Series Of Clusters Research Articles

Analysis of Worldwide Time-Series Data Reveals Some Universal Patterns of Evolution of the SARS-CoV-2 Pandemic

Predicting the evolution of the current epidemic depends significantly on understanding the nature of the underlying stochastic processes. To unravel the global features of these processes, we analyse the world data of SARS-CoV-2 infection events, scrutinising two 8-month periods associated with the epidemic’s outbreak and initial immunisation phase. Based on the correlation-network mapping, K-means clustering, and multifractal time series analysis, our results reveal several universal patterns of infection dynamics, suggesting potential predominant drivers of the pandemic. More precisely, the Laplacian eigenvectors localisation has revealed robust communities of different countries and regions that break into clusters according to similar profiles of infection fluctuations. Apart from quantitative measures, the immunisation phase differs significantly from the epidemic outbreak by the countries and regions constituting each cluster. While the similarity grouping possesses some regional components, the appearance of large clusters spanning different geographic locations is persevering. Furthermore, characteristic cyclic trends are related to these clusters; they dominate large temporal fluctuations of infection evolution, which are prominent in the immunisation phase. Meanwhile, persistent fluctuations around the local trend occur in intervals smaller than 14 days. These results provide a basis for further research into the interplay between biological and social factors as the primary cause of infection cycles and a better understanding of the impact of socio-economical and environmental factors at different phases of the pandemic.

Aromaticity of Singlet and Triplet Boron Disk-like Clusters: A Test for Electron Counting Aromaticity Rules.

Boron clusters are polyhedral boron-containing structures that have unique features and properties. The disk-like boron clusters are among the most fascinating boron cluster forms. These clusters have a molecular orbital (MO) distribution similar to the one derived from the simple particle-on-a-disk model. In this model, the MOs come in pairs except for m = 0. Disk-like boron clusters in their singlet ground state are aromatic when they reach a closed-shell structure. One could expect that disk-like aromatic boron clusters in the singlet state, when acquiring or releasing two electrons, may also be aromatic in the lowest-lying triplet state. We use magnetically induced current densities and bond current strengths to analyze the aromatic character of a series of disk-like boron clusters. Our results show that, with the exception of triplet 3B19-, the disk-like boron clusters follow Hückel and Baird's rules if one considers the different MOs grouped by their symmetry. We also found that if the lowest-lying triplet state in disk-like boron clusters is aromatic, this triplet state is the ground state for this species.

Fluorescence or Phosphorescence? The Metallic Composition of the Nanocluster Kernel Does Matter

AbstractIt remains challenging to manipulate the nature of photoluminescence as either fluorescence or phosphorescence for a correlated cluster series. In this work, two correlated nanoclusters, Au5Ag11(SR)8(DPPOE)2 and Pt1Ag16(SR)8(DPPOE)2 with comparable structure features, were synthesized and structurally determined. These two alloy nanoclusters displayed distinct photoluminescent nature—the Au5Ag11 nanocluster is fluorescent, whereas the Pt1Ag16 nanocluster is phosphorescent. The decay processes of the excited electrons in these two nanoclusters have been explicitly mapped out by both experimental and theoretical approaches, disclosing the mechanisms of their fluorescence and phosphorescence. Specifically, the metallic compositions of the nanocluster kernels mattered in determining their photoluminescent nature. The results herein provide an intriguing nanomodel that enables us to grasp the origin of photoluminescence at the atomic level, which further paves the way for fabricating novel nanoclusters or cluster‐based nanomaterials with customized photophysical properties.

Fluorescence or Phosphorescence? The Metallic Composition of the Nanocluster Kernel Does Matter.

