Journal articles: 'Toric domains'

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Hind, Richard, and Jun Zhang. "Hamiltonian knottedness and lifting paths from the shape invariant." Compositio Mathematica 159, no. 11 (September 18, 2023): 2416–57. http://dx.doi.org/10.1112/s0010437x23007479.

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The Hamiltonian shape invariant of a domain $X \subset \mathbb {R}^4$ , as a subset of $\mathbb {R}^2$ , describes the product Lagrangian tori which may be embedded in $X$ . We provide necessary and sufficient conditions to determine whether or not a path in the shape invariant can lift, that is, be realized as a smooth family of embedded Lagrangian tori, when $X$ is a basic $4$ -dimensional toric domain such as a ball $B^4(R)$ , an ellipsoid $E(a,b)$ with ${b}/{a} \in \mathbb {N}_{\geq ~2}$ , or a polydisk $P(c,d)$ . As applications, via the path lifting, we can detect knotted embeddings of product Lagrangian tori in many toric $X$ . We also obtain novel obstructions to symplectic embeddings between domains that are more general than toric concave or toric convex.

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Chuah, Meng-Kiat. "Reinhardt domains and toric models." Michigan Mathematical Journal 51, no. 1 (April 2003): 73–92. http://dx.doi.org/10.1307/mmj/1049832894.

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Landry, Michael, Matthew McMillan, and Emmanuel Tsukerman. "On symplectic capacities of toric domains." Involve, a Journal of Mathematics 8, no. 4 (June 23, 2015): 665–76. http://dx.doi.org/10.2140/involve.2015.8.665.

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Marinković, Aleksandra. "Examples of Weinstein Domains in the Complement of Smoothed Total Toric Divisors." Mathematica Slovaca 73, no. 4 (August 1, 2023): 997–1012. http://dx.doi.org/10.1515/ms-2023-0074.

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ABSTRACT In [ACG+1] and [ACG+2], it is shown that a complement of a neighborhood of a partially smoothed total toric divisor of a closed toric symplectic 4-manifold is a Weinstein domain. In this article, we extend the family of Weinstein domains that can be realized as such complements by producing an infinite family of new examples.

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Choi, Keon, Michael Hutchings, Daniel Cristofaro-Gardiner, David Frenkel, and Vinicius Gripp Barros Ramos. "Symplectic embeddings into four-dimensional concave toric domains." Journal of Topology 7, no. 4 (May 22, 2014): 1054–76. http://dx.doi.org/10.1112/jtopol/jtu008.

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Sparavigna, A., A. Mello, and B. Montrucchio. "Growth of toric domains in mesophases of oxadiazoles." Phase Transitions 81, no. 5 (May 2008): 471–77. http://dx.doi.org/10.1080/01411590701854938.

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McDuff, Dusa, and Kyler Siegel. "Symplectic capacities, unperturbed curves and convex toric domains." Geometry & Topology 28, no. 3 (May 10, 2024): 1213–85. http://dx.doi.org/10.2140/gt.2024.28.1213.

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Blanc, Christophe, and Maurice Kleman. "Tiling the plane with noncongruent toric focal conic domains." Physical Review E 62, no. 5 (November 1, 2000): 6739–48. http://dx.doi.org/10.1103/physreve.62.6739.

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Cristofaro-Gardiner, Dan. "Symplectic embeddings from concave toric domains into convex ones." Journal of Differential Geometry 112, no. 2 (June 2019): 199–232. http://dx.doi.org/10.4310/jdg/1559786421.

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Munteanu, Mihai. "Noncontractible loops of symplectic embeddings between convex toric domains." Journal of Symplectic Geometry 18, no. 4 (2020): 1169–96. http://dx.doi.org/10.4310/jsg.2020.v18.n4.a8.

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Kim, Yun Ho, Dong Ki Yoon, M. C. Choi, Hyeon Su Jeong, Mahn Won Kim, Oleg D. Lavrentovich, and Hee-Tae Jung. "Confined Self-Assembly of Toric Focal Conic Domains (The Effects of Confined Geometry on the Feature Size of Toric Focal Conic Domains)." Langmuir 25, no. 3 (February 3, 2009): 1685–91. http://dx.doi.org/10.1021/la802870z.

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Honglawan, Apiradee, Daniel A. Beller, Marcello Cavallaro, Randall D. Kamien, Kathleen J. Stebe, and Shu Yang. "Pillar-Assisted Epitaxial Assembly of Toric Focal Conic Domains of Smectic-A Liquid Crystals." Advanced Materials 23, no. 46 (October 17, 2011): 5519–23. http://dx.doi.org/10.1002/adma.201103008.

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Honglawan, Apiradee, Daniel A. Beller, Marcello Cavallaro, Randall D. Kamien, Kathleen J. Stebe, and Shu Yang. "Epitaxial Assembly: Pillar-Assisted Epitaxial Assembly of Toric Focal Conic Domains of Smectic-A Liquid Crystals (Adv. Mater. 46/2011)." Advanced Materials 23, no. 46 (December 2, 2011): 5460. http://dx.doi.org/10.1002/adma.201190189.

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Feng, Junchao, Jianjun Miao, Yue Tang, Yuechen Li, and Jundong Feng. "The Performance of Topic Evolution Based on a Feature Maximization Measurement for the Linguistics Domain." Axioms 11, no. 8 (August 18, 2022): 412. http://dx.doi.org/10.3390/axioms11080412.

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Understanding the performance of the data mining approach and topic evolution in a certain scientific domain is imperative to capturing key domain developments and facilitating knowledge transfer within and across domains. Our research selects linguistics as an exploratory domain and exploits the feature maximization (FM) measurement for feature selection, combined with the contrast ratio to conduct the diachronic analysis for the linguistics domain’s topics. To accurately mine the linguistics domain’s topics and obtain the optimal clustering model selection, we exploit an integrated method associated with the deep embedding for clustering (DEC) algorithm based on the keywords-based Text Representation Matrix (KTRM) and Lamirel’s EC index and test the performance of this method. The results show that the FM measurement is applicable in the linguistics domain for topic mining, and the combinatory method has the advantage of an unbiased clustering optimization model and applies to the design of non-parameter clustering and algorithms from the low dimension to the high dimension of datasets. The findings suggest that this approach could be suitable for a diachronic analysis of topic evolution and facilitate the performance of topic detection. In addition, these findings of text detection can rise to knowledge fusion cognition with the factor of language as an available research objective in interdisciplinary research.

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Li, Lianghao, Xiaoming Jin, and Mingsheng Long. "Topic Correlation Analysis for Cross-Domain Text Classification." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 998–1004. http://dx.doi.org/10.1609/aaai.v26i1.8308.

