DataSheet1_Low-carbon economic operation of IES based on life cycle method and hydrogen energy utilization.PDF

The Integrated Energy System (IES) that coordinates multiple energy sources can effectively improve energy utilization and is of great significance to achieving energy conservation and emission reduction goals. In this context, a low-carbon and economic dispatch model for IES is proposed. Firstly, a hydrogen energy-based IES (H2-IES) is constructed to refine the utilization process of hydrogen energy. Secondly, the carbon emissions of different energy chains throughout their life cycle are analyzed using the life cycle assessment method (LCA), and the carbon emissions of the entire energy supply and demand chain are considered. Finally, a staged carbon trading mechanism is adopted to promote energy conservation and emission reduction. Based on this, an IES low-carbon and economic dispatch model is constructed with the optimization goal of minimizing the sum of carbon trading costs, energy procurement costs, and hydrogen sales revenue, while considering network constraints and constraints on key equipment. By analyzing the model under different scenarios, the introduction of life cycle assessment, staged carbon trading, and hydrogen energy utilization is shown to promote low-carbon and economic development of the comprehensive energy system.</p

Flowchart of the experiment.

<p>The figure illustrates one trial of the experiment, beginning with a rest period (4 s) and continuing with a visual presentation of a pain or non-pain picture for 3 s, followed by another rest period of 2 s, and a response period of 2 s during which subjects pressed left or right button on a response pad to indicate whether the photograph depicted a pain or non-pain scene.</p

Signal detection analysis.

<p>Output from signal detection analysis including average scores (mean ± SD) for hit rate, false alarms, sensitivity index (d’) and response bias. T values and P values from statistical comparisons of each group are also shown.</p><p>Signal detection analysis.</p

Participant Age, Pain Catastrophizing Scale and Interpersonal Reactivity Scale scores.

<p>Age, Pain Catastrophizing Scale (PCS) and Interpersonal Reactivity (IRI) Scale scores (mean ± SD) are shown for high and low pain catastrophising groups. T values (with degrees of freedom), P values and effect sizes (Cohen’s d’) for statistical comparisons are also shown. For pain catastrophising, the output of the Mann-Whitney U test is shown.</p><p>Participant Age, Pain Catastrophizing Scale and Interpersonal Reactivity Scale scores.</p

Self-report picture ratings.

<p>Bar charts with standard error bars illustrate mean values for ratings of affective valence, arousal and pain in High-Cat and Low-Cat groups for both types of pictures. HP = High-Cat pain pictures, HN = High-Cat non-pain, LP = Low-Cat pain pictures, LN = Low-Cat non-pain.</p

Source dipole model and source waveforms.

<p><b>A.</b> The grand average waveforms of four equivalent source dipoles and their isopotential line maps. The isopotential maps were plotted at the temporal maxima, highlighted with an arrow and labelled with the latency value. The source dipoles are numbered from 1 to 4. <b>B.</b> CLARA source activation maps and source dipole locations of four cortical sources. The peak latency of each source corresponds to that in panel A. A = anterior, P = posterior, L = left, R = right. The numbering of dipoles corresponds to that in A. 1 = blue dipole, 2 = green dipole, 3 = ice blue dipole, 4 = magenta dipole. <b>C.</b> The grand average waveforms of four equivalent source dipoles, numbered from 1 to 4, in high and low pain catastrophising groups during viewing pain and non-pain scenes. Red line = pain photographs in High-Cat group, blue line = non-pain photographs in High-Cat group, black line = pain photographs in Low-Cat group, green line = non-pain photographs in Low-Cat group. The grey-filled rectangles indicate epochs used in statistical analyses. <b>D</b>. Bar chart of mean source activations and standard error bars for each condition during time windows of interest identified by permutation analysis (grey rectangles).</p

Correlations between sources activations and subjective ratings.

<p>Spearman’s correlations (Rho and P values) for the difference between pain and non-pain pictures in source activations and subjective ratings of valence, arousal and pain. Correlation is significant at the P<0.05 level (two-tailed) following Bonferroni-Šidák correction for multiple tests.</p><p>Correlations between sources activations and subjective ratings.</p

Correlations between source components and picture ratings.

<p>Scatter plots and the linear regression lines illustrating relationships between subjective ratings of valence, arousal and pain attributed to visual stimuli and the source amplitude differences between two conditions in the posterior cingulate source dipole in the interval of from 756 to 1144 ms. <b>A.</b> Valence. <b>B.</b> Arousal. <b>C.</b> Pain. High-Cat = high pain catastrophisers, dark circles, solid line. Low-Cat = low pain catastrophisers, white circles, dashed line.</p

Valence, arousal and pain ratings attributed to pictures.

<p>Average ratings (mean ± SD) for valence arousal and pain attributed to pain and non-pain pictures in high, and low, pain catastrophising groups. F values (with degrees of freedom), P values and effect sizes (η²_<i>p</i>) for ANOVA comparisons are also shown. C = main effect of catastrophising, P = main effect of picture type, C*I = interaction effect.</p><p>Valence, arousal and pain ratings attributed to pictures.</p

sj-docx-1-chl-10.1177_17475198221089833 – Supplemental material for A visible-light-responsive DiSCn(3)-type fluorescent probe for the rapid, sensitive, and specific detection of tin(II) ions in aqueous solution

Supplemental material, sj-docx-1-chl-10.1177_17475198221089833 for A visible-light-responsive DiSCn(3)-type fluorescent probe for the rapid, sensitive, and specific detection of tin(II) ions in aqueous solution by Ruiji Li, Dong Wang, Xiaoyun Li, Zehui Zhang and Wei Li in Journal of Chemical Research</p