Chromosome mapping of dragline silk genes in the genomes of widow spiders (araneae, theridiidae)

With its incredible strength and toughness, spider dragline silk is widely lauded for its impressive material properties. Dragline silk is composed of two structural proteins, MaSp1 and MaSp2, which are encoded by members of the spidroin gene family. While previous studies have characterized the genes that encode the constituent proteins of spider silks, nothing is known about the physical location of these genes. We determined karyotypes and sex chromosome organization for the widow spiders, Latrodectus hesperus and L. geometricus (Araneae, Theridiidae). We then used fluorescence in situ hybridization to map the genomic locations of the genes for the silk proteins that compose the remarkable spider dragline. These genes included three loci for the MaSp1 protein and the single locus for the MaSp2 protein. In addition, we mapped a MaSp1 pseudogene. All the MaSp1 gene copies and pseudogene localized to a single chromosomal region while MaSp2 was located on a different chromosome of L. hesperus. Using probes derived from L. hesperus, we comparatively mapped all three MaSp1 loci to a single region of a L. geometricus chromosome. As with L. hesperus, MaSp2 was found on a separate L. geometricus chromosome, thus again unlinked to the MaSp1 loci. These results indicate orthology of the corresponding chromosomal regions in the two widow genomes. Moreover, the occurrence of multiple MaSp1 loci in a conserved gene cluster across species suggests that MaSp1 proliferated by tandem duplication in a common ancestor of L. geometricus and L. hesperus. Unequal crossover events during recombination could have given rise to the gene copies and could also maintain sequence similarity among gene copies over time. Further comparative mapping with taxa of increasing divergence from Latrodectus will pinpoint when the MaSp1 duplication events occurred and the phylogenetic distribution of silk gene linkage patterns. © 2010 Zhao et al

Residential Energy Consumption in Urban China

Residential energy consumption (REC) is the second largest energy use category (10%) in China and urban residents account for most of the REC. Understanding the underlying drivers of variations of urban REC thus helps to identify challenges and opportunities and provide advices for future policy measures. This paper applies the logarithmic mean Divisia index (LMDI) to a decomposition of China’s urban REC during the period of 1998-2007 at disaggregated product/activity level using data collected from a wide range of sources. Our results have shown an extensive structure change towards a more energy-intensive household consumption structure as well as an intensive structure change towards high-quality and cleaner energy such as electricity, oil, and natural gas, which reflects a changing life style and consumption mode in pursuit of a higher level of comfort, convenience and environmental protection. We have also found that China’s price reforms in the energy sector have contributed to a reduction of REC while scale factors including increased urban population and income levels have played a key role in the rapid growth of REC. We suggest that further deregulation in energy prices and regulatory as well as voluntary energy efficiency and conservation policies in the residential sector should be promoted.Residential Energy Consumption, Index Decomposition Analysis (IDA), China, Consumer/Household Economics, Resource /Energy Economics and Policy, Q32, Q43,

Bridging Theory and Practice in Private Higher Education: Pedagogical Innovations for the Digital Age

With the application of big data in the information age, the popularization of artificial intelligence and the coming of the network society, the traditional university education model has been severely impacted and challenged. It is an inevitable trend for higher education to adapt to the new social development reality and make corresponding adjustment and reform. Traditional university education pays attention to the imparts of theoretical knowledge and the cultivation of practical ability, but in the information age, students can get rich information and knowledge through the Internet, thus weakening the monopoly of traditional education. In addition, the popularity of artificial intelligence technology also means that some traditional teaching activities can be replaced by automation and intelligence, and the value chain of traditional education has been reshaped. The rise of the network society has also posed new challenges to the traditional university education model. The network society is characterized by a high degree of information sharing and exchange, and students can access various online educational resources and learning opportunities through the network platform. Therefore, traditional university education needs to find a new positioning and role, pay more attention to cultivating innovative ability, practical ability and teamwork ability, and provide students with more competitive comprehensive ability. Faced with these challenges, higher education must make corresponding adjustments and changes. The article carries out relevant research and puts forward specific countermeasures, mainly to update the educational concept, change the educational mode, and focus on cultivating students’ innovative thinking and problem-solving ability. It is necessary to develop diversified educational resources, meet social needs, strengthen cooperation with industries and enterprises, and provide professional education that matches market demand. At the same time, it is also necessary to actively develop online and distance education, make full use of online platforms and technological means, and provide flexible and diverse learning opportunities

Spin transport and magnetoresistance in magnetic thin films with inversion broken crystals and multi-layers

This thesis firstly investigates spin-orbit torques (SOTs) generated by microwave current and detected by ferromagnetic resonance (FMR) spectroscopy in a uniform ferromagnetic system, namely NiMnSb, a half-Heusler ferromagnet with broken inversion symmetry at room temperature. The spin-orbit coupling (SOC) and the noncentrosymmetric structure of the epitaxial NiMnSb allow microwave current to induce oscillating SOTs on the magnetisation, and by analysing the measured FMR lineshape, the direction and magnitude of the effective spin-orbit fields (SOFs) are determined to characterise the SOTs. Furthermore, the observed current-induced SOFs have the symmetries of both Dresselhaus and Rashba SOC. The second part of this thesis explores the temperature-dependent behaviour of the current-induced SOFs in NiMnSb from 10 K to room temperature. We found that both Dresselhaus and Rashba types of SOFs are substantially enhanced at low temperature. This work is the first reported temperature-dependent SOFs in epitaxial NiMnSb system which provides more insights into the underlying mechanism that governs the SOFs in the noncentrosymmetric ferromagnets. Finally, the nonlinear magnetoresistance (MR) effect – unidirectional magnetoresistance (UMR) has been studied in CoFeB/Pt bilayer and epitaxial NiMnSb. In the CoFeB/Pt system, the close correspondence between the asymmetry in resistance and reduction in magnetisation confirmed by the current-induced spin-torque FMR (CI-FMR) measurements demonstrate that observed MR change is due to the creation or annihilation of magnons through spin-flip process and GHz magnetisation excitation by spin-torque effect. Motivated by the experimental approach established in the UMR study of CoFeB/Pt bilayer system, we investigate the resistance asymmetry in NiMnSb extracted from the non-resonating background voltage. The observed resistance asymmetry scales linearly with current density and has a crystallographic dependence. We interpret this resistance asymmetry in NiMnSb as the relative orientation between the magnetisation and the current-induced SOFs

Object Tracking with Multiple Instance Learning and Gaussian Mixture Model

Recently, Multiple Instance Learning (MIL) technique has been introduced for object tracking\linebreak applications, which has shown its good performance to handle drifting problem. While some instances in positive bags not only contain objects, but also contain the background, it is not reliable to simply assume that each feature of instances in positive bags obeys a single Gaussian distribution. In this paper, a tracker based on online multiple instance boosting has been developed, which employs Gaussian Mixture Model (GMM) and single Gaussian distribution respectively to model features of instances in positive and negative bags. The differences between samples and the model are integrated into the process of updating the parameters for GMM. With the Haar-like features extracted from the bags, a set of weak classifiers are trained to construct a strong classifier, which is used to track the object location at a new frame. And the classifier can be updated online frame by frame. Experimental results have shown that our tracker is more stable and efficient when dealing with the illumination, rotation, pose and appearance changes