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Cross-domain text classification aims to automatically train a precise text classifier for a target domain by using labeled text data from a related source domain. To this end, the distribution gap between different domains has to be reduced. In previous works, a certain number of shared latent features (e.g., latent topics, principal components, etc.) are extracted to represent documents from different domains, and thus reduce the distribution gap. However, only relying the shared latent features as the domain bridge may limit the amount of knowledge transferred. This limitation is more serious when the distribution gap is so large that only a small number of latent features can be shared between domains. In this paper, we propose a novel approach named Topic Correlation Analysis (TCA), which extracts both the shared and the domain-specific latent features to facilitate effective knowledge transfer. In TCA, all word features are first grouped into the shared and the domain-specific topics using a joint mixture model. Then the correlations between the two kinds of topics are inferred and used to induce a mapping between the domain-specific topics from different domains. Finally, both the shared and the mapped domain-specific topics are utilized to span a new shared feature space where the supervised knowledge can be effectively transferred. The experimental results on two real-world data sets justify the superiority of the proposed method over the stat-of-the-art baselines.

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Gon, Stéphanie, Marie-Thérèse Giudici-Orticoni, Vincent Méjean, and Chantal Iobbi-Nivol. "Electron Transfer and Binding of thec-Type Cytochrome TorC to the TrimethylamineN-Oxide Reductase inEscherichia coli." Journal of Biological Chemistry 276, no. 15 (October 30, 2000): 11545–51. http://dx.doi.org/10.1074/jbc.m008875200.

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Reduction of trimethylamineN-oxide (E′0(TMAO/TMA)= +130 mV) inEscherichia coliis carried out by the Tor system, an electron transfer chain encoded by thetorCADoperon and made up of the periplasmic terminal reductase TorA and the membrane-anchored pentahemicc-type cytochrome TorC. Although the role of TorA in the reduction of trimethylamineN-oxide (TMAO) has been clearly established, no direct evidence for TorC involvement has been presented. TorC belongs to the NirT/NapCc-type cytochrome family based on homologies of its N-terminal tetrahemic domain (TorCN) to the cytochromes of this family, but TorC contains a C-terminal extension (TorCC) with an additional heme-binding site. In this study, we show that both domains are required for the anaerobic bacterial growth with TMAO. The intact TorC protein and its two domains, TorCNand TorCC, were produced independently and purified for a biochemical characterization. The reduced form of TorC exhibited visible absorption maxima at 552, 523, and 417 nm. Mediated redox potentiometry of the heme centers of the purified components identified two negative midpoint potentials (−177 and −98 mV) localized in the tetrahemic TorCNand one positive midpoint potential (+120 mV) in the monohemic TorCC. In agreement with these values, thein vitroreconstitution of electron transfer between TorC, TorCN, or TorCCand TorA showed that only TorC and TorCCwere capable of electron transfer to TorA. Surprisingly, interaction studies revealed that only TorC and TorCNstrongly bind TorA. Therefore, TorCCdirectly transfers electrons to TorA, whereas TorCN, which probably receives electrons from the menaquinone pool, is involved in both the electron transfer to TorCCand the binding to TorA.

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Wahlsten, Jennifer L., and S. Ramakrishnan. "Separation of Function Between the Domains of Toxic Shock Syndrome Toxin-1." Journal of Immunology 160, no. 2 (January 15, 1998): 854–59. http://dx.doi.org/10.4049/jimmunol.160.2.854.

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Abstract Toxic shock syndrome toxin-1 (TSST1) is a superantigenic exotoxin produced by certain strains of Staphylococcus aureus. Structurally, TSST1 is composed of two domains: residues determined by crystallography to directly interact with MHC II molecules reside within the N-terminal domain, while TSST1 residues critical for superantigenicity are within the C-terminal domain. In this study, we expressed the individual N- and C-terminal domains of TSST1 in Escherichia coli and studied their biologic activities. The TSST1 N-terminal domain (TSST(1–87)) did not induce proliferation of human PBLs or release of TNF-β, but did induce TNF-α release. However, TSST1-elicited proliferation and release of both TNF isoforms were inhibited by a molar excess of TSST(1–87). The TSST1 C-terminal domain (TSST(88–194)) did not bind MHC II molecules, yet it elicited production of TNF-α and TNF-β, and induced TCR Vβ-specific proliferation similarly to intact TSST1. When covalently cross-linked to tumor cells, TSST(88–194) elicited a local in vivo antitumor response indistinguishable from TSST1. Although intact TSST1 causes lethal shock in vivo, the individual domains of this molecule may have therapeutic potential: the N-terminal domain to antagonize lymphocyte activation and TNF release during acute TSST1-precipitated toxic shock syndrome, and the C-terminal domain to stimulate antitumor responses without MHC II binding.

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18

Ballester, V., F. Granero, R. A. de Maagd, D. Bosch, J. L. Ménsua, and J. Ferré. "Role of Bacillus thuringiensis Toxin Domains in Toxicity and Receptor Binding in the Diamondback Moth." Applied and Environmental Microbiology 65, no. 5 (May 1, 1999): 1900–1903. http://dx.doi.org/10.1128/aem.65.5.1900-1903.1999.

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ABSTRACT The toxic fragment of Bacillus thuringiensis crystal proteins consists of three distinct structural domains. There is evidence that domain I is involved in pore formation and that domain II is involved in receptor binding and specificity. It has been found that, in some cases, domain III is also important in determining specificity. Furthermore, involvement of domain III in binding has also been reported recently. To investigate the role of toxin domains in the diamondback moth (Plutella xylostella), we used hybrid toxins with domain III substitutions among Cry1C, Cry1E, and Cry1Ab. Neither Cry1E nor G27 (a hybrid with domains I and II from Cry1E and domain III from Cry1C) was toxic, whereas Cry1C and F26 (the reciprocal hybrid) were equally toxic. H04 (a hybrid with domains I and II from Cry1Ab and domain III from Cry1C) showed toxicity that was of a similar level as that of Cry1Ab and significantly higher than that of Cry1C. Binding assays with 125I-Cry1C showed that Cry1C and F26 competed for the same binding sites on midgut membrane vesicles, whereas Cry1E, G27, and H04 did not bind to these sites. Our results show that, in contrast to findings in other insects for the toxins and hybrids used here, toxin specificity as well as specificity of binding to membrane vesicles in the diamondback moth is mediated by domain II (and/or I) and not by domain III.

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19

Li, Bin, and Jianmin Yao. "Selection of In-Domain Bilingual Sentence Pairs Based on Topic Information." Scientific Programming 2020 (December 15, 2020): 1–7. http://dx.doi.org/10.1155/2020/8879570.

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The performance of a machine translation system (MTS) depends on the quality and size of the training data. How to extend the training dataset for the MTS in specific domains with effective methods to enhance the performance of machine translation needs to be explored. A method for selecting in-domain bilingual sentence pairs based on the topic information is proposed. With the aid of the topic relevance of the bilingual sentence pairs to the target domain, subsets of sentence pairs related to the texts to be translated are selected from a large-scale bilingual corpus to train the translation system in specific domains to improve the translation quality for in-domain texts. Through the test, the bilingual sentence pairs are selected by using the proposed method, and further the MTS is trained. In this way, the translation performance is greatly enhanced.

