A STUDY OF HEAT TRANSFER AND FLOW CHARACTERISTICS OF RISING TAYLOR BUBBLES

Practical application of flow boiling to ground- and space-based thermal management systems hinges on the ability to predict the system’s heat removal capabilities under expected operating conditions. Research in this field has shown that the heat transfer coefficient within two-phase heat exchangers can be largely dependent on the experienced flow regime. This finding has inspired an effort to develop mechanistic heat transfer models for each flow pattern which are likely to outperform traditional empirical correlations. As a contribution to the effort, this work aimed to identify the heat transfer mechanisms for the slug flow regime through analysis of individual Taylor bubbles. An experimental apparatus was developed to inject single vapor Taylor bubbles into co-currently flowing liquid HFE 7100. The heat transfer was measured as the bubble rose through a 6 mm inner diameter heated tube using an infrared thermography technique. High-speed flow visualization was obtained and the bubble film thickness measured in an adiabatic section. Experiments were conducted at various liquid mass fluxes (43-200 kg/m2s) and gravity levels (0.01g-1.8g) to characterize the effect of bubble drift velocity on the heat transfer mechanisms. Variable gravity testing was conducted during a NASA parabolic flight campaign. Results from the experiments showed that the drift velocity strongly affects the hydrodynamics and heat transfer of single elongated bubbles. At low gravity levels, bubbles exhibited shapes characteristic of capillary flows and the heat transfer enhancement due to the bubble was dominated by conduction through the thin film. At moderate to high gravity, traditional Taylor bubbles provided small values of enhancement within the film, but large peaks in the wake heat transfer occurred due to turbulent vortices induced by the film plunging into the trailing liquid slug. Characteristics of the wake heat transfer profiles were analyzed and related to the predicted velocity field. Results were compared and shown to agree with numerical simulations of colleagues from EPFL, Switzerland. In addition, a preliminary study was completed on the effect of a Taylor bubble passing through nucleate flow boiling, showing that the thinning thermal boundary layer within the film suppressed nucleation, thereby decreasing the heat transfer coefficient.

Detecting cell assemblies in large neuronal populations

Recent progress in the technology for single unit recordings has given the neuroscientific community theopportunity to record the spiking activity of large neuronal populations. At the same pace, statistical andmathematical tools were developed to deal with high-dimensional datasets typical of such recordings.A major line of research investigates the functional role of subsets of neurons with significant co-firingbehavior: the Hebbian cell assemblies. Here we review three linear methods for the detection of cellassemblies in large neuronal populations that rely on principal and independent component analysis.Based on their performance in spike train simulations, we propose a modified framework that incorpo-rates multiple features of these previous methods. We apply the new framework to actual single unitrecordings and show the existence of cell assemblies in the rat hippocampus, which typically oscillate attheta frequencies and couple to different phases of the underlying field rhythm

Non-contact test set-up for aeroelasticity in a rotating turbomachine combining a novel acoustic excitation system with tip-timing

Due to trends in aero-design, aeroelasticity becomes increasingly important in modern turbomachines. Design requirements of turbomachines lead to the development of high aspect ratio blades and blade integral disc designs (blisks), which are especially prone to complex modes of vibration. Therefore, experimental investigations yielding high quality data are required for improving the understanding of aeroelastic effects in turbomachines. One possibility to achieve high quality data is to excite and measure blade vibrations in turbomachines. The major requirement for blade excitation and blade vibration measurements is to minimize interference with the aeroelastic effects to be investigated. Thus in this paper, a non-contact-and thus low interference-experimental set-up for exciting and measuring blade vibrations is proposed and shown to work. A novel acoustic system excites rotor blade vibrations, which are measured with an optical tip-timing system. By performing measurements in an axial compressor, the potential of the acoustic excitation method for investigating aeroelastic effects is explored. The basic principle of this method is described and proven through the analysis of blade responses at different acoustic excitation frequencies and at different rotational speeds. To verify the accuracy of the tip-timing system, amplitudes measured by tip-timing are compared with strain gage measurements. They are found to agree well. Two approaches to vary the nodal diameter (ND) of the excited vibration mode by controlling the acoustic excitation are presented. By combining the different excitable acoustic modes with a phase-lag control, each ND of the investigated 30 blade rotor can be excited individually. This feature of the present acoustic excitation system is of great benefit to aeroelastic investigations and represents one of the main advantages over other excitation methods proposed in the past. In future studies, the acoustic excitation method will be used to investigate aeroelastic effects in high-speed turbomachines in detail. The results of these investigations are to be used to improve the aeroelastic design of modern turbomachines.

