Secondary School Chorus: Practical Implication of Praxial Music Education In Sight-Singing and Ear-Training

High school chorus students are often required to sing and memorize a diverse range of choral repertoire for performances. In the process of performance preparation, students learn many techniques including basic breathing, vocalization, blending of the voice, singing in pitch, keeping the rhythm, and following dynamics. Sight-singing is an essential technique for singers because music requires coordination of sight and singing through recognition of notation and rhythm. When a group of singers have a higher skill level of sight-singing, the learning of the song is easier and more efficient. The competency of sight-singing level of a group of singers allows more focus on the musical and expressive aspect of the piece during rehearsals. Consequently, singers become more “fluent” in music as they develop their sight-singing technique. Thus, sight-singing can be important for the secondary school chorus. The praxial approach of sight-singing and ear-training make a significant influence on the secondary school’s choral music for the musical independency. More widespread usage of praxial approach in sight-singing and ear-training would likely contribute to students’ enjoyment in chorus program and expand opportunity of performance. A successful implementation of the research-based sight-singing and ear-training in secondary school chorus may help students become better musicians

Evaluating Feature Attribution Methods for Electrocardiogram

The performance of cardiac arrhythmia detection with electrocardiograms(ECGs) has been considerably improved since the introduction of deep learning models. In practice, the high performance alone is not sufficient and a proper explanation is also required. Recently, researchers have started adopting feature attribution methods to address this requirement, but it has been unclear which of the methods are appropriate for ECG. In this work, we identify and customize three evaluation metrics for feature attribution methods based on the characteristics of ECG: localization score, pointing game, and degradation score. Using the three evaluation metrics, we evaluate and analyze eleven widely-used feature attribution methods. We find that some of the feature attribution methods are much more adequate for explaining ECG, where Grad-CAM outperforms the second-best method by a large margin.Comment: 5 pages, 3 figures. Code is available at https://github.com/SNU-DRL/Attribution-EC

Testing for family influences on obesity: The role of genetic nurture

A large literature has documented strong positive correlations among siblings in health, including body mass index (BMI) and obesity. This paper tests whether that is explained by a specific type of peer effect in obesity: genetic nurture. Specifically, we test whether an individual’s weight is affected by the genes of their sibling, controlling for the individual’s own genes. Using genetic data in Add Health, we find no credible evidence that an individual’s BMI is affected by the polygenic risk score for BMI of their full sibling when controlling for the individual’s own polygenic risk score for BMI. Thus, we find no evidence that the positive correlations in BMI between siblings are attributable to genetic nurture within families.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149721/1/hec3889.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149721/2/hec3889_am.pd

Association of Contraceptive Knowledge, Sexual Double Standard and Contraceptive Self-Efficacy among Unmarried Women in Their 30s and 40s

PURPOSE: To determine association of contraceptive knowledge, sexual double standard, and contraceptive self-efficacy among unmarried women in their 30s and 40s. METHODS: With a survey design, data were collected from 119 unmarried women in their 30s and 40s in G city of Korea from September 2017 to March 2018. Data were analyzed by descriptive statistics, independent t-test, one-way ANOVA, Scheffé test, Pearson's correlation coefficients, and stepwise multiple regression. RESULTS: Contraceptive knowledge, sexual double standard, and contraceptive self-efficacy scores of participants were 8.97±2.22, 18.54±5.57, and 45.84 ± 6.90, respectively. Contraceptive self-efficacy was negatively correlated with sexual double standard. Factors influencing contraceptive self-efficacy were sexual double standard (β =−.26, p=.003), existence of boyfriend (β=.25, p=.004), and contraceptive education need for adults (β=.17, p=.044). They explained 19% of contraceptive self-efficacy of participants. CONCLUSION: To increase contraceptive self-efficacy of unmarried women in their 30s and 40s, lowering sexual double standard and developing customized contraceptive education according to age and knowledge level are needed. Research on factors related to contraceptive self-efficacy of unmarried women in their 30s and 40s from various regions are also needed in the future

