Pair Distance Research Articles

PLD2flex: Establishing the Phonological Levenshtein Distance for Pairs or Groups of (Pseudo)Words

PLD2flex: Establishing the Phonological Levenshtein Distance for Pairs or Groups of (Pseudo)Words

Visualization of the Distance-Dependent Synergistic Interaction in Heterogeneous Dual-Site Catalysis.

Understanding the characteristics of interfacial hydroxyl (OH) at the solid/liquid electrochemical interface is crucial for deciphering synergistic catalysis. However, it remains challenging to elucidate the influences of spatial distance between interfacial OH and neighboring reactants on reaction kinetics at the atomic level. Herein, we visualize the distance-dependent synergistic interaction in heterogeneous dual-site catalysis by using ex-situ infrared nanospectroscopy and in situ infrared spectroscopy techniques. These spectroscopic techniques achieve direct identification of the spatial distribution of synergistic species and reveal that OH facilitates the reactant deprotonation process depending on site distances in dual-site catalysts. Via modulating Ir-Co pair distances, we find that the dynamic equilibrium between generation and consumption of OH accounts for high-efficiency synergism at the optimized distance of 7.9 Å. At farther or shorter distances, spatial inaccessibility and resistance of OH with intermediates lead to OH accumulation, thereby diminishing the synergistic effect. Hence, a volcano-shaped curve has been established between the spatial distance and mass activity using formic acid oxidation as the probe reaction. This notion could also be extended to oxophilic metals, like Ir-Ru pairs, where volcano curves and dynamic equilibrium further evidence the universal significance of spatial distances.

Influence of design parameters on heat production of a multilateral butted closed loop geothermal system

To efficiently develop hot dry rock and other geothermal energy, a multilateral butted closed loop geothermal system (MBCLGS) is presented in this paper to replace the U-shaped closed-loop geothermal system (UCLGS). Besides, a casing-cement-formation transient heat transfer model is established to investigate the influences of key factors on the heat production of MBCLGS. After thermal-fluid-structural coupling analysis, we can find that higher injected rate and lower fluid temperature can improve heat power but reduce output temperature. In addition, the output temperature and heat power do not increase continuously with the increasing of branch well number. There is an optimal value of branch well number. Longer well pair distance can improve both output temperature and heat power. Considering the drilling technology level and design purpose, the recommended injected flow rate of MBCLGS is 90 m3/h, the injected fluid temperature is 42.5 °C, the number of branch wells is 10 and the well pair distance is 200m. Finally, by comparing MBCLGS and UCLGS, it is found that MBCLGS has a lower temperature decline rate and higher output temperature than UCLGS under the same conditions. It works more stable and has better economy. Overall, the proposal of MBCLGS is expected to promote the efficient development of deep geothermal resources.

Coordinate-based simulation of pair distance distribution functions for small and large molecular assemblies: implementation and applications.

X-ray scattering has become a major tool in the structural characterization of nanoscale materials. Thanks to the widely available experimental and computational atomic models, coordinate-based X-ray scattering simulation has played a crucial role in data interpretation in the past two decades. However, simulation of real-space pair distance distribution functions (PDDFs) from small- and wide-angle X-ray scattering, SAXS/WAXS, has been relatively less exploited. This study presents a comparison of PDDF simulation methods, which are applied to molecular structures that range in size from β-cyclo-dextrin [1 kDa molecular weight (MW), 66 non-hydrogen atoms] to the satellite tobacco mosaic virus capsid (1.1 MDa MW, 81 960 non-hydrogen atoms). The results demonstrate the power of interpretation of experimental SAXS/WAXS from the real-space view, particularly by providing a more intuitive method for understanding of partial structure contributions. Furthermore, the computational efficiency of PDDF simulation algorithms makes them attractive as approaches for the analysis of large nanoscale materials and biological assemblies. The simulation methods demonstrated in this article have been implemented in stand-alone software, SolX 3.0, which is available to download from https://12idb.xray.aps.anl.gov/solx.html.

