Merging Components Research Articles

ALMA-ALPINE [CII] survey: The sub-kpc morphology of three main sequence galaxy systems at z ∼ 4.5 revealed by ALMA

Context. Going from a redshift of 6 down to nearly 4, galaxies grow rapidly from low-mass galaxies towards the more mature types of massive galaxies seen at cosmic noon. Growth via gas accretion and mergers undoubtedly shape this evolution, however, there is considerable uncertainty at present over the contribution of each of these processes to the overall evolution of galaxies. Furthermore, previous characterisations of the morphology of galaxies in the molecular gas phase have been limited by the coarse resolution of earlier observations. Aims. In this work, we utilise new high-resolution ALMA [CII] observations to analyse three main sequence (MS) galaxy systems at a redshift of z ∼ 4.5 and at resolutions of up to 0.15″. This approach enables us to investigate the morphology and kinematics on a kpc scale and understand the processes at play as well as the classifications of galaxies at high resolution. Thanks to this unique window, we are able to gain insights into the molecular gas of MS galaxies undergoing mass assembly in the early Universe. Methods. We used intensity and velocity maps, position-velocity diagrams, and radial profiles of [CII] in combination with dust continuum maps to analyse the morphology and kinematics of the three systems. Results. In general, we find that the high-resolution ALMA data reveal more complex morpho-kinematic properties. For one galaxy in our sample, we identified interaction-induced clumps, demonstrating the profound effect that mergers have on the molecular gas in galaxies, which is consistent with what has been suggested by recent simulations. One galaxy that was previously classified as dispersion-dominated turned out to show two bright [CII] emission regions, which could either be classified as merging galaxies or massive star-forming regions within the galaxy itself. The high-resolution data for the other dispersion dominated object also revealed clumps of [CII] that had not been identified previously. Within the sample, we might also detect star-formation powered outflows (or outflows from active galactic nuclei) that appear to be fuelling diffuse gas regions and enriching the circumgalactic medium. The new high-resolution ALMA data we present in this paper reveal that the galaxies in our sample are much more complex than they previously appeared in the low-resolution ALPINE data. In particular, we find evidence of merger induced clumps in the galaxy DC8187, along with signs of merging components for the other two objects. This may be evidence that the number of mergers at high redshift are significantly underestimated at present.

Remaining useful life prediction of lithium battery based on CEEMD-SE-IPSO-LSSVM hybrid model

Abstract In order to prevent accidents caused by battery aging, accurately predicting the remaining useful life (RUL) is a critical and highly challenging task in battery management systems. This article describes a lithium-ion battery RUL prediction method based on a hybrid model of CEEMD-SE-IPSO-LSSVM. This method integrates various technologies and algorithms, enhancing the accuracy and practicality of predictions. Initially, the complete ensemble empirical mode decomposition (CEEMD) is utilized to decompose the raw data into multiple intrinsic mode functions, aiding in denoising and feature extraction. Subsequently, the sample entropy (SE) is used to assess the complexity and irregularity of the data, merging intrinsic mode function components with similar SE values into a new component. Building upon this, the advanced iterative particle swarm optimization (IPSO) algorithm refines the parameters of the least squares support vector machine (LSSVM) model, improving the predictive performance of the model. Finally, through iterative training and refinement of the LSSVM model, accurate prediction of the remaining life of lithium-ion batteries is achieved. This hybrid model approach integrates data processing, feature extraction, and model refinement, resulting in a significant improvement over the baseline model with a 69.5% increase in mean absolute percentage error and a 49.4% decrease in root mean squared error, providing a robust solution for predicting the remaining life of lithium-ion batteries.

Ultrasonic Vibrator Glove for Enhanced Mobility and Safety in Visually Impaired Individuals

Abstract: This paper explores the conception, production, and actual use of an ultrasonic vibrator glove intended to aid the blind. The glove accomplishes real-time obstacle detection and offers tactile feedback by merging cutting-edge components such an ultrasonic sensor, haptic motor, and Arduino UNO board. For people who are blind, this breakthrough dramatically improves mobility, independence, and safety. The glove's integration of haptic vibration and ultrasonic detection overcomes conventional constraints and gives users a natural approach to understand their environment. The Ultrasonic Vibrator Glove redefines the tactile experience, allowing those who are blind to navigate their environment more successfully through quick obstacle detection and intuitive vibrations. The end result is a solution that empowers people and encourages self-assurance, independence, and security in their daily lives.

