Relevant bibliographies by topics / Novel class discovery

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Novel class discovery'

Author: Grafiati
Published: 9 November 2024

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Journal articles on the topic "Novel class discovery"

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Chen, Guangyao, Peixi Peng, Yangru Huang, Mengyue Geng, and Yonghong Tian. "Adaptive Discovering and Merging for Incremental Novel Class Discovery." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 10 (March 24, 2024): 11276–84. http://dx.doi.org/10.1609/aaai.v38i10.29006.

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One important desideratum of lifelong learning aims to discover novel classes from unlabelled data in a continuous manner. The central challenge is twofold: discovering and learning novel classes while mitigating the issue of catastrophic forgetting of established knowledge. To this end, we introduce a new paradigm called Adaptive Discovering and Merging (ADM) to discover novel categories adaptively in the incremental stage and integrate novel knowledge into the model without affecting the original knowledge. To discover novel classes adaptively, we decouple representation learning and novel class discovery, and use Triple Comparison (TC) and Probability Regularization (PR) to constrain the probability discrepancy and diversity for adaptive category assignment. To merge the learned novel knowledge adaptively, we propose a hybrid structure with base and novel branches named Adaptive Model Merging (AMM), which reduces the interference of the novel branch on the old classes to preserve the previous knowledge, and merges the novel branch to the base model without performance loss and parameter growth. Extensive experiments on several datasets show that ADM significantly outperforms existing class-incremental Novel Class Discovery (class-iNCD) approaches. Moreover, our AMM also benefits the class-incremental Learning (class-IL) task by alleviating the catastrophic forgetting problem. The source code is included in the supplementary materials.
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Dandliker, Peter J., Steve D. Pratt, Angela M. Nilius, Candace Black-Schaefer, Xiaoan Ruan, Danli L. Towne, Richard F. Clark, et al. "Novel Antibacterial Class." Antimicrobial Agents and Chemotherapy 47, no. 12 (December 2003): 3831–39. http://dx.doi.org/10.1128/aac.47.12.3831-3839.2003.

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ABSTRACT We report the discovery and characterization of a novel ribosome inhibitor (NRI) class that exhibits selective and broad-spectrum antibacterial activity. Compounds in this class inhibit growth of many gram-positive and gram-negative bacteria, including the common respiratory pathogens Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus, and Moraxella catarrhalis, and are nontoxic to human cell lines. The first NRI was discovered in a high-throughput screen designed to identify inhibitors of cell-free translation in extracts from S. pneumoniae. The chemical structure of the NRI class is related to antibacterial quinolones, but, interestingly, the differences in structure are sufficient to completely alter the biochemical and intracellular mechanisms of action. Expression array studies and analysis of NRI-resistant mutants confirm this difference in intracellular mechanism and provide evidence that the NRIs inhibit bacterial protein synthesis by inhibiting ribosomes. Furthermore, compounds in the NRI series appear to inhibit bacterial ribosomes by a new mechanism, because NRI-resistant strains are not cross-resistant to other ribosome inhibitors, such as macrolides, chloramphenicol, tetracycline, aminoglycosides, or oxazolidinones. The NRIs are a promising new antibacterial class with activity against all major drug-resistant respiratory pathogens.
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Wang, Weishuai, Ting Lei, Qingchao Chen, and Yang Liu. "Semantic-Guided Novel Category Discovery." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 6 (March 24, 2024): 5607–14. http://dx.doi.org/10.1609/aaai.v38i6.28371.

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The Novel Category Discovery problem aims to cluster an unlabeled set with the help of a labeled set consisting of disjoint but related classes. However, existing models treat class names as discrete one-hot labels and ignore the semantic understanding of these classes. In this paper, we propose a new setting named Semantic-guided Novel Category Discovery (SNCD), which requires the model to not only cluster the unlabeled images but also semantically recognize these images based on a set of their class names. The first challenge we confront pertains to effectively leveraging the class names of unlabeled images, given the inherent gap between the visual and linguistic domains. To address this issue, we incorporate a semantic-aware recognition mechanism. This is achieved by constructing dynamic class-wise visual prototypes as well as a semantic similarity matrix that enables the projection of visual features into the semantic space. The second challenge originates from the granularity disparity between the classification and clustering tasks. To deal with this, we develop a semantic-aware clustering process to facilitate the exchange of knowledge between the two tasks. Through extensive experiments, we demonstrate the mutual benefits of the recognition and clustering tasks, which can be jointly optimized. Experimental results on multiple datasets confirm the effectiveness of our proposed method. Our code is available at https://github.com/wang-weishuai/Semantic-guided-NCD.
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Shinozuka, Tsuyoshi, Shuichiro Ito, Takako Kimura, Masanori Izumi, and Kenji Wakabayashi. "Discovery of a Novel Class of ERRα Agonists." ACS Medicinal Chemistry Letters 12, no. 5 (April 21, 2021): 817–21. http://dx.doi.org/10.1021/acsmedchemlett.1c00100.

