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Auswahl der wissenschaftlichen Literatur zum Thema „Plaque neurale“
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Zeitschriftenartikel zum Thema "Plaque neurale"
Ma, Wei, Xinyao Cheng, Xiangyang Xu, Furong Wang, Ran Zhou, Aaron Fenster und Mingyue Ding. „Multilevel Strip Pooling-Based Convolutional Neural Network for the Classification of Carotid Plaque Echogenicity“. Computational and Mathematical Methods in Medicine 2021 (18.08.2021): 1–13. http://dx.doi.org/10.1155/2021/3425893.
Der volle Inhalt der QuelleLi, Lincan, Tong Jia, Tianqi Meng und Yizhe Liu. „Deep convolutional neural networks for cardiovascular vulnerable plaque detection“. MATEC Web of Conferences 277 (2019): 02024. http://dx.doi.org/10.1051/matecconf/201927702024.
Der volle Inhalt der QuelleKim, Jun-Min, Woo Ram Lee, Jun-Ho Kim, Jong-Mo Seo und Changkyun Im. „Light-Induced Fluorescence-Based Device and Hybrid Mobile App for Oral Hygiene Management at Home: Development and Usability Study“. JMIR mHealth and uHealth 8, Nr. 10 (16.10.2020): e17881. http://dx.doi.org/10.2196/17881.
Der volle Inhalt der QuelleStreit, Wolfgang J., Jonas Rotter, Karsten Winter, Wolf Müller, Habibeh Khoshbouei und Ingo Bechmann. „Droplet Degeneration of Hippocampal and Cortical Neurons Signifies the Beginning of Neuritic Plaque Formation“. Journal of Alzheimer's Disease 85, Nr. 4 (15.02.2022): 1701–20. http://dx.doi.org/10.3233/jad-215334.
Der volle Inhalt der QuelleLi, Yanhan, Lian Zou, Li Xiong, Fen Yu, Hao Jiang, Cien Fan, Mofan Cheng und Qi Li. „FRDD-Net: Automated Carotid Plaque Ultrasound Images Segmentation Using Feature Remapping and Dense Decoding“. Sensors 22, Nr. 3 (24.01.2022): 887. http://dx.doi.org/10.3390/s22030887.
Der volle Inhalt der QuelleZafar, Haroon, Junaid Zafar und Faisal Sharif. „Automated Clinical Decision Support for Coronary Plaques Characterization from Optical Coherence Tomography Imaging with Fused Neural Networks“. Optics 3, Nr. 1 (10.01.2022): 8–18. http://dx.doi.org/10.3390/opt3010002.
Der volle Inhalt der QuelleXia Wei, 夏巍, 韩婷婷 Han Tingting, 陶魁园 Tao Kuiyuan, 王为 Wang Wei und 高静 Gao Jing. „基于卷积神经网络的IVOCT冠状动脉钙化斑块分割方法“. Chinese Journal of Lasers 51, Nr. 18 (2024): 1801019. http://dx.doi.org/10.3788/cjl240833.
Der volle Inhalt der QuelleBusche, Marc Aurel, und Arthur Konnerth. „Impairments of neural circuit function in Alzheimer's disease“. Philosophical Transactions of the Royal Society B: Biological Sciences 371, Nr. 1700 (05.08.2016): 20150429. http://dx.doi.org/10.1098/rstb.2015.0429.
Der volle Inhalt der QuelleZhang, Yue, Haitao Gan, Furong Wang, Xinyao Cheng, Xiaoyan Wu, Jiaxuan Yan, Zhi Yang und Ran Zhou. „A self-supervised fusion network for carotid plaque ultrasound image classification“. Mathematical Biosciences and Engineering 21, Nr. 2 (2024): 3110–28. http://dx.doi.org/10.3934/mbe.2024138.
