Cluster Structures Research Articles

Holographic matrix method for rapid material structural feature extraction and detection

The extraction of the structural features of materials is fundamental for investigating novel properties in fields such as electronic information and biochemistry. However, existing experimental methods have limitations in analyzing material structures with sufficient depth. Therefore, rapid and accurate extraction and analysis of structural features from atomic coordinates obtained through simulation calculations are crucial for advancing the exploration of new material properties. Herein, we propose an approach for extracting the structural features of materials by combining the holographic matrix method with Bayesian optimization and tensor flow operations. The proposed algorithm efficiently classifies and statistically analyzes cluster structures within materials. Experimental validation conducted on a system comprising 8000 atoms demonstrated a correct recognition rate exceeding 99.213%. Moreover, the algorithm achieved an average recognition time of approximately [Formula: see text][Formula: see text]s. The proposed analytical framework exhibits scalability and robustness, establishing an algorithmic foundation for future advancements in big data analytics for complex materials.

Structure and Thermodynamics of Li+Arn Clusters beyond the Second Solvation Shell

Small Li+Arn clusters are employed in this work as model systems to study microsolvation. Although first and second solvation shells are expected to be the most relevant ones for this type of atomic solvents, it is also interesting to explore larger clusters in order to identify the influence of external atoms on structural and thermodynamic properties. In this work, we perform a global geometry optimization for Li+Arn clusters (with n = 41–100) and parallel tempering Monte Carlo (PTMC) simulations for some selected sizes. The results show that global minimum structures of large clusters always have 6 argon atoms in the first solvation shell while maintaining the number of 14 or 16 argon atoms in the second one. By contrast, third and fourth solvation shells vary significantly the number of argon atoms with the cluster size, and other shells can hardly be assigned due to the reduced influence of Li+ on the external argon atoms for large clusters. In turn, PTMC calculations show that the melting of the most external solvation shells of large microsolvation clusters occurs at T∼50K, which is independent of cluster size. Structural transitions can be observed between quasi-degenerated structures at low temperatures. Moreover, the present results highlight the fluxional character of the external solvation shells of these large Li+Arn clusters, which may be seen as typical “snowball” structures.

Quantum cluster equilibrium theory applied to liquid ammonia.

Through this paper, the authors propose using the quantum cluster equilibrium (QCE) theory to reinvestigate ammonia clusters in the liquid phase. The ammonia clusters from size monomer to hexadecamer were considered to simulate the liquid ammonia in this approach. The clusterset used to model the liquid ammonia is an ensemble of different structures of ammonia clusters. After studious research of the representative configurations of ammonia clusters through the cluster research program ABCluster, the configurations have been optimized at the MN15/6-31++G(d,p) level of theory. These optimizations lead to geometries and frequencies as inputs for the Peacemaker code. The QCE study of this molecular system permits us to get the liquid phase populations in a temperature range of 190-260 K, covering the temperatures from the melting point to the boiling point. The results show that the population of liquid ammonia comprises mainly the ammonia hexadecamer followed by pentadecamer, tetradecamer, and tridecamer. We noted that the small-sized ammonia clusters do not contribute to the population of liquid ammonia. In addition, the thermodynamic properties, such as heat of vaporization, heat capacity, entropy, enthalpy, and free energies, obtained by the QCE theory have been compared to the experiment given some relatively good agreements in the gas phase and show considerable discrepancies in liquid phase except the density. Finally, based on the predicted population, we calculated the infrared spectrum of liquid ammonia at 215 K temperature. It comes out that the calculated infrared spectrum qualitatively agrees with the experiment.

CAR-mediated targeting of NK cells overcomes tumor immune escape caused by ICAM-1 downregulation

BackgroundThe antitumor activity of natural killer (NK) cells can be enhanced by specific targeting with therapeutic antibodies that trigger antibody-dependent cell-mediated cytotoxicity (ADCC) or by genetic engineering to express chimeric...

