Relevant bibliographies by topics / Target domain

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Target domain'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 May 2022

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Journal articles on the topic "Target domain"

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Li, Haoliang, Wen Li, and Shiqi Wang. "Discovering and incorporating latent target-domains for domain adaptation." Pattern Recognition 108 (December 2020): 107536. http://dx.doi.org/10.1016/j.patcog.2020.107536.

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Choi, Jongwon, Youngjoon Choi, Jihoon Kim, Jinyeop Chang, Ilhwan Kwon, Youngjune Gwon, and Seungjai Min. "Visual Domain Adaptation by Consensus-Based Transfer to Intermediate Domain." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 10655–62. http://dx.doi.org/10.1609/aaai.v34i07.6692.

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We describe an unsupervised domain adaptation framework for images by a transform to an abstract intermediate domain and ensemble classifiers seeking a consensus. The intermediate domain can be thought as a latent domain where both the source and target domains can be transferred easily. The proposed framework aligns both domains to the intermediate domain, which greatly improves the adaptation performance when the source and target domains are notably dissimilar. In addition, we propose an ensemble model trained by confusing multiple classifiers and letting them make a consensus alternately to enhance the adaptation performance for ambiguous samples. To estimate the hidden intermediate domain and the unknown labels of the target domain simultaneously, we develop a training algorithm using a double-structured architecture. We validate the proposed framework in hard adaptation scenarios with real-world datasets from simple synthetic domains to complex real-world domains. The proposed algorithm outperforms the previous state-of-the-art algorithms on various environments.
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Xu, Yifan, Kekai Sheng, Weiming Dong, Baoyuan Wu, Changsheng Xu, and Bao-Gang Hu. "Towards Corruption-Agnostic Robust Domain Adaptation." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 4 (November 30, 2022): 1–16. http://dx.doi.org/10.1145/3501800.

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Great progress has been achieved in domain adaptation in decades. Existing works are always based on an ideal assumption that testing target domains are independent and identically distributed with training target domains. However, due to unpredictable corruptions (e.g., noise and blur) in real data, such as web images and real-world object detection, domain adaptation methods are increasingly required to be corruption robust on target domains. We investigate a new task, corruption-agnostic robust domain adaptation (CRDA), to be accurate on original data and robust against unavailable-for-training corruptions on target domains. This task is non-trivial due to the large domain discrepancy and unsupervised target domains. We observe that simple combinations of popular methods of domain adaptation and corruption robustness have suboptimal CRDA results. We propose a new approach based on two technical insights into CRDA, as follows: (1) an easy-to-plug module called domain discrepancy generator (DDG) that generates samples that enlarge domain discrepancy to mimic unpredictable corruptions; (2) a simple but effective teacher-student scheme with contrastive loss to enhance the constraints on target domains. Experiments verify that DDG maintains or even improves its performance on original data and achieves better corruption robustness than baselines. Our code is available at: https://github.com/YifanXu74/CRDA .
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GLYNN, Paul. "Neuropathy target esterase." Biochemical Journal 344, no. 3 (December 8, 1999): 625–31. http://dx.doi.org/10.1042/bj3440625.

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Neuropathy target esterase (NTE) is an integral membrane protein present in all neurons and in some non-neural-cell types of vertebrates. Recent data indicate that NTE is involved in a cell-signalling pathway controlling interactions between neurons and accessory glial cells in the developing nervous system. NTE has serine esterase activity and efficiently catalyses the hydrolysis of phenyl valerate (PV) in vitro, but its physiological substrate is unknown. By sequence analysis NTE has been found to be related neither to the major serine esterase family, which includes acetylcholinesterase, nor to any other known serine hydrolases. NTE comprises at least two functional domains: an N-terminal putative regulatory domain and a C-terminal effector domain which contains the esterase activity and is, in part, conserved in proteins found in bacteria, yeast, nematodes and insects. NTE's effector domain contains three predicted transmembrane segments, and the active-site serine residue lies at the centre of one of these segments. The isolated recombinant domain shows PV hydrolase activity only when incorporated into phospholipid liposomes. NTE's esterase activity appears to be largely redundant in adult vertebrates, but organophosphates which react with NTE in vivo initiate unknown events which lead, after a delay of 1-3 weeks, to a neuropathy with degeneration of long axons. These neuropathic organophosphates leave a negatively charged group covalently attached to the active-site serine residue, and it is suggested that this may cause a toxic gain of function in NTE.
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Ye, Fei, and Mingjie Zhang. "Structures and target recognition modes of PDZ domains: recurring themes and emerging pictures." Biochemical Journal 455, no. 1 (September 13, 2013): 1–14. http://dx.doi.org/10.1042/bj20130783.

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PDZ domains are highly abundant protein–protein interaction modules and are often found in multidomain scaffold proteins. PDZ-domain-containing scaffold proteins regulate multiple biological processes, including trafficking and clustering receptors and ion channels at defined membrane regions, organizing and targeting signalling complexes at specific cellular compartments, interfacing cytoskeletal structures with membranes, and maintaining various cellular structures. PDZ domains, each with ~90-amino-acid residues folding into a highly similar structure, are best known to bind to short C-terminal tail peptides of their target proteins. A series of recent studies have revealed that, in addition to the canonical target-binding mode, many PDZ–target interactions involve amino acid residues beyond the regular PDZ domain fold, which we refer to as extensions. Such extension sequences often form an integral structural and functional unit with the attached PDZ domain, which is defined as a PDZ supramodule. Correspondingly, PDZ-domain-binding sequences from target proteins are frequently found to require extension sequences beyond canonical short C-terminal tail peptides. Formation of PDZ supramodules not only affords necessary binding specificities and affinities demanded by physiological functions of PDZ domain targets, but also provides regulatory switches to be built in the PDZ–target interactions. At the 20th anniversary of the discovery of PDZ domain proteins, we try to summarize structural features and target-binding properties of such PDZ supramodules emerging from studies in recent years.
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Yeung, W. K., and S. Evans. "Time-domain microwave target imaging." IEE Proceedings H Microwaves, Antennas and Propagation 132, no. 6 (1985): 345. http://dx.doi.org/10.1049/ip-h-2.1985.0063.

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Xu, Minghao, Jian Zhang, Bingbing Ni, Teng Li, Chengjie Wang, Qi Tian, and Wenjun Zhang. "Adversarial Domain Adaptation with Domain Mixup." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6502–9. http://dx.doi.org/10.1609/aaai.v34i04.6123.

