Low conductivity and hole mobility in the pristine metal phthalocyanines greatly limit their application in perovskite solar cells (PSCs) as the hole‐transporting materials (HTMs). Here, we prepare a ...Ni phthalocyanine (NiPc) decorated by four methoxyethoxy units as HTMs. In NiPc, the two oxygen atoms in peripheral substituent have a modified effect on the dipole direction, while the central Ni atom contributes more electron to phthalocyanine ring, thus efficiently increasing the intramolecular dipole. Calculation analyses reveal the extracted holes within NiPc are mainly concentrated on the phthalocyanine core induced by the intramolecular electric field, and further to be transferred by π‐π stacking space channel between NiPc molecules. Finally, the best efficiency of PSCs with NiPc as dopant‐free HTMs realizes a record value of 21.23 % (certified 21.03 %). The PSCs also exhibit the good moisture, heating and light stabilities. This work provides a novel way to improve the performance of PSCs with free‐doped metal phthalocyanines as HTMs.
A Ni phthalocyanine (NiPc) decorated by four methoxyethoxy units with a strong intramolecular electric field is prepared and used as hole‐transporting materials (HTMs) in perovskite solar cells (PSCs). The best PSCs with NiPc as dopant‐free HTM show a record efficiency of 21.23 % (certified 21.03 %). The PSCs also exhibit the excellent stability.
•Development of a robust and effective image labelling algorithm.•Development of an efficient deep-learning detector ‘LedNet’ for apple detection.•Achievement of real-time and accurate apple ...detection in orchards.•Validation of a fast and effective framework for apple detection.
To perform robust and efficient fruit detection in orchards is challenging since there are a number of variances in the working environments. Recently, deep-learning have shown a promising performance in many visual-guided agriculture applications. However, deep-learning based approaches requires labelling on training data, which is a labour-intensive and time-consuming task. In this study, a fast implementation framework of a deep-learning based fruit detector for apple harvesting is developed. The developed framework comprises an auto label generation module and a deep-learning-based fruit detector ‘LedNet’. The Label Generation algorithm utilises the multi-scale pyramid and clustering classifier to assist fast labelling of training data. LedNet adopts feature pyramid network and atrous spatial pyramid pooling to improve the detection performance of the model. A light-weight backbone is also developed and utilised to improve computational efficiency. From the experimental results, LedNet achieves 0.821 and 0.853 on recall and accuracy on apple detection in orchards, and its weights size and inference time are 7.4 M and 28 ms, respectively. The experimental results show that LedNet can perform real-time apple detection in orchards robustly and efficiently.
We conducted two studies to explore integrative, knowledge-centered team mechanisms through which transformational leadership affects team innovative performance. In the first study, using ...temporarily assembled project teams working on knowledge-intensive tasks, we found that transformational leadership promoted within-team knowledge sharing and team innovative performance through an integration mechanism manifest as team cooperative norms, and such a mediation process was significant even after controlling for another mediation process of team autonomy. In the second study, using permanent work teams in various functional areas, we replicated the integrative mechanism and associated transformational leadership with external team knowledge acquisition, which further moderated the relationship between knowledge sharing and innovation. Our findings point to the importance of the integration function of transformational leadership in enhancing collective innovation.
The novel coronavirus disease 2019 (COVID-19) infection has rapidly grown worldwide,
and many governments have implemented policies to control the infection rate. For example, school suspension, ...self-quarantine, requirement of citizens to stay at home,
travel and border controls, and discouragement of outdoor activities
have been used. Although these actions emphasizing the importance of "spatial distancing" are based on the perspective of public health, they may result in health problems other than COVID-19 infection, such as psychological distress and fear.
Therefore, the present authors examined the potential predictors for psychological distress among schoolchildren during COVID-19 school suspension.
Autonomous harvesting shows a promising prospect in the future development of the agriculture industry, while the vision system is one of the most challenging components in the autonomous harvesting ...technologies. This work proposes a multi-function network to perform the real-time detection and semantic segmentation of apples and branches in orchard environments by using the visual sensor. The developed detection and segmentation network utilises the atrous spatial pyramid pooling and the gate feature pyramid network to enhance feature extraction ability of the network. To improve the real-time computation performance of the network model, a lightweight backbone network based on the residual network architecture is developed. From the experimental results, the detection and segmentation network with ResNet-101 backbone outperformed on the detection and segmentation tasks, achieving an F 1 score of 0.832 on the detection of apples and 87.6% and 77.2% on the semantic segmentation of apples and branches, respectively. The network model with lightweight backbone showed the best computation efficiency in the results. It achieved an F 1 score of 0.827 on the detection of apples and 86.5% and 75.7% on the segmentation of apples and branches, respectively. The weights size and computation time of the network model with lightweight backbone were 12.8 M and 32 ms, respectively. The experimental results show that the detection and segmentation network can effectively perform the real-time detection and segmentation of apples and branches in orchards.
