Spatial Distribution Pattern and Influencing Factors of Bed-and-breakfasts(B&Bs)from the Perspective of Urban-rural Differences:A Case Study of Jiaodong Peninsula,China

There are significant differences between urban and rural bed-and-breakfasts(B&Bs)in terms of customer positioning,economic strength and spatial carrier.Accurately identifying the differences in spatial characteristics and influencing factors of each type,is essential for creating urban and rural B&B agglomeration areas.This study used density-based spatial clustering of applications with noise(DBSCAN)and the multi-scale geographically weighted regression(MGWR)model to explore similarities and differences in the spatial distribution patterns and influencing factors for urban and rural B&Bs on the Jiaodong Peninsula of China from 2010 to 2022.The results showed that:1)both urban and rural B&Bs in Jiaodong Peninsula went through three stages:a slow start from 2010 to 2015,rapid development from 2015 to 2019,and hindered development from 2019 to 2022.However,urban B&Bs demonstrated a higher development speed and agglomeration intensity,leading to an increasingly evident trend of uneven development between the two sectors.2)The clustering scale of both urban and rural B&Bs continued to expand in terms of quantity and volume.Urban B&B clusters characterized by a limited number,but a higher likelihood of transitioning from low-level to high-level clusters.While the number of rural B&B clusters steadily increased over time,their clustering scale was comparatively lower than that of urban B&Bs,and they lacked the presence of high-level clustering.3)In terms of development direction,urban B&B clusters exhibited a relatively stable pattern and evolved into high-level clustering centers within the main urban areas.Conversely,rural B&Bs exhibited a more pronounced spatial diffusion effect,with clusters showing a trend of multi-center development along the coastline.4)Transport emerged as a common influencing factor for both urban and rural B&Bs,with the density of road network having the strongest explanatory power for their spatial distribution.In terms of differences,population agglomeration had a positive impact on the distribution of urban B&Bs and a negative effect on the distribution of rural B&Bs.Rural B&Bs clustering was more influenced by tourism resources compared with urban B&Bs,but increasing tourist stay duration remains an urgent issue to be addressed.The findings of this study could provide a more precise basis for government planning and management of urban and rural B&B agglomeration areas.

Spatial correlation-based characterization of acoustic emission signal-cloud in a granite sample by a cube clustering approach

To extract more in-depth information of acoustic emission(AE)signal-cloud in rock failure under triaxial compression,the spatial correlation of scattering AE events in a granite sample is effectively described by the cube-cluster model.First,the complete connection of the fracture network is regarded as a critical state.Then,according to the Hoshen-Kopelman(HK)algorithm,the real-time estimation of fracture con-nection is effectively made and a dichotomy between cube size and pore fraction is suggested to solve such a challenge of the one-to-one match between complete connection and cluster size.After,the 3D cube clusters are decomposed into orthogonal layer clusters,which are then transformed into the ellip-soid models.Correspondingly,the anisotropy evolution of fracture network could be visualized by three orthogonal ellipsoids and quantitatively described by aspect ratio.Besides,the other three quantities of centroid axis length,porosity,and fracture angle are analyzed to evaluate the evolution of cube cluster.The result shows the sample dilatancy is strongly correlated to four quantities of aspect ratio,centroid axis length,and porosity as well as fracture angle.Besides,the cube cluster model shows a potential pos-sibility to predict the evolution of fracture angle.So,the cube cluster model provides an in-depth view of spatial correlation to describe the AE signal-cloud.

An Iterative Clustering-Based Localization Algorithm for Wireless Sensor Networks

In wireless sensor networks,node localization is a fundamental middleware service.In this paper,a robust and accurate localization algorithm is proposed,which uses a novel iterative clustering model to obtain the most representative intersection points between every two circles and use them to estimate the position of unknown nodes.Simulation results demonstrate that the proposed algorithm outperforms other localization schemes (such as Min-Max,etc.) in accuracy,scalability and gross error tolerance.

Study on electronic density topology of various cluster models of Mg/Al hydrotalcite by density functional theory

The geometry and electronic topology properties of Mg/Al hydrotalcite cluster models were comparatively investigated by means of density functional theory at GGA/DND levels.The results suggested that cluster model containing seven octahedral cations was the smallest size to be employed to simulate other properties.The fact that the n＋ charge of cluster models containing n aluminum atoms can reflect electronic properties of anionic clay layer sheet.The bond lengths of clusters can be modified by terminating with or without OH-/H2O groups in terms of principle of bond order conservation.

