443 research outputs found
Do the Number, Size, and Position of Partially Threaded Screws Affect the Radiological Healing of Surgically Treated Displaced Femoral Neck Fractures? A Review of 136 Children
No full textApproximation Algorithms for Min-Distance Problems
No full textWe study fundamental graph parameters such as the Diameter and Radius in directed graphs, when distances are measured using a somewhat unorthodox but natural measure: the distance between u and v is the minimum of the shortest path distances from u to v and from v to u. The center node in a graph under this measure can for instance represent the optimal location for a hospital to ensure the fastest medical care for everyone, as one can either go to the hospital, or a doctor can be sent to help.
By computing All-Pairs Shortest Paths, all pairwise distances and thus the parameters we study can be computed exactly in O~(mn) time for directed graphs on n vertices, m edges and nonnegative edge weights. Furthermore, this time bound is tight under the Strong Exponential Time Hypothesis [Roditty-Vassilevska W. STOC 2013] so it is natural to study how well these parameters can be approximated in O(mn^{1-epsilon}) time for constant epsilon>0. Abboud, Vassilevska Williams, and Wang [SODA 2016] gave a polynomial factor approximation for Diameter and Radius, as well as a constant factor approximation for both problems in the special case where the graph is a DAG. We greatly improve upon these bounds by providing the first constant factor approximations for Diameter, Radius and the related Eccentricities problem in general graphs. Additionally, we provide a hierarchy of algorithms for Diameter that gives a time/accuracy trade-off
Citation Author Topic Model in Expert Search
No full textThis paper proposes a novel topic model, Citation-Author-Topic (CAT) model that addresses a semantic search task we define as expert search – given a research area as a query, it returns names of experts in this area. For example, Michael Collins would be one of the top names retrieved given the query Syntactic Parsing. Our contribution in this paper is two-fold. First, we model the cited author informa-tion together with words and paper au-thors. Such extra contextual information directly models linkage among authors and enhances the author-topic association, thus produces more coherent author-topic distribution. Second, we provide a prelim-inary solution to the task of expert search when the learning repository contains ex-clusively research related documents au-thored by the experts. When compared with a previous proposed model (Johri et al., 2010), the proposed model pro-duces high quality author topic linkage and achieves over 33 % error reduction evaluated by the standard MAP measure-ment.
ERR gamma suppression by Sirt6 alleviates cholestatic liver injury and fibrosis
No full textOrphan nuclear receptor estrogen-related receptor gamma (ERR gamma) stimulates bile acid production; however, the role and the regulatory mechanism of ERR gamma in cholestatic liver disease are largely unknown. This study identifies that Sirt6 is a deacetylase of ERR gamma and suggests a potentially novel mechanism by which Sirt6 activation alleviates cholestatic liver damage and fibrosis through regulating ERR gamma. We observed that hepatic expression of Sirt6 is repressed, whereas hepatic expression of ERR gamma is upregulated in murine cholestasis models. Hepatocyte-specific Sirt6-KO mice were more severely injured after a bile duct ligation (BDL) than WT mice, and adenoviral reexpression of Sirt6 reversed liver damage and fibrosis as demonstrated by biochemical and histological analyses. Mechanistically, Sirt6 deacetylated ERR gamma, thereby destabilizing ERR gamma and inhibiting its transcriptional activity. Elimination of hepatic ERR gamma using Ad-shERR gamma abolished the deleterious effects of Sirt6 deficiency, whereas ERR gamma overexpression aggravated cholestatic liver injury. Administration of a Sirt6 deacetylase activator prevented BDL-induced liver damage and fibrosis. In patients with cholestasis, Sirt6 expression was decreased, whereas total ERR gamma and acetylated ERR gamma levels were increased, confirming negative regulation of ERR gamma by Sirt6. Thus, Sirt6 activation represents a potentially novel therapeutic strategy for treating cholestatic liver injury
Detecting Logic Bugs in Graph Database Management Systems via Injective and Surjective Graph Query Transformation
No full text<h2>Introduction</h2>
<p>GraphGenie is a bug-finding tool to detect logic bugs and performance issues (we also find internal errors) in graph database management systems. Specifically, unlike most existing testing works mutating query predicates, GraphGenie leverages Graph Query Transformations (GQT) to construct semantically equivalent or variant graph query patterns, which enables comparative analysis on their results to reveal bugs. GraphGenie has been tested and found previous unknown bugs on popular graph database engines like Neo4j.</p>
