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A novel statistical mechanical methodology is applied to clusters of N ≤ 7 atoms. Exact statistical analogs for any energy derivative of entropy ∂mS/∂Em are used in rigorous microcanonical Monte Carlo simulations to vastly enlarge the pool of measurable thermodynamic properties relative to previous work. All analogs are given for two alternative partition functions of the microcanonical ensemble. Coarse grained energy distributions are used to establish the existence of melting transitions. LJ7, LJ5, and LJ4 are found to exhibit trimodal distributions, a feature not being reported before. Varieties of combinations of entropy derivatives are tested for a direct detection of the melting region. It is shown that for such a purpose, derivatives of at least fourth order are necessary. [ABSTRACT FROM AUTHOR]

We describe a method to compute photon–matter interaction and atomic dynamics with x-ray lasers using a hybrid code based on classical molecular dynamics and collisional-radiative calculations. The forces between the atoms are dynamically determined based on changes to their electronic occupations and the formation of a free electron cloud created from the irradiation of photons in the x-ray spectrum. The rapid transition from neutral solid matter to dense plasma phase allows the use of screened potentials, reducing the number of non-bonded interactions. In combination with parallelization through domain decomposition, the hybrid code handles large-scale molecular dynamics and ionization. This method is applicable for large enough samples (solids, liquids, proteins, viruses, atomic clusters, and crystals) that, when exposed to an x-ray laser pulse, turn into a plasma in the first few femtoseconds of the interaction. We present four examples demonstrating the applicability of the method. We investigate the non-thermal heating and scattering of bulk water and damage-induced dynamics of a protein crystal using an x-ray pump–probe scheme. In both cases, we compare to the experimental data. For single particle imaging, we simulate the ultrafast dynamics of a methane cluster exposed to a femtosecond x-ray laser. In the context of coherent diffractive imaging, we study the fragmentation as given by an x-ray pump–probe setup to understand the evolution of radiation damage in the time range of hundreds of femtoseconds. [ABSTRACT FROM AUTHOR]

We introduce ACEpotentials.jl, a Julia-language software package that constructs interatomic potentials from quantum mechanical reference data using the Atomic Cluster Expansion [R. Drautz, Phys. Rev. B 99, 014104 (2019)]. As the latter provides a complete description of atomic environments, including invariance to overall translation and rotation as well as permutation of like atoms, the resulting potentials are systematically improvable and data efficient. Furthermore, the descriptor's expressiveness enables use of a linear model, facilitating rapid evaluation and straightforward application of Bayesian techniques for active learning. We summarize the capabilities of ACEpotentials.jl and demonstrate its strengths (simplicity, interpretability, robustness, performance) on a selection of prototypical atomistic modelling workflows. [ABSTRACT FROM AUTHOR]

A novel dual-function Ru/CuMnBP micro particle electrocatalyst is successfully fabricated via hydrothermal reaction and Ru soaking approaches for overall water splitting application, which exhibits a low cell voltage of 3.13 V at an industrial level current density of 2000 mA/cm2 in 1M KOH. The designed hybrid Pt/C|| Ru/CuMnBP shows higher catalytic behavior, requiring a lower bias of 2.64 V to maintain the current density of 2000 mA/cm2. [Display omitted] Electrochemical water splitting has been considered as a key pathway to generate environmentally friendly green hydrogen energy and it is essential to design highly efficient electrocatalysts at affordable cost to facilitate the redox reactions of hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). In this work, a novel micro-clustered Ru/CuMnBP electrocatalyst is introduced, prepared via hydrothermal deposition and soaking-assisted Ru doping approaches on Ni foam substrate. Ru/CuMnBP micro-clusters exhibit relatively low HER/OER turnover overpotentials of 11 mV and 85 mV at 10 mA/cm2 in 1 M KOH. It also demonstrates a low 2-E turnover cell voltage of 1.53 V at 10 mA/cm2 for the overall water-splitting, which is comparable with the benchmark electrodes of Pt/C||RuO 2. At a super high-current density of 2000 mA/cm2, the dual functional Ru/CuMnBP demonstrates an exceptionally low 2-E cell voltage of 3.13 V and also exhibits superior stability for over 10 h in 1 M KOH. Excellent electrochemical performances originate from the large electrochemical active surface area with the micro cluster morphology, high intrinsic activity of CuMnBP micro-clusters optimized through component ratio adjustment and the beneficial Ru doping effect, which enhances active site density, conductivity and stability. The usage of Ru in small quantities via the simple soaking doping approach significantly improves electrochemical reaction rates for both HER and OER, making Ru/CuMnBP micro-clusters promising candidates for advanced electrocatalytic applications. [ABSTRACT FROM AUTHOR]

Background: The LYP tyrosine phosphatase presents a SNP (1858C > T) that increases the risk of developing autoimmune diseases such as type I diabetes and arthritis. It remains unclear how this SNP affects LYP function and promotes the development of these diseases. The scarce information about LYP substrates is in part responsible for the poor understanding of LYP function. Results: In this study, we identify in T lymphocytes several adaptor proteins as potential substrates targeted by LYP, including FYB, SLP-76, HS-1, Vav, SKAP1 and SKAP2. We also show that LYP co-localizes with SLP76 in microclusters, upon TCR engagement. Conclusions: These data indicate that LYP may modulate T cell activation by dephosphorylating several adaptor proteins, such as FYB, SLP-76, HS-1, Vav, SKAP1 and SKAP2 upon TCR engagement. [ABSTRACT FROM AUTHOR]

Single‐atom catalysis involves loading the active metal onto the carrier's surface as a single‐atom. This atom is primarily bonded to the carrier surface through hetero‐atom bonding. It is important to note that the coordination environment of the metal atoms may not be the same when each dispersed active metal atom has an identical coordination environment on the carrier's surface. The utilization of single‐atom catalysts (SACs) doesn't strictly imply that a solitary metal atom with zero valency functions as the active core. Singular atoms can also engage in distant interactions with other atoms or clusters of atoms on the substrate, like electron transfer, and frequently demonstrate specific charges. The main reason for the high activity of the catalyst is the remote (i.e., long‐range) interaction of the active atom with the surrounding coordination atoms. For this reason, the study of the mechanism of long‐range interactions between multiple single‐atom sites and between single‐atom sites and atomic cluster sites has become an important and urgent task in the design and regulation of single‐atom catalyst performance. [ABSTRACT FROM AUTHOR]