A z = 1.85 galaxy group in CEERS: Evolved, dustless, massive intra-halo light and a brightest group galaxy in the making

We present CEERS JWST/NIRCam imaging of a massive galaxy group at z = 1.85, to explore the early JWST view on massive group formation in the distant Universe. The group contains ≳16 members (including six spectroscopic confirmations) down to log10(M⋆/M⊙) = 8.5, including the brightest group galaxy (BGG) in the process of actively assembling at this redshift. The BGG is comprised of multiple merging components extending ∼3.6″ (30 kpc) across the sky. The BGG contributes 69% of the group’s total galactic stellar mass, with one of the merging components containing 76% of the total mass of the BGG and a star formation rate > 1810 M⊙ yr−1. Most importantly, we detected intra-halo light (IHL) in several HST and JWST/NIRCam bands, allowing us to construct a state-of-the-art rest-frame UV-NIR spectral energy distribution of the IHL for the first time at this high redshift. This allows stellar population characterisation of both the IHL and member galaxies, as well as the morphology distribution of group galaxies versus their star formation activity when coupled with Herschel data. We created a stacked image of the IHL, giving us a sensitivity to extended emission of 28.5 mag arcsec−2 at rest-frame 1 μm. We find that the IHL is extremely dust poor (Av ∼ 0), containing an evolved stellar population of log10(t50/yr) = 8.8, corresponding to a formation epoch for 50% of the stellar material 0.63 Gyr before z = 1.85. There is no evidence of ongoing star formation in the IHL. The IHL in this group at z = 1.85 contributes ∼10% of the total stellar mass, comparable with what is observed in local clusters. This suggests that the evolution of the IHL fraction is more self-similar with redshift than predicted by some models, challenging our understanding of IHL formation during the assembly of high-redshift clusters. JWST is unveiling a new side of group formation at this redshift, which will evolve into Virgo-like structures in the local Universe.

475 Co-designing an intervention to support safe medicines self-management for older people living with frailty and polypharmacy

Abstract Introduction Older people face numerous challenges and safety risks when managing multiple medicines. They are required to cope with complex and changing regimens and co-ordinate input from multiple healthcare professionals. If not well managed, medicines can cause harm, and older people are more susceptible to errors. Some older people can devise and implement strategies to manage their medicines, e.g. creating checklists, ensuring timely supplies, solving problems, and seeking help (1). However, no interventions address the multiple tasks polypharmacy patients must perform to safely manage their regimens. Aim To develop an intervention to support medicines self-management for older people living with frailty and polypharmacy using experience-based co-design (EBCD) (2). Methods Following video or audio-recorded qualitative interviews with 32 older people taking 5 or more medicines, a ‘trigger film’ of patients’ medicines management experiences was produced and used during EBCD to facilitate priority setting. Separate meetings were held (1) with 16 staff (2 GPs, 4 GP practice administrators, 4 GP practice pharmacists, 1 practice lead, 2 senior nurses, 2 pharmacy technicians, 1 community pharmacist) and (2) with 13 patients and 2 family members, followed by a joint meeting with 8 older people and 9 staff where a shared set of three priorities was agreed. Two subsequent co-design workshops with 6 patients, 2 family members and 7 staff developed three candidate interventions. Workshop 1 explored key themes from the trigger film to develop solutions. Workshop 2 reviewed solutions and further developed design ideas. Intervention components were merged and those addressing patient safety challenges were retained to form the prototype intervention. Ethical approval was obtained for the interviews included in the trigger film, but not required for EBCD. EBCD meetings and workshops were conducted as quality improvement: people involved were collaborators, personal information was not captured, discussions were not recorded or analysed. Results Co-design priorities were to support patients in: day-to-day practical medicines management; understanding the wider medicines management system; communication with healthcare teams. The three solutions were: a quick-start guide to managing multiple medicines including talking about medicines and managing new routines; tips and tricks to support day-to-day management, including planning and adherence tools; a tool supporting preparation for medication reviews and asking questions about medicines. After merging intervention components and identifying those addressing medicines-self-management patient safety challenges, five areas were retained for the prototype intervention: checking what you get; keeping on top of supplies; monitoring how you take your medicines; times when problems are more likely; and how do I know if I need help? Discussion/Conclusion Through EBCD patients and staff worked together to improve people’s experiences of managing medicines and to enhance safety. The prototype intervention addresses five areas where older people with complex medicines regimens require support. The intervention requires feasibility testing and subsequent robust evaluation. Strengths and limitations: • A variety of staff roles joined the co-design, offering multiple different perspectives on medicines management • EBCD meetings and workshops were run online to avoid Covid infections. This may have excluded older people with no access to internet.

