Variations in the management of pneumonia in pediatric emergency departments: Compliance with the guidelines

Objective: We sought to assess compliance with evidence-based guidelines for the management of pediatric pneumonia, including the variations in tests ordered and antimicrobials prescribed. Our primary hypothesis was that compliance with the treatment recommendations from the most current guidelines would be low for antimicrobial prescriptions. Methods: We conducted a chart review at the Children\u27s Hospital in London, Ont., to assess variation in the management of pediatric pneumonia. All patients aged 3 months to 18 years seen at the pediatric emergency department between Apr. 1, 2006, and Mar. 31, 2007, with a diagnosis of pneumonia were eligible for inclusion in the study. Results: Compliance with management guidelines was 59.7% (95% confidence interval [CI] 53%-66%, n = 211) in children 5-18 years old and 83.0% (95% CI 80%-86%, n = 605) in children 3 months to 5 years old. Significant variation existed in the choice of antimicrobial agent for children with pneumonia, with nonrecommended agents frequently prescribed. Conclusion: Significant variation existed in the management of pediatric pneumonia, and adherence to guidelines was low for the group of patients aged 5-18 years. Future studies should attempt to provide guidance to distinguish between viral and bacterial etiology to allow judicious use of antimicrobials

An investigation of spatial signal transduction in cellular networks

<p>Abstract</p> <p>Background</p> <p>Spatial signal transduction plays a vital role in many intracellular processes such as eukaryotic chemotaxis, polarity generation and cell division. Furthermore it is being increasingly realized that the spatial dimension to signalling may play an important role in other apparently purely temporal signal transduction processes. It is increasingly being recognized that a conceptual basis for studying spatial signal transduction in signalling networks is necessary.</p> <p>Results</p> <p>In this work we examine spatial signal transduction in a series of standard motifs/networks. These networks include coherent and incoherent feedforward, positive and negative feedback, cyclic motifs, monostable switches, bistable switches and negative feedback oscillators. In all these cases, the driving signal has spatial variation. For each network we consider two cases, one where all elements are essentially non-diffusible, and the other where one of the network elements may be highly diffusible. A careful analysis of steady state signal transduction provides many insights into the behaviour of all these modules. While in the non-diffusible case for the most part, spatial signalling reflects the temporal signalling behaviour, in the diffusible cases, we see significant differences between spatial and temporal signalling characteristics. Our results demonstrate that the presence of diffusible elements in the networks provides important constraints and capabilities for signalling.</p> <p>Conclusions</p> <p>Our results provide a systematic basis for understanding spatial signalling in networks and the role of diffusible elements therein. This provides many insights into the signal transduction capabilities and constraints in such networks and suggests ways in which cellular signalling and information processing is organized to conform to or bypass those constraints. It also provides a framework for starting to understand the organization and regulation of spatial signal transduction in individual processes.</p

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.The research leading to these results has received funding from the Spanish Government and European FEDER funds (DPI2012-32390), the Valencia Regional Government (PROMETEO/2013/085) and the University of Alicante (GRE12-17)

Tribological performance of palm kernel oil with addition of pour point depressants as a lubricant using four-ball tribotester under variable load test

The growing of worldwide trend for promoting the use of the renewable material such as vegetable oil is due to the increasing concern about environmental damage that caused by the use of mineral oil which is not biodegradable. Vegetable oil has a potential to replace mineral oil as a lubricant because of its specific properties that is non-toxic and biodegradable. The main problem in using vegetable oil is having poor low temperature performance. In this research palm kernel oil (PKO) that behave a semi solid phase is used as a bio lubricant mixing with different weightage percentage of poor point depressant (PPD) to investigate the low temperature behaviour performance and also to determine the effect of lubricity performance when blended with different percentage of PPD (5w%, 10wt%, 20wt% and 30wt %). The experiment is according to ASTM D4172 with variation load test. The result of the experiment show that for low temperature performance, PKO with 20wt%PPD (A2-20%) and 30wt%PPD (A2-30%) show great performance which can withstand 15° C. The sample A2-20% shows good lubricity performance in terms of coefficient of friction compare to the other sample. The lubricity performance in terms of wear scar diameter (WSD) it can see that the different percentage PPD do not affect the WSD properties of the pure palm kernel oil. The most consistent and the desired value of the sample in terms of surface roughness is A2-5% and A2-10% where the surface roughness value is stable through the entire load test

Fuzzy logic-based controller of the bidirectional direct current to direct current converter in microgrid

Microgrids are small-scale power networks that include renewable energy sources, load, energy storage systems, and energy management systems (EMS). Lithium-ion batteries are the most used battery for energy storage in microgrids due to their advantages over other types of batteries. However, to protect the battery from the explosion and to manage to charge and discharge based on state-of-charge (SoC) value, this type of battery requires the use of an energy management system. The main objective of this paper is to propose an intelligent control strategy for energy management in the microgrid to control the charge and discharge of Li-ion batteries to stabilize the system and reduce the cost of electricity due to the high cost of grid electricity. The proposed technique is based on a fuzzy logic controller (FLC) for voltage control. The FLC is based on the measured voltage of the direct current (DC) bus and the fixed reference voltage to generate buck/boost converter signal control. The proposed technique has been simulated and tested using MATLAB/Simulink software which illustrates the tracking of desired power and DC bus voltage regulation. The simulation results confirm that the proposed systems can diminish the deviations of the system's voltage

Intravitreal AAV-Delivery of Genetically Encoded Sensors Enabling Simultaneous Two-Photon Imaging and Electrophysiology of Optic Nerve Axons