The place of cluster structures in the formation of strategies for the management of the competitiveness of agrarian enterprises

The article examines the possibility of introducing cluster structures into the strategy of managing the competitiveness of enterprises in the agrarian sector. The existing studies on this topic were analyzed, and the necessity of clustering the agricultural sector was substantiated. Research confirms that access to innovation is critical among all the benefits of the cluster approach. It is emphasized that modernizing the economy based on cluster strategies has been introduced previously. However, against the crisis caused by military actions, when traditional methods become ineffective, the cluster model of business organization becomes an indispensable tool for increasing the competitiveness of agrarian business enterprises. An algorithm for the integration of cluster structures into the strategy of managing the competitiveness of agricultural sector enterprises is proposed, the main stages of which are cluster formation and analysis of internal environments, analysis of the external environment and strategy formulation, strategy implementation and implementation of cluster initiatives, evaluation and adjustment of strategy, organizational culture and communication, innovation, and development. Formation of the management strategy of a competitive agricultural enterprise requires a comprehensive approach, covering internal and external factors. The involvement of cluster structures is an essential component of this strategy, as they combine the resources and experience of various enterprises for the joint achievement of strategic goals. The main stages of this process are analyzing the internal and external environment, determining competitive advantages, and developing an effective development strategy. The creation of a positive corporate culture, the development of effective communication and partnership relations, and the active support of innovation are significant. Successful strategy implementation requires constant monitoring and evaluation of results, as well as readiness to adjust the strategy to environmental changes. This approach will allow enterprises to effectively face market challenges and ensure stable development in the competitive agricultural sector. Keywords: cluster structures, strategic competitiveness management, agricultural sector, cluster, clusterization, agricultural enterprises.

Mechanism of fruit and vegetable canning production development based on formation of cluster structures

The article is devoted to the formation of the structure of the organizational-economic mechanism for the development of fruit and vegetable canning production in Ukraine. It is determined that the main components of the organizational-economic regulation of activity and development of fruit and vegetable canning production are: regulation of the integrity of the development of enterprises; regulation of innovation and investment activities based on equity; regulation of financial activities; creation of conditions for the implementation of operational activities; conducting practical commercial activities; providing motivating and motivational social conditions; providing information and analytical assessment of the search and control of the use of enterprise resources. The conceptual foundations for creating a new organizational structure for developing fruit and vegetable canning production in Ukraine have been formed. A definition of a new type of cluster structure in the fruit and vegetable canning production system is given. This structure is an organic unity of production, investment, innovation, financial, sales, and other activities of enterprises, united by the chain-network (technological-functional) principle into an interconnected system of functional "fields": production of raw materials, procurement, and storage processing, and marketing. The creation of integrated fruit and vegetable canning structures of the cluster type will solve the problems of industry development through the operation of the organizational and economic mechanism for the development of the industry in the cluster system. The capabilities of the cluster allow to solve the following tasks: meeting the existing and future needs of consumers in quality food products; providing canning enterprises with high-quality raw materials of domestic origin; overcoming price disparity and optimizing the distribution of profits between the links of the technological chain; combining the financial capabilities of enterprises to solve development problems; ensuring guaranteed sales of products at an adequate price for agricultural producers; updating the technical and technological base of production; increasing the economic efficiency of the cluster's production, reducing costs, more precise identification and use of reserves of economic development; dissemination of corporate culture, new methods of work organization, raising collective consciousness, motivation of creative activity; increase in labor productivity; implementation of modern quality management systems; more complete and rational use of resources; solving the problem of staffing. Keywords: agrarian sector, fruit and vegetable canning production, organizational and economic mechanism, integrated structure, clustering, cluster formations.

Agricultural clusters in the regional development strategic planning system

The world experience of the development of integration processes shows that integrated enterprises are more efficient and adapted to the conditions of the market economy due to the creation of a single progressive process of manufacturing and promoting products from their producers to end consumers. In today's conditions, the country has not yet developed a system innovation development mechanism. A comprehensive solution to the problem of innovative development of the agricultural sector is the formation of a cluster policy at both the state and regional levels. Adjustment of state and regional strategic plans and target programs considering the cluster initiative will allow to achieve the target strategic guidelines for the development of the agricultural cluster, to ensure the implementation of the goals and objectives of the development of the territory of the region. Strategic planning for the development of the region's economy, including the agricultural and processing sectors, should be based on the peculiarities of the territory, considering the disparities in the development of individual districts. The established sectoral and territorial structure of the Mykolaiv region and the natural and climatic conditions of the region determine the directions of clustering of the agricultural sector and the limits of influence of cluster structures as growth points. The implementation of the project of the formation and development of an agrarian cluster in the system of strategic management of the Mykolaiv region requires a review of the provisions of the main strategic plans of regional development, the "Strategy for the development of the Mykolaiv region for the period up to and including 2027", as well as medium-term plans and programs, strategies of industry direction and targets programs of regional and sectoral development. Keywords: clustering, agricultural sector, economic development, regional policy, strategic planning.