Amide–π Interactions in the Structural Stability of Proteins: Role in the Oligomeric Phycocyanins

This study investigates the influences and environmental preferences of amide–π interactions, a relatively unexplored class of charge-free interactions, in oligomeric phycocyanins. In a data set of 20 proteins, we observed 2086 amide–π interactions, all of which were part of the protein backbone. Phe and Tyr residues were found to be involved in amide–π interactions more frequently than Trp or His. The most favorable amide–π interactions occurred within a pair distance range of 5–7 Å, with a distinct angle preference for T-shaped ring arrangements. Multiple interaction patterns suggest that approximately 76% of the total interacting residues participate in multiple amide–π interactions. Our ab initio calculations revealed that most amide–π interactions have energy from 0 to −2 kcal/mol. Stabilization centers of phycocyanins showed that all residues in amide–π interactions play a crucial role in locating one or more such centers. Around 78% of the total interacting residues in the dataset contribute to creating hot-spot regions. Notably, the amide–π interacting residues were found to be highly evolutionarily conserved. These findings enhance our understanding of the structural stability and potential for protein engineering of phycocyanins used as bioactive natural colorants in various industries, including food and pharmaceuticals.

Potential energy of heavy quarkonium in flavor-dependent systems from a holographic model

Within the framework of the Einstein-Maxwell-dilaton model, which incorporates information on the equation of state and baryon number susceptibility from lattice results, we have conducted a comprehensive analysis of the potential energy, running coupling, and dissociation time for heavy-quark–antiquark pairs using gauge/gravity duality. This study encompasses various systems, including pure gluon systems, 2-flavor systems, 2+1-flavor systems, and 2+1+1-flavor systems under finite temperature and chemical potential. The results reveal that the linear component of the potential energy diminishes as the flavor increases. It is also found that our results are extremely close to the recent lattice results for 2+1-flavors at finite temperature. Moreover, we have thoroughly investigated the dissociation distance and effective running coupling constant of quark-antiquark pairs to gain a comprehensive understanding of their behavior across various flavors. Finally, we have examined real-time dynamics of quark dissociation. The findings indicate that the dissociation time of quark-antiquark pairs is dependent on temperature, chemical potential, and flavor of the systems. Published by the American Physical Society 2024

Electron diffraction of foam-like clusters between xenon and helium in superfluid helium droplets.

We report electron diffraction results of xenon clusters formed in superfluid helium droplets, with droplet sizes in the range of 105-106 atoms/droplet and xenon clusters from a few to a few hundred atoms. Under four different experimental conditions, the diffraction profiles can be fitted using four atom pairs of Xe. For the two experiments performed with higher helium contributions, the fittings with one pair of Xe-He and three pairs of Xe-Xe distances are statistically preferred compared with four pairs of Xe-Xe distances, while the other two experiments exhibit the opposite preference. In addition to the shortest pair distances corresponding to the van der Waals distances of Xe-He and Xe-Xe, the longer distances are in the range of the different arrangements of Xe-He-Xe and Xe-He-He-Xe. The number of independent atom pairs is too many for the small xenon clusters and too few for the large clusters. We consider these results evidence of xenon foam structures, with helium atoms stuck between Xe atoms. This possibility is confirmed by helium time-dependent density functional calculations. When the impact parameter of the second xenon atom is a few Angstroms or longer, the second xenon atom fails to penetrate the solvation shell of the first atom, resulting in a dimer with a few He atoms in between the two Xe atoms. In addition, our results for larger droplets point toward a multi-center growth process of dopant atoms or molecules, which is in agreement with previous proposals from theoretical calculations and experimental results.

Steering the Site Distance of Atomic Cu-Cu Pairs by First-Shell Halogen Coordination Boosts CO2-to-C2 Selectivity.

Electrocatalytic reduction of CO2 into C2 products of high economic value provides a promising strategy to realize resourceful CO2 utilization. Rational design and construct dual sites to realize the CO protonation and C-C coupling to unravel their structure-performance correlation is of great significance in catalysing electrochemical CO2 reduction reactions. Herein, Cu-Cu dual sites with different site distance coordinated by halogen at the first-shell are constructed and shows a higher intramolecular electron redispersion and coordination symmetry configurations. The long-range Cu-Cu (Cu-I-Cu) dual sites show an enhanced Faraday efficiency of C2 products, up to 74.1 %, and excellent stability. In addition, the linear relationships that the long-range Cu-Cu dual sites are accelerated to C2H4 generation and short-range Cu-Cu (Cu-Cl-Cu) dual sites are beneficial for C2H5OH formation are disclosed. In situ electrochemical attenuated total reflection surface enhanced infrared absorption spectroscopy, in situ Raman and theoretical calculations manifest that long-range Cu-Cu dual sites can weaken reaction energy barriers of CO hydrogenation and C-C coupling, as well as accelerating deoxygenation of *CH2CHO. This study uncovers the exploitation of site-distance-dependent electrochemical properties to steer the CO2 reduction pathway, as well as a potential generic tactic to target C2 synthesis by constructing the desired Cu-Cu dual sites.

