Institution
Worcester Polytechnic Institute
Education•Worcester, Massachusetts, United States•
About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Computer science & Population. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.
Topics: Computer science, Population, Data envelopment analysis, Nonlinear system, Finite element method
Papers published on a yearly basis
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16 Jun 2014
TL;DR: This paper proposes a new approach for automatically classifying text messages of individuals to infer their emotional states, using hash-tags as labels and utilizes a lexicon of emotions to tackle the problem of sparse and high dimensional feature vectors of messages.
Abstract: Social media and microblog tools are increasingly used by individuals to express their feelings and opinions in the form of short text messages. Detecting emotions in text has a wide range of applications including identifying anxiety or depression of individuals and measuring well-being or public mood of a community. In this paper, we propose a new approach for automatically classifying text messages of individuals to infer their emotional states. To model emotional states, we utilize the well-established Circumplex model that characterizes aective experience along two dimensions: valence and arousal. We select Twitter messages as input data set, as they provide a very large, diverse and freely avail- able ensemble of emotions. Using hash-tags as labels, our methodology trains supervised classiers to detect multiple classes of emotion on potentially huge data sets with no manual eort. We investigate the utility of several features for emotion detection, including unigrams, emoticons, negations and punctuations. To tackle the problem of sparse and high dimensional feature vectors of messages, we utilize a lexicon of emotions. We have compared the accuracy of several machine learning algorithms, including SVM, KNN, Decision Tree, and Naive Bayes for classifying Twitter messages. Our technique has an accuracy of over 90%, while demonstrating robustness across learning algorithms.
108 citations
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TL;DR: The relaxation response is a simple, no cost, non-pharmacological mechanism without side-effects which seemed to decrease the frequency of P.V.C.C.'s in most patients with ischaemic heart-disease.
108 citations
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TL;DR: In this paper, the authors confirmed that high performance Ni1/3Mn 1/3Co/3(OH)2 precursor and LiNi1/2Mn1/ 3Co/O2 cathode material can be synthesized from leaching solution of a lithium ion battery recovery stream.
108 citations
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TL;DR: It was demonstrated that the as-prepared SnO nanoflowers could be utilized as good anode materials for lithium ion rechargeable batteries with a high capacity of around 800 mA h g(-1), close to the theoretical value.
Abstract: A facile and reproducible approach was reported to synthesize nanoparticle-attached SnO nanoflowers via decomposition of an intermediate product Sn6O4(OH)4. Sn6O4(OH)4 formed after introducing water into the traditional nonaqueous reaction, and then decomposed to SnO nanoflowers with the help of free metal cations, such as Sn2+, Fe2+, and Mn2+. This free cation-induced formation process was found independent of the nature of the surface ligand. It was demonstrated further that the as-prepared SnO nanoflowers could be utilized as good anode materials for lithium ion rechargeable batteries with a high capacity of around 800 mA h g−1, close to the theoretical value (875 mA h g−1).
108 citations
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TL;DR: If shown to be clinically efficacious, well-tolerated, and compatible with the public health imperative of forestalling evolution of drug resistance, inexpensive, locally grown and processed A. annua might prove to be an effective addition to the global effort to reduce malaria morbidity and mortality.
Abstract: Drugs are primary weapons for reducing malaria in human populations. However emergence of resistant parasites has repeatedly curtailed the lifespan of each drug that is developed and deployed. Currently the most effective anti-malarial is artemisinin, which is extracted from the leaves of Artemisia annua. Due to poor pharmacokinetic properties and prudent efforts to curtail resistance to monotherapies, artemisinin is prescribed only in combination with other anti-malarials composing an Artemisinin Combination Therapy (ACT). Low yield in the plant, and the added cost of secondary anti-malarials in the ACT, make artemisinin costly for the developing world. As an alternative, we compared the efficacy of oral delivery of the dried leaves of whole plant (WP) A. annua to a comparable dose of pure artemisinin in a rodent malaria model (Plasmodium chabaudi). We found that a single dose of WP (containing 24 mg/kg artemisinin) reduces parasitemia more effectively than a comparable dose of purified drug. This increased efficacy may result from a documented 40-fold increase in the bioavailability of artemisinin in the blood of mice fed the whole plant, in comparison to those administered synthetic drug. Synergistic benefits may derive from the presence of other anti-malarial compounds in A. annua. If shown to be clinically efficacious, well-tolerated, and compatible with the public health imperative of forestalling evolution of drug resistance, inexpensive, locally grown and processed A. annua might prove to be an effective addition to the global effort to reduce malaria morbidity and mortality.
108 citations
Authors
Showing all 6336 results
Name | H-index | Papers | Citations |
---|---|---|---|
Andrew G. Clark | 140 | 823 | 123333 |
Ming Li | 103 | 1669 | 62672 |
Joseph Sarkis | 101 | 482 | 45116 |
Arthur C. Graesser | 95 | 614 | 38549 |
Kevin J. Harrington | 85 | 682 | 33625 |
Kui Ren | 83 | 501 | 32490 |
Bart Preneel | 82 | 844 | 25572 |
Ming-Hui Chen | 82 | 525 | 29184 |
Yuguang Fang | 79 | 572 | 20715 |
Wenjing Lou | 77 | 311 | 29405 |
Bernard Lown | 73 | 330 | 20320 |
Joe Zhu | 72 | 231 | 19017 |
Y.S. Lin | 71 | 304 | 16100 |
Kevin Talbot | 71 | 268 | 15669 |
Christof Paar | 69 | 399 | 21790 |