How do servant leadership and self-esteem at work shape family performance in China? : A resource-gain-development perspective

Acknowledgements This study was supported by National Natural Science Foundation of China (Grant No. 71872139), the Humanity and Social Science Foundation of Ministry of Education of China (Grant No. 18YJC630164) and The Fundamental Research Funds for the Central Universities of China.Peer reviewedPostprin

Four years of multi-modal odometry and mapping on the rail vehicles

Precise, seamless, and efficient train localization as well as long-term railway environment monitoring is the essential property towards reliability, availability, maintainability, and safety (RAMS) engineering for railroad systems. Simultaneous localization and mapping (SLAM) is right at the core of solving the two problems concurrently. In this end, we propose a high-performance and versatile multi-modal framework in this paper, targeted for the odometry and mapping task for various rail vehicles. Our system is built atop an inertial-centric state estimator that tightly couples light detection and ranging (LiDAR), visual, optionally satellite navigation and map-based localization information with the convenience and extendibility of loosely coupled methods. The inertial sensors IMU and wheel encoder are treated as the primary sensor, which achieves the observations from subsystems to constrain the accelerometer and gyroscope biases. Compared to point-only LiDAR-inertial methods, our approach leverages more geometry information by introducing both track plane and electric power pillars into state estimation. The Visual-inertial subsystem also utilizes the environmental structure information by employing both lines and points. Besides, the method is capable of handling sensor failures by automatic reconfiguration bypassing failure modules. Our proposed method has been extensively tested in the long-during railway environments over four years, including general-speed, high-speed and metro, both passenger and freight traffic are investigated. Further, we aim to share, in an open way, the experience, problems, and successes of our group with the robotics community so that those that work in such environments can avoid these errors. In this view, we open source some of the datasets to benefit the research community

A model-based circular binary segmentation algorithm for the analysis of array CGH data

<p>Abstract</p> <p>Background</p> <p>Circular Binary Segmentation (CBS) is a permutation-based algorithm for array Comparative Genomic Hybridization (aCGH) data analysis. CBS accurately segments data by detecting change-points using a maximal-<it>t </it>test; but extensive computational burden is involved for evaluating the significance of change-points using permutations. A recent implementation utilizing a hybrid method and early stopping rules (hybrid CBS) to improve the performance in speed was subsequently proposed. However, a time analysis revealed that a major portion of computation time of the hybrid CBS was still spent on permutation. In addition, what the hybrid method provides is an approximation of the significance upper bound or lower bound, not an approximation of the significance of change-points itself.</p> <p>Results</p> <p>We developed a novel model-based algorithm, extreme-value based CBS (eCBS), which limits permutations and provides robust results without loss of accuracy. Thousands of aCGH data under null hypothesis were simulated in advance based on a variety of non-normal assumptions, and the corresponding maximal-<it>t </it>distribution was modeled by the Generalized Extreme Value (GEV) distribution. The modeling results, which associate characteristics of aCGH data to the GEV parameters, constitute lookup tables (eXtreme model). Using the eXtreme model, the significance of change-points could be evaluated in a constant time complexity through a table lookup process.</p> <p>Conclusions</p> <p>A novel algorithm, eCBS, was developed in this study. The current implementation of eCBS consistently outperforms the hybrid CBS 4× to 20× in computation time without loss of accuracy. Source codes, supplementary materials, supplementary figures, and supplementary tables can be found at <url>http://ntumaps.cgm.ntu.edu.tw/eCBSsupplementary</url>.</p

The adoption of technological innovations in a B2B context and its impact on firm performance: An ethical leadership perspective

The introduction of the digital economy has opened much discussion on the various business models that challenge traditional thinking in B2B marketing. This includes technological innovation in the digital space which has brought about theoretical changes in the way marketing is applied, more so in the B2B environment where communication is essential in the alignment with various stakeholders. Several discussions on ethical leadership in the digital economy have provided some insights into addressing increased complexity in a society where markets are connected (physically) yet disconnected (proximity) and this has led marketing practices going astray. Our paper proposes the relevance of ethical leadership and its role in the application of technological innovation by arguing that technological innovation has a positive impact on firm performance and that ethical leadership plays a critical role in moderating this effect. We use a dynamic panel data system Generalized Method of Moment (GMM) approach to examine secondary data from 465 IT service companies and demonstrate that ethical leadership plays a critical role as it enables innovation through technology, and this has an impact on the firm’s performance

Oxidative Stress and Human Skin Connective Tissue Aging

Everyone desires healthy and beautiful-looking skin. However, as we age, our skin becomes old due to physiological changes. Reactive oxygen species (ROS) is an important pathogenic factor involved in human aging. Human skin is exposed to ROS generated from both extrinsic sources such as as ultraviolet (UV) light from the sun, and intrinsic sources such as endogenous oxidative metabolism. ROS-mediated oxidative stress damages the collagen-rich extracellular matrix (ECM), the hallmark of skin connective tissue aging. Damage to dermal collagenous ECM weakens the skin’s structural integrity and creates an aberrant tissue microenvironment that promotes age-related skin disorders, such as impaired wound healing and skin cancer development. Here, we review recent advances in our understanding of ROS/oxidative stress and skin connective tissue aging

Template-induced high-crystalline g-C3N4 nanosheets for enhanced photocatalytic H2 evolution

High-crystalline g-C3N4 nanosheets (HC−CN) with reduced structural defects have been constructed through Ni-foam-induced thermal condensation because Ni-foam not only serves as a template for deposition of the 2D g-C3N4 nanosheets with high surface area to prevent stacking of g-C3N4 nanosheets but also acts as a catalyst to promote the polymerization and crystallization of g-C3N4 via effective dehydrogenation of the −NH2 group. The obtained HC–CN exhibits superior photocatalytic performance for H2 evolution under visible light irradiation (λ > 400 nm), which significantly benefits from the prolonged lifetime of photogenerated charge carriers and the increase of the transfer path within 2D structures of high-crystalline g-C3N4 nanosheets