Measurement of Local Plastic Deformation in Aluminum Alloy by Means of X-ray 3D Imaging Technique

AbstractTo understand the local deformation behavior is very important for improvement of deformability in aluminum alloys which possess poor deformation limit in comparison with steels. However, measurement of local deformation in the interior of metal is not sufficiently carried out. In this study, the development of local plastic strain is measured by means of X-ray 3D imaging technique, i.e. high-resolution synchrotron X-ray microtomography. The marker tracking method, which is based on 3D image processing in volumetric image, is developed for obtaining local strains in 3D. Deformation behaviour is particularly different in individual grains. It was found that grains with different orientations deform maintaining harmony by shear deformation

Assessment of hydrogen embrittlement behavior in Al-Zn-Mg alloys by multi- modal 3D image-based simulation

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Why Guided Dialog Policy Learning performs well? Understanding the role of adversarial learning and its alternative

Dialog policies, which determine a system's action based on the current state at each dialog turn, are crucial to the success of the dialog. In recent years, reinforcement learning (RL) has emerged as a promising option for dialog policy learning (DPL). In RL-based DPL, dialog policies are updated according to rewards. The manual construction of fine-grained rewards, such as state-action-based ones, to effectively guide the dialog policy is challenging in multi-domain task-oriented dialog scenarios with numerous state-action pair combinations. One way to estimate rewards from collected data is to train the reward estimator and dialog policy simultaneously using adversarial learning (AL). Although this method has demonstrated superior performance experimentally, it is fraught with the inherent problems of AL, such as mode collapse. This paper first identifies the role of AL in DPL through detailed analyses of the objective functions of dialog policy and reward estimator. Next, based on these analyses, we propose a method that eliminates AL from reward estimation and DPL while retaining its advantages. We evaluate our method using MultiWOZ, a multi-domain task-oriented dialog corpus

CLASSIFICATION OF BIPOLAR DISORDER, MAJOR DEPRESSIVE DISORDER, AND HEALTHY STATE USING VOICE

Objective: In this study, we propose a voice index to identify healthy individuals, patients with bipolar disorder, and patients with major depressive disorder using polytomous logistic regression analysis.Methods: Voice features were extracted from voices of healthy individuals and patients with mental disease. Polytomous logistic regression analysis was performed for some voice features.Results: With the prediction model obtained using the analysis, we identified subject groups and were able to classify subjects into three groups with 90.79% accuracy.Conclusion: These results show that the proposed index may be used as a new evaluation index to identify depression

Myelin Basic Protein as a Novel Genetic Risk Factor in Rheumatoid Arthritis—A Genome-Wide Study Combined with Immunological Analyses

Rheumatoid arthritis (RA) is a major cause of adult chronic inflammatory arthritis and a typical complex trait. Although several genetic determinants have been identified, they account for only a part of the genetic susceptibility. We conducted a genome-wide association study of RA in Japanese using 225,079 SNPs genotyped in 990 cases and 1,236 controls from two independent collections (658 cases and 934 controls in collection1; 332 cases and 302 controls in collection2), followed by replication studies in two additional collections (874 cases and 855 controls in collection3; 1,264 cases and 948 controls in collection4). SNPs showing p<0.005 in the first two collections and p<10−4 by meta-analysis were further genotyped in the latter two collections. A novel risk variant, rs2000811, in intron2 of the myelin basic protein (MBP) at chromosome 18q23 showed strong association with RA (p = 2.7×10−8, OR 1.23, 95% CI: 1.14–1.32). The transcription of MBP was significantly elevated with the risk allele compared to the alternative allele (p<0.001). We also established by immunohistochemistry that MBP was expressed in the synovial lining layer of RA patients, the main target of inflammation in the disease. Circulating autoantibody against MBP derived from human brain was quantified by ELISA between patients with RA, other connective tissue diseases and healthy controls. As a result, the titer of anti-MBP antibody was markedly higher in plasma of RA patients compared to healthy controls (p<0.001) and patients with other connective tissue disorders (p<0.001). ELISA experiment using citrullinated recombinant MBP revealed that a large fraction of anti-MBP antibody in RA patients recognized citrullinated MBP. This is the first report of a genetic study in RA implicating MBP as a potential autoantigen and its involvement in pathogenesis of the disease

Biallelic variants in LIG3 cause a novel mitochondrial neurogastrointestinal encephalomyopathy

