Differentiable Display Photometric Stereo

Photometric stereo leverages variations in illumination conditions to reconstruct per-pixel surface normals. The concept of display photometric stereo, which employs a conventional monitor as an illumination source, has the potential to overcome limitations often encountered in bulky and difficult-to-use conventional setups. In this paper, we introduce Differentiable Display Photometric Stereo (DDPS), a method designed to achieve high-fidelity normal reconstruction using an off-the-shelf monitor and camera. DDPS addresses a critical yet often neglected challenge in photometric stereo: the optimization of display patterns for enhanced normal reconstruction. We present a differentiable framework that couples basis-illumination image formation with a photometric-stereo reconstruction method. This facilitates the learning of display patterns that leads to high-quality normal reconstruction through automatic differentiation. Addressing the synthetic-real domain gap inherent in end-to-end optimization, we propose the use of a real-world photometric-stereo training dataset composed of 3D-printed objects. Moreover, to reduce the ill-posed nature of photometric stereo, we exploit the linearly polarized light emitted from the monitor to optically separate diffuse and specular reflections in the captured images. We demonstrate that DDPS allows for learning display patterns optimized for a target configuration and is robust to initialization. We assess DDPS on 3D-printed objects with ground-truth normals and diverse real-world objects, validating that DDPS enables effective photometric-stereo reconstruction

Reliable Decision from Multiple Subtasks through Threshold Optimization: Content Moderation in the Wild

Social media platforms struggle to protect users from harmful content through content moderation. These platforms have recently leveraged machine learning models to cope with the vast amount of user-generated content daily. Since moderation policies vary depending on countries and types of products, it is common to train and deploy the models per policy. However, this approach is highly inefficient, especially when the policies change, requiring dataset re-labeling and model re-training on the shifted data distribution. To alleviate this cost inefficiency, social media platforms often employ third-party content moderation services that provide prediction scores of multiple subtasks, such as predicting the existence of underage personnel, rude gestures, or weapons, instead of directly providing final moderation decisions. However, making a reliable automated moderation decision from the prediction scores of the multiple subtasks for a specific target policy has not been widely explored yet. In this study, we formulate real-world scenarios of content moderation and introduce a simple yet effective threshold optimization method that searches the optimal thresholds of the multiple subtasks to make a reliable moderation decision in a cost-effective way. Extensive experiments demonstrate that our approach shows better performance in content moderation compared to existing threshold optimization methods and heuristics.Comment: WSDM2023 (Oral Presentation

CardioGuard: A Brassiere-based Reliable ECG Monitoring Sensor System for Supporting Daily Smartphone Healthcare Applications

We propose CardioGuard, a brassiere-based reliable electrocardiogram (ECG) monitoring sensor system, for supporting daily smartphone healthcare applications. It is designed to satisfy two key requirements for user-unobtrusive daily ECG monitoring: reliability of ECG sensing and usability of the sensor. The system is validated through extensive evaluations. The evaluation results showed that the CardioGuard sensor reliably measure the ECG during 12 representative daily activities including diverse movement levels; 89.53% of QRS peaks were detected on average. The questionnaire-based user study with 15 participants showed that the CardioGuard sensor was comfortable and unobtrusive. Additionally, the signal-to-noise ratio test and the washing durability test were conducted to show the high-quality sensing of the proposed sensor and its physical durability in practical use, respectively

Translation, Cultural Adaptation, and Validation of a Korean Version of the Information Needs in Cardiac Rehabilitation Scale

Objective To translate and culturally adapt the Information Needs in Cardiac Rehabilitation (INCR) questionnaire into Korean and perform psychometric validation. Methods The original English version of the INCR, in which patients are asked to rate the importance of 55 topics, was translated into Korean (INCR-K) and culturally adapted. The INCR-K was tested on 101 cardiac rehabilitation (CR) participants at Kangwon National University Hospital and Seoul National University Bundang Hospital in Korea. Structural validity was assessed using principal component analysis, and Cronbach’s alpha of the areas was computed. Criterion validity was assessed by comparing information needs according to CR duration and knowledge sufficiency according to receipt of education. Half of the participants were randomly selected for 1 month of re-testing to assess their responsiveness. Results Following cognitive debriefing, the number of items was reduced to 41 and ratings were added to assess participants’ sufficient knowledge of each item. The INCR-K structure comprised eight areas, each with sufficient internal consistency (Cronbach’s alpha>0.7). Criterion validity was supported by significant differences in mean INCR-K scores based on CR duration and knowledge sufficiency ratings according to receipt of education (p<0.05). Information needs and knowledge sufficiency ratings increased after 1 month of CR, thus supporting responsiveness (p<0.05). Conclusion The INCR-K demonstrated adequate face, content, cross-cultural, structural, and criterion validities, internal consistency, and responsiveness. Information needs changed with CR, such that multiple assessments of information needs may be warranted as rehabilitation progresses to facilitate patient-centered education

Factors influencing menstrual regularity among female workers: a cross-sectional analysis study

