40 research outputs found

    Read-only Prompt Optimization for Vision-Language Few-shot Learning

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    In recent years, prompt tuning has proven effective in adapting pre-trained vision-language models to downstream tasks. These methods aim to adapt the pre-trained models by introducing learnable prompts while keeping pre-trained weights frozen. However, learnable prompts can affect the internal representation within the self-attention module, which may negatively impact performance variance and generalization, especially in data-deficient settings. To address these issues, we propose a novel approach, Read-only Prompt Optimization (RPO). RPO leverages masked attention to prevent the internal representation shift in the pre-trained model. Further, to facilitate the optimization of RPO, the read-only prompts are initialized based on special tokens of the pre-trained model. Our extensive experiments demonstrate that RPO outperforms CLIP and CoCoOp in base-to-new generalization and domain generalization while displaying better robustness. Also, the proposed method achieves better generalization on extremely data-deficient settings, while improving parameter efficiency and computational overhead. Code is available at https://github.com/mlvlab/RPO.Comment: Accepted at ICCV202

    Fine-Grained Socioeconomic Prediction from Satellite Images with Distributional Adjustment

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    While measuring socioeconomic indicators is critical for local governments to make informed policy decisions, such measurements are often unavailable at fine-grained levels like municipality. This study employs deep learning-based predictions from satellite images to close the gap. We propose a method that assigns a socioeconomic score to each satellite image by capturing the distributional behavior observed in larger areas based on the ground truth. We train an ordinal regression scoring model and adjust the scores to follow the common power law within and across regions. Evaluation based on official statistics in South Korea shows that our method outperforms previous models in predicting population and employment size at both the municipality and grid levels. Our method also demonstrates robust performance in districts with uneven development, suggesting its potential use in developing countries where reliable, fine-grained data is scarce

    Ozone response to emission changes: a modeling study during the MCMA-2006/MILAGRO Campaign

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    The sensitivity of ozone production to precursor emissions was investigated under five different meteorological conditions in the Mexico City Metropolitan Area (MCMA) during the MCMA-2006/MILAGRO field campaign using the gridded photochemical model CAMx driven by observation-nudged WRF meteorology. Precursor emissions were constrained by the comprehensive data from the field campaign and the routine ambient air quality monitoring network. Simulated plume mixing and transport were examined by comparing with measurements from the G-1 aircraft during the campaign. The observed concentrations of ozone precursors and ozone were reasonably well reproduced by the model. The effects of reducing precursor emissions on urban ozone production were performed for three representative emission control scenarios. A 50% reduction in VOC emissions led to 7 to 22 ppb decrease in daily maximum ozone concentrations, while a 50% reduction in NOx [NO subscript x] emissions leads to 4 to 21 ppb increase, and 50% reductions in both NOx [NO subscript x] and VOC emission decrease the daily maximum ozone concentrations up to 10 ppb. These results along with a chemical indicator analysis using the chemical production ratios of H2O2 [H subscript 2 O subscript 2] to HNO3 [HNO subscript 3] demonstrate that the MCMA urban core region is VOC-limited for all meteorological episodes, which is consistent with the results from MCMA-2003 field campaign; however the degree of the VOC-sensitivity is higher during MCMA-2006 due to lower VOCs, lower VOC reactivity and moderately higher NOx [NO subscript x] emissions. Ozone formation in the surrounding mountain/rural area is mostly NOx-limited [NO subscript x - limited], but can be VOC-limited, and the range of the NOx-limited [NO subscript x - limited] or VOC-limited areas depends on meteorology.United States. Dept. of Energy. Office of Biological and Environmental Research. Atmospheric Science Program (DE-FG02-05ER63980)National Science Foundation (U.S.). Atmospheric Chemistry Program (ATM-0528227)National Science Foundation (U.S.). Atmospheric Chemistry Program (ATM-810931)Mexico. Comisión Ambiental MetropolitanaMolina Center for Energy and the Environmen

    Impact of national policy on hand hygiene promotion activities in hospitals in Korea

