Leucobryum is a moss genus that exhibits various bioactivities. However, the identification of Leucobryum species with morphology alone remains difficult. Nowadays, chemical profile analysis provides additional tools for plant classification, especially in medicinal plants. This method uses chemical similarities to identify the differences among some plants, especially for the different varieties of the same species. The objective of this study was to obtain the chemical profiles and use chemometrics to identify selected Leucobryum species found in Thailand. Lipophilic extracts from 18 samples of five taxa were analyzed with TLC and HPLC. Cluster analysis and PCA were used to investigate the similarities of the chemical profiles. PERMANOVA was performed to determine the difference among taxa. The results showed that the TLC profile could separate only the genus of the sample, while HPLC chromatograms showed separation among the Leucobryum taxa and consistent patterns within the same species. In addition, the chemical profiles of Leucobryum species were separated at the species level in PCA. The PERMANOVA showed significantly different profiles among the species (P = 0.002). Therefore, this work illustrated the potential of chemometrics as supporting evidence for species delimitation in the moss genus Leucobryum.

Physics of high-Tc superconducting cuprates is obscured by the effect of strong electronic correlations. One way to overcome the problem is to seek for an exact solution at least within the small cluster and expand it to the whole crystal. Such an approach is in the heart of the cluster perturbation theory (CPT). Here we develop CPT for the dynamic charge and spin susceptibilities (spin-CPT), within which the correlation effects are explicitly taken into account by the exact diagonalization. We apply spin-CPT to the effective two-band Hubbard model for the cuprates obtained from the three-band Emery model and calculate one- and two-particle correlation functions, namely, spectral function and spin and charge susceptibilities. Doping dependence of the spin susceptibility was studied within spin-CPT and CPT-RPA that is the CPT generalization of the random phase approximation (RPA). Both methods produce the low energy response at four incommensurate wave vectors in qualitative agreement to the results of the inelastic neutron scattering on overdoped cuprates.

Climate research shows that extreme weather events and their effects are increasing in frequency, severity, and impact. Extreme wind events can cause massive societal and economic damage. High wind occurrences and their causes must be identified because they are hard to define and understand. Extreme wind modeling affects wind power plant planning, installation, and building modeling. This applies to city, vegetation, and vegetational area modeling. The scientific literature utilizes statistical, dynamic (Weather Research and Forecasting-WRF), and machine learning methods to identify extreme wind speeds. This study explores the relationship between lower-level extreme wind speeds and upper-level parameters like Z500, and T850 based on cluster analysis. The aim is to explore the correlation between upper-level atmospheric dynamics and lower-level wind behavior. K-Means cluster analysis method was employed to classify Turkish regions with similar severe wind episodes. WRF model simulation findings from NEWA (New European Wind Atlas) project (2019) were used for that purpose. The NEWA project's wind speed data at 100m a.g.l. was used for cluster analysis. We simplify the process by grid point reduction and applying the top 2% percentile as threshold value. Self-Organized Maps (SOM) clustering was also applied using the upper-level variables.

This article examines the evolution of the most extensively researched subjects in E-mobility during the previous two decades. The objective of this analysis is to identify the lessons that the State of Kuwait, which is falling behind other nations in E-mobility, can absorb in its efforts to embrace adoptions of electric vehicles (EVs). To strengthen the body of knowledge and deter-mine the most effective and efficient route to an "EV-ready" nation, the authors compiled data on the latest developments in the EV industry. A bibliometric analysis was performed on 3,962 articles utilizing the VOSviewer software, which identified six noteworthy clusters that warranted further attention. Additionally, we examine the sequential progression of these clusters as follows: 1. The environmental ramifications of electric mobility; 2. Advancements in electric vehicle technology, including range extension and soundless engines; and capital (CAPEX) and operational (OPEX) expenditures of purchasing and operating EVs. 3. Concerns regarding effectiveness and durability of EV batteries, 4. Availability of EV charging stations and grid integration, 5. Charging time, and finally 6. Origin and source of the energy utilized in the development of e-mobility. We are of the opinion that by delineating the critical aspects of e-mobility development, policymakers and decision-makers in Kuwait will be better equipped to formulate timely and economical choices pertaining to sustainable transportation.