Copper has been reclusive with regard to its plasmonic investigations among the founding plasmonic metals. With the advent of technology and the associated improvements in understanding of plasmonics, copper has been able to make a stand for itself among its peers and even outshine them in a few aspects such as dielectric loss, cost, and a more intricate and facile tuning of the near and far field intensities of the plasmon-enhanced distributions. This review is aimed at highlighting the different classes of plasmonic copper (PC), ranging from its pristine version to the array of composited and alloyed compositions. The focus is on an all-encompassing review of PC with regard to its shortcomings and merits, its exploration for plasmonic applications, and emerging phenomena discovered due to the plasmonic virtue. We aim to bring about a comprehensive treatise of the investigations on PC, where the major discussions are on the topics of a generic treatise on surface plasmons (both localized and propagating), pristine copper and its potential for different applications, the almost inescapable phenomenon of oxidation, and the associations that copper has been made to form in order to be exploited for multiple uses such as chalcogenides, silicides, alloys, and other metamaterial architectures. Specific outcomes of the changes to the near and far-field distributions of PC in various conditions such as oxidized/alloyed/composited and stabilized have been discussed, highlighting the changes to PC in lieu of these modifications. The concluding sections highlight some fascinating compositions including multi-elemental copper and its atomic clusters and cursorily studied compositions which are among the few materials that could offer untapped capabilities which will be made evident from brief glimpses of their plasmonic character. The outlook for plasmonic copper has never been more promising, ranging from the need for comprehensive investigations of emerging material compositions and configurations (of both pristine and composited copper) to the realm of commercialization. Copper has, thus, been projected to be a viable alternative to existing options including the poster children of plasmonics, namely, silver and gold. [ABSTRACT FROM AUTHOR]

The evolution of data in text streams may cause feature and concept drifts. The former, while being less discussed in the literature, poses challenges for learning algorithms by changing the feature space of text representation. A common approach for handling concept drift is to maintain summarized groups of documents, known as micro-clusters. Despite the benefits, this scheme restricts document representation and poses challenges in the face of feature drift. In this paper, we propose an incremental text clustering algorithm that deals with both kinds of drifts. The algorithm uses incremental word embedding, which is rarely studied in the context of evolving data streams. We also propose a novel approach to leverage hierarchical summarized concepts instead of micro-clusters. The concepts reflect the semantic structure of the text stream and are continuously updated in the face of concept drift and evolution. The proposed method enables a customized low-dimensional and interpretable document representation, which improves the clustering quality. By employing concept modeling, in contrast with many available approaches, the proposed algorithm detaches the process of handling data evolution from document clustering. This modularization enables arbitrary variation in the granularity of document representation and allows for customized clustering when accessing the historical documents is impractical. The experimental results on several real datasets, and comparison with other incremental and non-incremental methods, show that the proposed algorithm can deal with dynamics in the feature space, and concept drift and evolution, while preserving its accuracy. [ABSTRACT FROM AUTHOR]

Stream clustering has emerged as a vital area for processing streaming data in real-time, facilitating the extraction of meaningful information. While efficient approaches for defining and updating clusters based on similarity criteria have been proposed, outliers and noisy data within stream clustering areas pose a significant threat to the overall performance of clustering algorithms. Moreover, the limitation of existing methods in generating non-spherical clusters underscores the need for improved clustering quality. As a new methodology, we propose a new stream clustering approach, MCMSTStream, to overcome the abovementioned challenges. The algorithm applies MST to micro-clusters defined by using the KD-Tree data structure to define macro-clusters. MCMSTStream is robust against outliers and noisy data and has the ability to define clusters with arbitrary shapes. Furthermore, the proposed algorithm exhibits notable speed and can handling high-dimensional data. ARI and Purity indices are used to prove the clustering success of the MCMSTStream. The evaluation results reveal the superior performance of MCMSTStream compared to state-of-the-art stream clustering algorithms such as DenStream, DBSTREAM, and KD-AR Stream. The proposed method obtained a Purity value of 0.9780 and an ARI value of 0.7509, the highest scores for the KDD dataset. In the other 11 datasets, it obtained much higher results than its competitors. As a result, the proposed method is an effective stream clustering algorithm on datasets with outliers, high-dimensional, and arbitrary-shaped clusters. In addition, its runtime performance is also quite reasonable. [ABSTRACT FROM AUTHOR]

The binary Cd5.7Yb phase representing the Tsai‐type category of the icosahedral quasicrystals is solved by the assignment of a unique atomic decoration to rhombohedral units in the Ammann–Kramer–Neri tiling. The unique decoration is found for units with an edge length of 24.1 Å and 3m internal point symmetry. The structural refinement was carried out for two underlying tilings generated by the projection method for 6D space. The difference lies in the location of the origin point which for one tiling is in the vertex and for the second one in the center of the 6D unit cell. The two tilings exhibit mutual duality. The choice of the tiling has a minor effect on the final structural model as both converge to an R factor of ∼11.5%. The main difference is related to the treatment of the Cd4 tetrahedral motif which is either orientationally ordered and aligned with the threefold axis or disordered and modeled as a partially occupied icosahedron. Both models can be presented as a covering by rhombic triacontahedral clusters with identical positions of clusters within rhombohedral units. The shell structure is Tsai‐type in the case of the first tiling and Bergman‐type for the other. [ABSTRACT FROM AUTHOR]

Big data applications generate a huge range of evolving, real-time, and high-dimensional streaming data. In many applications, data stream clustering regarding efficiency and effectiveness becomes challenging. A major issue in data mining is clustering of data streams. The several clustering techniques were implemented for stream data, but they are mostly quite restricted approaches to cluster dynamics. Generally, the data stream is an arrival of data sequence and also several factors are added in the clustering, which is rather than the classical clustering. For every data point, the stream is mostly unbounded and also the data has been estimated atleast once. It leads to higher processing time and an additional requirement on memory. In addition, the clusters in each data and their statistical property vary over time, and streams can be noisy. To address these challenges, this research work aims to implement a novel data stream clustering which is developed with a hybrid meta-heuristic model. Initially, a data stream is collected, and the micro-clusters are formed by the K-Means Clustering (KMC) technique. Then, the formation of micro-clusters, merge and sorting of the data clusters, where the cluster optimization is performed by the Hybrid Group Search Pelican Optimization (HGSPO). The main objective of the clustering is performed to maximize the accuracy through the radius, distance and similarity measures and then, the thresholds of these metrics are optimized. In the training phase, a stream of clustering threshold is fixed for each cluster. When new data comes into this stream clustering model, the output of training data is measured with new data output that is decided to forward the data into the appropriate clusters based on the assigned threshold with minimum similarity. Through the performance analysis and the attained results, the clustering quality of the recommended system is ensured regarding standard performance metrics by estimating with various clustering and heuristic algorithms. [ABSTRACT FROM AUTHOR]

