Improved 3D-2D Perovskite for Efficient Perovskite Photovoltaics with Low-Temperature Carbon Electrodes.

Surface passivation and interface modification are effective strategies to acquire outstanding performances for perovskite solar cells (PeSCs). To suppress charge recombination and enhance the stability of the perovskite device, a hydrophobic two-dimensional (2D) perovskite is presented to construct a 3D-2D composite perovskite, passivating the perovskite surface/interfacial imperfection. Herein, a 3D-2D heterojunction perovskite is in situ synthesized on a 3D surface to maximize the charge transport and environmental stability. Through optimizing the annealing procedure systematically, the champion 3D-2D carbon-based PeSC achieves a power conversion efficiency of 17.95% and has wonderful long-term stability. Especially, an improved 3D-2D (3D-2D+) PeSC from restrict annealing even maintains 96.2% of the initial efficiency in air over 800 h and 90% efficiency under continuous 70 °C heating for 10 h owing to the passivation of the surface and thorough crystal boundary for the 3D-2D+ perovskite. The strong environmental stability of 3D-2D PeSCs has provided a wider avenue for fully low-temperature carbon-based PeSCs.

Controlled-Release Nitrogen Mixed with Common Nitrogen Fertilizer Can Maintain High Yield of Rapeseed and Improve Nitrogen Utilization Efficiency.

Field experiments were conducted to study the effects of different proportions of controlled-release nitrogen fertilizer mixed with quick-acting nitrogen fertilizer on the yield and nitrogen utilization efficiency of direct-seeding rapeseed. Using a conventional nitrogen application rate of 180 kg ha-1 as a control, a total of 5 types of available nitrogen fertilizers and different proportions of controlled-release nitrogen fertilizers were mixed for fertilizer treatment. The proportion of available nitrogen fertilizer used was 135 kg ha-1, and the addition ratios of the five types of controlled-release nitrogen fertilizers were 0%, 30%, 50%, 70%, and 100%, respectively (i.e., the proportion of controlled-release nitrogen to the total nitrogen application amount). These ratios were represented as N135R0, N135R1, N135R2, N135R3, and N135R4, respectively. The results showed that there was no significant difference in the number of pods per plant, the number of seeds per pod, or the grain yield under the treatment of controlled-release nitrogen fertilizer mixed with quick-acting nitrogen fertilizer for proportions of 30-50% (N135R1~R3) when compared with the control, and a stable yield was achieved. Mixing controlled-release nitrogen fertilizer under reduced nitrogen application can significantly improve the apparent utilization rate of rapeseed nitrogen fertilizer, but it first increases and then decreases with the increase of the controlled-release nitrogen mixing ratio, reaching its highest under the N135R2 treatment. The agronomic utilization efficiency and partial productivity of nitrogen fertilizer first increased and then decreased with the increased proportion of controlled-release nitrogen, and both reached their highest utilization with the N135R2 treatment. The mixed treatment of controlled-release nitrogen did not affect soil urease activity, but significantly increased soil sucrase activity. The mixed treatment of controlled-release nitrogen also increased soil microbial biomass nitrogen and carbon content. Especially in the flowering stage, the soil microbial biomass nitrogen and carbon content was significantly higher under a controlled-release nitrogen mixing ratio of 30-50%. At the same time, it had a similar effect on soil inorganic nitrogen content. Therefore, a controlled-release nitrogen mixing treatment provided sufficient nitrogen for the key growth period of rapeseed. Under the condition of reducing the amount of nitrogen fertilizer by 25% based on the amount of nitrogen fertilizer applied to conventional rapeseed, the application of controlled-release urea mixed with common nitrogen fertilizer mixed at a ratio of 30-50% can be an effective way to maintain grain yield levels and improve nitrogen utilization efficiency.

Frequency Domain Filtering Method for SSVEP-EEG Preprocessing.

