Materials with circularly polarized luminescence properties have attracted wide attention in recent years. One of the most important applications of these materials is for circularly polarized ...organic light emitting diodes (CP-OLEDs), which have potential application in 3D displays. Chiral conjugated polymers, small organic molecules and metal complexes have already been employed as emitters for CP-OLEDs. Benefiting from the ability to harvest both singlet and triplet excitons, chiral phosphorescent metal complexes always show outstanding device performance. In this article we briefly discuss the recent progress, current challenges and out look of chiral phosphorescent metal complexes.
Chiral phosphorescent metal complexes always show outstanding CP-OLED performances. But unfortunately, the dissymmetry
g
factors are only at the 10
−4
-10
−2
level. A balance between these two elements is the main point for future work in this area.
A spiro‐axis skeleton not only introduces circularly polarized luminescence (CPL) into thermally activated delayed fluorescence (TADF) molecules but also enhances the intramolecular through space ...charge transfer (TSCT) process. Spiral distributed phenoxazine and 2‐(trifluoromethyl)‐9H‐thioxanthen‐9‐one‐10,10‐dioxide act as donor and acceptor units, respectively. The resulting TADF enantiomers, (rac)‐OSFSO, display emission maxima at 470 nm, small singlet‐triplet energy gap (ΔEST) of 0.022 eV and high photoluminescence quantum yield (PLQY) of 81.2 % in co‐doped film. The circularly polarized OLEDs (CP‐OLEDs) based on (R)‐OSFSO and (S)‐OSFSO display obvious circularly polarized electroluminescence (CPEL) signals with dissymmetry factor up to 3.0×10−3 and maximum external quantum efficiency (EQEmax) of 20.0 %. Moreover, the devices show remarkably low efficiency roll‐off with an EQE of 19.3 % at 1000 cd m−2 (roll‐off ca. 3.5 %), which are among the top results of CP‐OLEDs.
A chiral spiro‐axis skeleton introduced the circularly polarized luminescence property into TADF molecules and enhanced the intramolecular through space charge transfer process. The resulting TADF enantiomers display obvious CPEL signals with |gEL| factor up to 3.0×10−3 and EQE of 20.0 % with remarkably low efficiency roll‐off, which are among the top results of CP‐OLEDs.
•An intelligent surrogate model is proposed for predicting soil creep index.•Three best models are recommended for engineering practice.•The robustness of intelligent models is evaluated by ...additional unseen dataset.
Long-term settlement issues in engineering practice are controlled by the creep index, Cα, but current empirical models of Cα are not sufficiently reliable. In a departure from previous correlations, this study proposes a hybrid surrogate intelligent model for predicting Cα. The new combined model integrates a meta-heuristic particle optimization swarm (PSO) in the random forest (RF) to overcome the user experience dependence and local optimum problems. A total of 151 datasets having four parameters (liquid limit wL, plasticity index Ip, void ratio e, clay content CI) and one output variable Cα are collected from the literature. Eleven combinations of these four parameters (one with four parameters, four with three parameters and six with two parameters) are used as input variables in the RF algorithm to determine the optimal combination of variables. In this novel model, PSO is employed to determine the optimal hyper-parameters in the RF algorithm, and the fitness function in the PSO is defined as the mean prediction error for 10 cross-validation sets to enhance the robustness of the RF model. The performance of the RF model is compared specifically with the existing empirical formulae. The results indicate that the combinations IP–e, CI–IP–e and CI–wL–Ip–e are optimal RF models in their respective groups, recommended for predicting Cα in engineering practice. What’s more, these three proposed models demonstrably outperform empirical methods, featuring as they do lower levels of prediction error. Parametric investigation indicates that the relationships between Cα and the four input variables in the proposed RF models harmonize with the physical explanation. A Gini index generated during the RF process indicates that Cα is much more sensitive to e than to CI, Ip and wL, in that order – although the difference among the latter three variables can be negligible.
Infrared small target detection is still a challenge in the field of object detection. At present, although there are many related research achievements, it surely needs further improvement. This ...paper introduced a new application of severely occluded vehicle detection in the complex wild background of weak infrared camera aerial images, in which more than 50% area of the vehicles are occluded. We used YOLOv4 as the detection model. By applying secondary transfer learning from visible dataset to infrared dataset, the model could gain a good average precision (AP). Firstly, we trained the model in the UCAS_AOD visible dataset, then, we transferred it to the VIVID visible dataset, finally we transferred the model to the VIVID infrared dataset for a second training. Meanwhile, added the hard negative example mining block to the YOLOv4 model, which could depress the disturbance of complex background thus further decrease the false detecting rate. Through experiments the average precision improved from90.34% to 91.92%, the F1 score improved from 87.5% to 87.98%, which demonstrated that the proposed algorithm generated satisfactory and competitive vehicle detection results.