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Cubitt, Jonathan, Mari Davies, Ross Riseley, Gabrielle Evans, Sian E. Gardiner, Benson M. Kariuki, Simon E. Ward, Emyr Lloyd-Evans, Helen Waller-Evans, and D. Heulyn Jones. "Beware of N-Benzoyloxybenzamides." Molecules 29, no. 21 (October 31, 2024): 5143. http://dx.doi.org/10.3390/molecules29215143.

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Following a High-Throughput Screening campaign to discover inhibitors of acid ceramidase, we report the novel and extremely potent covalent inhibitor, 1. Following resynthesis and stability monitoring, we discovered that 1 is chemically unstable and reacts with DMSO at room temperature. This mode of decomposition is likely general for this class of compound, and we urge caution for their use in drug discovery research.
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Feng, Juexiao, Yuhong Yang, Yanchun Xie, Yaqian Li, Yandong Guo, Yuchen Guo, Yuwei He, Liuyu Xiang, and Guiguang Ding. "Debiased Novel Category Discovering and Localization." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 2 (March 24, 2024): 1753–60. http://dx.doi.org/10.1609/aaai.v38i2.27943.

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In recent years, object detection in deep learning has experienced rapid development. However, most existing object detection models perform well only on closed-set datasets, ignoring a large number of potential objects whose categories are not defined in the training set. These objects are often identified as background or incorrectly classified as pre-defined categories by the detectors. In this paper, we focus on the challenging problem of Novel Class Discovery and Localization (NCDL), aiming to train detectors that can detect the categories present in the training data, while also actively discover, localize, and cluster new categories. We analyze existing NCDL methods and identify the core issue: object detectors tend to be biased towards seen objects, and this leads to the neglect of unseen targets. To address this issue, we first propose an Debiased Region Mining (DRM) approach that combines class-agnostic Region Proposal Network (RPN) and class-aware RPN in a complementary manner. Additionally, we suggest to improve the representation network through semi-supervised contrastive learning by leveraging unlabeled data. Finally, we adopt a simple and efficient mini-batch K-means clustering method for novel class discovery. We conduct extensive experiments on the NCDL benchmark, and the results demonstrate that the proposed DRM approach significantly outperforms previous methods, establishing a new state-of-the-art.
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Shearer, Barry G., Hari S. Patel, Andrew N. Billin, James M. Way, Deborah A. Winegar, Millard H. Lambert, Robert X. Xu, et al. "Discovery of a novel class of PPARδ partial agonists." Bioorganic & Medicinal Chemistry Letters 18, no. 18 (September 2008): 5018–22. http://dx.doi.org/10.1016/j.bmcl.2008.08.011.

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Cheleski, Juliana, Josmar R. Rocha, Matheus P. Pinheiro, Helton José Wiggers, Albérico B. F. da Silva, Maria C. Nonato, and Carlos A. Montanari. "Novel insights for dihydroorotate dehydrogenase class 1A inhibitors discovery." European Journal of Medicinal Chemistry 45, no. 12 (December 2010): 5899–909. http://dx.doi.org/10.1016/j.ejmech.2010.09.055.

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Fukunaga, Alex S. "Automated Discovery of Local Search Heuristics for Satisfiability Testing." Evolutionary Computation 16, no. 1 (March 2008): 31–61. http://dx.doi.org/10.1162/evco.2008.16.1.31.

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The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey.
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Hilgeroth, Andreas, Marc Hemmer, Sebastian Neuber, Josef Molnar, and Hermann Lage. "Discovery of 9,10-Dihydroacridines as Novel Class of ABCB1 Inhibitors." Medicinal Chemistry 11, no. 4 (April 29, 2015): 329–35. http://dx.doi.org/10.2174/1573406410666141111100720.

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Dissertations / Theses on the topic "Novel class discovery"

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Troisemaine, Colin. "Novel class discovery in tabular data : an application to network fault diagnosis." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2024. http://www.theses.fr/2024IMTA0422.

