Cluster Model Research Articles

Improving Medication Safety Through Medication Reconciliation in Pediatric Neurology: Clinical Pharmacist Recommendations and Physician Uptake in a 13-Week Study

Background/Objectives: Clinical pharmacy plays a crucial role in optimizing medication use, particularly in pediatric settings where drug therapy can be complex and understudied. This study aims to assess the impact of clinical pharmacists in the Pediatric Neurology and Neurophysiology Unit of the Padova University Hospital, focusing on physician acceptance of pharmacist suggestions and the types of advice most frequently followed. Methods: A retrospective observational study was conducted over 13 weeks to describe the implementation phase of clinical pharmacists’ involvement in medication reconciliation in this setting. The study consisted of three steps. The study utilized a cluster model to categorize pharmacist suggestions and to evaluate physician acceptance rates. Results: The study included 57 hospitalized pediatric patients (53% male) with a median age of 3 years (IQR: 1–10.25). A total of 138 recommendations were shared, with an overall acceptance rate of 42%. Medication errors accounted for the largest cluster of suggestions (45%), though only 32% were accepted. Among the most frequently shared categories of suggestions, pharmaceutical form optimization (A) and drug supply (E) exhibited higher acceptance rates by clinicians (64% and 42%, respectively). The acceptance rate increased over time, peaking at 100% during weeks 7 and 11, correlating positively with enhanced collaboration between pharmacists and clinicians (R2 = 0.59). Conclusions: This study highlights the importance of clinical pharmacists in pediatric care, particularly in improving medication management through targeted interventions. The findings suggest that integrating clinical pharmacists into multidisciplinary teams can enhance patient care quality by fostering collaboration and trust among healthcare professionals.

The Coordination of Lanthanide Atoms with Stone–Wales Defects on Graphene: A Cluster DFT Analysis Using ECP Pseudopotentials

The main goal of the present study was to verify in detail whether the use of a cluster model for Stone–Wales (SW) defect-containing graphene (SWG) to study the adsorption of Ln atoms yields results similar to those previously obtained by employing a periodic model. We addressed this question by analyzing the optimized geometries of SWG + Ln complexes, their formation energies, and selected electronic parameters (in particular, the frontier orbital energies and atomic charges and spins). Within the frame of density functional theory, we used the computational methodology of the PBE-D2/DNP theoretical level using ECP pseudopotentials. The most important conclusion is that the use of a cluster model gives qualitatively similar results to those of the periodic model. While the corresponding plots of the dihedral angles θ versus the Ln atoms differ considerably, the two models have many common features in the trends of the bonding strength despite the use of two very different theoretical tools, namely periodic (plane waves) versus cluster calculations (localized basis sets). In comparing the results for SW defect-free and SW defect-containing cluster models, it is evident that SW defects serve as much more preferential adsorption sites compared to the conditions in the defect-free graphene model.

Fully Oxidized State of the Oxygen-Tolerant [NiFe] Hydrogenase from Hydrogenophilus thermoluteolus SH: A Quantum Mechanics Cluster and Quantum Mechanics/Molecular Mechanics Study.

The oxygen tolerance of some [NiFe] hydrogenase enzymes is crucial for designing efficient bioinspired catalysts for sustainable hydrogen production and advancing renewable energy technologies. To investigate this, we employed a quantum mechanical (QM) cluster model and quantum mechanics/molecular mechanics (QM/MM) calculations to study the fully oxidized state of the [NiFe]-hydrogenase from Hydrogenophilus thermoluteolus SH. Our analysis focused on the structural and electronic properties of the enzyme's active site across different spin states, including closed-shell singlet (CS, S = 0), high-spin triplet (HS, S = 1), and open-shell singlet broken symmetry (BS, S = 0). Using a comprehensive structural model (>300 atoms), we identified the ground state of the fully oxidized enzyme state to be a spin-coupled BS Ni(III)Fe(III) oxidation state, where residues beyond the first coordination sphere primarily contribute sterically. Notably, natural bond order calculations revealed an unusual three-center two-electron bond at the active site, which may enhance the open-shell ground state stability and the enzyme's resilience under oxidative conditions. Our comparative study of QM and QM/MM methods provides insights into their performance, facilitating and guiding the choice of suitable enzyme models when studying other metalloproteins.