Tracking the attenuation and nonbreaking dissipation of swells using altimeters

A method for systematically tracking swells across oceanic basins is developed by taking advantage of high-quality data from space-borne altimeters and wave model output. The evolution of swells is observed over large distances based on 202 swell events with periods ranging from 12 to 18 s. An empirical attenuation rate of swell energy of about 4 × 10−7 m−1 is estimated using these observations, and the nonbreaking energy dissipation rates of swells far away from their generating areas are also estimated using a point source model. The resulting acceptance range of nonbreaking dissipation rates is −2.5 to 5.0 × 10−7 m−1, which corresponds to a dissipation e-folding scales of at least 2000 km for steep swells, to almost infinite for small-amplitude swells. These resulting rates are consistent with previous studies using in-situ and synthetic aperture radar (SAR) observations. The frequency dispersion and angular spreading effects during swell propagation are discussed by comparing the results with other studies, demonstrating that they are the two dominant processes for swell height attenuation, especially in the near field. The resulting dissipation rates from these observations can be used as a reference for ocean engineering and wave modeling, and for related studies such as air-sea and wind-wave-turbulence interactions.

Learning Binary Code Representations for Effective and Efficient Image Retrieval

The size of online image datasets is constantly increasing. Considering an image dataset with millions of images, image retrieval becomes a seemingly intractable problem for exhaustive similarity search algorithms. Hashing methods, which encodes high-dimensional descriptors into compact binary strings, have become very popular because of their high efficiency in search and storage capacity. In the first part, we propose a multimodal retrieval method based on latent feature models. The procedure consists of a nonparametric Bayesian framework for learning underlying semantically meaningful abstract features in a multimodal dataset, a probabilistic retrieval model that allows cross-modal queries and an extension model for relevance feedback. In the second part, we focus on supervised hashing with kernels. We describe a flexible hashing procedure that treats binary codes and pairwise semantic similarity as latent and observed variables, respectively, in a probabilistic model based on Gaussian processes for binary classification. We present a scalable inference algorithm with the sparse pseudo-input Gaussian process (SPGP) model and distributed computing. In the last part, we define an incremental hashing strategy for dynamic databases where new images are added to the databases frequently. The method is based on a two-stage classification framework using binary and multi-class SVMs. The proposed method also enforces balance in binary codes by an imbalance penalty to obtain higher quality binary codes. We learn hash functions by an efficient algorithm where the NP-hard problem of finding optimal binary codes is solved via cyclic coordinate descent and SVMs are trained in a parallelized incremental manner. For modifications like adding images from an unseen class, we propose an incremental procedure for effective and efficient updates to the previous hash functions. Experiments on three large-scale image datasets demonstrate that the incremental strategy is capable of efficiently updating hash functions to the same retrieval performance as hashing from scratch.

