Facial Expression Recognition Based on SVM in E-learning

AbstractFacial expression is one of the most powerful channels of nonverbal communication which contains plenty of affective information. Recognition of facial expression and sending them back to the teacher is potentially helpful in E-learning. In this paper, we differentiate between person-relevant and person-irrelevant situations. Our goal is to extract powerful features used for facial expression recognition system in real-time and person-irrelevant situation. Previous work suggests that both facial shape features and appearance features could be used to recognize facial expressions. The first type is shape features calculated from positions on a face. The second type is a set of multi-scale and multi-orientation Gabor wavelet coefficients. The classifier is based on Support Vector Machines (SVM) and our expriments cover both person-relevant and person-irrelevant situations. The result shows that in person-irrelevant situation, using facial shape features outperforms using Gabor wavelet and it is faster. Furthermore, the radial basis function of SVM is more suitable for person-associated situation and the linear function describes person-irrelevant problems better

The Role of a transcription factor in regulating rice response to drought stress

The current water shortage is a major concern in regard to our global climate change crisis. A decrease in the availability of water will have direct effects on the development of plants. Some crops, such as Oryza sativa, or commonly known as rice, requires an abundant amount of water for adequate growth. With the water shortage crisis, it will become extremely difficult to harvest such crops to meet the world’s food demand. However, many plants have evolved mechanisms for overcoming and tolerating stresses such as drought. My research focuses on studying the proteins involved with these mechanisms. The WRKY superfamily is a family of transcription factors that up or down-regulate pathways in response to biotic and abiotic stresses in plants. We propose and hypothesize that OsWRKY70 plays a role in the abiotic stress of drought in rice. To identify the physiological role of this gene, we studied the phenotype of OsWRKY70 knockout mutants using an insertional transposon in comparison to its wildtype counterparts. This project aims to study the proteins involved with drought resistance in rice, which will pave the way for the production of genetically engineered crops that will be better at conserving water

Wetting and Drying of Colloidal Droplets: Physics and Pattern Formation

When a colloidal droplet is deposited on a solid substrate at ambient condition, it will experience the processes of wetting and drying spontaneously. These ostensibly simple and ubiquitous processes involve numerous physics: droplet spreading and wetting, three-phase contact line motion, flow fields inside droplets, and mass transportation within droplets during drying. Meanwhile, the continuous evaporation of liquid produces inter- and/or intra-molecular interactions among suspended materials and builds up the internal stress within droplets. After drying, interesting and complex desiccation patterns form in the dried droplets. These desiccation patterns are believed to have wide applications, e.g., medical diagnosis. However, many potential applications are limited by the current understanding of wetting and drying of colloidal droplets. This chapter focuses on the complex physics associated with these processes and the pattern formation in the dried colloidal droplets. Moreover, potential applications of these desiccation patterns and prospective works of wetting and drying of the colloidal droplets are outlined in this chapter

Genetically modifying Arabidopsis thaliana with a gene from Drought-tolerant Xerophyte Larrea tridentata (Creosote Bush)

L. tridentata, or desert creosote bush, is a xerophytic C3 plant native to the American Southwest, and is known to have evolutionarily developed sophisticated cellular mechanisms to deal with periods of intense abiotic stress. Particularly, complex signaling pathways in L. tridentata allow it to survive in periods of severe water deficiency. Through the findings of Zou et al. [5,6], LtWRKY21 synergistically works with abscisic acid (ABA) to transactivate both ABA-inducible HVA1 and HVA22 promoters. In addition, as ABA and gibberellic acid (GA) pathways are known to act antagonistically. Expectantly, the findings of Zou et al. suggest that LtWRKY21 activates ABA signaling pathways and represses GA signaling pathways [5,6]. More importantly, the LtWRKY21 transcription factor’s synergy with ABA is directly linked to some remarkable molecular adaptations of L. tridentata, some of which include stomatal closure to prevent transpiration, and slowing down gene expression to withstand dehydration [6]. To examine some of these mechanisms, the model plant Arabidopsis thaliana will be transformed with the LtWRKY21 coding region via Agrobacterium-mediated transformation. Successful transformants will be selected and the subsequent generation of transgenic plants will be assayed. Both phenotypic (screening) and genotypic (qRT-PCR and Southern Blot) examination will allow the function and expression patterns of LtWRKY21 to be elucidated under simulated drought. In order for LtWRKY21 to be successfully transformed into Arabidopsis, a tumor-inducing (Ti) plasmid must be engineered to carry LtWRKY21