Fe─N─C materials with Fe─N4 sites are considered as most promising non‐precious metal‐based electrocatalysts for low‐cost proton‐exchange‐membrane fuel cells (PEMFCs). Breaking the trade‐off between activity and stability has been a long‐standing challenge in the field of acidic oxygen reduction reaction (ORR). Herein, a "top‐down" thermally‐driven strategy is developed to achieve highly active pyrrolic N‐coordinated Fe sites in a high spin state with Fe atomic cluster (Fen@Fe─Npyrr─C) and discover that the neighboring Fen cluster can synergistically stabilize such vulnerable Fe─N4 sites by inhibiting their protonation. Consequently, the Fen@Fe─Npyrr─C catalysts exhibit much enhanced ORR activity and stability, endowing PEMFCs with a high power density of 804.6 mW cm−2 (testing conditions: 80 °C, 100% RH, 2.0 bar) and over 100 h durability (at 0.5 V). These findings open up opportunities for the exploration of durable Fe─N─C ORR electrocatalysts for non‐precious metal‐based PEMFCs and other applications. [ABSTRACT FROM AUTHOR]

Yunnan Province, residing in the eastern segment of the Qinghai–Tibet Plateau and the western part of the Yunnan–Guizhou Plateau, faces significant challenges due to its intricate geological structures and frequent geohazards. These pose monumental risks to community safety and infrastructure. Unfortunately, conventional spatial indexing methods struggle with the enormous influx of geohazard data, exhibiting inadequacies in efficient spatio-temporal querying and failing to meet the swift response imperatives for real-time geohazard monitoring and early warning mechanisms. In response to these challenges, this study proffers a cutting-edge spatio-temporal indexing model, the BCHR-index, undergirded by data stream clustering algorithms. The operational schema of the BCHR-index model is bifurcated into two stages: real-time and offline. The real-time phase proficiently uses micro-clusters shaped by the CluStream algorithm in unison with a B+ tree to construct indices in memory, thereby satisfying the exigent response necessities for geohazard data streams. Conversely, the offline stage employs the CluStream algorithm and the Hilbert curve to manage heterogeneously distributed spatial objects. Paired with a B+ tree, this framework promotes efficient spatio-temporal querying of geohazard data. The empirical results indicate that the indexing model implemented in this study affords millisecond-level responses when faced with query requests from real-time geohazard data streams. Moreover, in aspects of spatial query efficiency and data-insertion performance, it demonstrates superior results compared to the R-tree and Hilbert-R tree models. [ABSTRACT FROM AUTHOR]

The nonlinear Hall effect (NLHE) is a phenomenon which could produce a transverse Hall voltage in a time-reversal-invariant material. Here, we report the real space characterizations of NLHE evaluated through quantum transport in TaIrTe4 nanoribbon without the explicit Berry curvature dipole (BCD) information. We first characterize the NLHE in both transverse confined directions in global-level measurement. The impact of quantum confinement in NLHE is evaluated by adjusting the width of nanoribbons. Then, the probing area is trimmed to the atomic scale to evaluate the local texture, where we discover its patterns differ among the probed neighboring atomic groups. The analysis of charge distribution reveals the connections between NLHE's local patterns and its non-centrosymmetric nature, rendering nearly an order of Hall voltage enhancement through probe positioning. Our work paves the way to expand the range of NLHE study and unveil its physics in more versatile material systems. [ABSTRACT FROM AUTHOR]

The Greifswald multi-reflection time-of-flight setup has been extended with a magnetron sputtering gas aggregation source for the production of atomic cluster ions with sizes ranging from a single to thousands of atoms. This source, combined with a newly added quadrupole mass filter and a linear Paul trap, opens up the possibility of many new atomic-cluster studies not feasible with the setup before. The new components and their interfacing with the previous setup are described, and benchmarking as well as the first experimental results are presented. The capability of the system to handle singly charged ions with masses of several ten thousand atomic mass units is demonstrated. [ABSTRACT FROM AUTHOR]

We present important use cases and limitations when considering results obtained from cluster perturbation theory (CPT). CPT combines the solutions of small individual clusters of an infinite lattice system with the Bloch theory of conventional band theory to provide an approximation for the Green's function in the thermodynamic limit. To this end, we are investigating single-band and multi-band Hubbard models in 1D and 2D systems. A special interest is taken in the supposed pseudogap regime of the 2D square lattice at half-filling and intermediate interaction strength ( U ≤ 3 t ) as well as the metal–insulator transition. We point out that the finite-size level spacing of the cluster limits the resolution of spectral features within CPT. This restricts the investigation of asymptotic properties of the metal–insulator transition, as it would require much larger cluster sizes that are beyond computational capabilities. [ABSTRACT FROM AUTHOR]

Selective autophagy of the endoplasmic reticulum (ER), known as ER-phagy, is an important regulator of ER remodeling and essential to maintain cellular homeostasis during environmental changes. We recently showed that members of the FAM134 family play a critical role during stress-induced ER-phagy. However, the mechanisms on how they are activated remain largely unknown. In this study, we analyze phosphorylation of FAM134 as a trigger of FAM134-driven ER-phagy upon mTOR (mechanistic target of rapamycin) inhibition. An unbiased screen of kinase inhibitors reveals CK2 to be essential for FAM134B- and FAM134C-driven ER-phagy after mTOR inhibition. Furthermore, we provide evidence that ER-phagy receptors are regulated by ubiquitination events and that treatment with E1 inhibitor suppresses Torin1-induced ER-phagy flux. Using super-resolution microscopy, we show that CK2 activity is essential for the formation of high-density FAM134B and FAM134C clusters. In addition, dense clustering of FAM134B and FAM134C requires phosphorylation-dependent ubiquitination of FAM134B and FAM134C. Treatment with the CK2 inhibitor SGC-CK2-1 or mutation of FAM134B and FAM134C phosphosites prevents ubiquitination of FAM134 proteins, formation of high-density clusters, as well as Torin1-induced ER-phagy flux. Therefore, we propose that CK2-dependent phosphorylation of ER-phagy receptors precedes ubiquitin-dependent activation of ER-phagy flux. Berkane et al. investigated the activation process of selective autophagy of the ER. They show that that phosphorylation of FAM134 proteins by CK2 is a prerequisite for the formation of large micro-clusters of high-density at the ER membrane. [ABSTRACT FROM AUTHOR]