Efficient density functional tight-binding parameterization for accurate modeling of platinum clusters

Efficient density functional tight-binding parameterization for accurate modeling of platinum clusters

Nuclear α-cluster structures from valence-space microscopic cluster model

Nuclear α-cluster structures from valence-space microscopic cluster model

Customer Segmentation Using K-Means Clustering with RFM Method (Case Study : PT. Dewangga Travindo Semarang)

PT. Dewangga Travindo is a company that operates in the field of travel services which includes tours, travel, and Hajj and Umrah pilgrimages which is based in the city of Semarang and has received permission from the Ministry of Religion No. D/606 of 2013. Every year there is always an increase in sales of services. Hajj and Umrah. The higher transaction activity every day results in a large buildup of data in the database which will only become data waste. The ability to process data is increasingly sophisticated using data mining, which is an activity of looking for relationships between items to obtain patterns as information to assist in decision making. However, considering the large number of competitors offering the same services, it is necessary to increase competitiveness to overcome market segmentation at PT Dewangga Travindo. For this reason, this research was carried out which aims to overcome customer segmentation using the Clustering method with the K-Means algorithm which produces a visual cluster model with RStudio tools using RFM attributes applied to carry out segmentation. The data used in this research is data on Hajj and Umrah pilgrims in the 2018-2020 period.

Cluster Based Heterogeneous Federated Foundation Model Adaptation and Fine-Tuning

In recent years, the distributed training of foundation models (FMs) has seen a surge in popularity. In particular, federated learning enables collaborative model training among edge clients while safeguarding the privacy of their data. However, federated training of FMs across resource-constrained and highly heterogeneous edge devices encounter several challenges. These include the difficulty of deploying FMs on clients with limited computational resources and the high computation and communication costs associated with fine-tuning and collaborative training. To address these challenges, we propose FedCKMS, a Cluster-Aware Framework with Knowledge-Aware Model Search. Specifically, FedCKMS incorporates three key components. The first component is multi-factor heterogeneity-aware clustering, which groups clients based on both data distribution and resource limitations and selects an appropriate model for each cluster. The second component is knowledge-aware model architecture search, which enables each client to identify the optimal sub-model from the cluster model, facilitating adaptive deployment that accommodates highly heterogeneous computational resources across clients. The final component is cluster-aware knowledge transfer, which facilitates knowledge sharing between clusters and the server, addressing model heterogeneity, and reducing communication overhead. Extensive experiments demonstrate that FedCKMS outperforms state-of-the-art baselines by 3-10% in accuracy.

Study on Landscape Cluster Model and Continuous Conservation of Traditional Villages in Southeast Chongqing

Southeast Chongqing is one of the most concentrated areas of traditional villages in China, and its rich and diverse mountain traditional village landscape is an important historical and cultural heritage, which is formed under the dual influence of geography and ethnicity. Faced with the realistic requirement of concentrated and continuous conservation of traditional villages in this region, there is an immediate demand to investigate the formation background, cluster model and conservation and utilization system of traditional village landscape in the region. By using the research methodology of historical geography, GIS spatial analysis, and spatial planning, the study analyzes the clustering, correlation, systematization and specificity of traditional village landscape clustering pattern in southeast Chongqing and proposes the clustering conservation and utilization system and implementation strategy of traditional village landscape from three scales: regional, watershed and settlement, so as to explore the current stage of traditional village clustering conservation work. It also proposes an effective path for the conservation of traditional villages and sustainable development of the region.

Exceptionally Strong Double-Layer Barriers Generated by Polyampholyte Salt.

