Relevant bibliographies by topics / FZG machine

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Academic literature on the topic 'FZG machine'

Author: Grafiati
Published: 7 October 2023

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Journal articles on the topic "FZG machine"

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Höhn, B. R., and H. Winter. "Laboratories at work: Institute for machine elements, Gear Research Centre (FZG)." Tribotest 3, no. 3 (March 1997): 325–40. http://dx.doi.org/10.1002/tt.3020030306.

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Hargreaves, D. J., and Anton Planitz. "Assessing the energy efficiency of gear oils via the FZG test machine." Tribology International 42, no. 6 (June 2009): 918–25. http://dx.doi.org/10.1016/j.triboint.2008.12.016.

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Winter, H. "Integrating Universities and Industry—A German Approach." Proceedings of the Institution of Mechanical Engineers, Part B: Management and engineering manufacture 202, no. 1 (February 1988): 9–17. http://dx.doi.org/10.1243/pime_proc_1988_202_041_02.

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Starting from a list of topics which were suggested by the Institution of Mechanical Engineers this paper surveys the situation at German technical universities in the field of mechanical engineering. The details of teaching and research activities described here refer to the Institute for Machine Elements, Technical University of Munich, but the principles of the organization and the structure are mostly comparable with corresponding institutes at other universities in the Federal Republic of Germany. The following subjects will be discussed: 1. The organization of German technical universities, in particular the Institute's structure of a Faculty of Mechanical Engineering. 2. Undergraduate courses in engineering based on ‘vocational’ education; the means to ensure an education of approximately equal academic standard at different universities. 3. Machine element teaching at undergraduate level; efforts to ensure an equal level of knowledge in this field. 4. The structure and funding of postgraduate engineering research centres and institutes. For example the relationship between the Gear Research Centre (FZG) and the gearing and transmission industry in Germany will be discussed. 5. A summary of the research carried out at the FZG (gears, clutches, tribology)
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Massocchi, Davide, Marco Lattuada, Steven Chatterton, and Paolo Pennacchi. "SRV Method: Lubricating Oil Screening Test for FZG." Machines 10, no. 8 (July 28, 2022): 621. http://dx.doi.org/10.3390/machines10080621.

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Governments and institutions have the following sustainable development goals: the improvement of energy efficiency and the reduction of CO2 emissions, in a “green economy” approach, have currently become the fundamental drivers that push research and development activity toward the optimization of rotating machine components in the industrial sector, with a special focus on lubrication systems too. The activity is directed towards the optimization of tribological testing methods and equipment to better discriminate the performance of lubricants in operating conditions as predictive as possible of real applications. In this context, the present paper describes the results of an experimental campaign based on the use of a well-selected linear oscillation SRV * (Schwingung, Reibung, Verschleiss) tribometer procedure as a screening of a rig test, the FZG ** (Forschungsstelle für Zahnräder und Getreibebau (German: Research Centre for Gears and Gear; University of Munich; Munich, Germany)) test, leading to concrete benefits such as saving time (time duration is 76% less without mentioning visual inspection and mounting/dismounting phase) and operative costs. Four cases for the determination of the failure load stage of SRV have been defined as links to seizure and microseizure phenomena. The procedure was tested for ten oils differing in scope (gas turbine oil, turbine oil, gear oil and circulating oil). The tests have been repeated three times and a procedure was defined for repeatability (± 1 stage difference between the minimum and maximum) for nine out of ten cases a failure stage could be defined. The same oils were also tested using the FZG scuffing test, and it can be seen that the results are very comforting as follows: a good correlation with the FZG rig test has been found for eight out of ten oils.
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Ayel, J., Y. Kraus, and J. P. Michel. "Séverisation de l'essai de capacité de charge des lubrifiants sur machine a engrenages FZG." Revue de l'Institut Français du Pétrole 40, no. 6 (November 1985): 831–42. http://dx.doi.org/10.2516/ogst:1985049.

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Durand de Gevigney, J., C. Changenet, F. Ville, and P. Velex. "Thermal modelling of a back-to-back gearbox test machine: Application to the FZG test rig." Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology 226, no. 6 (January 16, 2012): 501–15. http://dx.doi.org/10.1177/1350650111433243.

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A thermal model of a back-to-back gear test rig relying on a network approach is presented in which the predictions of temperatures and power losses are coupled. The numerical findings are in good agreement with the measurements for transient regimes on a FZG test rig and it is demonstrated that the proposed simulation is reliable. A number of results are presented which illustrate the influence of the pinion and gear immersion depths. It is found that, in certain conditions, the classic isothermal method for estimating integral temperatures is questionable because the actual bulk temperature can substantially deviate from that of the oil sump. The practical consequences in terms of scuffing capacity are emphasised.
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Tao, J., T. G. Hughes, H. P. Evans, R. W. Snidle, N. A. Hopkinson, M. Talks, and J. M. Starbuck. "Elastohydrodynamic Lubrication Analysis of Gear Tooth Surfaces From Micropitting Tests." Journal of Tribology 125, no. 2 (March 19, 2003): 267–74. http://dx.doi.org/10.1115/1.1510881.