It remains challenging to manipulate the nature of photoluminescence as either fluorescence or phosphorescence for a correlated cluster series. In this work, two correlated nanoclusters, Au5 Ag11 (SR)8 (DPPOE)2 and Pt1 Ag16 (SR)8 (DPPOE)2 with comparable structure features, were synthesized and structurally determined. These two alloy nanoclusters displayed distinct photoluminescent nature-the Au5 Ag11 nanocluster is fluorescent, whereas the Pt1 Ag16 nanocluster is phosphorescent. The decay processes of the excited electrons in these two nanoclusters have been explicitly mapped out by both experimental and theoretical approaches, disclosing the mechanisms of their fluorescence and phosphorescence. Specifically, the metallic compositions of the nanocluster kernels mattered in determining their photoluminescent nature. The results herein provide an intriguing nanomodel that enables us to grasp the origin of photoluminescence at the atomic level, which further paves the way for fabricating novel nanoclusters or cluster-based nanomaterials with customized photophysical properties.

Metal-rich clusters: synthesis, structure and bonding of metallaboranes featuring µ5-boride and triply bridging borylene units

A series of metal-rich clusters of group 9 containing boride or borylene units have been isolated and structurally characterized. The thermolysis reaction of arachno-[IrCp*H2(B3H7)] (I) with [Ru3(CO)12] allowed to isolate the µ5-boride nido-[(IrCp*){Ru(CO)2}{Ru(CO)3}3(µ-H)5B2H2(μ5-B)] (1) and the tetrametallic cluster [(IrCp*)2{Ru(CO)2}{Ru(CO)3}(μ-CO)2(μ3-BH)] (2) with a µ3-coordinated triply-bridged borylene moiety. The geometry of cluster 1 can be derived from an eight-vertex closo-dodecadeltahedron by removal of one five-connected vertex followed by capping of a Ru(CO)3 moiety. The borylene moiety (BH) of cluster 2 is connected in a μ3-fashion to the deltahedral face of a tetrametallic tetrahedron (Ir2Ru2). To synthesize the Mn analogue of 2, thermolysis reaction with [Mn2(CO)10] was carried out, that afforded the trimetallic tetrahedral borylene [(IrCp*)2{MnH (CO)3}(μ-CO)2(μ3-BH)] (3) along with the known face-fused boride [{Ir(CO)2}3(IrCp*)3(μ3-CO)(μ-CO)(μ5-BH)] (4). Clusters 2 and 3 are the first triply-bridged borylenes having an Ir metal atom in the core. All these clusters were characterized by NMR (1H, 11B and 13C), infrared (IR) spectroscopies and mass spectrometry. The structure of cluster 1 was confirmed by X-ray diffraction analysis. In addition, density functional theory (DFT) calculations were conducted to interpret and study the nature of bonding and electronic structure of cluster 1.

Construction of the Largest Metal-Centered Double-Ring Tubular Boron Clusters Based on Actinide Metal Doping

Metal doping has been considered to be an effective approach to stabilize various boron clusters. In this work, we constructed a series of largest metal-centered double-ring tubular boron clusters An@B24 (An = Th, Pa, Pu, and Am). Extensive global minimum structural searches combined with density functional theory predicted that the global minima of An@B24 (An = Th, Pu, and Am) are double-ring tubular structures. Formation energy analysis indicates that these boron clusters are highly stable, especially for Th@B24 and Pa@B24. Detailed bonding analysis shows that the significant stability of An@B24 is determined by the covalent character of the An-B bonding, which stems from the interactions of An 5f and 6d orbitals and B 2p orbitals. These results show that actinide metal doping is a feasible route to construct stable large metal-centered double-ring tubular boron clusters, offering the possibility to design boron nanomaterials with special physiochemical properties.

Extra contribution to the crystal stability of insensitive explosive TATB: The cooperativity of intermolecular interactions

An in-depth analysis on the cooperativity of intermolecular interactions including hydrogen bonding and π-π stacking in 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) crystal was studied. Two quantities, cooperativity rate and energy, were defined to evaluate the nature and strength of cooperativity in a series of clusters diverging from 1D to 3D prototypes. The origin and mechanism of the cooperative effect were settled to demonstrate that the nature of cooperativity is determined by whether the non-covalent interactions compete or promote with each other, which is manifested by the changing trend of electron transfer. There exists obvious cooperative effect in intra-layer and inter-layer structures as they own the equivalent non-covalent interactions, while anti-cooperative effect is also observed if two interactions correlate with each other. On the whole, in the process of crystal formation, the apparent cooperativity is the check and balance of the two effects, which is capable to support a global interaction among all of molecules and contribute to the stabilization of system. Based on the results, one may get a new insight to understand the relationship between non-covalent interactions and low impact sensitivity.

