Judge, Localize, and Edit: Ensuring Visual Commonsense Morality for Text-to-Image Generation

Text-to-image generation methods produce high-resolution and high-quality images, but these methods should not produce immoral images that may contain inappropriate content from the commonsense morality perspective. Conventional approaches often neglect these ethical concerns, and existing solutions are limited in avoiding immoral image generation. In this paper, we aim to automatically judge the immorality of synthesized images and manipulate these images into a moral alternative. To this end, we build a model that has the three main primitives: (1) our model recognizes the visual commonsense immorality of a given image, (2) our model localizes or highlights immoral visual (and textual) attributes that make the image immoral, and (3) our model manipulates a given immoral image into a morally-qualifying alternative. We experiment with the state-of-the-art Stable Diffusion text-to-image generation model and show the effectiveness of our ethical image manipulation. Our human study confirms that ours is indeed able to generate morally-satisfying images from immoral ones. Our implementation will be publicly available upon publication to be widely used as a new safety checker for text-to-image generation models

The impact of education on cortical thickness in amyloid-negative subcortical vascular dementia: cognitive reserve hypothesis

Background: The protective effect of education has been well established in Alzheimer's disease, whereas its role in patients with isolated cerebrovascular diseases remains unclear. We examined the correlation of education with cortical thickness and cerebral small vessel disease markers in patients with pure subcortical vascular mild cognitive impairment (svMCl) and patients with pure subcortical vascular dementia (SVaD). Methods: We analyzed 45 patients with svMCl and 47 patients with SVaD with negative results on Pittsburgh compound B positron emission tomographic imaging who underwent structural brain magnetic resonance imaging. The main outcome was cortical thickness measured using surface-based morphometric analysis. We also assessed the volumes of white matter hyperintensities (WMH) and numbers of lacunes as other outcomes. To investigate the correlation of education with cortical thickness, WMH volume, and number of lacunes, multiple linear regression analyses were performed after controlling for covariates, including Mini Mental State Examination, in the svMCl and SVaD groups. Results: In the SVaD group, higher education was correlated with more severe cortical thinning in the bilateral dorsolateral frontal, left medial frontal, and parahippocampal areas, whereas there was no correlation of education with cortical thickness in the svMCl group. There was no correlation between education and cerebral small vessel disease, including WMH and lacunes, in both patients with svMCl and patients with SVaD. Conclusions: Our findings suggest that the compensatory effects of education on cortical thinning apply to patients with SVaD, which might be explained by the cognitive reserve hypothesis

Intracerebroventricular injection of human umbilical cord blood mesenchymal stem cells in patients with Alzheimer’s disease dementia: a phase I clinical trial

Backgrounds: Alzheimer's disease is the most common cause of dementia, and currently, there is no disease-modifying treatment. Favorable functional outcomes and reduction of amyloid levels were observed following transplantation of mesenchymal stem cells (MSCs) in animal studies. Objectives: We conducted a phase I clinical trial in nine patients with mild-to-moderate Alzheimer's disease dementia to evaluate the safety and dose-limiting toxicity of three repeated intracerebroventricular injections of human umbilical cord blood-derived MSCs (hUCB-MSCs). Methods: We recruited nine mild-to-moderate Alzheimer's disease dementia patients from Samsung Medical Center, Seoul, Republic of Korea. Four weeks prior to MSC administration, the Ommaya reservoir was implanted into the right lateral ventricle of the patients. Three patients received a low dose (1.0 × 107 cells/2 mL), and six patients received a high dose (3.0 × 107 cells/2 mL) of hUCB-MSCs. Three repeated injections of MSCs were performed (4-week intervals) in all nine patients. These patients were followed up to 12 weeks after the first hUCB-MSC injection and an additional 36 months in the extended observation study. Results: After hUCB-MSC injection, the most common adverse event was fever (n = 9) followed by headache (n = 7), nausea (n = 5), and vomiting (n = 4), which all subsided within 36 h. There were three serious adverse events in two participants that were considered to have arisen from the investigational product. Fever in a low dose participant and nausea with vomiting in another low dose participant each required extended hospitalization by a day. There were no dose-limiting toxicities. Five participants completed the 36-month extended observation study, and no further serious adverse events were observed. Conclusions: Three repeated administrations of hUCB-MSCs into the lateral ventricle via an Ommaya reservoir were feasible, relatively and sufficiently safe, and well-tolerated. Currently, we are undergoing an extended follow-up study for those who participated in a phase IIa trial where upon completion, we hope to gain a deeper understanding of the clinical efficacy of MSC AD therapy

RPPC: a Holistic Runtime System for Maximizing Performance under Power Capping

Maximizing performance in power-constrained computing environments is highly important in cloud and datacenter computing. To achieve the best possible performance of parallel applications under power capping, it is crucial to execute them with the optimal concurrency level and cross-component power allocation between CPUs and memory. Despite extensive prior works, it still remains unexplored to investigate the efficient runtime support that maximizes the performance of parallel applications under power capping through the coordinated control of concurrency level and cross-component power allocation. To bridge this gap, this work proposes RPPC, a holistic runtime system for maximizing performance under power capping. In contrast to the state-of-the-art techniques, RPPC robustly controls the two performance-critical knobs (i.e., concurrency level and cross-component power allocation) in a coordinated manner to maximize the performance of parallel applications under power capping. RPPC dynamically identifies the characteristics of the target parallel application and explores the system state space to find an efficient system state. Our experimental results demonstrate that RPPC significantly outperforms the two state-of-the-art power-capping techniques, achieves the performance comparable with the static best version that requires extensive per-application offline profiling, incurs small performance overheads, and provides the re-adaptation mechanism to external events such as total power budget changes