In recent years discrete element method (DEM) has gradually been applied to the traditional fluidization simulation of fine particles in micro fluidized bed (MFB). The application of DEM in simulating fast fluidization of fine particles in MFB has not yet received attention. This article presents a drag model that relies on the surrounding environment of particles, namely particle circumstance-dependent drag modle or PCDD model. Fast fluidization in MFB of fine particles is simulated using DEM based on the PCDD model. It is found that the gas-solid two-phase flow in MFB meets the common law of fast fluidization in circulating fluidized bed (CFB) to a certain extent, and also presents a special law that is significantly different from that in CFB. Simulations indicate that the local structure in MFB exhibits particle aggregation which is a natural property of fast fluidized, forming a structure where continuous dilute phase and dispersed concentrated phase coexist. The formation and fragmentation of particle clusters in different local regions of the bed have time synchronization. There exists strong effect of solid back-mixing in MFB, leading to relatively low outlet solid flux. The gas back-mixing effect is, however, not so distinct. The axial porosity shows a monotonically increasing distribution with the bed height, but does not strictly follow the single exponential distribution. The solid volume fraction at the bottom of the bed is significantly lower than the correlated value in CFB. The axial heterogeneous distribution of the cross-sectional average porosity in the lower half of the bed is also weakened. The radial porosity shows a distribution pattern of higher in the central region and lower in the sidewall region. Compared with the correlation results in CFB, the porosity near the central region in MFB is relatively low, while the porosity near the sidewall region is relatively high. The geometric size of the container, especially the radial size, is much smaller than that of a CFB. The relative area of contact between the MFB wall and particles is larger, and the wall friction factor becomes more significant. This may be the main reason for the time synchronization of particle agglomeration, severe particle back-mixing, low outlet solid flux, monotonically increasing axial porosity and weak core-annular structure of radial porosity.

Abstract: Hox gene clusters are crucial in Embryogenesis. It was observed that some Hox genes were located in order along the telomeric to centromeric direction of the DNA sequence: Hox1, Hox2, Hox3…. These genes were expressed in the same order in the ontogenetic units of the Drosophila embryo along the Anterior-Posterior axis. The two entities (genome and embryo) differ significantly in linear size and in-between distance. This strange phenomenon was named Spatial Collinearity (SP). Later, it was observed that, particularly in the Vertebrates, a Temporal Collinearity (TC) coexists: first is Hox1 expressed, later Hox2 and even later Hox3,…,. Hox clusters are irreversibly elongated along the force direction. According to a Biophysical Model (BM), pulling forces act at the anterior end of the cluster while a cluster fastening applies at the posterior end. During Evolution, the elongated Hox clusters are broken at variable lengths thus split clusters may be created. An Empirical Rule was formulated distinguishing development due to a complete Hox cluster from development due to split Hox clusters. BM can explain this Empirical Rule. In an accidental mutation where the cluster fastening is dismantled, a minimal pulling force can automatically shift the cluster inside the Hox activation domain. This cluster translocation can probably explain the absence of temporal collinearity in Drosophila.

This paper considers the problem of predicting earthquakes. It uses a small amount of information to create a descriptive key that can be used as a footprint to describe an event. A frequency grid clusters events that occurred at the same time and then the algorithm averages the history of these events over preceding days, in particular the gaps when the events did not occur. The gaps are measured for the clustered events only and can be used to create a description that is quite unique. Results suggest that seismic events can in fact be traced using this key and subsequently recognised again, if the same conditions reoccur. They also suggest that force direction may be more important than magnitude, after the initial cluster selections are made. Greek and USA datasets have been looked at and the prediction accuracy can be 70% or better. The author therefore suggests that this is an interesting method that deserves attention.