On Methods for Merging Mixture Model Components Suitable for Unsupervised Image Segmentation Tasks

Unsupervised image segmentation is one of the most important and fundamental tasks in many computer vision systems. Mixture model is a compelling framework for unsupervised image segmentation. A segmented image is obtained by clustering the pixel color values of the image with an estimated mixture model. Problems arise when the selected optimal mixture model contains a large number of mixture components. Then, multiple components of the estimated mixture model are better suited to describe individual segments of the image. We investigate methods for merging the components of the mixture model and their usefulness for unsupervised image segmentation. We define a simple heuristic for optimal segmentation with merging of the components of the mixture model. The experiments were performed with gray-scale and color images. The reported results and the performed comparisons with popular clustering approaches show clear benefits of merging components of the mixture model for unsupervised image segmentation.

Electrosynthesis of ternary nonprecious Ni, Cu, Fe oxide nanostructure as efficient electrocatalyst for ethanol electro-oxidation: Design strategy and electrochemical performance

Materials composed of various constituents with distinct physical or chemical features are named composites. Merging components in the composite structure leads to new properties creation or the intrinsic properties magnification of the components, or synergetic effects. Here, the ternary nanocomposite of copper, nickel, and iron oxides was electrodeposited on the glassy carbon electrode (GCE) surface to facilitate the ethanol electro-oxidation reaction (EOR) and overcome the electrode fouling problem while prolonging its efficiency. The GCEs were modified by three different procedures and activated by CV cycling in an alkaline solution, and their electro-catalytic activity was tested toward EOR. The ternary electrocatalysts prepared by two-steps electrodeposition of their components (Ni,Fe2O3/Cu and Cu/Ni,Fe2O3) demonstrated higher peak current and more negative peak potential (Epa = 476 mV, Ipa = 492 μA, and Epa = 510 mV, Ipa = 644 μA, respectively) than the binary electrocatalyst of Ni,Fe2O3 toward EOR. The best electro-catalytic efficiency was acquired for the simultaneous electrodeposition of nano Cu, Ni, and Fe2O3 on the GCE surface (Cu,Ni,Fe2O3, Epa = 530 mV, Ipa = 3179 μA). The physicochemical and electro-catalytic characterizations of the fabricated electrocatalysts were evaluated by various techniques. The fast and facile engineered design of the GCE modification with the ternary Cu,Ni,Fe2O3 components led to a high current density of about 101 mA/cm2 with increased tolerance against poisoning intermediates resulting in longtime stability for EOR in alkaline media. The synergistic effect between nano Ni, Cu, and Fe oxides provided promising properties for the EOR pursuing the construction of a powerful device with commercialization potential.

Combined Proactive Risk Assessment: Unifying Proactive and Reactive Risk Assessment Techniques In Health Care.

Reactive risk assessments (RRAs) such as incident reporting and root cause analysis (RCA), as well as proactive risk assessments (PRAs) such as failure mode and effects analysis, are generally conducted independently in health care. Literature promotes combining risk assessment techniques. This concept builds on previous methodologies and presents an innovative, scalable, and generalizable risk assessment methodology. A Combined Proactive Risk Assessment (CPRA) technique entails combining incident reports (RRAs), combining proactive risk assessments (PRAs), and merging components of PRA and RRA. Using specific keywords, this technique aligns patient safety reporting data with process steps and failure modes to assess risk within any of the process steps. This technique was tested by using PRAs from several Veterans Health Administration (VHA) facilities and national patient safety data from the VHA National Center for Patient Safety's database. Reported events and RCAs related to the outpatient blood draw process were used for this illustration. Repeatability was determined by independently applying the technique to two years of data and auditing results. Aggregating PRAs from multiple facilities identified 220% more failure modes; and integrating incident reports into PRA identified 310% more failure modes than the single facility average. Overlaying safety reports onto a comprehensive process flow diagram revealed that 85.8% of events occurred in three of seven process steps. Accuracy of this technique was generally above 85%. This technique is promising for identifying vulnerable points in health care processes or to compliment a traditional PRA. Single PRAs are less likely to identify all potential failures or focus on the most hazardous process steps. This technique may aid in assessing key health care processes at an enterprise level.