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Cette thèse porte sur la découverte de nouvelles classes dans le contexte de données tabulaires. Le problème de Novel Class Discovery (NCD) consiste à extraire d’un ensemble étiqueté de classes déjà connues des connaissances qui permettront de partitionner plus précisément un ensemble non étiqueté de nouvelles classes. Bien que le NCD ait récemment fait l’objet d’une grande attention de la part de la communauté, il est généralement résolu sur des problèmes de vision par ordinateur et parfois dans des conditions irréalistes. En particulier, le nombre de nouvelles classes est souvent supposé étant connu à l’avance, et leurs étiquettes sont parfois utilisées pour ajuster les hyperparamètres. Les méthodes qui reposent sur ces hypothèses ne sont pas applicables aux scénarios du monde réel. C’est pourquoi dans cette thèse nous nous concentrons sur la résolution de découverte dans les données tabulaires lorsqu’aucune connaissance a priori n’est disponible. Les méthodes développées au cours de la thèse sont appliquées à un cas réel : le diagnostic automatique des pannes dans les réseaux de télécommunication, spécifiquement les réseaux d’accès à fibre optique. Le but est d’avoir une gestion efficace des pannes, en particulier au stade du diagnostic lorsque des pannes inconnues (nouvelles classes) peuvent apparaitre
This thesis focuses on Novel Class Discovery (NCD) in the context of tabular data. The Novel Class Discovery problem consists in extracting knowledge from a labeled set of already known classes in order to more accurately partition an unlabeled set of new classes. Although NCD has recently received a lot of of attention from the community, it is generally addressed in computer vision problems and sometimes under unrealistic conditions. In particular, the number of novel classes is often assumed to be known in advance, and their labels are sometimes used to tune hyperparameters. Methods based on these assumptions are not applicable to realworld scenarios. Thus, in this thesis we focus on discovery resolution in tabular data when no a priori knowledge is available. The methods developed in the thesis are applied to a real-world case: automatic fault diagnosis in telecommunication networks, with a focus on fiber optic access networks. The aim is to achieve efficient fault management, particularly at the diagnosis stage when unknown faults (new classes) may appear
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Ordway, Gregory A. "Discovery of a New Biological Target for the Development of a Novel Class of Antidepressant Drugs." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/8655.

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Parker, Mackenzie James. "Discovery and investigation of the novel overall activity allosteric regulation of the Bacillus subtilis class Ib ribonucleotide reductase." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/109681.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemistry, 2017.
Page 490 blank. Cataloged from PDF version of thesis.
Includes bibliographical references.
Ribonucleotide reductases (RNRs) catalyze the reduction of nucleotides to 2'-deoxynucleotides in all organisms. Class lb RNRs consist of two subunits: a houses the catalytic and allosteric effector binding sites, and p houses a catalytically essential dimanganic-tyrosyl radical (Mn(III)2-Y*). The allosteric regulation of lb RNR activity has only been studied with the Salmonella enterica enzyme, which exhibits substrate specificity allosteric regulation by ATP and 2'-deoxynucleoside 5'-triphosphates (dNTPs), but not overall activity regulation by ATP and dATP. However, the S. enterica enzyme is not a good general model for Ib RNRs because it is not essential under most growth conditions, including pathogenesis. Other bacteria pathogenic to humans utilize lb RNRs as their sole source of dNTPs for DNA replication and repair. As RNR regulation plays a critical role in the high fidelity of these processes, the allosteric regulation of lb RNRs used as the primary dNTP supplier for a bacterium should be distinct from the S. enterica enzyme and, therefore, could provide a potential target for therapeutic development. Herein, the results of characterizing the allosteric regulation of the Ib RNR from the model organism Bacillus subtilis are presented. To facilitate these studies, we identified, cloned, and isolated the physiological reductant for RNR (thioredoxin/thioredoxin reductase/NADPH), thus allowing us to monitor activity spectrophotometrically. We discovered the effector dATP was a potent inhibitor of enzymatic activity at physiologically relevant concentrations, thereby demonstrating the first example of overall activity allosteric regulation in a class lb system. In other RNRs, overall activity regulation is mediated by a domain called the ATP-cone. This domain is absent from the B. subtilis enzyme; therefore, the inhibition represents a new mechanism of overall activity regulation. Analytical ultracentrifugation studies suggest dATP inhibition may be mediated by formation of large protein complexes. Biophysical studies also led to the discovery of tightly bound dAMP associated with a that increases the susceptibility of RNR to dATP inhibition. The potential physiological importance of dAMP is supported by studies examining YmaB, the unique fourth member of the B. subtilis RNR operon, which revealed this enzyme can hydrolyze dATP into dAMP and pyrophosphate and, therefore, might insert dAMP into a.
by Mackenzie James Parker.
Ph. D.
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Books on the topic "Novel class discovery"

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Stanton, Benjamin Z. Discovery and mechanistic characterization of a novel class of sonic hedgehog inhibitors. 2009.

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Yang, Jimmy Chen. Discovery, synthesis, and steps toward target identification of the novel 2-amino-3-hydroxyindole anti-malaria drug class. 2009.

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Coqueiro, Wilma dos Santos. Poéticas do deslocamento: O Bildungsroman de autoria feminina contemporânea. Brazil Publishing, 2021. http://dx.doi.org/10.31012/978-65-5861-338-1.