Der volle Inhalt der QuelleGuang, Yang, Wen He, Bin Ning, Hongxia Zhang, Chen Yin, Mingchang Zhao, Fang Nie et al. „Deep learning-based carotid plaque vulnerability classification with multicentre contrast-enhanced ultrasound video: a comparative diagnostic study“. BMJ Open 11, Nr. 8 (August 2021): e047528. http://dx.doi.org/10.1136/bmjopen-2020-047528.
Der volle Inhalt der QuelleDissertationen zum Thema "Plaque neurale"
Ghimouz, Rym. „Caractérisation du rôle des facteurs de transcription Homez et CBFbeta au cours de la neurogenèse et de la formation de la crête neurale chez Xenopus laevis“. Doctoral thesis, Universite Libre de Bruxelles, 2012. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209568.
Der volle Inhalt der QuelleLe premier clone d’ADNc code pour l’homologue du facteur de transcription Homez, contenant trois homéodomaines et deux motifs leucine zipper et dont la fonction est inconnue. Mes résultats ont montré que chez l’embryon de xénope au stade neurula, Homez est exprimé préférentiellement dans la plaque neurale, l’expression la plus forte étant détectée dans les domaines où les neurones primaires apparaissent. Plus tard, Homez est détecté dans le tube neural dans des cellules neurales postmitotiques en cours de différenciation. En accord avec ce profil d’expression, j’ai observé que Homez est régulé positivement par l’atténuation des signaux BMPs et par le facteur proneural Ngnr1 et négativement par la voie Notch. Bien que le facteur Homez ne soit pas suffisant pour induire une expression ectopique de marqueurs neuronaux dans l’embryon de xénope, j’ai pu montrer, en utilisant une approche de morpholino antisens, que celui-ci est requis en aval du facteur Ngnr1 pour la différenciation des précurseurs neuraux en neurones primaires.
Le deuxième clone code pour l’homologue du facteur CBFβ qui s’associe avec une famille de protéines CBFα1-3/Aml1-3/Runx1-3 pour former un complexe hétérodimérique liant l’ADN. Alors que chez la souris, les facteurs Runx1 et Runx3 jouent un rôle important dans la neurogenèse dans les ganglions spinaux et que chez le xénope, Runx1 est requis pour la formation des neurones Rohon-Beard, le rôle de CBFβ au cours du développement du système nerveux est actuellement mal connu. Mes résultats ont montré que chez l’embryon de xénope au stade neurula, CBFβ est coexprimé avec les facteurs Runx1-3 en bordure de la plaque neurale, mais de manière plus étendue et plus précoce. Comme attendu pour un marqueur de la bordure de la plaque neurale, j’ai observé que l’expression de CBFβ est régulée par les signaux BMP, Wnt, FGF et Notch. De manière intéressante, son expression est induite par les facteurs proneuraux alors que celle de Runx1 est inhibée. Des expériences de perte de fonction à l’aide de morpholinos antisens bloquant la traduction de CBFβ ont été réalisées. Ces expériences suggèrent que le facteur CBFβ est nécessaire à la mise en place de la CN et à la différenciation des neurones de Rohon-Beard.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
Panasenkava, Veranika. „Utilisation de cellules souches pluripotentes induites combinée à une approche transcriptomique pour améliorer le diagnostic moléculaire des troubles du neurodéveloppement chez l’homme“. Electronic Thesis or Diss., Université de Rennes (2023-....), 2024. http://www.theses.fr/2024URENB060.