Steady-state visual evoked potential (SSVEP) signal collected from the scalp typically contains other types of electric signals, and it is important to remove these noise components from the actual signal by application of a pre-processing step for accurate analysis. High-pass or bandpass filtering of the SSVEP signal in the time domain is the most common pre-processing method. Because frequency is the most important feature information contained in the SSVEP signal, a technique for frequency-domain filtering of SSVEP was proposed here. In this method, the time-domain signal is extended to multi-dimensional signal by empirical mode decomposition (EMD), where each dimension represents a intrinsic mode function (IMF). The multi-dimensional signal is transformed to a frequency-domain signal by 2-D Fourier transform, the Gaussian high-pass filter function is constructed to perform high-pass filtering, and then the filtered signal is transformed to time domain by 2-D inverse Fourier transform. Finally, the filtered multi-dimensional intrinsic mode function is superimposed and averaged as the frequency-domain filtered signal. Compared with the time-domain filtering method, the experimental results revealed that frequency-domain filtering method effectively removed the baseline drift in signal and effectively suppressed the low-frequency interference component. This method was tested using data from public datasets and the results show that the proposed frequency-domain filtering method can significantly improve the feature recognition performance of canonical correlation analysis (CCA), filter bank canonical correlation analysis (FBCCA), and task-related component analysis (TRCA) methods. Thus, the results suggest that the application of frequency-domain filtering in the pre-processing stage allows improved noise removal. The proposed method extends SSVEP signal filtering from time-domain to frequency-domain, and the results suggest that this analysis tool significantly promotes the practical application of SSVEP systems.

Hadronic uncertainties versus new physics for the W boson mass and Muon g - 2 anomalies.

There are now two single measurements of precision observables that have major anomalies in the Standard Model: the recent CDF measurement of the W mass shows a 7σ deviation and the Muon g - 2 experiment at FNAL confirmed a long-standing anomaly, implying a 4.2σ deviation. Doubts regarding new physics interpretations of these anomalies could stem from uncertainties in the common hadronic contributions. We demonstrate that these two anomalies pull the hadronic contributions in opposite directions by performing electroweak fits in which the hadronic contribution was allowed to float. The fits show that including the g - 2 measurement worsens the tension with the CDF measurement and conversely that adjustments that alleviate the CDF tension worsen the g - 2 tension beyond 5σ. This means that if we adopt the CDF W mass measurement, the case for new physics in either the W mass or muon g - 2 is inescapable regardless of the size of the SM hadronic contributions. Lastly, we demonstrate that a mixed scalar leptoquark extension of the Standard Model could explain both anomalies simultaneously.

Effect of intermittent shade on nitrogen dynamics assessed by 15N trace isotopes, enzymatic activity and yield of Brassica napus L.

Modern era of agriculture is concerned with the environmental influence on crop growth and development. Shading is one of the crucial factors affecting crop growth considerably, which has been neglected over the years. Therefore, a two-year field experiment was aimed to investigate the effects of shading at flowering (S1) and pod development (S2) stages on nitrogen (N) dynamics, carbohydrates and yield of rapeseed. Two rapeseed genotypes (Chuannong and Zhongyouza) were selected to evaluate the effects of shading on 15N trace isotopes, enzymatic activities, dry matter, nitrogen and carbohydrate distribution and their relationship with yield. The results demonstrated that both shading treatments disturbed the nitrogen accumulation and transportation at the maturity stage. It was found that shading induced the downregulation of the N mobilizing enzymes (NR, NiR, GS, and GOGAT) in leaves and pods at both developmental stages. Shading at both growth stages resulted in reduced dry matter of both varieties but only S2 exhibited the decline in pod shell and seeds dry weight in both years. Besides this, carbohydrates distribution toward economic organs was declined by S2 treatment and its substantial impact was also experienced in seed weight and seeds number per pod which ultimately decreased the yield in both genotypes. We also revealed that yield is positively correlated with dry matter, nitrogen content and carbohydrates transportation. In contrast to Chuannong, the Zhongyouza genotype performed relatively better under shade stress. Overall, it was noticed that shading at pod developmental stage considerable affected the transportation of N and carbohydrates which led to reduced rapeseed yield as compared to shading at flowering stage. Our study provides basic theoretical support for the management techniques of rapeseed grown under low light regions and revealed the critical growth stage which can be negatively impacted by low light.