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    Background After the Middle East respiratory syndrome coronavirus outbreak in Korea in 2015, the Government established a strategy for infection prevention to encourage infection control activities in hospitals. The new policy was announced in December 2015 and implemented in September 2016. The aim of this study is to evaluate how infection control activities improved within Korean hospitals after the change in government policy. Methods Three cross-sectional surveys using the WHO Hand Hygiene Self-Assessment Framework (HHSAF) were conducted in 2013, 2015, and 2017. Using a multivariable linear regression model, we analyzed the change in total HHSAF score according to survey year. Results A total of 32 hospitals participated in the survey in 2013, 52 in 2015, and 101 in 2017. The number of inpatient beds per infection control professionals decreased from 324 in 2013 to 303 in 2015 and 179 in 2017. Most hospitals were at intermediate or advanced levels of progress (90.6% in 2013, 86.6% in 2015, and 94.1% in 2017). In the multivariable linear regression model, total HHSAF score was significantly associated with hospital teaching status (β coefficient of major teaching hospital, 52.6; 95% confidence interval [CI], 8.9 to 96.4; P = 0.018), beds size (β coefficient of 100 beds increase, 5.1; 95% CI, 0.3 to 9.8; P = 0.038), and survey time (β coefficient of 2017 survey, 45.1; 95% CI, 19.3 to 70.9; P = 0.001). Conclusions After the new national policy was implemented, the number of infection control professionals increased, and hand hygiene promotion activities were strengthened across Korean hospitals.This work supported by grants (2017 N-E2805–00) from Korea Centers for Disease Control, which had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript

    Loss of the Promyelocytic Leukemia Protein in Gastric Cancer: Implications for IP-10 Expression and Tumor-Infiltrating Lymphocytes

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    Gastric cancer is one of the most common causes of cancer-related mortality worldwide. Expression of the tumor suppressor, promyelocytic leukemia (PML) protein, is reduced or abolished in gastric carcinomas, in association with an increased level of lymphatic invasion, development of higher pTNM staging, and unfavorable prognosis. Herein, we investigated the relationship between the extent of tumor-infiltrating lymphocytes and the status of PML protein expression in advanced gastric carcinoma. We observed higher numbers of infiltrating T-cells in gastric carcinoma tissues in which PML expression was reduced or abolished, compared to tissues positive for PML. The extent of T-cell migration toward culture supernatants obtained from interferon-gamma (IFN-γ-stimulated gastric carcinoma cell lines was additionally affected by expression of PML in vitro. Interferon-gamma-inducible protein 10 (IP-10/CXCL10) expression was increased in gastric carcinoma tissues displaying reduced PML levels. Moreover, both Pml knockout and knockdown cells displayed enhanced IP-10 mRNA and protein expression in the presence of IFN-γ. PML knockdown increased IFN-γ-mediated Signal Transducer and Activator of Transcription-1 (STAT-1) binding to the IP-10 promoter, resulting in elevated transcription of the IP-10 gene. Conversely, PML IV protein expression suppressed IP-10 promoter activation. Based on these results, we propose that loss of PML protein expression in gastric cancer cells contributes to increased IP-10 transcription via enhancement of STAT-1 activity, which, in turn, promotes lymphocyte trafficking within tumor regions

    Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

    Membrane fouling indicator of effluent organic matter with nanofiltration for wastewater reclamation, as obtained from flow field-flow fractionation

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    Membrane filtration processes, due to their great performance, have been recognized as one of the effective technologies for the reclamation of wastewater, especially for the removals of inorganic/organic micropollutants and wastewater effluent organic matter (EfOM). Although the attraction of membrane filtration is remarkable, membrane fouling is a major obstacle to its usage; thus, the degree of fouling can have a significant impact on the cost, design and operation of full-scale facilities. In this study, the propensity for membrane fouling by EfOM was investigated using a flow field-flow fractionation (FIFFF) technique by comparing two different nanofiltration (NF) membranes: meta-phenylene diamine (MPD) versus piperazine based polyamides. From the characterizations of EfOM with FIFFF, the mutual interaction between the membrane surface and solutes was elucidated from the shape of elution peak and the hydrodynamic sizes with respect to the different membrane properties. Therefore, the propensities for fouling of the two NF membranes by EfOM were evaluated in relation to the membrane characteristics. Finally, several indicators of the potential for membrane fouling have been suggested in this study. This FIFFF technique can not only characterize the physicochemical properties of EfOM based on certain membrane properties, but can also provide a quick and easy evaluation of the potential for membrane fouling in terms of the suggested indicators. Furthermore, this technique is expected to contribute to the optimal design of membrane systems through the optimum selection of membranes for water and wastewater treatment. (C) 2010 Elsevier B.V. All rights reservedclose7

    The 18S ribosomal RNA gene of an anthozoan Anthopleura Kurogane:

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