Nursing records for discharge. Report of the nursing history

The quality of care within our health care system depends upon an active and dynamic communication which bridges the different levels of care (primary and hospital) and will permit a continuity of services between the distinct parts. To insure this success, the authors propose an outpatient nursing record that will follow the patient upon his or her discharge. This record, to be called the "Discharged Patient Report", will be directed to other medical professionals so that they can be informed of previous treatments that the patient has received. Included in the report will be items such as; the previous nursing interactions that were used on the patient, how problems were resolved, possible other solutions, and health care information given to the patient. Using the report in this way will give us a great tool to know our patients and better understand how to serve them.     

Analysis of interferograms with a spatial radial carrier or closed fringes and its holographic analogy

It is well known that an interferogram can be demodulated to find the wave-front shape if a linear carrier is introduced. We show that it can also be demodulated if it has many closed fringes or a circular carrier appears. A basic assumption is that the carrier fringes are of a bandwidth adequate to contain the wave-front distortion. This phase determination, called here demodulation, is made in the space domain, as opposed to demodulation in Fourier space, but the low-pass filter characteristics must be properly chosen. For academic purposes a holographic analogy of this demodulation process is also presented, which shows that the common technique of multiplying by a sine function and a cosine function is equivalent to holographically reconstructing with a tilted-flat wave front. Alternatively, a defocused (spherical) wave front can be used as a reference to perform the reconstruction or demodulation of some closed-fringe interferograms.     

Fractional-Fourier-transform calculation through the fast-Fourier-transform algorithm

A method for the calculation of the fractional Fourier transform (FRT) by means of the fast Fourier transform (FFT) algorithm is presented. The process involves mainly two FFT's in cascade; thus the process has the same complexity as this algorithm. The method is valid for fractional orders varying from -1 to 1. Scaling factors for the FRT and Fresnel diffraction when calculated through the FFT are discussed.     

Endoscopic sclerotherapy is useful in Dieulafoy''s disease

1.5% Capsaicin (Cap) or Vehicle was respectively used to treat the right or left sciatic nerve in 20 Sprague-Dawley rats. On the seventh day, the 20 rats were at random divided into electroacupuncture (EA) group and non-EA group, the spinal cord corresponding to the afferent segments of sciatic nerve was taken out for observing the changes of acetylcholinesterase (AChE) activity and [3H]-quinuelidinylbenzylate (QNB) binding sites in the spinal dorsal horn (SDH). The results were as follows: (1) EA "Huantiao" could enhance AChE activity in the SDH and decrease [3H]-QNB binding sites; (2) Cap treating sciatice nerve could weaken AChE activity in the SDH and merease [3H]-QNB binding sites; (3) Cap treatment could inhibit or partially inhibit the actions of EA as above. The results indicated that ACh participated in the primary afferent of acupuncture information and might exist in Cap-sensitive neurons.     

Solving identity delegation problem in the e-government environment

At present, many countries allow citizens or entities to interact with the government outside the telematic environment through a legal representative who is granted powers of representation. However, if the interaction takes place through the Internet, only primitive mechanisms of representation are available, and these are mainly based on non-dynamic offline processes that do not enable quick and easy identity delegation. This paper proposes a system of dynamic delegation of identity between two generic entities that can solve the problem of delegated access to the telematic services provided by public authorities. The solution herein is based on the generation of a delegation token created from a proxy certificate that allows the delegating entity to delegate identity to another on the basis of a subset of its attributes as delegator, while also establishing in the delegation token itself restrictions on the services accessible to the delegated entity and the validity period of delegation. Further, the paper presents the mechanisms needed to either revoke a delegation token or to check whether a delegation token has been revoked. Implications for theory and practice and suggestions for future research are discussed.     

SENFIS: a Sensor Node File System for increasing the scalability and reliability of Wireless Sensor Networks applications

In the last years the Wireless Sensor Networks’ (WSN) technology has been increasingly employed in various application domains. The extensive use of WSN posed new challenges in terms of both scalability and reliability. This paper proposes Sensor Node File System (SENFIS), a novel file system for sensor nodes, which addresses both scalability and reliability concerns. SENFIS can be mainly used in two broad scenarios. First, it can transparently be employed as a permanent storage for distributed TinyDB queries, in order to increase the reliability and scalability. Second, it can be directly used by a WSN application for permanent storage of data on the WSN nodes. The experimental section shows that SENFIS implementation makes an efficient use of resources in terms of energy consumption, memory footprint, flash wear levelling, while achieving execution times similarly with existing WSN file systems.     

