New techniques for implementing membrane systems

Biomolecular computing is the focus of this thesis. In particular, the area of computing with the membranes of the living cells commonly referred as ‘membrane computing’ or ‘transition P-systems’. It introduces the concept of ‘adaptability’. The new idea of “adaptability “appears in this work. Adaptability means the ability for the membrane computing model to interact with other technologies in order to obtain optimal results when dealing with complex problems. In fact, new scenarios containing P-systems are shown. These scenarios have the transition P-systems working together with other technologies. Furthermore, methodologies and new software are introduced to implement the evolution rules application phase within membrane computing. These methodologies and software improve P-system’s functionality by processing the information in a faster way. This is especially useful to obtain optimal results when dealing with complex problems such as NP-complete problems. In particular this thesis reveals: Transition P-systems as an adaptable technology as they can interact with Multi-agent Systems and with robots to acquire an optimal performance. A random function to implement the evolution rules application phase is defined to make the model less deterministic. Moreover, introduced here are new techniques for evolution rules application that improve the current performance of the P-systems when solving problems that have a high computational complexity. The techniques described in this thesis use solutions of linear system Diophantine equations, data structures (virtual or physical) and probabilistic and statistical patterns. Este tesis se encuadra en computacion biomolecular y de una manera mas especifica en el area de las propiedades de las celulas vivas. Este area es conocida como computacion de membranas. Esta tesis introduce el concepto de adaptabilidad en la computacion de membranas. Se entiende por adaptabilidad como la habilidad de los P-sistemas de transicion para interactuar con otras tecnologias obteniendo resultados optimos en resolucion de problemas complejos. Se muestran, por tanto, escenarios compuestos y modelos nuevos que tienen a los P-sistemas como actores. Ademas, metodologias y software nuevos se proponen para manejar e implementar la fase de aplicacion de reglas de evolucion que ocurre cuando los P-sistemas evolucionan. Las metodologias y software que aqui se presentan mejoran la funcionalidad de los P-sistemas, procesando la informacion de manera mucho mas rapida. Esto es especialmente util para obtener resultados optimos cuando se resuelven problemas complejos como los problemas NP-completos. De manera mas especifica, esta tesis desarrolla: P-sistemas como una tecnologia adaptable donde de muestra un enlace entre los P- sistemas y los sistemas Multi-agente asi como un escenario donde varios robots autonomos y p-sistemas trabajan juntos para resolver problemas complejos. Se propone una funcion aleatoria para implementar el modelo de la fase de aplicacion de reglas de evolucion para que sea mas no determinista. Se crean nuevas tecnicas de aplicacion de reglas de evolucion que mejoran sensiblemente el rendimiento actual de los p-sistemas cunado resuelven problemas de gran complejidad. Una de ellas utiliza estructuras auxiliares en memoria principal. Otra usa la resolucion de ecuaciones lineales diofanticas y otra, sigue patrones probabilisticos y estadisticos

MEIA SYSTEMS: Membrane Encrypted Information Applications Systems

Membrane computing is a recent area that belongs to natural computing. This field works on computational models based on nature's behavior to process the information. Recently, numerous models have been developed and implemented with this purpose. P-systems are the structures which have been defined,developed and implemented to simulate the behavior and the evolution of membrane systems which we find in nature. What we show in this paper is a new model that deals with encrypted information which provides security the membrane systems communication. Moreover we find non deterministic and random applications in nature that are suitable to MEIA systems. The inherent parallelism and non determinism make this applications perfect object to implement MEIA systems

Virtual Membrane Systems

Within the membrane computing research field, there are many papers about software simulations and a few about hardware implementations. In both cases, algorithms for implementing membrane systems in software and hardware that try to take advantages of massive parallelism are implemented. P-systems are parallel and non deterministic systems which simulate membranes behavior when processing information. This paper presents software techniques based on the proper utilization of virtual memory of a computer. There is a study of how much virtual memory is necessary to host a membrane model. This method improves performance in terms of time

Differential Evoluiton - Particle Swarm Optimization

This paper shows the Particle Swarm Optimization algorithm with a Differential Evolution. Each candidate solution is sampled uniformly in [!5,5] D, whereDdenotes the search space dimension, and the evolution is performed with a classical PSO algorithm and a classical DE/x/1 algorithm according to a random threshold

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Towards the Natural Optimization with Particle Swarm Optimization.

This paper shows the Particle Swarm Optimization algorithm with a Differential Evolution. Each candidate solution is sampled in the interval [?5, 5] D where D indicates the dimension of the search space, and the evolution is performed with a classical PSO algorithm and a classical DE/x/1 algorithm according to a random threshold. Moreover, this paper provides concepts to deal with non-linear optimization through the use of PSO

Multidimensional knapsack problem optimization using a binary particle swarm model with genetic operations.

Particle swarm optimization is a heuristic and stochastic technique inspired by the flock of birds when looking for food. It is currently being used to solve continuous and discrete optimization problems. This paper proposes a hybrid, genetic inspired algorithm that uses random mutation/crossover operations and adds penalty functions to solve a particular case: the multidimensional knapsack problem. The algorithm implementation uses particle swarm for binary variables with a genetic operator. The particles update is performed in the following way: first using the iterative process (standard algorithm) described in the PSO algorithm and then using the best particle position (local) and the best global position to perform a random crossover/mutation with the original particle. The mutation and crossover operations specifically apply to personal and global best individuals. The obtained results are promising compared to those obtained by using the probability binary particle swarm optimization algorithm

Tele-Treatment Application Design for Disable Patients with Wireless Sensors

This paper consists of the development of a system to help patients with different disabilities, affected by rare or chronic diseases or any kind of dependence through tele assistance, virtual interaction and intelligent monitoring. The main goal is to increase the quality of life of the minorities who cannot take full advantage of the healthcare system by providing an alternative way of monitoring them with the technology embedded in this paper. The result of the paper is not intended to be a single solution, but a modular system that allows the construction of an application that is able to measure the needs of a health administration and the patients. The paper also pursues an educational training to the facultative trainees in a new way to approach patient treatments. It can improve the quality of life of the patients by saving them time and other resources in moving to the Health center and the professionals can also save time as they can take advantage of the online treatments by using the proposed system