97 research outputs found
Perspectives of transformational leadership by child welfare workers : impacts on turnover inention
Indiana University-Purdue University Indianapolis (IUPUI)It is not a new phenomenon that there is a high turnover rate among social workers. In particular, child welfare has shown the highest rates of staff turnover. To address the issue, turnover and retention of child welfare workers have been studied for decades. The history of research produced a long list of determinants for child welfare worker turnover, more than 20 factors, and showed conflicting findings with the same variables. Moreover, the long list of factors for workers’ decisions to leave has poorly contributed to organizational practices for retaining child welfare workers. Therefore, this study aims to examine organizational factors, particularly leadership, for child welfare worker turnover intention, in order to help child welfare agencies to invent a practice model to prevent qualified worker’s turnover. To do so, it is important to examine the effect of organizational commitment on employees’ turnover intention. Therefore, following is the primary research question: Does the use of transformational leadership style in social work organizations explain child welfare worker turnover intention?
A cross-sectional survey research was employed among workers in public child welfare agencies in a Midwest state, United States (N=214). Five models were examined in terms of the direct and indirect effects of transformational leadership on turnover intention of child welfare workers using STATA ver. 15. The study finding showed that transformational leadership styles of local office directors had a direct and negative effect on child welfare workers’ turnover intention. As a result, this study recommends that child welfare provide local office directors with leadership training to reduce preventable turnover of child welfare workers. However, the findings should be cautiously interpreted due to the sampling strategy used in this study
Applying Grounded Theory to Conceptual Data Modeling: Effects of Constant Comparative Method
This article presents an experimental design and the pilot experiment results of applying grounded theory to conceptual datamodeling. The objective of this study is to develop a procedural method for concept discovery, which is essential in datamodeling. The research focuses on addressing the lack of procedural methods for understanding domain knowledge by datamodeler. The key idea of this article is that conceptual modeling can be strengthened by applying a constant comparativemethod of coding and analysis, which has been used to discover concepts in the social sciences. This article contributes newknowledge about the effects of applying interdisciplinary concept discovery in the context of conceptual data modeling. Theresults of the pilot experiment show that the proposed approach would have positive results
The effect of off-diagonal density matrix in DFT+DMFT for LiMnO
LiMnO has garnered much attention as one of the new-generation
battery material, due to the high capacity and low cost. In the present work,
we performed density functional theory (DFT)+ and dynamical mean field
theory (DMFT) calculations with continuous time quantum Monte Carlo impurity
solver to study the electronic properties of LiMnO. Due to the nature
of monoclinic symmetry, the off-diagonal terms in the -orbital block
Hamiltonian (and -orbital density matrix) are large, which results the large
suppression of the energy gap due to the underestimation of the crystal-field
splitting. We diagonalize the Mn block in the full Hamiltonian by
applying unitary rotation matrix, and obtained an energy gap of 0.8 eV,
although it is still smaller than the experimental gap of 2.1 eV even with the
large . In the - model, a small double counting energy is essential to
reduce the - hybridization, thus to obtain the experimental gap. We show
that the low-energy (-only basis) model is efficient to study the electronic
structure of LiMnO, since the Wannier basis is the hybridized state of
Mn and O orbitals. These results suggest the correct way to investigate
the low-symmetry materials using DFT+ DMFT method and to our knowledge, there
is no systematic study of the effect of the off-diagonal terms so far. We also
find that the antiferromagnetic ground state is stable with within DFT+, which is much smaller than widely used =5 eV.Comment: 8 pages, 8 figure
-Poisson surface reconstruction in curl-free flow from point clouds
The aim of this paper is the reconstruction of a smooth surface from an
unorganized point cloud sampled by a closed surface, with the preservation of
geometric shapes, without any further information other than the point cloud.
Implicit neural representations (INRs) have recently emerged as a promising
approach to surface reconstruction. However, the reconstruction quality of
existing methods relies on ground truth implicit function values or surface
normal vectors. In this paper, we show that proper supervision of partial
differential equations and fundamental properties of differential vector fields
are sufficient to robustly reconstruct high-quality surfaces. We cast the
-Poisson equation to learn a signed distance function (SDF) and the
reconstructed surface is implicitly represented by the zero-level set of the
SDF. For efficient training, we develop a variable splitting structure by
introducing a gradient of the SDF as an auxiliary variable and impose the
-Poisson equation directly on the auxiliary variable as a hard constraint.