An adaptive, real-time, traffic monitoring system

In this paper we describe a computer vision-based traffic monitoring system able to detect individual vehicles in real-time. Our fully integrated system first obtains the main traffic variables: counting, speed and category; and then computes a complete set of statistical variables. The objective is to investigate some of the difficulties impeding existing traffic systems to achieve balanced accuracy in every condition; i.e. day and night transitions, shadows, heavy vehicles, occlusions, slow traffic and congestions. The system we present is autonomous, works for long periods of time without human intervention and adapts automatically to the changing environmental conditions. Several innovations, designed to deal with the above circumstances, are proposed in the paper: an integrated calibration and image rectification step, differentiated methods for day and night, an adaptive segmentation algorithm, a multistage shadow detection method and special considerations for heavy vehicle identification and treatment of slow traffic. A specific methodology has been developed to benchmark the accuracy of the different methods proposed.     

Two-stage cascaded classification approach based on genetic fuzzy learning for speech/music discrimination

Automatic discrimination of speech and music is an important tool in many multimedia applications. The paper presents a robust and effective approach for speech/music discrimination, which relies on a two-stage cascaded classification scheme. The cascaded classification scheme is composed of a statistical pattern recognition classifier followed by a genetic fuzzy system. For the first stage of the classification scheme, other widely used classifiers, such as neural networks and support vector machines, have also been considered in order to assess the robustness of the proposed classification scheme. Comparison with well-proven signal features is also performed. In this work, the most commonly used genetic learning algorithms (Michigan and Pittsburgh) have been evaluated in the proposed two-stage classification scheme. The genetic fuzzy system gives rise to an improvement of about 4% in the classification accuracy rate. Experimental results show the good performance of the proposed approach with a classification accuracy rate of about 97% for the best trial.     

Modeling of the intrinsic stress effect on the resonant frequency of NEMS resonators integrated by beams with variable cross-section

Nano-electro-mechanical systems (NEMS) resonators integrated by a double clamped beam with variable cross-section are used in several applications such as chemical and biological detectors, high-frequency filters, and signal processing. The structure of these resonators can experience intrinsic stresses produced during their fabrication process. We present an analytical model to estimate the first bending resonant frequency of NEMS resonators based on a double clamped beam with three cross-sections, which considers the intrinsic stress effect on the resonant structure. This model is obtained using the Rayleigh and Macaulay methods, as well as the Euler–Bernoulli beam theory. We applied the analytical model to a silicon carbide (SiC) resonator of 186 nm thickness reported in the literature. This resonator has a total length ranking from 80 to 258 μm and is subjected to a tensile intrinsic stress close to 110 MPa. Results from this model show good agreement with experimental results. The analytic frequencies have a maximum relative difference less than 6.3% respect to the measured frequencies. The tensile intrinsic stress on the resonant structure causes a significantly increase on its bending resonant frequency. The proposed model provides an insight into the study of the intrinsic stress influence on the resonant frequency of this nanostructure. In addition, this model can estimate the frequency shift due to the variations of the resonator geometrical parameters.     

Semi-formal transformation of secure business processes into analysis class and use case models: An MDA approach

ContextModel-Driven Development (MDD) is an alternative approach for information systems development. The basic underlying concept of this approach is the definition of abstract models that can be transformed to obtain models near implementation. One fairly widespread proposal in this sphere is that of Model Driven Architecture (MDA). Business process models are abstract models which additionally contain key information about the tasks that are being carried out to achieve the company’s goals, and two notations currently exist for modelling business processes: the Unified Modelling Language (UML), through activity diagrams, and the Business Process Modelling Notation (BPMN).ObjectiveOur research is particularly focused on security requirements, in such a way that security is modelled along with the other aspects that are included in a business process. To this end, in earlier works we have defined a metamodel called secure business process (SBP), which may assist in the process of developing software as a source of highly valuable requirements (including very abstract security requirements), which are transformed into models with a lower abstraction level, such as analysis class diagrams and use case diagrams through the approach presented in this paper.MethodWe have defined all the transformation rules necessary to obtain analysis class diagrams and use case diagrams from SBP, and refined them through the characteristic iterative process of the action-research method.ResultsWe have obtained a set of rules and a checklist that make it possible to automatically obtain a set of UML analysis classes and use cases, starting from SBP models. Our approach has additionally been applied in a real environment in the area of the payment of electrical energy consumption.ConclusionsThe application of our proposal shows that our semi-automatic process can be used to obtain a set of useful artifacts for software development processes.