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20

Albişoru, Andrei-Florin, and Dorin Ghişa. "Conformal Self Mappings of the Fundamental Domains of Analytic Functions and Computer Experimentation." WSEAS TRANSACTIONS ON MATHEMATICS 22 (September 26, 2023): 652–65. http://dx.doi.org/10.37394/23206.2023.22.72.

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Conformal self mappings of a given domain of the complex plane can be obtained by using the Riemann Mapping Theorem in the following way. Two different conformal mappings φ and ψ of that domain onto one of the standard domains: the unit disc, the complex plane or the Riemann sphere are taken and then ψ −1 ◦ φ is what we are looking for. Yet, this is just a theoretical construction, since the Riemann Mapping Theorem does not offer any concrete expression of those functions. The Möbius transformations are concrete, but they can be used only for particular circular domains. We are proving in this paper that conformal self mappings of any fundamental domain of an arbitrary analytic function can be obtained via Möbius transformations as long as we allow that domain to have slits. Moreover, those mappings enjoy group properties. This is a totally new topic. Although fundamental domains of some elementary functions are well known, the existence of such domains for arbitrary analytic functions has been proved only in our previous publications mentioned in the References section. No other publication exists on this topic and the reference list is complete. We deal here with conformal self mappings of fundamental domains in its whole generality and present sustaining illustrations. Those related to the case of Dirichlet functions represent a real achievement. Computer experimentation with these mappings are made for the most familiar analytic functions.

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Yang, Yuanfeng, Husheng Dong, Gang Liu, Liang Zhang, and Lin Li. "Cross-Domain Traffic Scene Understanding by Integrating Deep Learning and Topic Model." Computational Intelligence and Neuroscience 2022 (March 18, 2022): 1–15. http://dx.doi.org/10.1155/2022/8884669.

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Understanding cross-domain traffic scenarios from multicamera surveillance network is important for environmental perception. Most of existing methods select the source domain which is most similar to the target domain by comparing entire domains for cross-domain similarity and then transferring the motion model learned in the source domain to the target domain. The cross-domain similarity between overall different scenarios with similar local layouts is usually not utilized to improve any automatic surveillance tasks. However, these local commonalities, which may be shared across multiple traffic scenarios, can be transferred across scenarios as prior knowledge. To address these issues, we present a novel framework for cross-domain traffic scene understanding by integrating deep learning and topic model. This framework leverages the labeled samples with activity attribute labels from the source domain to annotate the target domain, where each label represents the local activity of some objects in the scene. When labeling the activity attributes of the target domain, there is no need to select the source domain, which avoids the phenomenon of performance degradation or even negative transfer due to wrong source domain selection. The effectiveness of the proposed framework is verified by extensive experiments carried out using public road traffic data.

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Brand, Charlotte O., Alex Mesoudi, and Thomas J. H. Morgan. "Trusting the experts: The domain-specificity of prestige-biased social learning." PLOS ONE 16, no. 8 (August 11, 2021): e0255346. http://dx.doi.org/10.1371/journal.pone.0255346.

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Prestige-biased social learning (henceforth “prestige-bias”) occurs when individuals predominantly choose to learn from a prestigious member of their group, i.e. someone who has gained attention, respect and admiration for their success in some domain. Prestige-bias is proposed as an adaptive social-learning strategy as it provides a short-cut to identifying successful group members, without having to assess each person’s success individually. Previous work has documented prestige-bias and verified that it is used adaptively. However, the domain-specificity and generality of prestige-bias has not yet been explicitly addressed experimentally. By domain-specific prestige-bias we mean that individuals choose to learn from a prestigious model only within the domain of expertise in which the model acquired their prestige. By domain-general prestige-bias we mean that individuals choose to learn from prestigious models in general, regardless of the domain in which their prestige was earned. To distinguish between domain specific and domain general prestige we ran an online experiment (n = 397) in which participants could copy each other to score points on a general-knowledge quiz with varying topics (domains). Prestige in our task was an emergent property of participants’ copying behaviour. We found participants overwhelmingly preferred domain-specific (same topic) prestige cues to domain-general (across topic) prestige cues. However, when only domain-general or cross-domain (different topic) cues were available, participants overwhelmingly favoured domain-general cues. Finally, when given the choice between cross-domain prestige cues and randomly generated Player IDs, participants favoured cross-domain prestige cues. These results suggest participants were sensitive to the source of prestige, and that they preferred domain-specific cues even though these cues were based on fewer samples (being calculated from one topic) than the domain-general cues (being calculated from all topics). We suggest that the extent to which people employ a domain-specific or domain-general prestige-bias may depend on their experience and understanding of the relationships between domains.

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Alarcon, Clara M., Joseph Heitman, and Maria E. Cardenas. "Protein Kinase Activity and Identification of a Toxic Effector Domain of the Target of Rapamycin TOR Proteins in Yeast." Molecular Biology of the Cell 10, no. 8 (August 1999): 2531–46. http://dx.doi.org/10.1091/mbc.10.8.2531.

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In complex with FKBP12, the immunosuppressant rapamycin binds to and inhibits the yeast TOR1 and TOR2 proteins and the mammalian homologue mTOR/FRAP/RAFT1. The TOR proteins promote cell cycle progression in yeast and human cells by regulating translation and polarization of the actin cytoskeleton. A C-terminal domain of the TOR proteins shares identity with protein and lipid kinases, but only one substrate (PHAS-I), and no regulators of the TOR-signaling cascade have been identified. We report here that yeast TOR1 has an intrinsic protein kinase activity capable of phosphorylating PHAS-1, and this activity is abolished by an active site mutation and inhibited by FKBP12-rapamycin or wortmannin. We find that an intact TOR1 kinase domain is essential for TOR1 functions in yeast. Overexpression of a TOR1 kinase-inactive mutant, or of a central region of the TOR proteins distinct from the FRB and kinase domains, was toxic in yeast, and overexpression of wild-type TOR1 suppressed this toxic effect. Expression of the TOR-toxic domain leads to a G1 cell cycle arrest, consistent with an inhibition of TOR function in translation. Overexpression of the PLC1gene, which encodes the yeast phospholipase C homologue, suppressed growth inhibition by the TOR-toxic domains. In conclusion, our findings identify a toxic effector domain of the TOR proteins that may interact with substrates or regulators of the TOR kinase cascade and that shares sequence identity with other PIK family members, including ATR, Rad3, Mei-41, and ATM.

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Wijaya, Rio N., Fiki T. Akbar, Jusak S. Kosasih, and Bobby E. Gunara. "BPS domain wall from toric hypermultiplet." Advanced Studies in Theoretical Physics 12, no. 8 (2018): 369–80. http://dx.doi.org/10.12988/astp.2018.827.

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Zhao, S., S. Saha, and X. X. Zhu. "GRAPH NEURAL NETWORK BASED OPEN-SET DOMAIN ADAPTATION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 31, 2022): 1407–13. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-1407-2022.