Efficient Image and Video Representations for Retrieval

Image (Video) retrieval is an interesting problem of retrieving images (videos) similar to the query. Images (Videos) are represented in an input (feature) space and similar images (videos) are obtained by finding nearest neighbors in the input representation space. Numerous input representations both in real valued and binary space have been proposed for conducting faster retrieval. In this thesis, we present techniques that obtain improved input representations for retrieval in both supervised and unsupervised settings for images and videos. Supervised retrieval is a well known problem of retrieving same class images of the query. We address the practical aspects of achieving faster retrieval with binary codes as input representations for the supervised setting in the first part, where binary codes are used as addresses into hash tables. In practice, using binary codes as addresses does not guarantee fast retrieval, as similar images are not mapped to the same binary code (address). We address this problem by presenting an efficient supervised hashing (binary encoding) method that aims to explicitly map all the images of the same class ideally to a unique binary code. We refer to the binary codes of the images as `Semantic Binary Codes' and the unique code for all same class images as `Class Binary Code'. We also propose a new class­ based Hamming metric that dramatically reduces the retrieval times for larger databases, where only hamming distance is computed to the class binary codes. We also propose a Deep semantic binary code model, by replacing the output layer of a popular convolutional Neural Network (AlexNet) with the class binary codes and show that the hashing functions learned in this way outperforms the state­ of ­the art, and at the same time provide fast retrieval times. In the second part, we also address the problem of supervised retrieval by taking into account the relationship between classes. For a given query image, we want to retrieve images that preserve the relative order i.e. we want to retrieve all same class images first and then, the related classes images before different class images. We learn such relationship aware binary codes by minimizing the similarity between inner product of the binary codes and the similarity between the classes. We calculate the similarity between classes using output embedding vectors, which are vector representations of classes. Our method deviates from the other supervised binary encoding schemes as it is the first to use output embeddings for learning hashing functions. We also introduce new performance metrics that take into account the related class retrieval results and show significant gains over the state­ of­ the art. High Dimensional descriptors like Fisher Vectors or Vector of Locally Aggregated Descriptors have shown to improve the performance of many computer vision applications including retrieval. In the third part, we will discuss an unsupervised technique for compressing high dimensional vectors into high dimensional binary codes, to reduce storage complexity. In this approach, we deviate from adopting traditional hyperplane hashing functions and instead learn hyperspherical hashing functions. The proposed method overcomes the computational challenges of directly applying the spherical hashing algorithm that is intractable for compressing high dimensional vectors. A practical hierarchical model that utilizes divide and conquer techniques using the Random Select and Adjust (RSA) procedure to compress such high dimensional vectors is presented. We show that our proposed high dimensional binary codes outperform the binary codes obtained using traditional hyperplane methods for higher compression ratios. In the last part of the thesis, we propose a retrieval based solution to the Zero shot event classification problem - a setting where no training videos are available for the event. To do this, we learn a generic set of concept detectors and represent both videos and query events in the concept space. We then compute similarity between the query event and the video in the concept space and videos similar to the query event are classified as the videos belonging to the event. We show that we significantly boost the performance using concept features from other modalities.

O ensino por investigação, favorecendo o desenvolvimento de atitudes e procedimentos : uma proposta didática aplicada em sala de aula

Dissertação (mestrado)—Universidade de Brasília, Decanato de Pesquisa e Pós-Graduação, Instituto de Ciências Biológicas, Instituto de Física, Instituto de Química, Faculdade UnB Planaltina, Programa de Pós-Graduação em Ensino de Ciências, Mestrado Profissional em Ensino de Ciências, 2016.

Assimetrias no crescimento e no desenvolvimento económico: um diagnóstico tridimensional da região do Algarve

Dissertação de Mestrado, Gestão Empresarial, Faculdade de Economia, Universidade do Algarve, 2015

Optimal resource allocation and budgeting in libraries

Libraries since their inception 4000 years ago have been in a process of constant change. Although, changes were in slow motion for centuries, in the last decades, academic libraries have been continuously striving to adapt their services to the ever-changing user needs of students and academic staff. In addition, e-content revolution, technological advances, and ever-shrinking budgets have obliged libraries to efficiently allocate their limited resources among collection and services. Unfortunately, this resource allocation is a complex process due to the diversity of data sources and formats required to be analyzed prior to decision-making, as well as the lack of efficient integration methods. The main purpose of this study is to develop an integrated model that supports libraries in making optimal budgeting and resource allocation decisions among their services and collection by means of a holistic analysis. To this end, a combination of several methodologies and structured approaches is conducted. Firstly, a holistic structure and the required toolset to holistically assess academic libraries are proposed to collect and organize the data from an economic point of view. A four-pronged theoretical framework is used in which the library system and collection are analyzed from the perspective of users and internal stakeholders. The first quadrant corresponds to the internal perspective of the library system that is to analyze the library performance, and costs incurred and resources consumed by library services. The second quadrant evaluates the external perspective of the library system; user’s perception about services quality is judged in this quadrant. The third quadrant analyses the external perspective of the library collection that is to evaluate the impact of the current library collection on its users. Eventually, the fourth quadrant evaluates the internal perspective of the library collection; the usage patterns followed to manipulate the library collection are analyzed. With a complete framework for data collection, these data coming from multiple sources and therefore with different formats, need to be integrated and stored in an adequate scheme for decision support. A data warehousing approach is secondly designed and implemented to integrate, process, and store the holistic-based collected data. Ultimately, strategic data stored in the data warehouse are analyzed and implemented for different purposes including the following: 1) Data visualization and reporting is proposed to allow library managers to publish library indicators in a simple and quick manner by using online reporting tools. 2) Sophisticated data analysis is recommended through the use of data mining tools; three data mining techniques are examined in this research study: regression, clustering and classification. These data mining techniques have been applied to the case study in the following manner: predicting the future investment in library development; finding clusters of users that share common interests and similar profiles, but belong to different faculties; and predicting library factors that affect student academic performance by analyzing possible correlations of library usage and academic performance. 3) Input for optimization models, early experiences of developing an optimal resource allocation model to distribute resources among the different processes of a library system are documented in this study. Specifically, the problem of allocating funds for digital collection among divisions of an academic library is addressed. An optimization model for the problem is defined with the objective of maximizing the usage of the digital collection over-all library divisions subject to a single collection budget. By proposing this holistic approach, the research study contributes to knowledge by providing an integrated solution to assist library managers to make economic decisions based on an “as realistic as possible” perspective of the library situation.