A time-frequency denoising method for single-channel event-related EEG.

Introduction: Electroencephalogram (EEG) acquisition is easily affected by various noises, including those from electrocardiogram (ECG), electrooculogram (EOG), and electromyogram (EMG). Because noise interference can significantly limit the study and analysis of brain signals, there is a significant need for the development of improved methods to remove this interference for more accurate measurement of EEG signals. Methods: Based on the non-linear and non-stationary characteristics of brain signals, a strategy was developed to denoise brain signals using a time-frequency denoising algorithm framework of short-time Fourier transform (STFT), bidimensional empirical mode decomposition (BEMD), and non-local means (NLM). Time-frequency analysis can reveal the signal frequency component and its evolution process, allowing the elimination of noise according to the signal and noise distribution. BEMD can be used to decompose the time-frequency signals into sub-time-frequency signals for noise removal at different scales. NLM relies on structural self-similarity to locally smooth an image to remove noise and restore its main geometric structure, making this method appropriate for time-frequency signal denoising. Results: The experimental results show that the proposed method can effectively suppress the high-frequency components of brain signals, resulting in a smoother brain signal waveform after denoising. The correlation coefficient of the reference signal, a superposition average of multiple trial signals, and the original single trial signal was determined, and then correlation coefficients were calculated between the reference signal and single trial signals processed by time-frequency denoising, ensemble empirical mode decomposition (EEMD)-independent component analysis (ICA), EEMD-canonical correlation analysis (CCA), and wavelet threshold denoising methods. The correlation coefficient was highest for the signal processed by the time-frequency denoising method and the reference signal, indicating that the single trial signal after time-frequency denoising was most similar to the waveform of the reference signal and suggesting this is a feasible strategy to effectively reduce noise and more accurately determine signals. Discussion: The proposed time-frequency denoising method exhibits excellent performance with promising potential for practical application.

Temporal complementarity between roots and mycorrhizal fungi drives wheat nitrogen use efficiency.

Improving nitrogen (N) use efficiency (NUE) to reduce the application of N fertilisers in a way that benefits the environment and reduces farmers' costs is an ongoing objective for sustainable wheat production. However, whether and how arbuscular mycorrhizal fungi (AMF) affect NUE in wheat is still not well explored. Three independent but complementary experiments were conducted to decipher the contribution of roots and AMF to the N uptake and utilisation efficiency in wheat. We show a temporal complementarity pattern between roots and AMF in shaping NUE of wheat. Pre-anthesis N uptake efficiency mainly depends on root functional traits, but the efficiency to utilise the N taken up during pre-anthesis for producing grains (EN,g ) is strongly affected by AMF, which might increase the uptake of phosphorus and thereby improve photosynthetic carbon assimilation. Root association with AMF reduced the N remobilisation efficiency in varieties with high EN,g ; whilst the overall grain N concentration increased, due to a large improvement in post-anthesis N uptake supported by AMF and/or other microbes. The findings provide evidence for the importance of managing AMF in agroecosystems, and an opportunity to tackle the contradiction between maximising grain yield and protein concentration in wheat breeding.

An improved cross-subject spatial filter transfer method for SSVEP-based BCI.

Objective.Steady-state visual evoked potential (SSVEP) training feature recognition algorithms utilize user training data to reduce the interference of spontaneous electroencephalogram activities on SSVEP response for improved recognition accuracy. The data collection process can be tedious, increasing the mental fatigue of users and also seriously affecting the practicality of SSVEP-based brain-computer interface (BCI) systems.Approach. As an alternative, a cross-subject spatial filter transfer (CSSFT) method to transfer an existing user data model with good SSVEP response to new user test data has been proposed. The CSSFT method uses superposition averages of data for multiple blocks of data as transfer data. However, the amplitude and pattern of brain signals are often significantly different across trials. The goal of this study was to improve superposition averaging for the CSSFT method and propose anEnsemblescheme based on ensemble learning, and anExpansionscheme based on matrix expansion.Main results. The feature recognition performance was compared for CSSFT and the proposed improved CSSFT method using two public datasets. The results demonstrated that the improved CSSFT method can significantly improve the recognition accuracy and information transmission rate of existing methods.Significance.This strategy avoids a tedious data collection process, and promotes the potential practical application of BCI systems.

