Structure Of Clusters Research Articles

Single synaptic vesicle tracking in TIRFM-amenable hippocampal synapses.

Single synaptic vesicle (SV) tracking is used to explore the dynamics of SV movement close to active zones (AZ) by total internal reflection fluorescence microscopy (TIRFM). To do so, we used cultured hippocampal ‘xenapses’, purely presynaptic boutons formed by neurons on micro-patterned coverslips, functionalized with synaptogenic cell adhesion proteins. For single SV labeling we developed surface-modified single-color quantum dots with improved photostability and pH-sensitivity for single SV tracking. Obtained single SV movies are analyzed with an improved single-particle tracking software, which combines Automatic Correction for sCMOS-related Noise algorithm (Nat. Commun., Mandracchia et al., 2020) for denoising, U-Track (Nat. Methods, Jaqaman et al., 2008) for frame-to-frame particle linking, and a newly developed single-particle localization algorithm. We yield a localization accuracy of 0.1229 ± 0.1004 pixels (110 nm pixel size) and are able to resolve merging and splitting events of two crossing particle trajectories even though they have low signal-to-noise ratio of ∼1.2. In hippocampal xenapses with active zones (AZ) facing the coverslip, SVs appear to jump between discrete levels of axial distance to AZs, and these discrete levels are remarkably stable over tens of seconds. As SVs in electron micrographs appear to be interconnected by short tethers, these discrete levels might arise from a layered structure of the SV cluster above the AZ.

Molecular Blueprinting by Word Processing

In this work, computer-assisted writing techniques for linear expressions of the structure of polycyclic molecules, branched molecules and clusters, based on formal languages, are tested. The techniques used only require the ability to process written texts, even just using a text editor, and one of the many available molecular drawing/optimization programs that accept input in the form of a SMILES string. A few specific syntactic operators acting on strings are characterized in terms of their effect on the corresponding structure, and although they are simply examples, they are already capable of producing non-trivial structures. The aim of this work is to encourage experiments that may lead to potentially interesting molecular schemata, in view of their symmetry and stereochemistry, as revealed by optimization, and to develop insight into the connection between formal expressions and structures. Given the simplicity and availability of the required tools, it can also be useful for education.

The Promoting Role of Ni on In2O3 for CO2 Hydrogenation to Methanol.

Ni-promoted indium oxide (In2O3) is a promising catalyst for the selective hydrogenation of CO2 to CH3OH, but the nature of the active Ni sites remains unknown. By employing density functional theory and microkinetic modeling, we elucidate the promoting role of Ni in In2O3-catalyzed CO2 hydrogenation. Three representative models have been investigated: (i) a single Ni atom doped in the In2O3(111) surface, (ii) a Ni atom adsorbed on In2O3(111), and (iii) a small cluster of eight Ni atoms adsorbed on In2O3(111). Genetic algorithms (GAs) are used to identify the optimum structure of the Ni8 clusters on the In2O3 surface. Compared to the pristine In2O3(111) surface, the Ni8-cluster model offers a lower overall barrier to oxygen vacancy formation, whereas, on both single-atom models, higher overall barriers are found. Microkinetic simulations reveal that only the supported Ni8 cluster can lead to high methanol selectivity, whereas single Ni atoms either doped in or adsorbed on the In2O3 surface mainly catalyze CO formation. Hydride species obtained by facile H2 dissociation on the Ni8 cluster are involved in the hydrogenation of adsorbed CO2 to formate intermediates and methanol. At higher temperatures, the decreasing hydride coverage shifts the selectivity to CO. On the Ni8-cluster model, the formation of methane is inhibited by high barriers associated with either direct or H-assisted CO activation. A comparison with a smaller Ni6 cluster also obtained with GAs exhibits similar barriers for key rate-limiting steps for the formation of CO, CH4, and CH3OH. Further microkinetic simulations show that this model also has appreciable selectivity to methanol at low temperatures. The formation of CO over single Ni atoms either doped in or adsorbed on the In2O3 surface takes place via a redox pathway involving the formation of oxygen vacancies and direct CO2 dissociation.

An Atomistic View of Platinum Cluster Growth on Pristine and Defective Graphene Supports.

