Griffith University

About: Griffith University is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 13830 authors who have published 49318 publications receiving 1420865 citations.

Disentangling the underlying dimensions of psychopathy and conduct problems in childhood: a community study.

Abstract: The psychometric and predictive validity of callous-unemotional (CU) traits as an early precursor of conduct disorder and antisocial behavior were assessed. A community sample of children (4-9 years of age) were tested 12 months apart with the Antisocial Process Screening Device (APSD; P. J. Frick & R. D. Hare, 2002), a measure of early signs of psychopathy in children. Factor analysis supported the structure of the APSD. Given controversy surrounding construct overlap between psychopathy and conduct problems, a factor analysis was conducted on pooled items from the Strengths and Difficulties Questionnaire and APSD. A 5-factor solution resulted: antisocial, hyperactivity, CU traits, anxiety, and peer problems. CU traits added small but significant improvements in the 12-month prediction of antisocial behavior for boys and older girls, after controlling for Time 1 measures. These results indicate that although the dimensions of the APSD overlap with dimensions of the disruptive behavior disorders, CU traits have unique predictive validity in childhood.

Multi-shelled metal oxides prepared via an anion-adsorption mechanism for lithium-ion batteries

Abstract: One of the major problems in the development of lithium-ion batteries is the relatively low capacity of cathode materials compared to anode materials. Owing to its high theoretical capacity, vanadium oxide is widely considered as an attractive cathode candidate. However, the main hindrances for its application in batteries are its poor capacity retention and low rate capability. Here, we report the development of multi-shelled vanadium oxide hollow microspheres and their related electrochemical properties. In contrast to the conventional cation-adsorption process, in which the metal cations adsorb on negatively charged carbonaceous templates, our approach enables the adsorption of metal anions. We demonstrate controlled syntheses of several multi-shelled metal oxide hollow microspheres. In particular, the multi-shelled vanadium oxide hollow microspheres deliver a specific capacity of 447.9 and 402.4mAhg(-1) for the first and 100th cycle at 1,000mAg(-1), respectively. The significant performance improvement offers the potential to reduce the wide capacity gap often seen between the cathode and anode materials.

Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.

Abstract: Direct prediction of protein structure from sequence is a challenging problem. An effective approach is to break it up into independent sub-problems. These sub-problems such as prediction of protein secondary structure can then be solved independently. In a previous study, we found that an iterative use of predicted secondary structure and backbone torsion angles can further improve secondary structure and torsion angle prediction. In this study, we expand the iterative features to include solvent accessible surface area and backbone angles and dihedrals based on Cα atoms. By using a deep learning neural network in three iterations, we achieved 82% accuracy for secondary structure prediction, 0.76 for the correlation coefficient between predicted and actual solvent accessible surface area, 19° and 30° for mean absolute errors of backbone φ and ψ angles, respectively, and 8° and 32° for mean absolute errors of Cα-based θ and τ angles, respectively, for an independent test dataset of 1199 proteins. The accuracy of the method is slightly lower for 72 CASP 11 targets but much higher than those of model structures from current state-of-the-art techniques. This suggests the potentially beneficial use of these predicted properties for model assessment and ranking.

Coexisting Single-Atomic Fe and Ni Sites on Hierarchically Ordered Porous Carbon as a Highly Efficient ORR Electrocatalyst

Abstract: The development of oxygen reduction reaction (ORR) electrocatalysts based on earth-abundant nonprecious materials is critically important for sustainable large-scale applications of fuel cells and metal-air batteries. Herein, a hetero-single-atom (h-SA) ORR electrocatalyst is presented, which has atomically dispersed Fe and Ni coanchored to a microsized nitrogen-doped graphitic carbon support with unique trimodal-porous structure configured by highly ordered macropores interconnected through mesopores. Extended X-ray absorption fine structure spectra confirm that Fe- and Ni-SAs are affixed to the carbon support via FeN4 and NiN4 coordination bonds. The resultant Fe/Ni h-SA electrocatalyst exhibits an outstanding ORR activity, outperforming SA electrocatalysts with only Fe- or Ni-SAs, and the benchmark Pt/C. The obtained experimental results indicate that the achieved outstanding ORR performance results from the synergetic enhancement induced by the coexisting FeN4 and NiN4 sites, and the superior mass-transfer capability promoted by the trimodal-porous-structured carbon support.