An ab initio Molecular Orbital Study of the Insertions of Difluorocarbene into Substituted Ethenes

Ab initio MO calculations predict the activation energies for the insertions of difluorocarbene into substituted ethenes C2H3X (X = F, Cl, Me) to be 61,68 and 52 kJ mol-1, respectively; these results indicate that the monosubstitution on the ethene has no significant effects on the activation energy of the reaction

Fostering creativity from an emotional perspective: Do teachers recognise and handle students’ emotions?

Emotions have a significant effect on the processes of designing and creative thinking. In an educational context, some emotions may even be detrimental to creativity. To further explore the link between creativity and emotion, a series of interviews were conducted with design and technology (D&T) teachers in Singapore, Hong Kong and Beijing concerning their experiences of working with students on design projects. The intent was to investigate how these teachers understood and managed their students’ emotions while teaching creative design skills. Some teachers indicated that they understood their students’ emotions through observing their behaviour, connecting with them by synchronising emotions or by evaluating student performance. The teachers also reported using various other methods to handle their students’ emotions. This study highlights the importance of equipping D&T teachers with skills for awareness and regulation of emotions so that they can better enable students to cultivate creativity in the design process

Accurate Modeling of the Effects of Fringing Area Interface Traps on Scanning Capacitance Microscopy Measurement

Scanning capacitance microscopy (SCM) is a dopant profile extraction tool with nanometre spatial resolution. While it is based on the high-frequency MOS capacitor theory, there are crucial second-order effects which make the extraction of dopant profile from SCM data a challenging task. Due to small size of the SCM probe, the trapped charges in the interface traps at the oxide-silicon dioxide interface surrounding the probe significantly affect the measured SCM data through the fringing electric field created by the trapped charges. In this paper, we present numerical simulation results to investigate the nature of SCM dC/dV data in the presence of interface traps. The simulation takes into consideration the traps response to the ac signal used to measure dC/dV as well as the fringing field of the trapped charge surrounding the probe tip. In the study, we present an error estimation of experimental SCM dopant concentration extraction when the interface traps and fringing field are ignored. The trap distribution in a typical SCM sample is also investigated

An Unifying Replacement Approach for Caching Systems

A cache replacement algorithm called probability based replacement (PBR) is proposed in this paper. The algorithm makes replacement decision based on the byte access probabilities of documents. This concept can be applied to both small conventional web documents and large video documents. The performance of PBR algorithm is studied by both analysis and simulation. By comparing cache hit probability, hit rate and average time spent in three systems, it is shown that the proposed algorithm outperforms the commonly used LRU and LFU algorithms. Simulation results show that, when large video documents are considered, the PBR algorithm provides up to 120% improvement in cache hit rate when comparing to that of conventional algorithms. The uniqueness of this work is that, unlike previous studies that propose different solutions for different types of documents separately, the proposed PBR algorithm provides a simple and unified approach to serve different types of documents in a single system

The VIX index under scrutiny of machine learning techniques and neural networks

The CBOE Volatility Index, known by its ticker symbol VIX, is a popular measure of the market's expected volatility on the SP 500 Index, calculated and published by the Chicago Board Options Exchange (CBOE). It is also often referred to as the fear index or the fear gauge. The current VIX index value quotes the expected annualized change in the SP 500 index over the following 30 days, based on options-based theory and current options-market data. Despite its theoretical foundation in option price theory, CBOE's Volatility Index is prone to inadvertent and deliberate errors because it is weighted average of out-of-the-money calls and puts which could be illiquid. Many claims of market manipulation have been brought up against VIX in recent years. This paper discusses several approaches to replicate the VIX index as well as VIX futures by using a subset of relevant options as well as neural networks that are trained to automatically learn the underlying formula. Using subset selection approaches on top of the original CBOE methodology, as well as building machine learning and neural network models including Random Forests, Support Vector Machines, feed-forward neural networks, and long short-term memory (LSTM) models, we will show that a small number of options is sufficient to replicate the VIX index. Once we are able to actually replicate the VIX using a small number of SP options we will be able to exploit potential arbitrage opportunities between the VIX index and its underlying derivatives. The results are supposed to help investors to better understand the options market, and more importantly, to give guidance to the US regulators and CBOE that have been investigating those manipulation claims for several years

A Study Of The National Aftercare Programme.

This study of the Aftercare Programme is a follow-up of an earlier study of official treatment and rehabilitation programmes for institutionalised drug dependents. The aims of this investigation were to provide an understanding of the aftercare programme and its relation to overall treatment and its rehabilitation efforts; to provide a description of the programme delivery process and analysis of the organizational aspects of the programme as perceived by programme officers

Genome sequence and genetic linkage analysis of Shiitake mushroom _Lentinula edodes_

_Lentinula edodes_ (Shiitake/Xianggu) is an important cultivated mushroom. Understanding the genomics and functional genomics of _L. edodes_ allows us to improve its cultivation and quality. Genome sequence is a key to develop molecular genetic markers for breeding and genetic manipulation. We sequenced the genome of _L. edodes_ monokaryon L54A using Roche 454 and ABI SOLiD genome sequencing. Sequencing reads of about 1400Mb were de novo assembled into a 40.2 Mb genome sequence. We compiled the genome sequence into a searchable database with which we have been annotating the genes and analyzing the metabolic pathways. In addition, we have been using many molecular techniques to analyze genes differentially expressed during development. Gene ortholog groups of _L. edodes_ genome sequence compared across genomes of several fungi including mushrooms identified gene families unique to mushroom-forming fungi. We used a mapping population of haploid basidiospores of dikaryon L54 for genetic linkage analysis. High-quality variations such as single nucleotide polymorphisms, insertions, and deletions of the mapping population formed a high-density genetic linkage map. We compared the linkage map to the _L. edodes_ L54A genome sequence and located selected quantitative trait loci. The Shiitake community will benefit from these resources for genetic studies and breeding.
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