Direct Write Fabrication of Waveguides and Interconnects for Optical Printed Wiring Boards

Current copper based circuit technology is becoming a limiting factor in high speed data transfer applications as processors are improving at a faster rate than are developments to increase on board data transfer. One solution is to utilize optical waveguide technology to overcome these bandwidth and loss restrictions. The use of this technology virtually eliminates the heat and cross-talk loss seen in copper circuitry, while also operating at a higher bandwidth. Transitioning current fabrication techniques from small scale laboratory environments to large scale manufacturing presents significant challenges. Optical-to-electrical connections and out-of-plane coupling are significant hurdles in the advancement of optical interconnects. The main goals of this research are the development of direct write material deposition and patterning tools for the fabrication of waveguide systems on large substrates, and the development of out-of-plane coupler components compatible with standard fiber optic cabling. Combining these elements with standard printed circuit boards allows for the fabrication of fully functional optical-electrical-printed-wiring-boards (OEPWBs). A direct dispense tool was designed, assembled, and characterized for the repeatable dispensing of blanket waveguide layers over a range of thicknesses (25-225 µm), eliminating waste material and affording the ability to utilize large substrates. This tool was used to directly dispense multimode waveguide cores which required no UV definition or development. These cores had circular cross sections and were comparable in optical performance to lithographically fabricated square waveguides. Laser direct writing is a non-contact process that allows for the dynamic UV patterning of waveguide material on large substrates, eliminating the need for high resolution masks. A laser direct write tool was designed, assembled, and characterized for direct write patterning waveguides that were comparable in quality to those produced using standard lithographic practices (0.047 dB/cm loss for laser written waveguides compared to 0.043 dB/cm for lithographic waveguides). Straight waveguides, and waveguide turns were patterned at multimode and single mode sizes, and the process was characterized and documented. Support structures such as angled reflectors and vertical posts were produced, showing the versatility of the laser direct write tool. Commercially available components were implanted into the optical layer for out-of-plane routing of the optical signals. These devices featured spherical lenses on the input and output sides of a total internal reflection (TIR) mirror, as well as alignment pins compatible with standard MT design. Fully functional OEPWBs were fabricated featuring input and output out-of-plane optical signal routing with total optical losses not exceeding 10 dB. These prototypes survived thermal cycling (-40°C to 85°C) and humidity exposure (95±4% humidity), showing minimal degradation in optical performance. Operational failure occurred after environmental aging life testing at 110°C for 216 hours.

Assessment of the Occurrence and Potential Risks of Antibiotics and their Metabolites in South Florida Waters Using Liquid Chromatography Tandem Mass Spectrometry