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Recent works on domain adaptation reveal the effectiveness of adversarial learning on filling the discrepancy between source and target domains. However, two common limitations exist in current adversarial-learning-based methods. First, samples from two domains alone are not sufficient to ensure domain-invariance at most part of latent space. Second, the domain discriminator involved in these methods can only judge real or fake with the guidance of hard label, while it is more reasonable to use soft scores to evaluate the generated images or features, i.e., to fully utilize the inter-domain information. In this paper, we present adversarial domain adaptation with domain mixup (DM-ADA), which guarantees domain-invariance in a more continuous latent space and guides the domain discriminator in judging samples' difference relative to source and target domains. Domain mixup is jointly conducted on pixel and feature level to improve the robustness of models. Extensive experiments prove that the proposed approach can achieve superior performance on tasks with various degrees of domain shift and data complexity.
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Ren, Chuan-Xian, Yong-Hui Liu, Xi-Wen Zhang, and Ke-Kun Huang. "Multi-Source Unsupervised Domain Adaptation via Pseudo Target Domain." IEEE Transactions on Image Processing 31 (2022): 2122–35. http://dx.doi.org/10.1109/tip.2022.3152052.

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Jin, Wei, and Nan Jia. "Learning Transferable Convolutional Proxy by SMI-Based Matching Technique." Shock and Vibration 2020 (October 14, 2020): 1–15. http://dx.doi.org/10.1155/2020/8873137.

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Domain-transfer learning is a machine learning task to explore a source domain data set to help the learning problem in a target domain. Usually, the source domain has sufficient labeled data, while the target domain does not. In this paper, we propose a novel domain-transfer convolutional model by mapping a target domain data sample to a proxy in the source domain and applying a source domain model to the proxy for the purpose of prediction. In our framework, we firstly represent both source and target domains to feature vectors by two convolutional neural networks and then construct a proxy for each target domain sample in the source domain space. The proxy is supposed to be matched to the corresponding target domain sample convolutional representation vector well. To measure the matching quality, we proposed to maximize their squared-loss mutual information (SMI) between the proxy and target domain samples. We further develop a novel neural SMI estimator based on a parametric density ratio estimation function. Moreover, we also propose to minimize the classification error of both source domain samples and target domain proxies. The classification responses are also smoothened by manifolds of both the source domain and proxy space. By minimizing an objective function of SMI, classification error, and manifold regularization, we learn the convolutional networks of both source and target domains. In this way, the proxy of a target domain sample can be matched to the source domain data and thus benefits from the rich supervision information of the source domain. We design an iterative algorithm to update the parameters alternately and test it over benchmark data sets of abnormal behavior detection in video, Amazon product reviews sentiment analysis, etc.
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Doğan, Tunca, Ece Akhan Güzelcan, Marcus Baumann, Altay Koyas, Heval Atas, Ian R. Baxendale, Maria Martin, and Rengul Cetin-Atalay. "Protein domain-based prediction of drug/compound–target interactions and experimental validation on LIM kinases." PLOS Computational Biology 17, no. 11 (November 29, 2021): e1009171. http://dx.doi.org/10.1371/journal.pcbi.1009171.

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Predictive approaches such as virtual screening have been used in drug discovery with the objective of reducing developmental time and costs. Current machine learning and network-based approaches have issues related to generalization, usability, or model interpretability, especially due to the complexity of target proteins’ structure/function, and bias in system training datasets. Here, we propose a new method “DRUIDom” (DRUg Interacting Domain prediction) to identify bio-interactions between drug candidate compounds and targets by utilizing the domain modularity of proteins, to overcome problems associated with current approaches. DRUIDom is composed of two methodological steps. First, ligands/compounds are statistically mapped to structural domains of their target proteins, with the aim of identifying their interactions. As such, other proteins containing the same mapped domain or domain pair become new candidate targets for the corresponding compounds. Next, a million-scale dataset of small molecule compounds, including those mapped to domains in the previous step, are clustered based on their molecular similarities, and their domain associations are propagated to other compounds within the same clusters. Experimentally verified bioactivity data points, obtained from public databases, are meticulously filtered to construct datasets of active/interacting and inactive/non-interacting drug/compound–target pairs (~2.9M data points), and used as training data for calculating parameters of compound–domain mappings, which led to 27,032 high-confidence associations between 250 domains and 8,165 compounds, and a finalized output of ~5 million new compound–protein interactions. DRUIDom is experimentally validated by syntheses and bioactivity analyses of compounds predicted to target LIM-kinase proteins, which play critical roles in the regulation of cell motility, cell cycle progression, and differentiation through actin filament dynamics. We showed that LIMK-inhibitor-2 and its derivatives significantly block the cancer cell migration through inhibition of LIMK phosphorylation and the downstream protein cofilin. One of the derivative compounds (LIMKi-2d) was identified as a promising candidate due to its action on resistant Mahlavu liver cancer cells. The results demonstrated that DRUIDom can be exploited to identify drug candidate compounds for intended targets and to predict new target proteins based on the defined compound–domain relationships. Datasets, results, and the source code of DRUIDom are fully-available at: https://github.com/cansyl/DRUIDom.
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Dissertations / Theses on the topic "Target domain"

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Gustafsson, Fredrik, and Erik Linder-Norén. "Automotive 3D Object Detection Without Target Domain Annotations." Thesis, Linköpings universitet, Datorseende, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148585.

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In this thesis we study a perception problem in the context of autonomous driving. Specifically, we study the computer vision problem of 3D object detection, in which objects should be detected from various sensor data and their position in the 3D world should be estimated. We also study the application of Generative Adversarial Networks in domain adaptation techniques, aiming to improve the 3D object detection model's ability to transfer between different domains. The state-of-the-art Frustum-PointNet architecture for LiDAR-based 3D object detection was implemented and found to closely match its reported performance when trained and evaluated on the KITTI dataset. The architecture was also found to transfer reasonably well from the synthetic SYN dataset to KITTI, and is thus believed to be usable in a semi-automatic 3D bounding box annotation process. The Frustum-PointNet architecture was also extended to explicitly utilize image features, which surprisingly degraded its detection performance. Furthermore, an image-only 3D object detection model was designed and implemented, which was found to compare quite favourably with current state-of-the-art in terms of detection performance. Additionally, the PixelDA approach was adopted and successfully applied to the MNIST to MNIST-M domain adaptation problem, which validated the idea that unsupervised domain adaptation using Generative Adversarial Networks can improve the performance of a task network for a dataset lacking ground truth annotations. Surprisingly, the approach did however not significantly improve upon the performance of the image-based 3D object detection models when trained on the SYN dataset and evaluated on KITTI.
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Collins, K. M. "Target recognition by multi-domain RNA-binding proteins." Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1460867/.

