Simulating Problem Difficulty in Arithmetic Cognition Through Dynamic Connectionist Models

The present study aims to investigate similarities between how humans and connectionist models experience difficulty in arithmetic problems. Problem difficulty was operationalized by the number of carries involved in solving a given problem. Problem difficulty was measured in humans by response time, and in models by computational steps. The present study found that both humans and connectionist models experience difficulty similarly when solving binary addition and subtraction. Specifically, both agents found difficulty to be strictly increasing with respect to the number of carries. Another notable similarity is that problem difficulty increases more steeply in subtraction than in addition, for both humans and connectionist models. Further investigation on two model hyperparameters --- confidence threshold and hidden dimension --- shows higher confidence thresholds cause the model to take more computational steps to arrive at the correct answer. Likewise, larger hidden dimensions cause the model to take more computational steps to correctly answer arithmetic problems; however, this effect by hidden dimensions is negligible.Comment: 7 pages; 15 figures; 5 tables; Published in the proceedings of the 17th International Conference on Cognitive Modelling (ICCM 2019

Comparison of First-Line Dual Combination Treatments in Hypertension: Real-World Evidence from Multinational Heterogeneous Cohorts.

Background and objectives: 2018 ESC/ESH Hypertension guideline recommends 2-drug combination as initial anti-hypertensive therapy. However, real-world evidence for effectiveness of recommended regimens remains limited. We aimed to compare the effectiveness of first-line anti-hypertensive treatment combining 2 out of the following classes: angiotensin-converting enzyme (ACE) inhibitors/angiotensin-receptor blocker (A), calcium channel blocker (C), and thiazide-type diuretics (D).Methods: Treatment-naïve hypertensive adults without cardiovascular disease (CVD) who initiated dual anti-hypertensive medications were identified in 5 databases from US and Korea. The patients were matched for each comparison set by large-scale propensity score matching. Primary endpoint was all-cause mortality. Myocardial infarction, heart failure, stroke, and major adverse cardiac and cerebrovascular events as a composite outcome comprised the secondary measure.Results: A total of 987,983 patients met the eligibility criteria. After matching, 222,686, 32,344, and 38,513 patients were allocated to A+C vs. A+D, C+D vs. A+C, and C+D vs. A+D comparison, respectively. There was no significant difference in the mortality during total of 1,806,077 person-years: A+C vs. A+D (hazard ratio [HR], 1.08; 95% confidence interval [CI], 0.97-1.20; p=0.127), C+D vs. A+C (HR, 0.93; 95% CI, 0.87-1.01; p=0.067), and C+D vs. A+D (HR, 1.18; 95% CI, 0.95-1.47; p=0.104). A+C was associated with a slightly higher risk of heart failure (HR, 1.09; 95% CI, 1.01-1.18; p=0.040) and stroke (HR, 1.08; 95% CI, 1.01-1.17; p=0.040) than A+D.Conclusions: There was no significant difference in mortality among A+C, A+D, and C+D combination treatment in patients without previous CVD. This finding was consistent across multi-national heterogeneous cohorts in real-world practice

nuQmm: Quantized MatMul for Efficient Inference of Large-Scale Generative Language Models

The recent advance of self-supervised learning associated with the Transformer architecture enables natural language processing (NLP) to exhibit extremely low perplexity. Such powerful models demand ever-increasing model size and, thus, large amounts of computations and memory footprints. In this paper, we propose an efficient inference framework for large-scale generative language models. As the key to reducing model size, we quantize weights by a non-uniform quantization method. Then, quantized matrix multiplications are accelerated by our proposed kernel, called nuQmm, which allows a wide trade-off between compression ratio and accuracy. Our proposed nuQmm reduces the latency of not only each GPU but also the entire inference of large LMs because a high compression ratio (by low-bit quantization) mitigates the minimum required number of GPUs. Assuming 2-bit quantization, we demonstrate that nuQmm can reduce latency to generate each token for OPT-175B (that requires 8 GPUs without nuQmm) by 47.3% using 8 GPUs or by 23.2% using only 2 GPUs.Comment: 15 pages (including 5 pages of References & Appendix), 14 figures, 7 table

Extending Achilles Heel Data Quality Tool with New Rules Informed by Multi-Site Data Quality Comparison

Large healthcare datasets of Electronic Health Record data became indispensable in clinical research. Data quality in such datasets recently became a focus of many distributed research networks. Despite the fact that data quality is specific to a given research question, many existing data quality platform prove that general data quality assessment on dataset level (given a spectrum of research questions) is possible and highly requested by researchers. We present comparison of 12 datasets and extension of Achilles Heel data quality software tool with new rules and data characterization measures