Density functional theory (DFT) is used to systematically investigate the electronic structure of platinum clusters grown on different graphene substrates. Platinum clusters with 1 to 10 atoms and graphene vacancy defect supports with 0 to 5 missing C atoms are investigated. Calculations show that Pt clusters bind more strongly as the vacancy size increases. For a given defect size, increasing the cluster size leads to more endothermic energy of formation, suggesting a templating effect that limits cluster growth. The opposite trend is observed for defect-free graphene where the formation energy becomes more exothermic with increasing cluster size. Calculations show that oxidation of the defect weakens binding of the Pt cluster, hence it is suggested that oxygen-free graphene supports are critical for successful attachment of Pt to carbon-based substrates. However, once the combined material is formed, oxygen adsorption is more favorable on the cluster than on the support, indicating resistance to oxidative support degradation. Finally, while highly-symmetric defects are found to encourage formation of symmetric Pt clusters, calculations also reveal that cluster stability in this size range mostly depends on the number of and ratio between PtC, PtPt, and PtO bonds; the actual cluster geometry seemssecondary.

Multihop Clustering Routing Protocol Based on Improved Coronavirus Herd Immunity Optimizer and Q-Learning in WSNs

Wireless sensor networks (WSNs) are composed of a large number of spatially distributed sensor nodes to monitor and transmit information from the environment. However, the batteries used by these sensor nodes have limited energy and cannot be charged or replaced due to the harsh deployment environment. This energy limitation will seriously affect the lifetime of the network. Therefore, the purpose of this research is to reduce energy consumption and balance the load of sensor nodes by clustering routing protocols, so as to prolong the lifetime of the network. First, the coronavirus herd immune optimizer is improved and used to optimize the network clustering. Second, the cluster heads (CHs) are selected according to the energy and location factors in the clusters, and a reasonable CH replacement mechanism is designed to avoid the extra communication energy consumption caused by the frequent replacement of CHs. Finally, a multihop routing mechanism between the CHs and the base station is constructed by Q-learning. Simulation results show that the proposed work can improve the structure of clusters, enhance the load balance of nodes, reduce network energy consumption, and prolong the network lifetime. The appearance time of the first energy-depleted node is delayed by 25.8%, 85.9%, and 162.2% compared with IGWO, ACA-LEACH, and DEAL in the monitoring area of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$300\times300$ </tex-math></inline-formula> m, respectively. In addition, the proposed protocol shows better adaptability in varying dynamic conditions.

Geological structure and gold prospectivity of the Shamansky ore cluster of the Altai-Sayan folded region (Republic of Khakassia)

In this work, we consider the geological settings, mineralogical composition and age of rocks and ores, as well as regularities in the formation of gold mineralization of the Shamansky ore cluster, which is one of the most prospective ore clusters in the Altai-Sayan mineragenic province. It is shown that the cluster has a complex fold-block structure. The rocks are characterized by intense folded and discontinuous dislocations. We identified the area of the reatest deformations, where the known prospective signs of gold mineralization are concentrated. Two morphological types of gold-sulfidequartz ores have been distinguished: veins and pyritequartz-sericite-ankerite metasomatite. We characterized the composition of gold and its morphological features. Sulfur isotope data of sulfides from gold-bearing quartz veins predominantly have values of δ34S from +3.7 to+6.5 ‰ that indicate their hydrothermal-sedimentary origin. 40Ar/39Ar isotope-geochronological data on sericite from gold-bearing quartz shows the age of 359.5 ± 5.5 Ma testifying to the Late Devonian-Early Carboniferous stage of the formation of gold-sulfide-quartz veins. A comparison of geological, metallogenic, mineralogical-geochemical and isotope-geochronological data allowed us to conclude that the gold mineralization of the Shamansky cluster belongs to the orogenic type. According to the model of formation, gold mineralization occurred in three stages: ore-preparation islandarc (540-520 Ma), main ore orogenic-1 accretion-collisional (510-450 Ma), and additional ore orogenic-2 transpressional-collisional (380-345 Ma).

Pyrolysis of Schiff‐Base Manganese Clusters: Effect of Ligand Modulation on the Performance of Supercapacitor Electrodes

