From Values to Opinions: Predicting Human Behaviors and Stances Using Value-Injected Large Language Models

Being able to predict people's opinions on issues and behaviors in realistic scenarios can be helpful in various domains, such as politics and marketing. However, conducting large-scale surveys like the European Social Survey to solicit people's opinions on individual issues can incur prohibitive costs. Leveraging prior research showing influence of core human values on individual decisions and actions, we propose to use value-injected large language models (LLM) to predict opinions and behaviors. To this end, we present Value Injection Method (VIM), a collection of two methods -- argument generation and question answering -- designed to inject targeted value distributions into LLMs via fine-tuning. We then conduct a series of experiments on four tasks to test the effectiveness of VIM and the possibility of using value-injected LLMs to predict opinions and behaviors of people. We find that LLMs value-injected with variations of VIM substantially outperform the baselines. Also, the results suggest that opinions and behaviors can be better predicted using value-injected LLMs than the baseline approaches.Comment: EMNLP 2023 main paper accepte

Posterior-Aided Regularization for Likelihood-Free Inference

The recent development of likelihood-free inference aims training a flexible density estimator for the target posterior with a set of input-output pairs from simulation. Given the diversity of simulation structures, it is difficult to find a single unified inference method for each simulation model. This paper proposes a universally applicable regularization technique, called Posterior-Aided Regularization (PAR), which is applicable to learning the density estimator, regardless of the model structure. Particularly, PAR solves the mode collapse problem that arises as the output dimension of the simulation increases. PAR resolves this posterior mode degeneracy through a mixture of 1) the reverse KL divergence with the mode seeking property; and 2) the mutual information for the high quality representation on likelihood. Because of the estimation intractability of PAR, we provide a unified estimation method of PAR to estimate both reverse KL term and mutual information term with a single neural network. Afterwards, we theoretically prove the asymptotic convergence of the regularized optimal solution to the unregularized optimal solution as the regularization magnitude converges to zero. Additionally, we empirically show that past sequential neural likelihood inferences in conjunction with PAR present the statistically significant gains on diverse simulation tasks

Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models

The proposed method, Discriminator Guidance, aims to improve sample generation of pre-trained diffusion models. The approach introduces a discriminator that gives explicit supervision to a denoising sample path whether it is realistic or not. Unlike GANs, our approach does not require joint training of score and discriminator networks. Instead, we train the discriminator after score training, making discriminator training stable and fast to converge. In sample generation, we add an auxiliary term to the pre-trained score to deceive the discriminator. This term corrects the model score to the data score at the optimal discriminator, which implies that the discriminator helps better score estimation in a complementary way. Using our algorithm, we achive state-of-the-art results on ImageNet 256x256 with FID 1.83 and recall 0.64, similar to the validation data's FID (1.68) and recall (0.66). We release the code at https://github.com/alsdudrla10/DG.Comment: International Conference on Machine Learning (ICML23

Association between nasal shedding and fever that influenza A (H3N2) induces in dogs

<p>Abstract</p> <p>Background</p> <p>Avian origin canine influenza virus was reported in Korea. The dog to dog contact transmission of the avian origin canine influenza virus (CIV) H3N2 and CIV H3N8 was shown by experimental contact transmission. This study was focused on viral excretion and fever in order to elucidate the epidemiological associations which might be helpful to control the disease transmissions in CIV outbreak in dogs.</p> <p>Methods</p> <p>An influenza seronegative 10-week-old Beagle dog was experimentally inoculated with the canine influenza virus A/canine/01/2007, subtype H3N2. Eight hours after inoculation, the infected dog was cohoused with seven uninfected Beagle dogs. Clinical signs including fever were recorded for 14 days post inoculation.</p> <p>Results</p> <p>The infected dog and four of seven contact dogs in the study showed clinical signs (sneezing, nasal discharge and coughing) during the study. Viral shedding occurred in all of the animals tested and began on 1 to 6 DPI in dogs with clinical signs. Elevated body temperatures above 39.5°C (geometric mean temperature of 39.86°C±0.49) were observed in all symptomatic dogs. The mean viral titer during fever was 2.99 log EID₅₀/ml, which was significantly higher than the viral titer detected in the non fever.</p> <p>Conclusions</p> <p>The data show that contact dogs with a canine influenza infected dog shed different levels of virus in their nasal excretions and demonstrate that clinical signs, including fever, significantly correlate with the viral shedding.</p