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Abstract. Owing to the presence of many sensors and geographic/seasonal variations, domain adaptation is an important topic in remote sensing. However, most domain adaptation methods focus on close-set adaptation, i.e., they assume that the source and target domains share the same label space. This assumption often does not hold in practice, as there can be previously unseen classes in the target domain. To circumnavigate this issue, we propose a method for open set domain adaptation, where the target domain contains additional unknown classes that are not present in the source domain. To improve the model’s generalization ability, we propose a Progressive Weighted Graph Learning (PWGL) method. The proposed method exploits graph neural networks in aggregating similar samples across source and target domains. The progressive strategy gradually separates the unknown samples apart from known samples and upgrades the source domain by incorporating the pseudolabeled known target samples. The weighted adversarial learning promotes the alignment of known classes across different domains and rejects the unknown class. The experiments performed on a multi-city dataset show the effectiveness of the proposed approach.

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Serra, Michael J., and Lindzi L. Shanks. "Blocked Presentation Leads Participants to Overutilize Domain Familiarity as a Cue for Judgments of Learning (JOLs)." Journal of Intelligence 11, no. 7 (July 17, 2023): 142. http://dx.doi.org/10.3390/jintelligence11070142.

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The accuracy of judgments of learning (JOLs) is vital for efficient self-regulated learning. We examined a situation in which participants overutilize their prior knowledge of a topic (“domain familiarity”) as a basis for JOLs, resulting in substantial overconfidence in topics they know the most about. College students rank ordered their knowledge across ten different domains and studied, judged, and then completed a test on facts from those domains. Recall and JOLs were linearly related to self-rated knowledge, as was overconfidence: participants were most overconfident for topics they knew more about, indicating the overutilization of domain familiarity as a cue for JOLs. We examined aspects of the task that might contribute to this pattern, including the order of the task phases and whether participants studied the facts blocked by topic. Although participants used domain familiarity as a cue for JOLs regardless of task design, we found that studying facts from multiple topics blocked by topic led them to overutilize this cue. In contrast, whether participants completed the rank ordering before studying the facts or received a warning about this tendency did not alter the pattern. The relative accuracy of participants’ JOLs, however, was not related to domain familiarity under any conditions.

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Mollá, Diego, and José Luis Vicedo. "Question Answering in Restricted Domains: An Overview." Computational Linguistics 33, no. 1 (March 2007): 41–61. http://dx.doi.org/10.1162/coli.2007.33.1.41.

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Automated question answering has been a topic of research and development since the earliest AI applications. Computing power has increased since the first such systems were developed, and the general methodology has changed from the use of hand-encoded knowledge bases about simple domains to the use of text collections as the main knowledge source over more complex domains. Still, many research issues remain. The focus of this article is on the use of restricted domains for automated question answering. The article contains a historical perspective on question answering over restricted domains and an overview of the current methods and applications used in restricted domains. A main characteristic of question answering in restricted domains is the integration of domain-specific information that is either developed for question answering or that has been developed for other purposes. We explore the main methods developed to leverage this domain-specific information.

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Luo, Xi, Yixin Li, Hongyuan Cheng, and Lihua Yin. "AGCN-Domain: Detecting Malicious Domains with Graph Convolutional Network and Attention Mechanism." Mathematics 12, no. 5 (February 22, 2024): 640. http://dx.doi.org/10.3390/math12050640.

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Domain Name System (DNS) plays an infrastructure role in providing the directory service for mapping domains to IPs on the Internet. Considering the foundation and openness of DNS, it is not surprising that adversaries register massive domains to enable multiple malicious activities, such as spam, command and control (C&C), malware distribution, click fraud, etc. Therefore, detecting malicious domains is a significant topic in security research. Although a substantial quantity of research has been conducted, previous work has failed to fuse multiple relationship features to uncover the deep underlying relationships between domains, thus largely limiting their level of performance. In this paper, we proposed AGCN-Domain to detect malicious domains by combining various relations. The core concept behind our work is to analyze relations between domains according to their behaviors in multiple perspectives and fuse them intelligently. The AGCN-Domain model utilizes three relationships (client relation, resolution relation, and cname relation) to construct three relationship feature graphs to extract features and intelligently fuse the features extracted from the graphs through an attention mechanism. After the relationship features are extracted from the domain names, they are put into the trained classifier to be processed. Through our experiments, we have demonstrated the performance of our proposed AGCN-Domain model. With 10% initialized labels in the dataset, our AGCN-Domain model achieved an accuracy of 94.27% and the F1 score of 87.93%, significantly outperforming other methods in the comparative experiments.

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Li, Jie, Shunli Wang, Shanshan Li, Pei Ge, Xiaohui Li, Wujun Ma, F. J. Zeller, Sai L. K. Hsam, and Yueming Yan. "Variations and classification of toxic epitopes related to celiac disease among α-gliadin genes from four Aegilops genomes." Genome 55, no. 7 (July 2012): 513–21. http://dx.doi.org/10.1139/g2012-038.

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The α-gliadins are associated with human celiac disease. A total of 23 noninterrupted full open reading frame α-gliadin genes and 19 pseudogenes were cloned and sequenced from C, M, N, and U genomes of four diploid Aegilops species. Sequence comparison of α-gliadin genes from Aegilops and Triticum species demonstrated an existence of extensive allelic variations in Gli-2 loci of the four Aegilops genomes. Specific structural features were found including the compositions and variations of two polyglutamine domains (QI and QII) and four T cell stimulatory toxic epitopes. The mean numbers of glutamine residues in the QI domain in C and N genomes and the QII domain in C, N, and U genomes were much higher than those in Triticum genomes, and the QI domain in C and N genomes and the QII domain in C, M, N, and U genomes displayed greater length variations. Interestingly, the types and numbers of four T cell stimulatory toxic epitopes in α-gliadins from the four Aegilops genomes were significantly less than those from Triticum A, B, D, and their progenitor genomes. Relationships between the structural variations of the two polyglutamine domains and the distributions of four T cell stimulatory toxic epitopes were found, resulting in the α-gliadin genes from the Aegilops and Triticum genomes to be classified into three groups.

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Dau, Hoan Manh, Ning Xu, and Tung Khac Truong. "A Survey of Using Weakly Supervised and Semi-Supervised for Cross-Domain Sentiment Classification." Advanced Materials Research 905 (April 2014): 637–41. http://dx.doi.org/10.4028/www.scientific.net/amr.905.637.

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Supervised machine learning techniques can analyze sentiment very effectively. However, in many languages, there are few appropriate data for training sentiment classifiers. Thus, they need a large corpus of training data. In this paper, weakly-supervised techniques using a large collection of unlabeled text to determine sentiment is presented. The performance of this method maybe less depends on the domain, topic and time period represented by the testing data. In addition, semi-supervised classification using a sentiment-sensitive thesaurus is mentioned. It can be applicable when it does not have any labeled data for a target domain but have some labeled data for other multiple domains designated as the source domains. This method can learn efficiently from multiple source domains. The results show that the weakly-supervised techniques are suitable for applications requiring sentiment classification across some domains and semi-supervised techniques can learn efficiently from multiple source domains.