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The novel as a great socio-literary institution, which projects the ideals of bourgeois class, becomes the maximum expression of modernity from the 18th century on. The genre, characterized by its malleability and ambivalence, reflects an individualistic and innovative orientation. In this sense, the novels of characters originate subtypes, as the Bildungsroman, whose paradigmatic model would be Wilhelm Meister’s Apprenticeship (1795), by the German writer Johann Wolfgang von Goethe. Since the novel is a genre in constant becoming, the concept of Bildungsroman undergoes problematizations and revisions and, today, it is possible to consider a novel of formation which includes ethnic, racial and sexual minorities. Some important steps in male Bildungsroman, such as fulfillment in love from several experiences and the discovery of a professional vocation and a philosophy of life, are still problematic in female novels of formation along the 20th century, due to the small space dedicated to woman in society, making her formative experiences more subjective, and culminating, in most cases, in the failed end of characters who cannot escape the webs of social oppresion. In this book I try to show that there is a process of subjectification of the female characters, in which the formative experiences occur through spatial and identity displacements, characteristic of modern times. Thus in the novels of formation from the 21th century – such as Pérolas Absolutas (2003), by Heloísa Seixas, Algum Lugar (2009), by Paloma Vidal, and Azul-corvo (2010), by Adriana Lisboa, – amid globalization and the dismantling of great utopias and truths, they experience other conflicts and problems resulting from the fluidity of human relations in modern times.
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Ryoo, Jean J., Jane Margolis, and Charis JB. Power On! The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14166.001.0001.

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A diverse group of teenage friends learn how computing can be personally and politically empowering and why all students need access to computer science education. This lively graphic novel follows a diverse group of teenage friends as they discover that computing can be fun, creative, and empowering. Taylor, Christine, Antonio, and Jon seem like typical young teens—they communicate via endless texting, they share jokes, they worry about starting high school, and they have each other's backs. But when a racially-biased artificial intelligence system causes harm in their neighborhood, they suddenly realize that tech isn't as neutral as they thought it was. But can an algorithm be racist? And what is an algorithm, anyway? In school, they decide to explore computing classes, with mixed results. One class is only about typing. The class that Christine wants to join is full, and the school counselor suggests that she take a class in “Tourism and Hospitality” instead. (Really??) But Antonio's class seems legit, Christine finds an after-school program, and they decide to teach the others what they learn. By summer vacation, all four have discovered that computing is both personally and politically empowering. Interspersed through the narrative are text boxes with computer science explainers and inspirational profiles of people of color and women in the field (including Katherine Johnson of Hidden Figures fame). Power On! is an essential read for young adults, general readers, educators, and anyone interested in the power of computing, how computing can do good or cause harm, and why addressing underrepresentation in computing needs to be a top priority.
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Carmean, Karen. Ernest J. Gaines. Greenwood, 1998. http://dx.doi.org/10.5040/9798400647208.

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Drawing on his rich Louisiana past, Ernest J. Gaines creates a fictional world representative of the human experience. His work explores the complex racial relationships—so much a part of Southern history and culture—and the unwritten and unspoken conventions of caste and class. Often structured around journeys of discovery, Gaines' works affirm the integrity of the individual and the unequivocal place in American life for Americans of African descent. This study offers a clear, accessible reading of Gaines' fiction. It analyzes in turn all of Gaines' novels as well as his collection of short stories. A complete bibliography of Gaines' fiction, as well as selected reviews and criticism, completes the study. Following a biographical chapter on Gaines' life, an overview of his fiction explores his work in light of his literary heritage and use of genre. Each of the following chapters examines an individual novel:Catherine Carmier(1964),Of Love and Dust(1967),The Autobiography of Miss Jane Pittman(1971),In My Father's House(1978),A Gathering of Old Men(1983),A Lesson Before Dying(1994), and a collection of short stories,Bloodline(1968). The discussion of each work includes sections on plot and character development, thematic issues, and an alternative critical approach from which to read the novel. Carmean shows how each of Gaines' novels focuses on themes of personal value and place and affirms the need for recognizing the value of the individual, regardless of race. This study will help readers to understand the compelling issue of human relationships raised by Gaines and to see why he is one of America's finest writers.
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Cao, Gang, and Lance DeLong. Physics of Spin-Orbit-Coupled Oxides. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780199602025.001.0001.

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Prior to 2010, most research on the physics and chemistry of transition metal oxides was dominated by compounds of the 3d-transition elements such as Cr, Mn, Fe, Co, Ni, and Cu. These materials exhibited novel, important phenomena that include giant magnetoresistance in manganites, as well as high-temperature superconductivity in doped La2CuO4 and related cuprates. The discovery in 1994 of an exotic superconducting state in Sr2RuO4 shifted some interest toward ruthenates. Moreover, the realization in 2008 that a novel variant of the classic Mott metal-insulator transition was at play in Sr2IrO4 provided the impetus for a burgeoning group of studies of the influence of strong spin-orbit interactions in “heavy” (4d- and 5d-) transition-element oxides. This book reviews recent experimental and theoretical evidence that the physical and structural properties of 4d- and 5d-oxides are decisively influenced by strong spin-orbit interactions that compete or collaborate with comparable Coulomb, magnetic exchange, and crystalline electric field interactions. The combined effect leads to unusual ground states and magnetic frustration that are unique to this class of materials. Novel couplings between the orbital/lattice and spin degrees of freedom, which lead to unusual types of magnetic order and other exotic phenomena, challenge current theoretical models. Of particular interest are recent investigations of iridates and ruthenates focusing on strong spin-orbit interactions that couple the lattice and spin degrees of freedom.
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Zangwill, Andrew. A Mind Over Matter. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198869108.001.0001.