Prognostic Role of TMED3 in Clear Cell Renal Cell Carcinoma: A Retrospective Multi-Cohort Analysis

Transmembrane p24 trafficking protein 3 (TMED3) is a metastatic suppressor in colon cancer and hepatocellular carcinoma. However, its function in the progression of clear cell renal cell carcinoma (ccRCC) is unknown. Here, we report that TMED3 could be a new prognostic marker for ccRCC. Patient data were extracted from cohorts in the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Differential expression of TMED3 was observed between the low stage (Stage I and II) and high stage (Stage III and IV) patients in the TCGA and ICGC cohorts and between the low grade (Grade I and II) and high grade (Grade III and IV) patients in the TCGA cohort. Further, we evaluated TMED3 expression as a prognostic gene using Kaplan-Meier survival analysis, multivariate analysis, the time-dependent area under the curve (AUC) of Uno’s C-index, and the AUC of the receiver operating characteristics at 5 years. The Kaplan-Meier analysis revealed that TMED3 overexpression was associated with poor prognosis for ccRCC patients. Analysis of the C-indices and area under the receiver operating characteristic curve further supported this. Multivariate analysis confirmed the prognostic significance of TMED3 expression levels (P = 0.005 and 0.006 for TCGA and ICGC, respectively). Taken together, these findings demonstrate that TMED3 is a potential prognostic factor for ccRCC

Hypoxia-dependent mitochondrial fission regulates endothelial progenitor cell migration, invasion, and tube formation

Tumor undergo uncontrolled, excessive proliferation leads to hypoxic microenvironment. To fulfill their demand for nutrient, and oxygen, tumor angiogenesis is required. Endothelial progenitor cells (EPCs) have been known to the main source of angiogenesis because of their potential to differentiation into endothelial cells. Therefore, understanding the mechanism of EPC-mediated angiogenesis in hypoxia is critical for development of cancer therapy. Recently, mitochondrial dynamics has emerged as a critical mechanism for cellular function and differentiation under hypoxic conditions. However, the role of mitochondrial dynamics in hypoxia-induced angiogenesis remains to be elucidated. In this study, we demonstrated that hypoxia-induced mitochondrial fission accelerates EPCs bioactivities. We first investigated the effect of hypoxia on EPC-mediated angiogenesis. Cell migration, invasion, and tube formation was significantly increased under hypoxic conditions; expression of EPC surface markers was unchanged. And mitochondrial fission was induced by hypoxia time-dependent manner. We found that hypoxia-induced mitochondrial fission was triggered by dynamin-related protein Drp1, specifically, phosphorylated DRP1 at Ser637, a suppression marker for mitochondrial fission, was impaired in hypoxia time-dependent manner. To confirm the role of DRP1 in EPC-mediated angiogenesis, we analyzed cell bioactivities using Mdivi-1, a selective DRP1 inhibitor, and DRP1 siRNA. DRP1 silencing or Mdivi-1 treatment dramatically reduced cell migration, invasion, and tube formation in EPCs, but the expression of EPC surface markers was unchanged. In conclusion, we uncovered a novel role of mitochondrial fission in hypoxia-induced angiogenesis. Therefore, we suggest that specific modulation of DRP1-mediated mitochondrial dynamics may be a potential therapeutic strategy in EPC-mediated tumor angiogenesis

