4,946 research outputs found

    The power of LinkedIn: Will professionals leave their organizations for professional advancement because of their use of LinkedIn?

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    With the growth of Web 2.0/3.0, social network sites have been created for various purposes for a wide spectrum of users. Creating a digital footprint has become imperative, especially for professionals seeking career development and professional advancement. This study explores professionals’ intention to leave an organization for professional advancement (ILPA) based on their use of a professional social network site, LinkedIn. Our framework leverages self-determination theory (SDT) to demonstrate why professionals use this online social networking service. To validate our theoretical framework, 379 randomly selected active LinkedIn users completed an online questionnaire. The extent to which using LinkedIn influences ILPA is examined and the results support all our hypotheses. Our post-hoc analysis indicates a strong relationship between needing support and motivation for participating in LinkedIn. We attempt to explain the findings by using the time perspective concept. This study is also of practical value to companies seeking to set policies to retain professionals. Implications for theory and practice are discussed

    Pre-clinical animal model for ovarian cancer using live imaging system

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    posterDevelopment of a live imaging animal model for orthotopic ovarian cancers in order to better understand disease mechanisms and response to potential anticancer drug treatments

    忠信與操縱 : 當代基督教《聖經》中文譯本研究

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    在基督教群體中,《聖經》向來被視為上帝的話,享有絕對的權威。 翻譯《聖經》的工作皆以忠於原文為首要目標。不同語言的《聖經》譯 本的數量早已成為古今中外譯本之冠。近一百多年來,基督教中文《聖經》的翻譯工作持續不斷,新的譯本相繼問世。這些譯本都宣稱以忠於原文為翻譯目的、比舊的譯本更忠實可信。然而《聖經》的原文早已遺失,不同譯本依據的源文又各有不同,譯本宣稱忠於原文的各種說法,不免有名不符實之嫌;而所謂忠信,亦是一個非常複雜的變動而相對的概念。本文擬採用描述性翻譯研究的方法,借用安德烈•勒菲弗爾 (André Lefevere) 的理論,嘗試從意識形態、詩學、贊助人三方面,探討聲稱以忠信為翻譯目標的當代《聖經》中文譯本在翻譯過程中對原文的操縱情況,揭示《聖經》中文譯本名為忠信、實為操縱的翻譯現象

    A Theoretical Analysis of the Repetition Problem in Text Generation

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    Text generation tasks, including translation, summarization, language models, and etc. see rapid growth during recent years. Despite the remarkable achievements, the repetition problem has been observed in nearly all text generation models undermining the generation performance extensively. To solve the repetition problem, many methods have been proposed, but there is no existing theoretical analysis to show why this problem happens and how it is resolved. In this paper, we propose a new framework for theoretical analysis for the repetition problem. We first define the Average Repetition Probability (ARP) to characterize the repetition problem quantitatively. Then, we conduct an extensive analysis of the Markov generation model and derive several upper bounds of the average repetition probability with intuitive understanding. We show that most of the existing methods are essentially minimizing the upper bounds explicitly or implicitly. Grounded on our theory, we show that the repetition problem is, unfortunately, caused by the traits of our language itself. One major reason is attributed to the fact that there exist too many words predicting the same word as the subsequent word with high probability. Consequently, it is easy to go back to that word and form repetitions and we dub it as the high inflow problem. Furthermore, we derive a concentration bound of the average repetition probability for a general generation model. Finally, based on the theoretical upper bounds, we propose a novel rebalanced encoding approach to alleviate the high inflow problem. The experimental results show that our theoretical framework is applicable in general generation models and our proposed rebalanced encoding approach alleviates the repetition problem significantly. The source code of this paper can be obtained from https://github.com/fuzihaofzh/repetition-problem-nlg.Comment: AAAI 21 Paper with Appendi

    Testing J/psi Production and Decay Properties in Hadronic Collisions

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    The polar and azimuthal angular distributions for the lepton pair arising from the decay of a J/psi meson produced at transverse momentum p_T balanced by a photon [or gluon] in hadronic collisions are calculated in the color singlet model (CSM). It is shown that the general structure of the decay lepton distribution is controlled by four invariant structure functions, which are functions of the transverse momentum and the rapidity of the J/psi. We found that two of these structure functions [the longitudinal and transverse interference structure functions] are identical in the CSM. Analytical and numerical results are given in the Collins-Soper and in the Gottfried-Jackson frame. We present a Monte Carlo study of the effect of acceptance cuts applied to the leptons and the photon for J/psi+ gamma production at the Tevatron.Comment: 22 pages (LaTeX) plus 11 postscript figures, MAD/PH/822, YUMS94-11. Figures are available from the authors or as a compressed tar file via anonymous ftp at phenom.physics.wisc.edu in directory {}~pub/preprints/madph-94-822-figs.tar.

    Effect of sucralfate on gastric mucosal blood flow in rats

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    Sucralfate possesses site protective and cytoprotective actions and heals ulcers effectively, but its effect on gastric mucosal blood flow is unknown. Using an ex vivo gastric chamber preparation, we studied the effect of sucralfate on gastric mucosal blood flow in rats by laser doppler flowmetry. Under both fasting and fed states, measurements of gastric mucosal blood flow and damage were made in rats after topical application of absolute ethanol alone or after pretreatment with sucralfate. Gastric mucosal damage was assessed by measuring the total area of haemorrhagic mucosal lesions. Ethanol induced gastric mucosal lesions were significantly less with sucralfate pretreatment than without (p less than 0.008). Mucosal blood flow significantly fell after ethanol application (p less than 0.001). The fall was significantly less in fed than in fasted rats (p less than 0.05), and after pretreatment with sucralfate 100 mg or 200 mg than without in both fasted (p less than 0.0008 and 0.00001, respectively) and fed (p less than 0.002 and 0.001, respectively) rats. Graded doses of sucralfate (25-400 mg) resulted in an increase in gastric mucosal blood flow in a dose dependent manner (r = 0.731, p less than 0.001). In conclusion that sucralfate increases gastric mucosal blood flow in rats and lessens the fall in blood flow in rats treated with ethanol, and this action may contribute to its protection against the vascular damage of mucosa by ethanol.published_or_final_versio

    Effect of sucralfate on gastric mucosal blood flow in rats

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    Sucralfate possesses site protective and cytoprotective actions and heals ulcers effectively, but its effect on gastric mucosal blood flow is unknown. Using an ex vivo gastric chamber preparation, we studied the effect of sucralfate on gastric mucosal blood flow in rats by laser doppler flowmetry. Under both fasting and fed states, measurements of gastric mucosal blood flow and damage were made in rats after topical application of absolute ethanol alone or after pretreatment with sucralfate. Gastric mucosal damage was assessed by measuring the total area of haemorrhagic mucosal lesions. Ethanol induced gastric mucosal lesions were significantly less with sucralfate pretreatment than without (p less than 0.008). Mucosal blood flow significantly fell after ethanol application (p less than 0.001). The fall was significantly less in fed than in fasted rats (p less than 0.05), and after pretreatment with sucralfate 100 mg or 200 mg than without in both fasted (p less than 0.0008 and 0.00001, respectively) and fed (p less than 0.002 and 0.001, respectively) rats. Graded doses of sucralfate (25-400 mg) resulted in an increase in gastric mucosal blood flow in a dose dependent manner (r = 0.731, p less than 0.001). In conclusion that sucralfate increases gastric mucosal blood flow in rats and lessens the fall in blood flow in rats treated with ethanol, and this action may contribute to its protection against the vascular damage of mucosa by ethanol.published_or_final_versio
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