Der volle Inhalt der QuelleAbstract : Holoprosencephaly (HPE) is a rare disorder that affects the development of the midline of the forebrain during the earliest stages of embryogenesis, making molecular diagnosis challenging. It primarily results from genetic alterations that lead to a reduction in the activity of the Sonic Hedgehog (SHH) signaling pathway. However, a precise molecular diagnosis is only possible for 30% of patients, highlighting the importance of developing new diagnostic approaches. The main challenge is the inaccessibility of the primary tissue, specifically the anterior affected by HPE, namely the anterior neuroectoderm. To overcome this challenge, I established an in vitro model of anterior neuroectoderm using induced pluripotent stem cells. This model allowed me to generate transcriptomic data to assess the molecular impacts of SHH deficiency and define transcriptomic signatures that describe variations in SHH pathway activity, which may correlate with the severity of HPE phenotypes. This work also revealed new co-expressed and SHH-regulated genes, which could serve as new genetic markers for HPE. These advances pave the way for innovative diagnostic tools aimed at improving diagnostic accuracy for patients with HPE
Kolluru, Chaitanya Kolluru. „Deep neural networks for A-line based plaque classification in intravascular optical coherence tomography images“. Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1530626730008246.
Der volle Inhalt der QuelleQurashi, Abrar Ahmad. „Neuronal remodeling in Drosophila melanogaster with WAVE/SCAR complex and its implication in cognitive functions“. Université Louis Pasteur (Strasbourg) (1971-2008), 2006. http://www.theses.fr/2006STR13112.
Der volle Inhalt der QuelleNeuronal morphogenesis and plasticity during development as well as in cognitive functions rely on actin cytoskeleton remodeling in response to extra-cellular signals that are interpreted by Rho family of small GTPases. The key subject of my thesis is to understand how signaling pathways downstream of Rac proteins, members of the Rho GTPase family, are utilized to orchestrate distinct aspects of neuronal morphogenesis and structural plasticity. WAVE/SCAR complex, an evolutionarily-conserved assembly of five proteins: WAVE (SCAR), PIR121 (CYFIP), Hem-2 (Kette), Abi and HSPC300 has emerged as a critical link between Rac1 and Arp2/3, molecular complex triggering actin nucleation. During my thesis I have used Drosophila melanogaster as a model system to understand the physiological significance of WAVE/SCAR complex. We have elucidated its role in neuronal actin remodeling underlying axon as well synapse development. Specifically, I have isolated mutations in the HSPC300 gene, and present its detailed characterization both at genetic and biochemical level. My thesis work provides evidence that in Drosophila melanogater SCAR, CYFIP, Kette and HSPC300 associate together to form a complex. All these proteins are highly expressed in the embryonic nervous system and show strong accumulation in central and motor neurons. Interestingly, in many processes examined, there are striking similarities between the phenotypes resulting from the mutations in any member of the complex, for example defects in axon path-finding, axon growth and Neuromuscular Junction (NMJ) morphology, thus demonstrating their pivotal roles for precise neuronal development. By biochemical and genetic experiments, we demonstrated that loss of any of the complex components leads to instability in other components. Therefore, the results provide an unequivocal reason for the common pathological condition noticed in single mutation of the WAVE/SCAR complex. Interestingly, mutation in individual components of the complex not only affects the stability of other complex components but also affects the multiple downstream pathways associated with them. For example, mutation in any component of the complex has an impact on CYFIP signaling to the Fragile X Mental Retardation Protein (FMRP) implicated in learning and memory in humans. Thus, our results identify the Drosophila WAVE/SCAR complex as a multifunctional unit orchestrating different pathways and aspects of neuronal connectivity and support an emerging theme: different aspects of xv morphogenesis may involve the regulation of common core signaling pathways. Additionally, my thesis also demonstrates the interaction of all three Racs (Rac1, Rac2 and Mtl) with CYFIP and suggests their requirement during NMJ growth and plasticity
Ravel-Chapuis, Aymeric. „Etude du contrôle des modifications de la chromatine musculaire par les facteurs neuraux“. Lyon, École normale supérieure (sciences), 2006. http://www.theses.fr/2006ENSL0379.
Der volle Inhalt der QuelleBosque-Freeman, Léorah. „Imagerie de la dégénérescence neuronale dans une maladie démyélinisante : la sclérose en plaques“. Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066522/document.
