Results Of Experiments Research Articles

Preexposure to running attenuates rats' running-based flavour avoidance: Testing associative blocking with a cover cues or context change.

Voluntary running in activity wheels by rats leads to a Pavlovian conditioned aversion to the flavour consumed immediately before the running, causing the rats to avoid that flavour. This learning process, known as running-based flavour avoidance learning (FAL), is weakened when the rats have had repeated exposure to the wheels before. According to the associative account, the association between the background context and running established during the preexposure phase blocks the conditioning of the target flavour because the running is highly predictable by the background context from the outset of the FAL phase. Experiments 1 and 2 examined this account by introducing another flavour as a cue signalling wheel access during the preexposure phase. In the framework of the associative account, the introduction of this cue should impede the formation of the context-running association during the preexposure phase, thereby hindering the contextual blocking of aversive conditioning for the target flavour in the FAL phase. This would result in unweakened FAL. Although the results of Experiment 1 align with this prediction, in Experiment 2, when highly distinct flavours were used as the target and second cues, the preexposure effect was not eliminated. This contradicts the predictions of the associative account, indicating that Experiment 1 may have been influenced by stimulus generalisation. In Experiment 3, changing background contexts between the preexposure and FAL phases had no impact on the preexposure effect, contrary to the predictions of the associative account. In general, the associative account was not supported.

PDTE: Pyramidal deep Taylor expansion for optical flow estimation

Optical flow estimation is an important hot research in computer vision. Although existing methods had got a considerable progress in improving their performance, they still have drawbacks, such as heavily computational burden, inaccurate pixel-level offset estimation, and poor interpretability. To address these issues, this letter proposes a pyramidal deep Taylor expansion (PDTE) framework, including: First, we seriously interpreted the relationship between optical flow computation and Taylor expansion. Then, the proposed PDTE is constructed by employing global motion aggregation (GMA) to calculate each derivative part which contributes to the final estimated optical flow. Quantitative and qualitative results on the Sintel and KITTI datasets validate that the proposed PDTE scheme is effective and outperforms the state-of-the-art optical flow estimation methods. The results of extensive experiments in the ablation study demonstrate that PDTE performs well on shape preservation and the accuracy improvement of optical flow estimation, even pixel-level offset calculation.

Efficient Homolytic Cleavage of H2O2 on Hydroxyl‐Enriched Spinel CuFe2O4 with Dual Lewis Acid Sites

AbstractTraditional H2O2 cleavage mediated by macroscopic electron transfer (MET) not only has low utilization of H2O2, but also sacrifices the stability of catalysts. We present a non‐redox hydroxyl‐enriched spinel (CuFe2O4) catalyst with dual Lewis acid sites to realize the homolytic cleavage of H2O2. The results of systematic experiments, in situ characterizations, and theoretical calculations confirm that tetrahedral Cu sites with optimal Lewis acidity and strong electron delocalization can synergistically elongate the O−O bonds (1.47 Å → 1.87 Å) in collaboration with adjacent bridging hydroxyl (another Lewis acid site). As a result, the free energy of H2O2 homolytic cleavage is decreased (1.28 eV → 0.98 eV). H2O2 can be efficiently split into ⋅OH induced by hydroxyl‐enriched CuFe2O4 without MET, which greatly improves the catalyst stability and the H2O2 utilization (65.2 %, nearly 2 times than traditional catalysts). The system assembled with hydroxyl‐enriched CuFe2O4 and H2O2 affords exceptional performance for organic pollutant elimination. The scale‐up experiment using a continuous flow reactor realizes long‐term stability (up to 600 mL), confirming the tremendous potential of hydroxyl‐enriched CuFe2O4 for practical applications.

Magnetic Supramolecular Spherical Arrays: Direct Formation of Micellar Cubic Mesophase by Lanthanide Metallomesogens with 7-Coordination Geometry.

Here, an unprecedented phenomenon in which 7-coordinate lanthanide metallomesogens, which align via hydrogen bonds mediated by coordinated H2O molecules, form micellar cubic mesophases at room temperature, creating body-centered cubic (BCC)-type supramolecular spherical arrays, is reported. The results of experiments and molecular dynamics simulations reveal that spherical assemblies of three complexes surrounded by an amorphous alkyl domain spontaneously align in an energetically stable orientation to form the BCC structure. This phenomenon differs greatly from the conventional self-assembling behavior of 6-coordinated metallomesogens, which form columnar assemblies due to strong intermolecular interactions. Since the magnetic and luminescent properties of different lanthanides vary, adding arbitrary functions to spherical arrays is possible by selecting suitable lanthanides to be used. The method developed in this study using 7-coordinate lanthanide metallomesogens as building blocks is expected to lead to the rational development of micellar cubic mesophases.

