Modélisation du polissage laser de pièces obtenues suivant les procédés primaires d’usinage et de fabrication directe.

In order to reach the functional quality imposed by specifications, a mechanical part needs several operations. Thereby, the manufacturing chain is composed by different processes. The primary processes enable to create surfaces, and for aesthetic or tribological functions these surfaces need a finishing operation. Conventional polishing processes hold some drawbacks in terms of quality, productivity, environment and health. In order to overcome these limitations, the laser polishing process is investigated.These thesis works take place into a global manufacturing chain context, with the investigation of laser polishing according to two primary processes: machining and direct metal deposition process.In order to master the laser polishing process, these works enable to propose a protocol and a methodology for the determination of laser polishing parameters, efficient into the feasibility and optimal domains. Based on behavior models obtained through experimentations, these tools take into consideration several qualitative objective functions. Moreover, regarding advantages of additive manufacturing process, these research works investigate laser polishing of complex and thin parts.The optimal parameters enable to obtain 99% of surface roughness reduction. Lastly, the methodology of investigation highlights the impact of part topology when choosing the laser polishing parameters.En vue d’atteindre la qualité fonctionnelle dictée par le cahier des charges, une pièce mécanique nécessite la réalisation de plusieurs opérations. Ainsi, la chaine manufacturière est composée de différents procédés de fabrication. Les procédés primaires permettent l’obtention de surfaces, qui pour des fonctions esthétiques ou tribologiques nécessitent la réalisation d’opérations de parachèvement. Les procédés de polissage conventionnels disposent d’inconvénients qualitatifs, productifs, environnementaux ou sanitaires, et en vue de pallier ces différentes problématiques tout en améliorant la qualité des surfaces, le procédé de polissage laser est investigué.Ces travaux de thèse s’intègrent dans un contexte global de fabrication par l’investigation du procédé de polissage laser en fonction de deux procédés primaires : l’usinage et la fabrication directe.Dans une optique de maitrise, et à partir d’investigations expérimentales et de modèles comportementaux, ces travaux permettent de proposer un protocole ainsi qu’une méthodologie de détermination des paramètres opératoires. Efficaces au sein des domaines de faisabilité et optimal, les outils proposés prennent en considération différentes fonctions objectif qualitatives. Aussi, compte tenu des avantages de la fabrication directe, ces travaux de thèse investiguent le polissage laser de pièces de formes complexes et de sections minces.Les paramètres optimaux déterminés permettent d’obtenir une réduction de rugosité surfacique de 99%. Enfin, la méthodologie d’investigation souligne l’importance de la topologie de la pièce lors du choix des paramètres opératoires

SAF-IS: a Spatial Annotation Free Framework for Instance Segmentation of Surgical Tools

Instance segmentation of surgical instruments is a long-standing research problem, crucial for the development of many applications for computer-assisted surgery. This problem is commonly tackled via fully-supervised training of deep learning models, requiring expensive pixel-level annotations to train. In this work, we develop a framework for instance segmentation not relying on spatial annotations for training. Instead, our solution only requires binary tool masks, obtainable using recent unsupervised approaches, and binary tool presence labels, freely obtainable in robot-assisted surgery. Based on the binary mask information, our solution learns to extract individual tool instances from single frames, and to encode each instance into a compact vector representation, capturing its semantic features. Such representations guide the automatic selection of a tiny number of instances (8 only in our experiments), displayed to a human operator for tool-type labelling. The gathered information is finally used to match each training instance with a binary tool presence label, providing an effective supervision signal to train a tool instance classifier. We validate our framework on the EndoVis 2017 and 2018 segmentation datasets. We provide results using binary masks obtained either by manual annotation or as predictions of an unsupervised binary segmentation model. The latter solution yields an instance segmentation approach completely free from spatial annotations, outperforming several state-of-the-art fully-supervised segmentation approaches

Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy

Purpose: Ureteroscopy is an efficient endoscopic minimally invasive technique for the diagnosis and treatment of upper tract urothelial carcinoma (UTUC). During ureteroscopy, the automatic segmentation of the hollow lumen is of primary importance, since it indicates the path that the endoscope should follow. In order to obtain an accurate segmentation of the hollow lumen, this paper presents an automatic method based on Convolutional Neural Networks (CNNs). Methods: The proposed method is based on an ensemble of 4 parallel CNNs to simultaneously process single and multi-frame information. Of these, two architectures are taken as core-models, namely U-Net based in residual blocks($m_1$) and Mask-RCNN($m_2$), which are fed with single still-frames $I(t)$. The other two models ($M_1$, $M_2$) are modifications of the former ones consisting on the addition of a stage which makes use of 3D Convolutions to process temporal information. $M_1$, $M_2$ are fed with triplets of frames ($I(t-1)$, $I(t)$, $I(t+1)$) to produce the segmentation for $I(t)$. Results: The proposed method was evaluated using a custom dataset of 11 videos (2,673 frames) which were collected and manually annotated from 6 patients. We obtain a Dice similarity coefficient of 0.80, outperforming previous state-of-the-art methods. Conclusion: The obtained results show that spatial-temporal information can be effectively exploited by the ensemble model to improve hollow lumen segmentation in ureteroscopic images. The method is effective also in presence of poor visibility, occasional bleeding, or specular reflections

Incidence of Energy Consumption, Mining Sector and Economic Growth on CO2 Emission Levels: Evidence from Peru

Environmental pollution and its harmful effects have become a growing topic of study in recent years because the exploitation of resources, rationalized by the prevailing desire for economic growth, is going to directly affect the sustainability of our existing ecosystem in the coming decades. This is considering that there are productive sectors that have a larger environmental footprint, such as the mining industry. This study focuses on establishing the relationship between the variables of energy consumption, GDP per capita, and mineral rents and their impact on the level of pollution by CO2 emissions in the period 1971–2019, using the Environmental Kuznets Curve (EKC) theory. To this end, we used statistical and econometric tools based on the ARDL dynamic model through a time series analysis starting from historical data. We concluded that the variables CEpc, PBIpc, and RM have deleterious effects as a 1% increase in these variables increases the level of environmental pollution by CO2 emissions by 0.724%, 0.136%, and 0.061%, respectively

Distortion and instability compensation with deep learning for rotational scanning endoscopic optical coherence tomography

Optical Coherence Tomography (OCT) is increasingly used in endoluminal procedures since it provides high-speed and high resolution imaging. Distortion and instability of images obtained with a proximal scanning endoscopic OCT system are significant due to the motor rotation irregularity, the friction between the rotating probe and outer sheath and synchronization issues. On-line compensation of artefacts is essential to ensure image quality suitable for real-time assistance during diagnosis or minimally invasive treatment. In this paper, we propose a new online correction method to tackle both B-scan distortion, video stream shaking and drift problem of endoscopic OCT linked to A-line level image shifting. The proposed computational approach for OCT scanning video correction integrates a Convolutional Neural Network (CNN) to improve the estimation of azimuthal shifting of each A-line. To suppress the accumulative error of integral estimation we also introduce another CNN branch to estimate a dynamic overall orientation angle. We train the network with semi-synthetic OCT videos by intentionally adding rotational distortion into real OCT scanning images. The results show that networks trained on this semi-synthetic data generalize to stabilize real OCT videos, and the algorithm efficacy is demonstrated on both ex vivo and in vivo data, where strong scanning artifacts are successfully corrected. (c) 2022 The Authors. Published by Elsevier B.V

Unbiased Proteomic Approach Identifies Unique and Coincidental Plasma Biomarkers in Repetitive mTBI and AD Pathogenesis