Evaluation of low-pass genome sequencing in polygenic risk score calculation for Parkinsons disease

Background Low-pass sequencing (LPS) has been extensively investigated for applicability to various genetic studies due to its advantages over genotype array data including cost-effectiveness. Predicting the risk of complex diseases such as Parkinsons disease (PD) using polygenic risk score (PRS) based on the genetic variations has shown decent prediction accuracy. Although ultra-LPS has been shown to be effective in PRS calculation, array data has been favored to the majority of PRS analysis, especially for PD. Results Using eight high-coverage WGS, we assessed imputation approaches for downsampled LPS data ranging from 0.5 × to 7.0 × . We demonstrated that uncertain genotype calls of LPS diminished imputation accuracy, and an imputation approach using genotype likelihoods was plausible for LPS. Additionally, comparing imputation accuracies between LPS and simulated array illustrated that LPS had higher accuracies particularly at rare frequencies. To evaluate ultra-low coverage data in PRS calculation for PD, we prepared low-coverage WGS and genotype array of 87 PD cases and 101 controls. Genotype imputation of array and downsampled LPS were conducted using a population-specific reference panel, and we calculated risk scores based on the PD-associated SNPs from an East Asian meta-GWAS. The PRS models discriminated cases and controls as previously reported when both LPS and genotype array were used. Also strong correlations in PRS models for PD between LPS and genotype array were discovered. Conclusions Overall, this study highlights the potentials of LPS under 1.0 × followed by genotype imputation in PRS calculation and suggests LPS as attractive alternatives to genotype array in the area of precision medicine for PD.This work has been supported by Macrogen Inc. (Grant No. MGR20-01)

Silicon Carbide-Based Hydrogen Gas Sensors for High-Temperature Applications

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Movement Time of Lower Trunk Muscles during Dynamic Postural Control in Response to a Sudden Visual Stimulus during Walking: A Pilot Study

Postural control during walking is maintained by the combination of various factors. Among these factors, adjustment of trunk movement is essential for maintaining postural control, and the response of muscles to unpredictable stimuli affects postural control. Loss of balance while walking increases the risk of accidents, the frequency of which depends on age and sex. In this study, we investigated whether there was a difference in the movement time of trunk muscles to sudden stimulation while walking according to age and sex. Fourteen healthy individuals aged 20–30 years (6 men, 8 women) and 12 individuals aged 50–70 years (4 men, 8 women) were included in the study. Movement time of bilateral erector spinae and rectus abdominis muscles in response to visual stimulation during walking was examined using surface electromyography. Movement time was calculated as the total muscle activation time excluding the reaction time. This study revealed no significant differences in movement time of the erector spinae muscles according to sex or age. The role of the rectus abdominis muscles in maintaining posture during walking was insignificant. In conclusion, the movement time of trunk muscles in response to sudden visual stimulation during walking did not differ by age or sex, and the difference in accident frequency may be associated with deterioration of other factors required to maintain posture

The Best Prediction Model for Trauma Outcomes of the Current Korean Population: a Comparative Study of Three Injury Severity Scoring Systems

Background: Injury severity scoring systems that quantify and predict trauma outcomes have not been established in Korea. This study was designed to determine the best system for use in the Korean trauma population. Methods: We collected and analyzed the data from trauma patients admitted to our institution from January 2010 to December 2014. Injury Severity Score (ISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) were calculated based on the data from the enrolled patients. Area under the receiver operating characteristic (ROC) curve (AUC) for the prediction ability of each scoring system was obtained, and a pairwise comparison of ROC curves was performed. Additionally, the cut-off values were estimated to predict mortality, and the corresponding accuracy, positive predictive value, and negative predictive value were obtained. Results: A total of 7,120 trauma patients (6,668 blunt and 452 penetrating injuries) were enrolled in this study. The AUCs of ISS, RTS, and TRISS were 0.866, 0.894, and 0.942, respectively, and the prediction ability of the TRISS was significantly better than the others (p < 0.001, respectively). The cut-off value of the TRISS was 0.9082, with a sensitivity of 81.9% and specificity of 92.0%; mortality was predicted with an accuracy of 91.2%; its positive predictive value was the highest at 46.8%. Conclusions: The results of our study were based on the data from one institution and suggest that the TRISS is the best prediction model of trauma outcomes in the current Korean population. Further study is needed with more data from multiple centers in Korea