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At least 37 records · Page 2

Emergency department overcrowding and its associated factors at HARME medical emergency center in Eastern Ethiopia

Introduction: Emergency department (ED) overcrowding has become a significant concern as it can lead to compromised patient care in emergency settings. Various tools have been used to evaluate overcrowding in ED. However, there is a lack of data regarding this issue in resource-limited countries, including Ethiopia. This study aimed to validate NEDOCS, assess level of ED overcrowding and identify associated factors at HARME Medical Emergency Center, located in Hiwot Fana Comprehensive Specialized Hospital, Harar, Ethiopia. Methods: A cross-sectional study was conducted at the HARME Medical Emergency Center, Hiwot Fana Comprehensive Specialized Hospital, involving a total of 899 patients during 120 sampling intervals. The area under the receiver operating characteristic curves (AUC) was calculated to evaluate the agreement between objective and subjective assessments of ED overcrowding. A multivariable logistic regression analysis was employed to identify factors associated with ED overcrowding and statistically significant association was declared using 95% confidence level and a p-value < 0.05. Results: The interrater agreement showed a strong correlation with a Cohen's kappa (κ) of 0.80. The National Emergency Department Overcrowding Study Score demonstrated a strong association with subjective assessments from residents and case team nurses, with an AUC of 0.81 and 0.79, respectively. According to residents' perceptions, ED were considered overcrowded 65.8% of the time. Factors significantly associated with ED overcrowding included waiting time for triage (AOR: 2.24; 95% CI: 1.54–3.27), working time (AOR: 2.23; 95% CI: 1.52–3.26), length of stay (AOR: 2.40; 95% CI: 1.27–4.54), saturation level (AOR: 2.35; 95% CI: 1.31–4.20), chronic illness (AOR: 2.19; 95% CI: 1.37–3.53), and abnormal pulse rate (AOR: 1.52; 95% CI: 1.06–2.16). Conclusion: The study revealed that ED were overcrowded approximately two-thirds of the time.

60 APPLIED LIFE SCIENCES↗

Ruggedness Evaluation of ASTM International Standard Test Methods for Shape Memory Materials: E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys

This paper evaluates the ruggedness testing of the newly released ASTM International E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys. The ruggedness experiment was designed with eight runs in two replicates, consisting of seven factors of strain rate (ė), heating and cooling rates (Ṫ(heat) and Ṫ(cool), respectively), upper and lower cycle temperatures (UCT and LCT, respectively), hold time (thold), and minimum load (Fmin) imparted on the samples. The results indicate that the hold time factor had no effect on any result variable. The minimum load factor, alternatively, had the greatest effect on several result variables, with the greatest influence on the strains at martensite start and finish (strain variation ~0.1 percent), and the strains at the upper and lower cycle temperatures (strain variation of 0.14 percent). The UCT was found to have a large effect on the austenite and martensite finish tangent line and data intersect, denoted by Af* and Mf*, by ~17 and 4 °C, respectively. The testing methodology, analysis techniques, and resulting conclusions on the ruggedness of the test methods are presented.

shape memory alloy↗

Hybrid simulations of collisionless ion tearing

Ion tearing in a thin collisionless neutral sheet is investigated using hybrid (particle ion, massless fluid electron) simulations in which dissipation effects are included through a model of the full electron pressure tensor in which self-consistently generated anisotropies are reduced via an isotropization time factor. The linear growth rates and ion dynamics are in qualitative agreement with linear theory and one-component simulations. The reconnection rate increases with the isotropization time.