C-Nanostructures Cluster Models in Organic Solvents： Fullerenes, Tubes, Buds and Graphenes

The existence of nanographene in cluster form is discussed in organic solvents. Theories are developed based on the columnlet, bundlet and droplet models describing the size-distribution functions. Phenomena present a unified explanation in the columnlet model in which free energy of Cgraphene involved in cluster is combined from a volume part proportional to the number of molecules n in cluster and a constant. The columnlet model enables describing distribution function of Cgraphene clusters by size. From purely geometrical considerations the columnlet （Cgraphene）, bundlet （single-wall carbon nanotube）, CNT （carbon nanotube）, SWNT （single-wall C-nanotube）, and carbon nanobud, CNB （carbon nanobud）） and droplet （fullerene） models predict dissimilar behaviours. The interaction-energy parameters of Cgraphene are taken from C60. An CNB behaviour or further is expected. The decay of solubility with rising temperature is smaller for Cgraphene than for SWNT and CNB and, furthermore, than for C60, in agreement with lesser numbers of units in Cgraphene clusters. The discrepancy between the experimental data of the heat of solution of fullerenes, CNTs, CNBs and graphenes is ascribed to the sharp concentration dependence of the heat of solution. The diffusion coefficient drops with temperature result greater for Cgraphene than CNB and SWNT than C60 corresponding to lesser number of units in clusters. The aggregates near （C60）13, SWNT/CNB7 and （Cgraphene）3 could be representative of the droplet, bundlet and columnlet models.

Selecting the Quantity of Models in Mixture Regression

Mixture regression is a regression problem with mixed data. Specifically, in the observations, some data are from one model, while others from other models. Only after assuming the quantity of the model is given, EM or other algorithms can be used to solve this problem. We propose an information criterion for mixture regression model in this paper. Compared to ordinary information citizen by data simulations, results show our citizen has better performance on choosing the correct quantity of models.

A bibliometric analysis of research on nursing models in countries other than China

Objectives＂ To deepen our understanding of the status quo and to identify the hot topics and develop- mental trends of research on nursing models in countries other than China in the most recent decade. Methods： The study subjects were the publications retrieved from the PubMed database using the MeSH terms of ＂Models, Nursing＂. Bibliographic item co-occurrence mining system （BICOMS） software was used for conventional bibliometric analysis of publications during two time periods, 2005-2009 and 2010-2014. The number of published journal articles, journal distribution, authors of publications, country of origin of journals, and language of publications were analyzed to establish a high-frequency keyword profile and co-occurrence matrix. Graphical clustering toolkit （gCLUTO） software was applied for two-way clustering analysis and visualized analysis. Results： A total of 1472 journal articles with a key theme of nursing models were retrieved for final analysis, including 771 published during 2005-2009 and 701 during 2010-2014. The bibliometric analysis revealed that publications other than China concerning nursing models were mostly concentrated in the United States and the United Kingdom and that the number of relevant publications has been continuously decreasing. The two-way clustering analysis showed that there were mainly four types of research themes in the relevant publications in countries other than China during 2005-2009, i.e., nursing education and theoretical research, clinical nursing and psychological care, nursing administration, and models of nursing education, whereas there were five types during 2010-2014, i.e., nursing theories and clinical nursing practice, nursing administration models and assessments of nurses＇ knowledge and skills, community nursing administration models, nursing human resource management, and nursing education models and approaches. Conclusions： Research on nursing models in countries other than China is relatively mature and stable with a broader view, but it has shown a declining trend in recent years. It emphasizes both theory and practice, with research content tending to be structured into four modules, i.e., nursing education, administration, clinical practice, and theoretical research. Community nursing models may become a key research direction in the international research on nursing models in the future.

Maternal and Child Health Care Quality Assessment: An Improved Approach Using K-Means Clustering

High maternal and child deaths in developing countries are frequently linked to poor health services provided to pregnant women and children. To improve the quality of maternal, neonatal and child health (MNCH) services, the government and other stakeholders in MNCH emphasize the importance of quality assessment. However, effective quality assessment approaches are mostly lacking in most developing countries, particularly in Tanzania. This study, therefore, aimed at developing a quality assessment approach that can effectively assess and report on the quality of MNCH services. Due to the need for a good quality assessment approach that suits a resource-constrained environment, machine learning-based approach was proposed and developed. K-means algorithm was used to develop a clustering model that groups MNCH data and performs cluster summarization to discover the knowledge portrayed in each group on the quality of MNCH services. Results confirmed the clustering model’s ability to assign the data points into appropriate clusters;cluster analysis with the collaboration of MNCH experts successfully discovered insights on the quality of services portrayed by each group.

