Efficient red thermally activated delayed fluorescence emitters achieved through precise control of excited state energy levels.

The variety of highly efficient red/near-infrared (NIR) materials with thermally activated delayed fluorescence (TADF) feature is extremely limited so far, and it is necessary to expand the candidate pool of excellent red/deep-red emitters. However, how to control the energy level alignment of the 1CT (singlet charge transfer) state and the 3LE (triplet local excitation) state to improve the emission efficiency of materials remains a challenge. Herein, based on our previously reported green fluorescent material 67dTPA-FQ, three new donor-acceptor type TADF materials (TQ-oMeOTPA, TsQ-oMeOTPA and SQ-oMeOTPA) were designed by introducing 4,4'-dimethoxy triphenylamine (MeOTPA) as the donor, and introduced S atoms on the acceptors to enhance the spin-orbit coupling (SOC) and CT effects. The theoretical calculations showed that the newly introduced MeOTPA and S atom successfully enhanced the CT effect of the materials, not only shifting the luminescence peak to the deep red region but also effectively adjusting the energy level alignment of the excited state, accelerating the reverse intersystem crossing process. Finally, the organic light-emitting diodes based on SQ-oMeOTPA exhibit an external quantum efficiency of 19.1%, with an emission peak at 619 nm. This work not only expands the candidate inventory of red TADF materials, but also proves the feasibility of designing emitters by adjusting the excited state energy levels, greatly broadening the diversity of TADF emitters in design, and providing a powerful means for rapidly screening efficient emitters in the future.

Carbon fluxes of China's coastal wetlands and impacts of reclamation and restoration.

Coastal wetlands play an important role in regulating atmospheric carbon dioxide (CO2) concentrations and contribute significantly to climate change mitigation. However, climate change, reclamation, and restoration have been causing substantial changes in coastal wetland areas and carbon exchange in China during recent decades. Here we compiled a carbon flux database consisting of 15 coastal wetland sites to assess the magnitude, patterns, and drivers of carbon fluxes and to compare fluxes among contrasting natural, disturbed, and restored wetlands. The natural coastal wetlands have the average net ecosystem exchange of CO2 (NEE) of -577 g C m-2 year-1, with -821 g C m-2 year-1 for mangrove forests and -430 g C m-2 year-1 for salt marshes. There are pronounced latitudinal patterns for carbon dioxide exchange of natural coastal wetlands: NEE increased whereas gross primary production (GPP) and respiration of ecosystem decreased with increasing latitude. Distinct environmental factors drive annual variations of GPP between mangroves and salt marshes; temperature was the dominant controlling factor in salt marshes, while temperature, precipitation, and solar radiation were co-dominant in mangroves. Meanwhile, both anthropogenic reclamation and restoration had substantial effects on coastal wetland carbon fluxes, and the effect of the anthropogenic perturbation in mangroves was more extensive than that in salt marshes. Furthermore, from 1980 to 2020, anthropogenic reclamation of China's coastal wetlands caused a carbon loss of ~3720 Gg C, while the mangrove restoration project during the period of 2021-2025 may switch restored coastal wetlands from a carbon source to carbon sink with a net carbon gain of 73 Gg C. The comparison of carbon fluxes among these coastal wetlands can improve our understanding of how anthropogenic perturbation can affect the potentials of coastal blue carbon in China, which has implications for informing conservation and restoration strategies and efforts of coastal wetlands.

Nomogram-Based Risk Stratification to Identify Patients with T3N0M0 Breast Cancer with Survival Benefit from Postmastectomy Radiotherapy.