As urbanization has accelerated, China has started to build smart cities, which have formed smart city clusters. It is critical to coordinate development within smart city clusters to enhance the efficiency of city cluster construction. From the perspective of demographic economics, this study innovatively constructed an evaluation system for the coordinated development of smart city clusters and utilized the coupled coordination degree model to conduct an in-depth study of smart city clusters in Jiangsu Province. The results show that there are clear differences in the development between the three regions of Jiangsu Province: Southern Jiangsu, Central Jiangsu, and Northern Jiangsu. The development within Jiangsu Province is imbalanced, where the overall development trend is high in the southern region and low in the northern region. The main driving factors include geography, the Matthew effect, game thinking, and industrial structure. Accordingly, the results suggest the following recommendations for the coordinated development of smart city clusters: strengthening cross-regional cooperation, promoting data sharing and interoperability, deepening synergistic industrial development, and expanding innovation capacity.

Heptanuclear {GdIII7} (complex 1) and tetradecanuclear {GdIII14} (complex 2) have been synthesized using a Rhodamine 6G ligand HL (Rhodamine 6G salicylaldehyde hydrazone) and characterized. Complex 1 has a rare disc-shaped structure, where the central Gd ion was connected to the peripheral six GdIII ions via CH3O-/μ3-OH- bridges. Complex 2 has an unexpected three-layer double sandwich structure with a rare μ6-O2- ion in the center of the cluster. Magnetic studies revealed that complex 1 exhibits a magnetic entropy change of 17.4 J kg−1 K−1 at 3 K and 5 T. On the other hand, complex 2 shows a higher magnetic entropy change of 22.3 J kg−1 K−1 at 2 K and 5 T.

Abstract Background: Cluster randomized controlled trials are increasingly becoming popular in public health research interventions and health services research in primary health care design and use in low and middle-income countries. However, the majority of researchers in these trials did not account correctly for the effect of confounders and clustering in the design and analysis stages. Objectives: This article aimed to review the main implications of implementing a cluster randomized controlled trials design in public health research and emphasize the practical application of proper analytical methods and the performance of different statistical models. Methods: The practical application of various analytical methods is validated via the utilization of experimental data from a public health research case study. This article also demonstrated the performance of hierarchical models and made comparisons in terms of empirically precise effect size estimates. Results: Three hierarchical statistical models were provided with highly varied effect sizes during the analysis of the intervention effect on outcome, such as model 1 (AOR: 14.32; 95% CI: 3.75–54.68), model 2 (ARR: 3.52; 95% CI: 2.16–5.77), and model 3 (ARR: 4.79; 95% CI: 2.69–5.52).Conclusion: Inaccurate results and potentially misleading conclusions can arise from improper cluster randomized controlled trial designs and analyses. This article has shown that real-world data can be adjusted for the effects of confounders and clustering, and we advocate for the routine use of suitable design and analytical methods. This article concludes that researchers should be careful when selecting hierarchical models to analyze cluster randomized controlled trials.

A unified electro-gravity (UEG) theory, which has been successfully used for modeling an elementary particle, is applied in this paper to model gravitation in spiral galaxies. The new UEG model would explain the "flat rotation curves'' commonly observed in the spiral galaxies, without need for any hypothetical dark matter. The UEG theory is implemented in a somewhat different manner for a spiral galaxy, as compared to the simple application of the UEG theory to an elementary particle. This is because the spiral galaxy, unlike the elementary particle, is not spherically symmetric. The UEG constant $\gamma$, required in the new model to support the galaxies' flat rotation speeds, is estimated using measured data from a galaxy survey, as well as for a selected galaxy for illustration. The estimates are compared with the $\gamma$ derived from the UEG model of an elementary particle. The UEG model for the galaxy is shown to explain the empirical Tully-Fisher Relationship (TFR), is consistent with the Modified Newtonian Dynamics (MOND), and is also independently supported by measured trends of galaxy thickness with surface brightness and rotation speed. The UEG theory may similarly be extended to emulate the hypothetical dark matter in galaxy clusters as well as in cosmology.

This research paper examines the effects, advantages, challenges, and economic aspects of a research town. The study concludes that inclusion and diversity not only constitute fundamental values but also serve as crucial drivers of business success and sustained competitiveness. Universities play a central role in shaping the prosperity of the research town by functioning as knowledge hubs, fostering collaboration, nurturing talent, and contributing to the broader innovation ecosystem. The symbiotic relationship between universities and industries within the cluster establishes a dynamic and resilient environment for research and development. The presence of startups within the research cluster introduces novel ideas, enhancing the overall vibrancy and competitiveness of the local economy. In an era where social media algorithms increasingly influence people's choices, the potential for foreign interference emerges as a significant threat.