Der volle Inhalt der QuelleMultiple sclerosis (MS) has long been regarded as an inflammatory demyelinating disorder of the white matter. But post-mortem studies have recently shed light on the extensive involvement of the grey matter (GM). Neuronal damage, characterized by synaptic and dendritic loss as well as neuronal apoptosis, is thought to be a major substrate of physical and cognitive deterioration in MS patients. There is a crucial need for new imaging techniques able to specifically assess neuronal damage in MS. Using positron emission tomography (PET) with [11C]flumazenil ([11C]FMZ), an antagonist of the central benzodiazepine site located within the GABAA receptor, and a non-invasive quantification method, we measured and mapped neurodegenerative changes in the GM of patients with MS at distinct disease stages. A cohort of 18 MS patients was compared to 8 healthy controls and underwent neurological and cognitive evaluations, high-resolution dynamic [11C]FMZ PET imaging and brain MRI. PET data were evaluated using a region of interest and a surface-based approach. [11C]FMZ binding was significantly decreased in the cortical and subcortical GM of MS patients compared to controls. These changes were significant in both progressive and relapsing-remitting forms of the disease and correlated moderately with white matter lesion load. [11C]FMZ cortical binding was also associated with cognitive performance. This pilot study is the first to quantify in vivo the neurodegenerative changes occurring in MS. Our results show that PET with [11C]FMZ could be a promising and sensitive quantitative marker to assess and map the neuronal substrate of GM pathology in MS
Lefevre, Fabien. „Caractérisation de structures du type plaque par ondes guidées générées et détectées par laser“. Valenciennes, 2010. http://ged.univ-valenciennes.fr/nuxeo/site/esupversions/24980ba6-f06c-4c75-988a-16e1228d2e42.
Der volle Inhalt der QuelleThe deposition of thin layers on substrates is more and more required in many applications. For example, to reach high technical performance, bumpers or other parts are nickeled to improve their impermeability and resistance. Another example in microelectronics is the realization of transistors found in LCDs where they are associated with each pixel. The use of these layer/substrate structures is growing, so the importance of having non-destructive techniques to monitor and characterize them is well understood. The point in using ultrasonic waves for non-destructive testing and evaluation of various materials and structures is well known. In this work, the aim was to use guided waves to monitor and to characterize plaque-like structures. The main advantage of using these modes lies in their ability to test very large areas and inaccessible structures. For the generation and detection of guided waves, the laser ultrasonics technique was preferred. It is a broadband and non contact method which doesn't imply the use of coupling medium and which can be adapted to complex geometries. To take full advantage of this technique, it has been combined with neural networks in order to solve the inverse problem posed by the propagation of guided waves. As a result, an original, e cient and polyvalent characterization method has been obtained, which allowed us to determine the geometric properties and / or the elastic parameters of di erent plate-like structures. Structures made of silicon have been studied with this method. Finite element simulations and studies concerning the in uence of defects, including adhesion, on the waves propagation are also presented
Schwartz, David, und David Schwartz. „Navigational Neural Coding and De-noising“. Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/625322.
Der volle Inhalt der QuelleBlair, Joel. „Building a better Placode: Modeling Neural Plate Border interactions with hPSCs“. University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627663141272833.
Der volle Inhalt der QuelleThelander, Jenny. „Neural Mechanisms Underlying Self-Localization in Rodents“. Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-11339.
Der volle Inhalt der QuelleBücher zum Thema "Plaque neurale"
Donaghy, Michael. The clinical approach. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780198569381.003.0030.
Der volle Inhalt der QuelleKam, Julia W. Y., und Todd C. Handy. Electrophysiological Evidence for Attentional Decoupling during Mind-Wandering. Herausgegeben von Kalina Christoff und Kieran C. R. Fox. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190464745.013.13.
Der volle Inhalt der QuelleGranacher, Robert P. Behavioral Neurological Aspects Involving the Elderly and the Law. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199374656.003.0003.
