Cultural Rehabilitation: Hansen’s Disease, Gender and Disability in Korea

This essay explores how leprosy was used to enforce cultural inferiority, which resulted in the oppression of affected people in Korea. The literature shows that images of lepers as cannibals infiltrated family lives in the communities and made institutionalization inevitable. Contemporary cultural representations depict marriage between disabled men and nondisabled women as a symbolic bridge between the segregated space of lepers and the healthy. Such efforts reinforce the normative power of heterosexual marriage

Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks

In this review we summarize our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions

Parameterized Algorithms for Min-Max Multiway Cut and List Digraph Homomorphism

In this paper we design {\sf FPT}-algorithms for two parameterized problems. The first is \textsc{List Digraph Homomorphism}: given two digraphs $G$ and $H$ and a list of allowed vertices of $H$ for every vertex of $G$, the question is whether there exists a homomorphism from $G$ to $H$ respecting the list constraints. The second problem is a variant of \textsc{Multiway Cut}, namely \textsc{Min-Max Multiway Cut}: given a graph $G$, a non-negative integer $\ell$, and a set $T$ of $r$ terminals, the question is whether we can partition the vertices of $G$ into $r$ parts such that (a) each part contains one terminal and (b) there are at most $\ell$ edges with only one endpoint in this part. We parameterize \textsc{List Digraph Homomorphism} by the number $w$ of edges of $G$ that are mapped to non-loop edges of $H$ and we give a time $2^{O(\ell\cdot\log h+\ell^2\cdot \log \ell)}\cdot n^{4}\cdot \log n$ algorithm, where $h$ is the order of the host graph $H$. We also prove that \textsc{Min-Max Multiway Cut} can be solved in time $2^{O((\ell r)^2\log \ell r)}\cdot n^{4}\cdot \log n$. Our approach introduces a general problem, called {\sc List Allocation}, whose expressive power permits the design of parameterized reductions of both aforementioned problems to it. Then our results are based on an {\sf FPT}-algorithm for the {\sc List Allocation} problem that is designed using a suitable adaptation of the {\em randomized contractions} technique (introduced by [Chitnis, Cygan, Hajiaghayi, Pilipczuk, and Pilipczuk, FOCS 2012]).Comment: An extended abstract of this work will appear in the Proceedings of the 10th International Symposium on Parameterized and Exact Computation (IPEC), Patras, Greece, September 201

The Moderating Effect Of Long-Term Orientation On The Relationship Between Interfirm Power Asymmetry And Interfirm Contracts: The Cases Of Korea And USA

The purpose of this study is to enhance our understanding of the effects of LTO culture on the contractual relationship between exchange parties under conditions in which varying levels of asymmetrical power structures exist. This study attempt to determine the validity of projecting conclusions originating from studies conducted in low LTO cultures such as U.S. and Western Europe to contractual relationships in the high LTO cultures of Asia. Therefore, investigations into the influence of LTO may be helpful in understanding contractual relationships formed in countries with differing levels of long-term orientation. Survey research was conducted to collect data from manufacturers, Structural Equation Modeling was used to purify measurement scales, and Multiple Regression was conducted to test the hypotheses. The findings show that LTO companies tend to prefer “soft” contracts, although they enjoy a power advantage over their suppliers; whereas low LTO partners with asymmetrical power advantages prefer “hard” contracts with explicitly detailed written requirements

Depressive symptoms and sleep disturbances in Korean American women

The purpose of this study was to examine the relationship between depressive symptoms and sleep disturbances among Korean American women. Forty-nine women completed the Center for Epidemiologic Studies Depression Scale, the Pittsburgh Sleep Quality Index, and revised Acculturation Rating Scale for Mexican Americans-II. Overall, participants scored 12.56 (SD = 9.93) on the Center for Epidemiologic Studies Depression Scale, 5.31 (SD = 3.01) on the Pittsburgh Sleep Quality Index, and -2.27 (SD = 1.64) on the Acculturation Rating Scale for Mexican Americans-II. Approximately 29% of the women (n = 14) scored 16 or higher on the Center for Epidemiologic Studies Depression Scale indicating that they had elevated depressive symptoms, and 39% (n = 19) scored 6 or higher on the Pittsburgh Sleep Quality Index, which indicated that they had sleep disturbances. Results from the stepwise multiple regression, controlling for the degree of the women’s acculturation, indicated that sleep disturbances (β = .39, p = .004) were significantly positively related to depressive symptoms, F(2, 46) = 7.27, p = .002 and the model explained 24% of the variance in women’s depressive symptoms. When taking care of Korean American women who have elevated depressive symptoms, their sleep disturbances need to be assessed. Health practitioners need to assess for depressive symptoms in women with sleep disturbances

