Leaving Parental Homes In Canada: An Examination Of Gender, Family And Culture

This dissertation first explores a theoretical synthesis for the home-leaving of young adults in Canada. It proposes that home-leaving decisions are made at the family level, instead of at the individual level. While young adults may base their considerations concerning their living arrangements primarily on their own self-interest, parents are more likely to consider not only their own interests but also the best interests of their children. Young adults from social groups with different levels of familism will also have different patterns of home-leaving.;The analysis involves the life table and the proportional hazards models, as well as logistic regression, using data from the 1990 General Social Survey of Canada. After identifying as many covariates as possible as of the time of the event (home-leaving), this research found that gender, family structure, culture, and financial considerations are important predictors of home-leaving. While women still leave home earlier than men, their reasons for leaving home are becoming quite similar to those of men in recent cohorts. Children from non-traditional, non-intact families are likely to leave home earlier than other children. On the other hand, children from more traditional ethnic and religious groups tend to leave home later. Young adults, especially young men are more likely to live apart from parents if they have achieved financial independence.;This research also points to several data needs for the study of home-leaving in Canada. First, more information concerning young adults, their parents and the family structure is needed as of the time of young adults\u27 home-leaving. Second, data must allow the linkage between this information and young adults\u27 pathways for exiting parental homes. Third, community level variables need to be included in data collection

Traveling wave phenomena in a nonlocal dispersal predator-prey system with the Beddington-DeAngelis functional response and harvesting

This paper is devoted to studying the existence and nonexistence of traveling wave solution for a nonlocal dispersal delayed predator-prey system with the Beddington-DeAngelis functional response and harvesting. By constructing the suitable upper-lower solutions and applying Schauder\u27s fixed point theorem, we show that there exists a positive constant c∗ such that the system possesses a traveling wave solution for any given c\u3ec∗. Moreover, the asymptotic behavior of traveling wave solution at infinity is obtained by the contracting rectangles method. The existence of traveling wave solution for c=c∗ is established by means of Corduneanu\u27s theorem. The nonexistence of traveling wave solution in the case of

G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification

Pathological glomerulus classification plays a key role in the diagnosis of nephropathy. As the difference between different subcategories is subtle, doctors often refer to slides from different staining methods to make decisions. However, creating correspondence across various stains is labor-intensive, bringing major difficulties in collecting data and training a vision-based algorithm to assist nephropathy diagnosis. This paper provides an alternative solution for integrating multi-stained visual cues for glomerulus classification. Our approach, named generator-to-classifier (G2C), is a two-stage framework. Given an input image from a specified stain, several generators are first applied to estimate its appearances in other staining methods, and a classifier follows to combine visual cues from different stains for prediction (whether it is pathological, or which type of pathology it has). We optimize these two stages in a joint manner. To provide a reasonable initialization, we pre-train the generators in an unlabeled reference set under an unpaired image-to-image translation task, and then fine-tune them together with the classifier. We conduct experiments on a glomerulus type classification dataset collected by ourselves (there are no publicly available datasets for this purpose). Although joint optimization slightly harms the authenticity of the generated patches, it boosts classification performance, suggesting more effective visual cues are extracted in an automatic way. We also transfer our model to a public dataset for breast cancer classification, and outperform the state-of-the-arts significantly.Comment: Accepted by AAAI 201