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Philip W. Anderson (1923–2020) is widely regarded as one of the most accomplished and influential physicists of the second half of the twentieth century. Educated at Harvard, he served during World War II as a radar engineer, and began a thirty-five year career at Bell Laboratories in 1949. He was soon recognized as one of the pre-eminent theoretical physicists in the world, specializing in understanding the collective behavior of the vast number of atoms and electrons in a sample of solid matter. He won a one-third share of the 1977 Nobel Prize for Physics for his discovery of a phenomenon common to all waves in disordered matter called Anderson localization and the development of the Anderson impurity model to study magnetism. At Cambridge and Princeton Universities, Anderson led the way in transforming solid-state physics into the deep, subtle, and coherent discipline known today as condensed matter physics. He developed the concepts of broken symmetry and emergence and championed the concept of complexity as an organizing principle to attack difficult problems inside and outside physics. In 1971, Anderson was the first scientist to challenge the claim of high-energy particle physicists that their work was the most deserving of federal funding. Later, he testified before Congress opposing the Superconducting Super Collider particle accelerator. Anderson was a dominant figure in his field for almost fifty years. At an age when most scientists think about retirement, he made a brilliant contribution to many-electron theory and applied it to a novel class of high-temperature superconductors.
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Zola, Émile. The Ladies' Paradise. Translated by Brian Nelson. Oxford University Press, 2008. http://dx.doi.org/10.1093/owc/9780199536900.001.0001.

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The Ladies’ Paradise (Au Bonheur des Dames) recounts the spectacular development of the modern department store in late nineteenth century Paris. The store is a symbol of capitalism, of the modern city, and of the bourgeois family; it is emblematic of consumer culture and the changes in sexual attitudes and class relations taking place at the end of the century. Octave Mouret, the store’s owner-manager, masterfully exploits the desires of his female customers. In his private life as much as in business he is the great seducer. But when he falls in love with the innocent Denise Baudu, he discovers she is the only one of the salesgirls who refuses to be commodified. This new translation of the eleventh book in the Rougon-Macquart cycle captures the spirit of one of Zola’s greatest novels of the modern city.
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Crease, Robert P., and Peter D. Bond. The Leak. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14577.001.0001.

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How the discovery of a harmless leak of radiation sparked a media firestorm, political grandstanding, and fearmongering that closed a vital scientific facility. In 1997, scientists at Brookhaven National Laboratory found a small leak of radioactive water near their research reactor. Brookhaven was—and is—a world-class, Nobel Prize–winning lab, and its reactor was the cornerstone of US materials science and one of the world's finest research facilities. The leak, harmless to health, came from a storage pool rather than the reactor. But its discovery triggered a media and political firestorm that resulted in the reactor's shutdown, and even attempts to close the entire laboratory. A quarter century later, the episode reveals the dynamics of today's controversies in which fears and the dismissal of science disrupt serious discussion and research of vital issues such as vaccines, climate change, and toxic chemicals. This story has all the elements of a thriller, with vivid characters and dramatic twists and turns. Key players include congressmen and scientists; journalists and university presidents; actors, supermodels, and anti-nuclear activists, all interacting and teaming up in surprising ways. The authors, each with insider knowledge of and access to confidential documents and the key players, reveal how a fact of no health significance could be portrayed as a Chernobyl-like disaster. This compelling exposé reveals the gaps between scientists, politicians, media, and the public that have only gotten more dangerous since 1997.
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Eliot, George, and K. M. Newton. Daniel Deronda. Edited by Graham Handley. Oxford University Press, 2014. http://dx.doi.org/10.1093/owc/9780199682867.001.0001.

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She felt herself standing at the game of life with many eyes upon her, daring everything to win much.’ Gwendolen Harleth gambles her happiness when she marries a sadistic aristocrat for his money. Beautiful, neurotic, and self-centred, Gwendolen is trapped in an increasingly destructive relationship, and only her chance encounter with the idealistic Deronda seems to offer the hope of a brighter future. Deronda is searching for a vocation, and in embracing the Jewish cause he finds one that is both visionary and life-changing. Damaged by their pasts, and alienated from the society around them, they must both discover the values that will give their lives meaning. George Eliot’s powerful novel is set in a Britain whose ruling class is decadent and materialistic, its power likely to be threatened by a politically emergent Germany. The novel’s exploration of sexuality, guilt, and the will to power anticipates later developments in fiction, and its linking of the personal and the political in a context of social and economic crisis gives it especial relevance to the dominant issues of the twenty-first century.
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Book chapters on the topic "Novel class discovery"

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Roy, Subhankar, Mingxuan Liu, Zhun Zhong, Nicu Sebe, and Elisa Ricci. "Class-Incremental Novel Class Discovery." In Lecture Notes in Computer Science, 317–33. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19827-4_19.