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The paper presents numerical results for the elastohydrodynamic lubrication of gear teeth using real surface roughness data taken from micropitting tests carried out on an FZG gear testing machine. Profiles and load conditions corresponding to four load stages in the micropitting test protocol are considered. Elastohydrodynamic film thickness and pressure analyses are presented for conditions having a slide/roll ratio of 0.3 during the single tooth contact phase of the meshing cycle. Comparisons are also included showing the elastohydrodynamic response of the tooth contacts at different times in the meshing cycle for one of the load stages. The rheological model adopted is based on Ree-Eyring non-Newtonian shear thinning, and comparisons are also included of models having constant and different pressure-dependent specifications of the Eyring shear stress parameter τ0. Parameters obtained from the micro EHL analyses are presented that quantify the degree of adversity experienced by the surfaces in elastohydrodynamic contact. These quantify extreme pressure behavior, extreme proximity of surfaces, and pressure cycling within the overall contact and indicate that the different fluid models considered lead to significantly different pressure and film thickness behavior within the contact.
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Hlebanja, Gorazd. "Gradual development of S-shaped gears." MATEC Web of Conferences 366 (2022): 01001. http://dx.doi.org/10.1051/matecconf/202236601001.

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Search for an improved gear tooth flank shape arose from heavy industry problems rolling mills. Original involute gears suffered severe flank damages. So, better gear teeth flanks should improve contact circumstances, decrease the flank pressure, and enhance a lubrication film. This was achieved by a curved, pole symmetric path of contact by purely graphical methods. And the developed gears, proven in heavy industry applications, showed highly improved properties. Specimens of both gear geometries, which were made of tempered and nitrided alloy steel, were tested on an FZG testing machine, and results confirmed the theoretical foundations of S-gears. Then it was necessary to replace the graphical method by a numerical one and to define the tool. So, the rack profile was defined by a pole symmetric parabolic-type function, which in turn defined the path of contact and finally gears with an arbitrary number of teeth. Many applications were developed with S-gear shape, e.g., helical, crossed, and planetary gears, various worm drives, etc. S-gear concept was also used with polymer gears and high transmission ratio planetary gears. Lately, this concept was used to develop crossed helical gear drive with perpendicular shafts. Such drives are often used in centrifuge drives (e. g. Alfa-Laval) and this implementation with the module m = 5 mm uses a large driving gear with 60 teeth (with the left-handed helix angle of 30°) on the horizontal shaft and a smaller driven gear with 20 teeth (with the right-handed helix angle of 60°) on the vertical shaft. This paper is a tribute to work of Professor Jože Hlebanja (1926-2022) whose research was dedicated to gears with improved properties, namely S-gears.
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Arri, Harwant Singh, Ramandeep Singh, Sudan Jha, Deepak Prashar, Gyanendra Prasad Joshi, and Ill Chul Doo. "Optimized Task Group Aggregation-Based Overflow Handling on Fog Computing Environment Using Neural Computing." Mathematics 9, no. 19 (October 7, 2021): 2522. http://dx.doi.org/10.3390/math9192522.

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It is a non-deterministic challenge on a fog computing network to schedule resources or jobs in a manner that increases device efficacy and throughput, diminishes reply period, and maintains the system well-adjusted. Using Machine Learning as a component of neural computing, we developed an improved Task Group Aggregation (TGA) overflow handling system for fog computing environments. As a result of TGA usage in conjunction with an Artificial Neural Network (ANN), we may assess the model’s QoS characteristics to detect an overloaded server and then move the model’s data to virtual machines (VMs). Overloaded and underloaded virtual machines will be balanced according to parameters, such as CPU, memory, and bandwidth to control fog computing overflow concerns with the help of ANN and the machine learning concept. Additionally, the Artificial Bee Colony (ABC) algorithm, which is a neural computing system, is employed as an optimization technique to separate the services and users depending on their individual qualities. The response time and success rate were both enhanced using the newly proposed optimized ANN-based TGA algorithm. Compared to the present work’s minimal reaction time, the total improvement in average success rate is about 3.6189 percent, and Resource Scheduling Efficiency has improved by 3.9832 percent. In terms of virtual machine efficiency for resource scheduling, average success rate, average task completion success rate, and virtual machine response time are improved. The proposed TGA-based overflow handling on a fog computing domain enhances response time compared to the current approaches. Fog computing, for example, demonstrates how artificial intelligence-based systems can be made more efficient.
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Alalibo, Belema P., Bing Ji, and Wenping Cao. "Short Circuit and Broken Rotor Faults Severity Discrimination in Induction Machines Using Non-invasive Optical Fiber Technology." Energies 15, no. 2 (January 14, 2022): 577. http://dx.doi.org/10.3390/en15020577.

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Multiple techniques continue to be simultaneously utilized in the condition monitoring and fault detection of electric machines, as there is still no single technique that provides an all-round solution to fault finding in these machines. Having various machine fault-detection techniques is useful in allowing the ability to combine two or more in a manner that will provide a more comprehensive application-dependent condition-monitoring solution; especially, given the increasing role these machines are expected to play in man’s transition to a more sustainable environment, where many more electric machines will be required. This paper presents a novel non-invasive optical fiber using a stray flux technique for the condition monitoring and fault detection of induction machines. A giant magnetostrictive transducer, made of terfenol-D, was bonded onto a fiber Bragg grating, to form a composite FBG-T sensor, which utilizes the machines’ stray flux to determine the internal condition of the machine. Three machine conditions were investigated: healthy, broken rotor, and short circuit inter-turn fault. A tri-axial auto-data-logging flux meter was used to obtain stray magnetic flux measurements, and the numerical results obtained with LabView were analyzed in MATLAB. The optimal positioning and sensitivity of the FBG-T sensor were found to be transverse and 19.3810 pm/μT, respectively. The experimental results showed that the FBG-T sensor accurately distinguished each of the three machine conditions using a different order of magnitude of Bragg wavelength shifts, with the most severe fault reaching wavelength shifts of hundreds of picometres (pm) compared to the healthy and broken rotor conditions, which were in the low-to-mid-hundred and high-hundred picometre (pm) range, respectively. A fast Fourier transform (FFT) analysis, performed on the measured stray flux, revealed that the spectral content of the stray flux affected the magnetostrictive behavior of the magnetic dipoles of the terfenol-D transducer, which translated into strain on the fiber gratings.
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Dissertations / Theses on the topic "FZG machine"

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Grenet, de Bechillon Nicolas. "Approche multi-échelles pour l'étude du grippage des dentures d'engrenages." Electronic Thesis or Diss., Lyon, INSA, 2023. http://www.theses.fr/2023ISAL0024.