Intergenerational Test Generation for Natural Language Processing Applications

The development of modern NLP applications often relies on various benchmark datasets containing plenty of manually labeled tests to evaluate performance. While constructing datasets often costs many resources, the performance on the held-out data may not properly reflect their capability in real-world application scenarios and thus cause tremendous misunderstanding and monetary loss. To alleviate this problem, in this paper, we propose an automated test generation method for detecting erroneous behaviors of various NLP applications. Our method is designed based on the sentence parsing process of classic linguistics, and thus it is capable of assembling basic grammatical elements and adjuncts into a grammatically correct test with proper oracle information. We implement this method into NLPLego, which is designed to fully exploit the potential of seed sentences to automate the test generation. NLPLego disassembles the seed sentence into the template and adjuncts and then generates new sentences by assembling context-appropriate adjuncts with the template in a specific order. Unlike the taskspecific methods, the tests generated by NLPLego have derivation relations and different degrees of variation, which makes constructing appropriate metamorphic relations easier. Thus, NLPLego is general, meaning it can meet the testing requirements of various NLP applications. To validate NLPLego, we experiment with three common NLP tasks, identifying failures in four state-of-art models. Given seed tests from SQuAD 2.0, SST, and QQP, NLPLego successfully detects 1,732, 5301, and 261,879 incorrect behaviors with around 95.7% precision in three tasks, respectively

Protective effect of astragalus injection against myocardial injury in septic young rats via inhibition of JAK/STAT signal pathway and regulation of inflammation

Purpose: To investigate the protective effect of astragalus injection against myocardial injury in septic young rats, and the underlying mechanism of action. Methods: Seventy-two healthy Sprague Dawley (SD) rats were randomly selected and used to establish a young rat model of sepsis. The young rats were randomly divided into 3 groups: sham, model and astragalus injection groups. Each group had 24 young rats. Serum cardiac troponin I (cTnI), IL-10, IL-6, JAK2 and STAT3 were measured after op. Results: Compared with sham group, serum cTnI level in the model group was significantly higher, while serum cTnI level of the drug group was significantly lower than that of the model group (p < 0.05). Compared with model group, the level of IL-10 in the myocardial tissue of the drug group was significantly elevated, while IL-6 level was lower (p < 0.05). Relative to sham rats, myocardial JAK2 and STAT3 protein levels in model rats were high. However, myocardial JAK2 and STAT3 proteins in the drug-treated rats were significantly downregulated, relative to model rats (p < 0.05). Conclusion: Astragalus injection upregulates IL-10 and IL-6 in rats by inhibiting the activation of JAK/STAT signal pathway, and via maintenance of pro-inflammation/anti-inflammation balance. Thus, astragalus exerts protective effect against myocardial injury in sepsis, and can potentially be developed for use as such in clinical practice. Keywords: Astragalus injection, JAK/STAT signal pathway, Pro-inflammatory/anti-inflammatory imbalance, Sepsis, Myocardial injur

LncRNA AK054921 and AK128652 are potential serum biomarkers and predictors of patient survival with alcoholic cirrhosis

Background: Alcoholic liver disease (ALD) is one of the leading causes of chronic liver disease. Recent studies have demonstrated the roles of long noncoding RNAs (lncRNAs) in the pathogenesis of several disease processes. However, the roles of lncRNAs in patients with ALD remain unexplored. Methods: Global profiling for human lncRNAs from peripheral blood RNA was performed in a well characterized cohort of healthy controls (HC, n=4), excessive drinkers without liver diseases (ED, n=4), and those with alcoholic cirrhosis with different severities (AC, n=12). The expression of unique lncRNA signatures were validated in a separate cohort of HC (n=17), ED (n=19), AC (n=48), and human liver tissues with ALD (n=19). Results: Detailed analysis of plasma lncRNAs in AC subjects with different severities compared to HC identified 244 commonly up-regulated lncRNAs and 181 commonly down-regulated lncRNAs. We further validated top 20 most differentially up- and down-regulated lncRNAs in ED and AC as compared to HC and also determined the expression of selected lncRNAs in human liver tissues with or without AC. Among those lncRNAs, AK128652 and AK054921 were two of the most abundantly expressed lncRNAs in normal human plasma and liver, and their levels were significantly elevated in AC. The prognostic significance of AK128652 and AK054921 was determined in 48 subjects with AC; who were prospectively followed for 520 days. The expression of AK128652 and AK054921 was inversely associated with survival in patients with AC. Conclusions: LncRNAs AK054921 and AK128652 are potential biomarkers to predict the progression to ALD in those with excessive alcohol consumption and are predictors of survival with patients with alcoholic cirrhosis