Identification of a laccase Glac15 from Ganoderma lucidum 77002 and its application in bioethanol production

Background Laccases have potential applications in detoxification of lignocellulosic biomass after thermochemical pretreatment and production of value-added products or biofuels from renewable biomass. However, their application in large-scale industrial and environmental processes has been severely thwarted by the high cost of commercial laccases. Therefore, it is necessary to identify new laccases with lower cost but higher activity to detoxify lignocellulosic hydrolysates and better efficiency to produce biofuels such as bioethanol. Laccases from Ganoderma lucidum represent proper candidates in processing of lignocellulosic biomass. Results G. lucidum 77002 produces three laccase isoenzymes with a total laccase activity of 141.1 U/mL within 6 days when using wheat bran and peanut powder as energy sources in liquid culture medium. A new isoenzyme named Glac15 was identified, purified, and characterized. Glac15 possesses an optimum pH of 4.5 to 5.0 and a temperature range of 45°C to 55°C for the substrates tested. It was stable at pH values ranging from 5.0 to 7.0 and temperatures lower than 55°C, with more than 80% activity retained after incubation for 2 h. When used in bioethanol production process, 0.05 U/mL Glac15 removed 84% of the phenolic compounds in prehydrolysate, and the yeast biomass reached 11.81 (optimal density at 600 nm (OD600)), compared to no growth in the untreated one. Addition of Glac15 before cellulase hydrolysis had no significant effect on glucose recovery. However, ethanol yield were improved in samples treated with laccases compared to that in control samples. The final ethanol concentration of 9.74, 10.05, 10.11, and 10.81 g/L were obtained from samples containing only solid content, solid content treated with Glac15, solid content containing 50% prehydrolysate, and solid content containing 50% prehydrolysate treated with Glac15, respectively. Conclusions The G. lucidum laccase Glac15 has potentials in bioethanol production industry

Spatiotemporal variation of marsh vegetation productivity and climatic effects in Inner Mongolia, China

Net primary productivity (NPP) is a vital ecological index that reflects the ecological function and carbon sequestration of marsh ecosystem. Inner Mongolia has a large area of marshes, which play a crucial role in the East Asian carbon cycle. Under the influence of climate change, the NPP of Inner Mongolian marsh has changed significantly in the past few decades, but the spatiotemporal variation in marsh vegetation NPP and how climate change affects marsh NPP remain unclear. This study explores, for the first time, the spatiotemporal variation of marsh NPP and its response to climatic change in Inner Mongolia based on the MODIS-NPP and climate datasets. We find that the long-term average annual NPP of marsh is 339.85 g⋅C/m2 and the marsh NPP shows a significantly increasing trend (4.44 g⋅C/m2/a; p < 0.01) over Inner Mongolia during 2000–2020. Spatially, the most prominent increase trend of NPP is mainly distributed in the northeast of the region (Greater Khingan Mountains). The partial correlation results show that increasing autumn and summer precipitation can increase the NPP of marsh vegetation over Inner Mongolia. Regarding the temperature effects, we observe a strong asymmetric effect of maximum (Tmax) and minimum (Tmin) temperature on annual NPP. A high spring Tmax can markedly increase marsh NPP in Inner Mongolia, whereas a high Tmin can significantly reduce it. In contrast to spring temperature effects on NPP, a high summer Tmax can decrease NPP, whereas a high Tmin can increase it. Our results suggest different effects of seasonal climate conditions on marsh vegetation productivity and highlight the influences of day-time and night-time temperatures. This should be considered in simulating and predicting marsh carbon sequestration in global arid and semi-arid regions