Hesse, Michael↗

Ruggedness Evaluation of ASTM International Standard Test Methods for Shape Memory Materials: E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys

This paper evaluates the ruggedness testing of the newly released ASTM International E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys. The ruggedness experiment was designed with eight runs in two replicates, consisting of seven factors of strain rate (ė), heating and cooling rates (T(sub heat) and T(sub cool), respectively), upper and lower cycle temperatures (UCT and LCT, respectively), hold time (t(sub hold)), and minimum load (F(sub min)) imparted on the samples. The results indicate that the hold time factor had no effect on any result variable. The minimum load factor, alternatively, had the greatest effect on several result variables, with the greatest influence on the strains at martensite start and finish (strain variation ~0.1 percent), and the strains at the upper and lower cycle temperatures (strain variation of 0.14 percent). The UCT was found to have a large effect on the austenite and martensite finish tangent line and data intersect, denoted by A(sub f(sup *)) and M(sub f(sup*)), by ~17 and 4 °C, respectively. The testing methodology, analysis techniques, and resulting conclusions on the ruggedness of the test methods are presented.

Benafan, Othmane↗

Applications of Power Spectral Analysis Methods to Maneuver Loads Obtained on Jet Fighter Airplanes During Service Operations

Power spectral densities of normal load factor have been obtained for two service operational training flights of a Republic F-84G airplane and three service operational training flights of a North American F-86A airplane in order to indicate the load-factor frequency content and possible uses of power spectral methods in analyzing maneuver load data. It was determined that the maneuvering load-factor time histories appeared to be described by a truncated normal distribution. The power spectral densities obtained were relatively level at frequencies below 0.03 cycle per second and varied inversely with approximately the cube of the frequency at the higher frequencies. In general, the frequency content was very low above 0.2 cycle per second. The load-factor peak distributions were estimated fairly well from the spectrum analysis. In addition, peak load data obtained during service operations of fighter-type airplanes with flight time totaling about 24,000 hours were examined and appeared to agree reasonably well with the type of equations obtained from spectrum peak-load distributions.

Mayer, John P.↗

Exponential approximation for daily average solar heating or photolysis

When incorporating formulations of instantaneous solar heating or photolytic rates as functions of altitude and sun angle into long range forecasting models, it may be desirable to replace the time integrals by daily average rates that are simple functions of latitude and season. This replacement is accomplished by approximating the integral over the solar day by a pure exponential. This gives a daily average rate as a multiplication factor times the instantaneous rate evaluated at an appropriate sun angle. The accuracy of the exponential approximation is investigated by a sample calculation using an instantaneous ozone heating formulation available in the literature.

Cogley, A. C.↗

Suomi-NPP VIIRS Solar Diffuser Stability Monitor Performance

When illuminated by the Sun, the onboard solar diffuser (SD) panel provides a known spectral radiance source to calibrate the reflective solar bands of the Visible Infrared Imaging Radiometer Suite on the Suomi-NPP satellite. The SD bidirectional reflectance distribution function (BRDF) degrades over time due to solar exposure, and this degradation is measured using the SD stability monitor (SDSM). The SDSM acts as a ratioing radiometer, comparing solar irradiance measurements off the SD panel to those from a direct Sun view. We discuss the design and operations of the SDSM, the SDSM data analysis, including improvements incorporated since launch, and present the results through 1000 days after launch. After 1000 days, the band-dependent H-factors, a quantity describing the relative degradation of the BRDF of the SD panel since launch, range from 0.716 at 412 nanometers to 0.989 at 926 nanometers. The random uncertainty of these H-factors is about 0.1 percent, which is confirmed by the similar standard deviation values computed from the residuals of quadratic exponential fits to the H-factor time trends. The SDSM detector gains have temperature sensitivity of up to about 0.36 percent per kelvin, but this does not affect the derived H-factors. An initial error in the solar vector caused a seasonal bias to the H-factors of up to 0.5 percent. The total exposure of the SD panel to UV light after 1000 orbits is equivalent to about 100 hours of direct sunlight illumination perpendicular to the SD panel surface.