An automated on-line SPE-LC-MS/MS method was developed for the quantitation of multiple classes of antibiotics in environmental waters. High sensitivity in the low ng/L range was accomplished by using large volume injections with 10-mL of sample. Positive confirmation of analytes was achieved using two selected reaction monitoring (SRM) transitions per antibiotic and quantitation was performed using an internal standard approach. Samples were extracted using online solid phase extraction, then using column switching technique; extracted samples were immediately passed through liquid chromatography and analyzed by tandem mass spectrometry. The total run time per each sample was 20 min. The statistically calculated method detection limits for various environmental samples were between 1.2 and 63 ng/L. Furthermore, the method was validated in terms of precision, accuracy and linearity. The developed analytical methodology was used to measure the occurrence of antibiotics in reclaimed waters (n=56), surface waters (n=53), ground waters (n=8) and drinking waters (n=54) collected from different parts of South Florida. In reclaimed waters, the most frequently detected antibiotics were nalidixic acid, erythromycin, clarithromycin, azithromycin trimethoprim, sulfamethoxazole and ofloxacin (19.3-604.9 ng/L). Detection of antibiotics in reclaimed waters indicates that they can’t be completely removed by conventional wastewater treatment process. Furthermore, the average mass loads of antibiotics released into the local environment through reclaimed water were estimated as 0.248 Kg/day. Among the surface waters samples, Miami River (reaching up to 580 ng/L) and Black Creek canal (up to 124 ng/L) showed highest concentrations of antibiotics. No traces of antibiotics were found in ground waters. On the other hand, erythromycin (monitored as anhydro erythromycin) was detected in 82% of the drinking water samples (n.d-66 ng/L). The developed approach is suitable for both research and monitoring applications. Major metabolites of antibiotics in reclaimed wates were identified and quantified using high resolution benchtop Q-Exactive orbitrap mass spectrometer. A phase I metabolite of erythromycin was tentatively identified in full scan based on accurate mass measurement. Using extracted ion chromatogram (XIC), high resolution data-dependent MS/MS spectra and metabolic profiling software the metabolite was identified as desmethyl anhydro erythromycin with molecular formula C36H63NO12 and m/z 702.4423. The molar concentration of the metabolite to erythromycin was in the order of 13 %. To my knowledge, this is the first known report on this metabolite in reclaimed water. Another compound acetyl-sulfamethoxazole, a phase II metabolite of sulfamethoxazole was also identified in reclaimed water and mole fraction of the metabolite represent 36 %, of the cumulative sulfamethoxazole concentration. The results were illustrating the importance to include metabolites also in the routine analysis to obtain a mass balance for better understanding of the occurrence, fate and distribution of antibiotics in the environment. Finally, all the antibiotics detected in reclaimed and surface waters were investigated to assess the potential risk to the aquatic organisms. The surface water antibiotic concentrations that represented the real time exposure conditions revealed that the macrolide antibiotics, erythromycin, clarithromycin and tylosin along with quinolone antibiotic, ciprofloxacin were suspected to induce high toxicity to aquatic biota. Preliminary results showing that, among the antibiotic groups tested, macrolides posed the highest ecological threat, and therefore, they may need to be further evaluated with, long-term exposure studies considering bioaccumulation factors and more number of species selected. Overall, the occurrence of antibiotics in aquatic environment is posing an ecological health concern.

Eulerian-Lagrangian definition of coarse bed-load transport: Theory and verification with low-cost inertial measurement units

Fluvial sediment transport is controlled by hydraulics, sediment properties and arrangement, and flow history across a range of time scales. This physical complexity has led to ambiguous definition of the reference frame (Lagrangian or Eulerian) in which sediment transport is analysed. A general Eulerian-Lagrangian approach accounts for inertial characteristics of particles in a Lagrangian (particle fixed) frame, and for the hydrodynamics in an independent Eulerian frame. The necessary Eulerian-Lagrangian transformations are simplified under the assumption of an ideal Inertial Measurement Unit (IMU), rigidly attached at the centre of the mass of a sediment particle. Real, commercially available IMU sensors can provide high frequency data on accelerations and angular velocities (hence forces and energy) experienced by grains during entrainment and motion, if adequately customized. IMUs are subjected to significant error accu- mulation but they can be used for statistical parametrisation of an Eulerian-Lagrangian model, for coarse sediment particles and over the temporal scale of individual entrainment events. In this thesis an Eulerian-Lagrangian model is introduced and evaluated experimentally. Absolute inertial accelerations were recorded at a 4 Hz frequency from a spherical instrumented particle (111 mm diameter and 2383 kg/m3 density) in a series of entrainment threshold experiments on a fixed idealised bed. The grain-top inertial acceleration entrainment threshold was approximated at 44 and 51 mg for slopes 0.026 and 0.037 respectively. The saddle inertial acceleration entrainment threshold was at 32 and 25 mg for slopes 0.044 and 0.057 respectively. For the evaluation of the complete Eulerian-Lagrangian model two prototype sensors are presented: an idealised (spherical) with a diameter of 90 mm and an ellipsoidal with axes 100, 70 and 30 mm. Both are instrumented with a complete IMU, capable of sampling 3D inertial accelerations and 3D angular velocities at 50 Hz. After signal analysis, the results can be used to parametrize sediment movement but they do not contain positional information. The two sensors (spherical and ellipsoidal) were tested in a series of entrainment experiments, similar to the evaluation of the 111 mm prototype, for a slope of 0.02. The spherical sensor entrained at discharges of 24.8 ± 1.8 l/s while the same threshold for the ellipsoidal sensor was 45.2 ± 2.2 l/s. Kinetic energy calculations were used to quantify the particle-bed energy exchange under fluvial (discharge at 30 l/s) and non-fluvial conditions. All the experiments suggest that the effect of the inertial characteristics of coarse sediments on their motion is comparable to the effect hydrodynamic forces. The coupling of IMU sensors with advanced telemetric systems can lead to the tracking of Lagrangian particle trajectories, at a frequency and accuracy that will permit the testing of diffusion/dispersion models across the range of particle diameters.