A recurrence of hepatocellular carcinoma (HCC) after living donor liver transplantation (LDLT) is one of the major concerns reflecting the higher mortality of HCC. This study aimed to explore the ...impact of circulating exosomes on HCC development and recurrence. One‐shot transfusion of hepatoma serum to naïve rats induced liver cancer development with gradual elevation of alpha‐fetoprotein (AFP), but exosome‐free hepatoma serum failed to induce AFP elevation. The microarray analysis revealed miR‐92b as one of the highly expressing microribonucleic acids in hepatoma serum exosomes. Overexpression of miR‐92b enhanced the migration ability of liver cancer cell lines with active release of exosomal miR‐92b. The hepatoma‐derived exosomal miR‐92b transferred to natural killer (NK) cells, resulting in the downregulation of CD69 and NK cell‐mediated cytotoxicity. Furthermore, higher expression of miR‐92b in serum exosomes was confirmed in HCC patients before LDLT, and its value at 1 month after LDLT was maintained at a higher level in the patients with posttransplant HCC recurrence. In summary, we demonstrated the impact of circulating exosomes on liver cancer development, partly through the suppression of CD69 on NK cells by hepatoma‐derived exosomal miR‐92b. The value of circulating exosomal miR‐92b may predict the risk of posttransplant HCC recurrence.
This study demonstrates the impact of circulating exosomes on liver cancer development in rats, explores functional roles of exosomal miR‐92b in the tumor microenvironment, and verifies its clinical value for early prediction of posttransplant hepatocellular carcinoma recurrence.
Electrocardiogram (ECG) signal, an important indicator for heart problems, is commonly corrupted by a low-frequency baseline wander (BW) artifact, which may cause interpretation difficulty or ...inaccurate analysis. Unlike current state-of-the-art approach using band-pass filters, wavelet transforms can accurately capture both time and frequency information of a signal. However, extant literature is limited in applying wavelet transforms (WTs) for baseline wander removal. In this study, we aimed to evaluate 5 wavelet families with a total of 14 wavelets for removing ECG baseline wanders from a semi-synthetic dataset.
We created a semi-synthetic ECG dataset based on a public QT Database on Physionet repository with ECG data from 105 patients. The semi-synthetic ECG dataset comprised ECG excerpts from the QT database superimposed with artificial baseline wanders. We extracted one ECG excerpt from each of 105 patients, and the ECG excerpt comprised 14 s of randomly selected ECG data. Twelve baseline wanders were manually generated, including sinusoidal waves, spikes and step functions. We implemented and evaluated 14 commonly used wavelets up to 12 WT levels. The evaluation metric was mean-square-error (MSE) between the original ECG excerpt and the processed signal with artificial BW removed.
Among the 14 wavelets, Daubechies-3 wavelet and Symlets-3 wavelet with 7 levels of WT had best performance, MSE = 0.0044. The average MSEs for sinusoidal waves, step, and spike functions were 0.0271, 0.0304, 0.0199 respectively. For artificial baseline wanders with spikes or step functions, wavelet transforms in general had lower performance in removing the BW; however, WTs accurately located the temporal position of an impulse edge.
We found wavelet transforms in general accurately removed various baseline wanders. Daubechies-3 and Symlets-3 wavelets performed best. The study could facilitate future real-time processing of streaming ECG signals for clinical decision support systems.
Golay complementary sequences and complementary sets have been proposed to deal with the high peak-to-average power ratio (PAPR) problem in orthogonal frequency division multiplexing (OFDM) system. ...The existing constructions of complementary sets based on generalized Boolean functions are limited to lengths, which are powers of two. In this paper, we propose novel constructions of binary and nonbinary complementary sets of non-power-of-two length. Regardless of whether or not the length of the complementary set is a power of two, its PAPR is still upper bounded by the size of the complementary set. Therefore, the constructed complementary sets can be applied in practical OFDM systems where the number of used subcarriers is not a power of two. In addition, while the binary Golay complementary pairs exist only for limited lengths, the constructed binary complementary sets of size 4 exist for more lengths with PAPR at most 4.
Since the industrial revolution, it has been assumed that fossil-fuel combustions dominate increasing nitrogen oxide (NO
) emissions. However, it remains uncertain to the actual contribution of the ...non-fossil fuel NO
to total NO
emissions. Natural N isotopes of NO
in precipitation (δ
N
) have been widely employed for tracing atmospheric NO
sources. Here, we compiled global δ
N
observations to evaluate the relative importance of fossil and non-fossil fuel NO
emissions. We found that regional differences in human activities directly influenced spatial-temporal patterns of δ
N
variations. Further, isotope mass-balance and bottom-up calculations suggest that the non-fossil fuel NO
accounts for 55 ± 7% of total NO
emissions, reaching up to 21.6 ± 16.6Mt yr
in East Asia, 7.4 ± 5.5Mt yr
in Europe, and 21.8 ± 18.5Mt yr
in North America, respectively. These results reveal the importance of non-fossil fuel NO
emissions and provide direct evidence for making strategies on mitigating atmospheric NO
pollution.
Drawing on social identity theory and social-cognitive theory, we hypothesize that organizational identification predicts unethical pro-organizational behavior (UPB) through the mediation of moral ...disengagement. We further propose that competitive interorganizational relations enhance the hypothesized relationships. Three studies conducted in China and the United States using both survey and vignette methodologies provided convergent support for our model. Study 1 revealed that higher organizational identifiers engaged in more UPB, and that this effect was mediated by moral disengagement. Study 2 found that organizational identification once again predicted UPB through the mediation of moral disengagement, and that the mediation relationship was stronger when employees perceived a higher level of industry competition. Finally, Study 3 replicated the above findings using a vignette experiment to provide stronger evidence of causality. Theoretical and practical implications are discussed.
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