Bodily maps of musical sensations across cultures

Emotions, bodily sensations and movement are integral parts of musical experiences. Yet, it remains unknown i) whether emotional connotations and structural features of music elicit discrete bodily sensations and ii) whether these sensations are culturally consistent. We addressed these questions in a cross-cultural study with Western (European and North American, n = 903) and East Asian (Chinese, n = 1035). We precented participants with silhouettes of human bodies and asked them to indicate the bodily regions whose activity they felt changing while listening to Western and Asian musical pieces with varying emotional and acoustic qualities. The resulting bodily sensation maps (BSMs) varied as a function of the emotional qualities of the songs, particularly in the limb, chest, and head regions. Music-induced emotions and corresponding BSMs were replicable across Western and East Asian subjects. The BSMs clustered similarly across cultures, and cluster structures were similar for BSMs and self-reports of emotional experience. The acoustic and structural features of music were consistently associated with the emotion ratings and music-induced bodily sensations across cultures. These results highlight the importance of subjective bodily experience in music-induced emotions and demonstrate consistent associations between musical features, music-induced emotions, and bodily sensations across distant cultures.

Identifying central symptom clusters and correlates in patients with lung cancer post-chemotherapy: A network analysis

ObjectiveThis study aims to investigate the network structures of symptoms and symptom clusters in patients with lung cancer post-chemotherapy, with a focus on identifying the central symptom cluster. Understanding the central cluster is crucial for targeted and effective symptom management. MethodsSymptom occurrence and severity were assessed using the Memorial Symptom Assessment Scale (MSAS). Principal component analysis (PCA) was employed to explore symptom clusters, while network analysis unveiled the network structure and pinpointed the central symptom cluster. ResultsThe study included 512 patients with lung cancer. Four distinct symptom clusters emerged: sickness behavior, psychological, lung cancer-specific, and epithelial. The sickness behavior symptom cluster was identified as the central symptom cluster. ConclusionsThis research designates the sickness behavior symptom cluster as central in post-chemotherapy patients with lung cancer, offering valuable insights for clinical nurses in devising more effective symptom management strategies. Trial registrationChiCTR2300070944 (Chinese Clinical Trial Register).

Textures and trace element geochemistry of pyrite in Gaoloushan ore section of the Yangshan gold belt, West Qinling: Implications for ore genesis