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Dovhopiatyi, Oleksandr, and Evgeny Sevost'yanov. "On the application of one modulus inequality to the mapping theory." Proceedings of the Institute of Applied Mathematics and Mechanics NAS of Ukraine 37 (January 23, 2024): 104–17. http://dx.doi.org/10.37069/1683-4720-2023-37-10.

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The authors study mappings that satisfy some estimate of the distortion of the modulus of families of paths. Under certain conditions on the domains between which the mappings act, we established that, these mappings are Hölder logarithmic continuous at the boundary points. It is known that, the Hölder continuity is established for many classes of mappings, say quasiconformal and quasiregular mappings. In this regard, it is possible to point to the classical distortion estimates by Martio-Rickman-Väisälä type, as well as the estimates related to the modern classes of mappings with finite distortion. In particular, V.I. Ryazanov together with R.R. Salimov and E.O. Sevost'yanov established local distortion estimates for plane and spatial mappings under FMO condition, or under the Lehto-type integral condition. Recently, the second co-author have obtained Hölder logarithmic continuity for the studied class at points of the unit sphere. This article considers the situation of similar mappings of different domains, not only the unit sphere. Namely, we consider mappings between quasiextremal distance domains (QED-domains) and convex domains. Note that, quasiextremal distance domains introduced by Gehring and Martio are structures in which the modulus of families of paths is metrically related to the diameter of sets. Also, convex domains are involved in the formulation of the main result; we consider mappings that surjectively act onto them. In addition, the article contains the formulations and proofs for some other results on this topic. We consider several more cases in detail, in particular when: 1) the definition domain is a domain with a locally quasiconformal boundary, and the image domain is a bounded convex domain; 2) the definition domain is a regular domain in the sense of prime ends, and the image domain is a bounded convex domain; 3) the mapping acts between the QED-domain and the bounded convex domain and has a fixed point. In all three cases, the mapping is Hölder logarithmic continuous; moreover, in case 2), which refers to prime ends, logarithmic continuity should also be understood in terms of prime ends.

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Kurmayer, Rainer, Guntram Christiansen, Marlies Gumpenberger, and Jutta Fastner. "Genetic identification of microcystin ecotypes in toxic cyanobacteria of the genus Planktothrix." Microbiology 151, no. 5 (May 1, 2005): 1525–33. http://dx.doi.org/10.1099/mic.0.27779-0.

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Microcystins (MCs) are toxic heptapeptides which are synthesized by the filamentous cyanobacterium Planktothrix and other genera via non-ribosomal peptide synthesis. MCs share the common structure cyclo(-d-ala1-l-x2-d-erythro-β-iso-aspartic acid3-l-z4-adda5-d-Glu6-N-methyl-dehydroalanine7) [Adda; (2S, 3S, 8S, 9S)-3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6-dienoic acid], in which numerous MC variants have been reported. In general, the variation in structure is due to different amino acid residues in positions 7, 2 and 4 within the MC molecule, which are thought to be activated by the adenylation domains mcyAAd1, mcyBAd1 and mcyCAd, respectively. It was the aim of the study (i) to identify MC ecotypes that differed in the production of specific MC variants and (ii) to correlate the genetic variation within adenylation domains with the observed MC variants among 17 Planktothrix strains. Comparison of the sequences of mcyAAd1 revealed two distinctive Ad-genotypes differing in base pair composition and the insertion of an N-methyl transferase (NMT) domain. The mcyAAd1 genotype with NMT (2854 bp) correlated with N-methyl-dehydroalanine and the mcyAAd1 genotype without NMT (1692 bp) correlated with dehydrobutyrine in position 7. Within mcyBAd1, a lower genetic variation (0–4 %) and an exclusive correlation between one Ad-genotype and homotyrosine as well as another Ad-genotype and arginine in position 2 was found. The sequences of mcyCAd were found to be highly similar (0–1 % dissimilarity) and all strains contained arginine in position 4. The results on adenylation domain polymorphism do provide insights into the evolutionary origin of adenylation domains in Planktothrix and may be combined with ecological research in order to provide clues about the abundance of genetically defined MC ecotypes in nature.

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Jepson, Marie, Angela Howells, Helen L. Bullifent, Barbara Bolgiano, Dennis Crane, Julie Miller, Jane Holley, Pramukh Jayasekera, and Richard W. Titball. "Differences in the Carboxy-Terminal (Putative Phospholipid Binding) Domains of Clostridium perfringens andClostridium bifermentans Phospholipases C Influence the Hemolytic and Lethal Properties of These Enzymes." Infection and Immunity 67, no. 7 (July 1, 1999): 3297–301. http://dx.doi.org/10.1128/iai.67.7.3297-3301.1999.

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ABSTRACT The phospholipases C of C. perfringens (alpha-toxin) and C. bifermentans (Cbp) show >50% amino acid homology but differ in their hemolytic and toxic properties. We report here the purification and characterisation of alpha-toxin and Cbp. The phospholipase C activity of alpha-toxin and Cbp was similar when tested with phosphatidylcholine in egg yolk or in liposomes. However, the hemolytic activity of alpha-toxin was more than 100-fold that of Cbp. To investigate whether differences in the carboxy-terminal domains of these proteins were responsible for differences in the hemolytic and toxic properties, a hybrid protein (NbiCα) was constructed comprising the N domain of Cbp and the C domain of alpha-toxin. The hemolytic activity of NbiCαwas 10-fold that of Cbp, and the hybrid enzyme was toxic. These results confirm that the C-terminal domain of these proteins confers different properties on the enzymatically active N-terminal domain of these proteins.

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Seemakurthy, Karthik, Charles Fox, Erchan Aptoula, and Petra Bosilj. "Domain Generalised Faster R-CNN." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 2 (June 26, 2023): 2180–90. http://dx.doi.org/10.1609/aaai.v37i2.25312.

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Domain generalisation (i.e. out-of-distribution generalisation) is an open problem in machine learning, where the goal is to train a model via one or more source domains, that will generalise well to unknown target domains. While the topic is attracting increasing interest, it has not been studied in detail in the context of object detection. The established approaches all operate under the covariate shift assumption, where the conditional distributions are assumed to be approximately equal across source domains. This is the first paper to address domain generalisation in the context of object detection, with a rigorous mathematical analysis of domain shift, without the covariate shift assumption. We focus on improving the generalisation ability of object detection by proposing new regularisation terms to address the domain shift that arises due to both classification and bounding box regression. Also, we include an additional consistency regularisation term to align the local and global level predictions. The proposed approach is implemented as a Domain Generalised Faster R-CNN and evaluated using four object detection datasets which provide domain metadata (GWHD, Cityscapes, BDD100K, Sim10K) where it exhibits a consistent performance improvement over the baselines. All the codes for replicating the results in this paper can be found at https://github.com/karthikiitm87/domain-generalisation.git

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Narbona, Javier, Luisa Hernández-Baraza, Rubén G. Gordo, Laura Sanz, and Javier Lacadena. "Nanobody-Based EGFR-Targeting Immunotoxins for Colorectal Cancer Treatment." Biomolecules 13, no. 7 (June 26, 2023): 1042. http://dx.doi.org/10.3390/biom13071042.