This paper proposes an active-reactive power collaborative scheduling model with cluster division for the flexible distributed energy resources (DERs) of smart building system to resolve the high complexity of centralized optimal scheduling of massive dispersed DERs in the distribution network. Specifically, the optimization objective of each cluster is to minimize the operational cost, the power loss cost, and penalty cost for the flexibility deficiency, and the second-order cone-based branch flow method is utilized to convert the power flow equations into the linearized cone constraints, reducing the nonlinearity and heavy computation burden of the scheduling model. Customized virtual battery models for the building-integrated flexible DERs are developed to aggregate the power characteristics of flexible resources while quantifying their regulation capacities with time-shifting power and energy boundaries. Moreover, a cluster division algorithm considering the module degree index based on the electrical distance and flexible balance contribution index is formulated for cluster division to achieve the information exchange and energy interaction in the distribution network with high proportion of building-integrated flexible DERs. Comparative studies have demonstrated the superior performance of the proposed methodology on the economic merits and voltage regulation.

Aiming at the problem of UAV cluster configuration reconstruction, in order to obtain the cluster reconstruction method, the theory and simulation of cluster reconstruction control strategy is studied by simplifying the model，deducing the theoretical formula and analyzing the example. Taking 10 UAVs cluster as an example, the distribution of UAVs in different configurations was analyzed. According to the change of cluster configuration, the principle of formation reconstruction and the execution ability of configuration, the cluster capability was analyzed. The group behavior is modeled by group behavior rules, reconfiguration topology analysis and reconfiguration cost measurement. Based on the cluster parameters and configuration characteristics, simulation experiments were carried out to obtain the change curve of the reconstruction cost and time and the trajectory movement diagram of the UAV in different configurations.

Iberian ham, a traditional Spanish meat product, is renowned for its unique nutritional and sensory attributes, garnering widespread appreciation both domestically and internationally [1]. It is one of the most outstanding Spanish gastronomic treasures, with very special nutritional and sensory properties that make it highly appreciated throughout the world [2]. Recent trends indicate a notable surge in its consumption, a pattern projected to persist [3]. For an enhanced online shopping experience, understanding the specific characteristics and requirements of various consumer segments is crucial. This study aims to scrutinize national Iberian ham consumption patterns and, through survey methodologies, discern the preferences and needs of online consumers purchasing whole Iberian hams. The subsequent cluster analysis will empower suppliers with insights to pinpoint business prospects and craft segment-specific online marketing strategies.

A mixture of nonlabeled (14N2H4) and 15N labeled hydrazine (15N2H4) in an aqueous solution is oxidized to 15N2, 14N2, and 14N15N molecules, indicating the intermediate existence of the 14NH2-14NH-15NH-15NH2 with subsequent hydrogen transfers and splitting of side N-N bonds. Structures, thermodynamics, and electron characteristics of various N4H6 molecules in aqueous solutions are investigated using theoretical treatment at the CCSD/cc-pVTZ level of theory to explain the crucial part of the hydrazine oxidation reaction. Most N4H6 structures in aqueous solutions are decomposed during geometry optimization. Splitting the bond between central nitrogen atoms is the most frequent, but the breakaway of the side nitrogen is energetically the most preferred. The N-N fissions are enabled by suitable hydrogen rearrangements. Gibbs free energy data indicate the dominant abundance of NH3... N2... NH3 species. The side N atoms have very high negative charges, which should support hydrogen transfers in aqueous solutions. The only stable cyclo-(NH)4…H2 structure has a too high Gibbs energy and breaks the H2 molecule. The remaining initial cyclic structures are split into hydrazine and HN≡NH or H2N≡N species, and their relative abundance in aqueous solutions is vanishing.

