Complexity Analysis of Balloon Drawing for Rooted Trees

In a balloon drawing of a tree, all the children under the same parent are placed on the circumference of the circle centered at their parent, and the radius of the circle centered at each node along any path from the root reflects the number of descendants associated with the node. Among various styles of tree drawings reported in the literature, the balloon drawing enjoys a desirable feature of displaying tree structures in a rather balanced fashion. For each internal node in a balloon drawing, the ray from the node to each of its children divides the wedge accommodating the subtree rooted at the child into two sub-wedges. Depending on whether the two sub-wedge angles are required to be identical or not, a balloon drawing can further be divided into two types: even sub-wedge and uneven sub-wedge types. In the most general case, for any internal node in the tree there are two dimensions of freedom that affect the quality of a balloon drawing: (1) altering the order in which the children of the node appear in the drawing, and (2) for the subtree rooted at each child of the node, flipping the two sub-wedges of the subtree. In this paper, we give a comprehensive complexity analysis for optimizing balloon drawings of rooted trees with respect to angular resolution, aspect ratio and standard deviation of angles under various drawing cases depending on whether the tree is of even or uneven sub-wedge type and whether (1) and (2) above are allowed. It turns out that some are NP-complete while others can be solved in polynomial time. We also derive approximation algorithms for those that are intractable in general

The Potential Economic Impact of Avian Flu Pandemic on Taiwan

This study analyzes the potential consequences of an outbreak of avian influenza (H5N1) on Taiwan¡¦s macro economy and individual industries. Both the Input-Output (IO) Analysis Model and Computable General Equilibrium (CGE) Model are used to simulate the possible damage brought by lowering domestic consumption, export, and labor supply. The simulation results indicates that if the disease is confined within the poultry sector, then the impact on real GDP is around -0.1%~-0.4%. Once it becomes a human-to-human pandemic, the IO analysis suggests that the potential impacts on real GDP would be as much as -4.2%~-5.9% while labor demand would decrease 4.9%~6.4%. In the CGE analysis, which allows for resource mobility and substitutions through price adjustments, the real GDP and labor demand would contract 2.0%~2.4% and 2.2%~2.4%, respectively, and bringing down consumer prices by 3%. As for the individual sector, the outbreak will not only damage the poultry sector and its upstream and downstream industries, but also affect the service sectors including wholesale, retail, trade, air transportation, restaurants, as well as healthcare services. These results can be used to support public investment in animal disease control measures.Avian Flu Pandemic, Input-output Model, Computable General Equilibrium Model, Livestock Production/Industries,

Rhythm-Flexible Voice Conversion without Parallel Data Using Cycle-GAN over Phoneme Posteriorgram Sequences

Speaking rate refers to the average number of phonemes within some unit time, while the rhythmic patterns refer to duration distributions for realizations of different phonemes within different phonetic structures. Both are key components of prosody in speech, which is different for different speakers. Models like cycle-consistent adversarial network (Cycle-GAN) and variational auto-encoder (VAE) have been successfully applied to voice conversion tasks without parallel data. However, due to the neural network architectures and feature vectors chosen for these approaches, the length of the predicted utterance has to be fixed to that of the input utterance, which limits the flexibility in mimicking the speaking rates and rhythmic patterns for the target speaker. On the other hand, sequence-to-sequence learning model was used to remove the above length constraint, but parallel training data are needed. In this paper, we propose an approach utilizing sequence-to-sequence model trained with unsupervised Cycle-GAN to perform the transformation between the phoneme posteriorgram sequences for different speakers. In this way, the length constraint mentioned above is removed to offer rhythm-flexible voice conversion without requiring parallel data. Preliminary evaluation on two datasets showed very encouraging results.Comment: 8 pages, 6 figures, Submitted to SLT 201

Anti-inflammatory and anti-coagulatory activities of caffeic acid and ellagic acid in cardiac tissue of diabetic mice