Relations of residents’ knowledge, satisfaction, perceived importance and participation in emergency management: A case study in modern and old urban communities of Ningbo, China

The community is the first scene of emergency events, and community residents are the primary responders. Participation of residents is highly important to the emergency management of urban communities, and it can be influenced by residents' attitudes towards both emergency management and the community. In this paper, the emergency management of urban communities is studied by statistical analysis within typical modern and old urban communities in Ningbo, China. Questionnaires were issued to collect residents' demographic characteristics, familiarity with emergency knowledge, perceived importance of emergency management, satisfaction with community management, and participation in emergency activities held by the community. Both descriptive and inferential statistics were used to analyze the data and explore the relations among variables. Finally, a series of path clusters involving 11 paths were proposed to explain the relations of residents’ demographics, knowledge, perceived importance, satisfaction, and their participation in emergency management in urban communities. Based on the primary data analysis and path clusters, some policy implications are provided to promote the emergency management participation of residents in urban communities.

Cu cluster embedded porous nanofibers for high-performance CO2 electroreduction

Metal-doped carbon materials, as one of the most important electrocatalytic catalysts for CO2 reduction reaction (CO2RR), have attracted increasing attention. Herein, a series of Cu cluster embedded highly porous nanofibers have been prepared through the carbonization of electro-spun MOF/PAN nanofibers. The obtained Cu cluster doped porous nanofibers possessed fibrous morphology, high porosity, conductivity, and uniformly dispersed Cu clusters, which could be applied as promising CO2RR catalysts. Specifically, best of them, MCP-500 exhibited high catalytic performance for CO2RR, in which the Faradaic efficiency of CO (FECO) was as high as 98% at −0.8 V and maintained above 95% after 10 h continuous electrocatalysis. The high performance might be attributed to the synergistic effect of tremendously layered graphene skeleton and uniformly dispersed Cu clusters that could largely promote the electron conductivity, mass transfer and catalytic activity during the electrocatalytic CO2RR process. This attempt will provide a new idea to design highly active CO2RR electrocatalyst.

Black Titanium-Oxo Clusters with Ultralow Band Gaps and Enhanced Nonlinear Optical Performance.

A series of catecholate-functionalized titanium-oxo clusters (TOCs), PTC-271 to PTC-277, with atomically precise structures were synthesized and characterized, including distinctive "boat" and "chair" conformations in PTC-273 and PTC-274, respectively. These cluster compounds are prominent for their ultralow optical band gaps, as is visually evident from the rather unusual black TOCs (B-TOCs), PTC-272 to PTC-277. The cluster structures were found to be ultrastable with respect to air, water, organic solvents, and even acidic or basic aqueous solutions in a wide pH range (pH 0-13), owing to the stabilizing effects of catecholate and its derivatives, as well as the carboxylate ligands. Another prominent feature is the occurrence of third-order nonlinear optical (NLO) performance, which has previously been unreported in the field of homometallic titanium-oxo clusters. Open-aperture Z-scan experiments show significant solid-state optical limiting (OL) applications of these B-TOCs, with high laser irradiation stability and low minimum normalized transmittance (Tmin) of PTC-273 as ∼0.17. Meanwhile, theoretical calculations indicate that the smaller band gaps of B-TOCs were beneficial for strengthening the NLO response. This work not only represents a significant milestone in the construction of stable low-band gap black titanium oxide materials but also contributes to the mechanism insights into their optical applications.