Since China’s economic reform launched in the late 1970s, rural industrial parks (RIPs) have played a crucial role in the rise of the manufacturing industry in the Pearl River Delta (PRD), transforming the former agricultural land into a location of world-famous factories. However, as China has put forward higher requirements for economic development and stricter control measures for environmental pollution, RIPs with low-end industries and low efficiency present an urgent need for renovation and upgrade. By analyzing the spatial and socioeconomic cross-sectional dataset of rural industrial parks in Nanhai District of Foshan City, this paper attempts to classify the existing industrial parks into groups and propose corresponding redevelopment strategies. The results of the spatial analysis show that the spatial distribution of rural industrial parks is closely related to their location and transportation conditions. Failure of the market has resulted in large tracts of advantageous land being taken up by inefficient industrial parks. Cluster analysis and overlay analysis are used evaluate the difficulty of redevelopment and divide the industrial parks into three clusters: retained RIPs, medium-term-removed RIPs, and near-term-removed RIPs. It is shown that some of the industrial parks are still in good form while the majority need substantial reconstruction. Taking economic and institutional factors into consideration, the authors put forward that different strategies should be adopted for the future renovation of medium-term-removed and near-term-removed RIPs.

This study introduces a compact Raman spectrometer with a 1064 nm excitation laser coupled with a fiber probe and an inexpensive motorized stage, offering a promising alternative to widely used Raman imaging instruments with 785 nm excitation lasers. The benefits of 1064 nm excitation for biomedical applications include further suppression of fluorescence background and deeper tissue penetration. The performance of the 1064 nm instrument in detecting cancer in human bladder resectates is demonstrated. Raman images with 1064 nm excitation were collected ex vivo from 10 human tumor and non-tumor bladder specimens and the results are compared to previously published Raman images with 785 nm excitation. K-Means cluster (KMC) analysis is used after pre-processing to identify Raman signatures of control, tumor, necrosis, and lipid-rich tissues. Hierarchical cluster analysis (HCA) groups the KMC centroids of all specimens as input. The tools for data processing and hyperspectral analysis were compiled in an open source Python library called SpectraMap (SpMap). In conclusion, the 1064 nm Raman system can differentiate between tumor and non-tumor bladder tissues in a similar way to 785 nm Raman spectroscopy. These findings hold promise for future clinical hyperspectral imaging.

China's economic development has shifted from high speed to high quality. This study constructs an evaluation index for China’s high-quality development utilizing a new development concept. The entropy method and cluster analysis were used to assess the level of high-quality development in China between 2015 and 2021. Kernel density estimation method was employed to explore spatiotemporal dynamics. The results reveal significant differences in the level of economic development among provinces in China; the eastern region is significantly better than the central, northeastern, and western regions. From the perspective of the sub-item evaluation, challenges with uneven, uncoordinated, and insufficient economic development exist in various Chinese provinces.

The NOSTR is a communication protocol for the social web, based on the w3c websockets standard. Although it is still in its infancy, it is well known as a social media protocol, thousands of trusted users and multiple user interfaces, offering a unique experience and enormous capabilities. To name a few, the NOSTR applications include but are not limited to direct messaging, file sharing, audio/video streaming, collaborative writing, blogging and data processing through distributed AI directories. In this work, we propose an approach that builds upon the existing protocol structure with end goal a decentralized marketplace for federated learning and LLM training. In this proposed design there are two parties: on one side there are customers who provide a dataset that they want to use for training an AI model. On the other side, there are service providers, who receive (parts of) the dataset, train the AI model, and for a payment as an exchange, they return the optimized AI model. The decentralized and censorship resistant features of the NOSTR enable the possibility of designing a fair and open marketplace for training AI models and LLMs.

To achieve n-type doping in diamond, extensive investigations employing first principles have been conducted on various models of phosphorus doping and boron-phosphorus co-doping. The primary focus of this study is to comprehensively analyze the formation energy, band structure, density of states, and ionization energy of these structures. It is observed that within a diamond structure solely composed of phosphorus atoms, the formation energy of an individual carbon atom is excessively high. However, the substitution of two carbon atoms leads to the conversion of diamond into a p-type semiconductor. Upon examining the P-B co-doping structure, it is revealed that the doped impurities exhibit a tendency to form more stable cluster configurations. As the separation between the freely doped atoms and the cluster impurity structure increases, the overall stability of the structure diminishes, consequently resulting in an elevation of the ionization energy. Analysis of the electronic density of states demonstrates that the electron orbit of the B atom makes negligible contributions to the impurity levels during P-B doping.