Evaluación de los contenidos de información de medicamentos en un grupo de agencias reguladoras de medicamentos

OBJETIVO: Evaluar las diferencias de información publicada por el Invima y otras Autoridades Reguladoras de Medicamentos en relación a un grupo de variables seleccionadas y analizar las diferencias aplicando estrategias de visualización de datos. METODOLOGÍA: Estudio descriptivo de corte transversal, en el cual se comparan las diferencias en la información de medicamentos publicada en las agencias reguladoras de medicamentos. Para la definición de los criterios de comparación, más relevantes se utilizó la técnica Delphi como metodología de consenso. Las visualizaciones fueron desarrolladas en Roassal, en el entorno de programación de Grafoscopio/Pharo. RESULTADOS Y CONCLUSIONES: De 24 variables en las que hubo acuerdo de considerarlas importantes y claves por el panel de expertos; el 96% se identificaron en la Aemps, MHRA e Infarmed; el 92% en Anmat, TGA, Anvisa, Health Canada y FDA; el 80% en Anamed. El grupo de agencias en las que se identificó una menor cantidad de información publicada fueron Cofepris, Invima, Dirección Nacional de Farmacias y Drogas de Panamá, Digemid, Arcsa y el Ministerio de Salud pública de Uruguay en las que se identificó el 67%, 58%, 46%, 46%, 38% y 4%, respectivamente. Las ausencias comunes de información en el grupo de agencias con menor cantidad de información se presentó en las variables relacionadas con usos fuera de indicación (off-label), gestión del riesgo, efectos adversos, restricciones especiales, precauciones y advertencias, prospecto, almacenamiento y resumen de las características del producto, es decir que mayor la limitación se presenta en la información relacionada con prescripción y uso.

Synthetic portfolio for event studies: Estimating the effects of volatility call auctions

We propose a method denoted as synthetic portfolio for event studies in market microstructure that is particularly interesting to use with high frequency data and thinly traded markets. The method is based on Synthetic Control Method and provides a robust data driven method to build a counterfactual for evaluating the effects of the volatility call auctions. We find that SMC could be used if the loss function is defined as the difference between the returns of the asset and the returns of a synthetic portfolio. We apply SCM to test the performance of the volatility call auction as a circuit breaker in the context of an event study. We find that for Colombian Stock Market securities, the asynchronicity of intraday data reduces the analysis to a selected group of stocks, however it is possible to build a tracking portfolio. The realized volatility increases after the auction, indicating that the mechanism is not enhancing the price discovery process.

Impacto de la implementación de un modelo de gestión integral de atención de la enfermedad y cuidado coordinado en la población en diálisis en Colombia

La atención hospitalaria en el costo global de la atención de los pacientes en diálisis es muy importante. Este estudio se realizó con el fin de evaluar resultados posteriores a la implementación de un modelo de gestión de la enfermedad y cuidado coordinado en una red de diálisis en Colombia, evaluando los cambios específicos en las tasas de hospitalización de una cohorte de pacientes renales con dos años de seguimiento. El modelo se enfoca básicamente en mejorar la atención de los pacientes en diálisis protocolizando en el manejo de comorbilidades (diabetes, riesgo cardiovascular, patologías infecciosas) y en el cuidado coordinado entre el tratamiento ambulatorio y hospitalario de los pacientes en diálisis asegurando la continuidad en el proceso de atención de los pacientes. El Estudio observacional analítico de cohortes compuesto por 2 fases una primera cohorte histórica retrospectiva y una segunda con dos cohortes prospectivas, incluyó pacientes mayores de 18 años, con más de 90 días en diálisis, con al menos tres meses de intervención con el modelo de gestión de enfermedad en la red Renal Therapy Services (RTS®). En conclusión, la realización de este estudio, se pudo asociar a la reducción en la atención hospitalaria de pacientes en diálisis y a una menor mortalidad, modelos como este y otras soluciones para mejorar los desenlaces en salud en los pacientes en diálisis deben seguir siendo implementados para aliviar la carga de la enfermedad y reducir los costos de la atención en salud de esta población.