Molecular basis of distinct responses to drought between rice and wheat genotypes

The water-intensive cultivation of rice in flooded conditions poses a great challenge to global water resources, particularly in the face of climate change. Wheat requires significantly less water than rice with fairly high yields. A main research question is whether there are any drought adaptive mechanisms in rice similar to those existing in wheat. We report a study, where precise moisture stress was imposed at the vegetative stage using a high-throughput drought simulator phenomics facility. Variability in stress response was captured through untargeted metabolome analysis. In the first experiment, using two rice cultivars with contrasting drought responses (IR64 and Apo) and a wheat cultivar, Weebill, we found distinct variations in regulation of metabolite levels under well-watered or water-limited conditions, both between and within species. Several biosynthetic pathways, including those of polyamines, flavonoids, flavones, and specific metabolites like sphinganine-1-phosphate and anthranilate were enhanced under water-limited conditions. These metabolites were more abundant in wheat than in rice. Among the rice cultivars, Apo had higher abundance of metabolites than IR64. Regulatory patterns governing these metabolic pathways provided basis for stress responses of the tolerant rice cultivar and wheat. A second experiment was conducted to screen rice germplasm lines for acquired tolerance traits contrasting for drought responsiveness. Eight genotypes (four sensitive and four tolerant ones) were selected to validate the candidate metabolites from the first experiment. In the third experiment, an RT-PCR analysis of the key regulatory genes governing the metabolic pathways was conducted, using plant materials from both experiments. The results of this third experiment provided a strong validation for the relevance of these metabolic pathways under stress in rice. We identified promising rice genotypes that exhibited fold change levels of stress resistance metabolites comparable to those of the wheat cultivar Weebill. This study helped identify key candidate metabolites that can be either developed as markers or as elicitors, and genotypes that can be used as trait donor lines for rice improvement.

The grammaticalization and grammatical meaning of a ‘do’ support verb in the northern Italian Camuno dialect

Abstract This paper provides a case study of the grammaticalization of ‘do’ as a support verb in the northern Italian dialect of Camuno. It demonstrates the relative compatibility of fa ‘do’ with different semantic types of supported verbs through the results of an elicitation experiment. A comparison of results from adjacent dialects reveals a series of progressively more grammaticalized forms with three stages: ‘pragmatic’ ‘do’-support, largely restricted to agentive-subject, activity verbs, where question type depends mainly on the pragmatics; ‘agentive’ ‘do’-support, where use with that core group of verbs is largely categorial, and there is more use with theme-subject, change-of-state verbs and a few experiencer-subject, stative verbs; and ‘generalized’ ‘do’-support where optionality remains only with the most resistant stative verbs. Along with loss of lexical content in ‘do’, comes a reduction in salience of the special question meaning. Furthermore, a question with lexical fa ‘do’ (in an optional FS dialect) implies physical evidence exists to determine the truth of a proposition. In a question with bleached fa ‘do’ (in an obligatory FS dialect) the connection to reality has been lost leaving only the implication, and fa ‘do’ has then become an epistemic modal.

Multi-modal deep learning methods for classification of chest diseases using different medical imaging and cough sounds.