Subspace Distribution Clustering HMM for Chinese Digit Speech Recognition

As a kind of statistical method, the technique of Hidden Markov Model （HMM） is widely used for speech recognition. In order to train the HMM to be more effective with much less amount of data, the Subspace Distribution Clustering Hidden Markov Model （SDCHMM）, derived from the Continuous Density Hidden Markov Model （CDHMM）, is introduced. With parameter tying, a new method to train SDCHMMs is described. Compared with the conventional training method, an SDCHMM recognizer trained by means of the new method achieves higher accuracy and speed. Experiment results show that the SDCHMM recognizer outperforms the CDHMM recognizer on speech recognition of Chinese digits.

Macro and micro mechanics behavior of granite after heat treatment by cluster model in particle flow code

In this paper, a cluster model in particle flow code was used to simulate granite specimens after heat treatment under uniaxial compression. The results demonstrated that micro-cracks are randomly distributed in the specimen when the temperature is below 300?C, and have partial coalescence when the temperature is up to 450?C, then form macro-cracks when the temperature is above 600?C. There is more inter-granular cracking than intra-granular cracking, and their ratio increases with increasing temperature.The micro-cracks are almost constant when the temperature decreases from 900?C to room temperature, except for quartz α–β phase transition temperature(573?C). The fracture evolution process is obviously affected by these cracks, especially at 600–900?C. Elevated temperature leads to easily developed displacement between the grains, and the capacity to store strain energy becomes weaker, corresponding to the plasticity of granite after heat treatment.

Sr-doping effects on La_2O_3 catalyst for oxidative coupling of methane

Density‐functional theory calculations were carried out to study the strontium(Sr)‐doping effect on methane activation over a lanthanum‐oxide(La2O3)catalyst for the oxidative coupling of methane(OCM)using the cluster model.Eight Sr‐doped La2O3cluster models were built from pure La2O3clusters that were used previously to model the La2O3catalyst.These form two distinct categories,namely,those without a radical character(LaSrO2(OH),La2SrO4,La3SrO5(OH),and La5SrO8(OH))and those with a radical character(LaSrO3,La2SrO4(OH),La3SrO6,and La5SrO9).The potential‐energy surface for CH4activation to form a CH3radical at different Sr-O and La-O pair sites on these Sr‐doped La2O3clusters was calculated to study the Sr‐doping effect on the OCM catalytic activity.CH4physisorption and chemisorption energies,and activation barriers,and CH3desorption energies were predicted.Compared with the pure La2O3clusters,in general,the Sr‐doped La2O3clusters are thermodynamically and kinetically more reactive with CH4.For the Sr‐doped La2O3clusters without the radical character,the Sr-O pair site is more reactive with CH4than the La-O pair site,although a direct release of the CH3radical is also highly endothermic as in the case of the pure La2O3clusters.In contrast,for the Sr‐doped La2O3clusters with a radical character,the activation of CH4at the oxygen radical site and the release of the CH3radical are much easier.Thus,our calculations suggest that the Sr dopant prompts the OCM catalytic activity of the La2O3catalyst by providing a highly active oxygen‐radical site and by strengthening the basicity of the M-O pair site,which leads to lower CH4activation energies and lower CH3desorption energies.

Theoretical study of NO adsorbed on the surface of TiO2（110） cluster model

The chemisorption properties of N^18O adsorption on TiO2(110) surface were investigated by experimental and theoretical methods. The results of temperature programmed desorption (TPD) indicated that the temperatures of the three desorption peaks of the main N2 molecules were at (low) temperature of 230 K, 450 K, and (high) temperature of 980 K. This meant that N^18O decomposed and recombined during the process of N2 desorption after N^18O was exposed. Analysis of thestable combination and orbital theory calculation of the surface reaction of NO adsorption on the TiO2(110) cluster modelshowed that there was clear preference for the Ti-NO orientation.