Epidemiological characteristics of local COVID-19 epidemics and control experience in routine prevention and control phase in China

The COVID-19 pandemic is still ongoing in the world, the risk of COVID-19 spread from other countries or in the country will exist for a long term in China. In the routine prevention and control phase, a number of local COVID-19 epidemics have occurred in China, most COVID-19 cases were sporadic ones, but a few case clusters or outbreaks were reported. Winter and spring were the seasons with high incidences of the epidemics; border and port cities had higher risk for outbreaks. Active surveillance in key populations was an effective way for the early detection of the epidemics. Through a series of comprehensive prevention and control measures, including mass nucleic acid screening, close contact tracing and isolation, classified management of areas and groups at risk, wider social distancing and strict travel management, the local COVID-19 epidemics have been quickly and effectively controlled. The experiences obtained in the control of the local epidemics would benefit the routine prevention and control of COVID-19 in China. The occurrence of a series of COVID-19 case clusters or outbreaks has revealed the weakness or deficiencies in the COVID-19 prevention and control in China, so this paper suggests some measures for the improvement of the future prevention and control of COVID-19.

Selective hydroboration of terminal alkynes catalyzed by heterometallic clusters with uranium–metal triple bonds

Selective hydroboration of terminal alkynes catalyzed by heterometallic clusters with uranium–metal triple bonds

Clustering Artikel pada Portal Berita Online Menggunakan Metode K-Means

The news categories on news portals are so diverse that the performance of the editors is increasing. The number of news articles each month, adds to the editor's task to manually categorize articles into predetermined categories. Clustering can be used to group data so that later it can group data in the same category with similar data. K-Means is a method that can be used to perform clustering. K-Means is a distance-based clustering technique that is divided into a series of clusters and only works for numeric attributes. The K-Means test conducted in this study is intended to compare cluster values. The K-Means made in this study apply TF-IDF, feature selection, and PCA. The cluster value assessment process uses visualization in the form of a bar plot of each metric value that is considered, namely the mean silhouette, accuracy, precision, recall, F1-score, and silhouette score. The results of the research that has been carried out by the K-Means method can achieve 94.93% accuracy and recall, 95.07% precision, and 94.94% F1-score.

Water quality forecasting based on data decomposition, fuzzy clustering and deep learning neural network

Water quality forecasting can provide useful information for public health protection and support water resources management. In order to forecast water quality more accurately, this paper proposes a novel hybrid model by combining data decomposition, fuzzy C-means clustering and bidirectional gated recurrent unit. Firstly, the original water quality data is decomposed into several subseries by empirical wavelet transform, and then, the decomposed subseries are recombined by fuzzy C-means clustering. Next, for each clustered series, bidirectional gated recurrent unit is applied to develop prediction model. Finally, the forecast result is obtained by the summation of the predictions for the subseries. The proposed forecast model is evaluated by the water quality data of Poyang Lake, China. Results show that the proposed forecast model provides highly accurate forecast result for all of the six water quality data: the average of MAPE of the forecast results for the six water quality datasets is 4.59% for 7 day ahead prediction. Furthermore, our model shows better forecast performance than the other models. Particularly, compared with the single BiGRU model, MAPE decreased by 32.86% in average. Results demonstrate that the proposed forecast model can be used effectively for water quality forecasting.

A Computational and Experimental View of Hydrogen Bonding in Glycerol Water Clusters.