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Joseph, K. J., Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, and Vineeth N. Balasubramanian. "Novel Class Discovery Without Forgetting." In Lecture Notes in Computer Science, 570–86. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20053-3_33.

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Nguyen, Hung, Xuejian Wang, and Leman Akoglu. "Continual Rare-Class Recognition with Emerging Novel Subclasses." In Machine Learning and Knowledge Discovery in Databases, 20–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46147-8_2.

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Feng, Wei, Lie Ju, Lin Wang, Kaimin Song, and Zongyuan Ge. "Towards Novel Class Discovery: A Study in Novel Skin Lesions Clustering." In Lecture Notes in Computer Science, 24–33. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43987-2_3.

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Islam, Mohammad Raihanul. "Recurring and Novel Class Detection in Concept-Drifting Data Streams Using Class-Based Ensemble." In Advances in Knowledge Discovery and Data Mining, 425–36. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06605-9_35.

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Kefi, Takoua, Riadh Ksantini, Mohamed Bécha Kaâniche, and Adel Bouhoula. "A Novel Incremental Covariance-Guided One-Class Support Vector Machine." In Machine Learning and Knowledge Discovery in Databases, 17–32. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46227-1_2.

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Swalley, Susanne E., and Atwood K. Cheung. "Chapter 8. Identification of a Novel Class of Small Molecules for Spinal Muscular Atrophy Through High-throughput Phenotypic Screening." In Drug Discovery, 140–59. Cambridge: Royal Society of Chemistry, 2020. http://dx.doi.org/10.1039/9781839160721-00140.

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Troisemaine, Colin, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, and Vincent Lemaire. "An Interactive Interface for Novel Class Discovery in Tabular Data." In Lecture Notes in Computer Science, 295–99. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43430-3_18.

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Hassan, Md Rafiul, Kotagiri Ramamohanarao, Chandan Karmakar, M. Maruf Hossain, and James Bailey. "A Novel Scalable Multi-class ROC for Effective Visualization and Computation." In Advances in Knowledge Discovery and Data Mining, 107–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13657-3_14.

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Masud, Mohammad M., Jing Gao, Latifur Khan, Jiawei Han, and Bhavani Thuraisingham. "Classification and Novel Class Detection in Data Streams with Active Mining." In Advances in Knowledge Discovery and Data Mining, 311–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13672-6_31.

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Conference papers on the topic "Novel class discovery"

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Michalski, Tomasz, Dawid Rymarczyk, Daniel Barczyk, and Bartosz Zieliński. "ProtoNCD: Prototypical Parts for Interpretable Novel Class Discovery." In ESANN 2024, 273–78. Louvain-la-Neuve (Belgium): Ciaco - i6doc.com, 2024. http://dx.doi.org/10.14428/esann/2024.es2024-70.

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Liu, Yu, Yaqi Cai, Qi Jia, Binglin Qiu, Weimin Wang, and Nan Pu. "Novel Class Discovery for Ultra-Fine-Grained Visual Categorization." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 17679–88. IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.01674.

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Liu, Jiaming, Yangqiming Wang, Tongze Zhang, Yulu Fan, Qinli Yang, and Junming Shao. "Open-world Semi-supervised Novel Class Discovery." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/445.

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Traditional semi-supervised learning tasks assume that both labeled and unlabeled data follow the same class distribution, but the realistic open-world scenarios are of more complexity with unknown novel classes mixed in the unlabeled set. Therefore, it is of great challenge to not only recognize samples from known classes but also discover the unknown number of novel classes within the unlabeled data. In this paper, we introduce a new open-world semi-supervised novel class discovery approach named OpenNCD, a progressive bi-level contrastive learning method over multiple prototypes. The proposed method is composed of two reciprocally enhanced parts. First, a bi-level contrastive learning method is introduced, which maintains the pair-wise similarity of the prototypes and the prototype group levels for better representation learning. Then, a reliable prototype similarity metric is proposed based on the common representing instances. Prototypes with high similarities will be grouped progressively for known class recognition and novel class discovery. Extensive experiments on three image datasets are conducted and the results show the effectiveness of the proposed method in open-world scenarios, especially with scarce known classes and labels.
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Gu, Peiyan, Chuyu Zhang, Ruijie Xu, and Xuming He. "Class-relation Knowledge Distillation for Novel Class Discovery." In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2023. http://dx.doi.org/10.1109/iccv51070.2023.01510.

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Zhao, Yuyang, Zhun Zhong, Nicu Sebe, and Gim Hee Lee. "Novel Class Discovery in Semantic Segmentation." In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2022. http://dx.doi.org/10.1109/cvpr52688.2022.00430.

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Mukherjee, Tanmoy, and Nikos Deligiannis. "Novel Class Discovery: A Dependency Approach." In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. http://dx.doi.org/10.1109/icassp43922.2022.9747827.

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Li, Wenbin, Zhichen Fan, Jing Huo, and Yang Gao. "Modeling Inter-Class and Intra-Class Constraints in Novel Class Discovery." In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2023. http://dx.doi.org/10.1109/cvpr52729.2023.00336.