AbstractLigand modulation on metal organic clusters endow them with different physical and chemical properties, while how ligand modulation further affects the electrochemical behavior of pyrolytic derivatives is still unclear. Herein, we constructed two trinuclear manganese clusters 1‐Mn3 [Mn3L12(Cl)2] [L1=N1,N3‐bis(3‐methoxysalicylidene) diethylenetriamine] and 2‐Mn3 [Mn3L22(C7H4O2)2] [L2=N1,N3‐bis(3‐salicylidene) diethylenetriamine] based on nitrogen‐rich Schiff‐base pentadentate ligands. The introduction of TG‐MS (thermogravimetry associated with mass spectroscopy) explores the difference and universality of the pyrolysis mechanism of two trinuclear manganese clusters, and divides the pyrolysis process into three Areas (Area I/II/III) according to temperature. Combined with other characterization techniques, the materials in these three areas were analyzed to explain the effect of ligand modification on the electrochemical properties of cluster pyrolysis derivatives. It is found that the Area III derivatives have the best capacitance performance, when the current density is 1 A g−1, the specific capacitance of 1‐900 is 1717 F g−1, and 2‐900 is 350 F g−1. By comparison of the phase evolution process and electrochemical performance of the two manganese clusters, it is proposed that the crumbling of the molecular structure and stacking mode of trinuclear manganese clusters during pyrolysis will affect the capacitive properties of the derivatives. This work provides a guidance for the differences of the properties of pyrolytic derivatives under ligand modulation.

Quantitative study on isotope effect of rubidium clusters

Because of the difficulty in measuring the cluster isotope displacement and identifying its cause, the resonance dissociation spectra, the moment shift and Zeeman energy shift of isotope cluster &lt;sup&gt;87,85&lt;/sup&gt;Rb&lt;sub&gt;&lt;i&gt;n&lt;/i&gt;&lt;/sub&gt; (&lt;i&gt;n&lt;/i&gt; = 1, 2, 3, ··· , 13) are obtained by the combination of optical magnetic resonance and thermal dissociation techniques in this study. The quantitative calculation is carried out based on the conceptual model of the giant atom, and the results are in excellent agreement with the measured results, which shows that rubidium clusters can be analyzed as giant atoms. Furthermore, 5s electron shell level structures of the rubidium cluster &lt;sup&gt;87,85&lt;/sup&gt;Rb&lt;sub&gt;&lt;i&gt;n&lt;/i&gt;&lt;/sub&gt; (&lt;i&gt;n&lt;/i&gt; = 1, 2, 3, ··· , 92) are calculated by using Zeeman level interval model. It is found that the main order and step distance of the 5s electron shell structure are similar to those of 3s single electron shell structure of sodium cluster in spherical symmetry. It is confirmed that the structure of the 5s electron shell of the rubidium cluster is determined by the largest energy gap in total Zeeman levels and the characteristic peaks of odd and even alternating and anomalous magnetic moments of special numbers such as &lt;i&gt;n&lt;/i&gt; = 2 are caused by the intrinsic properties of electrons and molecular structures. It is also found that &lt;sup&gt;87&lt;/sup&gt;Rb&lt;sub&gt;&lt;i&gt;n&lt;/i&gt;&lt;/sub&gt; level shell structure and &lt;sup&gt;85&lt;/sup&gt;Rb&lt;sub&gt;&lt;i&gt;n&lt;/i&gt;&lt;/sub&gt; level shell structure strictly conform to the ratio of 3/2 magnitude relationship, and that there are abnormal differences in spectral center frequency and broadening, which may be directly related to the &lt;sup&gt;85,87&lt;/sup&gt;Rb nuclei close to the shell closure.

ВИКОРИСТАННЯ ОСВІТНІХ КЛАСТЕРІВ ДЛЯ УПРАВЛІННЯ ФІНАНСОВИМ ЗАБЕЗПЕЧЕННЯМ РОЗВИТКУ ОСВІТИ НА МУНІЦИПАЛЬНОМУ РІВНІ

The process of clustering is one of the basic directions in the development of the modern regional economy. Cluster development of municipal education is a specific tool in the field of education. A market-oriented society forms the rules of activity of its subjects through laws, relations, industries, establishments, institutions, the banking sector, support institutions, etc. Therefore, a cluster existing within the framework of educational regulations is nothing more than a specially organized space that allows educational institutions, including schools, colleges, infrastructure facilities, research centers, universities and other educational institutions, to develop successfully. organizations, as well as territorial communities as a whole. Therefore, the question of using educational clusters to manage the financial support of education development at the municipal level is emerging. The article proves that educational clusters can be considered as a set of organizations, government and public structures that ensure the implementation of educational programs of a certain level and focus, as well as conditions for their development. The structure of the educational cluster is defined, which usually consists of a core, partners, infrastructure and management bodies. At the same time, each territorial educational cluster has its own specific composition and characteristics of elements. Outlined practical measures for the creation of territorial educational clusters can be built on the standard stages of cluster formation and may include: definition and justification of strategic initiatives in the field of education; forecasting the target (educational), social, economic (commercial and budgetary) efficiency of the cluster, taking into account various types of investments; determination of the composition of the cluster participants with a clear definition of their role and functions in achieving the final target results; development of forms of joint activity within the cluster; development of the cluster management structure; development and approval at the level of local authorities of the necessary regulatory and legal framework; development and implementation of institutional support; creation of information space. The advantages of using educational clusters to manage the financial support of education development at the municipal level are revealed: effective allocation of budgetary resources, joint attraction of investments, stimulation of innovations, development of infrastructure, increased access to resources, joint improvement of the quality of education. The key aspects of the use of educational clusters for the management of financial support for the development of education at the municipal level are characterized.