Planar oxide atomic clusters are of considerable scientific interest because of their potential for enhanced catalytic activity versus their three‐dimensional counterparts. This enhancement is the result of the substrate stabilizing novel planar configurations that have an extensive periphery where catalytic reactions can occur. A class of planar NbnOm atomic clusters that are synthesized by the evaporation of metallic Nb onto an Au(111) substrate in an ultrahigh vacuum environment and subsequent oxidation at elevated temperatures is reported. The atomic structures of the clusters are determined using a combination of scanning tunneling microscopy and density functional theory. The clusters are composed of structural units with four‐, five‐, and sixfold rotational symmetry and these units can assemble to form larger planar clusters. The theoretical comparison of supported structures with their hypothetical freestanding counterparts shows that the atomic and electronic structures of the oxide clusters are significantly altered by the interaction with the Au substrate. The substrate effects include interfacial charge transfer and structural relaxation to relieve the strain in the Nb‐O bonds. The substrate interactions also reduce the energy differences between clusters of different configurations and this enables the coexistence of a large variety of cluster configurations. [ABSTRACT FROM AUTHOR]

Self‐assembled nanoparticle networks have emerged as multifunctional building blocks for a new generation of highly sensitive sensing technologies that offer large surface‐to‐volume ratios and a range of associated benefits. Unfortunately, with nanoparticle networks often being held together by weak van der Waals forces, the development of useful commercial devices is slowed by the relatively low robustness and poor carrier transport characteristics. This study shows how the application of a single droplet of ethanol can induce capillary forces capability of delivering significant changes to the morphological, structural, optical, and electronic properties of ZnO nanoclusters. It demonstrates how ZnO nanocluster "dendrites" and nanoparticles are forced together to form micro‐scale islands and larger nanoparticles, and thereby improve the robustness of the layers and the quality of the junctions between the nanoparticles without significantly reducing the overall porosity of the layer or degrading the structural or optical properties in any way. The commensurate improvement in the electronic transport within the layers is found to greatly improve the photoresponse of UV detectors. It seems likely that the application of ethanol and the exploitation of capillary force can provide a technique that can greatly benefit any nanostructured, ultra‐porous device where poor charge transport currently limits performance. [ABSTRACT FROM AUTHOR]

In arterial myocytes, the canonical function of voltage-gated CaV1.2 and KV2.1 channels is to induce myocyte contraction and relaxation through their responses to membrane depolarization, respectively. Paradoxically, KV2.1 also plays a sex-specific role by promoting the clustering and activity of CaV1.2 channels. However, the impact of KV2.1 protein organization on CaV1.2 function remains poorly understood. We discovered that KV2.1 forms micro-clusters, which can transform into large macro-clusters when a critical clustering site (S590) in the channel is phosphorylated in arterial myocytes. Notably, female myocytes exhibit greater phosphorylation of S590, and macro-cluster formation compared to males. Contrary to current models, the activity of KV2.1 channels seems unrelated to density or macro-clustering in arterial myocytes. Disrupting the KV2.1 clustering site (KV2.1S590A) eliminated KV2.1 macro-clustering and sex-specific differences in CaV1.2 cluster size and activity. We propose that the degree of KV2.1 clustering tunes CaV1.2 channel function in a sex-specific manner in arterial myocytes. Advanced imaging and electrophysiology show that phosphorylation boosts the size of KV2.1 clusters, which in turn modulates dihydropyridine-sensitive CaV1.2 channel organization and function in arterial smooth muscle, with variations based on sex. [ABSTRACT FROM AUTHOR]

In order to obtain a new class of aggregation‐induced emission (AIE) polymers without common conjugated chromophores in their structures, hyperbranched polysiloxanes (HBPSi) containing halogen elements were obtained by introducing chlorine and bromine atoms into HBPSi (Cl‐HBPSi, Br‐HBPSi) through one‐step polycondensation reaction. The relationship between the chemical structure and fluorescence properties of the two types of HBPSi was studied. The results show that both Cl‐HBPSi and Br‐HBPSi prepared in this study can emit bright blue light under a UV lamp of 365 nm wavelength, and appropriate ratio of raw materials can endow the halogenated HBPSi with moderate degree of polymerization, and give it strong excitation intensity and emission intensity. Meanwhile, Br‐HBPSi exhibits a higher fluorescence intensity, which is due to the 'heavy atom effect' of halogen atoms. In addition, for different concentrations of tetrahydrofuran (THF) solutions with the same addition of HBPSi, the luminescence intensity increases gradually with the decrease of THF concentration. These results indicate that the emission intensity is affected by the molecular weight and concentration of polymers, and that the AIE properties of halogenated HBPSi are related to the 'impurity atomic clusters' formed by halogenated atoms and the hydroxyl groups formed by the heterogeneity of HBPSi. © 2023 Society of Industrial Chemistry. [ABSTRACT FROM AUTHOR]

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This study aims to compare the drivers of clustering of rural and urban creative industries in England. We use pre‐pandemic web‐scraped data from 154,618 creative industry organizations in England, and use a novel technique to identify 71 distinct rural creative "microclusters" of geographically proximate creative firms. We then consider the role of place‐based assets and agglomeration in the presence of microclusters at a micro‐level geography and find that the determinants of microclustering are generally consistent between rural and urban areas. On that basis we argue that policies to support creative clusters may drive rural regional development. [ABSTRACT FROM AUTHOR]

Faithfully representing chemical environments is essential for describing materials and molecules with machine learning approaches. Here, we present a systematic classification of these representations and then investigate (i) the sensitivity to perturbations and (ii) the effective dimensionality of a variety of atomic environment representations and over a range of material datasets. Representations investigated include atom centered symmetry functions, Chebyshev Polynomial Symmetry Functions (CHSF), smooth overlap of atomic positions, many-body tensor representation, and atomic cluster expansion. In area (i), we show that none of the atomic environment representations are linearly stable under tangential perturbations and that for CHSF, there are instabilities for particular choices of perturbation, which we show can be removed with a slight redefinition of the representation. In area (ii), we find that most representations can be compressed significantly without loss of precision and, further, that selecting optimal subsets of a representation method improves the accuracy of regression models built for a given dataset. [ABSTRACT FROM AUTHOR]

