A system identification approach to baroreflex sensitivity estimation

The body contains a bewildering array of regulatory systems which maintain homeostasis. There is considerable difficulty in isolating a single control loop for analysis, due to the interactions with other systems/loops. One important such regulatory loop is the baroreflex, and baroreflex sensitivity is a characteristic open-loop parameter which can help us to assess the health of the baroreflex. A diverse range of methods have been proposed to determine baroreflex sensitivity from experimental data. Unfortunately, there appears to be little consistency of result among the different methods and some explanation can be found in the nature of the problem: In most cases, an attempt is being made to determine open-loop measures from a system operating in closed-loop, subject to poor excitation. In this paper we propose a strict procedure, based on a rigourous mathematical framework, from which reliable estimates of baroreflex sensitivity can be obtained. A comparison with other methods for baroreflex sensitivity estimation, using the EuroBaVar data set, is performed

A system identication approach to baroreflex sensitivity estimation

The body contains a bewildering array of regulatory systems which maintain homeostasis. There is considerable dificulty in isolating a single control loop for analysis, due to the interactions with other systems/loops. One important such regulatory loop is the baroreflex, and baroreflex sensitivity is a characteristic open-loop parameter which can help us to assess the health of the baroreflex. A diverse range of methods have been proposed to determine baroreflex sensitivity from experimental data. Unfortunately, there appears to be little consistency of result among the different methods and some explanation can be found in the nature of the problem: In most cases, an attempt is being made to determine open-loop measures from a system operating in closed-loop, subject to poor excitation. In this paper we propose a strict procedure, based on a rigourous mathematical framework, from which reliable estimates of baroreflex sensitivity can be obtained. A comparison with other methods for baroreflex sensitivity estimation, using the EuroBaVar data set, is performed

Detailed structural elucidation of polyesters and acrylates using Fourier transform mass spectrometry

The detailed structural characterization of complex polymer architectures, like copolymers and polymer mixtures, by mass spectrometry presents a challenge. Even though soft ionization analyses revolutionized the characterization of large molecules and provided a means for determining the polymer’s molecular weight distribution, polydispersity, and end groups, full microstructure elucidation and monomer sequencing by soft ionization alone is not possible. The combination of high-resolution Fourier transform mass spectrometry (FTMS) and tandem mass spectrometry (MSn) provides a powerful analytical tool for addressing these challenges. This tool was used in our work to separate and identify the products of polymerization between 12-hydroxystearic acid (HSA) and stearic acid (SA), to provide precise information about the exact location of caprolactones on the Tris(2-hydroxyethyl)isocyanurate (THEIC) molecule, and to sequence a glycidyl methacrylate/methyl methacrylate (GMA/MMA) copolymer. The results highlight the value of ultrahigh resolution and tandem mass spectrometry for fine structural characterization and sequencing of polymers

A 5-component model for salt-induced hypertension

Salt-induced hypertension has been widely studied in rats, monkeys, chimpanzees and humans. Until recently, the multiple phases of this blood pressure increase to high salt intake had not been closely studied. This work builds upon a recent study, which developed a grey-box multicomponent model of salt-induced hypertension in the Dahl-S rat. The previous 3-component model has been extended here to include additional model dynamics to improve the model fit and add new important elements to the model response. The model was optimised using numerical techniques with experimental data from 4 different protocols with Dahl-S and hybrid rats. Results show a marked improvement over the previous model and confirm the merit of the 5-component model structure

THE INFLUENCE OF CROP ROTATION, ROTATION AND FERTILIZATION ON YIELD SUNFLOWER IN CLIMATIC CONDITIONS FROM VALUL LUI TRAIAN

The work paper includes the results of research regarding the influence of fertilization androtation on the yield to sunflower. The analyze dresults has been obtained in experiment splaced at the Research Stationand Agricultural Development Valu Traian which contain stwo crop rotations, a new one is installed atfour years so lajumpercultivated with alfalfaandotherold one oftwenty-sixyears, both rotating with the same four crops. The sunflower, which is the subjectof our experiment, follows thewinter wheat in rotation of four years. The sunfloweris a plant with less demanding for the previous plant. It shouldn’t be cultivated earlier than six years after self or plants with common diseases. The rotation should be considered the most efficient measureto fight with the crop diseases and pests

A 5-component mathematical model for salt-induced hypertension in Dahl-S and Dahl-R rats

Salt-induced hypertension has been demonstrated in a variety of species including rats, monkeys, chimpanzees and humans. Until recently, the multiple phases of this blood pressure increase due to high salt intake had not been closely studied. This work builds upon a recent study, which developed a grey-boxmulti-component model of salt-induced hypertension in the Dahl-S rat. The previous 3-component model has been extended here to include additional model dynamics to improve the model fit and add new important elements to the model response. The model was optimised using numerical techniques with experimental data from 4 different protocols with Dahl-S, Dahl-R and FF2 hybrid rats. Results show a marked improvement over the previous model and confirm the merit of the 5-component model structure. A comparison between the model dynamics for different rat strains has also been include