Elucidating the local structure and electronic properties of a highly active overall alkaline water splitting NixCo1-xO/hollow carbon sphere catalyst

A NixCo1-xO/HCS catalyst with superior water-splitting is presented. High water-splitting reaction kinetics and enhanced durability were observed. The structure-function relationship was investigated with XPS, which demonstrated the presence of dominant Ni2+ and Co2+ species and a functionalized HCS support where nucleation of small metal oxide nanoparticles occurred. The PDF showed broadened Nickel/Cobalt-oxide bonds and expansion of the metal-metal pair distances. The alteration of the Metal-Oxide and Metal-Metal-Oxide bonds favored better HER and OER electrocatalysis, also as supported by DFT. EXAFS showed the existence of the bimetallic oxide catalyst and the stretching of the Ni–O bonds due to the coordination of the Ni–O with the Co. The composite exhibited higher activity and enhanced electrocatalytic mechanism towards water splitting through higher exchange current densities (0.615 and 0.886 mA cm−2) and low charge transfer resistance (14 and 10 Ω) respectively. Chronoamperometry proved the catalyst's stability during prolonged electrolysis.

Loosely Bounded Exciton with Enhanced Delocalization Capability Boosting Efficiency of Organic Solar Cells.

In organic solar cells (OSCs), electronacceptorshaveundergone multipleupdates, from the initial fullerene derivatives, to the later acceptor-donor-acceptor type non-fullerene acceptors (NFAs), and now to Y-series NFAs, based on which efficiencies have reached over 19%. However, the key property responsible for further improved efficiency from molecular structure design is remained unclear. Herein, the material properties are comprehensively scanned by selecting PC71BM, IT-4F, and L8-BO as the representatives for different development stages of acceptors. For comparison, asymmetric acceptor of BTP-H5 with desired loosely bounded excitons is designed and synthesized. It's identified that the reduction of intrinsically exciton binding energy (Eb) and the enhancement of exciton delocalization capability act as the key roles in boosting the performance. Notably, 100 meV reduction in Eb has been observed from PC71BM to BTP-H5, correspondingly, electron-hole pair distance of BTP-H5 is almost two times over PC71BM. As a result, efficiency is improved from 40% of S-Q limit for PC71BM-based OSC to 60% for BTP-H5-based one, which achieves an efficiency of 19.07%, among the highest values for binary OSCs. This work reveals the confirmed function of exciton delocalization capability quantitatively in pushing the efficiency of OSCs, thus providing an enlightenment for future molecular design.

Evaporation-induced self-assembly of Janus pyramid molecules from fractal network to core-shell nanoclusters evidenced by small-angle X-ray scattering

Self-assembly of nanoclusters (NCs) is an effective synthetic method for preparing functionalized nanomaterials. However, the assembly process and mechanisms in solutions still remain ambiguous owing to the limited strategies to monitor intermediate assembled states. Herein, the self-assembly process of amphiphilic molecule 4POSS-DL-POM (consisting of four polyhedral oligomeric silsesquioxanes, a dendritic linker, and one polyoxometalate) by evaporation of acetone in a mixed acetone/n-decane solution is monitored by time-resolved synchrotron small-angle X-ray scattering (SAXS). Scattering data assessments, including Kratky analysis, pair distance distribution function, and model fitting, track the self-assembly process of 4POSS-DL-POM from a fractal network to compact NCs, then to core–shell NCs, and finally to superlattice structure. The calculated average aggregation number of a core–shell NC is 11 according to the parameters obtained from core-shell model fitting, in agreement with electron microscopy. The fundamental understanding of the self-assembly dynamics from heterocluster into NCs provides principles to control building block shape and guide target aggregation, which can further promote the design and construction of highly ordered cluster-assembled functional nanomaterials.

