Spatial multi-objective land use optimization toward livability based on boundary-based genetic algorithm: A case study in Singapore

Singapore Management University; Ministry of Education, Singapore under its Academic Research Funding Tier

Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR Errors

Multimodal sentiment analysis has attracted increasing attention and lots of models have been proposed. However, the performance of the state-of-the-art models decreases sharply when they are deployed in the real world. We find that the main reason is that real-world applications can only access the text outputs by the automatic speech recognition (ASR) models, which may be with errors because of the limitation of model capacity. Through further analysis of the ASR outputs, we find that in some cases the sentiment words, the key sentiment elements in the textual modality, are recognized as other words, which makes the sentiment of the text change and hurts the performance of multimodal sentiment models directly. To address this problem, we propose the sentiment word aware multimodal refinement model (SWRM), which can dynamically refine the erroneous sentiment words by leveraging multimodal sentiment clues. Specifically, we first use the sentiment word position detection module to obtain the most possible position of the sentiment word in the text and then utilize the multimodal sentiment word refinement module to dynamically refine the sentiment word embeddings. The refined embeddings are taken as the textual inputs of the multimodal feature fusion module to predict the sentiment labels. We conduct extensive experiments on the real-world datasets including MOSI-Speechbrain, MOSI-IBM, and MOSI-iFlytek and the results demonstrate the effectiveness of our model, which surpasses the current state-of-the-art models on three datasets. Furthermore, our approach can be adapted for other multimodal feature fusion models easily. Data and code are available at https://github.com/albertwy/SWRM.Comment: Findings of ACL 202

Preparation of Magnesium Ammonium Phosphate Mortar by Manufactured Limestone Sand Using Compound Defoaming Agents for Improved Strength and Impermeability

Magnesium ammonium phosphate cement (MAPC) mortar has recently risen up as high performance rapid repair material for concrete structures. But high costs of the raw materials limit its restoration and maintenance projects on a wide application range. This study proposes the use of manufactured limestone sand with lower cost and wider range of sources in replacement of quartz sand as fine aggregates to produce MAPC mortar. However, the limestone fines of manufactured sand were initially found to have negative effects on the performance of MAPC mortar, causing significant blistering and volume expansion and decreased compressive strength and interfacial bonding strength. To minimize these negative effects, polyether modified silicone (PMS) defoamer and its compound use with mineral admixtures Portland cement and silica fume were investigated on the effectiveness in reducing expansion and improving other properties of MAPC mortar. Results showed that the compound use of PMS defoamer and Portland cement as a new defoaming formula effectively reduced the volume expansion from 7.92% to 0.91%. The compressive strength and interfacial bonding strength were significantly improved by over 34% and 60% respectively. Moreover, this defoaming formula showed improvements in water-tight performance and resistance to chloride penetration. According to the mercury intrusion porosimetry (MIP) analysis, the total porosity of MAPC mortar after defoaming treatment was decreased by about 40% and the pore structure was also modified to be finer by significantly reducing the harmful macropores. Overall, the use of manufactured limestone sands as fine aggregates turned out to be a feasible and economic approach for promoting the filed application of MAPC mortar.</jats:p

A national dataset of 30 m annual urban extent dynamics (1985–2015) in the conterminous United States

Dynamics of the urban extent at fine spatial and temporal resolutions over large areas are crucial for developing urban growth models and achieving sustainable development goals. However, there are limited practices of mapping urban dynamics with these two merits combined. In this study, we proposed a new method to map urban dynamics from Landsat time series data using the Google Earth Engine (GEE) platform and developed a national dataset of annual urban extent (1985–2015) at a fine spatial resolution (30 m) in the conterminous United States (US). First, we derived the change information of urbanized years in four periods that were determined from the National Land Cover Database (NLCD), using a temporal segmentation approach. Then, we classified urban extents in the beginning (1985) and ending (2015) years at the cluster level through the implementation of a change vector analysis (CVA)-based approach. We also developed a hierarchical strategy to apply the CVA-based approach due to the spatially explicit urban sprawl over large areas. The overall accuracy of mapped urbanized years is around 90 % with the 1-year tolerance strategy. The mapped urbanized areas in the beginning and ending years are reliable, with overall accuracies of 96 % and 88 %, respectively. Our results reveal that the total urban area increased by about 20 % during the period of 1985–2015 in the US, and the annual urban area growth is not linear over the years. Overall, the growth pattern of urban extent in most coastal states is plateaued over the past three decades while the states in the Midwestern US show an accelerated growth pattern. The derived annual urban extents are of great use for relevant urban studies such as urban area projection and urban sprawl modeling over large areas. Moreover, the proposed mapping framework is transferable for developing annual dynamics of urban extent in other regions and even globally. The data are available at https://doi.org/10.6084/m9.figshare.8190920.v2 (Li et al., 2019c)