Chest disease refers to a wide range of conditions affecting the lungs, such as COVID-19, lung cancer (LC), consolidation lung (COL), and many more. When diagnosing chest disorders medical professionals may be thrown off by the overlapping symptoms (such as fever, cough, sore throat, etc.). Additionally, researchers and medical professionals make use of chest X-rays (CXR), cough sounds, and computed tomography (CT) scans to diagnose chest disorders. The present study aims to classify the nine different conditions of chest disorders, including COVID-19, LC, COL, atelectasis (ATE), tuberculosis (TB), pneumothorax (PNEUTH), edema (EDE), pneumonia (PNEU). Thus, we suggested four novel convolutional neural network (CNN) models that train distinct image-level representations for nine different chest disease classifications by extracting features from images. Furthermore, the proposed CNN employed several new approaches such as a max-pooling layer, batch normalization layers (BANL), dropout, rank-based average pooling (RBAP), and multiple-way data generation (MWDG). The scalogram method is utilized to transform the sounds of coughing into a visual representation. Before beginning to train the model that has been developed, the SMOTE approach is used to calibrate the CXR and CT scans as well as the cough sound images (CSI) of nine different chest disorders. The CXR, CT scan, and CSI used for training and evaluating the proposed model come from 24 publicly available benchmark chest illness datasets. The classification performance of the proposed model is compared with that of seven baseline models, namely Vgg-19, ResNet-101, ResNet-50, DenseNet-121, EfficientNetB0, DenseNet-201, and Inception-V3, in addition to state-of-the-art (SOTA) classifiers. The effectiveness of the proposed model is further demonstrated by the results of the ablation experiments. The proposed model was successful in achieving an accuracy of 99.01%, making it superior to both the baseline models and the SOTA classifiers. As a result, the proposed approach is capable of offering significant support to radiologists and other medical professionals.

High authenticity steering feel control strategy for Steer-by-Wire system based on terminal sliding mode rack force observer

This article proposes a high authenticity steering feel control strategy for Steer-by-Wire (SBW) system based on terminal sliding mode rack force observer, in response to the issue of how to design the steering feel of the SBW system to reflect road conditions. Firstly, a terminal sliding mode rack force observer is designed to achieve real-time and accurate estimation of steering system rack force. Then, based on the vehicle motion state, design the feedback characteristic curve of the rack force and the compensation torque of the handwheel to obtain the expected steering feel, and use the automatic disturbance rejection controller (ADRC) method to control the voltage of the handwheel motor. In simulation testing, a SBW open loop control system model is established to verify the performance of the designed rack force observer. The objective evaluation indicators are used to verify that the designed feedback method can intuitively adjust and meet the driver's steering feel needs, and the impact of various compensation torques on the evaluation indicators is analyzed. Finally, the results of actual vehicle experiments indicate that the designed method can provide suitable steering feel, verifying the feasibility of the design technology.

Classification of optical coherence tomography images using deep machine learning methods

Backgraund. Optical coherence tomography (OCT) is a modern high-tech and informative method for detecting pathology of the retina and preretinal layers of the vitreous body. However, the description and interpretation of the research results require high qualifications and special training of an ophthalmologist, and significant time expenditure for the doctor and the patient. At the same time, the use of mathematical models based on artificial neural networks (ANN- models) currently makes it possible to automate many processes associated with image processing. Therefore, solving problems associated with automating the process of classifying OCT images based on ANN models is actual.
 Aims. To develop architectures of mathematical (computer) models based on deep learning of convolutional neural networks (CNN) for classification of OCT images of the retina. To compare the results of computational experiments conducted using Python tools in the Google Colaboratory with single-model and multi-model approaches and evaluate classification accuracy. To make conclusions about the optimal architecture of ANN models and the values of the hyperparameters used.
 Materials and methods. The original dataset, which was anonymized OCT images of real patients, included more than 2000 images obtained directly from the device in a resolution of 1920 × 969 × 24 BPP. The number of image classes is 12. To create the training and validation data sets, a subject area of 1100 × 550 × 24 BPP was “cut out.” Various approaches were studied: the possibility of using pretrained CNNs with transfer learning, techniques for resizing and augmenting images, as well as various combinations of hyperparameters of ANN-models. When compiling the model, the following parameters were used: Adam optimizer, categorical_crossentropy loss function, accuracy metric. All technological processes with images and ANN-models were carried out using Python language tools in Google Colaboratory.
 Results. Single-model and multi-model principles for classifying OCT images of the retina are proposed. Computational experiments on automated classification of such images obtained from a DRI OCT Triton 3D tomograph using various ANN model architectures showed an accuracy of 98-100% during training and validation and 85% during an additional test, which is a satisfactory result. The optimal architecture of the ANN model - a six-layer convolutional network - was selected and the values of its hyperparameters were determined.
 Conclusions. The results of deep training of convolutional neural network models with various architectures, their validation and testing showed satisfactory classification accuracy of retinal OCT images. These developments can be used in decision support systems in the field of ophthalmology.