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Multi-functional RNA binding proteins regulate and coordinate the many steps of RNA metabolism. Accurate functioning of these processes is vital in cells and misregulation has been linked to many human diseases. RNA binding proteins contain multiple RNA binding domains. The ability to perform multiple functions depends on the recognition of a diverse range of targets and domains are used combinatorially to achieve this. In this thesis I ask how the sequence specificity of low affinity RNA-binding domains and the interplay between said domains plays a role in RNA target selectivity. Within this question I focus on three proteins; TUT4, a uridyl transferase involved in the regulation of both non-coding RNAs and histone mRNA; FMRP, a translational repressor whose loss in cells is the cause of Fragile X Syndrome; and RBM10 a regulator of alternative splicing and miRNA biogenesis. I found that through the use of separate RNA binding domains both TUT4 and RBM10 are able to exert flexibility in target recognition; TUT4 by using two CCHC-type zinc fingers, working independently to recognise short RNA stretches; and RBM10 by using different subsets of domains to recognise either specific high affinity splice site sequences or pre-miRNAs. In FMRP the determination of the sequence specificity of KH1 allowed us to isolate its contribution to target selection. In a secondary objective, looking at methodologies used in RNA-protein interaction, SIA was improved to make it both less laborious and to reduce the sample requirements, and with FMRP a novel mutational strategy was used in combination with SIA to determine the sequence specificity of this low affinity domain. In summary these data extend our understanding of the RNA binding mechanisms of the three systems studied and introduces improved or novel methodologies to the future study of protein-RNA interactions.
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Davis, Alicia Morgan. "CHARACTERIZATION OF INFLUENZA NUCLEOPROTEIN BODY DOMAIN AS ANTIVIRAL TARGET." CSUSB ScholarWorks, 2016. https://scholarworks.lib.csusb.edu/etd/364.

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Influenza is a segmented negative strand RNA virus. Each RNA segment is encapsulated by viral nucleoprotein (NP) and bound by the viral RNA dependent RNA polymerase (RdRP) to form viral ribonucleoproteins (vRNPs) responsible for RNA synthesis. NP is a structural component of the vRNP but also interacts with both viral and host factors to regulate viral RNA expression. NP is conserved among influenza A isolates, making NP interactions compelling antiviral targets. Here I characterize mutations within 5 amino acids of NP that comprise an accessible region of the NP body domain, as determined by NP crystal structure. This region was selected for mutagenesis to target interaction between NP and RdRP. NPbd3 encodes glycine at 5 amino acids within the accessible NP body domain. Cellular fractionation and Western Blot, in addition to NP-GFP fusions and fluorescence, confirm NPbd3 was expressed and localized as WT-NP. Gel shift with purified NP protein confirm NPbd3 bound nucleic acids as WT-NP. Although NPbd3 was expressed, localized, and bound nucleic acid as WT-NP, I found NPbd3 was defective for RNA expression in reconstituted vRNPs, as evaluated by reverse transcription and quantitative polymerase chain reaction (RT-qPCR). To investigate this NP body domain further, single and double amino acid mutations were cloned. Analysis of NP single mutants revealed that all were nearly as functional as WT-NP for RNA expression in reconstituted vRNPs, suggesting these accessible amino acids in the NP body domain play a redundant role. However, four different combinations of two amino acid mutations resulted in NP double mutants that displayed a significant defect in RNA expression in reconstituted vRNPs, confirming these accessible amino acids in the NP body domain play a significant role for viral RNA synthesis. A disruption in an essential NP interaction with the RdRP is likely the explanation for the RNA defect observed. In support of this, avian influenza virus passaged in human cells resulted in virus with one NP amino acid change in this domain consistently paired with specific changes in the PB2 subunit of the RdRP. I reason this accessible body domain of NP is a viable antiviral target. Indeed, two amino acids in this NP body domain comprise a novel groove implicated in binding the small molecule inhibitor nucleozin. My thesis highlights this conserved NP body domain as an important interaction surface essential for viral RNA synthesis and support further investigation of antiviral drugs that target this region of NP.
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Bishoff, Josef P. "Target detection using oblique hyperspectral imagery : a domain trade study /." Online version of thesis, 2008. http://hdl.handle.net/1850/7834.

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Atkins, Jane. "Biochemical characterisation of the catalytic domain of neuropathy target esterase." Thesis, University of Leicester, 2000. http://hdl.handle.net/2381/29643.

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Neuropathy target esterase (NTE) is an integral membrane protein found predominantly in neurones. Covalent modification of NTE's active site serine, by certain organophosphates (OPs), results in a neurodegenerative syndrome. NTE's physiological substrate is unknown and its catalytic activity does not seem to be vital in the adult animal. The enzyme domain of human NTE (residues 727-1216), called NEST, was expressed in E. coli and reacted with a carboxyl ester substrate and OP inhibitors the same as native NTE. During purification catalytic activity was lost, but was restored by reconstitution into the liposomes. Site-directed mutagenesis revealed that S966, D960 and D1086 were critical for catalysis. Mutation of two histidines, H860 and H885, also resulted in a loss of activity. Reacting NEST with [3H]diisopropylfluorophosphate, confirmed S966 as the active site serine and showed that an isopropyl group is transferred to an aspartate residue. Standard hydropathy analysis predicts no membrane-spanning helices in NEST; however, biochemical evidence indicated that NEST is an integral membrane protein. TMpred analysis, on the other hand, predicts three transmembrane helices (TM2-4), with S966 at the centre of TM4. For S966 to be located within the membrane, TM4 would need to line the lumen of an aqueous pore to allow access of water for catalysis. Patch clamp studies on NEST-containing giant liposomes indicated that NEST forms a pore in vitro, while other experiments demonstrated that NEST monomers are catalytically active: this raises the possibility that NEST forms a -barrel structure in the membrane.
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Kucheruk, Liliya. "Modern English Legal Terminology : linguistic and cognitive aspects." Thesis, Bordeaux 3, 2013. http://www.theses.fr/2013BOR30016/document.

