Development of a Control Strategy in an Isokinetic Device for Physical Rehabilitation.

Robotic-assisted rehabilitation is currently being applied to improve the effectiveness of human gait rehabilitation and recover the mobility and strength after a stroke or spinal cord injury; a robotic assistant can allow the active participation of the patient and the supervision of the collected data and decrease the labor required from therapists during the patient's training exercises. The goal of gait rehabilitation with robotic-based assistance is to restore motor function by using diverse control strategies, taking account of the physical interaction with the lower limbs of the patient. Over the last few years, researchers have extracted useful information from the patient's biological signals that can effectively reflect movement intention and muscle activation. One way to evaluate progress in rehabilitation is through isokinetic prototype tests that describe the dynamic characteristics of an isokinetic leg extension device for rehabilitation and control action. These tests use an isokinetic system to assess muscle strength and performance in a patient during isometric or isokinetic contraction. An experimental prototype shown in the following work allows the device's performance to be evaluated in a controlled environment before the patient's use. New features provide a control system that can be teleoperated for distributed structures, enabling the remote operation and management of the device. In order to achieve physical recovery from musculoskeletal injuries in the lower limbs and the reintegration of the affected subject into society as an independent and autonomous individual in their daily activities, a control model that introduces a medical isokinetic rehabilitation protocol is presented, in which the element that carries out such protocol consists of a magnetic particle brake whose control action is strongly influenced by the dynamics of the system when in contact with the end user-specifically, the patient's legs in the stretch from the knee to the ankle. The results of these tests are valuable for health professionals seeking to measure their patient's progress during the rehabilitation process and determine when it is safe and appropriate to advance in their treatment.

A novel kinetic model for a cocoa waste fermentation to ethanol reaction and its experimental validation.

A non-segregated kinetic model is proposed to describe a fermentation process of agro-industrial residues derived via cocoa (mucilage juice) by Pichia kudriavzevii. The novel proposed hybrid model is based on a multiple coupling reaction mechanisms (structured) to describe the kinetics of substrate consumption, biomass, carbon dioxide, and ethanol, coupled to an unstructured model for the activity enzyme. The parameters of the kinetic model are estimated by non-linear least-squares curve fitting using the Marquardt-Levenberg algorithm. In addition, numerical simulations were compared with the experimental data via residual graphs. The effectiveness of the model was statistically evaluated using dimensionless efficiency coefficients under different initial conditions. A global sensitivity analysis was applied (Fisher's information matrix). The experimental results of the batch reactor showed a maximum ethanol concentration of 29 g/L, with a yield of 0.48 g-ethanol/g-glucose and a productivity of 0.30 g/L h. The method determined that the cell formation coefficient and the specific substrate consumption rate (θ1 and θ2) directly influence most of the states of our system. The proposed scheme is particularly suitable to assist in the rational design of cell factory properties or fermentation processes because it can represent the complex biochemistry in more detail and under different initial experimental conditions; the above reveals that the generated model is robust and can be considered for control and optimization purposes.

Modelagem dinâmica e cenários urbanos de demanda de água: simulações em Campina Grande (PB) / Dynamic modeling and urban water demand scenarios: simulations in Campina Grande-PB

RESUMO Este trabalho propõe estimativas de demanda de água para cenários futuros de uso e ocupação do solo e de verticalização utilizando análises espaciais e modelagem dinâmica com base em autômatos celulares para uma fração urbana do município de Campina Grande (PB). Dados reais de uso e ocupação do solo e de verticalização dos anos de 2011 e 2018 são utilizados para identificar o processo de mudança nesses bairros. Um conjunto de variáveis estáticas e dinâmicas relacionadas é selecionado para subsidiar a parametrização do modelo e simular as mudanças no uso e ocupação do solo e na verticalização, ocorridas no período. Após a validação das simulações para o ano de 2018 com base nos dados observados, novos cenários futuros são propostos para os anos de 2040, 2070 e 2100, identificando, assim, uma tendência de ocupação com algumas características específicas, como a substituição de áreas residenciais de um ou dois pavimentos por novos empreendimentos verticais, seja residencial, empresarial ou de serviços. Dado o aumento de ocupação urbana, as demandas de água capazes de atender à população também aumentam, aumento este que se confirmou neste trabalho. Entre os anos 2018 e 2100, essa tendência de aumento foi estimada em 300%. Uma comparação de cenários futuros considerando usos convencionais e racionais de água (utilizando mecanismos poupadores) também é apresentada.