On radially symmetric oscillations of a collisional cold plasma

We study the influence of the friction term on the radially symmetric solutions of the repulsive Euler–Poisson equations with a non‐zero background, corresponding to cold plasma oscillations in multiple spatial dimensions. It is shown that for any arbitrarily small non‐negative constant friction coefficient, there exists a neighborhood of the zero equilibrium in the norm such that the solution of the Cauchy problem with initial data belonging to this neighborhood remains globally smooth in time. Moreover, this solution converges to zero as . This result contrasts with the situation of zero friction, where any small deviation from the zero equilibrium generally leads to a blow‐up. Our method allows us to estimate the lifetime of smooth solutions. Further, we prove that for any initial data, one can find such a coefficient of friction that the respective solution to the Cauchy problem keeps smoothness for all and converges to zero. We also present the results of numerical experiments for physically reasonable situations, which allows us to estimate the value of the friction coefficient, which makes it possible to suppress the formation of singularities of solutions.

Direction-dependent failure envelopes of sand-structure interfaces with snakeskin-inspired surfaces

Snakeskin-inspired surfaces generate direction-dependent interface strengths, with shearing in the cranial direction (i.e.; against the scales) generating greater strength than in the caudal one (i.e.; along the scales). This directionality is enabled by the transfer of load in friction and passive resistances. It is unclear if failure of these interfaces can be captured by models used for purely frictional interfaces. Interface shear tests complemented with particle image velocimetry (PIV) analyses were performed on snakeskin-inspired surfaces with different asperity geometries and on reference rough and smooth surfaces. The results of experiments performed at different initial effective stresses under constant normal stiffness boundary conditions show significant dilation-induced increases in effective stress. These increases were greater during cranial than caudal shearing, producing greater cranial strengths. These surfaces yielded nonlinear failure envelopes, with greater shear to effective stress ratios at smaller effective stresses, while the rough and smooth surfaces mobilized linear failure envelopes. The PIV analyses indicate that the snakeskin-inspired surfaces induce localized strains in the vicinity of the asperities, leading to wavy failure planes. The average shear strains are correlated with the mobilized shear strengths, with increases in effective stress leading to decreases in both strains and stress ratio.

Coaxial Electrospun Porous Core-Shell Nanofibrous Membranes for Photodegradation of Organic Dyes.

In this study, a series of AgCl/ZnO-loaded nanofibrous membranes were prepared using coaxial electrospinning. Their physical and chemical characteristics were evaluated by SEM, TEM, XRD, XPS, IR, PL, and UV-visible spectrometer, and the photocatalytic experiments using methylene blue (MB) as a model pollutant. The formation of AgCl/ZnO heterojunction and the structure of core-shell nanofibers with porous shell layer were confirmed. AgCl/ZnO photocatalysts were also effectively loaded onto the surfaces of the porous core-shell nanofibers. The results of photocatalytic experiments revealed that the AgCl/ZnO (MAgCl:MZnO = 5:5)-loaded nanofibrous membrane achieved a degradation efficiency of 98% in just 70 min and maintained a photocatalytic efficiency exceeding 95% over the first five experimental cycles, which successfully addressed the issues of photocatalytic efficiency loss during the photodegradation of MB with AgCl/ZnO nanoparticles as photocatalyst. The photodegradation mechanism was also researched and proposed.

Inkjet printer prediction under complicated printing conditions based on microscopic image features

A novel technique is introduced to predict the printer model used to produce a given document. Samples containing only a few letters printed under varying conditions (i.e., different printing modes, letter types, fonts) were collected to establish a dataset of 41 inkjet printer models from common manufacturers, such as HP, Canon, and Epson. Morphological features were analyzed by extraction of image features using several algorithms in a series of microscopic images and a Wilcoxon test was used to measure the significance of variations between printed samples. Significant differences between various printing conditions might post potential challenge to questioned document examination. Discriminant analysis and the k-nearest neighbor (KNN) algorithm were also employed for source printer prediction under varying printing condition on 30% images with the rest images as training dataset. The results of a validation experiment demonstrated that while quadratic discriminant analysis (QDA) achieved an accuracy of 96.3%, a combination of KNN and QDA reached 98.6%. As such, this technique could aid in the forensic examination of printed documents.

Performing Quantitative PCR after Chromatin Immunoprecipitation (ChIP) of Drosophila Antennal and Brain Samples.

