30,704 research outputs found
Rebels Lead to the Doctrine of the Mean: Opinion Dynamic in a Heterogeneous DeGroot Model
We study an extension of the DeGroot model where part of the players may be
rebels. The updating rule for rebels is quite different with that of normal
players (which are referred to as conformists): at each step a rebel first
takes the opposite value of the weighted average of her neighbors' opinions,
i.e. 1 minus that average (the opinion space is assumed to be [0,1] as usual),
and then updates her opinion by taking another weighted average between that
value and her own opinion in the last round. We find that the effect of rebels
is rather significant: as long as there is at least one rebel in every closed
and strongly connected group, under very weak conditions, the opinion of each
player in the whole society will eventually tend to 0.5.Comment: 7 pages, Proceedings of The 6th International Conference on
Knowledge, Information and Creativity Support Systems, Beijing, 201
Open-Category Classification by Adversarial Sample Generation
In real-world classification tasks, it is difficult to collect training
samples from all possible categories of the environment. Therefore, when an
instance of an unseen class appears in the prediction stage, a robust
classifier should be able to tell that it is from an unseen class, instead of
classifying it to be any known category. In this paper, adopting the idea of
adversarial learning, we propose the ASG framework for open-category
classification. ASG generates positive and negative samples of seen categories
in the unsupervised manner via an adversarial learning strategy. With the
generated samples, ASG then learns to tell seen from unseen in the supervised
manner. Experiments performed on several datasets show the effectiveness of
ASG.Comment: Published in IJCAI 201
Synthesis of 2-pyrone containing products and Hibiscone C
2-Pyrone is extremely prevalent in numerous natural products with a broad range of biological activities. Not only structurally complex natural products, but more and more 2-pyrone containing small molecules have also attracted the attention of organic chemists, medicinal chemists and agricultural scientist. Synthesizing valuable 2-pyrone containing products and testing their potential applications are of great importance.
In this dissertation, we summarized the synthesis of two 2-pyrone containing small molecule natural products and explored methods to functionalize triacetic acid lactone, a very promising 2-pyrone compound that has been identified as a bio-privileged molecule. Chapter 1 of this dissertation describes the synthesis of a class of 6-alkyl-2-pyrones and an antileukemic 2-pyrone. Chapter 2 discusses the involvement of triacetic acid lactone in multi-component reaction. The versatility of the bio-based triacetic acid lactone as a platform chemical has been further demonstrated via the 3-component Mannich reaction. The last chapter describes an approach to Hibiscone C, a bioactive and structurally interesting natural product. A strategically new approach to this molecule was depicted
Quantifying Carbon and Water Dynamics of Terrestrial Ecosystems At High Temporal And Spatial Resolutions Using Process-Based Biogeochemistry Models And In Situ And Satellite Data
To better understand the role of terrestrial ecosystems in the global carbon cycle and their feedbacks to the global climate system, process-based ecosystem models that are used for quantifying net carbon exchanges between the terrestrial biosphere and the atmosphere need to be improved. My research objective is to improve the model from following aspects: 1) Improving parameterization and model structure for carbon and water dynamics, 2) improving regional model simulations at finer spatial resolutions (from 0.5 degree to 0.05 degree or finer), 3) developing faster spin-up algorithms, and 4) evaluating high performance model simulations using fast spin-up technique deployed on various computing platforms. I improved the leaf area index (LAI) modeling in a terrestrial ecosystem model (TEM) for North America. The evaluated TEM was used to estimate ET at site and regional scales in North America from 2000 to 2010. The estimated annual ET varies from 420 to 450 mm yr-1 with the improved model, close to MODIS monthly data with root-mean-square-error less than 10 mmmonth-1 for the study period. Alaska, Canada, and the conterminous US accounts for 33%, 6% and 61% of the regional ET, respectively. I then used new algorithm for a fast spin-up for TEM. With the new spin-up algorithm, I showed that the model reached a steady state in less than 10 years of simulation time, while the original method requires more than 200 years on average of model run. Lastly, I conducted simulations under both original resolution and high resolution in the conterminous US. The high-resolution simulation predicts slightly higher average annual gross primary production (GPP) (~2%) from 2000 to 2015 in the conterminous US than original version of TEM. From the improved TEM simulation, I estimated that regional GPP is between 7.12 and 7.69 Pg C yr-1 and NEP is between 0.09 and 0.75 Pg C yr-1
Dissolution of different commercial aspirin tablets using a novel off-center paddle impeller (OPI) dissolution testing system
Dissolution testing is routinely conducted in the pharmaceutical industry to provide in vitro drug release information for quality control purposes. The most common dissolution testing system for solid dosage forms is the United States Pharmacopeia (USP) Dissolution Testing Apparatus 2. In this work, a modified Apparatus 2, termed OPI System for off-center paddle impeller, in which the impeller is placed 8 mm off center in the vessel is tested to determine its sensitivity to differentiate between the dissolution profiles of differently formulated and manufactured tablets. Dissolution tests are conducted with both the OPI System and the Standard System using three different brands of aspirin at nine different tablet positions. The OPI system produces dissolution profiles that are highly dependent on the different brands of aspirin used, similarly to those generates in the Standard System. However, the dissolution profiles obtained with the OPI apparatus are found to be largely independent of the tablet location at the vessel bottom, whereas those obtained in the Standard System generates statistically different profiles depending on tablet location. It can be concluded that the newly proposed OPI system can effectively eliminate artifacts generated by random settling of the tablet at the vessel bottom, thus making the test more robust, while at the same time being just as sensitive as the Standard System to actual differences in differently manufactured tablets having intrinsically different dissolution profiles
Thermodynamics and phase transition in central charge criticality of charged Gauss-Bonnet AdS black holes
In this paper, we investigate the thermodynamics of D-dimensional charged
Gauss-Bonnet black holes in anti-de Sitter spacetime. Varying the cosmological
constant, Newton constant and Gauss-Bonnet coupling constant in the bulk, one
can rewrite the first law of thermodynamics for black holes. Furthermore, we
introduce the central charge and study the critical behaviors, which show the
apparent discrepancy from other black holes. Based on this approach, we
disclose the phase transition structures in , and . Besides, a
triple point where the small/intermediate/large black holes can coexist is
found in
Predicting protein disorder by analyzing amino acid sequence
<p>Abstract</p> <p>Background</p> <p>Many protein regions and some entire proteins have no definite tertiary structure, presenting instead as dynamic, disorder ensembles under different physiochemical circumstances. These proteins and regions are known as Intrinsically Unstructured Proteins (IUP). IUP have been associated with a wide range of protein functions, along with roles in diseases characterized by protein misfolding and aggregation.</p> <p>Results</p> <p>Identifying IUP is important task in structural and functional genomics. We exact useful features from sequences and develop machine learning algorithms for the above task. We compare our IUP predictor with PONDRs (mainly neural-network-based predictors), disEMBL (also based on neural networks) and Globplot (based on disorder propensity).</p> <p>Conclusion</p> <p>We find that augmenting features derived from physiochemical properties of amino acids (such as hydrophobicity, complexity etc.) and using ensemble method proved beneficial. The IUP predictor is a viable alternative software tool for identifying IUP protein regions and proteins.</p
- …