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Immunotoxins (ITXs) are chimeric molecules that combine the specificity of a targeting domain, usually derived from an antibody, and the cytotoxic potency of a toxin, leading to the selective death of tumor cells. However, several issues must be addressed and optimized in order to use ITXs as therapeutic tools, such as the selection of a suitable tumor-associated antigen (TAA), high tumor penetration and retention, low kidney elimination, or low immunogenicity of foreign proteins. To this end, we produced and characterized several ITX designs, using a nanobody against EGFR (VHH 7D12) as the targeting domain. First, we generated a nanoITX, combining VHH 7D12 and the fungal ribotoxin α-sarcin (αS) as the toxic moiety (VHHEGFRαS). Then, we incorporated a trimerization domain (TIEXVIII) into the construct, obtaining a trimeric nanoITX (TriVHHEGFRαS). Finally, we designed and characterized a bispecific ITX, combining the VHH 7D12 and the scFv against GPA33 as targeting domains, and a deimmunized (DI) variant of α-sarcin (BsITXαSDI). The results confirm the therapeutic potential of α-sarcin-based nanoITXs. The incorporation of nanobodies as target domains improves their therapeutic use due to their lower molecular size and binding features. The enhanced avidity and toxic load in the trimeric nanoITX and the combination of two different target domains in the bispecific nanoITX allow for increased antitumor effectiveness.

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Jin, Jian, Qian Geng, Haikun Mou, and Chong Chen. "Author–Subject–Topic model for reviewer recommendation." Journal of Information Science 45, no. 4 (October 19, 2018): 554–70. http://dx.doi.org/10.1177/0165551518806116.

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Interdisciplinary studies are becoming increasingly popular, and research domains of many experts are becoming diverse. This phenomenon brings difficulty in recommending experts to review interdisciplinary submissions. In this study, an Author–Subject–Topic (AST) model is proposed with two versions. In the model, reviewers’ subject information is embedded to analyse topic distributions of submissions and reviewers’ publications. The major difference between the AST and Author–Topic models lies in the introduction of a ‘Subject’ layer, which supervises the generation of hierarchical topics and allows sharing of subjects among authors. To evaluate the performance of the AST model, papers in Information System and Management (a typical interdisciplinary domain) in a famous Chinese academic library are investigated. Comparative experiments are conducted, which show the effectiveness of the AST model in topic distribution analysis and reviewer recommendation for interdisciplinary studies.

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Shaukat, Kamran, Ibrahim A Hameed, Suhuai Luo, Imran Javed, Farhat Iqbal, Amber Faisal, Rabia Masood, et al. "Domain Specific Lexicon Generation through Sentiment Analysis." International Journal of Emerging Technologies in Learning (iJET) 15, no. 09 (May 15, 2020): 190. http://dx.doi.org/10.3991/ijet.v15i09.13109.

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Sentiment analysis (SA) is used to extract opinions from a huge amount of data and these opinions are comprised of multiple words. Some words have different semantic meanings in different fields and we call them domain specific (DS) words. A domain is defined as a special area in which a collection of queries about a specific topic are held when user do queries in the data regarding the domain appear. But Single word can be interpreted in many ways based on its context-dependency. Demonstrate each word under its domain is extremely important because their meanings differ from each other so much in different domains that a word meaning from A in one context can change into Z in another context or domain. The purpose of this research is to discover the correct sentiment in the message or comment and evaluate it either it is positive, negative or neutral. We collected tweets dataset from different domains and analyze it to extract words that have a different definition in those specific domains as if they are used in other fields of life they would be defined differently. We analyzed 52115 words for finding their DS meaning in seven different domains. Polarity had been given to words of the dataset according to their domains and based on this polarity they have been recognized as positive negative and neutral and evaluated as domain-specific words. The automatic way is used to extract the words of the domain as we integrated and afterward the comparison to identify that either this word differs from other words as far as domain is concerned. This research contribution is a prototype that processes your data and extracts their domain-specific words automatically. This research improved the knowledge about the context-dependency and found the core-specific meanings of words in multiple fields.

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Zaitseva, Jelena, Daniel Vaknin, Christian Krebs, James Doroghazi, Sara L. Milam, Deepa Balasubramanian, Nicholas B. Duck, and Joerg Freigang. "Structure–function characterization of an insecticidal protein GNIP1Aa, a member of an MACPF and β-tripod families." Proceedings of the National Academy of Sciences 116, no. 8 (February 6, 2019): 2897–906. http://dx.doi.org/10.1073/pnas.1815547116.

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The crystal structure of the Gram-negative insecticidal protein, GNIP1Aa, has been solved at 2.5-Å resolution. The protein consists of two structurally distinct domains, a MACPF (membrane attack complex/PerForin) and a previously uncharacterized type of domain. GNIP1Aa is unique in being a prokaryotic MACPF member to have both its structure and function identified. It was isolated from aChromobacterium piscinaestrain and is specifically toxic toDiabrotica virgifera virgiferalarvae upon feeding. In members of the MACPF family, the MACPF domain has been shown to be important for protein oligomerization and formation of transmembrane pores, while accompanying domains define the specificity of the target of the toxicity. In GNIP1Aa the accompanying C-terminal domain has a unique fold composed of three pseudosymmetric subdomains with shared sequence similarity, a feature not obvious from the initial sequence examination. Our analysis places this domain into a protein family, named here β-tripod. Using mutagenesis, we identified functionally important regions in the β-tripod domain, which may be involved in target recognition.

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Tanveer, Muhammad Hassan, Zainab Fatima, Shehnila Zardari, and David Guerra-Zubiaga. "An In-Depth Analysis of Domain Adaptation in Computer and Robotic Vision." Applied Sciences 13, no. 23 (November 29, 2023): 12823. http://dx.doi.org/10.3390/app132312823.

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This review article comprehensively delves into the rapidly evolving field of domain adaptation in computer and robotic vision. It offers a detailed technical analysis of the opportunities and challenges associated with this topic. Domain adaptation methods play a pivotal role in facilitating seamless knowledge transfer and enhancing the generalization capabilities of computer and robotic vision systems. Our methodology involves systematic data collection and preparation, followed by the application of diverse assessment metrics to evaluate the efficacy of domain adaptation strategies. This study assesses the effectiveness and versatility of conventional, deep learning-based, and hybrid domain adaptation techniques within the domains of computer and robotic vision. Through a cross-domain analysis, we scrutinize the performance of these approaches in different contexts, shedding light on their strengths and limitations. The findings gleaned from our evaluation of specific domains and models offer valuable insights for practical applications while reinforcing the validity of the proposed methodologies.

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Gregory, Kyle S., Otsile O. Mojanaga, Sai Man Liu, and K. Ravi Acharya. "Crystal Structures of Botulinum Neurotoxin Subtypes A4 and A5 Cell Binding Domains in Complex with Receptor Ganglioside." Toxins 14, no. 2 (February 8, 2022): 129. http://dx.doi.org/10.3390/toxins14020129.