On the structure and electronic properties of Ptn clusters: new most stable structures for n = 16-17.

The lowest energy structures and electronic properties of Ptn clusters up to n = 17 are investigated by using a genetic algorithm in combination with density functional theory calculations. There are several putative global minimum structures for platinum clusters which have been reported by using different approaches, but a comprehensive study for n = 15-17 has not been carried out so far. Herein, we perform a consensus using GGA (PBE), meta-GGA (TPSS) and hybrid (B3PW91, PBE0, PBEh-3c, M06-L) functionals in conjunction with the Def2-TZVP basis set. New most stable structures are found for Pt16 and Pt17, which are slightly lower in energy than the previously reported global minima. Molecular dynamics simulations show that the clusters are rigid at room temperature. We analyze the structural, electronic, energy and vibrational data of the investigated clusters in detail.

Structure, stability, and electronic and optical properties of TMDC-coinage metal composites: vertical atomically thin self-assembly of Au clusters.

Composites of metal clusters supported on transition metal dichalcogenides (TMDCs) often provide promising opportunities for applications in nanoelectronics, catalysis, sensing, etc. In the present investigation, a systematic attempt has been made to unveil the structure and stability of coinage M6 clusters supported on TMDC (MoS2 and WS2) monolayers. The more prominent objective is to explore potential candidates that stabilize the two-dimensional (2D) M6 clusters on their surface. Periodic energy decomposition analysis (pEDA) was carried out to probe the various interaction energy (IE) components that govern the stability of the M6 clusters in the composites. Attention has also been devoted to unravelling the electronic and optical properties of these TMDCs/M6 composites. Moreover, ab initio molecular dynamics (AIMD) simulations were performed to scrutinize the dynamic behaviour of Au cluster on WS2 monolayer. The results reveal that the coinage M6 clusters form energetically more stable composites on MoS2 than WS2 monolayer. It is worth mentioning that WS2 promotes the stability of 2D M6 clusters. Inclusion of dispersion correction marginally altered the geometries of the TMDCs/M6 composites but its impact on the IE values was significant. AIMD simulation explicitly emphasizes that the WS2 surface preferentially facilitates the vertical 2D self-assembling of Au atoms and, interestingly, the planarity is mostly retained during the course of simulations. The adsorption of coinage M6 clusters substantially influences the electronic and optical properties of the TMDCs. HSE06 calculation confirms that the decrease in energy gap is more pronounced in MoS2/M6 composites. The outcomes of this study render fundamental insights into the various TMDCs/M6 composites that would certainly be worthwhile probing for diverse practical applications.

Spatial structure of a protected area cluster in the Greater Yellowstone and its enlightenments to China

Spatial structure of a protected area cluster in the Greater Yellowstone and its enlightenments to China

Connectivity Enhancement of E-VANET Based on QL-mRSU Self-Learning Energy-Saving Algorithm

With the development of smart cities and smart electric vehicles (EVs), the problem of improving the performance of Vehicular Ad-hoc Networks (VANETs) is gradually being emphasized. To improve the network performance of VANETs, some scholars have considered parked vehicles as roadside units, but have not paid attention to the energy consumption characteristics of vehicles, especially electric vehicles. Therefore, in this paper, we propose a QL-mRSU series artificial intelligence energy saving method to optimize the energy consumption of parked electric vehicles during communication. The method is based on electric vehicle self-organizing networks (E-VANETs), which dynamically cluster electric vehicles parked in parking lots by parameters such as traffic flow, number of service demands, and charging index in reinforcement learning, select the most suitable vehicles as mobile roadside units (mRSUs), and adjust the working mode according to environmental changes such as the number of service demands to achieve the effects of self-learning and energy saving. The simulation experimental results show that compared with other energy-based routing algorithms, the method is able to make optimal choices through self-learning with guaranteed communication quality and is more adaptable to traffic flow changes on the road, thus ensuring the stability of energy-saving efficiency. In addition, the method significantly improves the energy structure of electric vehicle parking clusters.

