TPA: Fast, Scalable, and Accurate Method for Approximate Random Walk with Restart on Billion Scale Graphs

Given a large graph, how can we determine similarity between nodes in a fast and accurate way? Random walk with restart (RWR) is a popular measure for this purpose and has been exploited in numerous data mining applications including ranking, anomaly detection, link prediction, and community detection. However, previous methods for computing exact RWR require prohibitive storage sizes and computational costs, and alternative methods which avoid such costs by computing approximate RWR have limited accuracy. In this paper, we propose TPA, a fast, scalable, and highly accurate method for computing approximate RWR on large graphs. TPA exploits two important properties in RWR: 1) nodes close to a seed node are likely to be revisited in following steps due to block-wise structure of many real-world graphs, and 2) RWR scores of nodes which reside far from the seed node are proportional to their PageRank scores. Based on these two properties, TPA divides approximate RWR problem into two subproblems called neighbor approximation and stranger approximation. In the neighbor approximation, TPA estimates RWR scores of nodes close to the seed based on scores of few early steps from the seed. In the stranger approximation, TPA estimates RWR scores for nodes far from the seed using their PageRank. The stranger and neighbor approximations are conducted in the preprocessing phase and the online phase, respectively. Through extensive experiments, we show that TPA requires up to 3.5x less time with up to 40x less memory space than other state-of-the-art methods for the preprocessing phase. In the online phase, TPA computes approximate RWR up to 30x faster than existing methods while maintaining high accuracy.Comment: 12pages, 10 figure

Impact of Cognitive Function and Cancer Coping on Quality of Life among Women with Post-chemotherapy Breast Cancer

PURPOSE: This study was done to identify effects of cognitive function and cancer coping on quality of life among women with breast cancer treated with antineoplastic agents. METHODS: The study was correlational research and participants were 145 women with breast cancer who had received antineoplastic agents. Data were collected from October to November, 2015 via online replies. Cognitive function was measured with the Functional Assessment of Cancer Therapy-Cognitive Function Version-3 (FACT-Cog), cancer coping, with the Korean Cancer Coping Questionnaire (K-CCQ), and quality of life with the Functional Assessment of Cancer Therapy-Breast Version-4 (FACT-B). Data were analyzed using descriptive statistics, t-test, ANOVA, Scheffé test, ANCOVA, Bonferroni test, partial correlation coefficient, and hierarchical multiple regression with SPSS 21. RESULTS: Cognitive functions, total individual coping, and interpersonal coping explained 42% of quality of life. Cognitive function (β=.35, p<.001) was the best predictor of quality of life, followed by total individual coping (β=.34, p<.001), and interpersonal coping (β=.26, p<.001). CONCLUSION: Results indicate that cognitive function and cancer coping are meaningful factors for quality of life among breast cancer survivors. Therefore when developing intervention programs for these women, content on cognitive function and coping skills as well as coping resources should be included

Developing Social Robots with Empathetic Non-Verbal Cues Using Large Language Models

We propose augmenting the empathetic capacities of social robots by integrating non-verbal cues. Our primary contribution is the design and labeling of four types of empathetic non-verbal cues, abbreviated as SAFE: Speech, Action (gesture), Facial expression, and Emotion, in a social robot. These cues are generated using a Large Language Model (LLM). We developed an LLM-based conversational system for the robot and assessed its alignment with social cues as defined by human counselors. Preliminary results show distinct patterns in the robot's responses, such as a preference for calm and positive social emotions like 'joy' and 'lively', and frequent nodding gestures. Despite these tendencies, our approach has led to the development of a social robot capable of context-aware and more authentic interactions. Our work lays the groundwork for future studies on human-robot interactions, emphasizing the essential role of both verbal and non-verbal cues in creating social and empathetic robots

Exploring Environmental Inequity in South Korea: An Analysis of the Distribution of Toxic Release Inventory (TRI) Facilities and Toxic Releases