Chromatin immunoprecipitation (ChIP) is a technique used to study specific protein-DNA interaction. Briefly, in this technique, antibodies to proteins of interest are used to isolate regions of DNA where these proteins bind. ChIP samples can be processed and analyzed in different ways. One of the approaches for assessing the results of ChIP experiments is quantitative PCR (qPCR). qPCR is used to quantitatively measure the amount of DNA fragments that have been isolated, reflecting the signal of specific proteins interacting with these fragments. This protocol describes both the "percent input" method and the "fold enrichment" method for ChIP-qPCR data analysis using Drosophila tissues as an example. The "percent input" method measures signals of DNA fragments against the input measurement. In contrast, the "fold enrichment" method quantifies the amplified signal strength relative to a background control. Because the quality of primers is critical for the reliability of ChIP-qPCR results, this protocol also describes how to measure primer amplification efficiency using Drosophila genomic DNA.

Research and Development of Steel Fiber Reinforced Concrete Filling Material and Its Application in Gob-Side Entry Retaining Technology in Deep Mines

Against the background of the prevailing green development paradigm, numerous coal mines have embraced the adoption of gob-side entry retaining mining technology. The most commonly employed form of gob-side entry retaining involves building an artificial wall along the edge of the goaf behind the working face to maintain the roadway. The pivotal challenge in gob-side entry retaining lies in the roadside support. Currently, commonplace concrete serves as the predominant material for the roadside filling body. Nevertheless, traditional concrete exhibits drawbacks, including inadequate tensile strength and poor toughness, leading to wall cracks or even collapses in the retaining wall. Steel fiber, a frequently employed reinforcement and toughening agent in concrete, has found widespread application in the construction sector and other fields. However, its use as a roadside filling material in underground coal mines remains infrequent. Therefore, in this paper, the flow and mechanical properties of steel fiber concrete were tested and analyzed, and field industrial tests were conducted. Results of indoor experiments show that steel fibers reduce the slump of concrete. The addition of steel fibers shifted the pore compacting stage, linear elasticity stage, and destabilization stage forward and improved the post-peak bearing capacity. The addition of steel fibers makes the concrete compressive and tensile strength show a “first increase and then decrease” trend; both peaked at 1.5%, and the increase in tensile strength is more pronounced. Steel fibers enhance the strength of compressive strength of concrete at an early age, weaker at a late age, and tensile strength inversely. The addition of steel fiber can change the concrete matrix from tensile damage to shear damage, and the toughness index shows the trend of “first increase and then decrease”, and reaches the peak value when the dosage is 1.5%. Industrial test results show that steel fiber concrete as a roadside filling body can reduce the surrounding rock surface displacement and bolt (cable) force.

Selective Recovery of Lithium Hydroxide from Spent NCA (LiNiCoAlO2) Powder

This research was conducted on the method of recovering the lithium hydroxide and valuable metal from the NCA-based cathode active materials in the spent lithium-ion batteries. The recovery rate of lithium depends on the reaction temperature, retention time, reaction time during H2 reduction and solid-liquid ratio. Lithium hydroxide and valuable metals were recovered under each experimental condition, and the following optimal process conditions were determined based on the results of experiment. Based on the charging of 10g of NCA powder, the optimal process conditions were determined as follows: the reaction temperature of 700?; the retention time of 3hrs; and the H2 gas flowrate of 300cc/min; the leaching time of 1hr for water leaching; the solid-liquid ratio of the sample and distilled water at 1:30; the stirring speed of 300rpm at room temperature, and the recovery rate of 92.30% was achieved.

Adjuvant screening of the Senecavirus A inactivated vaccine in mice and evaluation of its immunogenicity in pigs

BackgroundSenecavirus A (SVA) causes an emerging vesicular disease (VD) with clinical symptoms indistinguishable from other vesicular diseases, including vesicular stomatitis (VS), foot-and-mouth disease (FMD), and swine vesicular disease (SVD). Currently, SVA outbreaks have been reported in Canada, the U.S.A, Brazil, Thailand, Vietnam, Colombia, and China. Based on the experience of prevention and control of FMDV, vaccines are the best means to prevent SVA transmission.ResultsAfter preparing an SVA inactivated vaccine (CH-GX-01-2019), we evaluated the immunogenicity of the SVA inactivated vaccine mixed with Imject® Alum (SVA + AL) or Montanide ISA 201 (SVA + 201) adjuvant in mice, as well as the immunogenicity of the SVA inactivated vaccine combined with Montanide ISA 201 adjuvant in post-weaned pigs. The results of the mouse experiment showed that the immune effects in the SVA + 201 group were superior to that in the SVA + AL group. Results from pigs immunized with SVA inactivated vaccine combined with Montanide ISA 201 showed that the immune effects were largely consistent between the SVA-H group (200 µg) and SVA-L group (50 µg); the viral load in tissues and blood was significantly reduced and no clinical symptoms occurred in the vaccinated pigs.ConclusionsMontanide ISA 201 is a better adjuvant choice than the Imject® Alum adjuvant in the SVA inactivated vaccine preparation, and the CH-GX-01-2019 SVA inactivated vaccine can provide effective protection for pigs.