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La présente étude intitulée «Terminologie juridique moderne de la langue anglaise: aspects linguistiques et cognitifs » aborde le langage juridique contemporain dans le cadre de la linguistique cognitive. Les objectifs de l'étude sont d'étudier les particularités de la terminologie juridique et de proposer des principes de systématisation, en se référant à la théorie cognitive de la métaphore. Il s’agit principalement : 1) de déterminer les concepts de base utilisés métaphoriquement dans la langue juridique ; 2) d'établir les correspondances principales entre domaines et les corrélations entre des éléments particuliers dans des domaines spécifiques. Pour répondre à cette question, un corpus d’anglais juridique a été constitué et soumis à une étude quantitative. Les expressions métaphoriques liées à la terminologie juridique ont été retirés et classés selon leur sens métaphorique. Il est ainsi apparu que les métaphores conceptuelles de la GUERRE, de la MEDECINE, du SPORT et de la CONSTRUCTION étaient les plus nombreuses et prégnantes en anglais juridique. Les projections et correspondances entre ces domaines sources et le domaine cible de la LOI ont été établies.Cette étude empirique repose sur 156 textes juridiques qui ont été rassemblés au sein d’un même corpus (COLE – Corpus of Legal English). Les sources renvoient à différentes catégories thématiques. Le corpus a été utilisé pour établir la réalité de certains phénomènes et interpréter les résultats quantitatifs dans le cadre de la théorie de la métaphore conceptuelle
The present doctoral dissertation entitled “Modern English Legal Terminology: linguistic and cognitive aspects” investigates the contemporary legal idiom, from a cognitive linguistics perspective. The aim of this study is to map out the peculiarities of English legal terminology and develop principles of systematization, within the framework of conceptual metaphor theory. This means 1) determining the basic concepts used metaphorically in English legal language, and 2) establishing the main cross-domain mappings and correlations between separate items within concrete domains.The Corpus of Legal English (COLE) was set up and a quantitative analysis performed, in which metaphorical expressions related to legal terminology were searched for and classified on the basis of meanings, conceptual domains and mappings. Thus, the conceptual metaphors of WAR, MEDICINE, SPORT and CONSTRUCTION were found to be the most numerous and valuable in Legal English. The main cross-domain mappings between these source domains and the target domain of LAW were established.In order to carry out this data-driven study, 156 legal texts were selected and compiled into the Corpus of Legal English (COLE). The source-texts represent various thematic categories. The COLE was systematically used to interpret frequency counts from the point of view of conceptual metaphor theory
Дисертаційне дослідження на тему «Сучасна англійська юридична термінологія: лінгвокогнитивний аспект» досліджує сучасну мову права з точки зору когнітивної лінгвістики. Головною метою дослідження було дослідження особливостей англійської юридичної термінології та принципів її систематизації з точки зору когнітивної теорії і власне теорії концептуальної метафори. В ході написання роботи були поставлені наступні цілі: 1) визначити головні концепти які використовуються у якості метафор в англійській мові права; 2) встановити головні концептуальні зв’язки між окремими елементами доменів.З метою вирішення цих питань і задач був проведений кількісний аналіз корпусу юридичної англійської мови. В ході цього аналізу біли виділені та класифіковані метафоричні вирази які пов’язані з юридичною термінологією згідно їх метафоричного значення. В результаті аналізу було виявлено що концептуальні метафори WAR, MEDICINE, SPORT та CONSTRUCTION займають домінуюче положення в мові права. Також були встановлені основні концептуальні зв’язки між сферою-джерелом та сферою-ціллю.В даному дослідженні було використано спеціально створений корпус, який включає в себе 156 правових текстів різноманітної сюжетної направленості, для проведення кількісного аналізу з точки зору концептуальної метафори
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Niemiec, Moritz Sebastian. "Human copper ion transfer : from metal chaperone to target transporter domain." Doctoral thesis, Umeå universitet, Kemiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-100511.

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Many processes in living systems occur through transient interactions among proteins. Those interactions are often weak and are driven by small changes in free energy. Due to the short-living nature of these interactions, our knowledge about driving forces, dynamics and structures of these types of protein-protein heterocomplexes are though limited. This is especially important for cellular copper (Cu) trafficking: Copper ions are essential for all eukaryotes and most bacteria. As a cofactor in many enzymes, copper is especially vital in respiration or detoxification. Since the same features that make copper useful also make it toxic, it needs to be controlled tightly. Additionally, in the reducing environment of the cytosol, Cu is present as insoluble Cu(I). To circumvent both toxicity and solubility issues, a system has evolved where copper is comforted by certain copper binding proteins, so-called Cu-chaperones. They transiently interact with each other to distribute the Cu atoms in a cell. In humans, one of them is Atox1. It binds copper with a binding site containing two thiol residues and transfers it to other binding sites, mostly those of a copper pump, ATP7B (also known as Wilsons disease protein). My work was aimed at understanding copper-mediated protein-protein interactions on a molecular and mechanistic level. Which amino acids interact with the metal? Which forces drive the transfer from one protein to the other? Using biophysical and biochemical methods such as chromatography and calorimetry on wild type and point-mutated proteins in vitro, we found that the copper is transferred via a dynamic intermediate complex that keeps the system flexible while shielding the copper against other interactions. Although similar transfer interactions can be observed in other organisms, and many conclusions in the copper field are drawn from bacterial and yeast analogs, we believe that it is important to investigate human proteins, too. Not only is their regulation different, but also only in humans we find the diseases linked to the proteins: Copper level regulation diseases are to be named first, but atypical copper levels have also been linked to tumors and amyloid dispositions. In summary, my observations and conclusions are of basic research character and can be of importance for both general copper and human medicinal research.
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Schaus, Brian M. "Improving maritime domain awareness using neural networks for target of interest classification." Thesis, Monterey, California: Naval Postgraduate School, 2015. http://hdl.handle.net/10945/45252.

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Techniques for classifying maritime domain targets-of-interest within images are explored in this thesis. Geometric and photometric features within each image are extracted from processed images and are used to train a neural network. The trained neural network is tested with features of a known object. In the binary classification case, the neural network is used to determine whether a ship is present or not present in the image. In the multi-class and multi-level classification cases, the neural network is used to determine if the object belongs to one of four classes specified: warship, cargo ship, small boat, or other. The Hough transformation is used to identify and characterize linear patterns exhibited by objects in images. As an alternative to geometric and photometric features to classify targets-of-interest, these linear patterns are used to train a neural network. The performance of the neural network is then tested for binary, multi-class, and multi-level classification schemes. The development of neural-network-based techniques for automated target-of-interest classification is a significant result of this thesis.
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Ferrari, Giovanna Maria. "The interaction of the α2 chimaerin SH2 domain with target proteins." Thesis, University College London (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325678.

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Chen, Yen-Lun. "Margin and Domain Classifications for Target Detection over Huge Population of Outliers." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1269539889.

