Development of an Al-load-cell-based wireless ringer's solution monitoring and alarm system: insight into vibrational error correction

In this study, we developed an aluminum-load-cell-based wireless Ringer's solution monitoring and alarm (WRMA) system. The Al load cell was designed with a rectangular shape, and the load was concentrated in the lower beam part of the load cell because of the anisotropic thickness. From the static analysis, we identifi ed the appropriate location for a Wheatstone bridge circuit consisting of four strain gauges. In addition, the modal and harmonic analyses showed that the vibrational frequencies of the hospital environment do not seriously interfere with the output voltage of the Al load cell. However, random vibrations generated by the movement of the WRMA system on various surfaces severely increase the standard deviation of the measured solution weight by ± 10 g or more. Such vibrational error is too large because the average weight of Ringer's solution is 30–40 g at the time of replacing Ringer's solution. Thus, this error could be confusing for nurses and result in mistakes in the timely replacement of the Ringer's solution. However, the standard deviation of the measured weight was dramatically reduced to ± 3 g or less by using the vibration correction algorithm developed in the present study.

Dynamic Characteristics of an Adolescent Idiopathic Scoliotic Spine / 医用生物力学

Objective To establish the three-dimensional (3D) finite element (FE) model of thoracolumbosacral T1-S spine based on the computed tomography (CT) images of patients with scoliosis and study its dynamic characteristics. Methods The established scoliotic model was validated by axial compression and shear loading, and the predicted responses were in good agreement with the experimental data. The modal and harmonic analyses were performed using the ABAQUS software, and during the harmonic analysis, the dynamic response of the model was collected at frequencies 5 Hz and 10 Hz. Results From the modal analysis, the first fourth-order modal was extracted. The first- and second-order resonant frequencies of the model were 1.097 Hz and 1.384 Hz, respectively, and the vibration mode was longitudinal bending and lateral bending, respectively. The distribution of the second- and third-order modal resonant frequencies were 5.688 Hz and 28.090 Hz, and the vibration mode was vertical vibration and twisting around the long axis, respectively. The peak amplitude in the harmonic analysis appeared near the modal frequencies, and the average amplitude of vertebral body of the lateral convex segment was larger than that of other segments of the scoliotic spine. Under the vibration frequencies of 5 Hz and 10 Hz, the stress inhomogeneously concentrated on the concave and convex sides of the segments of the vertebral deformity as well as on the intervertebral disc. Conclusions The segments of the spinal deformity in patients with scoliosis were the weak links of their spines and more vulnerable to damage in a vibrating environment. Patients with scoliosis should avoid a vibrating environment, particularly in a sensitive frequency range. The research outcomes provide methodological assistance and mechanical analysis references for the protection, rehabilitation treatment, and clinical pathological studies of patients with scoliosis.

Application of Harmonic Analysis in the Preliminary Prediction of Air Temperature over Lagos and Abuja, Nigeria.

Harmonic Analysis technique has been employed in predicting the hourly air temperature variations over Lagos and Abuja, Nigeria. The variations in hourly air temperatures over the two stations are periodic and thus have strong tendency of being repeated the next day, if all other atmospheric variables are constant. It was observed that the variation in hourly air temperature in the two stations is dominated by the first harmonic, thus it fluctuates by one cycle with a period of 24 hours. Invariably, harmonic equations could be applied to hourly temperature prediction even on a large scale data. The maximum hourly air temperature occurred two hours on the average after the maximum solar irradiance has occurred in each station. It was found that the temperature of the air at a particular hour is dependent on that of the previous hour.

Tidal forecasting in the bahia blanca estuary, Argentina / Predicción de mareas en el estuario de bahía blanca, Argentina / Previsão de marés no estuario de bahia branca, Argentina

In recent years, the availability of accurate ocean tide models has become increasingly important, as tides are the main contributor to disposal and movement of sediments, tracers and pollutants, and also due to a wide range of offshore applications in engineering, environmental observations, exploration and oceanography. Tides can be conventionally predicted by harmonic analysis, which is the superposition of many sinusoidal constituents with amplitudes and frequencies determined by a local analysis of the measured tide. However, accurate predictions of tide levels could not be obtained without a large number of tide measurements by the harmonic method. An application of the back-propagation artificial neural network using long-term and short-term measuring data is presented in this paper. On site tidal level data at Ingeniero White harbor in the inner part of Bahia Blanca estuary, Argentina, will be used to test the performance of the present model. Comparison with conventional harmonic methods indicates that the back-propagation neural network model also predicts accurately the long-term tidal levels.

Durante los últimos años, la disponibilidad de modelos oceánicos cada vez más exactos han aumentado en importancia, por ser las mareas el principal contribuyente para la disposición y movimiento de trazadores, sedimentos y contaminantes, y por una amplia variedad de aplicaciones en ingeniería, observaciones ambientales, exploración y oceanografía. Las mareas pueden ser pronosticadas mediante análisis armónico, que es la superposición de funciones sinusoidales con amplitudes y frecuencias determinadas en un análisis local de registros mareográficos. Sin embargo, la exactitud de las predicciones del nivel de marea por el método armónico no puede obtenerse sin un gran número de mediciones. En este trabajo se presenta una aplicación del método propagación hacia atrás (back-propagation) de redes neuronales empleando datos de corto y de largo plazo. Para medir la precisión del presente modelo se utilizan mediciones de nivel de marea correspondientes al Puerto Ingeniero White, en la parte interna del estuario de Bahia Blanca, Argentina. La comparación con métodos armónicos convencionales indica que las redes neuronales empleando back-propagation también predicen eficientemente los niveles de mareas a largo plazo.

Durante os últimos anos, a disponibilidade de modelos oceânicos cada vez mais exatos têm aumentado em importância, por ser as marés o principal contribuinte para a disposição e movimento de traçadores, sedimentos e contaminantes, e por uma ampla variedade de aplicações em engenharia, observações ambientais, exploração e oceanografia. As marés podem ser prognosticadas mediante análise armônico, que é a superposição de funções sinusoidais com amplitudes e frequências determinadas em uma análise local de registros maregráficos. Entretanto, a exatidão das previsões do nível da maré pelo método armônico não pode obter-se sem um grande número de medições. Neste trabalho se apresenta uma aplicação do método propagação para atrás (back-propagation) de redes neuronais empregando dados de curto e de longo prazo. Para medir a precisão do presente modelo se utilizam medições de nível de maré correspondentes ao Puerto Ingeniero White, na parte interna do estuario de Bahia Branca, Argentina. A comparação com métodos armônicos convencionais indica que as redes neuronais empregando back-propagation também predizem eficientemente os níveis de marés a longo prazo.