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Botulinum neurotoxins (BoNT) cause the potentially fatal neuroparalytic disease botulism that arises due to proteolysis of a SNARE protein. Each BoNT is comprised of three domains: a cell binding domain (HC), a translocation domain (HN), and a catalytic (Zn2+ endopeptidase) domain (LC). The HC is responsible for neuronal specificity by targeting both a protein and ganglioside receptor at the neuromuscular junction. Although highly toxic, some BoNTs are commercially available as therapeutics for the treatment of a range of neuromuscular conditions. Here we present the crystal structures of two BoNT cell binding domains, HC/A4 and HC/A5, in a complex with the oligosaccharide of ganglioside, GD1a and GM1b, respectively. These structures, along with a detailed comparison with the previously reported apo-structures, reveal the conformational changes that occur upon ganglioside binding and the interactions involved.

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Solimene, Raffaele, Maria Antonia Maisto, Giuseppe Romeo, and Rocco Pierri. "On the Singular Spectrum of the Radiation Operator for Multiple and Extended Observation Domains." International Journal of Antennas and Propagation 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/585238.

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The problem of studying how spatial diversity impacts on the spectrum (singular values) of the radiation operator is addressed. This topic is of great importance because of its connection with the so-called number of degrees of freedom concept which in turn is a key parameter in inverse source problems as well as to the problem of transmitting information by waves from a source domain to an observation domain. The case of a bounded rectilinear source with the radiated field observed over multiple bounded rectilinear domains parallel to the source is considered. Then, the analysis is generalized to two-dimensional extended observation domains. Analytical arguments are developed to estimate the pertinent singular value behavior. This allows highlighting the way observation domain features affect spectrum behavior. Numerical examples are shown to support the analytical results.

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Flemming, Dirk, Phillip Sarges, Philipp Stelter, Andrea Hellwig, Bettina Böttcher, and Ed Hurt. "Two structurally distinct domains of the nucleoporin Nup170 cooperate to tether a subset of nucleoporins to nuclear pores." Journal of Cell Biology 185, no. 3 (May 4, 2009): 387–95. http://dx.doi.org/10.1083/jcb.200810016.

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How individual nucleoporins (Nups) perform their role in nuclear pore structure and function is largely unknown. In this study, we examined the structure of purified Nup170 to obtain clues about its function. We show that Nup170 adopts a crescent moon shape with two structurally distinct and separable domains, a β-propeller N terminus and an α-solenoid C terminus. To address the individual roles of each domain, we expressed these domains separately in yeast. Notably, overexpression of the Nup170 C domain was toxic in nup170Δ cells and caused accumulation of several Nups in cytoplasmic foci. Further experiments indicated that the C-terminal domain anchors Nup170 to nuclear pores, whereas the N-terminal domain functions to recruit or retain a subset of Nups, including Nup159, Nup188, and Pom34, at nuclear pores. We conclude that Nup170 performs its role as a structural adapter between cytoplasmically oriented Nups and the nuclear pore membrane.

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Liu, Jiahui, Larry Birnbaum, and Bryan Pardo. "Spectrum: Retrieving Different Points of View from the Blogosphere." Proceedings of the International AAAI Conference on Web and Social Media 3, no. 1 (March 19, 2009): 114–21. http://dx.doi.org/10.1609/icwsm.v3i1.13953.

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Blogs have become an important medium for people to publish opinions and ideas on the web. Bloggers with interest and expertise in specific domains (e.g., politics, or technology) often create and maintain blogs to publish news, opinions and ideas about those domains. In this paper, we present Spectrum, a novel blog search system that enables users to search for different points of view related to a topic from the blogosphere. Given a topic, Spectrum retrieves blog posts from bloggers with interests and expertise in various domains, enabling users to browse and compare the opinions related to different aspects of the topic. To identify bloggers in a domain category, we propose a two-layer classification model that predicts bloggers’ interests based on short snippets of posts by the blogger and posts citing the blogger. The model characterizes the recurrent interests of bloggers and the importance of the bloggers in the domain. Experiments were conducted on a list of bloggers collected from blog directories, with their snippets collected from Google Blog Search. Categorization of bloggers’ interests achieves precision of 88.4% and recall of 84.5% by micro-averaging over all the categories, outperforming a baseline algorithm which directly classifies the bloggers’ snippets. We further apply this multi-perspective blog search to explore the ecological relationship between news and blogs. The system aggregates recent popular news stories and then automatically aggregates different points of view about those news stories in the blogosphere.

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de Maagd, Ruud A., Mieke Weemen-Hendriks, Willem Stiekema, and Dirk Bosch. "Bacillus thuringiensis Delta-Endotoxin Cry1C Domain III Can Function as a Specificity Determinant forSpodoptera exigua in Different, but Not All, Cry1-Cry1C Hybrids." Applied and Environmental Microbiology 66, no. 4 (April 1, 2000): 1559–63. http://dx.doi.org/10.1128/aem.66.4.1559-1563.2000.

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ABSTRACT In order to test our hypothesis that Bacillus thuringiensis delta-endotoxin Cry1Ca domain III functions as a determinant of specificity for Spodoptera exigua, regardless of the origins of domains I and II, we have constructed by cloning and in vivo recombination a collection of hybrid proteins containing domains I and II of various Cry1 toxins combined with domain III of Cry1Ca. Cry1Ab, Cry1Ac, Cry1Ba, Cry1Ea, and Cry1Fa all become more active against S. exigua when their domain III is replaced by (part of) that of Cry1Ca. This result shows that domain III of Cry1Ca is an important and versatile determinant of S. exigua specificity. The toxicity of the hybrids varied by a factor of 40, indicating that domain I and/or II modulate the activity as well. Cry1Da-Cry1Ca hybrids were an exception in that they were not significantly active against S. exigua or Manduca sexta, whereas both parental proteins were highly toxic. Incidentally, in a Cry1Ba-Cry1Ca hybrid, Cry1Ca domain III can also strongly increase toxicity for M. sexta.

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Whitley, Paul, and Ismael Mingarro. "Stitching proteins into membranes, not sew simple." Biological Chemistry 395, no. 12 (December 1, 2014): 1417–24. http://dx.doi.org/10.1515/hsz-2014-0205.

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Abstract Most integral membrane proteins located within the endomembrane system of eukaryotic cells are first assembled co-translationally into the endoplasmic reticulum (ER) before being sorted and trafficked to other organelles. The assembly of membrane proteins is mediated by the ER translocon, which allows passage of lumenal domains through and lateral integration of transmembrane (TM) domains into the ER membrane. It may be convenient to imagine multi-TM domain containing membrane proteins being assembled by inserting their first TM domain in the correct orientation, with subsequent TM domains inserting with alternating orientations. However a simple threading model of assembly, with sequential insertion of one TM domain into the membrane after another, does not universally stand up to scrutiny. In this article we review some of the literature illustrating the complexities of membrane protein assembly. We also present our own thoughts on aspects that we feel are poorly understood. In short we hope to convince the readers that threading of membrane proteins into membranes is ‘not sew simple’ and a topic that requires further investigation.