Polyol-water clusters provide a template to probe ionization and solvation processes of paramount interest in atmospheric and interstellar chemistry. We generate glycerol water clusters in a continuous supersonic jet expansion and interrogate the neutral species with synchrotron-based tunable vacuum ultraviolet photoionization mass spectrometry. A series of glycerol fragments (m/z 44, 61, 62, and 74) clustered with water are observed. A judicious combination of backing pressure, nozzle temperature, and water vapor pressure allows for tuning the mol % of glycerol. The recorded appearance energies of the water cluster series m/z 62 and 74 are similar to that observed in pure glycerol, while the m/z 61 series shows a dependence on cluster composition. Furthermore, this series also tracks the water concentration of the beam. Theoretical calculations on neutral and ionized clusters visualize the hydrogen bond network in these water clusters and provide an assessment of the number of glycerol-glycerol, glycerol-water, and water-water hydrogen bonds in the cluster, as well as their interaction energies. This method of bond counting and interaction energy assessment explains the changes in the mass spectrum as a function of mol % and offers a glimpse of the disruption of the hydrogen bond network in glycerol-water clusters. The calculations also reveal interesting barrierless chemical processes in photoionized glycerol water clusters that are either activated or do not occur without the presence of water. Examples include spontaneous intramolecular proton transfer within glycerol to form a distonic ion, nonactivated breaking of a C-C bond, and spontaneous proton transfer from glycerol to water. These results appear relevant to radiation-induced chemical processing of alcohol-water ices in the interstellar medium.

Evolution of Vibrational Spectra in the Manganese-Silicon Clusters Mn2Sin, n = 10, 12, and 13, and Cationic [Mn2Si13

A comparison of DFT-computed and measured infrared spectra reveals the ground state structures of a series of gas-phase silicon clusters containing a common Mn2 unit. Mn2Si12 and [Mn2Si13]+ are both axially symmetric, allowing for a clean separation of the vibrational modes into parallel (a1) and perpendicular (e1) components. Information about the Mn–Mn and Mn–Si bonding can be extracted by tracing the evolution of these modes as the cluster increases in size. In [Mn2Si13]+, where the antiprismatic core is capped on both hexagonal faces, a relatively simple spectrum emerges that reflects a pseudo-D6d geometry. In cases where the cluster is more polar, either because there is no capping atom in the lower face (Mn2Si12) or the capping atom is present but displaced off the principal axis (Mn2Si13), the spectra include additional features derived from vibrational modes that are forbidden in the parent antiprism.

MLTF: Model less time-series forecasting

Multi-step ahead long term forecasting remains a pertinent challenge in time series literature due to non-stationary behaviour of real-world data. Predominantly most traditional time series models are parametric in nature and they use the predicted values to generate forecast for future time steps. This leads to error accumulation in each step of the forecasting horizon which causes increasingly poorer forecast in long-term. Other than the problem of error accumulation, most parametric algorithms also require significant pre-processing, hyper-parameter tuning, training and post-processing which can often put high computational burden on the system. Therefore, this paper proposes, Model Less Time-series Forecasting (MLTF), a non-parametric approach for forecasting which does not require any pre-processing or traditional training (i.e. Backpropagation). MLTF is a non-parametric method which uses statistical representations such as trend, linearity, entropy etc. to cluster series from a pre-defined repository and the series from same cluster are tagged as similar series. The trajectory of the target series is extracted from these similar series after applying an adaptive re-sampling technique. There is minimal training involved in MLTF, therefore this framework is computationally very efficient. The model-less nature also enables it to not suffer from error accumulation in long-horizon forecast. MLTF is validated empirically with a rich set of experiments involving M1, M3 competition dataset, Electricity, Volatility and COVID-19 data (over 4500 independent uni-variate series of different frequencies i.e. Hourly, Daily, Monthly, Quarterly and Yearly). The experiments demonstrate that, MLTF is significantly faster while being similar (or better) in terms of forecasting accuracy than the state-of-the-art DL methods and other non-parametric time series model.

Structural, mixing, electronic and magnetic properties of small Cu-Pd nanoalloy clusters

Bimetallic CumPdn nanoalloy clusters of small size (m+n ≤ 12) are systematically studied using the spin polarized density functional theory to understand the evolution of structural, mixing, electronic and magnetic properties with size and composition of the binary system. The lowest-energy configurations of the series of bimetallic clusters are determined from unbiased global search with genetic algorithm. With the increase of size, Cu-Pd clusters tend to adopt compact geometries. For a given cluster size, Pd atom prefers the outer position, while Cu atom favors the inner site. Stability analysis reveals that nanoalloy formation for CumPdn clusters is favored for the overall range of sizes and compositions. The small changes in structures of magic clusters with their neighboring compositions indicate that their high stability is primarily due to the variation in composition, not to the change in structure. The electronic state of the Pd atom is promoted upon the formation of the Cu-Pd nanoalloy clusters, while that of the Cu atom remains almost unchanged. The magnetic moments of CumPdn clusters exhibit an evident oscillation behavior with the composition, which can be attributed to the substantial hybridization between the electronic states of Pd and Cu.