The Devonian Sanhekou Group phyllite in the Yangshan gold belt includes multiple stages of pyrite development, and Au is mainly distributed within the pyrite. Bodies within the Gaoloushan ore section of the gold belt are located in the broken and altered carbonaceous phyllite and granitic rock dykes, where quartz vein-type gold ores are more common as compared to other ore sections (Anba, Getiaowan). Studying the trace element distribution characteristics of gold-bearing and non-gold-bearing pyrite can constrain the evolution of ore-forming fluids and the types of ore deposit genesis. Based on detailed fieldwork and microscopic identification, 48 pyrite samples from the 69th exploration line of the Gaoloushan ore section were analyzed in situ by LA-ICP-MS. The following conclusions were drawn: (1) The gold-bearing pyrite formed during the ore-forming stage while the non-gold-bearing pyrite formed during the sedimentary and metamorphic period. The morphology of the pyrites differs, with gold-bearing pyrite mainly characterized by medium-fine grains, impregnation, fine veins, and reticulate structure, with crystal morphology mainly pentagonal dodecahedra or pentagonal octahedra, whereas non-gold-bearing pyrite is mainly characterized by a medium or medium-coarse grains, with stellate, strawberry, or cluster structures, and crystal morphology mainly in the form of cubes or pentagonal octahedra; (2) The As and Te content of the sedimentary pyrite is low, locally below the detection limit, and the Co and Ni contents and ratios vary greatly, with a distribution of 117–945 ppm and ratio distribution of 0.11–1.92. Pyrite from the ore-forming stage is primarily characterized by high As, Pb, Co, Ni, Cu, Sb, Zn, and Se concentrations, with Bi, Au, and trace amounts of Tl, Te, and Sn observed in later formations; (3) Au and As are positively correlated. The average Au content of 60.53 ppm in pyrite from granite dykes is higher than the average Au 15.97 ppm in carbonaceous phyllite. Pyrite particles with Au contents below the detection limit are sourced in carbonaceous phyllite. In addition, the higher As enrichment is observed in pyrite from granite dykes, averaging 35 770.60 ppm with a maximum value of 72 930.19 ppm. In comparison, the average As content in carbonaceous phyllite is 8974.66 ppm, with a maximum of 69 800.50 ppm, and the Au-As diagram indicates that gold in the Gaoloushan ore section is mainly in the form of solid solution gold within the pyrite lattice; (4) Statistical analysis of the Co/Ni ratio variation in the different lithologies and pyrite stages reveals an initial increase followed by a decrease. The median Co/Ni ratio variations during the mineralization stages of Py1s (0.51–0.7), Py1m (1.35–2.25), Py2 (1.43–1.87), Py1-2 m (1.53), Py2a (1.59), Py2b (1.4), Py2s (1.2), Py2m (1.63), and Py3 (0.19–1.40) suggest that magmatic-hydrothermal fluids dominated during the early stage of mineralization in the gold belt and metamorphic fluids during the main mineralization stage, with deep-seated metamorphic fluids playing a significant role in the late mineralization stage. The varying proportions of ore-forming fluids are likely to have been crucial in controlling gold mineralization in the Yangshan gold belt.

Micro Area Interface Wetting Structure with Tailored Li+-Solvation and Fast Transport Properties in Composite Polymer Electrolytes for Enhanced Performance in Solid-State Lithium Batteries.

To satisfy the demand for high safety and energy density in energy storage devices, all-solid-state lithium metal batteries with solid polymer electrolytes (SPE) replacing traditional liquid electrolytes and separators have been proposed and are increasingly regarded as one of the most promising candidates as next-generation energy storage systems. In this study, poly(vinylidene fluoride)-hexafluoropropylene/lignosulfonic acid (PVDF-HFP/LSA) composite polymer electrolyte (CPE) membranes with a micro area interface wetting structure were successfully prepared by incorporating LSA into the PVDF-HFP polymer matrix. The enhanced interaction between the polar functional group in LSA and the C═O in N-methylpyrrolidone (NMP) hinders the evaporation of solvent NMP, thus creating a micro area wetting structure, which offers a flexible region for the chain segment movement and enlarging the area of the amorphous zone in PVDF-HFP. From the results of IR and Raman spectroscopy, it was found that the presence of LSA induced unique ion transport channels created by the massive aggregated ion pair (AGG) and contact ion pair (CIP) of ion cluster structures composed of Li+ and multiple TFSI- and, at the same time, effectively reduced the crystallinity of the polymer electrolyte, hence further contributing to the Li+ diffusion. As a result, at a rate of 2 C, the Li|CPE-15|LiFePO4 solid-state battery delivers an initial discharge-specific capacity of 134.9 mAh g-1 and maintains stability with a retention of 84% during 400 charge-discharge cycles while the Li|CPE-0|LiFePO4 battery fails after only a few cycles at the same rate.

Automated Generation of ICD-11 Cluster Codes for Precision Medical Record Classification

Accurate clinical coding using the International Classification of Diseases (ICD) standard is essential for healthcare analytics. ICD-11 introduces new coding guidelines and cluster structures, posing challenges for existing coding tools. This research presents an automated approach to generate valid ICD-11 cluster codes from medical text. Natural language records are represented as vectors and compared to an ICD-11 corpus using cosine similarity. A bidirectional matching technique then refines similarity estimation. Experiments demonstrate the method yields up to 0.91 F1 score in coding accuracy, significantly outperforming a baseline tool. This work enables efficient high-quality ICD-11 coding to support healthcare informatics.