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Xia, Lixin, Zhongyi Wang, Chen Chen, and Shanshan Zhai. "Research on feature-based opinion mining using topic maps." Electronic Library 34, no. 3 (June 6, 2016): 435–56. http://dx.doi.org/10.1108/el-11-2014-0197.

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Purpose Opinion mining (OM), also known as “sentiment classification”, which aims to discover common patterns of user opinions from their textual statements automatically or semi-automatically, is not only useful for customers, but also for manufacturers. However, because of the complexity of natural language, there are still some problems, such as domain dependence of sentiment words, extraction of implicit features and others. The purpose of this paper is to propose an OM method based on topic maps to solve these problems. Design/methodology/approach Domain-specific knowledge is key to solve problems in feature-based OM. On the one hand, topic maps, as an ontology framework, are composed of topics, associations, occurrences and scopes, and can represent a class of knowledge representation schemes. On the other hand, compared with ontology, topic maps have many advantages. Thus, it is better to integrate domain-specific knowledge into OM based on topic maps. This method can make full use of the semantic relationships among feature words and sentiment words. Findings In feature-level OM, most of the existing research associate product features and opinions by their explicit co-occurrence, or use syntax parsing to judge the modification relationship between opinion words and product features within a review unit. They are mostly based on the structure of language units without considering domain knowledge. Only few methods based on ontology incorporate domain knowledge into feature-based OM, but they only use the “is-a” relation between concepts. Therefore, this paper proposes feature-based OM using topic maps. The experimental results revealed that this method can improve the accuracy of the OM. The findings of this study not only advance the state of OM research but also shed light on future research directions. Research limitations/implications To demonstrate the “feature-based OM using topic maps” applications, this work implements a prototype that helps users to find their new washing machines. Originality/value This paper presents a new method of feature-based OM using topic maps, which can integrate domain-specific knowledge into feature-based OM effectively. This method can improve the accuracy of the OM greatly. The proposed method can be applied across various application domains, such as e-commerce and e-government.

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Yao, Huifeng, Xiaowei Hu, and Xiaomeng Li. "Enhancing Pseudo Label Quality for Semi-supervised Domain-Generalized Medical Image Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (June 28, 2022): 3099–107. http://dx.doi.org/10.1609/aaai.v36i3.20217.

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Generalizing the medical image segmentation algorithms to unseen domains is an important research topic for computer-aided diagnosis and surgery. Most existing methods require a fully labeled dataset in each source domain. Although some researchers developed a semi-supervised domain generalized method, it still requires the domain labels. This paper presents a novel confidence-aware cross pseudo supervision algorithm for semi-supervised domain generalized medical image segmentation. The main goal is to enhance the pseudo label quality for unlabeled images from unknown distributions. To achieve it, we perform the Fourier transformation to learn low-level statistic information across domains and augment the images to incorporate cross-domain information. With these augmentations as perturbations, we feed the input to a confidence-aware cross pseudo supervision network to measure the variance of pseudo labels and regularize the network to learn with more confident pseudo labels. Our method sets new records on public datasets, i.e., M&Ms and SCGM. Notably, without using domain labels, our method surpasses the prior art that even uses domain labels by 11.67% on Dice on M&Ms dataset with 2% labeled data. Code is available at https://github.com/XMed-Lab/EPL SemiDG.

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Dhanal, Radhika Jinendra, and Vijay Ram Ghorpade. "Aspect term extraction from multi-source domain using enhanced latent Dirichlet allocation." Indonesian Journal of Electrical Engineering and Computer Science 35, no. 1 (July 1, 2024): 475. http://dx.doi.org/10.11591/ijeecs.v35.i1.pp475-484.

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This study presents a comprehensive exploration of sentiment analysis across diverse domains through the introduction of a multi-source domain dataset encompassing hospitals, laptops, restaurants, cell phones, and electronics. Leveraging this extensive dataset, an enhanced latent Dirichlet allocation (E-LDA) model is proposed for topic modeling and aspect extraction, demonstrating superior performance with a remarkable coherence score of 0.5727. Comparative analyses with traditional LDA and other existing models showcase the efficacy of E-LDA in capturing sentiments and specific attributes within different domains. The extracted topics and aspects reveal valuable insights into domain-specific sentiments and aspects, contributing to the advancement of sentiment analysis methodologies. The findings underscore the significance of considering multi-source datasets for a more holistic understanding of sentiment in diverse text corpora.

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Pan, Boxiao, Zhangjie Cao, Ehsan Adeli, and Juan Carlos Niebles. "Adversarial Cross-Domain Action Recognition with Co-Attention." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 11815–22. http://dx.doi.org/10.1609/aaai.v34i07.6854.

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Action recognition has been a widely studied topic with a heavy focus on supervised learning involving sufficient labeled videos. However, the problem of cross-domain action recognition, where training and testing videos are drawn from different underlying distributions, remains largely under-explored. Previous methods directly employ techniques for cross-domain image recognition, which tend to suffer from the severe temporal misalignment problem. This paper proposes a Temporal Co-attention Network (TCoN), which matches the distributions of temporally aligned action features between source and target domains using a novel cross-domain co-attention mechanism. Experimental results on three cross-domain action recognition datasets demonstrate that TCoN improves both previous single-domain and cross-domain methods significantly under the cross-domain setting.

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Williams, Ernest, Tsvetan Bachvaroff, and Allen Place. "Dinoflagellate Phosphopantetheinyl Transferase (PPTase) and Thiolation Domain Interactions Characterized Using a Modified Indigoidine Synthesizing Reporter." Microorganisms 10, no. 4 (March 23, 2022): 687. http://dx.doi.org/10.3390/microorganisms10040687.

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Photosynthetic dinoflagellates synthesize many toxic but also potential therapeutic compounds therapeutics via polyketide/non-ribosomal peptide synthesis, a common means of producing natural products in bacteria and fungi. Although canonical genes are identifiable in dinoflagellate transcriptomes, the biosynthetic pathways are obfuscated by high copy numbers and fractured synteny. This study focuses on the carrier domains that scaffold natural product synthesis (thiolation domains) and the phosphopantetheinyl transferases (PPTases) that thiolate these carriers. We replaced the thiolation domain of the indigoidine producing BpsA gene from Streptomyces lavendulae with those of three multidomain dinoflagellate transcripts and coexpressed these constructs with each of three dinoflagellate PPTases looking for specific pairings that would identify distinct pathways. Surprisingly, all three PPTases were able to activate all the thiolation domains from one transcript, although with differing levels of indigoidine produced, demonstrating an unusual lack of specificity. Unfortunately, constructs with the remaining thiolation domains produced almost no indigoidine and the thiolation domain for lipid synthesis could not be expressed in E. coli. These results combined with inconsistent protein expression for different PPTase/thiolation domain pairings present technical hurdles for future work. Despite these challenges, expression of catalytically active dinoflagellate proteins in E. coli is a novel and useful tool going forward.

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Journal articles on the topic 'Toric domains'

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