In the present work, we discuss the electronic properties of supported dispersed bimetallic clusters with respect to their size, geometry, and Aun/Agm (n + m = 6) composition. We have studied with supercell-density functional theory calculations the role of the charge transfer from the MgO defective support toward the cluster in the activation of O2 by AunAgm clusters. We first considered gas-phase clusters with different atomic compositions; then, we deposited all of them on a pristine (100)MgO surface and finally on a more realistic (100)MgO F-center. We performed a global and unrestricted search of the (cluster + surface) geometry. The Mexican enhanced genetic algorithm has been used to exhaustively explore the potential energy surface. Our results show that O2 activation depends on the Aun/Agm ratio. It has been found that both metals involved play different and important roles toward (a) the actual O2 dissociation and (b) weakening of the oxygen-cluster bond, which, in turn, may promote the possibility of a catalytic process to take place, such as the oxidation process of CO and NOx among others. [ABSTRACT FROM AUTHOR]

Transition metal oxide (TMO) anode materials in lithium‐ion batteries (LIBs) usually suffer from serious volume expansion leading to the pulverization of structures, further giving rise to lower specific capacity and worse cycling stability. Herein, by introducing polyoxometalate (POM) clusters into TMOs and precisely controlling the amount of POMs, the MnZnCuOx‐phosphomolybdic acid hybrid sub‐1 nm nanosheets (MZC‐PMA HSNSs) anode is successfully fabricated, where the special electron rich structure of POMs is conducive to accelerating the migration of lithium ions on the anode to obtain higher specific capacity, and the non‐covalent interactions between POMs and TMOs make the HSNSs possess excellent structural and chemical stability, thus exhibiting outstanding electrochemical performance in LIBs, achieving a high reversible capacity (1157 mAh g−1 at 100 mA g−1) and an admirable long‐term cycling stability at low and high current densities. [ABSTRACT FROM AUTHOR]

The crystal orientation effect on the mechanical properties and micro-deformation behavior of single-crystal iron (SC Fe) were revealed by molecular dynamics (MD) simulations. The results show that the surviving defects in the SC Fe models are [110] < [100] < [111], and only the vacancy and interstitial atomic clusters are formed in the [111] SC Fe model. Irradiation leads to the increase of elastic modulus owing to the annihilation of irradiation point defects. However, the non-annihilable irradiation clusters reduced the strength. The decrease of yield strain and yield strength of the [111] SC Fe model is significantly higher than those of [110] and [100] SC Fe models, exhibiting worse radiation damage resistance. This is due to the number and types of operation of slip systems in the [110] and [100] SC Fe after irradiation, which is caused by its poor inhibition of [111] crystal orientation on clusters under irradiation, being much lower than those in the [111] SC Fe. The yield strength of SC Fe increases with the increase of the number and length of 1/2 111 and 100 dislocations, while the plasticity decreases with the increase of the falling gradient of dislocations after yield. The purpose is to provide theoretical guidance for the microstructure design and regulation of radiation-damage-resistant iron-based materials. [ABSTRACT FROM AUTHOR]

Using repeated bundle extrusion of a Cu/NbTi composite, we have obtained a high-strength heterophase alloy having superconducting properties. X-ray diffraction characterization has shown that the material we obtained has an unstressed, relaxed structure in the form of self-consistent, locally diffusion-alloyed atomic groups ranging widely in size, which can be divided into three groups: (1) microcrystalline long-range-ordered particles about 450 Å in size, showing up as Debye peaks with sharp tops; (2) mesoscopic clusters with a nanoscale atomic order, responsible for broad diffuse lines; and (3) small low-dimensional atomic groups with short-range order (10–50 Å), responsible for incoherent diffuse X-ray scattering (very broad diffuse halos). [ABSTRACT FROM AUTHOR]

Despite the interest in copper clusters, a consensus on their atomic structure is still lacking. The experimental observation of isolated clusters is difficult, and theoretical predictions vary widely. The latter is because one must adequately describe the closed shell of d electrons both in its short- and long-range effects. Herein, we investigate the stability of small copper clusters (Cu N , N = 3–6 atoms) using spin-polarized DFT calculations under the GGA approximation, the Hubbard U correction, and the van der Waals forces. We found that the spin-polarized and vdW contributions have little effect on the binding energies of the isomers. The inclusion of U represents the most relevant contribution to the ordering of the Cu N isomers, and our calculated binding energies for the clusters agreed with the experimental values. We also found that atomic relaxations alone are not enough to determine the stability of small copper clusters. It is also necessary to build the energy landscape or calculate the vibrational frequencies of the isomers. We found that the vibrational frequencies of the isomers were in the THz range and the normal modes of vibration were discrete. This approach is relevant to future studies involving isolated or supported copper clusters. [ABSTRACT FROM AUTHOR]

First of all, we show that any spherically symmetric galactic model with integrated mass profile M (r) → 0 as r → 0 is physically correct close to the centre only provided that the circular velocity v c (r) → 0 and the gravitational field g (r) → 0 as r → 0 . Next, we apply this statement to a broad class of five-parameter spherical galactic models, including most of those used in astrophysics and cosmology. Specifically, we show that the Jaffe and Hernquist models can be trusted only for r ≳ 0.2 R e ( R e being the effective radius), while the Navarro–Frank–White (NFW) model cannot describe galaxies in the central region of regular clusters. We also briefly discuss the relevance of our result for the NFW profile of pure dark matter halos. However, we are unable to tell at which central distance the NFW model breaks down in either case, and this is a challenge for future investigations. [ABSTRACT FROM AUTHOR]