Cross-subject spatial filter transfer method for SSVEP-EEG feature recognition.

Objective.Steady-state visual evoked potential (SSVEP) is an important control method of the brain-computer interface (BCI) system. The development of an efficient SSVEP feature decoding algorithm is the core issue in SSVEP-BCI. It has been proposed to use user training data to reduce the spontaneous electroencephalogram activity interference on SSVEP response, thereby improving the feature recognition accuracy of the SSVEP signal. Nevertheless, the tedious data collection process increases the mental fatigue of the user and severely affects the applicability of the BCI system.Approach.A cross-subject spatial filter transfer (CSSFT) method that transfer the existing user model with good SSVEP response to the new user test data without collecting any training data from the new user is proposed.Main results.Experimental results demonstrate that the transfer model increases the distinction of the feature discriminant coefficient between the gaze following target and the non-gaze following target and accurately identifies the wrong target in the fundamental algorithm model. The public datasets show that the CSSFT method significantly increases the recognition performance of canonical correlation analysis (CCA) and filter bank CCA. Additionally, when the data used to calculate the transfer model contains one data block only, the CSSFT method retains its effective feature recognition capabilities.Significance.The proposed method requires no tedious data calibration process for new users, provides an effective technical solution for the transfer of the cross-subject model, and has potential application value for promoting the application of the BCI system.

Enhancement of Lodging Resistance and Lignin Content by Application of Organic Carbon and Silicon Fertilization in Brassica napus L.

This study was aimed to investigate the effects of organic carbon and silicon fertilizers on the lodging resistance, yield, and economic performance of rapeseed. Two cultivars, namely Jayou (lodging-resistant) and Chuannongyou (lodging-susceptible), were selected to evaluate the effects of various fertilizer treatments on rapeseed culm morphology, lignin accumulation, and their relationships with their lodging resistance indices. The results showed that both organic carbon and silicon fertilizer applications increased the plant height, basal stem diameter, internode plumpness, and bending strength of rapeseed in both the studied years. The bending strength was significantly and positively correlated with the lodging resistance index and lignin content. It was found that both organic carbon and silicon fertilizers had improved the activities of lignin biosynthesis enzymes (phenylalanine ammonia-lyase, 4-coumarate:CoA ligase, cinnamyl alcohol dehydrogenase, and peroxiredoxins) and their related genes to increase lignin accumulation in the culm, which ultimately improved the lodging resistance. At the same time, the thickness of the stem cortex, vascular bundle area, and xylem area was increased, and the stem strength was improved. The effect of silicon fertilizer was better than that of organic carbon fertilizer, but there was no significant difference with the mixed application of silicon fertilizer and organic carbon fertilizer. Similarly, silicon fertilizer increased the number of pods, significantly increased the yield, and improved the economic benefit, while organic carbon fertilizer had no significant effect on the yield. Therefore, we believe that organic carbon and silicon fertilizer can improve the lodging resistance of rape stems by improving the lignin accumulation and the mechanical tissue structure. Still, the effect of silicon fertilizer is the best. Considering the economic benefits, adding silicon fertilizer can obtain more net income than the mixed application of silicon fertilizer and organic carbon fertilizer.

SSVEP-EEG Denoising via Image Filtering Methods.

Steady-state visual evoked potential (SSVEP) is widely used in electroencephalogram (EEG) control, medical detection, cognitive neuroscience, and other fields. However, successful application requires improving the detection performance of SSVEP signal frequency characteristics. Most strategies to enhance the signal-to-noise ratio of SSVEP utilize application of a spatial filter. Here, we propose a method for image filtering denoising (IFD) of the SSVEP signal from the perspective of image analysis, as a preprocessing step for signal analysis. Arithmetic mean, geometric mean, Gaussian, and non-local means filtering methods were tested, and the experimental results show that image filtering of SSVEP cannot effectively remove the noise. Thus, we proposed a reverse solution in which the SSVEP noise signal was obtained by image filtering, and then the noise was subtracted from the original signal. Comparison of the recognition accuracy of the SSVEP signal before and after denoising was used to evaluate the denoising performance for stimuli of different duration. After IFD processing, SSVEP exhibited higher recognition accuracy, indicating the effectiveness of this proposed denoising method. Application of this method improves the detection performance of SSVEP signal frequency characteristics, combines image processing and brain signal analysis, and expands the research scope of brain signal analysis for widespread application.