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La prochaine génération de moteurs civils nécessite l’intégration de réducteurs à engrenages afin de permettre l’augmentation du rendement. Afin de concevoir un produit fiable, il convient de s’intéresser aux différents modes de défaillance et en particulier le grippage des dentures. Le grippage engendre une dégradation de l’état de surface des dentures, qui se traduit par une réduction du rendement de la transmission. Cet endommagement est caractérisé par la formation et l’arrachement de microsoudures au cours de l’engrènement. De nombreux critères ont été mis en place afin de tenter de prédire l’initiation de cette défaillance, sans pour autant que l’un d’entre eux ne fasse l’unanimité au sein de la communauté scientifique. La physique de l’initiation du grippage doit donc être étudiée. Afin d’apporter des éléments de réponse sur le mécanisme d’initiation de ce phénomène, la première partie de cette étude s’est attachée à investiguer le rôle de la rugosité. Un modèle numérique a été mis en place afin d’évaluer le rôle de la rugosité vis-à-vis des températures localement atteintes dans la zone de contact. Les calculs réalisés montrent que les températures atteintes ne semblent pas en mesure d’expliquer la formation de microsoudures par fusion des surfaces dans un contact lubrifié. Ces microsoudures semblent donc être la conséquence d’une potentielle rupture du film lubrifiant et non le point de départ de l’initiation du grippage. Cette rupture du film a été étudiée expérimentalement sur un dispositif de laboratoire permettant de simuler un contact représentatif de l’engrènement via l’utilisation de deux disques. Dans cette seconde partie, une procédure permettant d’étudier le phénomène en agissant sur l’épaisseur du film lubrifiant a été développée. Les essais réalisés semblent montrer que la rupture du film lubrifiant est gouvernée par sa température, qui dépend des conditions de fonctionnement. Ainsi, une piste de critère de grippage a été établie sur disques. Dans une dernière partie, des essais dentures ont été mis en place afin d’évaluer la piste de critère identifiée sur disques en la transposant à la denture. Les essais réalisés montrent, comme lors des essais bi-disques, que la température totale à elle seule ne permet pas de prédire le grippage. Cependant, le critère développé sur disques ne semble pas en mesure d’expliquer les grippages des dentures lors des essais réalisés. Dans la mesure où ni les critères classiques ni la piste identifiée sur disques ne semblent en mesure d’expliquer le grippage, une nouvelle approche est proposée. Enfin, les conclusions sur la chronologie du mécanisme d’initiation du grippage sont regroupées et des perspectives sont mises en avant. Celles-ci visent à améliorer la représentativité des disques vis-à-vis des dentures au sujet de l’état de surface, ou à investiguer expérimentalement l’hypothèse de la rupture du film lubrifiant comme mécanisme d’initiation du grippage
Environmental concerns are driving the aerospace industry to innovate and develop new technologies to achieve sustainable aviation. Among these innovations, the next generation of civil engines requires the integration of gearboxes within them. In order to design a reliable product, different failure modes, such as gear scuffing, must be taken into account. Scuffing is a sudden gear failure where material is transferred from one surface to another. This transfer is caused by local surface welding during meshing. Scuffing leads to degradation of the tooth surface, which reduces gear efficiency. Although this mode of gear failure has been extensively studied, there are no commonly accepted initiation criteria. Therefore, physical understanding of scuffing initiation is needed. The first part of this study focused on the role of roughness. A numerical model was set up to evaluate the temperatures reached locally in the contact zone. The calculations carried out show that these last ones at the roughness scale do not seem able to explain the formation of micro-welds by fusion of the surface asperities in a lubricated contact. Scuffing therefore appear to be the consequence of a potential break in the lubricant film. In a second part, this film breakage was studied experimentally on a twin-disk machine. A procedure was developed to study the phenomenon by acting on the lubricant film thickness. The performed tests seem to show that the breakdown of the lubricating film is governed by its temperature, which depends directly on the operating conditions. Thus, a scuffing criterion was established on discs.In the last part, gear tests were carried out. It was shown, as for disc tests, that total temperature alone does not predict scuffing. However, the criterion developed on discs does not seem to be able to explain tooth scuffing. Since no criteria seem to be able to explain the scuffing, a new approach is proposed. Finally, conclusions and prospects are proposed. The chronology of the scuffing initiation mechanism are recalled. The prospects aim, on the one hand, to improve the representativeness of the tests on discs compared to gears, in particular with regard to the geometry of the surface roughness; and, on the other hand, to analyse in detail and experimentally the hypothesis of the lubricating film breakage as a mechanism of scuffing initiation
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Badokhon, Alaa. "An Adaptable, Fog-Computing Machine-to-Machine Internet of Things Communication Framework." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1492450137643915.

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Holas, Jiří. "Modernizace řízení frézky FNG." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-442843.

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This thesis deals with a proposal modernisation of control and electroinstalation of the milling machine FNG 32. The thesis is divided into several sections: The first section is dedicated to the research of the milling machine and the description of its current condition. The second section deals with possible options of retrofitting and with the components.The third section includes the technical and economical evaluation and the selection of the solution. In the next section, the selected components are described and an electronic documentation of the machine has been created in EPLAN. In the last section, a proposal of control of the milling machine has been created with the help of the TwinCAT development environment provided by Beckhoff company.
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Gullo, Thomas W. "A Methodology to Evaluate the Dynamic Behavior of Back-to-back Test Machines." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555588592218025.

