LiSum: Open Source Software License Summarization with Multi-Task Learning

Open source software (OSS) licenses regulate the conditions under which users can reuse, modify, and distribute the software legally. However, there exist various OSS licenses in the community, written in a formal language, which are typically long and complicated to understand. In this paper, we conducted a 661-participants online survey to investigate the perspectives and practices of developers towards OSS licenses. The user study revealed an indeed need for an automated tool to facilitate license understanding. Motivated by the user study and the fast growth of licenses in the community, we propose the first study towards automated license summarization. Specifically, we released the first high quality text summarization dataset and designed two tasks, i.e., license text summarization (LTS), aiming at generating a relatively short summary for an arbitrary license, and license term classification (LTC), focusing on the attitude inference towards a predefined set of key license terms (e.g., Distribute). Aiming at the two tasks, we present LiSum, a multi-task learning method to help developers overcome the obstacles of understanding OSS licenses. Comprehensive experiments demonstrated that the proposed jointly training objective boosted the performance on both tasks, surpassing state-of-the-art baselines with gains of at least 5 points w.r.t. F1 scores of four summarization metrics and achieving 95.13% micro average F1 score for classification simultaneously. We released all the datasets, the replication package, and the questionnaires for the community

Risk of uterine leiomyomata with menstrual and reproductive factors in premenopausal women: Korea nurses health study

Background Uterine leiomyomata (UL) are benign smooth muscle tumors that may cause significant morbidity in women of reproductive age. This study aimed to investigate the relationship of menstrual and reproductive factors with the risk of UL in premenopausal women. Methods This prospective study included 7,360 premenopausal women aged 22–48 years who were part of the Korea Nurses Health Study. Information on the menstrual cycle and reproductive history was assessed between 2014 and 2016, and self-reported cases of UL were obtained through 2021. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). Results During 32,072 person-years of follow-up, 447 incident cases of UL were reported. After adjusting for other risk factors, women with late age at menarche had a lower incidence of UL (≥ 16 vs. 12–13 years: HR 0.68; 95% CI 0.47–0.99; p for trend = 0.026). The risk of UL was inversely associated with current menstrual cycle length (≥ 40 or too irregular to estimate vs. 26–31 days: HR 0.40; 95% CI 0.24–0.66) and cycle length at ages 18–22 years (HR 0.45; 95% CI 0.31–0.67; p for trend < 0.001, each). Parous women had lower risk of UL than nulliparous women (HR 0.40; 95% CI 0.30–0.53) and women who were aged 29–30 years at first birth had a lower risk of UL than those who were aged ≤ 28 years at first birth (HR 0.58; 95% CI 0.34–0.98). There was no significant association of the number of births or breastfeeding with the risk of UL among parous women. Neither a history of infertility nor oral contraceptive use was associated with the risk of UL. Conclusions Our results suggest that age at menarche, menstrual cycle length, parity, and age at first birth are inversely associated with the risk of UL in premenopausal Korean women. Future studies are warranted to confirm the long-term effects of menstrual and reproductive factors on womens health.This research was supported by the National Institute of Health research project (2021-NI-015-02)

Dietary pattern and health-related quality of life among breast cancer survivors

Background There is limited evidence for the association between dietary pattern and quality of life among breast cancer survivors. We examined the association between dietary patterns and health-related quality of life (HRQoL) among Korean breast cancer survivors. Methods Our study included a total of 232 women, aged 21 to 79 years, who had been diagnosed with stage I to III breast cancer and who underwent breast cancer surgery at least 6 months prior to our baseline evaluation. We assessed HRQoL using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and the Quality of Life Questionnaire Breast Cancer Module 23 (QLQ-BR23). We conducted a factor analysis to identify the major dietary patterns and used a generalized linear model to obtain the least squares mean (LS mean) and 95% confidence interval (CI) for HRQoL according to the dietary pattern scores. Results We identified 2 major dietary patterns: the Healthy dietary pattern and the Western dietary pattern. We found that breast cancer survivors who had higher Healthy dietary pattern scores tended to have lower dyspnea scores but higher insomnia scores, compared to breast cancer survivors with lower Healthy dietary pattern scores. For dyspnea, the LS mean (95% CI) was 8.86 (5.05-15.52) in the bottom quartile and 2.87 (1.62-5.08) in the top quartile (p for trend = 0.005). This association was limited to survivors with stage I for dyspnea or survivors with stage II or III for insomnia. Conclusions Healthy dietary patterns were associated with better scores for dyspnea but worse scores for insomnia among breast cancer survivors. Other components of EORTC QLQ did not vary by dietary patterns overall, but they warrant further investigation for subgroups of breast cancer survivors.This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014R1A2A2A01007794). The funding body had no role in the design of the study, collection, analysis and interpretation of data, and manuscript writing