Isotropic Representation Can Improve Dense Retrieval

The recent advancement in language representation modeling has broadly affected the design of dense retrieval models. In particular, many of the high-performing dense retrieval models evaluate representations of query and document using BERT, and subsequently apply a cosine-similarity based scoring to determine the relevance. BERT representations, however, are known to follow an anisotropic distribution of a narrow cone shape and such an anisotropic distribution can be undesirable for the cosine-similarity based scoring. In this work, we first show that BERT-based DR also follows an anisotropic distribution. To cope with the problem, we introduce unsupervised post-processing methods of Normalizing Flow and whitening, and develop token-wise method in addition to the sequence-wise method for applying the post-processing methods to the representations of dense retrieval models. We show that the proposed methods can effectively enhance the representations to be isotropic, then we perform experiments with ColBERT and RepBERT to show that the performance (NDCG at 10) of document re-ranking can be improved by 5.17\%$\sim$8.09\% for ColBERT and 6.88\%$\sim$22.81\% for RepBERT. To examine the potential of isotropic representation for improving the robustness of DR models, we investigate out-of-distribution tasks where the test dataset differs from the training dataset. The results show that isotropic representation can achieve a generally improved performance. For instance, when training dataset is MS-MARCO and test dataset is Robust04, isotropy post-processing can improve the baseline performance by up to 24.98\%. Furthermore, we show that an isotropic model trained with an out-of-distribution dataset can even outperform a baseline model trained with the in-distribution dataset.Comment: 9 pages, 4 figure

Effects of Sex Communication with Friends and Sexual Double Standard on Contraceptive Self-efficacy among University Students

PURPOSE: To determine the effect of sex communication with friends and sexual double standard on contraceptive self-efficacy among university students. METHODS: With a survey design, data were collected from 251 university students from three universities in G city from September 2016 to October 2016. Data were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and stepwise multiple regression. RESULTS: Sex communication with friends, sexual double standard, and contraceptive self-efficacy scores of participants were 58.82±8.78, 21.73±6.00, and 44.20±5.91, respectively. Sex communication with friends and sexual double standard were related to contraceptive self-efficacy. Sexual double standard, sex communication with friends, female, contraceptive education, and contraceptive experience explained 33% of contraceptive self-efficacy of participants. CONCLUSION: Sexual double standard and sex communication with friends were influencing factors of contraceptive self-efficacy. To improve contraceptive self-efficacy of university students, a program is needed to eliminate sexual double standard and improve sex communication with friends among university students in Korea

Chromosome-level genome assembly of Patagonian moray cod (Muraenolepis orangiensis) and immune deficiency of major histocompatibility complex (MHC) class II

The Patagonian moray cod, Muraenolepis orangiensis, belongs to the family Muraenolepididae and is the sole order of Gadiformes that inhabits the temperate and cold waters of the southern hemisphere. One of the features of the Gadiformes order is that they have a remarkably unique immune gene repertoire that influences innate and adaptive immunity, and they lack major histocompatibility complex (MHC) class II, invariant chains (CD74), and CD4 genes. In this study, a high-quality chromosome-level genome assembly was constructed, resulting in a final assembled genome of 893.75 Mb, with an N50 scaffold length of 30.07 Mb and the longest scaffold being 39.77 Mb. Twenty-five high-quality pseudochromosomes were assembled, and the complete BUSCO rate was 93.4%. A total of 34,553 genes were structurally annotated, and 27,691 genes were functionally annotated. Among the 10 primary genes involved in MHC class II, only two ERAP1 genes and one AIRE gene were identified through the genome study. Although no specific reason for the MHC class II deficiency has been identified, it has been shown that the toll-like receptors (TLRs), which are significant to the innate immune response, are significantly expanded in M. orangiensis. A total of 44 TLRs have been identified, with 32 TLR13 genes distributed evenly on six different pseudochromosomes. This study is the first to reveal the whole genome of a Muraenolepididae family and provides valuable insights into the potential rationale for the MHC class II deficiency in a Gadiformes fish species

Quickly Finding a Truss in a Haystack

The k-truss of a graph is a subgraph such that each edge is tightly connected to the remaining elements in the k-truss. The k-truss of a graph can also represent an important community in the graph. Finding the k-truss of a graph can be done in a polynomial amount of time, in contrast finding other subgraphs such as cliques. While there are numerous formulations and algorithms for finding the maximal k-truss of a graph, many of these tend to be computationally expensive and do not scale well. Many algorithms are iterative and use static graph triangle counting in each iteration of the graph. In this work we present a novel algorithm for finding both the k- truss of the graph (for a given k), as well as the maximal k-truss using a dynamic graph formulation. Our algorithm has two main benefits. 1) Unlike many algorithms that rerun the static graph triangle counting after the removal of nonconforming edges, we use a new dynamic graph formulation that only requires updating the edges affected by the removal. As our updates are local, we only do a fraction of the work compared to the other algorithms. 2) Our algorithm is extremely scalable and is able to concurrently detect deleted triangles in contrast to past sequential approaches. While our algorithm is architecture independent, we show a CUDA based implementation for NVIDIA GPUs. In numerous instances, our new algorithm is anywhere from 100X-10000X faster than the Graph Challenge benchmark. Furthermore, our algorithm shows significant speedups, in some cases over 70X, over a recently developed sequential and highly optimized algorithm