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Lu, Shen. "Early identification of Alzheimer's disease using positron emission tomography imaging and machine learning." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23735.

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Dementia is a chronic neurodegenerative disease impacting millions of elderlies globally every single day. There are several well-known forms of dementia. Alzheimer’s Disease (AD) is the most prevalent and deadly with no known cure. However, there are effective interventions to delay onset of AD only if it is detected early. Fludeoxyglucose/Pittsburgh compound B Positron Emission Tomography (FDG/PiB PET) is one of the most effective medical imaging modalities used by doctors for early AD identification for prospective patients. The task of diagnosing AD by visually examining PET images, however, is usually time consuming and highly depends on the experience of the examiners. Another challenge related to this task is the potential loss of valuable information contained in past PET scans once they are archived post-diagnosis. There is a need for computer-aided early AD identification systems to assist doctors in clinical environment by providing useful second opinion. However, building such systems are extremely challenging due to three main reasons. Firstly, the poor resolution of brain scans acquired from PET scanner makes extracting salient spatial features from these scans a challenging task. Secondly, in PET images obtained from clinical environment are usually poorly labelled due to the fact that Alzheimer’s disease cannot be confirmed until a series of follow-up scans over a long period of time are examined or after post-mortem. This prevents supervised machine learning models from being trained properly. At last, longitudinal PET images are usually difficult to obtain due to subject drop-off during follow-up period. These data provide extremely valuable insights into the development of dementia. And understanding how dementia progresses for different subject will greatly benefit the development of personalised dementia care. In this thesis, we focus on solving these key issues by proposing several different machine learning-based methods. To select the salient feature variables from PET images, we propose a novel feature selection algorithm inspired by evolutionary computing. We also propose a method for simultaneous feature selection and Alzheimer’s disease classification, and we show the consistency between the selected features and clinically verified knowledge. To solve the PET image quality issue, we propose a novel kernel learning method under the Robust Programming framework. We then focus on the challenging data issues existing in clinical environment and propose two different but related semi-supervised learning methods. At last, we design and implement a pipeline for dementia progression direction prediction using longitudinal PET images. The pipeline contains a sequence recovery component to recover missing observations and a sequence recognition component for temporal pattern recognition. The significance of our study is that it shows doctors the usefulness of the second opinion for early AD detection in several different practical scenarios, provided by efficient and effective machine learning models built on PET imaging data.
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Egli, Sebastian [Verfasser], and Jörg [Akademischer Betreuer] Bendix. "Satellite-Based Fog Detection: A Dynamic Retrieval Method for Europe Based on Machine Learning / Sebastian Egli ; Betreuer: Jörg Bendix." Marburg : Philipps-Universität Marburg, 2019. http://d-nb.info/1187443476/34.

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Di, Donato Davide. "Sviluppo, Deployment e Validazione Sperimentale di Architetture Distribuite di Machine Learning su Piattaforma fog05." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19021/.

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Ultimamente sta crescendo sempre di più l'interesse riguardo al fog computing e alle possibilità che offre, tra cui la capacità di poter fruire di una capacità computazionale considerevole anche nei nodi più vicini all’utente finale: questo permetterebbe di migliorare diversi parametri di qualità di un servizio come la latenza nella sua fornitura e il costo richiesto per le comunicazioni. In questa tesi, sfruttando le considerazioni sopra, abbiamo creato e testato due architetture di machine learning distribuito e poi le abbiamo utilizzate per fornire un servizio di predizione (legato al condition monitoring) che migliorasse la soluzione cloud relativamente ai parametri citati prima. Poi, è stata utilizzata la piattaforma fog05, un tool che permette la gestione efficiente delle varie risorse presenti in una rete, per eseguire il deployment delle architetture sopra. Gli obiettivi erano due: validare le architetture in termini di accuratezza e velocità di convergenza e confermare la capacità di fog05 di gestire deployment complessi come quelli necessari nel nostro caso. Innanzitutto, sono state scelte le architetture: per una, ci siamo basati sul concetto di gossip learning, per l'altra, sul federated learning. Poi, queste architetture sono state implementate attraverso Keras e ne è stato testato il funzionamento: è emerso chiaramente come, in casi d'uso come quello in esame, gli approcci distribuiti riescano a fornire performance di poco inferiori a una soluzione centralizzata. Infine, è stato eseguito con successo il deployment delle architetture utilizzando fog05, incapsulando le funzionalità di quest'ultimo dentro un orchestratore creato ad-hoc al fine di gestire nella maniera più automatizzata e resiliente possibile la fornitura del servizio offerto dalle architetture sopra.
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Anjum, Ayesha. "Differentiation of alzheimer's disease dementia, mild cognitive impairment and normal condition using PET-FDG and AV-45 imaging : a machine-learning approach." Toulouse 3, 2013. http://thesesups.ups-tlse.fr/2238/.