Summarizing Finite Mixture Model with Overlapping Quantification.

Finite mixture models are widely used for modeling and clustering data. When they are used for clustering, they are often interpreted by regarding each component as one cluster. However, this assumption may be invalid when the components overlap. It leads to the issue of analyzing such overlaps to correctly understand the models. The primary purpose of this paper is to establish a theoretical framework for interpreting the overlapping mixture models by estimating how they overlap, using measures of information such as entropy and mutual information. This is achieved by merging components to regard multiple components as one cluster and summarizing the merging results. First, we propose three conditions that any merging criterion should satisfy. Then, we investigate whether several existing merging criteria satisfy the conditions and modify them to fulfill more conditions. Second, we propose a novel concept named clustering summarization to evaluate the merging results. In it, we can quantify how overlapped and biased the clusters are, using mutual information-based criteria. Using artificial and real datasets, we empirically demonstrate that our methods of modifying criteria and summarizing results are effective for understanding the cluster structures. We therefore give a new view of interpretability/explainability for model-based clustering.

Short-Time Impedance Spectroscopy Using a Mode-Switching Nonsinusoidal Oscillator: Applicability to Biological Tissues and Continuous Measurement.

Herein, we propose an impedance spectroscopy method using a mode-switching nonsinusoidal oscillator and apply this method for measuring the impedance of biological tissues and continuous impedance measurement. To obtain impedance spectra over a wide frequency range, we fabricated a novel nonsinusoidal oscillator incorporating binary counters and analog switches. This oscillator could periodically switch oscillation frequency through the mode switching of the feedback resistor. From the oscillation waveform at each oscillation frequency of this circuit (oscillator), we determined the impedance spectrum of a measured object using the discrete-time Fourier transform. Subsequently, we obtained the broad impedance spectrum of the measured object by merging odd-order harmonic spectral components up to the 19th order for each oscillation frequency. From the measured spectrum, the resistive and capacitive components of the circuit simulating bioimpedance were estimated with high accuracy. Moreover, the proposed method was used to measure the impedance of porcine myocardium; changes in the impedance spectrum of the myocardial tissue due to coagulation could be measured. Furthermore, rapid variations in the resistance value of a CdS photocell could be continuously measured using the proposed method.

Prototipe Kontrol Lampu Dengan SCADA dan Android

Controlling the flames lighting still using manual control, then require the officer to control the condition of the flame lights at a certain time. Therefore, the control of street lighting and the room is automatically required to facilitate the operation of the flame of the lamp. Processing using arduino Mega 2560 and NodeMCU ESP8266 as a controller, sensor DHT 11 as a detection value of the temperature and humidity sensor LDR as the control of street lighting, and the module RTC as a controller of the lighting in the room. The method used is the process of merging multiple components to form a construction. The result of the manufacture of the tool that is controlling the lights street lighting on and off based on LDR sensor, as well as the lighting on the room which is set using the set point time module RTC. the control can be operated and monitored using a SCADA system and Android, as well as can termonitoring values of temperature and humidity in a room which is displayed on the LED dot matrix. Distance control using the android system with a maximum of 22 meters.

Estimates of the Early Electromagnetic Emission from Compact Binary Mergers

Abstract Compact binary mergers that involve at least one neutron star, either binary neutron star or black hole–neutron star coalescences, are thought to be the potential sources of electromagnetic emission due to the material ejected during the merger or those left outside the central object after the merger. Since the intensity of these electromagnetic transients decays rapidly with time, one should pay more attention to early emissions from such events, which are useful in revealing the nature of these mergers. In this work, we study the early emission of kilonovae, short gamma-ray bursts (GRBs), and cocoons that could be produced in those mergers. We estimate their luminosities and timescales as functions of the chirp mass, which is the most readily constrained parameter from the gravitational wave detections of these events. We focus on the range of chirp mass as 1.3–2.7 M ⊙, which is compatible with one of the merging components being a so-called “mass gap” black hole. We show that the electromagnetic observation of these transients could be used to distinguish the types of the mergers when the detected chirp mass falls in the range of 1.5–1.7 M ⊙. Applying our analysis to the subthreshold GRB GBM-190816, we found that for this particular event the effective spin should be larger than 0.6 and the mass of the heavier object might be larger than 5.5 M ⊙ for the phenomenological Steiner–Fischer–Hempel equation of state.