Enhancing detection of steady-state visual evoked potentials using channel ensemble method.

Objective.This study proposed and evaluated a channel ensemble approach to enhance detection of steady-state visual evoked potentials (SSVEPs).Approach.Collected multi-channel electroencephalogram signals were classified into multiple groups of new analysis signals based on correlation analysis, and each group of analysis signals contained signals from a different number of electrode channels. These groups of analysis signals were used as the input of a training-free feature extraction model, and the obtained feature coefficients were converted into feature probability values using thesoftmaxfunction. The ensemble value of multiple sets of feature probability values was determined and used as the final discrimination coefficient.Main results.Compared with canonical correlation analysis, likelihood ratio test, and multivariate synchronization index analysis methods using a standard approach, the recognition accuracies of the methods using a channel ensemble approach were improved by 5.05%, 3.87%, and 3.42%, and the information transfer rates (ITRs) were improved by 6.00%, 4.61%, and 3.71%, respectively. The channel ensemble method also obtained better recognition results than the standard algorithm on the public dataset. This study validated the efficiency of the proposed method to enhance the detection of SSVEPs, demonstrating its potential use in practical brain-computer interface (BCI) systems.Significance. A SSVEP-based BCI system using a channel ensemble method could achieve high ITR, indicating great potential of this design for various applications with improved control and interaction.

Towards a fundamental safe theory of composite Higgs and dark matter.

We present a novel paradigm that allows to define a composite theory at the electroweak scale that is well defined all the way up to any energy by means of safety in the UV. The theory flows from a complete UV fixed point to an IR fixed point for the strong dynamics (which gives the desired walking) before generating a mass gap at the TeV scale. We discuss two models featuring a composite Higgs, Dark Matter and partial compositeness for all SM fermions. The UV theories can also be embedded in a Pati-Salam partial unification, thus removing the instability generated by the U ( 1 ) running. Finally, we find a Dark Matter candidate still allowed at masses of 260 GeV, or 1.5-2 TeV, where the latter mass range will be covered by next generation direct detection experiments.

Comparison of the performance of six stimulus paradigms in visual acuity assessment based on steady-state visual evoked potentials.

PURPOSE: There are several stimulus paradigms used in objective visual acuity assessment based on steady-state visual evoked potentials (SSVEPs). The aim of this study was to explore the difference and performance of common used six stimulus paradigms (reverse vertical sinusoidal gratings, reverse horizontal sinusoidal gratings, reverse vertical square-wave gratings, brief-onset vertical sinusoidal gratings, reversal checkerboards and oscillating expansion-contraction concentric-rings) of SSVEP acuity assessment. METHODS: We tested subjective visual acuity both by tumbling E and Freiburg Visual Acuity and Contrast Test (FrACT) in 11 subjects. SSVEPs were induced by 11 spatial frequencies for each paradigm, and then a threshold determination criterion was used to define the objective SSVEP visual acuity. RESULTS: After SSVEP signal analysis, we found there was difference in SSVEP response of harmonic components and no difference in sensitive electrode placement for the six paradigms. We selected six electrodes (PO3, POz, PO4, O1, Oz and O2) as the sensitive electrodes to use in data processing for each paradigm. The results showed that except for brief-onset vertical sinusoidal gratings, the correlation and agreement between objective SSVEP and subjective FrACT acuity were all quite good, demonstrating good performance in acuity detection for the rest five paradigms. CONCLUSION: Except for brief-onset vertical sinusoidal gratings, all the five stimulus paradigms of reverse vertical sinusoidal gratings, reverse horizontal sinusoidal gratings, reverse vertical square-wave gratings, reversal checkerboards and oscillating expansion-contraction concentric-rings performed quite well in objective SSVEP visual acuity assessment.

