| 1. |
- Beal, Jacob, et al.
(author)
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Robust estimation of bacterial cell count from optical density
- 2020
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In: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Journal article (peer-reviewed)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 2. |
- Luo, Yifei, et al.
(author)
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Technology Roadmap for Flexible Sensors
- 2023
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In: ACS Nano. - : American Chemical Society. - 1936-0851 .- 1936-086X. ; 17:6, s. 5211-5295
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Research review (peer-reviewed)abstract
- Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.
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| 3. |
- Hu, Qitao, et al.
(author)
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Current gain and low-frequency noise of symmetric lateral bipolar junction transistors on SOI
- 2018
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In: 2018 48th European Solid-State Device Research Conference (ESSDERC). - 9781538654019 - 9781538654002 - 9781538654026 ; , s. 258-261
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Conference paper (peer-reviewed)abstract
- This paper presents a comprehensive study of symmetric lateral bipolar junction transistors (LBJTs) fabricated on SOI substrate using a CMOS-compatible process; LBJTs find many applications including being a local signal amplifier for silicon-nanowire sensors. Our LBJTs are characterized by a peak gain (β) over 50 and low-frequency noise two orders of magnitude lower than what typically is of the SiO 2 /Si interface for a MOSFET. β is found to decrease at low base current due to recombination in the space charge region at the emitter-base junction and at the surrounding SiO 2 /Si interfaces. This decrease can be mitigated by properly biasing the substrate.
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| 4. |
- Wang, Juan, et al.
(author)
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Identification of Quantitative Trait Nucleotides and Development of Diagnostic Markers for Nine Fatty Acids in the Peanut
- 2024
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In: Plants. - 2223-7747. ; 13:1
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Journal article (peer-reviewed)abstract
- The cultivated peanut (Arachis hypogaea L.) is an important oilseed crop worldwide, and fatty acid composition is a major determinant of peanut oil quality. In the present study, we conducted a genome-wide association study (GWAS) for nine fatty acid traits using the whole genome sequences of 160 representative Chinese peanut landraces and identified 6-1195 significant SNPs for different fatty acid contents. Particularly for oleic acid and linoleic acid, two peak SNP clusters on Arahy.09 and Arahy.19 were found to contain the majority of the significant SNPs associated with these two fatty acids. Additionally, a significant proportion of the candidate genes identified on Arahy.09 overlap with those identified in early studies, among which three candidate genes are of special interest. One possesses a significant missense SNP and encodes a known candidate gene FAD2A. The second gene is the gene closest to the most significant SNP for linoleic acid. It codes for an MYB protein that has been demonstrated to impact fatty acid biosynthesis in Arabidopsis. The third gene harbors a missense SNP and encodes a JmjC domain-containing protein. The significant phenotypic difference in the oleic acid/linoleic acid between the genotypes at the first and third candidate genes was further confirmed with PARMS analysis. In addition, we have also identified different candidate genes (i.e., Arahy.ZV39IJ, Arahy.F9E3EA, Arahy.X9ZZC1, and Arahy.Z0ELT9) for the remaining fatty acids. Our findings can help us gain a better understanding of the genetic foundation of peanut fatty acid contents and may hold great potential for enhancing peanut quality in the future.
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| 5. |
- Chen, Sinan, et al.
(author)
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Mitigation of DSS-Induced Colitis Potentially via Th1/Th2 Cytokine and Immunological Function Balance Induced by Phenolic-Enriched Buckwheat (Fagopyrum esculentum Moench) Bee Pollen Extract
- 2022
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In: Foods. - : MDPI AG. - 2304-8158. ; 11:9
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Journal article (peer-reviewed)abstract
- Colitis is an inflammatory disease that results from the overactivation of effector immune cells, producing a high quantity of pro-inflammatory cytokines. Our study aimed to explore whether buckwheat (F. esculentum) bee pollen extract (FBPE) could inhibit the progression of dextran sulfate sodium (DSS)-induced colitis via regulating immune function. We isolated and identified six main phenolic compounds of FBPE such as luteolin (9.46 mg/g) by column chromatography, HPLC-DAD, ESI-MS and NMR spectroscopy, then assessed their effects on colonic mucosal injury by clinical symptoms, histomorphology and immunohistochemistry examinations. The results showed that FBPE at 25.2 g/kg body weight (g/kg BW) changed the clinical symptoms of colitis, the ICAM-1 expression in colon, the activity of related inflammatory mediators in colon tissue and helped restore the immune system. Compared with the model group (40.28%), the CD4 positivity was significantly reduced in the HD (High-dose group: 25.2 g FBPE/kg BW/day) group (20.45%). Administration of 25.2 g/kg BW of FBPE decreased the IFN-gamma, TNF-alpha and IL-4 levels, while enhancing the IL-10 level, and significantly inhibited the abnormally decreased IgG (Model: 13.25 mg/mL, HD: 14.06 mg/mL), showing a reversal effect on the Th1/Th2 levels in colitis. These findings suggested that FBPE at 25.2 g/kg BW had the effects of alleviating colitis and immunomodulation, which can help in the development of safe and effective immune therapy.
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| 6. |
- Li, Xiangdong, et al.