Theoretical estimation of sonochemical yield in bubble cluster in acoustic field

In order to learn more about the physical phenomena occurring in cloud cavitation,the nonlinear dynamics of a spherical cluster of cavitation bubbles and cavitation bubbles in cluster in an acoustic field excited by a square pressure wave are numerically investigated by considering viscosity,surface tension,and the weak compressibility of the liquid.The theoretical prediction of the yield of oxidants produced inside bubbles during the strong collapse stage of cavitation bubbles is also investigated.The effects of acoustic frequency,acoustic pressure amplitude,and the number of bubbles in cluster on bubble temperature and the quantity of oxidants produced inside bubbles are analyzed.The results show that the change of acoustic frequency,acoustic pressure amplitude,and the number of bubbles in cluster have an effect not only on temperature and the quantity of oxidants inside the bubble,but also on the degradation types of pollutants,which provides a guidance in improving the sonochemical degradation of organic pollutants.

Density Functional Investigation of Methanethiol and Dimethyl Sulfide Adsorption on Zeolite

The density functional theory and cluster model methods have been employed to investigate the interactions between methanethiol, dimethyl sulfide and zeolites. The molecular complexes formed by adsorption of methanethiol or dimethyl sulfide on silanol H3SiOSi（OH）2OSiH3 with five coordination forms or four coordination forms, and complexes formed by interactions of BrSnsted acid sites of bridging hydroxyl H3Si（OH）AI（OH）2OSiH3 with methanethiol or dimethyl sulfide have been investigated. Full optimization and frequency analysis of all cluster models have been carried out using the B3LYP hybrid method at 6-31＋G （d,p） basis set level for hydrogen, silicon, aluminum, oxygen, carbon, and sulfur atoms. The structures and energy changes of different coordination forms between methanethiol and H3Si（OH）Al（OH）2OSiH3, dimethyl sulfide and H3Si（OH）Al（OH）2OSiH3, methanethiol and H3SiOSi（OH）2OSiH3, dimethyl sulfide and H3SiOSi（OH）2OSiH3 complexes have been comparatively studied. The calculated results showed the nature of interactions that led to the formation of all complexes was van der Waals force confirmed by an insignificant change of geometric structures and properties. The conclusions that methanethiol and dimethyl sulfide molecules were adsorbed on bridging hydroxyl group prior to silanol group were obtained on the basis of adsorption heat, the most stable adsorption models of a 6 ring structure for interaction between bridging hydroxyl and methanethiol, and a 7 ring structure for interaction between bridging hydroxyl and dimethyl sulfide.

Influence of Spin-Orbit Force on Nucleon-Nucleon Scattering in the Quark Delocalization Colour Screening Model

The symmetric spin-orbit interactions of one-gluon-exchange and confinement are included in the nucleon-nucleon phase shift calculation in the framework of quark delocalization eolour screening model. The spin-orbit interaction has little influence on D wave phase shift. For the triplet P waves, aPT is in good agreement with the experimental data and 3pLs is attractive but not strong enough, whereas 3 Pc is too strongly repulsive. Our results indicate that the symmetric spin-orbit interaction of one-gluon-exchange and confinement potential cannot give a good description of the triplet P wave phase shifts. More sophisticated considerations, the delocalization depending on the relative orientation between two cluster, might be needed to improve the description of P-wave NN interaction.

Cluster modeling of the short-range correlation of acoustically emitted scattering signals

As a widely used measurement technique in rock mechanics,spatial correlation modeling of acoustic emission(AE)scattering signals is attracting increasing focus for describing mechanical behavior quantitatively.Unlike the statistical description of the spatial distribution of randomly generated AE signals,spatial correlation modeling is based mainly on short-range correlation considering the interrelationship of adjacent signals.As a new idea from percolation models,the covering strategy is used to build the most representative cube cluster,which corresponds to the critical scale at peak stress.Its modeling process of critical cube cluster depends strongly on the full connection of the main fracture network,and the corresponding cube for coverage is termed the critical cube.The criticality pertains to not only the transition of local-to-whole connection of the fracture network but also the increasing-to-decreasing transition of the deviatoric stress with an obvious stress drop in the brittle failure of granite.Determining a reasonable critical cube guarantees the best observation scale for investigating the failure process.Besides,the topological connection induces the geometric criticality of three descriptors,namely anisotropy,pore fraction,and specific surface area,which are evaluated separately and effectively.The results show that cluster modeling based on the critical cube is effective and has criticality in both topology and geometry,as well as the triaxial behavior.Furthermore,the critical cube length presents a high confidence probability of being correlated to the mineral particle size.Besides,its pore fraction of cube cluster is influenced strongly by the critical cube length and confining pressure.