Tourism Industry Specialization, Overtourism, and Community Resilience: A Spatial Path Analysis Approach

Despite the positive and negative impacts of tourism, prior studies have rarely focused on addressing how each tourism sector differently affects community resilience, and which factor significantly influences their mixed relationships across communities. This study addresses previous limitations by exploring spatially heterogeneous mixed effects of tourism industry specialization on community resilience and identifying a key moderator that affects their mixed relationships. Geographically weighted regression combined with spatial path analysis was applied to case studies of 3,108 counties in the United States and 67 counties in Florida. The findings show that tourism industry specialization has spatially heterogeneous mixed effects on community resilience, and these effects are strongly affected by the degree of environmental pollution. Specifically, environmental pollution negatively affects the relationships between community resilience and (a) arts/entertainment/recreation tourism sectors in the United States and (b) accommodation/food service tourism sectors in Florida. Theoretical and practical implications of the findings are also discussed

Basic Enhancement Strategies When Using Bayesian Optimization for Hyperparameter Tuning of Deep Neural Networks

Compared to the traditional machine learning models, deep neural networks (DNN) are known to be highly sensitive to the choice of hyperparameters. While the required time and effort for manual tuning has been rapidly decreasing for the well developed and commonly used DNN architectures, undoubtedly DNN hyperparameter optimization will continue to be a major burden whenever a new DNN architecture needs to be designed, a new task needs to be solved, a new dataset needs to be addressed, or an existing DNN needs to be improved further. For hyperparameter optimization of general machine learning problems, numerous automated solutions have been developed where some of the most popular solutions are based on Bayesian Optimization (BO). In this work, we analyze four fundamental strategies for enhancing BO when it is used for DNN hyperparameter optimization. Specifically, diversification, early termination, parallelization, and cost function transformation are investigated. Based on the analysis, we provide a simple yet robust algorithm for DNN hyperparameter optimization - DEEP-BO (Diversified, Early-termination-Enabled, and Parallel Bayesian Optimization). When evaluated over six DNN benchmarks, DEEP-BO mostly outperformed well-known solutions including GP-Hedge, BOHB, and the speed-up variants that use Median Stopping Rule or Learning Curve Extrapolation. In fact, DEEP-BO consistently provided the top, or at least close to the top, performance over all the benchmark types that we have tested. This indicates that DEEP-BO is a robust solution compared to the existing solutions. The DEEP-BO code is publicly available at <uri>https://github.com/snu-adsl/DEEP-BO</uri>

A content analysis of social media posts among recreational cyclists: A gender perspective

Recreational cyclists are pertinent but rarely studied leisure and tourism segment. Recreational cycling has traditionally been considered as a ‘masculine stereotyped’ sport. The purpose of the research is to better understand a gendered consumer view of recreational cycling and to possibly promote recreational cycling to women and men in countries like South Africa with keen interests of recreational cycling in the form of sport tourism. This research employs a content analysis of social media posts on Facebook, Instagram and Twitter as a research method. Specifically, the gendered nature of recreational cycling is focused upon. In total, 2,504 posts from 1,598 unique authors from South Africa are analysed. As a result, this research shows that in the South African context male cyclists tend to like to attend the specialised event and race for their health and fitness while female cyclists seem to find more enjoyable and family-friendly (children focused) cycling. The results also confirm the paradox that women are generally presented in more family oriented roles, while men are typically shown as more independent in the media. Managerial implications and future research are also presented