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Books on the topic "Target domain"

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Dewey, John K. Electrostatic target detection: A preliminary investigation. Monterey, Calif: Naval Postgraduate School, 1994.

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Lee, Christina. The SH3 domain of the yeast protein Fus1 binds and unusual target sequence. Ottawa: National Library of Canada, 2002.

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Behrle, Charles D. Computer simulation studies of multiple broadband target localization via frequency domain beamforming for planar arrays. Monterey, California: Naval Postgraduate School, 1988.

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Berube, Christina Louise. Characterization of PIDD, a death domain-containing p53 target gene. 2006.

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Bohon, Cara. Research Domain Criteria. Edited by W. Stewart Agras and Athena Robinson. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190620998.013.2.

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A primary goal of the research domain criteria (RDoC) project from the National Institute of Mental Health in the United States is to better characterize and understand the pathology and etiology of mental illness by examining constructs with biological underpinnings and their effects on psychiatric symptoms. This endeavor shows promise in helping to better conceptualize dysfunction in the field of eating disorders, where there appears to be great heterogeneity within diagnostic groups. Treatments designed for a particular diagnosis may result in improved remission rates if they instead target underlying mechanisms of eating disorder symptoms. This system is not without challenge and limitations, however. This chapter includes a brief review of relevant literature on the proposed RDoC functional domains in eating disorders and discussion of the benefits and costs of this type of approach in improving patient care.
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Anagnostopoulou, Elena. Voice, manners, and results in adjectival passives. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198767886.003.0005.

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The chapter argues that there are two functional heads in the VP domain: a little v head introducing an event and Voice introducing the external argument. Evidence is drawn from adjectival passives, which split into several types that can be described in terms of this architecture. The chapter explores the interaction between Voice, v, and manner vs. result interpretations of verbal meaning in resultant state vs. target state adjectival passives. First, a summary is given of the main arguments for postulating a v head and a Voice head in adjectival passives. The chapter then focuses on the absence of Voice in target state adjectival passives. New evidence for the absence of Voice comes from two empirical domains: constraints on verb classes that are allowed and disallowed to form target state adjectival passives and a phenomenon of coercion of manner, instrument-based denominal verbs into result verbs in target state adjectival passives.
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Goldman, Alvin I. Theory of Mind. Edited by Eric Margolis, Richard Samuels, and Stephen P. Stich. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780195309799.013.0017.

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The article provides an overview of ‘Theory of Mind’ (ToM) research, guided by two classifications. The first covers four competing approaches to mentalizing such as the theory-theory, modularity theory, rationality theory, and simulation theory. The second classification is the first-person/third-person contrast. Jerry Fodor claimed that commonsense psychology is so good at helping predict behavior that it is practically invisible. It works well because the intentional states it posits genuinely exist and possess the properties generally associated with them. The modularity model has two principal components. First, whereas the child-scientist approach claims that mentalizing utilizes domain-general cognitive equipment, the modularity approach posits one or more domain-specific modules, which use proprietary representations and computations for the mental domain. Second, the modularity approach holds that these modules are innate cognitive structures, which mature or come on line at preprogrammed stages and are not acquired through learning. The investigators concluded that autism impairs a domain-specific capacity dedicated to mentalizing. Gordon, Jane Heal, and Alvin Goldman explained simulation theory in such a way that mind readers simulate a target by trying to create similar mental states of their own as proxies or surrogates of those of the target. These initial pretend states are fed into the mind reader's own cognitive mechanisms to generate additional states, some of which are then imputed to the target.
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Skopeteas, Stavros. Information Structure in Modern Greek. Edited by Caroline Féry and Shinichiro Ishihara. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199642670.013.15.

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This chapter deals with the prosodic and syntactic reflexes of information structure in Modern Greek. The relevant properties of this language are: (a) the word order is sensitive to information structure, such that topics and foci target positions in the left periphery and background information is right dislocated; (b) the intonational nucleus depends on the focus domain and is realized through pitch accents; and (b) definite complements must be doubled through co-referent clitic pronouns if they are not accented, which depends on information structure. This chapter introduces these phenomena and outlines their interaction for the expression of information structural notions.
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Pillai, Jagan A. Predementia Disorders. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190233563.003.0009.

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Neurodegenerative disorders (NDDs) are currently conceptualized as proteinopathies with a long trajectory of pathological changes preceding the onset of clinical symptoms by over a decade. Predementia, the stage of disease before onset of clinical symptoms and dementia where significant irreversible neuronal damage and cognitive decline have yet to occur, is seen as a promising stage to target for a new generation of therapeutic interventions. This chapter reviews the growing understanding of the predementia stages across NDDs and some of the developing challenges to the present clinical characterization of the predementia stage. It further surveys the clinical trials being currently undertaken across NDDs in this domain.
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Axel-Tober, Katrin. Origins of verb-second in Old High German. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198813545.003.0003.

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This chapter investigates the characteristics of the left sentence periphery in Old High German. In the earlier OHG prose texts we still find some archaic characteristics of a non- or pre-verb-second grammar. These include residual and partly productive features of a non-conflated C-domain arguably inherited from Proto-Germanic or even Proto-Indo-European. On the other hand, there is ample evidence that the precursor of the so-called prefield position already existed in OHG and that it was already a target for both operator movement and Stylistic Fronting. All these phenomena shed interesting light on the question of which syntactic steps the language had to take in order consolidate its verb-second grammar.
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Book chapters on the topic "Target domain"

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Ranger, Graham. "Anyway: Configuration by Target Domain." In Discourse Markers, 93–134. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-70905-5_3.

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Dalgaard, Johnny. "ISPS Code Implementation: Overkill and Off-Target." In Sustainability in the Maritime Domain, 131–53. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69325-1_7.

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Zuo, Hua, Guangquan Zhang, and Jie Lu. "Fuzzy Domain Adaptation Using Unlabeled Target Data." In Neural Information Processing, 242–50. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04182-3_22.

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Lv, Fengmao, Hao Chen, Jinzhao Wu, Linfeng Zhong, Xiaoyu Li, and Guowu Yang. "Improving Target Discriminability for Unsupervised Domain Adaptation." In Neural Information Processing, 287–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04221-9_26.

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Bracamonte, Javier, Michael Ansorge, Fausto Pellandini, and Pierre-André Farine. "Efficient Compressed Domain Target Image Search and Retrieval." In Lecture Notes in Computer Science, 154–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11526346_19.