Gound State Properties of Nuclei in ^(295)118 α-Decay Chain

The properties of nuclei belonging to the α-decay chain of superheavy element ^295118 have been studied in the framework of axially deformed relativistic mean field （RMF） theory with the parameter set of NL-Z2 in the blocked BCS approximation. Some ground state properties such as binding energies, deformations, and α-decay energies Qα have been obtained and agree well with those from finite-range droplet model （FRDM）. The single-particle spectra of nuclei in ^295118 α-decay chain show that the shell gaps present obviously nucleon number dependence. The root-mean-square （rms） radii of proton, neutron and matter distributions change slowly from ^283112 to ^295118 but dramatically from ^279110 to ^283112, which may be due to the subshell closure at Z = 110 in ^279110. The α-decay half-lives in 295118 decay chain are evaluated by employing the cluster model and the generalized liquid drop model （GLDM）, and the overall agreement is found when they are compared with the known experimental data. The α-decay lifetimes obtained from the cluster model are slightly larger than those of GLDM ones. Finally, we predict the α-decay half-lives of Z=118, 116, 114, 112 isotopes using the cluster model and GLDM, which also indicate these two models can corroborate each other in studies on superheavy nuclei. The results from GLDM are always lower than those obtained from the cluster model.

Catalytic activity of phosphorus and steam modified HZSM-5 and the theoretical selection of phosphorus grafting model

The modification of HZSM-5 zeolite with phosphorus and steam has been studied. Results show that 1% phosphorus and steam modified HZSM-5 has the highest catalytic activity for n-heptane. Physicochemical and catalytic properties of 1% phosphorus and steam modified HZSM-5 zeolites have been investigated. The X-ray diffraction （XRD） results exhibit that there is considerable variation in the relative intensity of the individual diffraction peaks. The acidity of the samples decreases with an increase in the steaming temperature, which is determined by the IR of adsorbed pyridine and temperature programmed desorption （TPD） of ammonia. The oxidation state of phosphorus shown by XPS is ＋5, and a model for surface structure modification is proposed. The nitrogen adsorption isotherm for all samples is a combination of type I and type IV, all hysteresis loops resemble the H4-type. The density functional and cluster model methods have been invoked to select the phosphorus grafting model, and it was found that the phosphorus grafting model were more probable in the form of the terminal oxygen coordinating with aluminum.

A DFT Study for NH_3 Adsorption on the GaN (0001) Surface

The ammonia adsorption on the GaN (0001) surface has been investigated by using DFT/B3LYP method combined with the cluster model approach. The dissociative adsorp- tion of NH2 and H is found thermodynamically favored relative to the molecular NH3 adsorption by decreasing the total energy of 0.95 eV. The adsorption geometries of the molecular and dis- sociative NH3 are given in detail, among which the molecular NH3 bonds to the surface Ga with its lone electronic pair, and the N atom of NH2 adspecies forms the four-fold coordinated N by bridging two surface Ga atoms.

A Novel Unsupervised Change Detection Method with Structure Consistency and GFLICM Based on UAV Images

With the rapid development of Unmanned Aerial Vehicle(UAV)technology,change detection methods based on UAV images have been extensively studied.However,the imaging of UAV sensors is susceptible to environmental interference,which leads to great differences of same object between UAV images.Overcoming the discrepancy difference between UAV images is crucial to improving the accuracy of change detection.To address this issue,a novel unsupervised change detection method based on structural consistency and the Generalized Fuzzy Local Information C-means Clustering Model(GFLICM)was proposed in this study.Within this method,the establishment of a graph-based structural consistency measure allowed for the detection of change information by comparing structure similarity between UAV images.The local variation coefficient was introduced and a new fuzzy factor was reconstructed,after which the GFLICM algorithm was used to analyze difference images.Finally,change detection results were analyzed qualitatively and quantitatively.To measure the feasibility and robustness of the proposed method,experiments were conducted using two data sets from the cities of Yangzhou and Nanjing.The experimental results show that the proposed method can improve the overall accuracy of change detection and reduce the false alarm rate when compared with other state-of-the-art change detection methods.