Group IIIA elements are electron deficient, and the transition metal doped clusters can be used to build cluster-based materials. This paper study the global lowest energy structures of In8FeNan (n = 0, 2, 4, 6, 8) by using evolutionary algorithm combined with spin polarized density functional theories. The electronic structures show that the Na atoms donate electrons to the In8Fe core and combine on the peripheries of the clusters through electrostatic interactions. Analyses on density of states and molecular orbitals reveal that the 5s orbitals of In atoms do not mix with other atomic orbitals and form superatomic orbitals with lower energies. The 3d orbitals of Fe atom interact strongly with the superatomic orbitals formed by In 5p. Different interaction patterns compete and it makes the lowest electronic ground states be singlet or triplet. In the triplet states of In8FeNan, the α orbitals have three or four 3d orbitals localized on the Fe atom. For the singlet states, there exists no pure 3d atomic orbitals and the upper valence states show obvious features of bonding or antibonding interactions between atomic Fe 3d and superatomic orbitals composed of In 5p. The strong orbital interactions enhance significantly the stabilities of the clusters. [ABSTRACT FROM AUTHOR]

Clustering is a technique for statistical data analysis and is widely used in many areas where class labels are not available. Major problems related to clustering algorithms are handling high-dimensional, imbalanced, and/or varying-density datasets, detecting outliers, and defining arbitrary-shaped clusters. In this study, we proposed a novel clustering algorithm named as MCMSTClustering (Defining Non-Spherical Clusters by using Minimum Spanning Tree over KD-Tree-based Micro-Clusters) to overcome mentioned issues simultaneously. Our algorithm consists of three parts. The first part is defining micro-clusters using the KD-Tree data structure with range search. The second part is constructing macro-clusters by using minimum spanning tree (MST) on defined micro-clusters, and the final part is regulating defined clusters to increase the accuracy of the algorithm. To state the efficiency of our algorithm, we performed some experimental studies on some state-of-the-art algorithms. The findings were presented in detail with tables and graphs. The success of the proposed algorithm using various performance evaluation criteria was confirmed. According to the experimental studies, MCMSTClustering outperformed competitor algorithms in aspects of clustering quality in acceptable run-time. Besides, the obtained results showed that the novel algorithm can be applied effectively in solving many different clustering problems in the literature. [ABSTRACT FROM AUTHOR]

With recent advances in immune checkpoint inhibitors (ICIs), immunotherapy has become the standard treatment for various malignant tumors. Their indications and dosages have been determined empirically, taking individually conducted clinical trials into consideration, but without a standard method to evaluate them. Here we establish an advanced imaging system to visualize human PD-1 microclusters, in which a minimal T cell receptor (TCR) signaling unit co-localizes with the inhibitory co-receptor PD-1 in vitro. In these microclusters PD-1 dephosphorylates both the TCR/CD3 complex and its downstream signaling molecules via the recruitment of a phosphatase, SHP2, upon stimulation with the ligand hPD-L1. In this system, blocking antibodies for hPD-1-hPD-L1 binding inhibits hPD-1 microcluster formation, and each therapeutic antibody (pembrolizumab, nivolumab, durvalumab and atezolizumab) is characterized by a proprietary optimal concentration and combinatorial efficiency enhancement. We propose that our imaging system could digitally evaluate PD-1-mediated T cell suppression to evaluate their clinical usefulness and to develop the most suitable combinations among ICIs or between ICIs and conventional cancer treatments. Immune checkpoint inhibitors are now routinely used in cancer therapy, however, the dosage and integration into conventional cancer therapy is determined via empirical experience rather than mechanistic rationale. Here authors establish an advanced single-molecule imaging method, by with which they are directly monitoring and evaluating the effect of immune checkpoint inhibitors on T cell signaling. [ABSTRACT FROM AUTHOR]

In this work, we would like to explore the possibility of studying phase change behaviour in pure Lennard-Jones clusters as well as the effect of introducing a heteroatom. The system studied are Ar 10 , Xe 10 and Ar 10 - 1 Xe 1 as well as Ar 10 - 9 Xe 9 . The phase change is followed by the temperature variation in classical configuration heat capacity. As the heat capacity is calculated by evaluating the variance in the energy of the isomers possible, an important aspect is to sample the Lennard-Jones surface effectively and pick out as many isomers which are possible for this system. The sampling at various temperatures has been done using the replica exchange Monte Carlo or Parallel tempering procedure. The main focus of the present work is to see how the phase change behaviour is affected on going from the pure Lennard-Jones systems to the once possessing dopants. To further aid in the understanding bond length fluctuation parameter has also been calculated for all the systems with changing temperature along with the classical configuration. Synopsis: The phase change behavior of pure Lennard-Jones clusters and the effect of introducing a heteroatom was studied using replica exchange Monte Carlo or parallel tempering techniques and examining the classical configuration heat capacity and bond length fluctuation parameter. The systems studied were Ar10 , Xe10 and Ar10−1 Xe1 as well as Ar10−9 Xe9. [ABSTRACT FROM AUTHOR]

Clustering high dimensional data is challenging as data dimensionality increases the distance between data points, resulting in sparse regions that degrade clustering performance. Subspace clustering is a common approach for processing high-dimensional data by finding relevant features for each cluster in the data space. Subspace clustering methods extend traditional clustering to account for the constraints imposed by data streams. Data streams are not only high-dimensional, but also unbounded and evolving. This necessitates the development of subspace clustering algorithms that can handle high dimensionality and adapt to the unique characteristics of data streams. Although many articles have contributed to the literature review on data stream clustering, there is currently no specific review on subspace clustering algorithms in high-dimensional data streams. Therefore, this article aims to systematically review the existing literature on subspace clustering of data streams in high-dimensional streaming environments. The review follows a systematic methodological approach and includes 18 articles for the final analysis. The analysis focused on two research questions related to the general clustering process and dealing with the unbounded and evolving characteristics of data streams. The main findings relate to six elements: clustering process, cluster search, subspace search, synopsis structure, cluster maintenance, and evaluation measures. Most algorithms use a two-phase clustering approach consisting of an initialization stage, a refinement stage, a cluster maintenance stage, and a final clustering stage. The density-based top-down subspace clustering approach is more widely used than the others because it is able to distinguish true clusters and outliers using projected microclusters. Most algorithms implicitly adapt to the evolving nature of the data stream by using a time fading function that is sensitive to outliers. Future work can focus on the clustering framework, parameter optimization, subspace search techniques, memory-efficient synopsis structures, explicit cluster change detection, and intrinsic performance metrics. This article can serve as a guide for researchers interested in high-dimensional subspace clustering methods for data streams. [ABSTRACT FROM AUTHOR]