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Nous avons utilisé l'imagerie TEP avec les traceurs F18-FDG et AV45 en conjonction avec les méthodes de classification du domaine du "Machine Learning". Les images ont été acquises en mode dynamique, une image toutes les 5 minutes. Les données ont été transformées par Analyse en Composantes Principales et Analyse en Composantes Indépendantes. Les images proviennent de trois sources différentes: la base de données ADNI (Alzheimer's Disease Neuroimaging Initiative) et deux protocoles réalisés au sein du centre TEP de l'hôpital Purpan. Pour évaluer la performance de la classification nous avons eu recours à la méthode de validation croisée LOOCV (Leave One Out Cross Validation). Nous donnons une comparaison entre les deux méthodes de classification les plus utilisées, SVM (Support Vector Machine) et les réseaux de neurones artificiels (ANN). La combinaison donnant le meilleur taux de classification semble être SVM et le traceur AV45. Cependant les confusions les plus importantes sont entre les patients MCI et les sujets normaux. Les patients Alzheimer se distinguent relativement mieux puisqu'ils sont retrouvés souvent à plus de 90%. Nous avons évalué la généralisation de telles méthodes de classification en réalisant l'apprentissage sur un ensemble de données et la classification sur un autre ensemble. Nous avons pu atteindre une spécificité de 100% et une sensibilité supérieure à 81%. La méthode SVM semble avoir une meilleure sensibilité que les réseaux de neurones. L'intérêt d'un tel travail est de pouvoir aider à terme au diagnostic de la maladie d'Alzheimer
We used PET imaging with tracers F18-FDG and AV45 in conjunction with the classification methods in the field of "Machine Learning". PET images were acquired in dynamic mode, an image every 5 minutes. The images used come from three different sources: the database ADNI (Alzheimer's Disease Neuro-Imaging Initiative, University of California Los Angeles) and two protocols performed in the PET center of the Purpan Hospital. The classification was applied after processing dynamic images by Principal Component Analysis and Independent Component Analysis. The data were separated into training set and test set. To evaluate the performance of the classification we used the method of cross-validation LOOCV (Leave One Out Cross Validation). We give a comparison between the two most widely used classification methods, SVM (Support Vector Machine) and artificial neural networks (ANN) for both tracers. The combination giving the best classification rate seems to be SVM and AV45 tracer. However the most important confusion is found between MCI patients and normal subjects. Alzheimer's patients differ somewhat better since they are often found in more than 90%. We evaluated the generalization of our methods by making learning from set of data and classification on another set. We reached the specifity score of 100% and sensitivity score of more than 81%. SVM method showed a bettrer sensitivity than Artificial Neural Network method. The value of such work is to help the clinicians in diagnosing Alzheimer's disease
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Dukart, Jürgen. "Contribution of FDG-PET and MRI to improve Understanding, Detection and Differentiation of Dementia." Doctoral thesis, Universitätsbibliothek Leipzig, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-66495.

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Progression and pattern of changes in different biomarkers of Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD) like [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and magnetic resonance imaging (MRI) have been carefully investigated over the past decades. However, there have been substantially less studies investigating the potential of combining these imaging modalities to make use of multimodal information to further improve understanding, detection and differentiation of various dementia syndromes. Further the role of preprocessing has been rarely addressed in previous research although different preprocessing algorithms have been shown to substantially affect diagnostic accuracy of dementia. In the present work common preprocessing procedures used to scale FDG-PET data were compared to each other. Further, FDG-PET and MRI information were jointly analyzed using univariate and multivariate techniques. The results suggest a highly differential effect of different scaling procedures of FDG-PET data onto detection and differentiation of various dementia syndromes. Additionally, it has been shown that combining multimodal information does further improve automatic detection and differentiation of AD and FTLD.
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Castellanos, Carlos. "Development of a validation shape sensing algorithm in Python with predictive and automatedanalysis." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-454942.

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Difficulties with wind turbines can arise during operation due to externalforces provoked by the wind. Calculating the deflection of the blades can beused to give break points for maintenance, design and/or monitoring purposes. Fiber Bragg Grating (FBG) sensors can be installed on the windblades to detect signals that can be reinterpreted as deflection in differentdirections. In this project a tool was developed that can take this information in real time to analyze critical issues which is important to save timeand operational and maintenance costs (O&M). To do so, a predictive model is used to anticipate the deflection in the blades caused by the impact ofthe wind in different orientations. The main purpose of this work is to showan algorithm that can transform optical signals from the FBG sensors into ashape calculator for the deflection for maintenance purposes. At the sametime, it is shown that this algorithm can be used as a forecast tool takinginto consideration the weather data.
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Books on the topic "FZG machine"

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Free cash flow: Seeing through the accounting fog machine to find great stocks. Hoboken, N.J: Wiley, 2009.

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Die Entwicklung der Firma Kugelfischer, Georg Schäfer & Co.: Unter besonderer Berücksichtigung der Kontinuität als Familienunternehmen und die regionalen Auswirkungen ihrer Entwicklung aus betriebs- und industriebezogener Sicht. Würzburg: Creator, 1988.

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Fandel, G. Modern Production Concepts: Theory and Applications Proceedings of an International Conference, Fernuniversität, Hagen, FRG, August 20-24, 1990. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991.

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Fog Machine. Lucky Sky Press, 2014.

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Fog Machine. Lucky Sky Press, 2014.

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The fog machine: A novel. 2014.

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Misra, Sudip, Subhadeep Sarkar, and Subarna Chatterjee. Sensors Cloud and Fog. Taylor & Francis Group, 2019.

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Christy, George C. Free Cash Flow: Seeing Through the Accounting Fog Machine to Find Great Stocks. Wiley & Sons, Limited, John, 2011.

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Ergonomic Data for Equipment Design: Proceedings of the NATO ARI held in Munich, FRG, March 22-26, 1982 (Nato Conference Series III, Vol 25: Human Factors). Springer, 1985.

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Misra, Sudip, Subhadeep Sarkar, and Subarna Chatterjee. Sensors, Cloud, and Fog: The Enabling Technologies for the Internet of Things. Taylor & Francis Group, 2019.

