A study of school adjustment related variables of young children

The school adjustment of children is the cornerstone of their development, and has been known to be influenced by a variety of factors. This study investigated the effects of peer relationships, theory of mind (ToM), hot executive function (hot EF), and cognitive ability on young children’s school adjustment. Participants were 183 children with a mean age of 62.6 months attending ten kindergartens in Korea. Data was collected using the Preschool Adjustment Questionnaire, the Penn Interactive Peer Play Scale, three theory of mind tasks, two hot executive function tasks, and the Korean version of the Kaufman Assessment Battery for Children. School adjustment was found to correlate with peer relationships, cognitive ability, hot EF, and ToM. Using Hierarchical Regression analyses, hot EF was found to contribute unique variance in predicting school adjustment, even when variance due to peer relationships and cognitive abilities was excluded. This study has implications for identifying relevant variables that affect the school adjustment of young children, which can have a significant impact on future research on school adaptation.Keywords: cognitive ability; hot executive function; peer relationships; school adjustment; theory of min

System-reliability-based Disaster Resilience Evaluation of Cable-stayed Bridge under Fire Hazard Using Reliability-Redundancy Analysis

The 20th working conference of the IFIP Working Group 7.5 on Reliability and Optimization of Structural Systems (IFIP 2022) will be held at Kyoto University, Kyoto, Japan, September 19-20, 2022.The concept of disaster resilience recently emerged in efforts to gain holistic understanding of civil infrastructure systems exposed to various natural or human-made hazards. To effectively evaluate the resilience of complex infrastructure systems generally consisting of many interdependent structural components, Lim et al. (2022) proposed a system-reliability-based framework for disaster resilience. In the proposed framework, the disaster resilience of a civil infrastructure system is characterized by three criteria: reliability, redundancy, and recoverability. For comprehensive resilience analyses at the scale of individual structures, the reliability (β) and redundancy (π) indices were newly defined in the context of component- and system-level reliability analysis, respectively. Reliability-redundancy diagram, i.e., the scatter plot of the reliability and redundancy indices computed for each initial disruption scenario, was also proposed to help a decision-maker check whether the corresponding risk is acceptable for the society. In this paper, we demonstrate the framework through its application to a cable-stayed bridge in South Korea, the Seohae Grand Bridge under fire hazards. First, a probabilistic model is developed to describe the hazard of fire scenarios that may occur on the deck of the cable-stayed bridge. Next, finite element simulations are performed to compute the reliability and redundancy indices through component and system reliability analyses for the fire accident scenarios. An adaptive simulation method, AK-MCS (Echard et al. 2011), is employed to overcome the computational cost issue. The example successfully demonstrates that the reliability-redundancy analysis and diagram facilitate a comprehensive assessment of the disaster resilience of a complex civil infrastructure such as a cable-stayed bridge by using sophisticated computational simulations and advanced reliability methods

Effects of neutron-rich nuclei masses on symmetry energy

We explore the impact of neutron-rich nuclei masses on the symmetry energy properties using the mass table evaluated by the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) model. First, using the semi-empirical mass formula with the DRHBc mass table, we investigate the symmetry energy at saturation density $\rho_0$, denoted as $S_0$, and the ratio of surface to volume contributions to the symmetry energy, $\kappa$. As a result, we obtain $S_0=27.85\,{\rm MeV}$ ($\kappa=1.38$) for $a_{\rm sym}(A) =S_0 (1 - \kappa A^{-1/3})$ (Type I) and $S_0=32.66\,{\rm MeV}$ ($\kappa=3.15$) for $a_{\rm sym}(A) = S_0 (1 + \kappa A^{-1/3} )^{-1}$ (Type II), which are lower than those obtained using the AME2020 mass table, $S_0=28.54\,{\rm MeV}$ ($\kappa=1.29$) for Type I and $S_0=33.81\,{\rm MeV}$ ($\kappa=3.04$) for Type II. Second, we further investigate the effect of these changes in $a_{\rm sym}(A)$ on the density-dependent symmetry energy by employing the empirical model of $S(\rho) = C_k(\rho/\rho_0)^{2/3} + C_1(\rho/\rho_0) + C_2(\rho/\rho_0)^{\gamma}$ and universal relation of $a_{\rm sym}(A=208) = S(\rho=0.1\,{\rm fm}^{-3})$. Compared to the experimental constraints, we find that $S_0$ and slope parameter $L$, determined by the DRHBc mass table with Type II, are more suitable to explain the constraints by heavy ion collisions and isobaric analog states than AME2020. We also discuss the neutron skin thickness derived from the $L$, comparing it with experimental measurements