Abstract Background Regularity of menstrual cycles is an important indicator of women’s health and fertility, and female workers are exposed to several factors, such as sleep disorders, stress, and shift work, that affect their menstrual regularity. This makes it necessary to comprehensively identify the determinants of menstrual regularity. Therefore, this study identified the factors affecting menstrual regularity among female workers from physiological, psychological, and situational dimensions based on the theory of unpleasant symptoms. Methods This was a secondary analysis of the 2010–2012 Korea National Health and Nutrition Examination Survey and utilized the data of 2418 female workers. Based on the theory of unpleasant symptoms, physiological factors included age, age at menarche, childbirth experience, body mass index, and sleep duration. Psychological factors included stress level, depressive mood, and suicidal ideation. Situational factors included education level, household income, consumption of alcohol, engagement in smoking, and work schedule. The χ²-test and hierarchical logistic regression analysis were performed, reflecting the complex sample design. Results Age at menarche, childbirth experience, and body mass index among physiological factors and education level and work schedule among situational factors were found to be related to menstrual regularity. A higher risk of menstrual irregularities was found among those who had given birth (versus those who had not), had a high age at menarche (versus those with a low age at menarche), were obese (versus those who had a normal body mass index), had elementary school-level or lesser educational achievements (versus those with college graduate-level or higher educational achievements), and who had a shift work schedule (versus those with a fixed schedule). Conclusions Intervention is needed for female workers who have these risk factors, and special attention must be paid to female workers who have a shift work schedule. Additionally, since body mass index can be controlled, intervention concerning body mass index is necessary to reduce menstrual irregularity

Draft Genome Sequence of the Reference Strain of the Korean Medicinal Mushroom Wolfiporia cocos KMCC03342.

Wolfiporia cocos is a wood-decay brown rot fungus belonging to the family Polyporaceae. While the fungus grows, the sclerotium body of the strain, dubbed Bokryeong in Korean, is formed around the roots of conifer trees. The dried sclerotium has been widely used as a key component of many medicinal recipes in East Asia. Wolfiporia cocos strain KMCC03342 is the reference strain registered and maintained by the Korea Seed and Variety Service for commercial uses. Here, we present the first draft genome sequence of W. cocos KMCC03342 using a hybrid assembly technique combining both short- and long-read sequences. The genome has a total length of 55.5 Mb comprised of 343 contigs with N50 of 332 kb and 95.8% BUSCO completeness. The GC ratio was 52.2%. We predicted 14,296 protein-coding gene models based on ab initio gene prediction and evidence-based annotation procedure using RNAseq data. The annotated genome was predicted to have 19 terpene biosynthesis gene clusters, which was the same number as the previously sequenced W. cocos strain MD-104 genome but higher than Chinese W. cocos strains. The genome sequence and the predicted gene clusters allow us to study biosynthetic pathways for the active ingredients of W. cocos

A Detection of Convectively Induced Turbulence Using in Situ Aircraft and Radar Spectral Width Data

A commercial aircraft, departing from Seoul to Jeju Island in South Korea, encountered a convectively induced turbulence (CIT) at about z = 2.2 km near Seoul on 28 October 2018. At this time, the observed radar reflectivity showed that the convective band with cloud tops of z = 6–7 km passed the CIT region with high values of spectral width (SW; larger than 4 m s–1). Using the 1 Hz wind data recorded by the aircraft, we estimated an objective intensity of the CIT as a cube root of eddy dissipation rate (EDR) based on the inertial range technique, which was about 0.33–0.37 m2/3 s−1. Radar-based EDR was also derived by lognormal mapping technique (LMT), showing that the EDR was about 0.3–0.35 m2/3 s−1 near the CIT location, which is consistent with in situ EDR. In addition, a feasibility of the CIT forecast was tested using the weather and research forecast (WRF) model with a 3 km horizontal grid spacing. The model accurately reproduced the convective band passing the CIT event with an hour delay, which allows the use of two methods to calculate EDR: The first is using both the sub-grid and resolved turbulent kinetic energy to infer the EDR; the second is using the LMT for converting absolute vertical velocity (and its combination with the Richardson number) to EDR-scale. As a result, we found that the model-based EDRs were about 0.3–0.4 m2/3 s−1 near the CIT event, which is consistent with the estimated EDRs from both aircraft and radar observations

Barriers against and strategies for malaria control during the COVID-19 pandemic in low- and middle-income countries: a systematic review

Abstract Background The COVID-19 pandemic has disrupted malaria control activities globally. Notably, high levels of excess malaria morbidity and mortality in low- and middle-income countries (LMICs) were reported. Although it is crucial to systematically understand the main causes of the disruption to malaria control and synthesize strategies to prepare for future pandemics, such studies are scarce. Therefore, this study aims to better identify barriers against and strategies for malaria control. Methods Following the PRISMA guidelines and through searches of electronic databases and Google Scholar, a systematic literature review was conducted to identify studies pertaining to malaria control published between January 2020 and December 2021. Only studies that discussed reported barriers and/or strategies related to malaria were included for the review. The Mixed Methods Quality Appraisal Tool (MMAT) and the Authority, Accuracy, Coverage, Objectivity, Date and Significance (AACODS) checklist were used for quality appraisal. Key information such as literature type, study design, setting and population, interventions, outcomes, barriers, and strategies were extracted. With an existing framework of four dimensions (accessibility, affordability, availability, and acceptability) further subdivided by the supply and demand sides, this study synthesized information on barriers and strategies related to malaria control and further categorized the strategies based on the time frame. Results From the 30 selected studies, 27 barriers and 39 strategies were identified. The lockdown measures, which mainly threatened geographic accessibility and availability of malaria control services, were identified to be the main barrier hindering effective mobilization of community health workers and resources. Among the identified strategies, clear risk communication strategies would alleviate psychosocial barriers, which challenged acceptability. Some strategies that cross-cut points across all four dimensions would, require systems-level integration to enhance availability and affordability of malaria control. The strategies were distinguished between short-term, for instant response, and mid to long-term for future readiness. Conclusions The pandemic resulted in complex barriers to malaria control, particularly imposing a double burden on LMICs. Identifying strategies to overcome said barriers provides useful insights in the decision-making processes for the current and future pandemic. Cross-cutting strategies that integrate all dimensions need to be considered. Health system strengthening and resilience strategy appropriate for country-specific context is fundamental