Based on the curl-free property of the gradient field, we impose a curl-free
constraint on the auxiliary variable, which leads to a more faithful
reconstruction. Experiments on standard benchmark datasets show that the
proposed INR provides a superior and robust reconstruction. The code is
available at \url{https://github.com/Yebbi/PINC}.Comment: 21 pages, accepted for Advances in Neural Information Processing
Systems, 202
Smooth Model Predictive Path Integral Control without Smoothing
We present a sampling-based control approach that can generate smooth actions
for general nonlinear systems without external smoothing algorithms. Model
Predictive Path Integral (MPPI) control has been utilized in numerous robotic
applications due to its appealing characteristics to solve non-convex
optimization problems. However, the stochastic nature of sampling-based methods
can cause significant chattering in the resulting commands. Chattering becomes
more prominent in cases where the environment changes rapidly, possibly even
causing the MPPI to diverge. To address this issue, we propose a method that
seamlessly combines MPPI with an input-lifting strategy. In addition, we
introduce a new action cost to smooth control sequence during trajectory
rollouts while preserving the information theoretic interpretation of MPPI,
which was derived from non-affine dynamics. We validate our method in two
nonlinear control tasks with neural network dynamics: a pendulum swing-up task
and a challenging autonomous driving task. The experimental results demonstrate
that our method outperforms the MPPI baselines with additionally applied
smoothing algorithms.Comment: Accepted to IEEE Robotics and Automation Letters (and IROS 2022). Our
video can be found at https://youtu.be/ibIks6ExGw
Delocalized polaron and Burstein-Moss shift induced by Li in -: DFT+DMFT study
We performed density functional theory (DFT)+ and dynamical mean field
theory (DMFT) calculations with continuous time quantum Monte Carlo impurity
solver to investigate the electronic properties of VO and
LiVO ( = 0.125 and 0.25). Pristine VO is a
charge-transfer insulator with strong O -V hybridization, and exhibits a
large band gap () as well as non-zero conduction band (CB)
gap. We show that the band gap, the number of electrons of vanadium, ,
and conduction band (CB) gap for VO obtained from our DMFT calculations
are in excellent agreement with the experimental values. While the DFT+
approach replicates the experimental band gap, it overestimates the value of
and underestimates the CB gap. In the presence of low Li doping, the
electronic properties of VO are mainly driven by a polaronic mechanism,
the electron spin resonance and electron nuclear double resonance
spectroscopies observed the coexistence of free and bound polarons. Notably,
our DMFT results identify both polaron types, with the bound polaron being
energetically preferred, while DFT+ method predicts only the free polaron.
Our DMFT analysis also reveals that increased Li doping leads to electron
filling in the conduction band, shifting the Fermi level, this result
consistent with the observed Burstein-Moss shift upon enhanced Li doping and we
thus demonstrate that the DFT+DMFT approach can be used for accurate and
realistic description of strongly correlated materials.Comment: 12 pages, 13 figure
First-principle Study of Multiple Metastable Charge Ordering States in LaSrFeO
La doped SrFeO, LaSrFeO, exhibits a
metal-to-insulator transition accompanied by both antiferromagnetic and charge
ordering states along with the Fe-O bond disproportionation below a critical
temperature near 200K. Unconventionally slow charge dynamics measured in this
material near the critical temperature shows that its excited charge ordering
states can exhibit novel electronic structures with nontrivial energy profiles.
Here, we reveal possible metastable states of charge ordering structures in
LaSrFeO using the first-principle and climbing image
nudged elastic band methods. In the strong correlation regime,
LaSrFeO is an antiferromagnetic insulator with a charge
ordering state of the big-small-big pattern, consistent with the experimental
measurement of this material at the low temperature. As the correlation effect
becomes weak, we find at least two possible metastable charge ordering states
with the distinct Fe-O bond disproportionation. Remarkably, a ferroelectric
metallic state emerges with the small energy barrier of 7 meV, driven by
a metastable CO state of the small-medium-big pattern. The electronic
structures of these metastable charge ordering states are noticeably different
from those of the ground-state. Our results can provide an insightful
explanation to multiple metastable charge ordering states and the slow charge
dynamics of this and related oxide materials.Comment: The paper has 8 pages and 6 figure
Highly reproducible alkali metal doping system for organic crystals through enhanced diffusion of alkali metal by secondary thermal activation
In this paper, we report an efficient alkali metal doping system for organic single crystals. Our system employs an enhanced diffusion method for the introduction of alkali metal into organic single crystals by controlling the sample temperature to induce secondary thermal activation. Using this system, we achieved intercalation of potassium into picene single crystals with closed packed crystal structures. Using optical microscopy and Raman spectroscopy, we confirmed that the resulting samples were uniformly doped and became K2picene single crystal, while only parts of the crystal are doped and transformed into K2picene without secondary thermal activation. Moreover, using a customized electrical measurement system, the insulator-to-semiconductor transition of picene single crystals upon doping was confirmed by in situ electrical conductivity and ex situ temperature-dependent resistivity measurements. X-ray diffraction studies showed that potassium atoms were intercalated between molecular layers of picene, and doped samples did not show any KH- nor KOH-related peaks, indicating that picene molecules are retained without structural decomposition. During recent decades, tremendous efforts have been exerted to develop high-performance organic semiconductors and superconductors, whereas as little attention has been devoted to doped organic crystals. Our method will enable efficient alkali metal doping of organic crystals and will be a resource for future systematic studies on the electrical property changes of these organic crystals upon doping. © 2018 The Author(s
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