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Martin, Douglas W., and Whitlow W. L. Au. "An Automatic Target Recognition Algorithm Using Time-Domain Features." In Animal Sonar, 829–33. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-7493-0_89.

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Mironov, Ilya. "Domain Extension for Enhanced Target Collision-Resistant Hash Functions." In Fast Software Encryption, 153–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13858-4_9.

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Zhou, Haiyan. "Design of Bifunctional Antisense Oligonucleotides for Exon Inclusion." In Methods in Molecular Biology, 53–62. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2010-6_3.

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AbstractBifunctional antisense oligonucleotide (AON) is a specially designed AON to regulate pre-messenger RNA (pre-mRNA) splicing of a target gene. It is composed of two domains. The antisense domain contains sequences complementary to the target gene. The tail domain includes RNA sequences that recruit RNA binding proteins which may act positively or negatively in pre-mRNA splicing. This approach can be designed as targeted oligonucleotide enhancers of splicing, named TOES, for exon inclusion; or as targeted oligonucleotide silencers of splicing, named TOSS, for exon skipping. Here, we provide detailed methods for the design of TOES for exon inclusion, using SMN2 exon 7 splicing as an example. A number of annealing sites and the tail sequences previously published are listed. We also present methodology of assessing the effects of TOES on exon inclusion in fibroblasts cultured from a SMA patient. The effects of TOES on SMN2 exon 7 splicing were validated at RNA level by PCR and quantitative real-time PCR, and at protein level by western blotting.
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Ge, Hongwei, Yao Yao, Zheng Chen, and Liang Sun. "Unsupervised Transformation Network Based on GANs for Target-Domain Oriented Multi-domain Image Translation." In Computer Vision – ACCV 2018, 398–413. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20890-5_26.

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Schultz, Joachim E., Torsten Dunkern, Elvira Gawlitta-Gorka, and Gabriele Sorg. "The GAF-Tandem Domain of Phosphodiesterase 5 as a Potential Drug Target." In Phosphodiesterases as Drug Targets, 151–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17969-3_6.

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Conference papers on the topic "Target domain"

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Weeks, Deborah, and Samuel Rivera. "Domain adaptation by topology regularization." In Automatic Target Recognition XXXI, edited by Timothy L. Overman, Riad I. Hammoud, and Abhijit Mahalanobis. SPIE, 2021. http://dx.doi.org/10.1117/12.2585705.

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Zhang, Xiaohong, Haofeng Zhang, Jianfeng Lu, Ling Shao, and Jingyu Yang. "Target-targeted Domain Adaptation for Unsupervised Semantic Segmentation." In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021. http://dx.doi.org/10.1109/icra48506.2021.9560785.

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Liang, Jian, Dapeng Hu, and Jiashi Feng. "Domain Adaptation with Auxiliary Target Domain-Oriented Classifier." In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2021. http://dx.doi.org/10.1109/cvpr46437.2021.01636.

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Tang, Jianheng, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric Xing, and Zhiting Hu. "Target-Guided Open-Domain Conversation." In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/p19-1565.

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Havlicek, Joseph P., Chuong T. Nguyen, and Mark Yeary. "Modulation domain infrared target models." In Defense and Security Symposium, edited by Wendell R. Watkins and Dieter Clement. SPIE, 2006. http://dx.doi.org/10.1117/12.666340.

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Yao, Chun-Han, Boqing Gong, Hang Qi, Yin Cui, Yukun Zhu, and Ming-Hsuan Yang. "Federated Multi-Target Domain Adaptation." In 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2022. http://dx.doi.org/10.1109/wacv51458.2022.00115.

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Peng, Minlong, Qi Zhang, Yu-gang Jiang, and Xuanjing Huang. "Cross-Domain Sentiment Classification with Target Domain Specific Information." In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/p18-1233.

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Zhu, Feng, Yan Wang, Chaochao Chen, Guanfeng Liu, and Xiaolin Zheng. "A Graphical and Attentional Framework for Dual-Target Cross-Domain Recommendation." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/415.

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The conventional single-target Cross-Domain Recommendation (CDR) only improves the recommendation accuracy on a target domain with the help of a source domain (with relatively richer information). In contrast, the novel dual-target CDR has been proposed to improve the recommendation accuracies on both domains simultaneously. However, dual-target CDR faces two new challenges: (1) how to generate more representative user and item embeddings, and (2) how to effectively optimize the user/item embeddings on each domain. To address these challenges, in this paper, we propose a graphical and attentional framework, called GA-DTCDR. In GA-DTCDR, we first construct two separate heterogeneous graphs based on the rating and content information from two domains to generate more representative user and item embeddings. Then, we propose an element-wise attention mechanism to effectively combine the embeddings of common users learned from both domains. Both steps significantly enhance the quality of user and item embeddings and thus improve the recommendation accuracy on each domain. Extensive experiments conducted on four real-world datasets demonstrate that GA-DTCDR significantly outperforms the state-of-the-art approaches.
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Osahor, Uche, and Nasser Nasrabadi. "Deep adversarial attack on target detection systems." In Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, edited by Tien Pham. SPIE, 2019. http://dx.doi.org/10.1117/12.2518970.

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Wawer, Aleksander. "Towards Domain-Independent Opinion Target Extraction." In 2015 IEEE International Conference on Data Mining Workshop (ICDMW). IEEE, 2015. http://dx.doi.org/10.1109/icdmw.2015.255.

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Reports on the topic "Target domain"

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Hammerman, Peter. Characterization of the Discoidin Domain Receptor 2 Kinase as a Novel Therapeutic Target for Squamous Cell Lung Cancer. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada573105.

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Fluhr, Robert, and Maor Bar-Peled. Novel Lectin Controls Wound-responses in Arabidopsis. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7697123.bard.