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Book chapters on the topic "FZG machine"

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Thomas, Priya, and Deepa V. Jose. "Edge/Fog Computing." In Machine Intelligence, 47–64. Boca Raton: Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003424550-3.

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Lohani, Kaustubh, Prajwal Bhardwaj, and Ravi Tomar. "Fog Computing and Machine Learning." In Fog Computing, 133–51. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003188230-10.

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Jaiswal, Kabir, and Niharika Singh. "Application of Machine Learning in Fog Computing." In Fog Computing, 41–50. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003188230-4.

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Gaba, Smriti, Susheela Dahiya, Samarth Vashisht, and Avita Katal. "The Use of Machine Learning in Fog Computing." In Fog Computing, 27–39. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003188230-3.

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Moh, Melody, and Robinson Raju. "Using Machine Learning for Protecting the Security and Privacy of Internet of Things (IoT) Systems." In Fog and Edge Computing, 223–57. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119525080.ch10.

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Yan, Xuan, Xiaolong Xu, Yu Zheng, and Fei Dai. "Fog Server Placement for Multimodality Data Fusion in Neuroimaging." In Machine Learning for Cyber Security, 234–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62223-7_20.

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Gutiérrez, Norma, Eva Rodríguez, Sergi Mus, Beatriz Otero, and Ramón Canal. "Privacy Preserving Deep Learning Framework in Fog Computing." In Machine Learning, Optimization, and Data Science, 504–15. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64583-0_45.

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Pinto, Manuel, Nicola Roveri, Gianluca Pepe, Andrea Nicoletti, Gabriele Balconi, and Antonio Carcaterra. "Extraction of the Beam Elastic Shape from Uncertain FBG Strain Measurement Points." In Mechanisms and Machine Science, 362–69. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03320-0_39.

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Martin, John Paul, Christina Terese Joseph, K. Chandrasekaran, and A. Kandasamy. "Machine Learning Powered Autoscaling for Blockchain-Based Fog Environments." In Blockchain and Applications, 281–91. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86162-9_28.

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Prasad, Devendra, Pradeep Singh Rawat, and Neeraj Rathore. "Optimized Cloud Storage Data Analysis Using the Machine Learning Model." In Bio-Inspired Optimization in Fog and Edge Computing Environments, 165–84. New York: Auerbach Publications, 2022. http://dx.doi.org/10.1201/9781003322931-10.

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Conference papers on the topic "FZG machine"

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Michalczewski, Remigiusz, Marian Szczerek, Waldemar Tuszynski, and Jan Wulczynski. "The Scuffing Resistance of the Coated Tribosystems Lubricated With Ecological Oils." In World Tribology Congress III. ASMEDC, 2005. http://dx.doi.org/10.1115/wtc2005-63432.

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The objective of the paper is to show that thin, hard coatings deposited on heavy-loaded machine components working in a non-conformal contact (e.g. gears) and lubricated with ecological oils, make it possible to increase the service-life of these components. The scuffing resistance was assessed by employing a high-resolution four-ball test method realized in a tester with continuously increasing load. Also another test method — FZG scuffing test — was realized using a back-to-back gear test rig. The test balls and gears were coated with thin, hard TiN and WC/C coatings deposited using arc-vacuum and reactive sputtering techniques respectively. The performed tests indicate that the presence of thin coatings on machine components gives a possibility of eliminating or reducing the content of toxic AW/EP additives in lubricating oils, as well as using ecological oils made of renewable resources, without any risk of a scuffing failure.
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Gai, Yuxian, Huiying Liu, and Shen Dong. "Vibration Control System for a Sub-Micro Ultra-Precision Turning Machine." In 2007 First International Conference on Integration and Commercialization of Micro and Nanosystems. ASMEDC, 2007. http://dx.doi.org/10.1115/mnc2007-21040.

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For a sub-micro ultra-precision turning machine using airsprings as vibration isolation elements, a 5 FOG mathematical model is established, activation f acted on the machine bed is as the input, the output are vertical displacement y1, oscillating φ1, ψ1 around the horizontal axle x and z of the machine bed, vertical displacement y2 of the main spindle box, and vertical displacement y3 of the slider. The equations for vibration system of 5 FOG are solved. The results indicate, when actuation force f ≠ 0, the outputs of all 5 FOG are increasing with the increasing of f. when activation f = 0, the outputs of all 5 FOG tend to zero. Assuming f include the vibration of machine base and an external force, when external force is equal to that of the vibration of machine base, then f = 0. The vibration of 5 FOG can be effectively isolated, so electromagnetic actuators as an external force, also as active vibration isolation elements can be used in the isolation system. Three electro-magnetic actuators arranging as triangle act as an external force, the quantity is equal to that of the base vibration, and the phase reverse. In fact ultra-precision turning machine is a complicated mechanism system and in the machining process, the headstock and horizontal-slider are in the movement, that is to say, the center of mass of the ultra-precision machine is changeable. Impossible is f = 0 for a practical control. In order to get a effective vibration isolation, fuzzy controller is used. The synthetic experiments have been done for the 5 FOG vibration system of the ultra-precision turning machine. The result of three actuations experiment that has been done in y direction indicates that the vibration of y direction, and oscillating φ1, ψ2 around the horizontal axle x and z of the machine bed are to be controlled. A work-piece of aluminum alloy has been machined using the sub-micro ultra-precision turning machine with the active vibration isolation elements, and without the active vibration isolation elements, AFM microscope graphs show the surface roughness of the work-piece machined by the former better as by the latter.
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Wu, Dazhong, Janis Terpenny, Li Zhang, Robert Gao, and Thomas Kurfess. "Fog-Enabled Architecture for Data-Driven Cyber-Manufacturing Systems." In ASME 2016 11th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/msec2016-8559.