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Zhong, Zhun, Enrico Fini, Subhankar Roy, Zhiming Luo, Elisa Ricci, and Nicu Sebe. "Neighborhood Contrastive Learning for Novel Class Discovery." In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2021. http://dx.doi.org/10.1109/cvpr46437.2021.01072.

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Fini, Enrico, Enver Sangineto, Stephane Lathuiliere, Zhun Zhong, Moin Nabi, and Elisa Ricci. "A Unified Objective for Novel Class Discovery." In 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2021. http://dx.doi.org/10.1109/iccv48922.2021.00915.

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Wei, Qian, Zongyong Cui, Yijie Deng, Bin Li, and Zongjie Cao. "Research on Novel Class Discovery of SAR Target." In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2023. http://dx.doi.org/10.1109/igarss52108.2023.10283051.

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Reports on the topic "Novel class discovery"

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Barkan, Terrance. The Role of Graphene in Achieving e-Mobility in Aerospace Applications. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, December 2022. http://dx.doi.org/10.4271/epr2022030.

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<div class="section abstract"><div class="htmlview paragraph">Advanced two-dimensional (2D) materials discovered in the last two decades are now being produced at scale and are contributing to a wide range of performance enhancements in engineering applications. The most well-known of these novel materials is graphene, a nearly transparent nanomaterial comprising a single layer of bonded carbon atoms. In relative terms, it has the highest level of heat and electrical conductivity, protects against ultraviolet rays, and is strongest material ever measured. These properties have made graphene an attractive potential material for a variety of applications, particularly for transportation related uses, and especially for aerospace engineering. </div><div class="htmlview paragraph"><b>The Role of Graphene in Achieving e-Mobility in Aerospace Applications</b> reviews the current state of graphene-related aerospace applications and identifies the technological challenges facing engineers that look to benefit from graphene’s attractive properties.</div><div class="htmlview paragraph"><a href="https://www.sae.org/publications/edge-research-reports" target="_blank">Click here to access the full SAE EDGE</a><sup>TM</sup><a href="https://www.sae.org/publications/edge-research-reports" target="_blank"> Research Report portfolio.</a></div></div>
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Altstein, Miriam, and Ronald J. Nachman. Rational Design of Insect Control Agent Prototypes Based on Pyrokinin/PBAN Neuropeptide Antagonists. United States Department of Agriculture, August 2013. http://dx.doi.org/10.32747/2013.7593398.bard.