Association of lipid profile with obesity among breast cancer survivors: a cross-sectional study

Background The role of lipid metabolism in obesity and cancer manifestations cannot be underestimated, but whether alterations in lipid metabolism can manipulate the vasculature to promote obesity among breast cancer (BC) survivors is yet to be clearly understood. This study quantified plasma lipid and particle sizes using high-throughput proton (1H) nuclear magnetic resonance (NMR) and tested their associations with obesity among breast cancer (BC) survivors. Methods A total of 348 (225 premenopausal and 123 postmenopausal) BC survivors enrolled from five hospitals in Korea were included. We assessed thirty-four plasma lipid biomarkers using 1H NMR, and obesity status was defined as a body mass index (BMI) of 25 kg/m2 or greater. Generalized linear and logistic regression models were applied to estimate the least-square means of BMI (kg/m2) and odds ratio (OR)s of obesity, respectively, and the corresponding 95% confidence interval (CI)s across plasma lipid levels. Results Mean (SD) values of BMI was 23.3 (3.2) kg/m2 and 90 (25.9%) had BMI of ≥ 25 kg/m2. BMI levels increased with increasing total triglycerides (TG), TG in lipoproteins and very-low-density lipoprotein (VLDL) subfractions. However, BMI levels decreased with increasing tertiles of high-density lipoprotein (HDL)-cholesterol (C) and HDL particle size (HDL-p). Similar associations were observed in the logistic regression models. The increasing and decreasing BMI trends with TG and HDL profiles respectively were predominantly limited to premenopausal BC survivors. Conclusions Increasing levels of plasma total TG and TG in lipoproteins were associated with increasing levels of BMI among premenopausal BC survivors. High HDL-C levels and large HDL-p were inversely associated with obesity among premenopausal BC survivors. Due to the cross-sectional design of this study, longitudinal studies are necessary to examine the association between obesity and lipid profile among BC survivors.This research was supported by the Brain Pool Program supported through the National Research Foundation of Korea, funded by the Ministry of Science and ICT (2020H1D3A1A04081265). Also, the data collection and recruitment of this work were supported by the National Research Foundation of Korea Grant funded by the Korean government (MSIT) (No. 2014R1A2A2A01007794, 2019R1F1A1061017 and 2021R1F1A1062476). The funders had no role in the study design, data collection and analysis, or decision to prepare and publish the manuscript

PROVABGS: The Probabilistic Stellar Mass Function of the BGS One-Percent Survey

We present the probabilistic stellar mass function (pSMF) of galaxies in the DESI Bright Galaxy Survey (BGS), observed during the One-Percent Survey. The One-Percent Survey was one of DESI's survey validation programs conducted from April to May 2021, before the start of the main survey. It used the same target selection and similar observing strategy as the main survey and successfully observed the spectra and redshifts of 143,017 galaxies in the $r < 19.5$ magnitude-limited BGS Bright sample and 95,499 galaxies in the fainter surface brightness and color selected BGS Faint sample over $z < 0.6$. We derive pSMFs from posteriors of stellar mass, $M_*$, inferred from DESI photometry and spectroscopy using the Hahn et al. (2022a; arXiv:2202.01809) PRObabilistic Value-Added BGS (PROVABGS) Bayesian SED modeling framework. We use a hierarchical population inference framework that statistically and rigorously propagates the $M_*$ uncertainties. Furthermore, we include correction weights that account for the selection effects and incompleteness of the BGS observations. We present the redshift evolution of the pSMF in BGS as well as the pSMFs of star-forming and quiescent galaxies classified using average specific star formation rates from PROVABGS. Overall, the pSMFs show good agreement with previous stellar mass function measurements in the literature. Our pSMFs showcase the potential and statistical power of BGS, which in its main survey will observe >100$\times$ more galaxies. Moreover, we present the statistical framework for subsequent population statistics measurements using BGS, which will characterize the global galaxy population and scaling relations at low redshifts with unprecedented precision.Comment: 25 pages, 12 figures; data used to generate figures is available at https://doi.org/10.5281/zenodo.8018936; submitted to Ap

