Active learning for feasible region discovery

Often in the design process of an engineer, the design specifications of the system are not completely known initially. However, usually there are some physical constraints which are already known, corresponding to a region of interest in the design space that is called feasible. These constraints often have no analytical form but need to be characterised based on expensive simulations or measurements. Therefore, it is important that the feasible region can be modeled sufficiently accurate using only a limited amount of samples. This can be solved by using active learning techniques that minimize the amount of samples w.r.t. what we try to model. Most active learning strategies focus on classification models or regression models with classification accuracy and regression accuracy in mind respectively. In this work, regression models of the constraints are used, but only the (in) feasibility is of interest. To tackle this problem, an information-theoretic sampling strategy is constructed to discover these regions. The proposed method is then tested on two synthetic examples and one engineering example and proves to outperform the current state-of-the-art

Stiffness and damping identification for asymmetric building frame with in-plane flexible floors

In most building structures, floors with sufficient in-plane stiffness exist and an assumption of rigid in-plane stiffness is valid. However, in some building structures, an assumption of rigid in-plane stiffness does not hold. A method of system identification (SI) for physical parameters (stiffness, damping) is proposed for three-dimensional (3D) building structures with in-plane flexible floors. The stiffness and damping parameters of each vertical structural frame in the 3D building structure are identified from the measured floor horizontal accelerations together with the stiffness and damping parameters of each floor. It is shown that a batch processing least-squares estimation method for many discrete time-domain measured data enables the direct identification of both the stiffness and damping parameters of each vertical structural frame and the stiffness and damping parameters of each floor. The proposed method possesses an advantage that all stiffness and damping parameters of vertical frames and horizontal frames (floors) can be identified simultaneously without search iteration. The accuracy and reliability of the proposed method are made clear by numerical simulations for measured data without noise and measured data with noise. A method of noise elimination is proposed to enhance the identification accuracy. Finally, experiments using a shaking table are conducted for the accuracy investigation of the proposed identification method. It is confirmed that the proposed identification method possesses a reliable ability to identify the stiffness and damping parameters for 3D building structures with in-plane flexible floors

An Empirical Study on the New Keynesian Wage Phillips Curve: Japan and the US

We present an empirical analysis on the New Keynesian Wage Phillips Curve (NKWPC), which is derived by Gali (2011) as a micro-founded structural relationship between wage inflation and the unemployment rate under a sticky wage framework using data for Japan and the US. We find that the empirical fit of the NKWPC is generally superior for Japan. We also find that the slope of the NKWPC is much steeper in Japan than in the US. These results suggest that wages are less sticky in Japan than in the US. Inflation indexation plays a key role in the US, but is less important in Japan. Rolling estimations indicate that the NKWPC has flattened over time in Japan. Analysis of recent data indicates that in both countries the role of inflation indexation is quantitatively smaller than before, although this result might be influenced by low and stable inflation rates over the past few decades

An Empirical Study on the New Keynesian Wage Phillips Curve: Japan and the US

We present an empirical analysis on the New Keynesian Wage Phillips Curve (NKWPC), which is derived by Gali (2011) as a micro-founded structural relationship between wage inflation and the unemployment rate under a sticky wage framework using data for Japan and the US. We find that the empirical fit of the NKWPC is generally superior for Japan. We also find that the slope of the NKWPC is much steeper in Japan than in the US. These results suggest that wages are less sticky in Japan than in the US. Inflation indexation plays a key role in the US, but is less important in Japan. Rolling estimations indicate that the NKWPC has flattened over time in Japan. Analysis of recent data indicates that in both countries the role of inflation indexation is quantitatively smaller than before, although this result might be influenced by low and stable inflation rates over the past few decades

Batch Bayesian active learning for feasible region identification by local penalization

Identifying all designs satisfying a set of constraints is an important part of the engineering design process. With physics-based simulation codes, evaluating the constraints becomes considerable expensive. Active learning can provide an elegant approach to efficiently characterize the feasible region, i.e., the set of feasible designs. Although active learning strategies have been proposed for this task, most of them are dealing with adding just one sample per iteration as opposed to selecting multiple samples per iteration, also known as batch active learning. While this is efficient with respect to the amount of information gained per iteration, it neglects available computation resources. We propose a batch Bayesian active learning technique for feasible region identification by assuming that the constraint function is Lipschitz continuous. In addition, we extend current state-of-the-art batch methods to also handle feasible region identification. Experiments show better performance of the proposed method than the extended batch methods

Increased Stathmin1 Expression in the Dentate Gyrus of Mice Causes Abnormal Axonal Arborizations

Pituitary adenylate cyclase-activating polypeptide (PACAP) is involved in multiple brain functions. To clarify the cause of abnormal behavior in PACAP deficient-mice, we attempted the identification of genes whose expression was altered in the dentate gyrus of PACAP-deficient mice using the differential display method. Expression of stathmin1 was up-regulated in the dentate gyrus at both the mRNA and protein levels. PACAP stimulation inhibited stathmin1 expression in PC12 cells, while increased stathmin1expression in neurons of the subgranular zone and in primary cultured hippocampal neurons induced abnormal arborization of axons. We also investigated the pathways involved in PACAP deficiency. Ascl1 binds to E10 box of the stathmin1 promoter and increases stathmin1 expression. Inhibitory bHLH proteins (Hes1 and Id3) were rapidly up-regulated by PACAP stimulation, and Hes1 could suppress Ascl1 expression and Id3 could inhibit Ascl1 signaling. We also detected an increase of stathmin1 expression in the brains of schizophrenic patients. These results suggest that up-regulation of stathmin1 in the dentate gyrus, secondary to PACAP deficiency, may create abnormal neuronal circuits that cause abnormal behavior

Long-term interest rates and bank loan supply: Evidence from firm-bank loan-level data

Based on a mean-variance model of bank portfolio selection subject to the value-at-risk constraint, we make predictions on transmission channels through which lower long-term interest rates increase bank loan supply: the portfolio balance channel, the bank balance sheet channel, and the risk-taking channel. Using a firm-bank loan-level panel dataset for Japan, we find evidence of the presence of these channels. First, an unanticipated reduction in long-term rates increased bank loan supply. Second, banks that enjoyed larger capital gains on their bond holdings increased loan supply. Further, this effect was stronger for loans to smaller, more leveraged, and less creditworthy firms.基盤研究(S) = Grants-in-Aid for Scientific Research (S)60 p

Palladium-Catalyzed Desymmetrization of Silacyclobutanes with Alkynes: Enantioselective Synthesis of Silicon-Stereogenic 1-Sila-2-cyclohexenes and Mechanistic Considerations

A palladium-catalyzed enantioselective desymmetrization of silacyclobutanes with alkynes has been developed to give silicon-stereogenic 1-sila-2-cyclohexenes with high enantioselectivity. The products thus obtained undergo further derivatizations with complete stereoselectivity, and a new catalytic cycle involving alkyne coordination (oxidative cyclization)–transmetalation (σ-bond metathesis)–reductive elimination has also been proposed

Palladium-Catalyzed Desymmetrization of Silacyclobutanes with Alkynes: Enantioselective Synthesis of Silicon-Stereogenic 1-Sila-2-cyclohexenes and Mechanistic Considerations

A palladium-catalyzed enantioselective desymmetrization of silacyclobutanes with alkynes has been developed to give silicon-stereogenic 1-sila-2-cyclohexenes with high enantioselectivity. The products thus obtained undergo further derivatizations with complete stereoselectivity, and a new catalytic cycle involving alkyne coordination (oxidative cyclization)–transmetalation (σ-bond metathesis)–reductive elimination has also been proposed