Deep clustering framework review using multicriteria evaluation

The application of clustering has always been an important method for problem-solving. In the era of big data, most classical clustering methods suffer from the curse of dimensionality and scalability issues. Recently, deep clustering models have garnered more attention due to their capabilities in dealing with complex, high-dimensional, and large-scale datasets. They offer intriguing perspectives owing to their outstanding representative capacity and fast inference speed. The remaining major problem in clustering scenarios with high-dimensional data revolves around determining an appropriately compressed representation that semantically preserves cluster structures. Without labels, defining an objective function to encourage a suitable representation becomes a critical question. After several years of stagnation, impressive results have been achieved in the last two years. This paper proposes a comprehensive and up-to-date review of deep clustering methods. We first introduce the basic concepts shared by several deep clustering algorithms, available network architectures, and optimization strategies. Then, a detailed review is presented for each family by analyzing their most representative algorithms. These algorithms are then assessed based on their classification accuracy and from a multi-criteria perspective to aid investigators in selecting the most appropriate solution. Finally, an overview of the diversity of tasks and application domains is provided, and current issues and challenges are discussed.

Unsupervised Discriminative Feature Selection via Contrastive Graph Learning.

Due to many unmarked data, there has been tremendous interest in developing unsupervised feature selection methods, among which graph-guided feature selection is one of the most representative techniques. However, the existing feature selection methods have the following limitations: (1) All of them only remove redundant features shared by all classes and neglect the class-specific properties; thus, the selected features cannot well characterize the discriminative structure of the data. (2) The existing methods only consider the relationship between the data and the corresponding neighbor points by Euclidean distance while neglecting the differences with other samples. Thus, existing methods cannot encode discriminative information well. (3) They adaptively learn the graph in the original or embedding space. Thus, the learned graph cannot characterize the data's cluster structure. To solve these limitations, we present a novel unsupervised discriminative feature selection via contrastive graph learning, which integrates feature selection and graph learning into a uniform framework. Specifically, our model adaptively learns the affinity matrix, which helps characterize the data's intrinsic and cluster structures in the original space and the contrastive learning. We minimize l1,2 -norm regularization on the projection matrix to preserve class-specific features and remove redundant features shared by all classes. Thus, the selected features encode discriminative information well and characterize the discriminative structure of the data. Generous experiments indicate that our proposed model has state-of-the-art performance.

Hierarchical structures and magnetism of Co clusters: a perspective from integration of deep learning and a hybrid differential evolution algorithm.

Theoretically determining the lowest-energy structure of a cluster has been a persistent challenge due to the inherent difficulty in accurate description of its potential energy surface (PES) and the exponentially increasing number of local minima on the PES with the cluster size. In this work, density-functional theory (DFT) calculations of Co clusters were performed to construct a dataset for training deep neural networks to deduce a deep potential (DP) model with near-DFT accuracy while significantly reducing computational consumption comparable to classic empirical potentials. Leveraging the DP model, a high-efficiency hybrid differential evolution (HDE) algorithm was employed to search for the lowest-energy structures of CoN (N = 11-50) clusters. Our results revealed 38 of these clusters superior to those recorded in the Cambridge Cluster Database and identified diverse architectures of the clusters, evolving from layered structures for N = 11-27 to Marks decahedron-like structures for N = 28-42 and to icosahedron-like structures for N = 43-50. Subsequent analyses of the atomic arrangement, structural similarity, and growth pattern further verified their hierarchical structures. Meanwhile, several highly stable clusters, i.e., Co13, Co19, Co22, Co39, and Co43, were discovered by the energetic analyses. Furthermore, the magnetic stability of the clusters was verified, and a competition between the coordination number and bond length in affecting the magnetic moment was observed. Our study provides high-accuracy and high-efficiency prediction of the optimal structures of clusters and sheds light on the growth trend of Co clusters containing tens of atoms, contributing to advancing the global optimization algorithms for effective determination of cluster structures.