<p>If you use, extend or build upon GraphGenie we kindly ask you to cite our ICSE'24 paper:</p>
<div>
<pre><code>@inproceedings{jiang2024detecting,
title={Detecting Logic Bugs in Graph Database Management Systems via Injective and Surjective Graph Query Transformation},
author={Jiang, Yuancheng and Liu, Jiahao and Ba, Jinsheng and Yap, Roland H.C. and Liang, Zhenkai and Rigger, Manuel},
booktitle={Proceedings of the 46th International Conference on Software Engineering},
publisher = {{ACM}},
year={2024},
doi = {10.1145/3597503.3623307}
}
</code></pre>
<div> </div>
</div>
<h2>Environment Requirement</h2>
<p>The code has been tested running under Python 3.8.10. The OS is 20.04.2 LTS Ubuntu Linux 64-bit distribution.</p>
<p><strong>Dependencies</strong></p>
<div>
<pre><code>apt install python3
apt install python3-pip
pip3 install configparser
pip3 install neo4j
pip3 install redisgraph
pip3 install psycopg2
</code></pre>
<div> </div>
</div>
<h2>Graph Database Engine Setup</h2>
<p>We do not initialize graph data. We use existing graph dataset like <a href="https://github.com/neo4j-graph-examples/recommendations.git">recommendations</a>. We give concrete steps for setting up the <a href="https://github.com/neo4j/neo4j">Neo4j</a> below. For other graph database engines, please refer to official documentations for installation and dataset initialization. We include the python drivers for <a href="https://github.com/RedisGraph/RedisGraph/">RedisGraph</a> and <a href="https://github.com/bitnine-oss/agensgraph/">AgensGraph</a> in our code.</p>
<p><strong>Neo4j</strong></p>
<div>
<pre><code>apt install openjdk-17-jdk;
cd dbs;
wget https://dist.neo4j.org/neo4j-community-5.11.0-unix.tar.gz;
tar -xvf neo4j-community-5.11.0-unix.tar.gz;
git clone https://github.com/neo4j-graph-examples/recommendations.git;
cd neo4j-community-5.11.0;
./bin/neo4j-admin dbms set-initial-password 12344321
./bin/neo4j-admin database load --from-stdin --overwrite-destination=true neo4j < ../recommendations/data/recommendations-50.dump;
echo "dbms.transaction.timeout=30s" >> ./conf/neo4j.conf
./bin/neo4j start
</code></pre>
<div> </div>
</div>
<h2>Usage</h2>
<p>Config graphgenie.ini first and then start the testing:</p>
<p>If you test Neo4j, simply run the main.py</p>
<div>
<pre><code>./main.py
</code></pre>
<div> </div>
</div>
<p>For other databases, you need to first initialize the dataset and specify</p>
<div>
<pre><code>node_labels, edge_labels, node_properties, connectivity_matrix
</code></pre>
<div> </div>
</div>
<p>in main.py line 332, or implement your own schema scanner (should be similar to Neo4j one).</p>
<p>Detected bugs can be found in <code>./bug.log</code> (logic bugs or performance issues) or <code>./exception.log</code> (internal errors). The <code>./testing.log</code> records all executed queries.</p>
<h2>Todos</h2>
<p>We only implement the prototype code. There are still many todos:</p>
<ul>
<li>to support GDBMS: Memgraph/Kuzu/FalkorDB/..</li>
<li>to have an option for automatically initializing the graph data so we do not need existing dataset</li>
<li>to support testing update/insert clauses</li>
<li>to have more mutation rules</li>
<li>to limit the max threads</li>
</ul>
<h2>About Gremlin</h2>
<p>We focus on testing Cypher query language. Currently we do not release the code for testing Gremlin database engines because we are using the <a href="https://github.com/opencypher/cypher-for-gremlin">cypher-for-gremlin</a> translator, which sometimes leads to inaccurate translation and false bug alarm.</p>
<h2>Bugs we found:</h2>
<p><a href="https://github.com/neo4j/neo4j/issues/created_by/YuanchengJiang">Neo4j</a>, <a href="https://github.com/RedisGraph/RedisGraph/issues/created_by/YuanchengJiang">RedisGraph</a>, <a href="https://github.com/bitnine-oss/agensgraph/issues/created_by/YuanchengJiang">AgensGraph</a></p>
Microbial co-existence and stable equilibria in a mechanistic model of enteric methane production : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mathematics at Massey University, Manawatū Campus, New Zealand