Der volle Inhalt der QuelleHalassa, Michael M., Hrsg. The Thalamus. Cambridge University Press, 2022. http://dx.doi.org/10.1017/9781108674287.
Der volle Inhalt der QuelleTumber, Paul Singh, und Philip W. H. Peng. Peripheral Nerve Blocks in Chronic Pain. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199908004.003.0037.
Der volle Inhalt der Quelle12th International School-Seminar “Satellite Methods and Systems for Earth Exploration”. IKI, 2024. http://dx.doi.org/10.21046/2070-7401-12tarusa2024.
Der volle Inhalt der QuelleBuchteile zum Thema "Plaque neurale"
Cho, Hyungjoo, Dongmin Choi, Hyun-Seok Min, Soo-Jin Kang und Hwiyoung Kim. „Neural Angular Plaque Characterization: Automated Quantification of Polar Distribution for Plaque Composition“. In Lecture Notes in Computer Science, 113–22. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93722-5_13.
Der volle Inhalt der QuelleAnam, Syaiful, Eiji Uchino und Noriaki Suetake. „Coronary Plaque Boundary Calculation in IVUS Image by Modified PMD Filter and Fuzzy Inference“. In Neural Information Processing, 509–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-42051-1_63.
Der volle Inhalt der QuelleStasiak, Bartłomiej, Paweł Tarasiuk, Izabela Michalska, Arkadiusz Tomczyk und Piotr S. Szczepaniak. „Convolutional Neural Network Based Segmentation of Demyelinating Plaques in MRI“. In Biomedical Engineering Systems and Technologies, 163–88. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94806-5_10.
Der volle Inhalt der QuelleWang, Liang, und Jianxin Zhao. „Deep Neural Networks“. In Architecture of Advanced Numerical Analysis Systems, 121–47. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8853-5_5.
Der volle Inhalt der QuelleBlahuta, Jiri, Tomas Soukup und Jakub Skacel. „Pilot Design of a Rule-Based System and an Artificial Neural Network to Risk Evaluation of Atherosclerotic Plaques in Long-Range Clinical Research“. In Artificial Neural Networks and Machine Learning – ICANN 2018, 90–100. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01421-6_9.
Der volle Inhalt der QuelleCheimariotis, G. A., M. Riga, K. Toutouzas, D. Tousoulis, A. Katsaggelos und N. Maglaveras. „Automatic Characterization of Plaques and Tissue in IVOCT Images Using a Multi-step Convolutional Neural Network Framework“. In IFMBE Proceedings, 261–65. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-9035-6_47.
Der volle Inhalt der QuelleHooker, Cliff. „On the Organizational Roots of Bio-cognition“. In History, Philosophy and Theory of the Life Sciences, 85–102. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-38968-9_5.
Der volle Inhalt der QuelleOldenburg, Ian Antón, Hayley Anne Bounds und Nicolas C. Pégard. „High-Speed All-Optical Neural Interfaces with 3D Temporally Focused Holography“. In Neuromethods, 101–35. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-2764-8_4.
Der volle Inhalt der QuelleAgerri, Rodrigo, Eneko Agirre, Itziar Aldabe, Nora Aranberri, Jose Maria Arriola, Aitziber Atutxa, Gorka Azkune et al. „State-of-the-Art in Language Technology and Language-centric Artificial Intelligence“. In European Language Equality, 13–38. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28819-7_2.
Der volle Inhalt der QuelleBlahuta, Jiří, Tomáš Soukup und Jiri Martinu. „An Expert System Based on Using Artificial Neural Network and Region-Based Image Processing to Recognition Substantia Nigra and Atherosclerotic Plaques in B-Images: A Prospective Study“. In Advances in Computational Intelligence, 236–45. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59153-7_21.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Plaque neurale"
Yoshidomi, Takeshi, Shinji Kume, Hiroaki Aizawa und Akira Furui. „Classification of Carotid Plaque with Jellyfish Sign Through Convolutional and Recurrent Neural Networks Utilizing Plaque Surface Edges“. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 1–4. IEEE, 2024. https://doi.org/10.1109/embc53108.2024.10782813.
