Introduction to linear and nonlinear programming

Dielectric relaxation and NMR spectrum of water in biological systems such as proteins, DNA, and reverse micelles can often be described by two widely different time constants, one of which is in the picosecond while the other is in the nanosecond regime. Although it is widely believed that the bimodal relaxation arises from water at the hydration shell, a quantitative understanding of this important phenomenon is lacking. In this article we present a theory of dielectric relaxation of biological water. The time dependent relaxation of biological water is described in terms of a dynamic equilibrium between the free and bound water molecules. It is assumed that only the free water molecules undergo orientational motion; the bound water contribution enters only through the rotation of the biomolecule, which is also considered. The dielectric relaxation is then determined by the equilibrium constant between the two species and the rate of conversion from bound to free state and vice versa. However, the diele...

/pdf/dielectric-relaxation-of-biological-water-2zevupbr37.pdf

Dielectric Relaxation of Biological Water

The internet of things (IoT) aims to extend the internet to real-world objects, connecting smart and sensing devices into a global network infrastructure by connecting physical and virtual objects. The IoT has the potential to increase the quality of life of inhabitants and users of intelligent ambient assisted living (AAL) environments. The paper overviews and discusses the IoT technologies and their foreseen impacts and challenges for the AAL domain. The results of this review are summarized as the IoT based gerontechnology acceptance model for the assisted living domain. The model focuses on the acceptance of new technologies by older people and underscores the need for the adoption of the IoT for the AAL domain.

https://www.mdpi.com/1999-5903/11/12/259/pdf

A Review of Internet of Things Technologies for Ambient Assisted Living Environments

Apparatus and method for non-invasive diagnosis of cardiovascular and related disorders. The system establishes a correspondence between the dynamics of the wave contour of the arterial pressure pulse and the associated disease states. The system comprises an input module, a contour signal receiver, and a processing module. The input module utilizes a pressure transducer for taking a non-invasive measurement of the arterial pulse. The contour signal receiver amplifies, digitizes and normalizes the arterial pressure pulse signal. In the processing module, the normalized arterial pressure contour is subjected to wavelet analysis, which transforms the dynamics of the time series of arterial blood pressure contour into multi-resolution wavelet coefficients or signatures. The processing module includes a neural network which is trained to associate the diagnostic features of the transformed arterial pressure contour embedded in the coefficients with a disease condition. After the learning phase, the system is capable of diagnosing known cardiovascular conditions in patients.

Method and apparatus for non-invasive diagnosis of cardiovascular and related disorders

Evaluation of complex permittivity of aqueous solution by time domain reflectometry

Study of Bound Water of Poly-Adenine Using High Frequency Dielectric Measurements

An algorithm for fast minimum search is proposed, which achieves very satisfying performance harmonising the Vogl's and the Conjugate Gradient algorithms. Such effectiveness is achieved by making adaptive, in a very simple and satisfactory way, both the learning rate and the momentum term, and by executing controls and corrections both on the possible cost function increase and on moves opposite to the direction of the negative of the gradient. Thanks to these improvements, we can obtain a good scaling relationship in learning. As regards the real world context, a musical application showed favourable results: besides the good convergence speed, a high generalisation capability has been achieved, as confirmed both by subjective musical evaluations and by objective tests.

An Adaptive Momentum Back Propagation (AMBP)

An application of the back-propagation (BP) neural network (NN) for the discrimination between normal and pathological electrocardiogram (ECG) complexes is presented. The BP is used as a part of an unsupervised method: the network output has not been used to discriminate normal and pathological complexes, but only to extract the prototype complex of the analyzed ECG. An attempt is made to automatically individualize a pathological QRS morphology on those ECGs where anomalous premature ventricular contraction (PVC) beats were less than 15%. Results show a sensitivity of 0.991 and a specificity of 0.985. >

Neural network for automatic anomalous QRS complex detection

The correlation dimensions of random noise and electrocardiograms of both normal and sick subjects have been analyzed and compared. The noisy signal has been obtained by using the random function of a DEC VAX computer; ECG data have been obtained from the MIT-BIH Arrhythmia Data Base. It was expected that a lower dimensionality of the ECG signal would be obtained with respect to the noisy one. This hypothesis has been confirmed by the analysis. An attempt was made to evaluate differences in the dimensionality of sick and normal subjects. The complexity and time-consuming aspects of the computations made it possible to examine only four patients. Up to now, there has not been enough evidence of significant differences between sick and normal subjects, and thus it is necessary to increase the number of analyzed cases. In order to obtain a good saturation of the correlation dimension, the embedding space has been spanned from 2 to 50. >

Study of the correlation dimension of ECG signals based on MIT-BIH Arrhythmia Data Base ECGs

The paper presents the outline and the preliminary developments of NINFA (iNtelligent Integrated Network For Aged people), a project for the well-being of the elderly people at home. This architecture is based on a service platform suited for elder people called the Virtual Village Network, whose user interface allows to deliver different services at home, namely: user supervision, communication and interaction among users for social inclusion, exergame delivering, monitoring of the wellness status. After the discussion of some results of the investigation on the acceptability issues of the ICT technologies related to the project, the User Interface (UI) and the novel Human Computer Interface (HCI) have been developed. The HCI is particularly suited for elderly people and motor impaired patients because the interaction is managed only by finger/hand gestures and by vocal control through simple commands. A set of preliminary exergames developed for the user training and monitoring are presented. During the exergame execution, the user interface allows the real-time acquisition of a set of motor, linguistic and cognitive parameters related to the user performance. The analysis of the verbal production of each subject is used to observe its language evolution and to detect the onset of any cognitive deficit. The relationship between some parameters and the neurological/wellness status of the user is discussed.

An Integrated Approach to the Well-Being of the Elderly People at Home

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