No full textGlobally, 14.5% of all anthropogenic greenhouse gases come from ruminants. One of these is methane, which is produced in the rumen of ruminant animals. Feed is degraded by microbes to produce volatile fatty acids (which are absorbed by the animal) and hydrogen (which is metabolized by methanogens to form methane). The dynamics of hydrogen production and metabolism are subject to thermodynamic control imposed by the hydrogen concentration. Existing models to estimate methane production are based on calculation of hydrogen balances without considering the presence of methanogens and do not include thermodynamic control. In this project, a model is developed based on glucose-hydrogenmethanogen dynamics to estimate methane production and illustrates a co-existence of microbes that employs different fermentation pathways competing for the same food source in the rumen. Glucose was chosen as an example of a fermentable feed component. A thermodynamic term was integrated into a Monod-type model to represent the thermodynamic control of hydrogen concentration on the rates of hydrogen generation and hydrogen metabolism. Results of this model suggest that the microbial community composition and the combination of the different pathways are determined by the rumen environment, biological parameters of the microbes and the feedback imposed by substrate and product concentrations. The mathematical enunciation of this model is therefore consistent with biological expectations. This model could be expanded to include plant polymer degradation rate, feeding level and feeding frequency to explore their effects on methane production. This model could also be integrated into models of whole rumen function to address more complex questions. It would also support experimentation with animals for understanding factors that control methane formation and to explore methane mitigation strategies
Performance of supertree methods for estimating species trees
No full textPhylogenetics is the research of ancestor-descendant relationships among different groups of organisms, for example, species or populations of interest. The datasets involved are usually sequence alignments of various subsets of taxa for various genes.
A major task of phylogenetics is often to combine estimated gene trees from many loci sampled from the genes into an overall estimate species tree topology. Eventually, one can construct the tree of life that depicts the ancestor-descendant relationships for all known species around the world. If there is missing data or incomplete sampling in the datasets, then supertree methods can be used to assemble gene trees with different subsets of taxa into an estimated overall species tree topology.
In this study, we assume that gene tree discordance is solely due to incomplete lineage sorting under the multispecies coalescent model (Degnan and Rosenberg, 2009). If there is missing data or incomplete sampling in the datasets, then supertree methods can be used to assemble gene trees with different subsets of taxa into an estimated species tree topology. In addition, we examine the performance of the most commonly used supertree method (Wilkinson et al., 2009), namely matrix representation with parsimony (MRP), to explore its statistical properties in this setting. In particular, we show that MRP is not statistically consistent. That is, an estimated species tree topology other than the true species tree topology is more likely to be returned by MRP as the number of gene trees increases. For some situations, using longer branch lengths, randomly deleting taxa or even introducing mutation can improve the performance of MRP so that the matching species tree topology is recovered more often.
In conclusion, MRP is a supertree method that is able to handle large amounts of conflict in the input gene trees. However, MRP is not statistically consistent, when using gene trees arise from the multispecies coalescent model to estimate species trees
Defense Against Adversarial Attacks in Deep Learning
No full textNeural networks are very vulnerable to adversarial examples, which threaten their application in security systems, such as face recognition, and autopilot. In response to this problem, we propose a new defensive strategy. In our strategy, we propose a new deep denoising neural network, which is called UDDN, to remove the noise on adversarial samples. The standard denoiser suffers from the amplification effect, in which the small residual adversarial noise gradually increases and leads to misclassification. The proposed denoiser overcomes this problem by using a special loss function, which is defined as the difference between the model outputs activated by the original image and denoised image. At the same time, we propose a new model training algorithm based on knowledge transfer, which can resist slight image disturbance and make the model generalize better around the training samples. Our proposed defensive strategy is robust against both white-box or black-box attacks. Meanwhile, the strategy is applicable to any deep neural network-based model. In the experiment, we apply the defensive strategy to a face recognition model. The experimental results show that our algorithm can effectively resist adversarial attacks and improve the accuracy of the model
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