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Over the past few decades, both small- and medium-sized manufacturers as well as large original equipment manufacturers (OEMs) have been faced with an increasing need for low cost and scalable intelligent manufacturing machines. Capabilities are needed for collecting and processing large volumes of real-time data generated from manufacturing machines and processes as well as for diagnosing the root cause of identified defects, predicting their progression, and forecasting maintenance actions proactively to minimize unexpected machine down times. Although cloud computing enables ubiquitous and instant remote access to scalable information and communication technology (ICT) infrastructures and high volume data storage, it has limitations in latency-sensitive applications such as high performance computing and real-time stream analytics. The emergence of fog computing, Internet of Things (IoT), and cyber-physical systems (CPS) represent radical changes in the way sensing systems, along with ICT infrastructures, collect and analyze large volumes of real-time data streams in geographically distributed environments. Ultimately, such technological approaches enable machines to function as an agent that is capable of intelligent behaviors such as automatic fault and failure detection, self-diagnosis, and preventative maintenance scheduling. The objective of this research is to introduce a fog-enabled architecture that consists of smart sensor networks, communication protocols, parallel machine learning software, and private and public clouds. The fog-enabled architecture will have the potential to enable large-scale, geographically distributed online machine and process monitoring, diagnosis, and prognosis that require low latency and high bandwidth in the context of data-driven cyber-manufacturing systems.
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Arandjelovic, Ognjen, and Roberto Cipolla. "Colour invariants for machine face recognition." In Gesture Recognition (FG). IEEE, 2008. http://dx.doi.org/10.1109/afgr.2008.4813306.

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Goncalves, Diogo, Karima Velasquez, Marilia Curado, Luiz Bittencourt, and Edmundo Madeira. "Proactive Virtual Machine Migration in Fog Environments." In 2018 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2018. http://dx.doi.org/10.1109/iscc.2018.8538655.

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Bittencourt, Luiz Fernando, Marcio Moraes Lopes, Ioan Petri, and Omer F. Rana. "Towards Virtual Machine Migration in Fog Computing." In 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC). IEEE, 2015. http://dx.doi.org/10.1109/3pgcic.2015.85.

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Li-Xia Xie, Hong-Yu Yang, and Yi Lu. "FUG based intelligent query for audit database." In 2008 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2008. http://dx.doi.org/10.1109/icmlc.2008.4620837.

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Hu, Ching-Piao, and C. F. Liao. "Optical holographic Hough processor for machine vision." In 15th Int'l Optics in Complex Sys. Garmisch, FRG, edited by F. Lanzl, H. J. Preuss, and G. Weigelt. SPIE, 1990. http://dx.doi.org/10.1117/12.34930.

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Foukalas, Fotis, and Athanasios Tziouvaras. "A Federated Machine Learning Protocol for Fog Networks." In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2021. http://dx.doi.org/10.1109/infocomwkshps51825.2021.9484485.

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Ingistov, Steve. "Fog System Performance in Power Augmentation of Heavy Duty Power Generating Gas Turbines Model 7EA." In ASME Turbo Expo 2000: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/2000-gt-0305.

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Ambient air temperature plays significant role in performance of a Gas Turbine. Frequently Gas Turbines in electrical power generation are single rotor and are directly coupled to the Electrical Generators. These machines normally operate 8,000 hours per calendar year under the 100% load. The control of the combustion air flow is achieved by modulating compressor Inlet Guide Vanes (IGV). The single shaft axial compressor consumes as a rule of thumb more than 50% of turbine useful expansion work. Axial compressor is high-volume, moderate discharge pressure machine. Its power demand to discharge ambient air to the turbine combustion system is very dependent on ambient conditions such as pressure, temperature and relative humidity. The optimization of the axial compressor aerodynamic loading under various ambient conditions is therefore mandatory. During the hot and humid summer days, especially from the noon time to 6:00 PM, the demand for the power is at its maximum. This Paper describes selection, design and installation of the Inlet Air Cooling System. (IACS). The selected IACS is fine water mist, FOG. FOG System (FS) was selected because of its efficiency and because the clean water was available. FS incorporates Fog Generating Skid (FGS) and Fog Curtain (FC). FC is comprised of lateral lines with equally spaced. FOG Nozzles (FN). The FN is specially designed to generate individual “Fog Cones” that efficiently dissipate the water particles in the space. Fine water particles are atomized by incoming air in the Inlet Air (IA) duct. The homogenous mixture of FOG and IA is required to enhance the water mist particles evaporation process. In cases when the FS works in tandem with Evaporative Cooler (EC) most of the FOG particles are “injected” into the compressor suction. The injected FOG particles start to evaporate during the IA compression process. The water evaporation process simultaneously causes cooling of the IA being compressed. The result is reduced compression work and improved performance of GT.
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Reports on the topic "FZG machine"

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Michaelis, K., and H. Winter. Development of a High Temperature FZG-Ryder Gear Lubricant Load Capacity Machine. Fort Belvoir, VA: Defense Technical Information Center, May 1989. http://dx.doi.org/10.21236/ada210799.

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Alber, Charlotte, Laura Dusl, Brigitte Ecker, and Sabine Pohoryles-Drexel. Erfahrungen und Ergebnisse aus der begleitenden Erhebung zum Pilot w-fFORTE Innovatorinnen. BMDW, July 2021. http://dx.doi.org/10.22163/fteval.2021.523.