ABSTRACT This work estimates urban water demands for future land-use scenarios using spatial analysis and dynamic modeling based on cellular automata for an urban area of the city of Campina Grande, Paraíba State, Brazil. Ground truth for two dates (2011 and 2018) is used to identify the process of land-use change in these neighborhoods. Some static and dynamic variables are defined in order to support the model parameterization and to simulate the changes occurred in the period. After the validation of those simulations for 2018, based on the observed data, new future scenarios are proposed for the years 2040, 2070, and 2100, thus identifying a tendency of occupation with some specific characteristics such as the replacement of residential areas new buildings with multiple floors, whether residential, business, or services. Due to the increase in urban occupation, the water demands for attending to the population also increase. Between 2018 and 2100, this upward trend is estimated at 300%. A comparison of future scenarios considering conventional and rational water uses (using saving mechanisms) is also simulated.

Modelación dinámica del comportamiento hidrológico de un humedal urbano bajo condiciones del fenómeno ENSO / Dynamic modeling of the hydrological behavior of an urban wetland under conditions of ENSO phenomenon

RESUMEN El estado actual y las continuas alteraciones que aquejan a los humedales ubicados en la ciudad de Bogotá (Colombia), motiva el desarrollo de instrumentos y herramientas, que permitan explicar su comportamiento hidrológico bajo tensiones climáticas, como lo es el fenómeno ENSO. Este artículo presenta la formulación de un modelo de las condiciones hidrológicas del humedal urbano de Torca. La simulación, se realizó con el software Vensim® y la validación estadística del modelo, se efectuó mediante un análisis de sensibilidad multivariable (MVSS), a partir del método Montecarlo. Se evidenció que en los años de ocurrencia del fenómeno climatológico ENSO (2001) y (2011), el patrón de comportamiento de la precipitación y del flujo de entrada (Qi) de la cuenca aferente del humedal fueron paralelos. El tiempo hidráulico de retención (THR) sugirió un comportamiento inverso con relación a la precipitación. En efecto, la precipitación promedio mensual fue de 47,8mm y 158,7mm y el THR promedio fue de 55 días y 33 días, para los años El Niño y La Niña, respectivamente. El flujo de entrada y de salida presentaron un comportamiento paralelo durante el período de estudio, debido, probablemente, a que el cuerpo de agua se convirtió en un cauce de salida. Durante El Niño, cuatro meses registraron desbordamiento del humedal (junio, septiembre, octubre y diciembre), con volúmenes de agua superiores a 130.645m3. Durante La Niña, todos los meses registraron desbordamiento del humedal, a excepción de agosto y septiembre, en donde se observaron volúmenes de agua de 100.018m3 y 109.166m3, respectivamente.

ABSTRACT The current state and the continuous changes that affect the wetlands located in the city of Bogotá (Colombia), motivates the development of instruments and tools that illustrate their hydrological behavior under climatic stresses such as the ENSO phenomenon. This article presents the formulation of a model of the hydrological conditions of the urban wetland of Torca. The simulation was carried out with the Vensim® software and the statistical validation of the model was carried out by means of a multivariate sensitivity analysis (MVSS) using the Montecarlo method. It was evidenced that in the years of occurrence of the ENSO climatological phenomenon (2001) and (2011), the behavior pattern of precipitation and inflow (Qi) of the afferent basin of the wetland were parallel. Hydraulic retention time (THR) suggested an inverse behavior in relation to precipitation. Indeed, the average monthly rainfall was 47,8mm and 158,7mm, and the average THR was 55 days and 33 days for the El Niño and La Niña years, respectively. The inflow and outflow presented a parallel behavior during the study period, probably due to the fact that the body of water became an outlet channel. During El Niño, the wetland overflowed for four months (June, September, October and December), with volumes exceeding 130,645m3. During La Niña, the wetland overflowed every month; except for August and September, where volumes of 100.018m3 and 109.166m3 were observed, respectively.

Dynamic Modeling of CHO Cell Metabolism Using the Hybrid Cybernetic Approach With a Novel Elementary Mode Analysis Strategy.

