High-flow nasal cannula improves hypoxemia in dogs failing conventional oxygen therapy.

OBJECTIVE: A prospective clinical trial was performed to evaluate the efficacy and tolerance of high-flow nasal cannula (HFNC) in dogs with hypoxemia. ANIMALS: 20 client-owned dogs failing conventional oxygen therapy (COT). PROCEDURES: Patients admitted to the ICU for treatment of hypoxemic respiratory failure were enrolled in the study. PaO2, SPO2, respiratory rate (RR), and acute patient physiologic and laboratory evaluation scores were obtained at the time of COT failure and after initiation of HFNC. Complications and patient tolerance while receiving HFNC were also recorded. RESULTS: Compared to COT, the median PaO2 and SO2 were significantly higher when dogs were receiving HFNC (60.8 vs 135.6 mm Hg and 90.7% vs 99.25%, respectively). Dogs receiving HFNC had a significant reduction in median RR as compared to dogs undergoing COT (52 vs 36 breaths per minute). After the initiation of HFNC, all dogs showed clinical improvement as measured by PaO2, SO2, and RR. Of 20 dogs, 6 ultimately failed HFNC and mechanical ventilation was recommended. Nine dogs undergoing HFNC survived to discharge, and acute patient physiologic and laboratory evaluation scores had a significant positive severity correlation with death. Complications included pneumothorax in 1 dog. CLINICAL RELEVANCE: COT has limited flow rates due to airway irritation caused by room temperature, nonhumidified oxygen. HFNC uses vapor humidification and heated oxygen, allowing for higher flow rates. In people, HFNC is used as escalation of oxygen therapy when COT fails. Dogs treated with HFNC had significant improvements in PaO2, SO2, and RR as compared to COT. HFNC is well tolerated and effective in treating hypoxemia in dogs.

Precise Temperature Measurement for Increasing the Survival of Newborn Babies in Incubator Environments.

Precise temperature measurement is essential in a wide range of applications in the medical environment, however the regarding the problem of temperature measurement inside a simple incubator, neither a simple nor a low cost solution have been proposed yet. Given that standard temperature sensors don't satisfy the necessary expectations, the problem is not measuring temperature, but rather achieving the desired sensitivity. In response, this paper introduces a novel hardware design as well as the implementation that increases measurement sensitivity in defined temperature intervals at low cost.

Real time voltage and current phase shift analyzer for power saving applications.

Nowadays, high importance is given to low energy devices (such as refrigerators, deep-freezers, washing machines, pumps, etc.) that are able to produce reactive power in power lines which can be optimized (reduced). Reactive power is the main component which overloads power lines and brings excessive thermal stress to conductors. If the reactive power is optimized, it can significantly lower the electricity consumption (from 10 to 30%-varies between countries). This paper will examine and discuss the development of a measuring device for analyzing reactive power. However, the main problem is the precise real time measurement of the input and output voltage and current. Such quality measurement is needed to allow adequate action intervention (feedback which reduces or fully compensates reactive power). Several other issues, such as the accuracy and measurement speed, must be examined while designing this device. The price and the size of the final product need to remain low as they are the two important parameters of this solution.

Non destructive defect detection by spectral density analysis.

The potential nondestructive diagnostics of solid objects is discussed in this article. The whole process is accomplished by consecutive steps involving software analysis of the vibration power spectrum (eventually acoustic emissions) created during the normal operation of the diagnosed device or under unexpected situations. Another option is to create an artificial pulse, which can help us to determine the actual state of the diagnosed device. The main idea of this method is based on the analysis of the current power spectrum density of the received signal and its postprocessing in the Matlab environment with a following sample comparison in the Statistica software environment. The last step, which is comparison of samples, is the most important, because it is possible to determine the status of the examined object at a given time. Nowadays samples are compared only visually, but this method can't produce good results. Further the presented filter can choose relevant data from a huge group of data, which originate from applying FFT (Fast Fourier Transform). On the other hand, using this approach they can be subjected to analysis with the assistance of a neural network. If correct and high-quality starting data are provided to the initial network, we are able to analyze other samples and state in which condition a certain object is. The success rate of this approximation, based on our testing of the solution, is now 85.7%. With further improvement of the filter, it could be even greater. Finally it is possible to detect defective conditions or upcoming limiting states of examined objects/materials by using only one device which contains HW and SW parts. This kind of detection can provide significant financial savings in certain cases (such as continuous casting of iron where it could save hundreds of thousands of USD).