The relationship between repetitive mild traumatic brain injury (r-mTBI) and Alzheimer’s disease (AD) is well-recognized. However, the precise nature of how r-mTBI leads to or precipitates AD pathogenesis is currently not understood. Plasma biomarkers potentially provide non-invasive tools for detecting neurological changes in the brain, and can reveal overlaps between long-term consequences of r-mTBI and AD. In this study we address this by generating time-dependent molecular profiles of response to r-mTBI and AD pathogenesis in mouse models using unbiased proteomic analyses. To model AD, we used the well-validated hTau and PSAPP(APP/PS1) mouse models that develop age-related tau and amyloid pathological features, respectively, and our well-established model of r-mTBI in C57BL/6 mice. Plasma were collected at different ages (3, 9, and 15 months-old for hTau and PSAPP mice), encompassing pre-, peri- and post-“onset” of the cognitive and neuropathological phenotypes, or at different timepoints after r-mTBI (24 h, 3, 6, 9, and 12 months post-injury). Liquid chromatography/mass spectrometry (LC-MS) approaches coupled with Tandem Mass Tag labeling technology were applied to develop molecular profiles of protein species that were significantly differentially expressed as a consequence of mTBI or AD. Mixed model ANOVA after Benjamini–Hochberg correction, and a stringent cut-off identified 31 proteins significantly changing in r-mTBI groups over time and, when compared with changes over time in sham mice, 13 of these were unique to the injured mice. The canonical pathways predicted to be modulated by these changes were LXR/RXR activation, production of nitric oxide and reactive oxygen species and complement systems. We identified 18 proteins significantly changing in PSAPP mice and 19 proteins in hTau mice compared to their wild-type littermates with aging. Six proteins were found to be significantly regulated in all three models, i.e., r-mTBI, hTau, and PSAPP mice compared to their controls. The top canonical pathways coincidently changing in all three models were LXR/RXR activation, and production of nitric oxide and reactive oxygen species. This work suggests potential biomarkers for TBI and AD pathogenesis and for the overlap between these two, and warrant targeted investigation in human populations. Data are available via ProteomeXchange with identifier PXD010664

Nasalization by Nasalis larvatus: larger noses audiovisually advertise conspecifics in proboscis monkeys

Male proboscis monkeys have uniquely enlarged noses that are prominent adornments, which may have evolved through their sexually competitive harem group social system. Nevertheless, the ecological roles of the signals encoded by enlarged noses remain unclear. We found significant correlations among nose, body, and testis sizes and a clear link between nose size and number of harem females. Therefore, there is evidence supporting both male-male competition and female choice as causal factors in the evolution of enlarged male noses. We also observed that nasal enlargement systematically modifies the resonance properties of male vocalizations, which probably encode male quality. Our results indicate that the audiovisual contributions of enlarged male noses serve as advertisements to females in their mate selection. This is the first primate research to evaluate the evolutionary processes involved in linking morphology, acoustics, and socioecology with unique masculine characteristics

Serological evidence of exposure of Bornean wild carnivores to feline-related viruses at the domestic animal-wildlife interface

We conducted an exploratory serological survey to evaluate the exposure of Bornean wild carnivores to several viruses common to domestic felids, at interface areas between protected forest and industrial agriculture in the Kinabatangan floodplain (Sabah, Malaysia). Blood samples, collected from wild carnivores (n = 21) and domestic cats (n = 27), were tested for antibodies against feline coronavirus (FCoV), feline panleukopenia virus (FPLV), feline herpesvirus (FHV) and feline calicivirus (FCV), using commercial enzyme-linked immunosorbent assay (ELISA) test kits. Anti-FCoV antibodies were detected in most species, including one flat-headed cat (Prionailurus planiceps, [1/2]), leopard cats (Prionailurus bengalensis, [2/5]), Malay civets (Viverra tangalunga, [2/11]) and domestic cats (Felis catus, [2/27]). Anti-FCV antibodies were present in all domestic cats and one flat-headed cat, while anti-FPLV antibodies were identified in Sunda clouded leopards (Neofelis diardi, [2/2]), domestic cats [12/27] and Malay civets [2/11]. Anti-FHV antibodies were only detected in domestic cats [2/27]. Our findings indicate pathogen transmission risk between domestic and wild carnivore populations at the domestic animal–wildlife interface, emphasizing the concern for wildlife conservation for several endangered wild carnivores living in the area. Special consideration should be given to species that benefit from their association with humans and have the potential to carry pathogens between forest and plantations (e.g., Malay civets and leopard cats). Risk reduction strategies should be incorporated and supported as part of conservation actions in human-dominated landscapes

New neutron detector based on Micromegas technology for ADS projects

A new neutron detector based on Micromegas technology has been developed for the measurement of the simulated neutron spectrum in the ADS project. After the presentation of simulated neutron spectra obtained in the interaction of 140 MeV protons with the spallation target inside the TRIGA core, a full description of the new detector configuration is given. The advantage of this detector compared to conventional neutron flux detectors and the results obtained with the first prototype at the CELINA 14 MeV neutron source facility at CEA-Cadarache are presented. The future developments of operational Piccolo-Micromegas for fast neutron reactors are also described