Experiments using the surface force apparatus have found anomalously long-range interactions between charged surfaces in concentrated salt solutions. Ion clustering has been suggested as a possible origin of this behavior. In this work, we demonstrate that if such stable clusters indeed form, they are able to induce remarkably strong free energy barriers under conditions where a corresponding solution of simple salt provides negligible forces. Our cluster model is based on connected ions producing a polyampholyte salt containing a symmetric mixture of monovalent cationic and anionic polyampholytes. Ion distributions and surface interactions are evaluated utilizing statistical-mechanical (classical) polymer density functional theory, cDFT. In the Supporting Information, we briefly investigate a range of different polymer architectures (connectivities), but in the main part of the work, a polyampholyte ion is modeled as a linear chain with alternating charges, in which the ends carry an identical charge (hence, a monovalent net charge). These salts are able to generate repulsions, between similarly charged surfaces, of a remarkable strength, exceeding those from simple salts by orders of magnitude. The underlying mechanism for this is the formation of brush-like layers at the surfaces, i.e., the repulsion is strongly related to excluded volume effects, in a manner similar to the interaction between surfaces carrying grafted polymers. We believe our results are relevant not only to possible mechanisms underlying anomalously long-ranged underscreening in concentrated simple salt solutions but also for the potential use of synthesized polyampholyte salt as extremely efficient stabilizers of colloidal dispersions.

Optimal Scheduling of Electric Vehicles for Peak Load Regulation: A Multi-Time Scale Approach with Comprehensive Evaluation and Feedback

With the increasing prevalence of electric vehicles (EVs), optimizing their scheduling for grid peak-shaving has become a focal point of research. This study develops a multi-time-scale optimization model for EV clusters to participate in peak shaving, integrating a comprehensive evaluation and feedback mechanism. The innovation of this paper lies in the addition of an evaluation and feedback loop to the multi-time-scale scheduling optimization method for EVs participating in peak shaving, which fully utilizes the scheduling potential of EV clusters and mitigates the impact of uncertainties associated with EV clusters. The multi-time-scale approach mitigates response errors stemming from EV uncertainties. A feedback loop enables the grid to adaptively adjust scheduling commands to match real-time conditions. Simulations on the IEEE 33-node system demonstrate that the proposed model effectively optimizes EV load profiles, reducing the peak-to-valley difference rate from 41.74% to 35.19%. It also enhances response accuracy to peak-shaving instructions and upgrades the peak-shaving evaluation from a C rating to a B rating, ultimately increasing the revenue for aggregators participating in peak shaving.

Molybdenum-Iron-Sulfur Cluster with a Bridging Carbide Ligand as a Partial FeMoco Model: CO Activation, EPR Studies, and Bonding Insight.

Nitrogenase enzymes catalyze the reduction of N2 to NH3 at a complex Fe-M (M = Mo, Fe, or V) cofactor (FeMco), which displays eight metal centers and sulfide and carbide bridges with a MFe7S8C composition. The role of the unusual μ6-carbide ligand and its effects on the metal centers remain unclear. Here, we describe the transfer of a carbide ligand to a MoFe3S3 cluster supported by a bisphenoxide ligand from a previously reported terminal Mo carbide complex to yield a pentametallic cluster of MoS3Fe3CMo composition, which also displays a bridging CO that resembles the lo-CO form of nitrogenase. This cluster has an S = 1/2 spin state amenable to studies by pulse EPR spectroscopy, revealing a significantly larger carbide 13C hyperfine interaction (aiso(13C) = 12.5 MHz) than any observed for various states of FeMoco studied by EPR thus far (|aiso(13C)| = 0.89 to 2.7 MHz). This report provides a strategy for the synthesis of carbide-containing iron-sulfur clusters relevant to nitrogenase cluster modeling, as well as benchmarking information for the metal-carbon interactions by EPR methods.