SIRT2 regulates macrophage chemotaxis by de-modifying histone H4K8 lactylation

Objective·To explore the regulatory role of silent information regulator 2 (SIRT2) in modulating the immune phenotype of macrophages after infection by removing the lactylation at H4K8 site of histone and the corresponding mechanism.Methods·Human THP-1 leukemia cells were induced by phorbol 12-myristate 13-acetate (PMA) and stimulated by lipopolysaccharide (LPS) to establish a macrophage infection model. Macrophages without LPS treatment (pTHP-1) were set as the control (CTRL) group, and macrophages with LPS treatment were set as the infected (LPS) group. Western blotting was used to detect the level of histone modification and SIRT2 protein in macrophages. RT-qPCR was used to detect the expression level of glycolytic key enzymes [phosphofructokinase liver type (PFKL), lactate dehydrogenase A (LDHA)] and modulators genes hypoxia inducible factor 1α (HIF-1α), and the expression level of Sirtuin genes and HDAC genes between the two groups. Transwell was used to detect the ability of macrophage chemotaxis. Lentivirus packaging and cell infection were used to construct SIRT2 overexpression cell line. The interaction analysis method of RNA sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) was used to analyze the difference and pathway enrichment of the genes specifically bound to H4K8 lactylation (H4K8la).Results·Compared to the CTRL group, macrophage glycolysis was upregulated and the level of H4K8la was significantly increased in the LPS group (P0.05). The interactive analysis of ChIP-seq and RNA-seq revealed that chemotaxis-related genes were regulated by H4K8la, and macrophage chemotaxis ability significantly decreased after the overexpression of SIRT2 and downregulation of H4K8la (P<0.05).Conclusion·SIRT2 can change the expression of target genes related to chemotaxis by removing H4K8la modification, thereby reducing the chemotaxis ability of macrophages. Targeting SIRT2 and H4K8la modification may help control inflammation mediated by macrophages

An Experimental Investigation on the Effects of Limestone Fines in Manufactured Sands on the Performance of Magnesia Ammonium Phosphate Mortar

Magnesium ammonium phosphate cement (MAPC) prepared with ammonium dihydrogen phosphate (NH4H2PO4, ADP) and dead-burned Magnesium oxide (MgO) is a new type of rapid patch repair material for concrete structures. In order to reduce the material costs of MAPC mortar, manufactured limestone sands, being a more widely-available resource with lower cost, was investigated in this study as an alternative to quartz sands for the preparation of MAPC mortar. The limestone fines in manufactured sands were found to be the key factor that influences properties of MAPC mortar by causing bubbling and volume expansion before hardening. As a result, the mechanical strength of MAPC mortar decreased with the increasing content of limestone fines due to increased porosity. According to microstructure analysis, the mechanism of these negative effects can be inferred as the reaction between limestone fines and ADP with the gas generation of CO2 and NH3. This reaction mainly occurred during a short period before setting while most limestone fines remained unreactive in the hardened MAPC mortar. Based on the above detailed experimental findings on the effects of limestone fines in manufactured sand on the properties of MAPC mortar, this paper pointed out that effective defoaming methods for inhibiting bubbling was the key to the utilization of manufactured sands in preparation of high performance MAPC mortar.</jats:p

Characterization and health risk assessment of airborne pollutants in commercial restaurants in northwestern China: Under a low ventilation condition in wintertime

Impacts on indoor air quality of dining areas from cooking activities were investigated in eight categories of commercial restaurants including Szechwan Hotpot, Hunan, Shaanxi Noodle, Chinese Barbecue, Chinese Vegetarian, Korean Barbecue, Italian, and Indian, in Northwestern China during December 2011 to January 2012. Chemical characterization and health risk assessment for airborne carbonyls, and particulate-bound polycyclic aromatic hydrocarbons (PAHs) and heavy metals were conducted under low ventilation conditions in wintertime. The highest total quantified carbonyls (Sigma(carbonyls)) concentration of 313.6 mu g m(-3) was found in the Chinese Barbecue, followed by the Szechwan Hotpot (222.6 mu g m(-3)) and Indian (221.9 mu g m(-3)) restaurants. However, the highest Sigma(carbonyls) per capita was found at the Indian restaurant (4500 mu g capita(-1)), suggesting that cooking methods such as stir-fly and bake for spices ingredients released more carbonyls from thermal cooking processes. Formaldehyde, acetaldehyde, and acetone were the three most abundant species, totally accounting for &gt;60% of mass concentrations of the Sigma(carbonyls). Phenanthrene, chrysene, and benzo[a]anthracene were the three most abundant PAHs. Low molecular weight fraction (Sigma PAHs(&lt;= 178)) had the highest contributions accounting for 40.6%-65.7%, much greater than their heaver counterparts. Diagnostic PAHs ratios suggest that cooking fuel and environmental tobacco smoke (ETS) contribute to the indoor PAHs profiles. Lead was the most abundant heavy metal in all sampled restaurants. High quantity of nickel was also found in samples due to the emissions from stainless-steel made kitchen utensils and cookware and ETS. Cancer risk assessments on the toxic substances demonstrate that the working environment of dining areas were hazard to health. Formation of reactive organic species (ROS) from the cooking activities was evidenced by measurement of hydroxyl radical (center dot OH) formed from simulating particulate matter (PM) react with surrogate lung fluid. The highest center dot OH concentration of 294.4 ng m(-3) was detected in Chinese Barbecue. In addition, the elevation of the concentrations of PM and center dot OH after non-dining periods implies that the significance of formation of oxidizing-active species indoor at poor ventilation environments. (c) 2018 Elsevier B.V. All rights reserved