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Innate immune responses in animals and plants involve receptors that recognize microbe-associated molecules. In plants, one set of this defense system is characterized by large families of TIR–nucleotide binding site–leucine-rich repeat (TIR-NBS-LRR) resistance genes. The direct interaction between plant proteins harboring the TIR domain with proteins that transmit and facilitate a signaling pathway has yet to be shown. The Arabidopsis genome encodes TIR-domain containing genes that lack NBS and LRR whose functions are unknown. Here we investigated the functional role of such protein, TLW1 (TIR LECTIN WOUNDRESPONSIVE1). The TLW1 gene encodes a protein with two domains: a TIR domain linked to a lectin-containing domain. Our specific aim in this proposal was to examine the ramifications of the TL1-glycan interaction by; A) The functional characterization of TL1 activity in the context of plant wound response and B) Examine the hypothesis that wounding induced specific polysaccharides and examine them as candidates for TL-1 interactive glycan compounds. The Weizmann group showed TLW1 transcripts are rapidly induced by wounding in a JA-independent pathway and T-DNA-tagged tlw1 mutants that lack TLW1 transcripts, fail to initiate the full systemic wound response. Transcriptome methodology analysis was set up and transcriptome analyses indicates a two-fold reduced level of JA-responsive but not JA-independent transcripts. The TIR domain of TLW1 was found to interact directly with the KAT2/PED1 gene product responsible for the final b-oxidation steps in peroxisomal-basedJA biosynthesis. To identify potential binding target(s) of TL1 in plant wound response, the CCRC group first expressed recombinant TL1 in bacterial cells and optimized conditions for the protein expression. TL1 was most highly expressed in ArcticExpress cell line. Different types of extraction buffers and extraction methods were used to prepare plant extracts for TL1 binding assay. Optimized condition for glycan labeling was determined, and 2-aminobenzamide was used to label plant extracts. Sensitivity of MALDI and LC-MS using standard glycans. THAP (2,4,6- Trihydroxyacetophenone) showed minimal background peaks at positive mode of MALDI, however, it was insensitive with a minimum detection level of 100 ng. Using LC-MS, sensitivity was highly increased enough to detect 30 pmol concentration. However, patterns of total glycans displayed no significant difference between different extraction conditions when samples were separated with Dionex ICS-2000 ion chromatography system. Transgenic plants over-expressing lectin domains were generated to obtain active lectin domain in plant cells. Insertion of the overexpression construct into the plant genome was confirmed by antibiotic selection and genomic DNA PCR. However, RT-PCR analysis was not able to detect increased level of the transcripts. Binding ability of azelaic acid to recombinant TL1. Azelaic acid was detected in GST-TL1 elution fraction, however, DHB matrix has the same mass in background signals, which needs to be further tested on other matrices. The major findings showed the importance of TLW1 in regulating wound response. The findings demonstrate completely novel and unexpected TIR domain interactions and reveal a control nexus and mechanism that contributes to the propagation of wound responses in Arabidopsis. The implications are to our understanding of the function of TIR domains and to the notion that early molecular events occur systemically within minutes of a plant sustaining a wound. A WEB site (http://genome.weizmann.ac.il/hormonometer/) was set up that enables scientists to interact with a collated plant hormone database.
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Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, December 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are obtained by manual sampling of the filed in a grid pattern. Maps of various field attributes are then prepared from these samples by the "Inverse Distance" interpolation method or by Kriging. An improved interpolation method was developed which is based on minimizing the overall curvature of the resulting map. Such maps are the ground truth reference, used for training the algorithm that generates the predicted field maps from remote sensing imagery. Both the reference and the predicted maps are stratified into "Prototype Plots", e.g. 15xl5 blocks of 2m pixels whereby the block size is 30x30m. This averaging reduces the datasets to manageable size and significantly improves the typically poor repeatability of remote sensing imaging systems. In the first two years of the project we used the Normalized Difference Vegetation Index (NDVI), for generating predicted yield maps of sugar beets and com. The NDVI was computed from image cubes of three spectral bands, generated by an optically filtered three camera video imaging system. A two dimensional FFT based regression model Y=f(X), was used wherein Y was the reference map and X=NDVI was the predictor. The FFT regression method applies the "Wavelet Based", "Pixel Block" and "Image Rotation" transforms to the reference and remote images, prior to the Fast - Fourier Transform (FFT) Regression method with the "Phase Lock" option. A complex domain based map Yfft is derived by least squares minimization between the amplitude matrices of X and Y, via the 2D FFT. For one time predictions, the phase matrix of Y is combined with the amplitude matrix ofYfft, whereby an improved predicted map Yplock is formed. Usually, the residuals of Y plock versus Y are about half of the values of Yfft versus Y. For long term predictions, the phase matrix of a "field mask" is combined with the amplitude matrices of the reference image Y and the predicted image Yfft. The field mask is a binary image of a pre-selected region of interest in X and Y. The resultant maps Ypref and Ypred aremodified versions of Y and Yfft respectively. The residuals of Ypred versus Ypref are even lower than the residuals of Yplock versus Y. The maps, Ypref and Ypred represent a close consensus of two independent imaging methods which "view" the same target. In the last two years of the project our remote sensing capability was expanded by addition of a CASI II airborne hyperspectral imaging system and an ASD hyperspectral radiometer. Unfortunately, the cross-noice and poor repeatability problem we had in multi-spectral imaging was exasperated in hyperspectral imaging. We have been able to overcome this problem by over-flying each field twice in rapid succession and developing the Repeatability Index (RI). The RI quantifies the repeatability of each spectral band in the hyperspectral image cube. Thereby, it is possible to select the bands of higher repeatability for inclusion in the prediction model while bands of low repeatability are excluded. Further segregation of high and low repeatability bands takes place in the prediction model algorithm, which is based on a combination of a "Genetic Algorithm" and Partial Least Squares", (PLS-GA). In summary, modus operandi was developed, for deriving important plant growth attribute maps (yield, leaf nitrate, biomass and sugar percent in beets), from remote sensing imagery, with sufficient accuracy for precision cropping applications. This achievement is remarkable, given the inherently high cross-noice between the reference and remote imagery as well as the highly non-repeatable nature of remote sensing systems. The above methodologies may be readily adopted by commercial companies, which specialize in proving remotely sensed data to farmers.
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Fromm, Hillel, and Joe Poovaiah. Calcium- and Calmodulin-Mediated Regulation of Plant Responses to Stress. United States Department of Agriculture, September 1993. http://dx.doi.org/10.32747/1993.7568096.bard.

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We have taken a molecular approach to clone cellular targets of calcium/calmodulin (Ca2+/CaM). A 35S-labeled recombinant CaM was used as a probe to screen various cDNA expression libraries. One of the isolated clones from petunia codes for the enzyme glutamate decarboxylase (GAD) which catalyzes the conversion of glutamate to g-aminobutyric acid (GABA). The activity of plant GAD has been shown to be dramatically enhanced in response to cold and heat shock, anoxia, drought, mechanical manipulations and by exogenous application of the stress phytohormone ABA in wheat roots. We have purified the recombinant GAD by CaM-affinity chromatography and studied its regulation by Ca2+/CaM. At a physiological pH range (7.0-7.5), the purified enzyme was inactive in the absence of Ca2+ and CaM but could be stimulated to high levels of activity by the addition of exogenous CaM (K0.5 = 15 nM) in the presence of Ca2+ (K 0.5 = 0.8 mM). Neither Ca2+ nor CaM alone had any effect on GAD activity. Transgenic tobacco plants expressing a mutant petunia GAD lacking the CaM-binding domain, or transgenic plants expressing the intact GAD were prepared and studied in detail. We have shown that the CaM-binding domain is necessary for the regulation of glutamate and GABA metabolism and for normal plant development. Moreover, we found that CaM is tightly associated with a 500 kDa GAD complex. The tight association of CaM with its target may be important for the rapid modulation of GAD activity by Ca2+ signaling in response to stresses.
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Eshed-Williams, Leor, and Daniel Zilberman. Genetic and cellular networks regulating cell fate at the shoot apical meristem. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7699862.bard.