P186 Beyond the snapshot: leveraging longitudinal c-reactive protein trends to predict number of biologic use in axial spondyloarthritis

Abstract Background/Aims Axial Spondyloarthritis (axSpA) is characterised by chronic inflammation of the axial skeleton. C-reactive protein (CRP), as a marker of inflammation, can be a predictor of response to targeted therapies. We aim to explore whether CRP fluctuations prior to biologic drug initiation could predict the number of targeted therapies required. Methods Electronic medical records of axSpA patients (n = 244) attending the Royal National Hospital for Rheumatic Diseases and starting targeted therapies (Anti-TNF, JAK inhibitor and IL-17 inhibitor) between 2016 and 2018 were retrospectively reviewed. Patients required a minimum of three CRP results over five years pre- and post- biologic initiation to be included on the analysis. We applied clustering methods to create five clusters of CRP measurements. These cluster models were then compared in terms of their prediction accuracy to find the best prediction model. Results Table-1 shows the clusters and the mean value of up to five CRP measurements. Different clusters represent different trends of CRP. The R-Squared value of the prediction model is 68%. This indicates that the CRP trends can be used to predict the number of biologic drugs patients will likely use. The analyses demonstrate that multiple CRP measurements add value to the prediction of response to initial targeted therapies. Table-1 also shows the number of drugs used by percentage of patients in the corresponding cluster. Patients in clusters 1 and 2 used three biologics, while cluster 3 patients are more likely to be responsive to first biologic. Patients in cluster 4 and 5 used two biologics and did not require to switch to a third biologic drug. Conclusion Our study shows the benefit of assessing multiple CRP measurements before biologic drug administration to predict how many times patients would likely switch biologic treatment. Based on our current analyses, we will further investigate if specific classes of targeted therapies can be used first line, stratified by the CRP cluster model to optimise drug survival. Disclosure M. Ho: None. A. Aziz: None. E.G. Ozpolat: None. C. Vasilakis: None. E.R. Gates: None. R. Sengupta: Consultancies; Pfizer, Abbvie, Biogen, BMS, Chugai, Lilly, Novartis, UCB. Honoraria; Pfizer, Abbvie, Lilly, Novartis, UCB. Grants/research support; UCB and Novartis - paid to institution. Other; support for attending meetings - Abbvie, Lilly, UCB, Novartis.

DFT Study of H2 Adsorption and Dissociation on Supported PdZn Clusters

Abstract The adsorption and dissociation of hydrogen molecules are essential for various hydrogenation reactions and utilization in hydrogen storage. Herein, by utilizing Density Functional Theory (DFT), we introduce Zn atoms to a Pd subnanometer cluster to investigate H2 dissociation. Two cluster models with ZrO2 support are considered, namely Pd4Zn/ZrO2 and Pd3Zn2/ZrO2. We find that H2 molecule strongly adsorbed on the Pd clusters, where Pd3Zn/ZrO2 gives slightly lower adsorption energy. Both configurations were found to facilitate the H2 dissociation into two H atoms thermodynamically, which takes place on top of Pd atoms with activation barriers of 0.63 and 0.67 eV on the Pd4Zn/ZrO2 and Pd3Zn2/ZrO2., respectively. Overall, this study provides new insights into the effect of cluster forms of Pd-based catalyst on the reaction mechanism of H2 dissociation.

Simulation of external environment of air-source heat pump cluster group for cold area heating

Abstract As an efficient and clean heating technology, air source heat pumps have been widely used in central heating in North China. A numerical simulation model of an air source heat pump cluster was established and the influence of external environment and cluster configuration on the inlet air temperature of the heat pump cluster were studied. The external environment includes wind speed and direction, while the cluster configuration includes overhead height, number of cluster, and installation direction. The simulation results show that the inlet temperature of the heat pump cluster will decrease with the increase of environmental wind speed; The inlet temperature of the heat pump cluster in the longitudinal frontside wind direction is higher than that in the other two wind directions; The inlet air temperature of the heat pump cluster will increase with the increase of the height above ground, but when the overhead height is increased again after reaching a certain height (0.5m), there will be no significant change in the inlet air temperature of the heat pump cluster; The more heat pumps there are in the cluster, the lower the inlet air temperature of the middle position heat pump is compared to the environmental temperature; In a calm state, the arrangement of the finned coil evaporator of the heat pump cluster can increase the average inlet air temperature from 269.63K of inward to 269.85K of outward.