PROVABGS: The Probabilistic Stellar Mass Function of the BGS One-percent Survey

We present the probabilistic stellar mass function (pSMF) of galaxies in the DESI Bright Galaxy Survey (BGS), observed during the One-percent Survey. The One-percent Survey was one of DESI’s survey validation programs conducted from 2021 April to May, before the start of the main survey. It used the same target selection and similar observing strategy as the main survey and successfully observed the spectra and redshifts of 143,017 galaxies in the r 100 × more galaxies. Moreover, we present the statistical framework for subsequent population statistics measurements using BGS, which will characterize the global galaxy population and scaling relations at low redshifts with unprecedented precision

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Dietary Patterns Related to Triglyceride and High-Density Lipoprotein Cholesterol and the Incidence of Type 2 Diabetes in Korean Men and Women

We aimed to examine whether dietary patterns that explain the variation of triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio were associated with the incidence of type 2 diabetes in Korean adults. We included a total of 5097 adults without diabetes at baseline with a mean follow-up of 11.54 years. Usual diet was assessed by a validated food frequency questionnaire, and serum levels of TG and HDL-C were measured at baseline. We derived dietary pattern scores using 41 food groups as predictors and the TG/HDL-C ratio as a response variable in a stepwise linear regression. We calculated the odds ratio (OR) with the 95% confidence interval (CI) of type 2 diabetes according to pattern scores using multivariate logistic regression. A total of 1069 incident cases of type 2 diabetes were identified. A list of foods characterizing the dietary pattern differed by sex. Higher dietary pattern scores were associated with an increased risk of type 2 diabetes; ORs (95% CIs) comparing extreme quintiles were 1.53 (1.12&#8315;2.09; p for trend = 0.008) for men and 1.33 (0.95&#8315;1.86; p for trend = 0.011) for women. Our study suggests the evidence that dietary patterns associated with low levels of TG/HDL-C ratio may have the potential to reduce the burden of type 2 diabetes

Scene Changes Understanding Framework Based on Graph Convolutional Networks and Swin Transformer Blocks for Monitoring LCLU Using High-Resolution Remote Sensing Images

High-resolution remote sensing images with rich land surface structure can provide data support for accurately understanding more detailed change information of land cover and land use (LCLU) at different times. In this study, we present a novel scene change understanding framework for remote sensing which includes scene classification and change detection. To enhance the feature representation of images in scene classification, a robust label semantic relation learning (LSRL) network based on EfficientNet is presented for scene classification. It consists of a semantic relation learning module based on graph convolutional networks and a joint expression learning framework based on similarity. Since the bi-temporal remote sensing image pairs include spectral information in both temporal and spatial dimensions, land cover and land use change monitoring can be improved by using the relationship between different spatial and temporal locations. Therefore, a change detection method based on swin transformer blocks (STB-CD) is presented to obtain contextual relationships between targets. The experimental results on the LEVIR-CD, NWPU-RESISC45, and AID datasets demonstrate the superiority of LSRL and STB-CD over other state-of-the-art methods

Adsorptive removal of Ni and Cd from wastewater using a green longan hull adsorbent

The adsorptive removal of Ni 2+ and Cd 2+ at concentrations of approximately 50 mg L −1 in wastewater is investigated using an agricultural adsorbent, longan hull, and the adsorptive mechanism is characterized. The maximum adsorption capacity of approximately 4.19 mg g −1 Cd 2+ was obtained under the optimized conditions of room temperature, pH 5.0, and a solid-to-liquid ratio of 1:30 in approximately 15 min. For Ni 2+ , the maximum adsorption capacity of approximately 3.96 mg g −1 was obtained at pH 4.7 in approximately 20 min. The adsorption kinetics for both metal ions on the longan hull can be described by a pseudo second-order rate model and are well fitted to the Langmuir adsorption isotherm. The adsorption mechanism of the longan hull to Ni 2+ and Cd 2+ ions is shown to be a monolayer adsorption of metal ions onto the absorbent surface. Thereinto, the longan hull adsorbent contains N–H, C–H, C=O, and C=C functional groups that can form ligands when loaded with Ni 2+ and Cd 2+ , which reduces the fluorescence of the dried longan hull material