How end-user programmers forage in online repositories? An information foraging perspective

End-user (non-professional) programmers often opportunistically create programs, they evaluate various alternatives and reuse existing code by merging components from it or modifying it to suit the context or problems of their programs. Finding and evaluating which program variants to reuse code from is challenging because the searching mechanisms within online repositories are not optimal. To understand the reuse behavior of end-user programmers and to provide implications on how to further support them, we conducted an empirical study in which eight end-user programmers foraged in online repositories, specifically App Inventor Gallery and File Exchange. Using Information Foraging Theory, we qualitatively analyzed the end-user programmers’ behavior and focused on not only program variants from a single source, but also on similar variants from various sources developed over time and by different authors. This analysis revealed new cue types and strategies specific to novice and experienced end-user programmers as they foraged between- and within-variants.

Classifying settlement types from multi-scale spatial patterns of building footprints

Urban settlements and urbanised populations continue to grow rapidly and much of this transition is occurring in less developed countries. Remote sensing techniques are now often applied to monitor urbanisation and changes in settlement patterns. In particular, increasing availability of very high resolution imagery (<1 m spatial resolution) and computing power is enabling complete sets of settlement data in the form of building footprints to be extracted from imagery. These settlement data provide information on the changes occurring in cities, particularly in countries which may lack other data on urbanisation. While spatially detailed, extracted building footprints typically lack other information that identify building types or can be used to differentiate intra-urban land uses or neighbourhood types. This work demonstrates an approach to classifying settlement types through multi-scale spatial patterns of urban morphology visible in building footprint data extracted from very high resolution imagery. The work uses a Gaussian mixture modelling approach to select and hierarchically merge components into clusters. The results are maps classifying settlement types on a high spatial resolution (100 m) grid. The approach is applied in Kaduna, Nigeria; Kinshasa, Democratic Republic of the Congo; and Maputo, Mozambique and demonstrates the potential of computational methods to take advantage of large spatial datasets and extract meaningful information to support monitoring of urban areas. The model-based approach produces a hierarchy of potential clustering solutions, and we suggest that this can be used in partnership with local knowledge of the context when creating settlement typologies.

Advance in the computational tools that support the cooperative sector in Colombia

The technological evolution in the 21st century allows organizations to define flexible and integral processes and information systems that guarantee their competitiveness and sustainability. The dynamics of the cooperative sector seeks to use, merge and implement new technological components, aimed mainly at strengthening its business model. The descriptive quantitative research achieves an approach with seven cooperatives (savings and credit) of the Catatumbo Region, Colombia, through the survey technique in order to determine the adaptation of cooperatives in the global panorama of information and communication technologies. In conclusion, the managers of savings and credit cooperatives require technologies to support administrative and strategic operations, as well as contribute to the design and implementation of software to ensure quality, security and effectiveness of institutional information and services to all their stakeholders, prioritizing in contributing to closing the digital divide and social inequality.

Additive manufacturing adoption in product design: an overview from literature and industry

Additive Manufacturing (AM) technologies have greatly extended design possibilities and freedom. However, in the designer everyday work, the decision regarding the adoption of AM for some components is not straightforward. There is a need to evaluate the properties of the available materials, their compatibility with the specific application, redesign shapes accordingly to additive rather than subtractive or deforming processes, conceive merging components in unique complex multifunctional parts. Indeed, economic, procurement and logistics evaluations, possibly extended to the entire life cycle, are necessary to come to a decision for a new and radical solution. In this context, the paper investigates the complex set of information involved in the process to guide a designer in a structured assessment and evaluation of opportunities for the adoption of AM. The approach includes the analysis of the design requirements to evaluate the applicability of additive technologies. Selected design questions are presented as attention points to help designers in the decision-making process along with a metric to merge the answers in an overall compliance index. Finally, some test cases from the literature and industry are reported to validate the proposed decision process.

