Developing Asset Maintenance Evaluation System

In today’s global environment, asset maintenance has become a prominent function for manufacturing organizations to enhance production operations and support business transition. Significant efforts have been conducted by researchers and practitioners on selecting maintenance strategies, implementing advanced technologies for optimizing asset’s life cycle cost. Meanwhile, the increasing importance of asset maintenance management requires the maintenance activities be measured in terms of their productivity. However, there is no “easy way” to measure the performance of asset maintenance due to the complexity of maintenance function. The existing approaches cost organizations a tremendous amount of time and resources. The purpose of this study is to develop a model that provides thorough and accurate evaluation for asset maintenance in a time-efficient and cost-effective manner. The developed model could be used for both external assessment to obtain concrete information prior to providing service and internal assessment to enhance continuous improvement. A number of organizations have participated in this study for validating the effectiveness and applicability of the model

Developing a Bayesian Network risk model to enhance Lean Six Sigma

In today\u27s global market, manufacturing organizations are striving to improve their pro- duction performance in order to remain competitive advantages. For the past few decades, many efforts have been conducted by both researchers and practitioners to develop managerial and technical approaches to improve manufacturing processes. Among them, Lean and Six Sigma have become the two most recognized methodologies and together they comprise the primary components of process improvement strategies. However, with the manufacturing system and its external environment becoming more and more complex, a great range of risk factors can affect the results of the Lean Six Sigma initiatives. Consequently, the organization is constantly exposed to risks of not being able to generate a quality product to meet the customer\u27s requirements. The existence of risk is often neglected because there is no easy way to perform the risk analysis for Lean Six Sigma activities due to their complexity. The purpose of this study is to develop a risk-informed model that provides a systematic evaluation for potential risks to enhance the implementation of Lean Six Sigma initiatives. The methodology derives from the Bayesian Network methodology and is incorporated with other risk management techniques. Combining graphical approach to represent cause-and-effect relationships between events of interests and probabilistic inference to estimate their likelihoods, Bayesian Network provides an effective method to evaluate the reliability of Lean Six Sigma. The developed model can be used for assessing the potential risks associated with Lean Six Sigma initiatives and prioritizing efforts to minimize their impacts. The model can serve as a primary component of the decision-making toolbox for maximizing the effectiveness of Lean Six Sigma initiatives and subsequently increasing the competitiveness of a manufacturing firm

How and what kind of cities benefit from the development of digital inclusive finance? Evidence from the upgrading of export in Chinese cities

Employing Chinese customs data and the Peking University Digital Financial Inclusion Index of China, this paper studies the impact of China’s digital finance development on the upgrading of export at the city level and further explores the heterogeneity across cities and the mechanisms through which digital finance influences export upgrading. Benchmark results suggest that digital inclusive finance can significantly promote the upgrading of export. The heterogeneity analysis shows that cities with a smaller size, lower wage, higher human capital level, and better location advantage experience greater facilitating effects of digital inclusive finance on promoting export upgrading. It suggests that, compared with ‘icing on the cake’, the digital inclusive finance plays a better role in ‘offering fuel in snowy weather’, whereas full exertion of the inclusiveness of digital finance requires higher human capital and location advantage. Further mechanism analysis shows that innovation effect and market effect are the main channels where digital inclusive finance promotes the upgrading of a city’s export

Change Point Detection on a Separable Model for Dynamic Networks

This paper studies the change point detection problem in time series of networks, with the Separable Temporal Exponential-family Random Graph Model (STERGM). We consider a sequence of networks generated from a piecewise constant distribution that is altered at unknown change points in time. Detection of the change points can identify the discrepancies in the underlying data generating processes and facilitate downstream dynamic network analysis tasks. Moreover, the STERGM that focuses on network statistics is a flexible model to fit dynamic networks with both dyadic and temporal dependence. We propose a new estimator derived from the Alternating Direction Method of Multipliers (ADMM) and the Group Fused Lasso to simultaneously detect multiple time points, where the parameters of STERGM have changed. We also provide Bayesian information criterion for model selection to assist the detection. Our experiments show good performance of the proposed method on both simulated and real data. Lastly, we develop an R package CPDstergm to implement our method

Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning

We present a reinforcement learning (RL) framework that enables quadrupedal robots to perform soccer goalkeeping tasks in the real world. Soccer goalkeeping using quadrupeds is a challenging problem, that combines highly dynamic locomotion with precise and fast non-prehensile object (ball) manipulation. The robot needs to react to and intercept a potentially flying ball using dynamic locomotion maneuvers in a very short amount of time, usually less than one second. In this paper, we propose to address this problem using a hierarchical model-free RL framework. The first component of the framework contains multiple control policies for distinct locomotion skills, which can be used to cover different regions of the goal. Each control policy enables the robot to track random parametric end-effector trajectories while performing one specific locomotion skill, such as jump, dive, and sidestep. These skills are then utilized by the second part of the framework which is a high-level planner to determine a desired skill and end-effector trajectory in order to intercept a ball flying to different regions of the goal. We deploy the proposed framework on a Mini Cheetah quadrupedal robot and demonstrate the effectiveness of our framework for various agile interceptions of a fast-moving ball in the real world.Comment: First two authors contributed equally. Accompanying video is at https://youtu.be/iX6OgG67-Z

Phosphorylation of HOX11/TLX1 on Threonine-247 during mitosis modulates expression of cyclin B1

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background The HOX11/TLX1 (hereafter referred to as HOX11) homeobox gene was originally identified at a t(10;14)(q24;q11) translocation breakpoint, a chromosomal abnormality observed in 5-7% of T cell acute lymphoblastic leukemias (T-ALLs). We previously reported a predisposition to aberrant spindle assembly checkpoint arrest and heightened incidences of chromosome missegregation in HOX11-overexpressing B lymphocytes following exposure to spindle poisons. The purpose of the current study was to evaluate cell cycle specific expression of HOX11. Results Cell cycle specific expression studies revealed a phosphorylated form of HOX11 detectable only in the mitotic fraction of cells after treatment with inhibitors to arrest cells at different stages of the cell cycle. Mutational analyses revealed phosphorylation on threonine-247 (Thr247), a conserved amino acid that defines the HOX11 gene family and is integral for the association with DNA binding elements. The effect of HOX11 phosphorylation on its ability to modulate expression of the downstream target, cyclin B1, was tested. A HOX11 mutant in which Thr247 was substituted with glutamic acid (HOX11 T247E), thereby mimicking a constitutively phosphorylated HOX11 isoform, was unable to bind the cyclin B1 promoter or enhance levels of the cyclin B1 protein. Expression of the wildtype HOX11 was associated with accelerated progression through the G2/M phase of the cell cycle, impaired synchronization in prometaphase and reduced apoptosis whereas expression of the HOX11 T247E mutant restored cell cycle kinetics, the spindle checkpoint and apoptosis. Conclusions Our results demonstrate that the transcriptional activity of HOX11 is regulated by phosphorylation of Thr247 in a cell cycle-specific manner and that this phosphorylation modulates the expression of the target gene, cyclin B1. Since it is likely that Thr247 phosphorylation regulates DNA binding activity to multiple HOX11 target sequences, it is conceivable that phosphorylation functions to regulate the expression of HOX11 target genes involved in the control of the mitotic spindle checkpoint.Published versio