Analysis of Residential Satisfaction Changes by the Land Bank Program Using Text Mining

Many American manufacturing cities have experienced depopulation and economic downturns over the past five decades, and various revitalization strategies have been suggested to overcome the decline issue—ranging from redevelopment to smart decline. However, while most land bank-related studies have focused on socioeconomic dynamics (income levels, unemployment rate, etc.) through the program, there is a lack of direct research on residential satisfaction changes. Additionally, surveys were frequently used in previous studies to evaluate residential satisfaction; however, this method has disadvantages, including constraints on time and cost, and the inability to take into account external factors that may affect residential satisfaction. Furthermore, most studies on urban decline have focused primarily on declining factors, and there have been few investigations into how cities change as urban regeneration strategies advance. Therefore, the primary purpose of this study is to identify the influence of the land bank program on residential satisfaction by using Twitter data. Approximately 300,000 Twitter posts containing location information generated within the city of Detroit were collected to determine the degree of sensitivity to each tweet and categorized into positive and negative emotions to determine the relationship between residential satisfaction and the land bank program. As a result, the increase in homeownership, built year, house value, and the number of land banking sold properties were found to have a negative effect on neighborhood satisfaction in Detroit. Although the research results indicated that while the land bank program did not significantly improve residential satisfaction in Detroit, it has made a partial contribution to improving living standards. These findings emphasize the importance of enhancing residential satisfaction and suggest the need for policy change. In response to the problem of urban contraction, it seems that indiscriminately distributing houses is not the only solution to prevent urban shrinkage. Furthermore, this study shows meaningful results on text mining and provides the possibility of developing research using social network services

Analysis of Residential Satisfaction Changes by the Land Bank Program Using Text Mining

Many American manufacturing cities have experienced depopulation and economic downturns over the past five decades, and various revitalization strategies have been suggested to overcome the decline issue—ranging from redevelopment to smart decline. However, while most land bank-related studies have focused on socioeconomic dynamics (income levels, unemployment rate, etc.) through the program, there is a lack of direct research on residential satisfaction changes. Additionally, surveys were frequently used in previous studies to evaluate residential satisfaction; however, this method has disadvantages, including constraints on time and cost, and the inability to take into account external factors that may affect residential satisfaction. Furthermore, most studies on urban decline have focused primarily on declining factors, and there have been few investigations into how cities change as urban regeneration strategies advance. Therefore, the primary purpose of this study is to identify the influence of the land bank program on residential satisfaction by using Twitter data. Approximately 300,000 Twitter posts containing location information generated within the city of Detroit were collected to determine the degree of sensitivity to each tweet and categorized into positive and negative emotions to determine the relationship between residential satisfaction and the land bank program. As a result, the increase in homeownership, built year, house value, and the number of land banking sold properties were found to have a negative effect on neighborhood satisfaction in Detroit. Although the research results indicated that while the land bank program did not significantly improve residential satisfaction in Detroit, it has made a partial contribution to improving living standards. These findings emphasize the importance of enhancing residential satisfaction and suggest the need for policy change. In response to the problem of urban contraction, it seems that indiscriminately distributing houses is not the only solution to prevent urban shrinkage. Furthermore, this study shows meaningful results on text mining and provides the possibility of developing research using social network services

Design and Implementation of Bandwidth-Aware Memory Placement and Migration Policies for Heterogeneous Memory Systems

Heterogeneous memory systems that comprise memory nodes based on widely-different device technologies (e.g., DRAM and nonvolatile memory (NVM)) are emerging in various computing domains ranging from high-performance to embedded computing. Despite the extensive prior work on architectural and system software support for heterogeneous memory systems, relatively little work has been done to investigate the OS-level memory placement and migration policies that consider the bandwidth differences of heterogeneous memory nodes. To bridge this gap, this work investigates the design and implementation of memory placement and migration policies for bandwidth-intensive applications on heterogeneous memory systems. Specifically, we propose three bandwidth-aware memory placement policies (i.e., bandwidth-aware interleave, random, and local policies) and a bandwidth-aware memory migration policy and implement the proposed policies in the Linux kernel. Through our quantitative evaluation based on real system software and hardware stacks, we demonstrate that the bandwidth-aware memory placement and migration policies achieve significantly higher performance than the conventional bandwidth-oblivious policies across a wide range of the DRAM-to-NVM bandwidth ratios when executing bandwidth-intensive workloads

POSTER: The Performance Impact of Thread Packing on Synchronization-Intensive Applications

Thread packing (TP) is a widely-used technique to improve the efficiency of parallel systems. Despite extensive prior works, relatively little work has been done to investigate its performance inefficiencies. To bridge this gap, we quantify its performance impact on synchronization-intensive applications and identify the root causes of its performance inefficiencies

PALM: Progress- and Locality-Aware Adaptive Task Migration for Efficient Thread Packing

Thread packing (TP) is an effective and widely-used technique to significantly improve the efficiency of parallel systems by dynamically controlling the number of cores allocated to multithreaded applications based on their requirements such as performance and energy efficiency. Despite the extensive prior works on TP, little work has been done to investigate and address its performance inefficiencies that arise across various parallel systems and applications with different characteristics. To bridge this gap, we investigate the performance inefficiencies of TP using a wide range of parallel applications and system configurations and identify their root causes. Guided by the in-depth performance characterization results, we propose PALM, progress- and locality-aware adaptive task migration for efficient TP. Through quantitative evaluation, we demonstrate that PALM achieves significantly higher performance and lower energy consumption than TP across various synchronization-intensive applications and system configurations, provides the performance and energy consumption comparable with the thread reduction technique, and considerably improves the efficiency of dynamic server consolidation and the performance under power capping