Black Carbon and PM

Poor outdoor air quality increases air pollutants indoors. Indoor and outdoor air pollutants adversely affect human health, especially in children, who are particularly vulnerable. In this study, indoor and outdoor BC (Black Carbon) and PM2.5 were measured in an elementary school classroom located in an urban city in South Korea. Indoor and outdoor concentrations (BC and PM2.5) were monitored for 7 days (140 hours) during the winter of December 2021. In addition, the classroom schedule was surveyed to identify the occupancy conditions. The reason for air pollution in the urban school was traffic. Classroom BC and PM2.5 concentrations were affected by outdoor and indoor factors. The primary outdoor factor was infiltration, and the impact was larger for BC than for PM2.5. The primary indoor factor was occupant behavior and the impact was more significant for PM2.5 than for BC

Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions

A heat pump with thermal storage system is a system that operates a heat pump during nighttime using inexpensive electricity; during this time, the generated thermal energy is stored in a thermal storage tank. The stored thermal energy is used by the heat pump during daytime. Based on a model of a dual latent thermal storage tank and a heat pump, this study conducts control simulations using both conventional and advanced methods for heating in a building. Conventional methods include the thermal storage priority method and the heat pump priority method, while advanced approaches include the region control method and the dynamic programming method. The heating load required for an office building is identified using TRNSYS (Transient system simulation), used for simulations of various control methods. The thermal storage priority method shows a low coefficient of performance (COP), while the heat pump priority method leads to high electricity costs due to the low use of thermal storage. In contrast, electricity costs are lower for the region control method, which operates using the optimal part load ratio of the heat pump, and for dynamic programming, which operates the system by following the minimum cost path. According to simulation results for the winter season, the electricity costs using the dynamic programming method are 17% and 9% lower than those of the heat pump priority and thermal storage priority methods, respectively. The region control method shows results similar to the dynamic programming method with respect to electricity costs. In conclusion, advanced control methods are proven to have advantages over conventional methods in terms of power consumption and electricity costs

Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation

Recent advances in diffusion models bring state-of-the-art performance on image generation tasks. However, empirical results from previous research in diffusion models imply an inverse correlation between density estimation and sample generation performances. This paper investigates with sufficient empirical evidence that such inverse correlation happens because density estimation is significantly contributed by small diffusion time, whereas sample generation mainly depends on large diffusion time. However, training a score network well across the entire diffusion time is demanding because the loss scale is significantly imbalanced at each diffusion time. For successful training, therefore, we introduce Soft Truncation, a universally applicable training technique for diffusion models, that softens the fixed and static truncation hyperparameter into a random variable. In experiments, Soft Truncation achieves state-of-the-art performance on CIFAR-10, CelebA, CelebA-HQ 256x256, and STL-10 datasets.Comment: 28 pages, 16 figures, 15 table

Changes in trust and the use of Korean medicine in South Korea: a comparison of surveys in 2011 and 2014

Abstract Background Korean medicine (KM) has been widely used in Korea. This study aimed to assess the general perceptions of KM, to investigate the patterns of its usage in 2014, and to compare the results with those of an earlier survey from 2011. Methods A cross-sectional study was conducted with 1000 Korean people. The questionnaire included items regarding trust in KM, reasons for distrust of KM, and visit frequency to KM clinics. This study used methods consistent with those of a 2011 survey to examine changes in attitudes over 3 years. Results Despite high rates of trust in KM, the visit frequency decreased from 69.3% in 2011 to 63.2% in 2014. Usage among young adults (in their 20s and 30s) was significantly reduced compared to all other age groups. The KM modality most commonly used by participants was acupuncture, whereas the use of moxibustion and cupping therapies has decreased since 2011. Men and women were most likely to distrust KM due to a “lack of scientific evidence” (59.3%) and “suspicion of KM safety” (47.4%), respectively. Conclusions The findings suggested that KM use and trust in KM were slightly lower in 2014 than in 2011. The decreases were most notable among individuals in their 30s and in the use of moxibustion in KM therapy. This study aimed to produce practical insights by reviewing patterns of KM use and perceptions over time. Additional surveys must be considered to produce a more in-depth analysis