The molecular gas properties in the gravitationally lensed merger HATLAS J142935.3–002836

ABSTRACT Follow-up observations of (sub-)mm-selected gravitationally lensed systems have allowed a more detailed study of the dust-enshrouded phase of star formation up to very early cosmic times. Here, the case of the gravitationally lensed merger in HATLAS J142935.3–002836 (also known as H1429−0028; zlens = 0.218, zbkg = 1.027) is revisited following recent developments in the literature and new Atacama Pathfinder EXperiment (APEX) observations targeting two carbon monoxide (CO) rotational transitions Jup = 3 and 6. We show that the line profiles comprise three distinct velocity components, where the fainter high velocity one is less magnified and more compact. The modelling of the observed spectral line energy distribution of CO Jup = 2–6 and [C i] 3P1−3P0 assumes a large velocity gradient scenario, where the analysis is based on four statistical approaches. Since the detected gas and dust emission comes exclusively from only one of the two merging components (the one oriented north–south, NS), we are only able to determine upper limits for the companion. The molecular gas in the NS component in H1429−0028 is found to have a temperature of ∼70 K, a volume density of log (n[cm−3]) ∼ 3.7, to be expanding at ∼10 km s−1 pc−1, and amounts to ${M_{\rm H_2} = 4_{-2}^{+3} \times 10^9\,{\rm M}_\odot }$. The CO to H2 conversion factor is estimated to be $\alpha _{\rm CO} = 0.4_{-0.2}^{+0.3}\,$ M⊙/(K km s−1 pc2). The NS galaxy is expected to have a factor of ≳10× more gas than its companion (${M_{\rm H_2}}\lesssim 3\times 10^8$ M⊙). Nevertheless, the total amount of molecular gas in the system comprises only up to 15 per cent (1σ upper limit) of the total (dynamical) mass.

Growing a ‘cosmic beast’: observations and simulations of MACS J0717.5+3745

ABSTRACTWe present a gravitational lensing and X-ray analysis of a massive galaxy cluster and its surroundings. The core of MACS J0717.5+3745 ($M(R\lt 1\, {\rm Mpc})\sim$ $2 \times 10^{15}\, \, {\rm M}_{\odot }$, $z$ = 0.54) is already known to contain four merging components. We show that this is surrounded by at least seven additional substructures with masses ranging $3.8{-}6.5\times 10^{13}\, \, {\rm M}_{\odot }$, at projected radii 1.6–4.9 Mpc. We compare MACS J0717 to mock lensing and X-ray observations of similarly rich clusters in cosmological simulations. The low gas fraction of substructures predicted by simulations turns out to match our observed values of 1–$4{{\ \rm per\ cent}}$. Comparing our data to three similar simulated haloes, we infer a typical growth rate and substructure infall velocity. That suggests MACS J0717 could evolve into a system similar to, but more massive than, Abell 2744 by $z$ = 0.31, and into a ∼ $10^{16}\, \, {\rm M}_{\odot }$ supercluster by $z$ = 0. The radial distribution of infalling substructure suggests that merger events are strongly episodic; however, we find that the smooth accretion of surrounding material remains the main source of mass growth even for such massive clusters.

Complexity and systemic organizational redirection

PurposeThe purpose of this paper is to assess the effects of officers’ perceptions of complexity in merging organizational change components (culture, mission, values, decentralization, policies and procedures, administrative reporting practices, weapons, contract, pay, benefits, patrol boundaries, equalization of workload, size of boundaries, communications, 10-codes, and car numbers) during a major metropolitan police department consolidation.Design/methodology/approachThe current study utilizes data collected from 390 sworn officers from two agencies in Kentucky that were merged, the Louisville Division of Police and the Jefferson County Police Department. Statistical inquiry included factor analysis and a series of bivariate and multivariate logistic regression analysis (controlling for demographic measures).FindingsResults revealed a noteworthy, positive effect on support for consolidation related to the complexity of three factors: benefits, mission, and policies.Originality/valueTo date, the relevance of complexity on support for organizational change and, more specifically, police consolidation, is unknown. With this study, the authors aim to add to the discussion.

Merging the components of a finite mixture using posterior probabilities

Methods in parametric cluster analysis commonly assume data can be modelled by means of a finite mixture of distributions. However, associating each mixture component to one cluster is frequently misleading because different mixture components can overlap, and then, associated clusters can overlap too suggesting a unique cluster. A number of approaches have already been proposed to construct the clusters by merging components using the posterior probabilities. This article presents a generic approach for building a hierarchy of mixture components that integrates and generalizes some techniques proposed earlier in the literature. Using this proposal, two new techniques based on the log-ratio of posterior probabilities are introduced. Moreover, to decide the final number of clusters, two new methods are presented. Simulated and real datasets are used to illustrate this methodology.