•Introducing a standard process of building a machine learning based settlement prediction model.•Hybrid meta-heuristic and machine learning algorithms is proposed.•Gini importance index is employed ...to investigate the importance of input parameters.
Machine learning (ML) algorithms have been gradually used in predicting tunneling-induced settlement, but there is no uniform process for establishing ML models and even obviously exists deficiency in the existing settlement prediction ML models. This study systematically demonstrates the process of application of machine learning (ML) algorithms in predicting tunneling-induced settlement. The whole process can be categorized into four phases: the selection of ML algorithms, the determination of optimum-hyper-parameters, the improvement in model robustness and sensitivity analysis. The prediction performance of five commonly used ML algorithms back-propagation (BPNN), general regression neural network (GRNN), extreme learning machine (ELM), support vector machine (SVM) and random forest (RF) was comprehensively compared. The results indicate that proposed hybrid intelligent algorithm with the integration of the meta-heuristic algorithm particle swarm optimization (PSO) and ML can effectively determine the global optimum hyper-parameters of ML algorithms. The mean prediction error of k-fold cross-validation sets defined as the fitness function of the PSO algorithm can improve the robustness of ML models. RF algorithm outperforms the remaining four ML algorithms in recognizing the evolution of tunneling-induced settlement. BPNN shows great extrapolation capability, so it is recommended to establish settlement prediction model if the existing datasets are small. Sensitivity analysis indicates the geological and geometric parameters are the most influential variables for the settlement.
In this study, we report the first circularly polarized white organic light‐emitting diodes (CP‐WOLEDs) based on all thermally activated delayed fluorescence (TADF) materials. Two pairs of spiro‐type ...TADF enantiomers, (R/S)‐SPOCN (5,5′‐((2,2′,3,3′‐tetrahydro‐1,1′‐spirobiindene‐7,7′‐diyl)bis(oxy))bis(4‐(10H‐phenoxazin‐10‐yl)phthalonitrile)) and (R/S)‐OSFSO (2′‐(trifluoromethyl)‐spiroquinolino3,2,1‐klphenoxazine‐9,9′‐thioxanthene‐10′,10′‐dioxide), serve as emitters with complementary emission. The CP‐OLEDs exhibit warm white emission with a CIE coordinate of (0.35, 0.46). Besides, decent device performances are observed with an external quantum efficiency of up to 21.6 % at maximum and 11.8 % at 1000 cd m−2. Obvious circularly polarized electroluminescence signals are detected with a dissymmetry factor |gEL| of around 3.0×10−3. This is the first report of CP‐WOLEDs that can harvest both singlet and triplet excitons, which provides a feasible strategy for the development of CP‐WOLEDs with remarkable device performances.
Circularly polarized white organic light‐emitting diodes that can harvest both singlet and triplet excitons have been developed by combining two pairs of spiro‐type circularly polarized delayed fluorescence enantiomers with complementary emissions as chiral emissive layers. Remarkable device performances are observed, with an external quantum efficiency of up to 21.6 % and intense circularly polarized luminescence having a |gEL| factor of 3.0×10−3.
Triclosan (TCS) is a broad-spectrum antimicrobial agent that is frequently used in pharmaceuticals and personal care products. Reports have shown that TCS is a potential endocrine disruptor; however, ...the potential effects of TCS on placental endocrine function are unclear. The aim of this study was to investigate the endocrine disrupting effects of TCS on the placenta in pregnant rats. Pregnant rats from gestational day (GD) 6 to GD 20 were treated with 0, 30, 100, 300 and 600 mg/kg/d TCS followed by analysis of various biochemical parameters. Of the seven tissues examined, the greatest bioaccumulation of TCS was observed in the placenta. Reduction of gravid uterine weight and the occurrence of abortion were observed in the 600 mg/kg/d TCS-exposed group. Moreover, hormone detection demonstrated that the serum levels of progesterone (P), estradiol (E2), testosterone (T), human chorionic gonadotropin (hCG) and prolactin (PRL) were decreased in groups exposed to higher doses of TCS. Real-time quantitative reverse transcriptase-polymerase chain reaction (Q-RT-PCR) analysis revealed a significant increase in mRNA levels for placental steroid metabolism enzymes, including UDP-glucuronosyltransferase 1A1 (UGT1A1), estrogen sulfotransferase 1E1 (SULT1E1), steroid 5α-reductase 1 (SRD5A1) and steroid 5α-reductase 2 (SRD5A2). Furthermore, the transcriptional expression levels of progesterone receptor (PR), estrogen receptor (ERα) and androgen receptor (AR) were up-regulated. Taken together, these data demonstrated that the placenta was a target tissue of TCS and that TCS induced inhibition of circulating steroid hormone production might be related to the altered expression of hormone metabolism enzyme genes in the placenta. This hormone disruption might subsequently affect fetal development and growth.