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The general objective of this study was to develop rationally designed mimetic antagonists (and agonists) of the PK/PBAN Np class with enhanced bio-stability and bioavailability as prototypes for effective and environmentally friendly pest insect management agents. The PK/PBAN family is a multifunctional group of Nps that mediates key functions in insects (sex pheromone biosynthesis, cuticular melanization, myotropic activity, diapause and pupal development) and is, therefore, of high scientific and applied interest. The objectives of the current study were: (i) to identify an antagonist biophores (ii) to develop an arsenal of amphiphilic topically active PK/PBAN antagonists with an array of different time-release profiles based on the previously developed prototype analog; (iii) to develop rationally designed non-peptide SMLs based on the antagonist biophore determined in (i) and evaluate them in cloned receptor microplate binding assays and by pheromonotropic, melanotropic and pupariation in vivo assays. (iv) to clone PK/PBAN receptors (PK/PBAN-Rs) for further understanding of receptor-ligand interactions; (v) to develop microplate binding assays for screening the above SMLs. In the course of the granting period A series of amphiphilic PK/PBAN analogs based on a linear lead antagonist from the previous BARD grant was synthesized that incorporated a diverse array of hydrophobic groups (HR-Suc-A[dF]PRLa). Others were synthesized via the attachment of polyethylene glycol (PEG) polymers. A hydrophobic, biostablePK/PBAN/DH analog DH-2Abf-K prevented the onset of the protective state of diapause in H. zea pupae [EC50=7 pmol/larva] following injection into the preceding larval stage. It effectively induces the crop pest to commit a form of ‘ecological suicide’. Evaluation of a set of amphiphilic PK analogs with a diverse array of hydrophobic groups of the formula HR-Suc-FTPRLa led to the identification of analog T-63 (HR=Decyl) that increased the extent of diapause termination by a factor of 70% when applied topically to newly emerged pupae. Another biostablePK analog PK-Oic-1 featured anti-feedant and aphicidal properties that matched the potency of some commercial aphicides. Native PK showed no significant activity. The aphicidal effects were blocked by a new PEGylated PK antagonist analog PK-dF-PEG4, suggesting that the activity is mediated by a PK/PBAN receptor and therefore indicative of a novel and selective mode-of-action. Using a novel transPro mimetic motif (dihydroimidazole; ‘Jones’) developed in previous BARD-sponsored work, the first antagonist for the diapause hormone (DH), DH-Jo, was developed and shown to block over 50% of H. zea pupal diapause termination activity of native DH. This novel antagonist development strategy may be applicable to other invertebrate and vertebrate hormones that feature a transPro in the active core. The research identifies a critical component of the antagonist biophore for this PK/PBAN receptor subtype, i.e. a trans-oriented Pro. Additional work led to the molecular cloning and functional characterization of the DH receptor from H. zea, allowing for the discovery of three other DH antagonist analogs: Drosophila ETH, a β-AA analog, and a dF analog. The receptor experiments identified an agonist (DH-2Abf-dA) with a maximal response greater than native DH. ‘Deconvolution’ of a rationally-designed nonpeptide heterocyclic combinatorial library with a cyclic bis-guanidino (BG) scaffold led to discovery of several members that elicited activity in a pupariation acceleration assay, and one that also showed activity in an H. zea diapause termination assay, eliciting a maximal response of 90%. Molecular cloning and functional characterization of a CAP2b antidiuretic receptor from the kissing bug (R. prolixus) as well as the first CAP2b and PK receptors from a tick was also achieved. Notably, the PK/PBAN-like receptor from the cattle fever tick is unique among known PK/PBAN and CAP2b receptors in that it can interact with both ligand types, providing further evidence for an evolutionary relationship between these two NP families. In the course of the granting period we also managed to clone the PK/PBAN-R of H. peltigera, to express it and the S. littoralis-R Sf-9 cells and to evaluate their interaction with a variety of PK/PBAN ligands. In addition, three functional microplate assays in a HTS format have been developed: a cell-membrane competitive ligand binding assay; a Ca flux assay and a whole cell cAMP ELISA. The Ca flux assay has been used for receptor characterization due to its extremely high sensitivity. Computer homology studies were carried out to predict both receptor’s SAR and based on this analysis 8 mutants have been generated. The bioavailability of small linear antagonistic peptides has been evaluated and was found to be highly effective as sex pheromone biosynthesis inhibitors. The activity of 11 new amphiphilic analogs has also been evaluated. Unfortunately, due to a problem with the Heliothis moth colony we were unable to select those with pheromonotropic antagonistic activity and further check their bioavailability. Six peptides exhibited some melanotropic antagonistic activity but due to the low inhibitory effect the peptides were not further tested for bioavailability in S. littoralis larvae. Despite the fact that no new antagonistic peptides were discovered in the course of this granting period the results contribute to a better understanding of the interaction of the PK/PBAN family of Nps with their receptors, provided several HT assays for screening of libraries of various origin for presence of PK/PBAN-Ragonists and antagonists and provided important practical information for the further design of new, peptide-based insecticide prototypes aimed at the disruption of key neuroendocrine physiological functions in pest insects.
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Dawson, William O., and Moshe Bar-Joseph. Creating an Ally from an Adversary: Genetic Manipulation of Citrus Tristeza. United States Department of Agriculture, January 2004. http://dx.doi.org/10.32747/2004.7586540.bard.

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Citrus is one of the major agricultural crops common to Israel and the United States, important in terms of nutrition, foreign exchange, and employment. The economy of both citrus industries have been chronically plagued by diseases caused by Citrus tristeza virus (CTV). The short term solution until virus-resistant plants can be used is the use of mild strain cross-protection. We are custom designing "ideal" protecting viruses to immunize trees against severe isolates of CTV by purposely inoculating existing endangered trees and new plantings to be propagated as infected (protected) citrus budwood. We crossed the substantial technological hurdles necessary to accomplish this task which included developing an infectious cDNA clone which allows in vitro manipulation of the virus and methods to then infect citrus plants. We created a series of hybrids between decline-inducing and mild CTV strains, tested them in protoplasts, and are amplifying them to inoculate citrus trees for evaluation and mapping of disease determinants. We also extended this developed technology to begin engineering transient expression vectors based on CTV as tools for genetic improvement of tree crops, in this case citrus. Because of the long periods between genetic transformation and the ultimate assay of mature tree characteristics, there is a great need for an effective system that allows the expression or suppression of target genes in fruiting plants. Virus-based vectors will greatly expedite progress in citrus genetic improvement. We characterized several components of the virus that provides necessary information for designing virus-based vectors. We characterized the requirements of the 3 ’-nontranslated replication promoter and two 3 ’-ORF subgenomic (sg) mRNA controller elements. We discovered a novel type of 5’-terminal sgRNAs and characterized the cis-acting control element that also functions as a strong promoter of a 3 ’-sgRNA. We showed that the p23 gene controls negative-stranded RNA synthesis and expression of 3 ’ genes. We identified which genes are required for infection of plants, which are host range determinants, and which are not needed for plant infection. We continued the characterization of native dRNA populations and showed the presence of five different classes including class III dRNAs that consists of infectious and self-replicating molecules and class V dRNAs that contain all of the 3 ’ ORFs, along with class IV dRNAs that retain non-contiguous internal sequences. We have constructed and tested in protoplasts a series of expression vectors that will be described in this proposal.
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