Atomic‐molecular engineering is an effective way to accurately tailor the microstructures and components of materials at the micro‐nano scale, which can be applied to flexibly manipulate their electromagnetic (EM) response. Herein, graphene microlaminates with multi‐layer structure are fabricated by atomic cluster engineering and oxidative molecular layer deposition for the first time. The microlaminates enable a tunable EM loss (from 0.93 to 3.94 for imaginary permittivity and from 0.17 to 0.25 for imaginary permeability) by changing poly(3,4‐ethylenedioxythiophene) cycles, and the attenuation constant reaches 160. On this basis, multifunctional antennas are conceived, achieving frequency‐selective response that enables steady harvest of > 90% of EM energy from signal source, and tactfully recycling waste heat energy and mechanical energy. This study will furnish a new horizon for information transmission and artificial intelligence in the future. [ABSTRACT FROM AUTHOR]

We performed a combination of quantum chemical calculations and molecular dynamics simulations to assess the stability of various size N H 3 n − ammonia cluster anions up to n = 32 monomers. In the n = 3–8 size range, cluster anions are optimized and the vertical detachment energy of the excess electron (VDE) from increasing size clusters is computed using various level methods including density functional theory, MP2, and coupled-cluster singles doubles with perturbative triples. These clusters bind the electrons in nonbranched hydrogen bonding chains in dipole bound states. The VDE increases with size from a few millielectron volt up to ∼200 meV. The electron binding energy is weaker than that in water clusters but comparable to small methanol cluster VDEs. We located the first branched hydrogen bonding cluster that binds the excess electron at n = 7. For larger (n = 8–32) clusters, we generated cold, neutral clusters by semiempirical and ab initio molecular dynamics simulations and added an extra electron to selected neutral configurations. VDE calculations on the adiabatic and the relaxed anionic structures suggest that the n = 12–32 neutral clusters weakly bind the excess electron. Electron binding energies for these clusters (∼100 meV) appear to be significantly weaker than those extrapolated from experimental data. The observed excess electron states are diffuse and localized outside the molecular frame (surface states) with minor (∼1%) penetration to the nitrogen frontier orbitals. Stable minima with excess electron states surrounded by solvent molecules (cavity states) were not found in this size regime. [ABSTRACT FROM AUTHOR]

Using the fixed-node diffusion Monte Carlo (FN-DMC) method, we calculate the total energy of small lithium clusters Lin (n = 2–6) to obtain the many-body decomposition of the interaction energy of 2- up to 6-body interactions. The obtained many-body decomposition of the interaction energy shows an alternating series with even and odd terms of attractive and repulsive contributions, respectively. The two-body attractive interactions guarantee the stability of the Li2, Li3, and Li4 clusters. For larger clusters Li5 and Li6, the 4-body attractive interactions are required for their stabilization once the strength of the 3-body repulsive interactions overwhelms that of the 2-body attractive ones. With increasing the cluster size, the additive and nonadditive contributions to the interaction energy increase linearly in magnitude but with different slopes for the two-dimensional (2D) planar and three-dimensional (3D) cagelike clusters. The significant increment in nonadditive effects from the 4-atom to the 5-atom cluster has driven the structural transition from 2D to 3D. Combining the FN-DMC calculations with the Hartree-Fock many-body decomposition of the interaction energy, we extract the correlation effects, showing that an odd-even competition pattern in the many-body repulsive and attractive interactions is crucial for the stabilization of the clusters. [ABSTRACT FROM AUTHOR]

A first-principle study of (Pt 3 Cu) n n = 10–11 nanoclusters was performed using the linear combination of Gaussian-type orbitals within the auxiliary density functional theory (ADFT) framework. Neutral, anionic and cationic clusters species were studied. To carry on a detailed exploration of the potential energy surface of these systems, Born-Oppenheimer molecular dynamics (BOMD) simulations have been performed. Several dozens of structures were taken along the generated BOMD trajectories as initial geometries for geometry optimizations. Successive geometry optimizations of these systems, in different electron spin multiplicities and without any type of restriction, were computed. The obtained optimized structures have been characterized by frequency analysis calculations. Computed minima structures, harmonic frequencies, average bond lengths, magnetic moments, spin density plots, dissociation energy, ionization potential and electron affinity are reported. The formation of octahedra moieties has been observed in the most stable structures. The findings of the growing pattern of these clusters can serve as guide to search a synthetic route that can yield nanoparticles with desired geometries and high stability. [ABSTRACT FROM AUTHOR]

Given a million escort advertisements, how can we spot near-duplicates? Such micro-clusters of ads are usually signals of human trafficking (HT). How can we summarize them to convince law enforcement to act? Spotting micro-clusters of near-duplicate documents is useful in multiple, additional settings, including spam-bot detection in Twitter ads, plagiarism, and more. We present InfoShield, which makes the following contributions: practical, being scalable and effective on real data; parameter-free and principled, requiring no user-defined parameters; interpretable, finding a document to be the cluster representative, highlighting all the common phrases, and automatically detecting “slots” (i.e., phrases that differ in every document); and generalizable, beating or matching domain-specific methods in Twitter bot detection and HT detection, respectively, as well as being language independent. Interpretability is particularly important for the anti-HT domain, where law enforcement must visually inspect ads. Our experiments on real data show that InfoShield correctly identifies Twitter bots with an F1 score over 90% and detects HT ads with 84% precision. Moreover, it is scalable, requiring about 8 hours for 4 million documents on a stock laptop. Our incremental version, DeltaShield, allows for fast, incremental updates, with minor loss of accuracy. [ABSTRACT FROM AUTHOR]

The regulation of electron distribution of single‐atomic metal sites by atomic clusters is an effective strategy to boost their intrinsic activity of oxygen reduction reaction (ORR). Herein we report the construction of single‐atomic Mn sites decorated with atomic clusters by an innovative combination of post‐adsorption and secondary pyrolysis. The X‐ray absorption spectroscopy confirms the formation of Mn sites via Mn‐N4 coordination bonding to FeMn atomic clusters (FeMnac/Mn‐N4C), which has been demonstrated theoretically to be conducive to the adsorption of molecular O2 and the break of O−O bond during the ORR process. Benefiting from the structural features above, the FeMnac/Mn‐N4C catalyst exhibits excellent ORR activity with half‐wave potential of 0.79 V in 0.5 M H2SO4 and 0.90 V in 0.1 M KOH as well as preeminent Zn‐air battery performance. Such synthetic strategy may open up a route to construct highly active catalysts with tunable atomic structures for diverse applications. [ABSTRACT FROM AUTHOR]