Optimal Nitrogen Fertilization Management of Seed-sowing Rapeseed in Yangtze River Basin of China.

BACKGROUND AND OBJECTIVE: For cultivation and high yield of oilseed rape (Brassica napus L.) in China, traditional seedling transplanting is replaced by seed-sowing but, better nitrogen management is crucial and not established yet. This study aimed to adapt N management to the seed-sowing method for the winter oilseed rape and to minimize the N fertilizer-derived pollution potential in the upper reaches of Yangtze River Basin. MATERIALS AND METHODS: Three field experiments were conducted to check effect of different doses of N fertilizers, split doses of N and different types of N fertilizers for seed-sowing winter oilseed rape with high plant density in upper reaches of Yangtze River Basin in Sichuan province of China. RESULTS: In first experiment, among four doses (0, 90, 180 and 270 kg N ha-1) on average 3.54 t ha-1 was in 180 kg N ha-1 and 3.61 t ha-1 in 270 kg N ha-1 while cultivars dy6 and cn3 produced 3.23 and 3.29 t ha-1 which is significantly higher than zs11. There was no significant difference in N-use efficiency among three cultivars tested and second experiment showed no significant difference in seed yield with split N application. The third experiment compared the effects of different fertilizer types (urea, coated urea, 1:1 mixture of urea and coated urea and compound nitrogen fertilizer) on seed yield and get no significant difference in seed yield. CONCLUSION: This experiment proved that seed sowing method with higher nitrogen had high yield in the upper reaches of Yangtze River Basin in China, but higher N application may cause environment pollution. So, seed sowing method with nitrogen 180 kg N ha-1 was proved to be more effective.

Pd catalyzed insertion of alkynes into cyclic diaryliodoniums: a direct access to multi-substituted phenanthrenes.

Cyclic diaryliodoniums remain unexplored compared to linear iodoniums. In our current work, internal alkynes were for the first time applied to react with cyclic iodoniums, catalyzed by Pd, resulting in a [4 + 2] benzannulation. Our work offers a new strategy to synthesize multi-substituted phenanthrene derivatives which are not easily accessed by conventional methods.

Palladium catalyzed dual C-H functionalization of indoles with cyclic diaryliodoniums, an approach to ring fused carbazole derivatives.

Palladium(II)-catalyzed dual C-H functionalization of indoles with cyclic diaryliodoniums was successfully achieved, providing a concise method to synthesize dibenzocarbazoles. In a single operation, two C-C bonds and one ring were formed. The reaction was ligand free and tolerated air and moisture conditions.

Three-component Pd/Cu-catalyzed cascade reactions of cyclic iodoniums, alkynes, and boronic acids: an approach to methylidenefluorenes.

Linear diaryliodonium salts are widely used as arylating reagents for C-C and C-X bond formation. Meanwhile, synthetic applications of cyclic iodoniums are relatively rare although they offer the opportunity to set up reaction cascades. We demonstrate an atom and step economical three-component reaction involving cyclic diphenyleneiodoniums, alkynes, and boronic acids, resulting in the construction of methylidenefluorenes in a single operation. Our route enables facile access to both symmetrical and unsymmetrical methylidenefluorene derivatives, compounds that have attracted interest due to their optical properties.

The nitrate leached below maize root zone is available for deep-rooted wheat in winter wheat-summer maize rotation in the North China Plain.

In winter wheat (Triticum aestivum L.)-summer maize (Zea mays L.) rotation system in the North China Plain, maize roots do not extend beyond 1.2 m in the vertical soil profile, but wheat roots can reach up to 2.0 m. Increases in soil nitrate content at maize harvest and significant reductions after winter wheat harvest were observed in the 1.4-2.0 m depth under field conditions. The recovery of 15N isotope (calcium nitrate) from various (1.0, 1.2, 1.4, 1.6, 1.8 and 2.0 m) soil depths showed that deep-rooting winter wheat could use soil nitrate up to the 2.0 m depth. This accounted partially, for the reduced nitrate in the 1.4-2.0 m depth of the soil after harvest of wheat in the rotation system.