Risk model and dynamic network analysis of symptom clusters in esophageal cancer patients undergoing chemoradiotherapy

Risk model and dynamic network analysis of symptom clusters in esophageal cancer patients undergoing chemoradiotherapy

Psychometric properties of the Chinese version of the quality of nursing care scale among hospital nurses: a bifactor exploratory structural equation modeling analysis

BackgroundNurses play an indispensable role in healthcare teams. The quality of nursing care reflects nurses’ ability to integrate care and their overall performance in patient care, making it a core objective of clinical nursing. The Chinese version of the Quality of Nursing Care (QNC) scale is a multidimensional assessment tool used for self-evaluation of nursing care quality and holds significant importance in clinical practice. This study aimed to assess the reliability and validity of the Chinese version of the QNC scale among nurses.MethodsThis was an observational, cross-sectional, methodological study conducted at three hospitals in southern Taiwan. The 25-item Chinese version of the QNC scale was employed in the study. Data were collected from 944 nurses (response rate: 65.42%) through an online survey conducted between July and August 2022. The factor structure of the QNC scale was evaluated using confirmatory factor analysis (unidimensional, independent cluster model, higher-order, and bifactor) and first-order, higher-order, and bifactor ESEM. Model comparisons were conducted to determine the best-fitting factor structure.ResultsThe bifactor ESEM provided the best fit for the QNC scale, consisting of a general QNC factor and seven specific factors: patient satisfaction, health promotion, complication prevention, well-being and self-care, functional readaptation, nursing care organization, and responsibility and rigor. Some items exhibited significant cross-loadings, highlighting the model’s ability to capture the multidimensional nature of nursing care quality.ConclusionsThe bifactor ESEM model demonstrated the best model fit for the Chinese version of the QNC scale, offering a reliable and interpretable representation of the multidimensional nature of nursing care. The validated scale provides a valuable tool for assessing nursing care quality in clinical practice.

РЕГІОНАЛЬНИЙ ВЕКТОР ЯК ІМПЕРАТИВ СТАЛОГО РОЗВИТКУ ТУРИСТИЧНО-РЕКРЕАЦІЙНОГО КЛАСТЕРУ

The article studies conditions and factors of recreation and tourism sphere tourism development in region and gives recommendations concerning improvement management of recreation and tourism cluster potential. The study analyzes the essence of the concept economic category «recreation and tourism cluster» by constructing a structural and logical sequence. The concept «recreation and tourism cluster models» has been formulated and substantiated. It is characterized as strategic unity of development of integrated components forming the tourism industry potential (i.e. institutional, innovative, social, environmental, economic and financial components) and socioeconomic as well as environmental subsystems. It is aimed at coherence and rational use of natural, health, cultural and historical resources for development of regions or countries in order to meet the needs of consumers, increase the welfare of society and build the potential of the tourism industry as well as the national economy in the strategic aspect. A holistic concept of balanced development of the potential of the tourism industry in of regions, has been proposed and substantiated. The author offers the scheme of realization of the integral concept which is built on complex use of system-target approach to a choice and realization of management options for the balanced development of tourism industry potential of regions. The scientific approach to the balanced development of the tourism industry potential of region has been proposed (basing on the results of regions modeling). The positive features and possibilities of creating tourism clusters in the regions of the organizational and managerial support resources, A rationalist model of tourism cluster formation at the regional level has been developed and substantiated with the use of the methodological provisions given in the thesis. The thesis improves the boundary model of factors influencing the balanced development of the tourism industry potential of regions. The theoretical optimization model of forming the strategy of tourism cluster development in region has received its further development; the organizational and economic mechanism of its realization have been highlighted. Strategic ways of developing tourist and recreational complex in region have been determined. The organizational and management mechanism of effective recreational activity, which should take into account the combined effect of a number of objective and subjective factors, which in one way or another determine the real conditions for its realization, is substantiated. It is determined that the organizational and management mechanism of the implementation of tourist and recreational activities is realized through certain organizational structures that promote the realization of the interests of state, private, communal enterprises and institutions at the international, national, regional and local (local) levels