Surface functionalization of discrete metal-chalcogenide supertetrahedral clusters and the photocatalytic application

A facile approach for modifying the surface structure of discrete metal chalcogenide supertetrahedral clusters to improve their contact with MXene nanosheets, thus enhancing their photocatalytic performance.

Implementation of multi-source and multi-agent and fuzzy logic optimized QOS-based dynamic resource allocation

The cloud computing system that is based on the Internet of Things is faced with new challenges on a regular basis. This is due to the sophisticated structure of system clusters as well as the vast quantity of data that is handled by the systems. The ability to obtain resources in an elastic manner is seen as the most compelling rationale for the implementation of an architecture for cloud computing that is based on the Internet of Things (IoT). The capacity to dynamically scale up or down the amount of virtual resources in response to the requirements of Internet of Things (IoT) cloud users is the primary focus of the concept of elasticity. Elasticity refers to the ability to accomplish this. The purpose of this article is to propose a multi

Distributed Clustering for Cooperative Multi-Task Learning Networks

Distributed learning enables collaborative training of machine learning models across multiple agents by exchanging model parameters without sharing local data. Each agent generates data from distinct but related distributions, and multi-task learning can be effectively used to model related tasks. This paper focuses on clustered multi-task learning, where agents are partitioned into clusters with distinct objectives, and agents in the same cluster share the same objective. The structure of such clusters is unknown apriori. Cooperation with the agents in the same cluster is beneficial and improves the overall learning performance. However, indiscriminate cooperation of agents with different objectives leads to undesired outcomes. Accurately capturing the clustering structure benefits the cooperation and offers many practical benefits; for instance, it helps advertising companies better target their ads. This paper proposes an adaptive clustering method that allows distributed agents to learn the most appropriate neighbors to collaborate with and form clusters. We prove the convergence of every agent towards its objective and analyze the network learning performance using the proposed clustering method. Further, we present revision2 a method of computing combination weights that approximately optimizes the network's learning performance to determine how one should aggregate the neighbors' model parameters after the clustering step. The theoretical analysis is well-validated by the evaluation results using target localization and digits classification, showing that the proposed clustering method outperforms existing distributed clustering methods as well as the case where agents do not cooperate.

Структурні моделі циркулярних біоенергетичних кластерів

The article examines the impact of the military conflict and the pandemic on the business environment of Ukraine, especially on the energy and manufacturing sectors. In the context of these changes, the need to develop cluster models and introduce circular bioenergy clusters turned out to be important. For the first time, Ukraine is implementing circular bioenergy clusters that provide cities with energy, solve waste problems and contribute to sustainable development. The study focuses on the bioenergy circulation of the Zaporizhzhya "Engineering-Automation-Machine Building" cluster, which even in the conditions of military conflict is successfully growing and developing, ensuring its energy independence through the production of biomethane. The research is aimed at determining the factors that will contribute to the sustainable transformation of business models of the Ukrainian circular economy in the context of modernization and post-war recovery. The article also emphasizes the development of a cluster ecosystem of startups aimed at using digital technologies and bioenergy resources. The importance of uniting clusters and cooperation with other regions to achieve common goals is noted. The authors consider various models of the organizational structure of circular bioenergy clusters in the context of their formation and development. The protocluster model, the monocentric model, the megacluster model, and the polycentric model are analyzed in detail regarding their features, advantages, and disadvantages. In general, the study reveals important aspects of the development of circular bioenergy clusters in the conditions of the double transition I5.0, taking into account the impact of military conflict.

Моделювання рівня соціально-економічного розвитку регіонів на основі proxy-змінних