Self-assembly of octanuclear Ln(III)-based clusters: their large magnetocaloric effects and highly efficient conversion of CO2.

The design and construction of high-nuclear lanthanide clusters with fascinating topology and functional properties have been an active area of research, however, the development of an effective approach for obtaining high-nuclear lanthanide clusters with multifunctional properties is still extremely difficult. Up to now, a systematic approach for guiding the further expansion of Ln(III)-based clusters showing good functional properties is lacking. Herein, we design and synthesize a polydentate Schiff base ligand (HL), which reacts with β-diketonate salts Ln(acac)3·2H2O, and a series of Ln8 clusters [Ln8(acac)6(L)2(μ3-O)6(μ2-C2H5O)4(μ2-Hacac)2]·2CH3CN (Ln(III) = Gd (1), Dy (2), and Ho (3); HL = pyridine-2-carboxylic acid (5-hydroxymethyl-furan-2-ylmethylene)-hydrazide, Hacac = acetylacetone) have been successfully synthesized. Single-crystal X-ray diffraction studies reveal that clusters 1-3 are isostructural and can be viewed as a Ln8 core bridged by eighteen μ2-O atoms, six μ3-O atoms and two μ4-O atoms. Magnetic studies show that cluster 1-Gd8 displays a large magnetocaloric effect with -ΔSm = 46.14 J kg-1 K-1 (T = 2.0 K and ΔH = 7.0 T); cluster 2-Dy8 exhibits single-molecule magnet behavior under zero-field conditions. It is worth mentioning that the -ΔSm of cluster 1-Gd8 is larger than that of most reported polynuclear Gd(III)-based clusters; the 2-Dy8 cluster is one of the rare polynuclear Lnn SMMs (n ≥ 8) under zero dc field. Importantly, these Ln(III)-based clusters (1-3) can catalyze the cycloaddition of CO2 with epoxides with high efficiency under mild conditions; and cluster 1-Gd8 as a catalyst could be reused at least three times without obvious loss of catalytic performance.

Trinuclear ReFePt clusters with a μ3-phenylvinylidene ligand: synthetic approaches, rearrangement of vinylidene, and redox-induced transformations.

A series of trinuclear μ3-vinylidene ReFePt clusters were synthesized by the application of two approaches: (i) reactions of the binuclear RePt μ-vinylidene complexes with Fe2(CO)9; (ii) ligand substitution or exchange reactions at the Pt atom in the synthesized ReFePt clusters. The molecular structures of CpReFePt(μ3-CCHPh)(CO)5[P(OEt)3]L [L = CO; P(OEt)3] were determined by an X-ray diffraction study. The obtained compounds were studied by IR and 1H, 13C and 31P NMR spectroscopy. The spectroscopic study revealed that the clusters CpReFePt(μ3-CCHPh)(CO)5[P(OEt)3]L [L = CO; P(OEt)3] and CpReFePt(μ3-CCHPh)(CO)6[P(OPri)3] undergo isomerization upon dissolution, resulting in three isomers with different positions of the μ3-vinylidene ligand over the ReFePt core. The redox properties of the clusters were studied by electrochemical methods. The relatively stable cation-radicals obtained by chemical oxidation of CpReFePt(μ3-CCHPh)(CO)6[P(OPri)3] and CpReFePt(μ3-CCHPh)(CO)5[P(OEt)3]2 with ferrocenium tetrafluoroborate were characterized by EPR spectroscopy.