none67si: Abnormal gut motility is a feature of several mitochondrial encephalomyopathies, and mutations in genes such as TYMP and POLG, have been linked to these rare diseases. The human genome encodes three DNA ligases, of which only one, ligase III (LIG3), has a mitochondrial splice variant and is crucial for mitochondrial health. We investigated the effect of reduced LIG3 activity and resulting mitochondrial dysfunction in seven patients from three independent families, who showed the common occurrence of gut dysmotility and neurological manifestations reminiscent of mitochondrial neurogastrointestinal encephalomyopathy. DNA from these patients was subjected to whole exome sequencing. In all patients, compound heterozygous variants in a new disease gene, LIG3, were identified. All variants were predicted to have a damaging effect on the protein. The LIG3 gene encodes the only mitochondrial DNA (mtDNA) ligase and therefore plays a pivotal role in mtDNA repair and replication. In vitro assays in patient-derived cells showed a decrease in LIG3 protein levels and ligase activity. We demonstrated that the LIG3 gene defects affect mtDNA maintenance, leading to mtDNA depletion without the accumulation of multiple deletions as observed in other mitochondrial disorders. This mitochondrial dysfunction is likely to cause the phenotypes observed in these patients. The most prominent and consistent clinical signs were severe gut dysmotility and neurological abnormalities, including leukoencephalopathy, epilepsy, migraine, stroke-like episodes, and neurogenic bladder. A decrease in the number of myenteric neurons, and increased fibrosis and elastin levels were the most prominent changes in the gut. Cytochrome c oxidase (COX) deficient fibres in skeletal muscle were also observed. Disruption of lig3 in zebrafish reproduced the brain alterations and impaired gut transit in vivo. In conclusion, we identified variants in the LIG3 gene that result in a mitochondrial disease characterized by predominant gut dysmotility, encephalopathy, and neuromuscular abnormalities.This work was supported by Telethon Grant GGP15171 to E.B. and R.D.G. and by a donation from Kobe city to the Department of General Pediatrics, Kobe University Graduate School of Medicine (K550003302). S.C. was supported by a Dutch Cancer Foundation grant (KWF11011). V.C. and A.M. were supported by the Italian Ministry of Health (“Ricerca Corrente” funding). R.D.G. is the recipient of grants from University of Ferrara (FAR and FIR funds).openBonora, Elena; Chakrabarty, Sanjiban; Kellaris, Georgios; Tsutsumi, Makiko; Bianco, Francesca; Bergamini, Christian; Ullah, Farid; Isidori, Federica; Liparulo, Irene; Diquigiovanni, Chiara; Masin, Luca; Rizzardi, Nicola; Cratere, Mariapia Giuditta; Boschetti, Elisa; Papa, Valentina; Maresca, Alessandra; Cenacchi, Giovanna; Casadio, Rita; Martelli, Pierluigi; Matera, Ivana; Ceccherini, Isabella; Fato, Romana; Raiola, Giuseppe; Arrigo, Serena; Signa, Sara; Sementa, Angela Rita; Severino, Mariasavina; Striano, Pasquale; Fiorillo, Chiara; Goto, Tsuyoshi; Uchino, Shumpei; Oyazato, Yoshinobu; Nakamura, Hisayoshi; Mishra, Sushil K; Yeh, Yu-Sheng; Kato, Takema; Nozu, Kandai; Tanboon, Jantima; Morioka, Ichiro; Nishino, Ichizo; Toda, Tatsushi; Goto, Yu-Ichi; Ohtake, Akira; Kosaki, Kenjiro; Yamaguchi, Yoshiki; Nonaka, Ikuya; Iijima, Kazumoto; Mimaki, Masakazu; Kurahashi, Hiroki; Raams, Anja; MacInnes, Alyson; Alders, Mariel; Engelen, Marc; Linthorst, Gabor; de Koning, Tom; den Dunnen, Wilfred; Dijkstra, Gerard; van Spaendonck, Karin; van Gent, Dik C; Aronica, Eleonora M; Picco, Paolo; Carelli, Valerio; Seri, Marco; Katsanis, Nicholas; Duijkers, Floor A M; Taniguchi-Ikeda, Mariko; De Giorgio, RobertoBonora, Elena; Chakrabarty, Sanjiban; Kellaris, Georgios; Tsutsumi, Makiko; Bianco, Francesca; Bergamini, Christian; Ullah, Farid; Isidori, Federica; Liparulo, Irene; Diquigiovanni, Chiara; Masin, Luca; Rizzardi, Nicola; Cratere, Mariapia Giuditta; Boschetti, Elisa; Papa, Valentina; Maresca, Alessandra; Cenacchi, Giovanna; Casadio, Rita; Martelli, Pierluigi; Matera, Ivana; Ceccherini, Isabella; Fato, Romana; Raiola, Giuseppe; Arrigo, Serena; Signa, Sara; Sementa, Angela Rita; Severino, Mariasavina; Striano, Pasquale; Fiorillo, Chiara; Goto, Tsuyoshi; Uchino, Shumpei; Oyazato, Yoshinobu; Nakamura, Hisayoshi; Mishra, Sushil K; Yeh, Yu-Sheng; Kato, Takema; Nozu, Kandai; Tanboon, Jantima; Morioka, Ichiro; Nishino, Ichizo; Toda, Tatsushi; Goto, Yu-Ichi; Ohtake, Akira; Kosaki, Kenjiro; Yamaguchi, Yoshiki; Nonaka, Ikuya; Iijima, Kazumoto; Mimaki, Masakazu; Kurahashi, Hiroki; Raams, Anja; MacInnes, Alyson; Alders, Mariel; Engelen, Marc; Linthorst, Gabor; de Koning, Tom; den Dunnen, Wilfred; Dijkstra, Gerard; van Spaendonck, Karin; van Gent, Dik C; Aronica, Eleonora M; Picco, Paolo; Carelli, Valerio; Seri, Marco; Katsanis, Nicholas; Duijkers, Floor A M; Taniguchi-Ikeda, Mariko; De Giorgio, Robert

An Affordable Image-Analysis Platform to Accelerate Stomatal Phenotyping During Microscopic Observation

Recent technical advances in the computer-vision domain have facilitated the development of various methods for achieving image-based quantification of stomata-related traits. However, the installation cost of such a system and the difficulties of operating it on-site have been hurdles for experimental biologists. Here, we present a platform that allows real-time stomata detection during microscopic observation. The proposed system consists of a deep neural network model-based stomata detector and an upright microscope connected to a USB camera and a graphics processing unit (GPU)-supported single-board computer. All the hardware components are commercially available at common electronic commerce stores at a reasonable price. Moreover, the machine-learning model is prepared based on freely available cloud services. This approach allows users to set up a phenotyping platform at low cost. As a proof of concept, we trained our model to detect dumbbell-shaped stomata from wheat leaf imprints. Using this platform, we collected a comprehensive range of stomatal phenotypes from wheat leaves. We confirmed notable differences in stomatal density (SD) between adaxial and abaxial surfaces and in stomatal size (SS) between wheat-related species of different ploidy. Utilizing such a platform is expected to accelerate research that involves all aspects of stomata phenotyping