Graduate employment prediction with bias

The failure of landing a job for college students could cause serious social consequences such as drunkenness and suicide. In addition to academic performance, unconscious biases can become one key obstacle for hunting jobs for graduating students. Thus, it is necessary to understand these unconscious biases so that we can help these students at an early stage with more personalized intervention. In this paper, we develop a framework, i.e., MAYA (Multi-mAjor emploYment stAtus) to predict students’ employment status while considering biases. The framework consists of four major components. Firstly, we solve the heterogeneity of student courses by embedding academic performance into a unified space. Then, we apply a generative adversarial network (GAN) to overcome the class imbalance problem. Thirdly, we adopt Long Short-Term Memory (LSTM) with a novel dropout mechanism to comprehensively capture sequential information among semesters. Finally, we design a bias-based regularization to capture the job market biases. We conduct extensive experiments on a large-scale educational dataset and the results demonstrate the effectiveness of our prediction framework. Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Feng Xia” is provided in this record*

Graduate Employment Prediction with Bias

The failure of landing a job for college students could cause serious social consequences such as drunkenness and suicide. In addition to academic performance, unconscious biases can become one key obstacle for hunting jobs for graduating students. Thus, it is necessary to understand these unconscious biases so that we can help these students at an early stage with more personalized intervention. In this paper, we develop a framework, i.e., MAYA (Multi-mAjor emploYment stAtus) to predict students' employment status while considering biases. The framework consists of four major components. Firstly, we solve the heterogeneity of student courses by embedding academic performance into a unified space. Then, we apply a generative adversarial network (GAN) to overcome the class imbalance problem. Thirdly, we adopt Long Short-Term Memory (LSTM) with a novel dropout mechanism to comprehensively capture sequential information among semesters. Finally, we design a bias-based regularization to capture the job market biases. We conduct extensive experiments on a large-scale educational dataset and the results demonstrate the effectiveness of our prediction framework

β-1,3-Glucan-Induced Host Phospholipase D Activation Is Involved in Aspergillus fumigatus Internalization into Type II Human Pneumocyte A549 Cells

The internalization of Aspergillus fumigatus into lung epithelial cells is a process that depends on host cell actin dynamics. The host membrane phosphatidylcholine cleavage driven by phospholipase D (PLD) is closely related to cellular actin dynamics. However, little is known about the impact of PLD on A. fumigatus internalization into lung epithelial cells. Here, we report that once germinated, A. fumigatus conidia were able to stimulate host PLD activity and internalize more efficiently in A549 cells without altering PLD expression. The internalization of A. fumigatus in A549 cells was suppressed by the downregulation of host cell PLD using chemical inhibitors or siRNA interference. The heat-killed swollen conidia, but not the resting conidia, were able to activate host PLD. Further, β-1,3-glucan, the core component of the conidial cell wall, stimulated host PLD activity. This PLD activation and conidia internalization were inhibited by anti-dectin-1 antibody. Indeed, dectin-1, a β-1,3-glucan receptor, was expressed in A549 cells, and its expression profile was not altered by conidial stimulation. Finally, host cell PLD1 and PLD2 accompanied A. fumigatus conidia during internalization. Our data indicate that host cell PLD activity induced by β-1,3-glucan on the surface of germinated conidia is important for the efficient internalization of A. fumigatus into A549 lung epithelial cells

Polyamine Oxidases Play Various Roles in Plant Development and Abiotic Stress Tolerance

Polyamines not only play roles in plant growth and development, but also adapt to environmental stresses. Polyamines can be oxidized by copper-containing diamine oxidases (CuAOs) and flavin-containing polyamine oxidases (PAOs). Two types of PAOs exist in the plant kingdom; one type catalyzes the back conversion (BC-type) pathway and the other catalyzes the terminal catabolism (TC-type) pathway. The catabolic features and biological functions of plant PAOs have been investigated in various plants in the past years. In this review, we focus on the advance of PAO studies in rice, Arabidopsis, and tomato, and other plant species.</jats:p

Polyamine Oxidases Play Various Roles in Plant Development and Abiotic Stress Tolerance

Polyamines not only play roles in plant growth and development, but also adapt to environmental stresses. Polyamines can be oxidized by copper-containing diamine oxidases (CuAOs) and flavin-containing polyamine oxidases (PAOs). Two types of PAOs exist in the plant kingdom; one type catalyzes the back conversion (BC-type) pathway and the other catalyzes the terminal catabolism (TC-type) pathway. The catabolic features and biological functions of plant PAOs have been investigated in various plants in the past years. In this review, we focus on the advance of PAO studies in rice, Arabidopsis, and tomato, and other plant species

Gender differences in the effects of perceived control on thermal response during summer

Perceived control is considered one of the influencing factors that affect the thermal satisfaction and comfort of indoor occupants. In order to explore the relationship between human gender in thermal response and perceived control and conduct in-depth research, field research was conducted on 1186 occupants in a college dormitory in Jiaozuo (the cold region of China). The perceived control vote was divided into four scales from “ no control ” to “ complete control ” . Through collation and analysis of the data obtained, we found that with improved perceived control, females ’ discomfort is significantly reduced, which is lower than males’. Therefore, there are significant gender differences in the impact of perceived control on the thermal response, which can be explained by individual differences in physiological regulation. Similarly, there are body type differences in perceived control. This research can provide support for the adaptive model and provide a new perspective for further research on individual differences in adaptive psychological adjustment