Measurement of outer diameter parameters of manual grinding cable joints based on 3D point cloud processing

For the problems associated with low measurement accuracy caused by surface shrinkage, uneven grinding, and irregular shapes in manual grinding cable joints, as well as the limitations of existing machine vision measurement techniques for the outer diameter parameters, this paper proposes a non-contact outer diameter parameters measurement method of manual grinding cable joints based on three-dimensional (3D) point cloud processing. Firstly, statistical filtering is used to remove discrete noise, and coordinate transformation preprocessing is conducted to ordered the point cloud. Secondly, a bidirectional point cloud slicing method is proposed based on the cable joint structure and point cloud distribution to preserve the original features for effective measurement. Subsequently, the normalized mean curvature is utilized as the weight of point cloud coordinate averaging to construct key points for surface slices, which reduces the amount of data in the sliced point cloud and improves the matching efficiency. Finally, the key points are matched according to the position of the surface slices, and the distance of point pairs is calculated to complete the measurement of the outer diameter parameters. Experiments and error analysis are conducted on multiple manual grinding 110 kV and 500 kV real cable joints. The absolute error in the measurement of the outer diameter is less than 0.2 mm, with a relative error within 1 %. The absolute error of the XY-axis outer diameter deviation is less than 0.1 mm. The experiments demonstrate that the proposed method exhibits superior performance in cable joint outer diameter measurement.

Elucidating the failure of the Ideal Adsorbed Solution Theory for CO2/H2O mixture adsorption in CALF-20

The use of CALF-20 for CO2 capture from humid flue gases has attracted a vast amount of attention from both academia and industry. The focus of this article is on CO2/H2O mixture adsorption for which published experimental data demonstrate the severe limitations of the Ideal Adsorbed Solution Theory (IAST) in providing a quantitative estimation of the component loadings. We use Configurational-Bias Monte Carlo (CBMC) simulations for elucidating the origins of thermodynamic non-idealities. The CBMC simulations reveal that two distinct regimes prevail during mixture adsorption. For low relative humidities less than say 20 %, the CO2 loadings in the adsorbed phase is significantly higher than anticipated by the IAST. CBMC simulations of intermolecular distances for guest pairs reveal that failure of the IAST can be traced to the phenomenon of segregated adsorption. The H2O-H2O pairs are close together at typical distances of about 3 Å. The CO2-H2O pairs are typically 8 Å apart, occupying adjacent adsorption sites corresponding to the O atoms of the oxalate group. This implies that the CO2 molecules face a less severe competitive adsorption with H2O than is anticipated by the IAST, whose applicability mandates a uniform and homogeneous distribution of adsorbates in pore space. The situation changes dramatically at high values of relative humidities, typically larger than about 50 %; in this scenario, the adsorbed phase is significantly richer in H2O. The CO2 molecules are compelled to share same adsorption site with pairs of H2O molecules that are hydrogen-bonded with each other. Consequently, the competition faced by CO2 is significantly higher than anticipated by the IAST, resulting in significantly lower CO2 uptakes.The important message that emerges from this investigation is the need to incorporate the Real Adsorbed Solution Theory (RAST) for quantitative modelling of fixed-bed adsorbers in CO2 capture with CALF-20.

Catalytic NIR chemiluminescence sensor with enhanced persistence and intensity for in vivo imaging

Chemiluminescence (CL) is a self-illumination phenomenon that involves the emission of light from chemical reactions, and it provides favorable spatial and temporal information on biological processes. However, it is still a great challenge to construct effective CL sensors that equip strong CL intensity, long emission wavelength, and persistent luminescence for deep tissue imaging. Here, we report a liposome encapsulated polymer dots (Pdots)-based system using catalytic CL substrates (L-012) as energy donor and fluorescent polymers and dyes (NIR 695) as energy acceptors for efficient Near-infrared (NIR) CL in vivo imaging. Thanks to the modulation of paired donor and acceptor distance and the slow diffusion of biomarker by liposome, the Pdots show a NIR emission wavelength (λ em, max = 720 nm), long CL duration (>24 h), and a high chemiluminescence resonance energy transfer efficiency (46.5 %). Furthermore, the liposome encapsulated Pdots possess excellent biocompatibility, sensitive response to H2O2, and persistent whole-body NIR CL imaging in the drug-induced inflammation and the peritoneal metastatic tumor mouse model. In a word, this NIR-II CL nanoplatform with long-lasting emission and high spatial-temporal resolution will be a concise strategy in deep tissue imaging and clinical diagnostics.