Myelination of axons by oligodendrocytes is a key feature of the remarkably fast operating CNS. Oligodendrocytes not only tune axonal conduction speed but are also suggested to maintain long-term axonal integrity by providing metabolic support to the axons they ensheath. However, how myelinating oligodendrocytes impact axonal energy homeostasis remains poorly understood and difficult to investigate. Here, we provide a method of how to study electrically active myelinated axons expressing genetically encoded sensors by combining electrophysiology and two-photon imaging of acutely isolated optic nerves. We show that intravitreal adeno-associated viral (AAV) vector delivery is an efficient tool to achieve functional sensor expression in optic nerve axons, which is demonstrated by measuring axonal ATP dynamics following AAV-mediated sensor expression. This novel approach allows for fast expression of any optical sensor of interest to be studied in optic nerve axons without the need to go through the laborious process of producing new transgenic mouse lines. Viral-mediated biosensor expression in myelinated axons and the subsequent combination of nerve recordings and sensor imaging outlines a powerful method to investigate oligodendroglial support functions and to further interrogate cellular mechanisms governing axonal energy homeostasis under physiological and pathological conditions

Point Absorber Method as Wave Energy Convertor Device for Power Generation: Effect of Buoy Arrangements

A point absorber is a floating structure with components that move relative to each other due to wave action. They utilize the up and down movement of the wave height at a single point for energy conversion. The relative up and down which is bobbing motion caused by passing waves used to drive electromechanical energy converters to generate power output. This experiment investigates behaviour of the point absorber device used the pneumatic sensor to take the frequency of the displacement of buoy while testing in the wave maker generator. Then, study the efficiency power output of point absorber WEC device and studies the behaviour of the point absorber in a regular wave. Fabricate the linear generator which as power absorption to estimate the effectiveness power output on different configuration by using the multimeter device. The point absorber at the front position of the configuration has good behaviour because of the high frequency produced. By estimated the behaviour of the device on configuration achieved. Configuration shape design of the point absorber used in this testing is square, diamond and parallelogram shape for an estimate the best power output. The configuration of the parallelogram has the best power output compared to another configuration. The best arrangement of the device for efficiency by measure the output voltage as power output is 68.14 mV and increase 8% in every minute

Control visual dinámico basado en FPGA de un robot manipulador de 6 grados de libertad

[Resumen] En este artículo se describe la formulación, implementación y experimentación de un sistema de control visual dinámico aplicado a un robot de 6 grados de libertad. Se propone una arquitectura hardware basada en FPGAs para la implementación de los controladores. Con el objetivo de limitar la latencia del controlador se ha implementado en la FPGA no sólo el controlador sino también la captura y procesamiento de la información visual. Se hace uso de las capacidades de procesamiento paralelo de la FPGA para optimizar los diferentes componentes del sistema de control visual propuesto. Finaliza el artículo con los resultados experimentales obtenidos en tareas de posicionamiento de un robot Mitsubishi PA10 de 6 grados de libertad.Este trabajo ha sido financiado por el Ministerio de Economía y competitividad mediante el proyecto DPI2015-68087-Rhttps://doi.org/10.17979/spudc.978849749808

Influence of laser surface texturing (LST) parameters on the surface characteristics of Ti6al4v and the effects thereof on laser heating

With rapid growth in laser-based manufacturing technologies, laser brazing has attracted significant attention in various industries such as automotive, biomedical and aerospace. Material heating in laser brazing is one of the factors to ensure maximum reaction between the filler and the base metal. During laser heating the energy needed to melt the filler is also dependent on the laser-material interaction, so in this work the effect of laser surface texturing (LST) parameters such as power, pulse frequency and scan speed on the surface morphology and roughness properties of Ti6Al4V were investigated using a fibre laser. It was found that an increase in laser power accompanied by a decrease in frequency and scan speed could increase the surface roughness. Additionally, the effect of surface roughness towards laser heating temperature was also studied with a fibre laser. When laser beam radiates a rougher surface the maximum temperature attained is 41.4% higher compared to a polished surface. This was mainly due to the laser energy scattering over a larger and rougher surface area causing amplification of the energy absorption in the form of temperature rise

Identification of a suitable machine learning model for detection of asymptomatic Ganoderma boninense infection in oil palm seedlings using hyperspectral data

In Malaysia, oil palm industry has made an enormous contribution to economic and social prosperity. However, it has been affected by basal stem rot (BSR) disease caused by Ganoderma boninense (G. boninense) fungus. The conventional practice to detect the disease is through manual inspection by a human expert every two weeks. This study aimed to identify the most suitable machine learning model to classify the inoculated (I) and uninoculated (U) oil palm seedlings with G. boninense before the symptoms’ appearance using hyperspectral imaging. A total of 1122 sample points were collected from frond 1 and frond 2 of 28 oil palm seedlings at the age of 10 months old, with 540 and 582 reflectance spectra extracted from U and I seedlings, respectively. The significant bands were identified based on the high separation between U and I seedlings, where the differences were observed significantly in the NIR spectrum. The reflectance values of each selected band were later used as input parameters of the 23 machine learning models developed using decision trees, discriminant analysis, logistic regression, naïve Bayes, support vector machine (SVM), k-nearest neighbor (kNN), and ensemble modelling with various types of kernels. The bands were optimized according to the classification accuracy achieved by the models. Based on the F-score and performance time, it was demonstrated that coarse Gaussian SVM with 9 bands performed better than the models with 35, 18, 14, and 11 bands. The coarse Gaussian SVM achieved an F-score of 95.21% with a performance time of 1.7124 s when run on a personal computer with an Intel® Core™ i7-8750H processor and 32 GB RAM. This early detection could lead to better management in the oil palm industry