EMPLOYEE VOICE BEHAVIOR DURING ORGANIZATIONAL CHANGE

I seek to understand the dynamic organizational change process by focusing on employees' change-related voice as the mechanism through which their dissatisfaction with change implementation processes relates to their positive behavioral outcomes during organizational change. I propose that employees who are dissatisfied with their organization's change implementation processes are more likely to engage in change-related voice behavior - defined as behavior that expresses constructive suggestions (promotive voice) and challenges (prohibitive voice) to improve change processes - and that their affective commitment to change, change efficacy, and work-unit leader's empowering leader behavior will positively moderate the relationship between dissatisfaction and change-related voice behavior. Through a survey with a sample of 192 employees and 27 work-unit leaders working for an organization undergoing a large-scale organizational change, I found that the patterns of how the hypothesized antecedents relate to change-related voice behavior vary depending on the type of voice behavior. Specifically, employees are more likely to make constructive suggestions (promotive voice) when their work-unit leader shows empowering behaviors and when they are high in change efficacy. Employees who are dissatisfied with the change implementation processes engage in promotive voice behavior only when they are strongly committed to change (affective commitment to change) and believe they are not capable of handling change demands (change efficacy). Furthermore, employees tend to point out problems in current change implementation processes (prohibitive voice) when the levels of their work-unit leader's empowering leader behavior and dissatisfaction with the current change processes are high; and the relationship between dissatisfaction and prohibitive voice was stronger when the level of their change efficacy is low rather than high. Lastly, increased levels of employee change-related voice behavior in both types are positively related with their individual performance of change tasks

Electronic structure of biased alternating-twist multilayer graphene

We theoretically study the energy and optical absorption spectra of alternating twist multilayer graphene (ATMG) under a perpendicular electric field. We obtain analytically the low-energy effective Hamiltonian of ATMG up to pentalayer in the presence of the interlayer bias by means of first-order degenerate-state perturbation theory, and present general rules for constructing the effective Hamiltonian for an arbitrary number of layers. Our analytical results agree to an excellent degree of accuracy with the numerical calculations for twist angles $\theta \gtrsim 2.2^{\circ}$ that are larger than the typical range of magic angles. We also calculate the optical conductivity of ATMG and determine its characteristic optical spectrum, which is tunable by the interlayer bias. When the interlayer potential difference is applied between consecutive layers of ATMG, the Dirac cones at the two moir\'{e} Brillouin zone corners $\bar{K}$ and $\bar{K}'$ acquire different Fermi velocities, generally smaller than that of monolayer graphene, and the cones split proportionally in energy resulting in a step-like feature in the optical conductivity.Comment: 11 pages, 11 figures, 2 table

Nearly flat bands in twisted triple bilayer graphene

We investigate the electronic structure of alternating-twist triple Bernal-stacked bilayer graphene (t3BG) as a function of interlayer coupling $\omega$, twist angle $\theta$, interlayer potential difference $\Delta$, and top-bottom bilayers sliding vector $\boldsymbol{\tau}$ for three possible configurations AB/AB/AB, AB/BA/AB, and AB/AB/BA. The parabolic low-energy band dispersions in a Bernal-stacked bilayer and gap-opening through a finite interlayer potential difference $\Delta$ allows the flattening of bands in t3BG down to $\sim 20$~meV for twist angles $\theta \lesssim 2^{\circ}$ regardless of the stacking types. The easier isolation of the flat bands and associated reduction of Coulomb screening thanks to the intrinsic gaps of bilayer graphene for finite $\Delta$ facilitate the formation of correlation-driven gaps when it is compared to the metallic phases of twisted trilayer graphene under electric fields. We obtain the stacking dependent Coulomb energy versus bandwidth $U/W \gtrsim 1$ ratios in the $\theta$ and $\Delta$ parameter space. We also present the expected $K$-valley Chern numbers for the lowest-energy nearly flat bands.Comment: 15 pages, 10 figure

Pixel-wise classification in graphene-detection with tree-based machine learning algorithms

Mechanical exfoliation of graphene and its identification by optical inspection is one of the milestones in condensed matter physics that sparked the field of 2D materials. Finding regions of interest from the entire sample space and identification of layer number is a routine task potentially amenable to automatization. We propose supervised pixel-wise classification methods showing a high performance even with a small number of training image datasets that require short computational time without GPU. We introduce four different tree-based machine learning algorithms -- decision tree, random forest, extreme gradient boost, and light gradient boosting machine. We train them with five optical microscopy images of graphene, and evaluate their performances with multiple metrics and indices. We also discuss combinatorial machine learning models between the three single classifiers and assess their performances in identification and reliability. The code developed in this paper is open to the public and will be released at github.com/gjung-group/Graphene_segmentation.Comment: 12 pages, 6 figure

Peptidyl-prolyl cis/trans isomerase Pin1 interacts with hepatitis B virus core particle, but not with HBc protein, to promote HBV replication

Here, we demonstrate that the peptidyl-prolyl cis/trans isomerase Pin1 interacts noncovalently with the hepatitis B virus (HBV) core particle through phosphorylated serine/threonine-proline (pS/TP) motifs in the carboxyl-terminal domain (CTD) but not with particle-defective, dimer-positive mutants of HBc. This suggests that neither dimers nor monomers of HBc are Pin1-binding partners. The 162TP, 164SP, and 172SP motifs within the HBc CTD are important for the Pin1/core particle interaction. Although Pin1 dissociated from core particle upon heat treatment, it was detected as an opened-up core particle, demonstrating that Pin1 binds both to the outside and the inside of the core particle. Although the amino-terminal domain S/TP motifs of HBc are not involved in the interaction, 49SP contributes to core particle stability, and 128TP might be involved in core particle assembly, as shown by the decreased core particle level of S49A mutant through repeated freeze and thaw and low-level assembly of the T128A mutant, respectively. Overexpression of Pin1 increased core particle stability through their interactions, HBV DNA synthesis, and virion secretion without concomitant increases in HBV RNA levels, indicating that Pin1 may be involved in core particle assembly and maturation, thereby promoting the later stages of the HBV life cycle. By contrast, parvulin inhibitors and PIN1 knockdown reduced HBV replication. Since more Pin1 proteins bound to immature core particles than to mature core particles, the interaction appears to depend on the stage of virus replication. Taken together, the data suggest that physical association between Pin1 and phosphorylated core particles may induce structural alterations through isomerization by Pin1, induce dephosphorylation by unidentified host phosphatases, and promote completion of virus life cycle

Laboratory information management system for COVID-19 non-clinical efficacy trial data

Background : As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. Results : In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. Conclusions : This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.This research was supported by the National research foundation of Korea(NRF) grant funded by the Korea government(MSIT) (2020M3A9I2109027 and 2021M3H9A1030260)

Substrate effect on edge states of a quantum spin Hall insulator in Kane–Mele model

We investigate the topological phases and the edge states of a quantum spin Hall insulator of the Kane–Mele model placed on top of a two-dimensional normal insulator caused by the staggered lattice potential. We show that, in the parameter space of interlayer hopping and the staggered lattice potential, there occurs a topological phase transition between the two phases, topological and normal insulating phases. Effective Hamiltonian for the edge states is constructed and it is verified that it reproduces well the edge-state energy dispersion in the presence of small interlayer hopping. Finally, we estimate the edge-state width by fitting the probability densities numerically and discuss how the edge-state width changes near the phase boundary and in an asymptotic region