Cherry growth modeling based on Prior Distance Embedding contrastive learning: Pre-training, anomaly detection, semantic segmentation, and temporal modeling

In current plant phenotyping research, the study of plant time-series images based on deep learning has received widespread attention. While such image data is relatively easy to obtain, the cost of annotation is high. One efficient method for achieving cost-effective training is through contrastive learning. Plant growth is slow, and the changes in image sequences over a period of time are small, with simple semantic information. Previous contrastive pre-training models struggled to effectively distinguish positive samples from the same image with different augmented views and similar negative samples from different images. Therefore, this paper proposes a method called self-supervised contrastive learning method for plant time-series images with a Priori Distance Embedding (PDE). The semantic information in images corresponding to different phenological stages of plants varies. This method transforms this crucial domain knowledge into prior distances for image pairs and conducts contrastive learning pre-training. The learned weights can be transferred to downstream tasks. Building upon this method, experiments were conducted on cherry time-series images to assess the quality of pre-training through a plant phenotyping image semantic segmentation task. To provide a comprehensive example of plant time-series image phenotypic analysis, this paper establishes a cherry growth temporal model, specifically including PDE pre-training, anomaly detection, semantic segmentation, and recording the results from the temporal dimension. The experiments indicate that this self-supervised contrastive learning method can be effectively applied to the pre-training of plant time-series images, demonstrating broad applicability in various computer vision studies related to plant phenotyping.

First PWV Retrieval Using MERSI‐LL Onboard FY‐3E and Cross Validation With Co‐Platform Occultation and Ground GNSS

AbstractFY‐3E plays a vital role in the meteorological global earth observing system. Precipitable water vapor (PWV) is an essential parameter for the water cycle and global climate change. Here, we carry out the PWV retrieval using the MERSI‐LL sensor onboard the FY‐3E satellite for the first time. The retrieval accuracy under different cloudage conditions is validated by the extra PWV from ground‐based GNSS and spaceborne occultation. For the results against ground‐based GNSS, the total accuracy shows an RMSE of 2.69–3.36 mm as the clouds increase, and correlation coefficients higher than 0.95. The spatial accuracy distribution indicates that inland stations have higher accuracy than the coast and island stations. As for the results against spaceborne occultation, the verification accuracy varies with the spatial pairing distance, showing poor accuracy in the low latitude area. This study can provide an essential reference for the community to understand the current water vapor inversion performance of MERSI‐LL.

Insights into elastic properties of coarse-grained DNA models: q-stiffness of cgDNA vs cgDNA.

Coarse-grained models have emerged as valuable tools to simulate long DNA molecules while maintaining computational efficiency. These models aim at preserving interactions among coarse-grained variables in a manner that mirrors the underlying atomistic description. We explore here a method for testing coarse-grained vs all-atom models using stiffness matrices in Fourier space (q-stiffnesses), which are particularly suited to probe DNA elasticity at different length scales. We focus on a class of coarse-grained rigid base DNA models known as cgDNA and its most recent version, cgDNA+. Our analysis shows that while cgDNA+ closely follows the q-stiffnesses of the all-atom model, the original cgDNA shows some deviations for twist and bending variables, which are rather strong in the q → 0 (long length scale) limit. The consequence is that while both cgDNA and cgDNA+ give a suitable description of local elastic behavior, the former misses some effects that manifest themselves at longer length scales. In particular, cgDNA performs poorly on twist stiffness, with a value much lower than expected for long DNA molecules. Conversely, the all-atom and cgDNA+ twist are strongly length scale dependent: DNA is torsionally soft at a few base pair distances but becomes more rigid at distances of a few dozen base pairs. Our analysis shows that the bending persistence length in all-atom and cgDNA+ is somewhat overestimated.

Abstract 5978: Therapeutic targeting of MELK using a drug repurposing approach to combat TNBC cells