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Mit w-fFORTE Innovatorinnen strebt das Bundesministerium für Digitalisierung und Wirtschaftsstandort (BMDW) an, Frauen in standortrelevanter Forschung und Innovation (F&I) gezielt zu unterstützen und sichtbar zu machen. Hochqualifizierte Frauen werden darin bestärkt, ihre Ideen zu entfalten, neue Netzwerk-Kontakte aufzubauen und zu mehr Gestaltungsspielräumen und beruflicher Weiterentwicklung zu gelangen. Die FFG hat dafür im Zeitraum 2018-2019 in enger Zusammenarbeit mit dem BMDW ein innovatives Leadership- & Empowerment-Programm entwickelt. Der erste Durchgang fand als Pilot von Juni 2020 bis April 2021 mit insgesamt 21 Innovatorinnen statt, die von einer Jury aus einer Vielzahl von Bewerberinnen ausgewählt wurden. Während der Pilot-Laufzeit wurde eine begleitende Erhebung durch WPZ Research durchgeführt. Ziel war es, die Wirksamkeit des Pilots zu prüfen und Evidenzen für eine mögliche Weiterführung der Aktivitäten zu erhalten.
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Warta, Katharina, Tobias Dudenbostel, María del Carmen Calatrava Moreno, Francesca Guadagno, Simon Zingerle, Sandra Skok, and Harald Grill. Evaluierung des COMET-Programms. Technopolis Group - Austria, June 2021. http://dx.doi.org/10.22163/fteval.2022.524.

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Technopolis wurde im Mai 2020 vom Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie (BMK) und dem Bundesministerium für Digitalisierung und Wirtschaftsstandort (BMDW) mit der Evaluierung des COMET-Programms beauftragt. Die vorliegende Evaluierung bezieht sich auf die 25 aktuell existierenden Zentren. Der Fokus der Evaluierung liegt auf der Charakterisierung der COMET-Zentren und auf dem Monitoring- und Kennzahlensystem von COMET. Im Jahr der Corona-Pandemie wurden die Methoden angepasst, Interviews mit Stakeholdern und den Zentren wurden meist per Videocalls oder telefonisch geführt, geplante on-site Visits sowie internationale Workshops konnten nicht durchgeführt werden. Zentrale Quellen der Evaluierung sind eine Befragung der Zentren und der Unternehmens- und Wissenschaftspartner sowie die Datenbasis der FFG, die wir durch diverse Harmonisierungsschritte für neuwertige Auswertungen nutzbar machten. Dies umfasst insbesondere einen historischen Rückblick sowie eine Cluster- und Netzwerkanalyse. Die Auswartungen sind in zwei Dashboards angelegt, das Dashboard zur COMET-Befragung ist anonymisiert und daher öffentlich zugänglich.
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Kirchhoff, Helmut, and Ziv Reich. Protection of the photosynthetic apparatus during desiccation in resurrection plants. United States Department of Agriculture, February 2014. http://dx.doi.org/10.32747/2014.7699861.bard.

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In this project, we studied the photosynthetic apparatus during dehydration and rehydration of the homoiochlorophyllous resurrection plant Craterostigmapumilum (retains most of the photosynthetic components during desiccation). Resurrection plants have the remarkable capability to withstand desiccation, being able to revive after prolonged severe water deficit in a few days upon rehydration. Homoiochlorophyllous resurrection plants are very efficient in protecting the photosynthetic machinery against damage by reactive oxygen production under drought. The main purpose of this BARD project was to unravel these largely unknown protection strategies for C. pumilum. In detail, the specific objectives were: (1) To determine the distribution and local organization of photosynthetic protein complexes and formation of inverted hexagonal phases within the thylakoid membranes at different dehydration/rehydration states. (2) To determine the 3D structure and characterize the geometry, topology, and mechanics of the thylakoid network at the different states. (3) Generation of molecular models for thylakoids at the different states and study the implications for diffusion within the thylakoid lumen. (4) Characterization of inter-system electron transport, quantum efficiencies, photosystem antenna sizes and distribution, NPQ, and photoinhibition at different hydration states. (5) Measuring the partition of photosynthetic reducing equivalents between the Calvin cycle, photorespiration, and the water-water cycle. At the beginning of the project, we decided to use C. pumilum instead of C. wilmsii because the former species was available from our collaborator Dr. Farrant. In addition to the original two dehydration states (40 relative water content=RWC and 5% RWC), we characterized a third state (15-20%) because some interesting changes occurs at this RWC. Furthermore, it was not possible to detect D1 protein levels by Western blot analysis because antibodies against other higher plants failed to detect D1 in C. pumilum. We developed growth conditions that allow reproducible generation of different dehydration and rehydration states for C. pumilum. Furthermore, advanced spectroscopy and microscopy for C. pumilum were established to obtain a detailed picture of structural and functional changes of the photosynthetic apparatus in different hydrated states. Main findings of our study are: 1. Anthocyan accumulation during desiccation alleviates the light pressure within the leaves (Fig. 1). 2. During desiccation, stomatal closure leads to drastic reductions in CO2 fixation and photorespiration. We could not identify alternative electron sinks as a solution to reduce ROS production. 3. On the supramolecular level, semicrystalline protein arrays were identified in thylakoid membranes in the desiccated state (see Fig. 3). On the electron transport level, a specific series of shut downs occur (summarized in Fig. 2). The main events include: Early shutdown of the ATPase activity, cessation of electron transport between cyt. bf complex and PSI (can reduce ROS formation at PSI); at higher dehydration levels uncoupling of LHCII from PSII and cessation of electron flow from PSII accompanied by crystal formation. The later could severe as a swift PSII reservoir during rehydration. The specific order of events in the course of dehydration and rehydration discovered in this project is indicative for regulated structural transitions specifically realized in resurrection plants. This detailed knowledge can serve as an interesting starting point for rationale genetic engineering of drought-tolerant crops.
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