Flying Target Detection Technology Based on GNSS Multipath Signals.

In this study, a passive radar system that detects flying targets is developed in order to solve the problems associated with traditional flying target detection systems (i.e., their large size, high power consumption, complex systems, and poor battlefield survivability). On the basis of target detection, the system uses the multipath signal (which is usually eliminated as an error term in navigation and positioning), enhances it by supporting information, and utilizes the multi-source characteristics of ordinary omnidirectional global navigation satellite system (GNSS) signals. The results of a validation experiment showed that the system is able to locate a passenger airplane and obtain its flight trajectory using only one GNSS receiving antenna. The system is characterized by its light weight (less than 5 kg), low power consumption, simple system, good portability, low cost, and 24/7 and all-weather work. It can be installed in large quantities and has good prospects for development.

Numerical simulation investigation of the mechanism of lacquer curtain formation in curtain coating

To study the key factors on integrated curtain formation and breakup in curtain coating production process, we used the numerical simulation method to analyze the various stages of the curtains from full curtain to full thread state by changing the inlet flow rate, which is, changing the Weber number (We). The numerical model was based on an actual production machine, and the physical properties of the lacquer were accurately measured for the simulation. It is found that with the gradual breakup of the curtain, the oscillation of the curtain gradually increased, there was obvious distortion and increase in Turbulent Viscosity Ratio (TVR) at the breakup, and there was a decrease in Dynamic Pressure (DP) at the top of the breakup. Different curtain state reflects a shift from inertia force dominance to a balance of forces and finally to surface tension dominance. The finding from the simulation, also the comparison between the results of simulation and experiments provided the basis to understand the mechanism of curtain coating, also inspired the engineers to optimize the geometry of curtain coater and the coating production parameters for easier integrated curtain forming.

Processing of Legume Green Manures Slowdowns C Release, Reduces N Losses and Increases N Synchronisation Index for Two Years

The number of livestock farms decreased by 40% in Europe over the last 10-year period. Stockless organic cropping systems started to dominate in many intensive agricultural regions in Europe. Developing the sustainable management of an organic stockless agroecosystem is related to guaranteeing self-sufficiency in nitrogen (N) supply, maintaining high grain yields, and promoting carbon (C) sequestration in the soil. The aim of this study was to investigate if the processed legume green manures can be an alternative to granulated cattle manure and direct ploughing of legume biomass in order to develop the sustainability of the stockless organic cropping system. The decomposition rate and C and N release were observed for green manures made of fermented red clover and composted red clover with wheat straw. Fresh red clover biomass and granulated cattle manure were used for the comparison. Results of the 3-year field experiment showed that technologically processed legume biomass had a positive effect on the productivity of crops at least two years in rotation. Fermented red clover and red clover compost increased N use efficiency by 15% and biomass output efficiency by 16% compared with fresh red clover biomass. Processed legume green manures significantly increased the synchronisation index between crop N demand and N supply. In autumn, incorporated fresh red clover biomass lost 65.6% of its initial C and 37.6 kg ha−1 (50.1%) of its initial N under decomposition in the first non-growing season. It also increased mineral N losses deeper into the subsoil by 52.7%. Meanwhile, fermented red clover and red clover compost released 43% of its N during the first crop growing season, sustained at least one year slower C release to the soil, promoted ecosystem productivity, prevented mineral N losses to subsoil and gained high N synchrony indexes. The best N synchrony was achieved using fermented red clover, with a higher decomposition rate positively significantly correlated (r = 0.47–0.78, p < 0.05) with grain yield, total biomass, protein content and total N accumulated in the plant of spring wheat and spring barley.