Dipole-Allowed Direct Band Gap Silicon Superlattices

Silicon is the most popular material used in electronic devices. However, its poor optical properties owing to its indirect band gap nature limit its usage in optoelectronic devices. Here we present the discovery of super-stable pure-silicon superlattice structures that can serve as promising materials for solar cell applications and can lead to the realization of pure Si-based optoelectronic devices. The structures are almost identical to that of bulk Si except that defective layers are intercalated in the diamond lattice. The superlattices exhibit dipole-allowed direct band gaps as well as indirect band gaps, providing ideal conditions for the investigation of a direct-to-indirect band gap transition. The transition can be understood in terms of a novel conduction band originating from defective layers, an overlap between the valence- and conduction-band edge states at the interface layers, and zone folding with quantum confinement effects on the conduction band of non-defective bulk-like Si. The fact that almost all structural portions of the superlattices originate from bulk Si warrants their stability and good lattice matching with bulk Si. Through first-principles molecular dynamics simulations, we confirmed their thermal stability and propose a possible method to synthesize the defective layer through wafer bonding

What is Needed the Most in MT-Supported Paper Writing

PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

Application of Artificial Neural Network to Search for Gravitational-Wave Signals Associated with Short Gamma-Ray Bursts

We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts. The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability is improved by the artificial neural network in comparison to the conventional detection statistic. Therefore, this algorithm increases the distance at which a gravitational-wave signal could be observed in coincidence with a gamma-ray burst. In order to demonstrate the performance, we also evaluate a few seconds of gravitational-wave data segment using the trained networks and obtain the false alarm probability. We suggest that the artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short gamma-ray bursts.Comment: 30 pages, 10 figure

Ionothermal Synthesis of Metal-Organic Framework

Ionothermal synthesis employs ionic liquids for synthesis of metal organic frameworks (MOFs) as solvent and template. The cations and anions of ionic liquids may be finely adjusted to produce a great variety of reaction environments and thus frameworks. Organisation of the structures synthesised from related ionic liquid combinations give rise to provocative chemical trends that may be used to predict future outcomes. Further analysis of their structures is possible by reducing the complex framework to its underlying topology, which by itself brings more precision to prediction. Through reduction, many seemingly different, but related classes of structures may be merged into larger groups and provide better understanding of the nanoscopic structures and synthesis conditions that gave rise to them. Ionothermal synthesis has promised to enable us to effectively plan the synthesis ahead for a given purpose. However, for its promise to be kept, several difficult limitations must be overcome, including the inseparable cations from the solvent that reside in the framework pore

An Efficient Building Evacuation Algorithm in Congested Networks

This paper proposes a new network model for the building evacuation problem considering congestion levels and provides a mixed integer linear programming (MILP) model and an efficient heuristic algorithm solving the problem. Constructing an optimization model with several congestion levels, we introduce a new network called the multi-class time-expanded (MCTE) network having several exclusive arcs connecting the same tail and head nodes. The MCTE networks make both the MILP model and the heuristic algorithm reflect a realistic situation in congested networks. Considering MCTE networks makes the problem difficult to solve, which motivates us to develop an efficient heuristic algorithm. We test our heuristic algorithm using several real-world networks such as a multiplex cinema, a subway station, and a large-size complex shopping mall in addition to an artificial network for clear comparison between the proposed algorithm and the MILP approaches. The results indicate that the proposed algorithm runs fast and produces a near-optimal solution compared with those from MILP models with a commercial solver.11Ysciescopu

COMPARATIVE GAIT ANALYSIS BETWEEN CHILDREN WITH AUTISM AND AGE MATCHED CONTROLS

There are very few studies that have analyzed the gait of children with autism. The purpose of this study was to investigate gait of children with autism using temporal-spatial variables. Fifteen children with autism and fifteen age matched typically developing children walked 3 times on the GAITRite® system. Dependent variables were statistically analyzed using independent samples t-tests with Bonferroni adjustments. Results show a reduction in cadence, gait velocity, step length and an increase in step width for the children with autism. In conclusion, our results suggest that the children with autism have abnormal gait compared to age matched controls

A Multilevel Study Of Supportive Leadership And Individual Work Outcomes: The Mediating Roles Of Team Cooperation, Job Satisfaction, And Team Commitment

Due to increasing empowerment in work teams, team leaders’ supportive role in helping team members perform their tasks is deemed important. The present study aimed at exploring the multilevel dynamics involving team leaders’ supportive leadership and individual work outcomes. Longitudinal survey data were collected from 536 employees in 69 teams of a large engineering company located in South Korea. The results of multilevel structural equation modeling showed that individuals’ perceptions of supportive leadership were positively related to their subsequent task performance, and that this relationship was mediated by team commitment. The relationship between individual-level perceptions of supportive leadership and organizational citizenship behavior (OCB) was mediated by job satisfaction and team commitment. On the other hand, team cooperation mediated the relationship between team-level perceptions of supportive leadership and OCB. These findings provide meaningful insights into multilevel mediation processes involving different levels of supportive leadership perceptions

Acute dystonia by droperidol during intravenous patient-controlled analgesia in young patients.

Patient-controlled analgesia (PCA) is an important means for postoperative analgesia with parenteral opioid. However, postoperative nausea and vomiting (PONV) remains a major problem with a PCA system. Droperidol is used in PCA to prevent PONV. Extrapyramidal reactions by droperidol are, however, occasionally induced. We describe two cases of severe extrapyramidal hypertonic syndrome with an intravenous administration of droperidol in PCA in young patients, following orthopedic surgery