The article proposes models for assessing the level of socioeconomic development and economic security of regions, on the basis of a synthesis of the proxy variable technique and cluster analysis, which allow to assess changes in interregional differentiation, spatial economic transformations, identify «pivotal» regions, assess the level of economic security of regions under conditions of limited data. The system of proxy-variables of socioeconomic development of regions is substantiated; classifications of regions by the level of socioeconomic development on the basis of methods of hierarchical, agglomerative and iterative cluster analysis have been developed; a dynamic analysis of the structure of clusters is carried out; changes in the characteristics of the distribution of proxy-variables are analyzed; an assessment of interregional differentiation and asymmetry of development is carried out. The results of the carried out cluster analysis based on proxy variables helped to conclude that recent years have led to significant transformations of the economic space in the regional aspect. In the cluster of «pivotal» regions, there is a strengthening of the positions of Dnipropetrovsk and Lviv regions, convergence with regions with an average level of development – Kyiv, Kharkiv and Odesa regions. The most critical situation is typical for Luhansk, Donetsk, and Kherson regions. Donetsk region has moved from a cluster of regions with an average level of development to a cluster of regions with crisis development. The relocation of enterprises and smoothing out the asymmetry in the variable of «Growth of legal entities» currently affects the indicators of budget security of the regions to a lesser extent. Kharkiv region, despite the deterioration of the socioeconomic situation, maintains its position in the cluster of «pivotal» regions. The obtained results can be used in the system of anticipative management of regional development to adapt regional strategies to new realities.

Nanorod-like Structure of ZnO Nanoparticles and Zn8O8 Clusters Using 4-Dimethylamino Benzaldehyde Liquid to Study the Physicochemical and Antimicrobial Properties of Pathogenic Bacteria

To study their physicochemical and antimicrobial properties, zinc oxide nanoparticles were synthesized using a simple chemical route and 4-dimethylaminobenzaldehyde (4DB) as an organic additive. ZnO nanoparticles were characterized with XRD analysis, which confirmed the presence of a hexagonal wurtzite structure with different crystalline sizes. The SEM morphology of the synthesized nanoparticles confirmed the presence of nanorods in both modifications of ZnO nanoparticles. EDS analysis proved the chemical composition of the synthesized samples via different chemical approaches. In addition, the optical absorption results indicated that the use of 4DB increased the band gap energy of the synthesized nanoparticles. The synthesized Zn8O8 and Zn8O8:4DB clusters were subjected to HOMO-LUMO analysis, and their ionization energy (I), electron affinity (A), global hardness (η), chemical potential (σ), global electrophilicity index (ω), dipole moment (μ), polarizability (αtot), first-order hyperpolarizability (βtot), and other thermodynamic properties were determined. Furthermore, the antimicrobial properties of the ZnO nanoparticles were studied against G+ (S. aureus and B. subtilis) and G- (K. pneumoniae and E. coli) bacteria in a nutrient agar according to guidelines of the Clinical and Laboratory Standards Institute (CLSI).

Creation of agro-tourism cluster as the basis of innovative renewal of Kharkiv oblast in the post-war period

The article is devoted to the study of the possibilities of implementing the cluster concept of the development of the tourism industry in the Kharkiv region. The project of the agro-tourism cluster "Slobozhanska kazka" is proposed. The idea of the cluster is to create a chain of various services, where overnight accommodation is organized in one place, quality food in another, and a master class is held. The strength of the cluster is that it creates a collective agritourism product, increases the capacity of the local tourism market and expands the flow of tourists. The subject of the research is the organizational and economic relations that are formed in the process of adaptation and ensuring sustainable interaction of the participants of the market of rural green tourism in accordance with the modern trends of clustering of the economy. The purpose of the work is the development of theoretical and methodological provisions for the improvement of the domestic market of rural green tourism based on the study of the possibilities of implementing the cluster concept in the regions of Ukraine. The achievement of the set goal was ensured by the following interrelated tasks: to characterize the types of active clusters in Ukraine; consider the essence of the concept and structure of an agro-tourism cluster; to develop a Roadmap for the implementation of the cluster concept of Ukraine's economy in the post-war period to support and popularize rural green tourism in Ukraine. The methodological basis of the study consists of a systematic and program-targeted approach, monographic, graphic and economic-statistical methods of scientific research. The following results were obtained.The development of the agro-tourism cluster of the Kharkiv region will allow further application of a comprehensive approach to the development of enterprises in the field of tourism and the organization of promotion of their products both on the domestic market of the region and on the Ukrainian and international markets. The cluster mechanism will promote the innovative activities of its participants, will ensure the development of infrastructure, the expansion of the spectrum and the growth of the quality of their products (goods, works, services), as well as the satisfaction of the collective interests of the participants of the tourism cluster. Conclusions. The Roadmap for the implementation of the cluster concept of Ukraine's economy in the post-war period for 3 years has been developed. These recommendations will make it possible to create a positive image and increase the attractiveness of the territory, form a regional tourist product, increase the flow of tourists and ensure the replenishment of the budget.