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| 3. |
- Hsu, Yu-Cheng, et al.
(författare)
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One-Pot Tandem Photoredox and Cross-Coupling Catalysis with a Single Palladium Carbodicarbene Complex
- 2018
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Ingår i: Angewandte Chemie International Edition. - : Wiley. - 1433-7851 .- 1521-3773. ; 57:17, s. 4622-4626
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Tidskriftsartikel (refereegranskat)abstract
- The combination of conventional transition-metal-catalyzed coupling (2e(-) process) and photoredox catalysis (1e(-) process) has emerged as a powerful approach to catalyze difficult cross-coupling reactions under mild reaction conditions. Reported is a palladium carbodicarbene (CDC) complex that mediates both a Suzuki-Miyaura coupling and photoredox catalysis for C-N bond formation upon visible-light irradiation. These two catalytic pathways can be combined to promote both conventional transition-metal-catalyzed coupling and photoredox catalysis to mediate C-H arylation under ambient conditions with a single catalyst in an efficient one-pot process.
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| 5. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)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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| 6. |
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| 7. |
- Chen, Weimin, et al.
(författare)
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Exciton spin relaxation in diluted magnetic semiconductor Zn1-xMnxSe/CdSe superlattices : Effect of spin splitting and role of longitudinal optical phonons
- 2003
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Ingår i: Physical Review B. Condensed Matter and Materials Physics. - 1098-0121 .- 1550-235X. ; 67:12
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Tidskriftsartikel (refereegranskat)abstract
- Exciton spin relaxation in diluted magnetic semiconductor (DMS) structures based on ZnMnSe is closely examined as a function of exciton spin splitting in an external magnetic field. A drastic increase in spin relaxation is observed when exciton spin splitting exceeds the longitudinal optical (LO) phonon energy. Direct experimental evidence has been provided from (1) spin injection from the DMS to an adjacent nonmagnetic quantum well that can be modulated by the LO-assisted spin relaxation and (2) hot exciton photoluminescence within the DMS where a spin flip is accompanied by the emission of one LO phonon.
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| 8. |
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| 9. |
- Ho, Hung Chak, et al.
(författare)
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Systematic identification of heat events associated with emergency admissions to enhance the heat-health action plan in a subtropical city: a data-driven approach
- 2022
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Ingår i: Environmental Science and Pollution Research. - : Springer Nature. - 0944-1344 .- 1614-7499. ; 29:59, s. 89273-89282
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Tidskriftsartikel (refereegranskat)abstract
- According to the United Nations Office for Disaster Risk Reduction (UNDRR), a heat-health action plan should address various impacts of hazards at different levels, including an early warning system to monitor risks and behaviour enhancement to increase disaster preparedness. It is necessary to comply with guidelines regarding heat duration/intensity. In this study, we developed a data-driven approach to rapidly and systematically estimate the impacts of various heat events on emergency admissions among the adult population (n = 7,086,966) in Hong Kong in order to enhance the heat-health action plan. Immediate, short-term, and long-term impacts determined by 1-day, 4-day, and 8-day windows were estimated to identify specific heat events suitable for early warnings. In addition, underestimated risk, determined by a continuous increase in heat risk after days without significant emergency admissions, was estimated to evaluate potential maladaptive behaviours among a specific subpopulation. Based on age- and gender-specific analyses, 1D, 1D1N, and 2D2N were observed to have a stronger immediate impact on emergency admissions. 1D1N and 2D2N also showed notable short-term and long-term impacts. Based on heat vulnerability factors (age and gender), 2D2N was a higher-priority extreme heat event for early warning measures than 1D1N. Furthermore, men aged 19 to 64 had the highest underestimated risk. Specifically, they had IRR values of 1.113 [1.087, 1.140], 1.061 [1.035, 1.087], and 1.069 [1.043, 1.095] during lag days 3-5 of 3D2N, respectively, possibly due to a lack of adaptive behaviour. By adopting our approach, the duration of heat events with significant health impacts can be identified in order to further enhance relevant heat stress information. This framework can be applied to other cities with a similar background for rapid assessment.
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| 13. |
- Zhou, Huiquan, et al.
(författare)
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Predicting Emergency Department Utilization among Older Hong Kong Population in Hot Season: A Machine Learning Approach
- 2022
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Ingår i: Information. - : MDPI. - 2078-2489. ; 13:9
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Tidskriftsartikel (refereegranskat)abstract
- Previous evidence suggests that temperature is associated with the number of emergency department (ED) visits. A predictive system for ED visits, which takes local temperature into account, is therefore needed. This study aimed to compare the predictive performance of various machine learning methods with traditional statistical methods based on temperature variables and develop a daily ED attendance rate predictive model for Hong Kong. We analyzed ED utilization among Hong Kong older adults in May to September from 2000 to 2016. A total of 103 potential predictors were derived from 1- to 14-day lag of ED attendance rate and meteorological and air quality indicators and 0-day lag of holiday indicator and month and day of week indicators. LASSO regression was used to identify the most predictive temperature variables. Decision tree regressor, support vector machine (SVM) regressor, and random forest regressor were trained on the selected optimal predictor combination. Deep neural network (DNN) and gated recurrent unit (GRU) models were performed on the extended predictor combination for the previous 14-day horizon. Maximum ambient temperature was identified as a better predictor in its own value than as an indicator defined by the cutoff. GRU achieved the best predictive accuracy. Deep learning methods, especially the GRU model, outperformed conventional machine learning methods and traditional statistical methods.
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| 14. |
- Kanai, M, et al.
(författare)
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- 2023
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