This paper analyzes music festivals as a territorial structuring tool as part of a larger reflection on the resilience of territories highly dependent on tourism. The results obtained from our study on the Empordà (Costa Brava), through in-depth interviews and a system of quantitative indicators, confirm that these cultural tourism products function as microclusters, creating and reinforcing stable relationships between local actors. When they become one more product in a multifunctional territory, they can contribute to making destinations and territories more resilient. [ABSTRACT FROM AUTHOR]

Catalytic systems based on sub-nanoclusters deposited over different supports are promising for very relevant chemical transformations such as many electrocatalytic processes as the ORR. These systems have been demonstrated to be very fluxional, as they are able to change shape and interconvert between each other either alone or in the presence of adsorbates. In addition, an accurate representation of their catalytic activity requires the consideration of ensemble effects and not a single structure alone. In this sense, a reliable theoretical methodology should assure an accurate and extensive exploration of the potential energy surface to include all the relevant structures and with correct relative energies. In this context, we applied DFT in conjunction with global optimization techniques to obtain and analyze the characteristics of the many local minima of Pt6 sub-nanoclusters over a carbon-based support (graphene)—a system with electrocatalytic relevance. We also analyzed the magnetism and the charge transfer between the clusters and the support and paid special attention to the dependence of dispersion effects on the ensemble characteristics. We found that the ensembles computed with and without dispersion corrections are qualitatively similar, especially for the lowest-in-energy clusters, which we attribute to a (mainly) covalent binding to the surface. However, there are some significant variations in the relative stability of some clusters, which would significantly affect their population in the ensemble composition. [ABSTRACT FROM AUTHOR]

Using the sol–gel method, Ni–Zn–Co ferrite doped with Sm3+ were prepared. The chemical formula is Ni0.2Zn0.1Co0.7Fe2-xSmxO4. The doping amount x ranged from 0 to 0.1, and the change in the doping amount of each sample was 0.025. X-ray diffraction (XRD) results showed that the structure of the sample is cubic spinel. Fourier transform infrared spectroscopy (FTIR) can reveal information about atomic groups indicating the chemical properties of samples, and the variation of the modulus of elastic modulus is consistent with the structural characteristics of XRD. Utilizing scanning electron microscope (SEM) and transmission electron microscope (TEM), the morphologies of the samples are spherical cubic. Energy dispersive spectrum (EDS) showed that there were no other impurity elements in the compositions of the prepared samples. Vibrating sample magnetometer (VSM) was used to examine the samples' magnetic characteristics. The M–H loop showed the soft magnetic characteristics of the samples. Coercivity values are related to domain wall displacement and domain wall rotation. [ABSTRACT FROM AUTHOR]

Using the sol–gel method, Ni–Zn–Co ferrite doped with Sm3+ were prepared. The chemical formula is Ni0.2Zn0.1Co0.7Fe2-xSmxO4. The doping amount x ranged from 0 to 0.1, and the change in the doping amount of each sample was 0.025. X-ray diffraction (XRD) results showed that the structure of the sample is cubic spinel. Fourier transform infrared spectroscopy (FTIR) can reveal information about atomic groups indicating the chemical properties of samples, and the variation of the modulus of elastic modulus is consistent with the structural characteristics of XRD. Utilizing scanning electron microscope (SEM) and transmission electron microscope (TEM), the morphologies of the samples are spherical cubic. Energy dispersive spectrum (EDS) showed that there were no other impurity elements in the compositions of the prepared samples. Vibrating sample magnetometer (VSM) was used to examine the samples' magnetic characteristics. The M–H loop showed the soft magnetic characteristics of the samples. Coercivity values are related to domain wall displacement and domain wall rotation. [ABSTRACT FROM AUTHOR]

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The evolution of the chemical composition of grain boundaries during layering of metal microvolumes on the friction surfaces is studied using Auger electron spectroscopy. Metal layering on the friction surfaces leads to its saturation with oxygen from the working medium and dissolution of the carbide phase. Most of both the oxygen atoms and the carbon atoms of dissolved carbides are in friction layers in the form of a solid solution in structurally disorganized near-boundary regions of grains. The individual nearest atomic surrounding of impurity atoms in the near-boundary regions of grains is determined by analysing the extended fine structure of the scattered electron energy loss spectra (EELS). The carbon atoms at the grain boundaries of the deformed original metal are located in the octahedral pores of the b.c.c.-iron– chromium alloy and form a dispersed carbide phase (Cr, Fe)7C3. The finely dispersed carbide phase (Cr, Fe)7C3 disappears in the near-boundary regions of the grains of the friction surface layers. In this case, a significant number of carbon atoms are transferred to new crystal structure positions. Together with oxygen atoms and metal atoms, they form metastable Fe–O–C (Fe–Cr– O–C) atomic clusters. The effect of impurity atoms on the electronic structure and character of interatomic bonds in the near-boundary regions of grains is studied using zone calculations within the LAPW approximation using the full potential and the generalized gradient correction of electron density (GGA). As shown, the carbon atoms in the octahedral pores of the b.c.c.-iron–chromium alloy form strong covalent bonds with the surrounding metal atoms. They reduce the mobility of atoms and increase the work hardening of the metal. Metastable Fe–O–C (Fe–Cr–O–C) atomic clusters and the metal atoms around them separate regions with low electron density. The consequence of this is the limited participation of valence electrons in the formation of bonds between the metal atoms and the clusters’ atoms. These bonds are easily destroyed during local deformation of the metal. This increases the plasticity of the metal in places of accumulation of metastable atomic clusters. The instability of the interatomic bonds formed by 3d electrons of clusters’ metal atoms with the shift of the atoms also contributes to this effect. As shown, metal layering on the friction surfaces causes the accumulation of metastable atomic clusters Fe–O–C (Fe–Cr–O–C) and ultrafine oxide phase α-Fe2О3 at the grain boundaries of friction layers. This one contributes to the formation of dynamic systems in the friction layers. The mechanism of deformation of these systems is connected with the collective forms of motion of defects in the crystal lattice. Therefore, a high-energy impulse impact on the ultrafine systems saturated with oxygen and carbon can transfer them into a structurally unstable state. In this case, a crystalamorphous nanostructured material is formed. [ABSTRACT FROM AUTHOR]