Chinese hamster ovary (CHO) cell culture has a major importance on the production of biopharmaceuticals, including recombinant therapeutic proteins such as monoclonal antibodies (MAb). Mathematical modeling of biological systems can successfully assess metabolism complexity while providing logical and systematic methods for relevant genetic target and culture parameter identification toward cell growth and productivity improvements. Most modeling approaches on CHO cells have been performed under stationary constraints, and only a few dynamic models have been presented on simplified reaction sets, due to substantial overparameterization problems. The hybrid cybernetic modeling (HCM) approach has been recently used to describe the dynamic behavior by incorporating regulation between different metabolic states by elementary mode participation control, with sets of equations evaluated by objective functions. However, as metabolic networks evaluated are constructed toward a genomic scale, and cell compartmentalization is considered, identification of the active set becomes more difficult as EM number exponentially grows. Thus, the development of robust approaches for EM active set selection and analysis with smaller computational requirements is required to impulse the use of cybernetic modeling on larger up to genome-scale networks. In this report, a novel elementary mode selection strategy, based on a polar representation of the convex solution space is presented and coupled to a cybernetic approach to model the dynamic physiologic and metabolic behavior of CHO-S cell cultures. The proposed Polar Space Yield Analysis (PSYA) was compared to other reported elementary mode selection approaches derived from Common Metabolic Objective Analysis (CMOA) used in Flux Balance Analysis (FBA), Yield Space Analysis (YSA), and Lumped Yield Space Analysis (LYSA). For this purpose, exponential growth phase dynamic metabolic models were calculated using kinetic rate equations based on previously modeled growth parameters. Finally, complete culture dynamic metabolic flux models were constructed using the HCM approach with selected elementary mode sets. The yield space elementary mode- and the polar space elementary mode- hybrid cybernetic models presented the best fits and performances. Also, a flux reaction perturbation prediction approach based on the polar yield solution space resulted useful for metabolic network flux distribution capability analysis and identification of potential genetic modifications targets.

Cooling Effectiveness of a Data Center Room under Overhead Airflow via Entropy Generation Assessment in Transient Scenarios.

Forecasting data center cooling demand remains a primary thermal management challenge in an increasingly larger global energy-consuming industry. This paper proposes a dynamic modeling approach to evaluate two different strategies for delivering cold air into a data center room. The common cooling method provides air through perforated floor tiles by means of a centralized distribution system, hindering flow management at the aisle level. We propose an idealized system such that five overhead heat exchangers are located above the aisle and handle the entire server cooling demand. In one case, the overhead heat exchangers force the airflow downwards into the aisle (Overhead Downward Flow (ODF)); in the other case, the flow is forced to move upwards (Overhead Upward Flow (OUF)). A complete fluid dynamic, heat transfer, and thermodynamic analysis is proposed to model the system's thermal performance under both steady state and transient conditions. Inside the servers and heat exchangers, the flow and heat transfer processes are modeled using a set of differential equations solved in MATLAB™ 2017a. This solution is coupled with ANSYS-Fluent™ 18, which computes the three-dimensional velocity, temperature, and turbulence on the Airside. The two approaches proposed (ODF and OUF) are evaluated and compared by estimating their cooling effectiveness and the local Entropy Generation. The latter allows identifying the zones within the room responsible for increasing the inefficiencies (irreversibilities) of the system. Both approaches demonstrated similar performance, with a small advantage shown by OUF. The results of this investigation demonstrated a promising approach of data center on-demand cooling scenarios.

Transfer and consumption of oxygen during the cultivation of the ectomycorrhizal fungus Rhizopogon nigrescens in an airlift bioreactor.

The study had the objective of examining the aspects involved in the cultivation of ectomycorrhizal fungi for the production of commercially sustainable inoculant to attend the demands of the seedling nursery industry. It focused on certain parameters, such as the oxygen consumption levels, during the cultivation of the ectomycorrhizal fungus Rhizopogon nigrescens CBMAI 1472, which was performed in a 5-L airlift bioreactor. The dynamic method was employed to determine the volumetric coefficient for the oxygen transfer (k L a) and the specific oxygen uptake rate (Q O2 ). The results indicate that specific growth rates (µ X ) and oxygen consumption decline rapidly with time, affected mainly by increases in biomass concentration (X). Increases in X are obtained primarily by increases in the size of pellets that are formed, altering, consequently, the cultivation dynamics. This is the result of natural increases in transferring resistance that are observed in these environments. Therefore, to avoid critical conditions that affect viability and the productivity of the process, particular settings are discussed.