(author)
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Predicting user visual attention in virtual reality with a deep learning model
- 2021
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In: Virtual Reality. - : Springer Science and Business Media LLC. - 1359-4338 .- 1434-9957. ; 25, s. 1123-1136
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Journal article (peer-reviewed)abstract
- Recent studies show that user's visual attention during virtual reality museum navigation can be effectively estimated with deep learning models. However, these models rely on large-scale datasets that usually are of high structure complexity and context specific, which is challenging for nonspecialist researchers and designers. Therefore, we present the deep learning model, ALRF, to generalise on real-time user visual attention prediction in virtual reality context. The model combines two parallel deep learning streams to process the compact dataset of temporal-spatial salient features of user's eye movements and virtual object coordinates. The prediction accuracy outperformed the state-of-the-art deep learning models by reaching record high 91.03%. Importantly, with quick parametric tuning, the model showed flexible applicability across different environments of the virtual reality museum and outdoor scenes. Implications for how the proposed model may be implemented as a generalising tool for adaptive virtual reality application design and evaluation are discussed.
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| 7. |
- Norbäck, Dan, et al.
(author)
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Prenatal and perinatal home environment and reported onset of wheeze, rhinitis and eczema symptoms in preschool children in Northern China
- 2021
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In: Science of the Total Environment. - : Elsevier. - 0048-9697 .- 1879-1026. ; 774
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Journal article (peer-reviewed)abstract
- Early life environment can affect asthma and allergies but few cohort studies on this issue are available from China. Our aim was to investigate reported onset of childhood wheeze, rhinitis and eczema symptoms in relation to prenatal, perinatal and postnatal home environment. Data on home environment and symptoms (ISAAC based questions) in first two years of life and in the past 12 months were reported by parents of the children (3-6 y) in a cross-sectional questionnaire survey in ten day care centers in Taiyuan, northern China (N = 3606). Changes of symptoms from the first 2 years of life to the past 12 months (recall period) were calculated retrospectively. Multilevel logistic regression analysis was applied. Reported onset of wheeze, rhinitis and eczema were 11.8%, 22.2% and 3.3%, respectively. Redecorating during pregnancy increased reported onset of rhinitis (OR = 2.29) and eczema (OR = 4.91). New furniture during pregnancy increased reported onset of rhinitis (OR = 1.47). Perinatal indoor mould increased reported onset of wheeze (OR = 1.51), rhinitis (OR = 1.65) and eczema (OR = 1.91). Perinatal mould odour increased reported onset of wheeze (OR = 1.85). Perinatal window pane condensation increased reported onset of wheeze (OR = 1.54) and rhinitis (OR = 1.24). Perinatal stuffy air and dry air in the home increased reported onset of all three symptoms (ORs 1.46-2.24). Dog keeping increased reported onset of wheeze (OR = 1.69) and eczema (OR = 2.13). Based on principal component analysis, four exposure scores were calculated (renovation, new furniture, mould and indoor air quality scores). Dose-response relationships were observed between these exposure scores and reported onset of symptoms. In conclusion, prenatal and postnatal exposure to emissions from renovation and new furniture can increase reported onset of childhood wheeze, rhinitis and eczema. Perinatal indoor mould, mould odour, condensation on window panes and impaired indoor air quality at home can be associated with reported development of wheeze, rhinitis and eczema in preschoolers in northern China. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
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| 8. |
- Wang, Juan, et al.
(author)
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The genetic base for peanut height-related traits revealed by a meta-analysis
- 2021
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In: Plants. - : MDPI AG. - 2223-7747. ; 10:6
-
Journal article (peer-reviewed)abstract
- Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide, and peanut height has been shown to be closely related to yield, therefore a better understanding of the genetic base of plant height-related traits may allow us to have better control of crop yield. Plant height-related traits are quantitative traits that are genetically controlled by many genes, and distinct quantitive trait loci (QTLs) may be identified for different peanut accessions/genotypes. In the present study, in order to gain a more complete picture of the genetic base for peanut height-related traits, we first make use of the high quality NGS sequence data for 159 peanut accessions that are available within our research groups, to carry out a GWAS study for searching plant height-related regions. We then perform a literature survey and collect QTLs for two plant height-related traits (Ph: peanut main stem height, and Fbl: the first branch length) from earlier related QTL/GWAS studies in peanut. In total, we find 74 and 21 genomic regions that are, associated with traits Ph and Fbl, respectively. Annotation of these regions found a total of 692 and 229 genes for, respectively, Ph and Fbl, and among those genes, 158 genes are shared. KEGG and GO enrichment analyses of those candidate genes reveal that Ph-and Fbl-associated genes are both enriched in the biosynthesis of secondary metabolites, some basic processes, pathways, or complexes that are supposed to be crucial for plant development and growth.
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| 9. |
- Zhang, Xiaoning, et al.
(author)
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Smart real-time evaluation of tunnel fire risk and evacuation safety via computer vision
- 2024
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In: Safety Science. - 0925-7535. ; 177
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Journal article (peer-reviewed)abstract
- The distribution of vehicles during a tunnel fire is a crucial factor that affects fire development and hazards, as well as the following evacuation and rescue operations. This work proposed a novel method using computer vision for assessing the real-time tunnel fire risk and evacuation safety by considering the classification and entry flow of vehicles. The proposed system utilizes YOLOv7 and DeepSORT for vehicle detection, classification, and tracking to enable a real-time digital twin for tunnel fire safety management. Vehicles are divided into 10 categories, in terms of their size, usage, number of passengers, fuel load, and peak fire HRR. After monitoring the vehicle flow at the tunnel portals, the real-time vehicle and fire load distribution are predicted. Then, the real-time tunnel fire scenarios and the safety of the evacuation process are evaluated based on the distribution of vehicles. The system is demonstrated in real road tunnels with traffic video cameras and exhibits a robust performance. The proposed vision-based real-time tunnel fire risk evaluation enables intelligent daily fire safety management and supports fire emergency response and decision-making.
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