Розвиток обліку в кластерних структурах на основі положень теорії трансакційних витрат і контрактної теорії

The aim of the article is to substantiate the prerequisites for the development of accounting in cluster structures on the basis of the provisions of key institutional theories – the theory of transaction costs and the contract theory. The theoretical and methodological basis of the article is the basic provisions of institutional economic theory and scientific developments of scientists on the problems of interorganizational accounting. The study was carried out with the use of general scientific and special techniques and methods: scientific abstraction – to study problematic issues and more detailed elaboration of mechanisms for improving accounting; generalization – to systematize the existing scientific approaches; concretization – to characterize the theoretical tools, content and formation of proposals for the development of accounting; graphic – for non-textual display of research results. The recommendations presented in the article regarding the improvement of accounting will allow to more thoroughly and comprehensively identify the economic essence of transaction costs and contractual relations, to reveal the features and form a methodology for their management, including the features of accounting and analysis for operational regulation, control and identification of reserves for reducing transaction costs in the cluster. The allocated directions of development of accounting in the cluster on the basis of the theory of transaction costs and the contract theory, which partially intersect with each other, allow to expand the theoretical provisions of accounting through the explanation of the relationship between participants in terms of the implementation of accounting procedures. The obtained scientific results of theoretical nature can become the starting point for further research in the direction of a better understanding of the current state of scientific developments on the topic. The originality of the study is that it thoroughly reveals the theoretical issues of accounting in the interorganizational management of cluster structures.

Clusterization aspects in the states of non-rotating and fast rotating nuclei

The understanding of clustering aspects at the ground state of nuclei and in fast rotating ones within the framework of covariant density functional theory has been reviewed and reanalyzed. The appearance of many exotic nuclear shapes in nuclear chart can be inferred from combined analysis of nodal structure of the densities of the single-particle states and the evolution of such states in the Nilsson diagram with deformation and particle number. Such analysis which is supported by fully self-consistent calculations allows to predict the existence of nuclear configurations with specific shape or cluster properties at ground state and at high spin. For example, it indicates that in a given shell with principal quantum number N only the lowest in energy two-fold degenerate deformed state can contribute to the formation of linear chain α cluster structures.

On the brink of self-hydration: the water heptadecamer.

For pure, neutral, isolated molecular clusters, (H2O)17 marks the transition from structures with all water molecules on the cluster surface to water self-hydration, i.e., cluster structures around one central water molecule. Getting this right with water model potentials turns out to be challenging. Even the best water potentials currently available, which reproduce collective properties very well, still deliver contradicting results for (H2O)17, when different low-energy isomers from global structure optimizations are examined. Interestingly, ab initio quantum chemistry also struggles with the only seemingly simple question if (H2O)17 is all-surface or water-centered. Hence, although the long history of water potential development may be entering its final phase, it is not quite finished yet.

A summary and outlook for SOTANCP5

The present contribution provides an overview of the SOTANCP5 conference and the progress that was reported in state-of-the-art experiment and theoretical cluster studies. An exciting array of topics ranging from correlations, halo nuclei, clustering in reactions and nuclear astrophysics, alpha-gas states, ab intio theory, alpha-particle like cluster structures, the role of the continuum and the latest developments in experimental facilities. These contributions are brought together in the following summary. Some additional thoughts and perspectives are also provided.

Size-dependent linear and nonlinear optical responses of silicon clusters.

Owing to strong quantum confinement effects and no periodic constraints, the geometric and electronic structures of silicon clusters differ from those of crystalline silicon. Although previous studies have elucidated the optical properties of silicon clusters, some issues remain unresolved. To address these, this study examined the size-dependent linear and nonlinear optical responses of silicon clusters through first-principles calculations. Silicon clusters exhibited lone-pair-electron-dominated optical response behaviors. With the investigated size range, the orientationally average polarizability (αave) and second-order hyperpolarizability (γave) increased with cluster size. However, αave and γave per atom exhibited no evident size-dependent trends owing to co-modulation of the lone-pair-number-to-atomic-number ratio and geometry. αave and γave were notably sensitive to the nuclear binding strength of lone-pair electrons. Thus, the nonlinear optical effects of silicon clusters are superior to those of phosphorus and sulfur clusters. This investigation offers valuable insights into the optical responses of atomic-precision clusters.