Abstract Background: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer linked to high chemo-resistant metastatic cases and limited therapeutic options due to the absence of conventional bioreceptors. Therefore, to treat TNBC, it is imperative to identify promising druggable biological targets. Experimental Procedures: An integrated bioinformatic analysis of microarray datasets was performed to identify significantly differentially expressed genes (DEGs) in TNBC. For selecting a potent therapeutic target, the function and significance of the upregulated DEGs in TNBC was investigated by an in silico study employing the UALCAN portal, String database, KM plotter, and Enrichr tools. This analysis included gene expression validation, insights into protein-protein interactions, survival analysis, and pathway mapping of the genes. To obtain potent drugs binding to the selected target MELK (maternal embryonic leucine zipper kinase), a drug repurposing approach was employed starting with virtual screening followed by molecular dynamic simulation (MDS) using GROMACS. Further, the anti-cancer activity of the top two drugs was validated by live-dead imaging, gene expression analyses, MTT-based cell viability and ROS detection assays. Results: Based on a stringent criterion for significant DEG identification (log2|FC|>1 & adjust P-value < 0.05), 25 overlapping upregulated genes were obtained from three selected datasets. Further, in silico analysis revealed that MELK is significantly upregulated across the four stages and subtypes of breast cancer, including TNBC. Higher MELK expression and its oncogenic interactions correlated with poor overall survival of TNBC patients. Evidence suggests that the existing inhibitor for MELK (OTSSP167) has shown poor specificity. Therefore, to block its activity, a library of 1293 FDA-approved drugs was screened against the kinase domain of MELK. MDS study and analysis using parameters like RMSD, RMSF and pair distance revealed that the top 10 drugs were strongly stabilized by H-bonds in the binding pocket of MELK, with minimal deviation and reduced fluctuations of MELK upon drug binding. Binding free energy calculation of drug-MELK interaction using the MM-PBSA method revealed that nine drugs possessed higher binding energy than the inhibitor. The top two drugs obtained from the study (originally kinase and reductase inhibitors respectively) were further validated for their in vitro anti-cancer efficacy in MDA-MB-231 and MDA-MB-468 cells. Treatment with these drugs exhibited (a) a dose-dependent decrease in proliferation, (b) significant cell death, (c) a marked increase in the cellular ROS levels, and (d) a decrease in the expression of MELK and its downstream targets in TNBC cell lines. Conclusion: The present study opens the avenue for using repurposed drugs as potential therapeutic molecules against MELK activity to combat TNBC progression. Citation Format: Arisha Arora, Shilpi Sarkar, Siddhartha S. Ghosh. Therapeutic targeting of MELK using a drug repurposing approach to combat TNBC cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5978.

The Effect of Branchless Collisions and Population Control on Correlations in Monte Carlo Power Iteration

The investigation of correlations in Monte Carlo power iteration has long been dominated by the question of generational correlations and their effects on the estimation of statistical uncertainties. More recently, there has been a growing interest in spatial correlations, prompted by the discovery of neutron clustering. Despite several attempts, a comprehensive framework concerning how Monte Carlo sampling strategies, population control, and variance reduction methods affect the strength of such correlations is still lacking. In this work, we propose a set of global and local (i.e., space-dependent) tallies that can be used to characterize the impact of correlations. These tallies encompass Shannon entropy, pair distance, normalized variance, and Feynman moment. In order to have a clean yet fully meaningful setting, we carry out our analysis in a few homogeneous and heterogeneous benchmark problems of varying dominance ratio. Several classes of collision sampling strategies, population control, and variance reduction techniques are tested, and their relative advantages and drawbacks are assessed with respect to the proposed tallies. The major finding of our study is that branchless collisions, which suppress the emergence of branches in neutron histories, also considerably reduce the effects of correlations in most of the explored configurations.

Цифровая обработка фотометрических данных дистанционного зондирования полей озимой ржи

Abstract. The paper considers the possibility of using neural network structures of an artificial intelligence system for processing photometric data of remote sensing of winter rye crops grown in the conditions of the Leningrad Region on the field of the educational and experimental garden of Saint Petersburg State Agrarian University in 2014–2015. In the process of cultivating plants, various types of treatments were applied: the application of mineral fertilizers, microelements and a microbial biological product. To process the photometric data, the Rosenblatt perceptron was used, which analyzes the similarities and differences in the photometric NDVI profiles of winter rye crops obtained from different variants of the experiment. According to the numerical indicators of vegetation indices, it was possible to construct phase portraits of the trajectory of their movement on the coordinate plane of the field. Further cluster analysis of the data obtained, converted into a square matrix of paired Euclidean distances, made it possible to identify on the dendrogram a grouping of variants in which the connecting components were the use of a microbiological inoculant. When using a biological product, there is a more complete development of plants in crops and their evenness in the field improves. The minimum coefficient of variation was observed for the variant without the use of a biological product, but with the joint use of a complex of all mineral fertilizers (50 phosphorite flour + 50 KCl + 50 ammonium nitrate) and microelements at a dose of 250 kg/ha. Based on the results of the analysis, it can be concluded that the images of the trajectories of the points of the NDVI profiles provide qualitative information reflecting the dynamics of the ontogeny phases of winter rye plants. Based on the nature of the selected sections of these trajectories, it is possible to create a digital map of the experimental field, with the help of which to conduct a protocol for remote diagnostics of the state of crop productivity and make a forecast of their yield during harvesting.