Notes

Primary Attention Investigation : Impacting as well as Utilizing Directly into Plan.
In addition, the efficiency of CPM removal through condensation and adsorption could reach up to 51% at 35 °C when flue gas at 130 °C was used as the initial flue gas.The destruction of forest cover by wildfires has important consequences on the stability of forest ecosystems. selleckchem It is well recognized that forests play a key role in regulating the hydrological cycle by modifying rainfall interception and evapotranspiration but also affecting hydrological and erosion responses of the soil surface. For these reasons, in areas devoted to forestry, wildfires can cause loss of biomass production and serious off-site problems related to overland flow and the amount of sediment delivered downstream. Quantifying the consequences caused by wildfires on the soil surface in terms of runoff and soil loss is a great challenge for scientists and foresters. In this paper, a plot experiment aimed at evaluating the effects on soil erosion by wildfires of different severity is firstly described. The experiment was carried out in 1999 in three small plots, located in Southern Italy, covered by pine trees planted in the early '60s. The results obtained from this experiment provided evidence of a short-time effect of wildfire on soil erosion. However, the normal conditions of the pre-fire period seemed to be re-established after a few months following fire. In order to explore possible long-term effects on soil loss, estimates of soil erosion provided by recent 137Cs measurements carried out in the same plots were made. The overall results indicated, for the study area, the absence of a long-term effect on soil erosion caused by the passage of fire and suggested that the 137Cs technique can be a useful tool to explore the effect of wildfires in forested ecosystems.Measuring the wax deposition inside pipelines is one of the critical parameters in the oil, gas and petrochemical industries to control the flow through the pipelines. This paper presents a novel method using artificial neural networks to measure the thickness of the wax. This method was based on counting the backscattered gamma-ray from different thicknesses of the wax inside the pipes with different diameters. For this purpose, the system was simulated by MCNPX code and the designed setup was optimized. The main analyses were based on the simulation results but the verification was performed using a real experimental setup. The results showed a good agreement between the simulation results and the experimental data with a root mean square error less than 1%. Response of the detector was simulated for a standard industrial nominal pipe ranged from 2 to 4.5 inches and for radiation sources 137Cs and 60Co. Using these data, a multilayer perceptron for different energy sources was trained. The best prediction of the wax thickness was obtained for the case of using two radiation sources, simultaneously. The output of the trained neural network showed that the proposed method is capable of measuring the wax thickness inside the pipe with a good accuracy.Inorganic scintillator-based gamma spectrometry is typically carried out under laboratory conditions by using systems that require AC mains supply and dedicated computers for their operation. In this study, an in-house grown CsI(Tl) single crystal scintillator is optically coupled to a bialkali photomultiplier tube (PMT). The output of the PMT is fed to a pulse processing chain consisting of a preamplifier followed by an in-house designed and developed field programmable gate array (FPGA) based multichannel analyzer (MCA). Spectral data from this MCA is sent via serial communication to a microcontroller. A global system for mobile communications (GSM) modem transmits this data in the form of short message service (SMS) packets to a central receiving station, where the spectrum is reconstructed. The requirement of on-site data logging computer to store large spectral data has thereby been eliminated, which, in turn, has eliminated the requirement of AC power supply, reduced the overall power consumption and size of the system, and made it possible to develop a standalone solar-powered unit. For further reduction of overall power consumption, the spectrometer is turned-on only when a Geiger Mueller (GM) counter based gross gamma detection circuit, also included in the system, detects an ambient gamma dose rate beyond a pre-set threshold level. A mathematical methodology has also been implemented for restoration of recorded spectra, shifted due to temperature variations in the environment. All these features have been integrated and a standalone, solar-powered and battery operated field-deployable environmental gamma spectrometry system (EGSS) has been developed and tested for open field deployment. Presence of 41Ar in ambient air was successfully detected by the system.
Simulation-based training has been widely used in various disciplines and has increasingly been recognized as useful in healthcare education during the past decade. In nursing schools, simulation-based training was initially used to train nursing students. However, there is a growing trend to use simulation-based training for continuing education and lifelong learning among professional healthcare workers.

To investigate if simulation-based training has an effect on self-efficacy, self-perceived leadership qualities and team performance in a neonatal intensive care unit.

Time series design.

One referral neonatal intensive care unit in a general hospital in Flanders, Belgium.

Convenience sample of 71 nurses and midwives.

Participants were involved in a series of three simulation-based training sessions. Before and after these series, a set of validated questionnaires was completed to measure the self-efficacy and self-perceived leadership qualities of the participants. Each session was videotaped act on these outcomes, regardless of the number of years of NICU experience. The effect on team performance could not be confirmed in this study.
The core competencies of new graduate nurses (NGNs) have significant health outcomes in the clinical environment. However, these nurses experience a theory-practice gap, which creates a barrier in the transition process when they first enter the clinical workplace.

To understand the general overview of the transition of the core competencies of NGNs to clinical practice in China and the influencing factors.

A cross-sectional study design consisting of a multi-stratified grounded random sample from 31 hospitals in seven regions nationwide.

2400 NGNs were recruited by email.

The Competencies Inventory for Registered Nurse (CIRN) was applied to evaluate NGNs' core competencies.

NGNs performed best on leadership and worst on critical thinking or research aptitude. Core competencies were predicted by depressive symptoms, worked for two-three years, having a nurse-in-charge title, professional values, department, happiness, etc. Besides, the preceptor program also has significant to core competencies.

The average level of Chinese NGNs' core competencies was at a moderate level, which wasn't well optimized.
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