Recently, location data regarding the Toxic Release Inventory (TRI) in South Korea was released to the public. This study investigated the spatial patterns of TRIs and releases of toxic substances in all 230 local governments in South Korea to determine whether spatial clusters relevant to the siting of noxious facilities occur. In addition, we employed spatial regression modeling to determine whether the number of TRI facilities and the volume of toxic releases in a given community were correlated with the community's socioeconomic, racial, political, and land use characteristics. We found that the TRI facilities and their toxic releases were disproportionately distributed with clustered spatial patterning. Spatial regression modeling indicated that jurisdictions with smaller percentages of minorities, stronger political activity, less industrial land use, and more commercial land use had smaller numbers of toxic releases, as well as smaller numbers of TRI facilities. However, the economic status of the community did not affect the siting of hazardous facilities. These results indicate that the siting of TRI facilities in Korea is more affected by sociopolitical factors than by economic status. Racial issues are thus crucial for consideration in environmental justice as the population of Korea becomes more racially and ethnically diverse

Carpal Tunnel Syndrome Caused by Space Occupying Lesions

PURPOSE: To evaluate the diagnosis and treatment of the carpal tunnel syndrome (CTS) due to space occupying lesions (SOL). MATERIALS and METHODS: Eleven patients and 12 cases that underwent surgery for CTS due to SOL were studied retrospectively. We excluded SOL caused by bony lesions, such as malunion of distal radius fracture, volar lunate dislocation, etc. the average age was 51 years. There were 3 men and 8 women. Follow-up period was 12 to 40 months with an average of 18 months. the diagnosis of CTS was made clinically and electrophysiologically. in patients with swelling or tenderness on the area of wrist flexion creases, magnetic resonance imaging (MRI) and/or computed tomogram (CT) were additionally taken as well as the carpal tunnel view. We performed conventional open transverse carpal ligament release and removal of SOL. RESULTS: the types of lesion confirmed by pathologic examination were; tuberculosis tenosynovitis in 3 cases, nonspecific tenosynovitis in 2 cases, and gout in one case. Other SOLs were tumorous condition in five cases, and abnormal palmaris longus hypertrophy in 1 case. Tumorous conditions were due to calcifying mass in 4 cases and ganglion in 1 case. Following surgery, all cases showed alleviation of symptom without recurrence or complications. CONCLUSION: in cases with swelling or tenderness on the area of wrist flexion creases, it is important to obtain a carpal tunnel view, and MRI and/or CT should be supplemented in order to rule out SOLs around the carpal tunnel, if necessary.ope

Does Objective Structured Clinical Examinations Score Reflect the Clinical Reasoning Ability of Medical Students?

Abstract:BackgroundClinical reasoning ability is an important factor in a physician's competence and thus should be taught and tested in medical schools. Medical schools generally use objective structured clinical examinations (OSCE) to measure the clinical competency of medical students. However, it is unknown whether OSCE can also evaluate clinical reasoning ability. In this study, the authors investigated whether OSCE scores reflected students' clinical reasoning abilities.MethodsSixty-five fourth-year medical students participated in this study. Medical students completed the OSCE with 4 cases using standardized patients. For assessment of clinical reasoning, students were asked to list differential diagnoses and the findings that were compatible or not compatible with each diagnosis. The OSCE score (score of patient encounter), diagnostic accuracy score, clinical reasoning score, clinical knowledge score and grade point average (GPA) were obtained for each student, and correlation analysis was performed.ResultsClinical reasoning score was significantly correlated with diagnostic accuracy and GPA (correlation coefficient = 0.258 and 0.380; P = 0.038 and 0.002, respectively) but not with OSCE score or clinical knowledge score (correlation coefficient = 0.137 and 0.242; P = 0.276 and 0.052, respectively). Total OSCE score was not significantly correlated with clinical knowledge test score, clinical reasoning score, diagnostic accuracy score or GPA.ConclusionsOSCE score from patient encounters did not reflect the clinical reasoning abilities of the medical students in this study. The evaluation of medical students' clinical reasoning abilities through OSCE should be strengthened