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The shoot apical meristem establishes plant architecture by continuously producing new lateral organs such as leaves, axillary meristems and flowers throughout the plant life cycle. This unique capacity is achieved by a group of self-renewing pluripotent stem cells that give rise to founder cells, which can differentiate into multiple cell and tissue types in response to environmental and developmental cues. Cell fate specification at the shoot apical meristem is programmed primarily by transcription factors acting in a complex gene regulatory network. In this project we proposed to provide significant understanding of meristem maintenance and cell fate specification by studying four transcription factors acting at the meristem. Our original aim was to identify the direct target genes of WUS, STM, KNAT6 and CNA transcription factor in a genome wide scale and the manner by which they regulate their targets. Our goal was to integrate this data into a regulatory model of cell fate specification in the SAM and to identify key genes within the model for further study. We have generated transgenic plants carrying the four TF with two different tags and preformed chromatin Immunoprecipitation (ChIP) assay to identify the TF direct target genes. Due to unforeseen obstacles we have been delayed in achieving this aim but hope to accomplish it soon. Using the GR inducible system, genetic approach and transcriptome analysis [mRNA-seq] we provided a new look at meristem activity and its regulation of morphogenesis and phyllotaxy and propose a coherent framework for the role of many factors acting in meristem development and maintenance. We provided evidence for 3 different mechanisms for the regulation of WUS expression, DNA methylation, a second receptor pathway - the ERECTA receptor and the CNA TF that negatively regulates WUS expression in its own domain, the Organizing Center. We found that once the WUS expression level surpasses a certain threshold it alters cell identity at the periphery of the inflorescence meristem from floral meristem to carpel fate [FM]. When WUS expression highly elevated in the FM, the meristem turn into indeterminate. We showed that WUS activate cytokinine, inhibit auxin response and represses the genes required for root identity fate and that gradual increase in WUCHEL activity leads to gradual meristem enlargement that affect phyllotaxis. We also propose a model in which the direction of WUS domain expansion laterally or upward affects meristem structure differently. We preformed mRNA-seq on meristems with different size and structure followed by k-means clustering and identified groups of genes that are expressed in specific domains at the meristem. We will integrate this data with the ChIP-seq of the 4 TF to add another layer to the genetic network regulating meristem activity.
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Mei, Kenneth K. Time Domain Scattering of Focused Electromagnetic Beam by Lossy Targets. Fort Belvoir, VA: Defense Technical Information Center, September 1989. http://dx.doi.org/10.21236/ada227741.

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Curran, Meghan. Soft Targets & Black Markets: Terrorist Activities in the Maritime Domain. One Earth Future, May 2019. http://dx.doi.org/10.18289/oef.2019.038.

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Gafni, Yedidya, Moshe Lapidot, and Vitaly Citovsky. Dual role of the TYLCV protein V2 in suppressing the host plant defense. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7597935.bard.

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TYLCV-Is is a major tomato pathogen, causing extensive crop losses in Israel and the U.S. We have identified a TYLCV-Is protein, V2, which acts as a suppressor of RNA silencing. Intriguingly, the counter-defense function of V2 may not be limited to silencing suppression. Our recent data suggest that V2 interacts with the tomato CYP1 protease. CYP1 belongs to the family of papain-like cysteine proteases which participate in programmed cell death (PCD) involved in plant defense against pathogens. Based on these data we proposed a model for dual action of V2 in suppressing the host antiviral defense: V2 targets SGS3 for degradation and V2 inhibits CYP1 activity. To study this we proposed to tackle three specific objectives. I. Characterize the role of V2 in SGS3 proteasomal degradation ubiquitination, II. Study the effects of V2 on CYP1 maturation, enzymatic activity, and accumulation and, III. Analyze the effects of the CYP1-V2 interaction on TYLCV-Is infection. Here we describe results from our study that support our hypothesis: the involvement of the host's innate immune system—in this case, PCD—in plant defense against TYLCV-Is. Also, we use TYLCV-Is to discover the molecular pathway(s) by which this plant virus counters this defense. Towards the end of our study we discovered an interesting involvement of the C2 protein encoded by TYLCV-Is in inducing Hypersensitive Response in N. benthamianaplants which is not the case when the whole viral genome is introduced. This might lead to a better understanding of the multiple processes involved in the way TYLCV is overcoming the defense mechanisms of the host plant cell. In a parallel research supporting the main goal described, we also investigated Agrobacteriumtumefaciens-encoded F-box protein VirF. It has been proposed that VirF targets a host protein for the UPS-mediated degradation, very much the way TYLCV V2 does. In our study, we identified one such interactor, an Arabidopsistrihelix-domain transcription factor VFP3, and further show that its very close homolog VFP5 also interacted with VirF. Interestingly, interactions of VirF with either VFP3 or VFP5 did not activate the host UPS, suggesting that VirF might play other UPS-independent roles in bacterial infection. Another target for VirF is VFP4, a transcription factor that both VirF and its plant functional homolog VBF target to degradation by UPS. Using RNA-seqtranscriptome analysis we showed that VFP4 regulates numerous plant genes involved in disease response, including responses to viral and bacterial infections. Detailed analyses of some of these genes indicated their involvement in plant protection against Agrobacterium infection. Thus, Agrobacterium may facilitate its infection by utilizing the host cell UPS to destabilize transcriptional regulators of the host disease response machinery that limits the infection.
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Zhang, Zhongfei. Qualitive Detection of Independently Moving Targets in MPEG Video Within the Compressed Domain. Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada427149.

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Songyang, Zhou. A Proteomic Approach to Identify Phosphorylation-Dependent Targets of BRCT Domains. Fort Belvoir, VA: Defense Technical Information Center, March 2008. http://dx.doi.org/10.21236/ada487327.

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