Feature selection (FS) is vitally important for determining the optimum subsets of features with effective information and maximizing the model accuracy. This study proposes a novel FS method based ...on global sensitivity analysis (GSA) for effectively determining the most relevant feature subsets and improving prediction performance of machine learning (ML)based models. Feature ranking is determined based on the results obtained from three global sensitivity analysis (GSA) including Pearson, Sobol’ and PAWN. This novel GSA-based FS method is applied to engineering practice with the combination of ML algorithm random forest (RF) to predict tunnelling-induced settlement prediction model. Meanwhile, the feature extraction method principle component analysis (PCA) is also used to develop RF-based model for comparing the performance of proposed GSA-based FS method. The results indicate the novel GSA-based FS method effectively determines the significance of input variables. The prediction performance of RF-based model with the integration of GSA-based FS methods is enhanced dramatically, and obviously outperforms the model with the integration of PCA-based dimensionality reduction method.
•A novel global sensitivity analysis based feature selection method is proposed.•Proposed feature selection method is integrated with random forest.•The performance of proposed feature selection is compared with principle component analysis.
The development of lithium-ions batteries (LIBs) is suffering from a huge challenge from insufficient lithium resources. Thus, it is vital to develop novel rechargeable devices as alternative energy ...storage technologies. Due to the abundant potassium resources and low redox potential, potassium-ion batteries (PIBs) attract more and more attention. In particularly, carbon materials with low cost, high conductivity and nontoxic are regarded as one of the most promising anode materials. However, the sluggish kinetics of potassium-ions insertion/extraction and the architecture instability of the electrode materials are hindering practical applications for large-scale storage energy. Based on this, this review analyzes the factors that affect rapid dynamics and structural stability, such as interlayer distance, defects, specific surface area and engineering structure, etc. Recent progresses on enhancing fast kinetics and structure stability are presented. The corresponding electrochemical properties of different types of carbon materials (graphite, hard carbon, soft carbon and graphene) are discussed. More importantly, the critical issues, challenges and perspectives of PIBs are also analyzed.
•The fast kinetics and structure stability have a vital influence on carbon anodes.•The factors that affect fast kinetics and stability of carbon anodes are analyzed.•Summarized key issues and challenges for the carbon anodes of potassium ion battery.•Some critical reviews about constructing high properties carbon anodes are presented.
According to the very limited cancer registry, incidence and mortality rates for female breast cancer in China are regarded to be increasing especially in the metropolitan areas. Representative data ...on the breast cancer profile of Chinese women and its time trend over years are relatively rare. The aims of the current study are to illustrate the breast cancer profile of Chinese women in time span and to explore the current treatment approaches to female breast cancer.
This was a hospital-based nation-wide and multi-center retrospective study of female primary breast cancer cases. China was divided into 7 regions according to the geographic distribution; from each region, one tertiary hospital was selected. With the exception of January and February, one month was randomly selected to represent each year from year 1999 to 2008 at every hospital. All inpatient cases within the selected month were reviewed and related information was collected based on the designed case report form (CRF). The Cancer Hospital/Institute, Chinese Academy of Medical Sciences (CICAMS) was the leading hospital in this study.
Four-thousand two-hundred and eleven cases were randomly selected from the total pool of 45,200 patients and were included in the analysis. The mean age at diagnosis was 48.7 years (s.d. = 10.5 yrs) and breast cancer peaked in age group 40-49 yrs (38.6%). The most common subtype was infiltrating ductal carcinoma (86.5%). Clinical stage I & II accounted for 60.6% of 4,211 patients. Three-thousand five-hundred and thirty-four cases had estrogen receptor (ER) and progestin receptor (PR) tests, among them, 47.9% were positive for both. Two-thousand eight-hundred and forty-nine cases had human epidermal growth factor receptor 2(HER-2) tests, 25.8% of them were HER-2 positive. Among all treatment options, surgery (96.9% (4,078/4,211)) was predominant, followed by chemotherapy (81.4% (3,428/4,211). Much less patients underwent radiotherapy (22.6% (952/4,211)) and endocrine therapy (38.0% (1,599/4,211)).
The younger age of breast cancer onset among Chinese women and more advanced tumor stages pose a great challenge. Adjuvant therapy, especially radiotherapy and endocrine therapy are of great unmet needs.