Fulbright, Jon↗

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decom- pose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high- level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for one-year lead hourly load below 5% MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below $5\%$ MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM: Preprint

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below 5% MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗

Windows(Registered Trademark)-Based Software Models Cyclic Oxidation Behavior

Oxidation of high-temperature aerospace materials is a universal issue for combustion-path components in turbine or rocket engines. In addition to the question of the consumption of material due to growth of protective scale at use temperatures, there is also the question of cyclic effects and spallation of scale on cooldown. The spallation results in the removal of part of the protective oxide in a discontinuous step and thereby opens the way for more rapid oxidation upon reheating. In experiments, cyclic oxidation behavior is most commonly characterized by measuring changes in weight during extended time intervals that include hundreds or thousands of heating and cooling cycles. Weight gains occurring during isothermal scale-growth processes have been well characterized as being parabolic or nearly parabolic functions of time because diffusion controls reaction rates. In contrast, the net weight change in cyclic oxidation is the sum of the effects of the growth and spallation of scale. Typically, the net weight gain in cyclic oxidation is determined only empirically (that is, by measurement), with no unique or straightforward mathematical connection to either the rate of growth or the amount of metal consumed. Thus, there is a need for mathematical modeling to infer spallation mechanisms. COSP is a computer program that models the growth and spallation processes of cyclic oxidation on the basis of a few elementary assumptions that were discussed in COSP: A Computer Model of Cyclic Oxidation, Oxidation of Metals, vol. 36, numbers 1 and 2, 1991, pages 81-112. Inputs to the model include the selection of an oxidation-growth law and a spalling geometry, plus oxide-phase, growth-rate, cycle-duration, and spall-constant parameters. (The spalling fraction is often shown to be a constant factor times the existing amount of scale.) The output of COSP includes the net change in weight, the amounts of retained and spalled oxide, the total amounts of oxygen and metal consumed, and the terminal rates of weight loss and metal consumption.

Smialek, J. L.↗

Electrostatic dust remediation for future exploration of the Moon

Dust accumulation is one of the critical issues that must be mitigated on in-situ lunar explorations because an in-situ probe is exposed to small dust particles, which are easily attached to it, during its operations. The Lunar Dust Science Definition Team is organized by the Jet Propulsion Lab/California Institute of Technology through NASA’s Biological and Physical Sciences Division to define key science questions and assess dust remediation techniques. Here, we assess three electrostatic remediation technology concepts: electrostatic dust shield; surface electrostatically collecting dust, later called attractive surface; and electron beam — plasma jet inducing electrostatic dust lofting from a surface. We qualitatively investigate their maturity by defining six operational factors: Time and location; Amount of dust removal; Contamination of target surfaces; Operation duration; Installation; and Safety. In addition to these techniques, we discuss a supporting system that loads dust particles onto a test article to examine dust removal efficiency. Here, the results show that further development increases the maturity of all the technologies. While laboratory and theoretical demonstrations reported whether each technology robustly work on the Moon, which hosts a complex, heterogeneous dust environment, we find that it is still uncertain if this is the case because none has been tested in the lunar environment. Particularly, operation duration and safety are critical to be addressed further on both laboratory and spaceflight scales.

42 ENGINEERING↗

Development of Superconducting RF Cavity in Traveling-Wave Regime at Fermilab

Niobium Superconducting RF (SRF) cavities have a theoretical peak magnetic field which limits the accelerating field to 50-60 MV/m. Presently, all SRF cavities operate in a Standing Wave (SW) resonance field in which particles experience an accelerating force alternating from zero to peak. In contrast, a resonance field in Traveling Wave (TW) mode propagates along with a structure, so particles in such field can experience a constant acceleration force and could have higher energy gain than that of SW mode. This phenomenon is defined by the cavity’s transit time factor, T. A TW structure proposed in an early study achieves T ~0.9, suggesting an increase in acceleration per structure by more than 20% compared to a SW structure (T ~0.7). The early stages of developments had been funded by several SBIR grants to Euclid Techlabs and completed in collaboration with Fermilab through a 1-cell prototype and a proof-of-principle 3-cell TW cavity. It demonstrated the TW resonance excitation at room temperature in the “as-fabricated” 3-cell structure. Here we report recent progresses and the first cryogenic testing of the 3-cell TW cavity in 2 K liquid helium at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Surface depletion during effusion.

Surface depletion errors in using effusion method for determining alloy thermodynamic properties, noting time factor

THERMODYNAMIC PROPERTY↗