BACKGROUND: The survival benefit of postmastectomy radiotherapy (PMRT) for patients with T3N0M0 breast cancer remains controversial. This study aimed to identify patients with a survival benefit from PMRT by developing a novel risk stratification model. PATIENTS AND METHODS: The study recruited 2062 patients with pT3N0M0 breast cancer from the Surveillance, Epidemiology, and End Results (SEER) database who underwent mastectomy between 2010 and 2019. Overall survival (OS) and breast-cancer-specific survival (BCSS) prognostic nomograms based on multivariate Cox regression were constructed to quantify the survival risk and classify patients into low- and high-risk groups. Subgroup analyses were undertaken to assess the role of PMRT according to age and risk stratification. RESULTS: In the overall cohort, PMRT was beneficial in improving OS in patients with pT3N0 breast cancer (5-year OS, non-PMRT versus PMRT: 76.6% vs. 84.2%, P < 0.001), while the benefit on BCSS was not significant (P = 0.084). On the basis of the risk stratification nomogram, in the high-risk group, PMRT improved OS in young patients by 10.1%, OS in elderly patients by 12.4%, and BCSS by 10.2% (P < 0.05), but the use of PMRT in the low-risk group did not improve OS and BCSS in all patients (P > 0.05). CONCLUSIONS: We presented a new method for quantifying risk using the nomogram to identify patients with high risk of pT3N0M0 breast cancer. This study found that older patients in the newly constructed high-risk group benefited from OS and BCSS benefits from PMRT, while for younger high-risk patients, there was only a benefit in terms of OS.

Evapotranspiration dynamics and their drivers in a temperate mixed forest in northeast China.

Evapotranspiration (ET) is a vital part of the global water cycle and is closely related to carbon sequestration. Analysing ET dynamics and their drivers would benefit for improving our understanding of the global water and carbon cycles. Using an eddy covariance (EC) approach, we analysed ET dynamics and their drivers in a temperate mixed forest over northeast China from 2016 to 2017. The results showed that 43.55% of our eddy covariance data passed the quality control. In addition, the energy balance ratio was 0.62, indicating that measurements were reliable. The measured ET showed clear single peak patterns with seasonal and diurnal variations. The daily ET ranged from 0 to 7.75 mm d-1 and the hourly ET ranged from 0 to 0.28 mm h-1. The ranges of hourly ET floated from 0 to 0.05 mm h-1 at non-growing season (November to April) while ranged from 0 to 0.28 mm h-1 at active growing season (May to October). The diurnal ET dynamics during the non-growing season were driven by air temperature (T a), but were governed by global radiation (R g) during the active growing season. Leaf area index (LAI) comprehensively reflected the variations of T a and R g, and was found to be the primary factor shaping the seasonal dynamics of ET. The annual ET rates were 501.91 ± 5.30 mm year-1 and 554.60 ± 11.24 mm year-1 for 2016 and 2017, respectively. Therefore, energy supply, represented by T a and R g, governed ET dynamics in our temperate mixed forest, while variables representing the energy supply affecting ET dynamics differed among seasons and time scales. ET dynamics indicated that a temperate mixed forest is important to the global water cycle. Our results improved our understanding of ET dynamics in the studied region.

Real-Time 3D Reconstruction Method Based on Monocular Vision.

Real-time 3D reconstruction is one of the current popular research directions of computer vision, and it has become the core technology in the fields of virtual reality, industrialized automatic systems, and mobile robot path planning. Currently, there are three main problems in the real-time 3D reconstruction field. Firstly, it is expensive. It requires more varied sensors, so it is less convenient. Secondly, the reconstruction speed is slow, and the 3D model cannot be established accurately in real time. Thirdly, the reconstruction error is large, which cannot meet the requirements of scenes with accuracy. For this reason, we propose a real-time 3D reconstruction method based on monocular vision in this paper. Firstly, a single RGB-D camera is used to collect visual information in real time, and the YOLACT++ network is used to identify and segment the visual information to extract part of the important visual information. Secondly, we combine the three stages of depth recovery, depth optimization, and deep fusion to propose a three-dimensional position estimation method based on deep learning for joint coding of visual information. It can reduce the depth error caused by the depth measurement process, and the accurate 3D point values of the segmented image can be obtained directly. Finally, we propose a method based on the limited outlier adjustment of the cluster center distance to optimize the three-dimensional point values obtained above. It improves the real-time reconstruction accuracy and obtains the three-dimensional model of the object in real time. Experimental results show that this method only needs a single RGB-D camera, which is not only low cost and convenient to use, but also significantly improves the speed and accuracy of 3D reconstruction.