Der volle Inhalt der QuelleKumari, Anuradha, und M. Tanveer. „Dual center based intuitionistic fuzzy plane based classifiers“. In 2024 International Joint Conference on Neural Networks (IJCNN), 1–8. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650896.
Der volle Inhalt der QuelleMedeiros, Thiago, und Alfredo Weitzenfeld. „A Place Cell Model for Spatio-Temporal Navigation Learning with LSTM“. In 2024 International Joint Conference on Neural Networks (IJCNN), 1–8. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650241.
Der volle Inhalt der QuelleMonvoisin, Mathilde, Yuxin Zhang und Diana Mateus. „Compact Implicit Neural Representations for Plane Wave Images“. In 2024 IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint Symposium (UFFC-JS), 1–4. IEEE, 2024. https://doi.org/10.1109/uffc-js60046.2024.10793747.
Der volle Inhalt der QuelleRao, Milind Singh, Anita Agrawal und Ananth Raghav. „Neural Net-Eyes: Advanced License Plate Recognition System“. In 2024 International Conference on Modeling, Simulation & Intelligent Computing (MoSICom), 7–10. IEEE, 2024. https://doi.org/10.1109/mosicom63082.2024.10881497.
Der volle Inhalt der QuelleHe, Shenglin, Xiaoyang Qu, Jiguang Wan, Guokuan Li, Changsheng Xie und Jianzong Wang. „PRENet: A Plane-Fit Redundancy Encoding Point Cloud Sequence Network for Real-Time 3D Action Recognition“. In 2024 International Joint Conference on Neural Networks (IJCNN), 1–8. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650453.
Der volle Inhalt der QuelleLuu, Nhan T., Duong T. Luu, Pham Ngoc Nam und Truong Cong Thang. „Improvement of Spiking Neural Network with Bit Plane Coding“. In 2024 IEEE 16th International Conference on Computational Intelligence and Communication Networks (CICN), 1220–24. IEEE, 2024. https://doi.org/10.1109/cicn63059.2024.10847438.
Der volle Inhalt der QuelleLuo, Yilin, Anle Wang, Mengmeng Liu, Tian Lei, Xiaochuan Zhang, Zhaobing Gao, Hualiang Liang, Hui Gong und Jing Yuan. „Cryo-micro-optical sectioning tomography for label-free brainwide visualization of senile plaque (Conference Presentation)“. In Neural Imaging and Sensing 2018, herausgegeben von Qingming Luo und Jun Ding. SPIE, 2018. http://dx.doi.org/10.1117/12.2296253.
Der volle Inhalt der QuelleTian, Wei, Yishen Pang, Sijie Niu, Haochen Yang, Jiwen Dong, Jin Zhou und Yuehui Chen. „Automatic identification of vulnerable plaque based on flexible neural tree“. In 2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2018. http://dx.doi.org/10.1109/spac46244.2018.8965435.
Der volle Inhalt der QuelleDong, Yuxi, Yuchao Pan, Xihai Zhao, Rui Li, Chun Yuan und Wei Xu. „Identifying Carotid Plaque Composition in MRI with Convolutional Neural Networks“. In 2017 IEEE International Conference on Smart Computing (SMARTCOMP). IEEE, 2017. http://dx.doi.org/10.1109/smartcomp.2017.7947015.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Plaque neurale"
Rafaeli, Ada, Russell Jurenka und Chris Sander. Molecular characterisation of PBAN-receptors: a basis for the development and screening of antagonists against Pheromone biosynthesis in moth pest species. United States Department of Agriculture, Januar 2008. http://dx.doi.org/10.32747/2008.7695862.bard.
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