continuous Learn-to-Rank for Edge Devices in a P2P Network
No full textRanking algorithms in traditional search engines are powered by enormous training data sets that are meticulously engineered and curated by a centralized entity. Decentralized peer-to-peer (p2p) networks such as torrenting applications and Web3 protocols deliberately eschew centralized databases and computational architectures when designing services and features. As such, robust search-and-rank algorithms designed for such domains must be engineered specifically for decentralized networks, and must be lightweight enough to operate on consumer-grade personal devices such as a smartphone or laptop computer. We introduce G-Rank, an unsupervised ranking algorithm designed exclusively for decentralized networks. We demonstrate that accurate, relevant ranking results can be achieved in fully decentralized networks without any centralized data aggregation, feature engineering, or model training. Furthermore, we show that such results are obtainable with minimal data preprocessing and computational overhead, and can still return highly relevant results even when a user’s device is disconnected from the network. G-Rank is highly modular in design, is not limited to categorical data, and can be implemented in a variety of domains with minimal modification. The results herein show that unsupervised ranking models designed for decentralized p2p networks are not only viable, but worthy of further research.https://github.com/awrgold/G-RankComputer Scienc
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