[Urban heat island intensity and its grading in Liaoning Province of Northeast China].

According to the recorded air temperature data and their continuity of each weather station, the location of each weather station, the numbers of and the distances among the weather stations, and the records on the weather stations migration, several weather stations in Liaoning Province were selected as the urban and rural representative stations to study the characteristics of urban heat island (UHI) intensity in the province. Based on the annual and monthly air temperature data of the representative stations, the ranges and amplitudes of the UHI intensity were analyzed, and the grades of the UHI intensity were classified. The Tieling station, Dalian station, Anshan station, Chaoyang station, Dandong station, and Jinzhou station and the 18 stations including Tai' an station were selected as the representative urban and rural weather stations, respectively. In 1980-2009, the changes of the annual UHI intensity in the 6 representative cities differed. The annual UHI intensity in Tieling was in a decreasing trend, while that in the other five cities was in an increasing trend. The UHI intensity was strong in Tieling but weak in Dalian. The changes of the monthly UHI intensity in the 6 representative cities also differed. The distribution of the monthly UHI intensity in Dandong, Jinzhou and Tieling took a "U" shape, with the maximum and minimum appeared in January and in May-August, respectively, indicating that the monthly UHI intensity was strong in winter and weak in summer. The ranges of the annual and monthly UHI intensity in the 6 cities were 0.57-2.15 degrees C and -0.70-4.60 degrees C, and the ranges of 0.5-2.0 degrees C accounted for 97.8% and 72.3%, respectively. The UHI intensity in the province could be classified into 4 grades, i. e., weak, strong, stronger and strongest.

[Characteristics of CO2 flux before and in the heating period at urban complex underlying surface area].

Urban areas were significant contributors to global carbon dioxide emissions. The eddy covariance (EC) was used to measure carbon dioxide (CO2) concentration and flux data at urban area in Shenyang. This research analyzed the characteristics of atmospheric CO2 concentration and flux in October 2008 to November 2008 period before and in the heating period. The results showed that the daily variation of CO2 concentration was two-peak curve. The first peak time appeared as same as sunrise time, while the second peak time impacted by vehicles and heating. The result of CO2 flux showed that urban atmospheric CO2 was net emissions, vegetation photosynthesis absorbed CO2 of traffic, the CO2 flux peak appeared at 17:15-18:15 in the heating period, CO2 emission increased 29.37 g x (m2 x d)(-1) in the heating period than that before the heating period; there was corresponding relationship between CO2 flux and the time when temperature peak and sensible heating flux (Hc) turn positive. The results also indicated that atmospheric CO2 concentration and its flux were affected seriously by both wind direction and carbon sources.

[Vertical distribution of soil organic carbon and total nitrogen in reed wetland].

With element analyzer, this paper measured the variation of organic carbon and total nitrogen in different soil depths of reed wetland. The results showed that soil organic carbon, total nitrogen, and C/N ratio were decreased gradually with increasing soil depth, and their accumulation peaks were differed with soil layers and months. Soil temperature and moisture and the growth status of reed were the main factors caused the differences. Soil organic carbon was strongly positively correlated with soil total nitrogen content in July, August and October, the R2 being 0.73, 0.73 and 0.71 respectively, but weakly correlated in September. Soil C/N ratio was negatively correlated to soil organic carbon and total nitrogen, but the correlativity was higher with soil total nitrogen than with soil organic carbon, suggesting that soil C/N ratio was more determined by the content of soil total nitrogen.