<p>Abstract</p> <p>Background</p> <p>Caffeic acid (CA) and ellagic acid (EA) are phenolic acids naturally occurring in many plant foods. Cardiac protective effects of these compounds against dyslipidemia, hypercoagulability, oxidative stress and inflammation in diabetic mice were examined.</p> <p>Methods</p> <p>Diabetic mice were divided into three groups (15 mice per group): diabetic mice with normal diet, 2% CA treatment, or 2% EA treatment. One group of non-diabetic mice with normal diet was used for comparison. After 12 weeks supplement, mice were sacrificed, and the variation of biomarkers for hypercoagulability, oxidative stress and inflammation in cardiac tissue of diabetic mice were measured.</p> <p>Results</p> <p>The intake of CA or EA significantly increased cardiac content of these compounds, alleviated body weight loss, elevated plasma insulin and decreased plasma glucose levels in diabetic mice (<it>p </it>< 0.05). These treatments also significantly enhanced plasma antithrombin-III and protein C activities (<it>p </it>< 0.05); and decreased triglyceride content in cardiac tissue and plasma (<it>p </it>< 0.05), in which the hypolipidemic effects of EA were significantly greater than that of CA (<it>p </it>< 0.05). CA or EA significantly lowered cardiac levels of malondialdehyde, reactive oxygen species, interleukin (IL)-beta, IL-6, tumor necrosis factor (TNF)-alpha and monocyte chemoattractant protein (MCP)-1 (<it>p </it>< 0.05); and retained cardiac activity of glutathione peroxidase (GPX), superoxide dismutase (SOD) and catalase (<it>p </it>< 0.05). These compounds also significantly up-regulated cardiac mRNA expression of GPX1, SOD and catalase; and down-regulated IL-1beta, IL-6, TNF-alpha and MCP-1 mRNA expression in diabetic mice (<it>p </it>< 0.05).</p> <p>Conclusion</p> <p>These results support that CA and EA could provide triglyceride-lowering, anti-coagulatory, anti-oxidative, and anti-inflammatory protection in cardiac tissue of diabetic mice. Thus, the supplement of these agents might be helpful for the prevention or attenuation of diabetic cardiomyopathy.</p

Applying a Heuristic Approach for a Minimum-cost Operating Strategy for Tap Water

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

High-throughput Automated Muropeptide Analysis (HAMA) Reveals Peptidoglycan Composition of Gut Microbial Cell Walls

Peptidoglycan (PGN), a net-like polymer constituted by muropeptides, provides protection for microorganisms and has been a major target for antibiotics for decades. Researchers have explored host-microbiome interactions through PGN recognition systems and discovered key muropeptides modulating host responses. However, most common characterization techniques for muropeptides are labor-intensive and require manual analysis of mass spectra due to the complex cross-linked PGN structures. Each species has unique moiety modifications and inter-/intra-bridges, which further complicates the structural analysis of PGN. Here, we developed a high-throughput automated muropeptide analysis (HAMA) platform leveraging tandem mass spectrometry and in silico muropeptide MS/MS fragmentation matching to comprehensively identify muropeptide structures, quantify their abundance, and infer PGN cross-linking types. We demonstrated the effectiveness of HAMA platform using well-characterized PGNs from E. coli and S. aureus and further applied it to common gut bacteria including Bifidobacterium, Bacteroides, Lactobacillus, Enterococcus, and Akkermansia muciiniphila. Specifically, we found that the stiffness and strength of the cell envelopes may correspond to the lengths and compositions of interpeptide bridges within Bifidobacterium species. In summary, the HAMA framework exhibits an automated, intuitive, and accurate analysis of PGN compositions, which may serve as a potential tool to investigate the post-synthetic modifications of saccharides, the variation in interpeptide bridges, and the types of cross-linking within bacterial PGNs.</p

BIOADI: a machine learning approach to identifying abbreviations and definitions in biological literature

BACKGROUND: To automatically process large quantities of biological literature for knowledge discovery and information curation, text mining tools are becoming essential. Abbreviation recognition is related to NER and can be considered as a pair recognition task of a terminology and its corresponding abbreviation from free text. The successful identification of abbreviation and its corresponding definition is not only a prerequisite to index terms of text databases to produce articles of related interests, but also a building block to improve existing gene mention tagging and gene normalization tools. RESULTS: Our approach to abbreviation recognition (AR) is based on machine-learning, which exploits a novel set of rich features to learn rules from training data. Tested on the AB3P corpus, our system demonstrated a F-score of 89.90% with 95.86% precision at 84.64% recall, higher than the result achieved by the existing best AR performance system. We also annotated a new corpus of 1200 PubMed abstracts which was derived from BioCreative II gene normalization corpus. On our annotated corpus, our system achieved a F-score of 86.20% with 93.52% precision at 79.95% recall, which also outperforms all tested systems. CONCLUSION: By applying our system to extract all short form-long form pairs from all available PubMed abstracts, we have constructed BIOADI. Mining BIOADI reveals many interesting trends of bio-medical research. Besides, we also provide an off-line AR software in the download section on http://bioagent.iis.sinica.edu.tw/BIOADI/