Conversion Reactions of Transition Metal Chlorides

Li-ion batteries have become an attractive key component in energy storage systems as the worldwide energy infrastructure shifts towards being more environmentally concerned. The development of Li-ion batteries has also been pressured from the rapid growth of modern technologies such as mobile electronic device and an electric vehicle based transportation society. However, unlike the fast pace development of other aspects of these technologies, the development of better Li-ion batteries has remained a limiting factor. Therefore, today’s technology market demands the appearance of new Li-ion battery system with higher energy density. To satisfy this demand, Li-ion batteries must advance beyond intercalation cathode materials. Transition metal chloride cathode conversion materials show promise of a new paradigm in energy storage system due to their relatively high energy density. However, disintegration of metal chlorides remains a critical issue in application to a battery. In this thesis, highly concentrated electrolytes that consist of 0.1M LiCl/6M LiTFSI and 0.1M LiCl/0.1M LiNO3/6M LiTFSI in TEGDME solvent is introduced to effectively suppress the dissolution of cathode materials. Among metal chloride materials, CoCl2 and NiCl2 show promise with high capacities of 160 mAh g-1 and 330 mAh g-1, up to 40% and 80% of their theoretical capacities respectively, in a superconcentrated electrolyte with LiNO3 additive introduced to protect the lithium surface. NiCl2 in a properly treated electrolyte (0.1M LiCl/0.1M LiNO3/6M LiTFSI in TEGDME) showed the most promising behavior with stable cycling and low hysteresis ~ 0.5 V as a new positive electrode material to replace intercalation based rechargeable battery

Detecting Contextual Network Anomaly in the Radio Network Controller from Bayesian Data Analysis

This thesis presents Bayesian approach for a contextual network anomaly detection. Network anomaly detection is important in a computer system performance monitoring perspective. Detecting a contextual anomaly is much harder since we need to take the context into account in order to explain whether it is normal or abnormal. The main idea of this thesis is to find contextual attributes from a set of indicators, then to estimate the resource loads through the Bayesian model. The proposed algorithm offers three advantages. Firstly, the model can estimate resource loads with automatically selected indicators and its credible intervals. Secondly, both point and collective contextual anomalies can be captured by the posterior predictive distribution. Lastly, the structural interpretation of the model gives us a way to find similar nodes. This thesis employs real data from Radio Network Controller (RNC) to validate the effectiveness in detecting contextual anomalies

Detecting Contextual Network Anomaly in the Radio Network Controller from Bayesian Data Analysis

This thesis presents Bayesian approach for a contextual network anomaly detection. Network anomaly detection is important in a computer system performance monitoring perspective. Detecting a contextual anomaly is much harder since we need to take the context into account in order to explain whether it is normal or abnormal. The main idea of this thesis is to find contextual attributes from a set of indicators, then to estimate the resource loads through the Bayesian model. The proposed algorithm offers three advantages. Firstly, the model can estimate resource loads with automatically selected indicators and its credible intervals. Secondly, both point and collective contextual anomalies can be captured by the posterior predictive distribution. Lastly, the structural interpretation of the model gives us a way to find similar nodes. This thesis employs real data from Radio Network Controller (RNC) to validate the effectiveness in detecting contextual anomalies

Conversion Reactions of Transition Metal Chlorides

Li-ion batteries have become an attractive key component in energy storage systems as the worldwide energy infrastructure shifts towards being more environmentally concerned. The development of Li-ion batteries has also been pressured from the rapid growth of modern technologies such as mobile electronic device and an electric vehicle based transportation society. However, unlike the fast pace development of other aspects of these technologies, the development of better Li-ion batteries has remained a limiting factor. Therefore, today’s technology market demands the appearance of new Li-ion battery system with higher energy density. To satisfy this demand, Li-ion batteries must advance beyond intercalation cathode materials. Transition metal chloride cathode conversion materials show promise of a new paradigm in energy storage system due to their relatively high energy density. However, disintegration of metal chlorides remains a critical issue in application to a battery. In this thesis, highly concentrated electrolytes that consist of 0.1M LiCl/6M LiTFSI and 0.1M LiCl/0.1M LiNO3/6M LiTFSI in TEGDME solvent is introduced to effectively suppress the dissolution of cathode materials. Among metal chloride materials, CoCl2 and NiCl2 show promise with high capacities of 160 mAh g-1 and 330 mAh g-1, up to 40% and 80% of their theoretical capacities respectively, in a superconcentrated electrolyte with LiNO3 additive introduced to protect the lithium surface. NiCl2 in a properly treated electrolyte (0.1M LiCl/0.1M LiNO3/6M LiTFSI in TEGDME) showed the most promising behavior with stable cycling and low hysteresis ~ 0.5 V as a new positive electrode material to replace intercalation based rechargeable battery

The first complete plastome sequence from family Flagellariaceae (Flagellaria indica L., Poales)

As a part of phylogenomic study of graminids, we report the complete plastome sequence of Flagellaria indica L. (Flagellariaceae) (NCBI No. MZ504969). This is the first reported complete plastome sequence from the Flagellariaceae. This plastome shows typical quadripartite structure. The plastome size is 161,643 bp, which consists of 88,714 bp large single copy (LSC), 19,065 bp small single-copy (SSC), and 26,932 bp inverted repeat (IR) regions. However, we detected F. indica plastome has a 288 bp small inversion between ycf3 and trnS-GGA. The palindromic repeats of 10 bp (TTCCAATTTC/GAAATTGGAA) were located on the two break points of inversion. F. indica plastome contains 113 genes, including 79 protein-coding, 30 tRNA, and four rRNA genes. Unlike other families of graminids, the functional ycf1 and ycf2 genes exist. Sixteen genes contain one intron and two genes (clpP and ycf3) have two introns. Sixty-two simple sequence repeat (SSR) loci are scattered in the plastome, respectively. The phylogenetic tree shows that Flagellariaceae are the basal sister lineage of other graminid families

A Combined Spectroscopic Investigation of Charge Trapping Mechanism In Polymer Semiconducotrs for High Operational Stablity of Polymer Field-Effect Transistors

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