A Resource-Sharing Method for College English Translation Corpora Under the Background of Informatization

In today’s information age, the ability of intelligent sharing and scheduling of college English translation corpus resources needs to be improved. Therefore, a method based on fuzzy autocorrelation statistical feature analysis is proposed. First of all, a model must be constructed to detect the semantically relevant dimensional features of college English translation corpus resources under the background of informatization, and to analyze the essential attributes of translation activities by using the hierarchical parameter detection method of translated texts in the narrative structure. Then, a quantitative difference coverage model of word clusters of different lengths is established, with lexical attribute extraction and statistical examination of these resources being performed via a similarity attribute extraction technique for high-frequency word clusters. Subsequently, a semantic dynamic attribute analysis model is developed to derive statistical attributes of college English translation corpus resources within the informatized context. Ultimately, based on the obtained attribute extraction results, a fuzzy autocorrelation statistical attribute analysis method is employed for clustering large datasets. Furthermore, an intelligent particle swarm optimization algorithm is implemented to extract and disseminate lexical attributes of college English translation corpus resources within the information-driven context, so that the college English translation corpus resources can be optimized under the information background. According to the simulation results, this method has excellent accuracy in extracting and sharing lexical features of translated texts, and its feature discrimination ability is also good. It can indeed improve the ability of extracting, sharing, and detecting lexical features of translated texts from college English translation corpus resources.

Symmetry Breaking around Aqueous Ammonia Revealed in Nitrogen K-edge X-ray Absorption.

Nitrogen K-edge X-ray absorption (XA) spectroscopy of aqueous ammonia reveals a splitting in the main-edge, which through theoretical modeling is shown to be related to symmetry breaking in hydrogen bonding. The XA main-edge of NH3 is formed by a pair of degenerate core-excitations into extended molecular orbitals. In aqueous solution, these form an antibonding mixture with orbitals of the surrounding water molecules. Although the spectral response to distortions is complex, we show that the degeneracy of the core-excitations is lifted by asymmetry in hydrogen bond donation (NH···O). A quantitative relation between asymmetry in the hydration shell and splitting in the main-edge of the nitrogen K-edge XA spectrum is established from systematic symmetry breaking in well-defined cluster models and through molecular dynamics sampling of simulated XA spectra of aqueous ammonia. The finding indicates that XA spectroscopy is a sensitive probe of asymmetry in solvation also around functional groups in biomolecules.

Pivoting through the chiral-clock family

The Onsager algebra, invented to solve the two-dimensional Ising model, can be used to construct conserved charges for a family of integrable NN-state chiral clock models. We show how it naturally gives rise to a “pivot” procedure for this family of chiral Hamiltonians. These Hamiltonians have an anti-unitary CPT symmetry that when combined with the usual \mathbb{Z}_NℤN clock symmetry gives a non-Abelian dihedral symmetry group D_{2N}D2N. We show that this symmetry gives rise to symmetry-protected topological (SPT) order in this family for all even NN, and representation-SPT (RSPT) physics for all odd NN. The simplest such example is a next-nearest-neighbour chain generalising the spin-1/2 cluster model, an SPT phase of matter. We derive a matrix-product state representation of its fixed-point ground state along with the ensuing entanglement spectrum and symmetry fractionalisation. We analyse a rich phase diagram combining this model with the Onsager-integrable chiral Potts chain, and find trivial, symmetry-breaking and (R)SPT orders, as well as extended gapless regions. For odd NN, the phase transitions are “unnecessarily” critical from the SPT point of view.