Weight Loss Prediction by Operating Conditions of CA Storage

2017 ◽  
Vol 21 (4) ◽  
pp. 312-317 ◽  
Author(s):  
Chun Wan Park ◽  
Seok Ho Park ◽  
Jin Se Kim ◽  
Dong Soo Choi ◽  
Yong Hun Kim ◽  
...  
2014 ◽  
Vol 2014 (1) ◽  
pp. 000662-000667 ◽  
Author(s):  
Stephani Gulbrandsen ◽  
Joelle Arnold ◽  
Greg Caswell ◽  
Ken Cartmill

This research compared the lifetime of similar aluminum electrolytic capacitors from different manufacturers using an accelerated life test, which consisted of critical weight loss testing and rate of weight loss testing. In critical weight loss testing, capacitors are perforated to speed up electrolyte evaporation and the equivalent series resistance (ESR) and weight are measured periodically to determine their relationship. In rate of weight loss testing, capacitors are subjected to final operating conditions (i.e. voltage and ripple current are applied) and the weight is periodically measured over the course of 500 hours. After test completion the relationship between ESR and weight loss is used to calculate the critical weight loss that occurs at datasheet-defined failure, which is typically a 200% increase in ESR. The rate of weight loss is extrapolated to the critical weight to estimate a time to failure that can be compared to other capacitors tested using the same accelerated approach. In this research, testing compared 450 V, 68 μF capacitors from Manufacturer A and Manufacturer B, and results indicated Manufacturer A had a significantly longer lifetime. Therefore, capacitors from Manufacturer A are more reliable than capacitors from Manufacturer B.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rikke Linnemann Nielsen ◽  
Marianne Helenius ◽  
Sara L. Garcia ◽  
Henrik M. Roager ◽  
Derya Aytan-Aktug ◽  
...  

AbstractDiet is an important component in weight management strategies, but heterogeneous responses to the same diet make it difficult to foresee individual weight-loss outcomes. Omics-based technologies now allow for analysis of multiple factors for weight loss prediction at the individual level. Here, we classify weight loss responders (N = 106) and non-responders (N = 97) of overweight non-diabetic middle-aged Danes to two earlier reported dietary trials over 8 weeks. Random forest models integrated gut microbiome, host genetics, urine metabolome, measures of physiology and anthropometrics measured prior to any dietary intervention to identify individual predisposing features of weight loss in combination with diet. The most predictive models for weight loss included features of diet, gut bacterial species and urine metabolites (ROC-AUC: 0.84–0.88) compared to a diet-only model (ROC-AUC: 0.62). A model ensemble integrating multi-omics identified 64% of the non-responders with 80% confidence. Such models will be useful to assist in selecting appropriate weight management strategies, as individual predisposition to diet response varies.


2018 ◽  
Author(s):  
Zahava P. Michaelson ◽  
Sai T. Bondalapati ◽  
Selma Amrane ◽  
Robert W. Prosser ◽  
Daniel M. Hill ◽  
...  

AbstractObjectTo study the ability of custom-built, web-enabled scales to monitor liquid nitrogen (LN2) levels in cryostorage dewars.DesignLaboratory studySettingA large academic fertility center in New York City.InterventionsCryostorage dewars were placed on top of the custom-engineered scales with continuous real-time monitoring, and weight and temperature data were recorded in the setting of slow, medium, and fast rate-loss of LN2 designed to mimic models of tank failures.Main Outcome MeasuresWeights were continuously monitored and recorded, with a calculated alarm trigger set at 10% weight loss. Temperature within the tanks was simultaneously monitored with probes placed near the top of the tanks, with calculated alarms using a −185 °C as the threshold. For the “slow rate-loss” simulations, tanks were left intact and closed in usual operating conditions, and LN2 was allowed to evaporate at the normal rate. For the “medium rate-loss” simulation, the foam core of the tank neck was removed and the insulating vacuum was eliminated by making a 1/16 inch hole in the outer tank wall. For the “fast rate-loss” simulation, a 1/16” hole was made through the outer tank wall and LN2 was released at a rate of 0.15 L/second. All simulations were performed in duplicate.ResultsWith an intact and normally functioning tank, a 10% loss in LN2 occurred in 4.2-4.9 days. Warming to −185 °C occurred in 37.8 - 43.7 days, over 30 days after the weight-based alarm was triggered. Full evaporation of LN2required 36.8 days. For the medium rate-loss simulation, a 10% loss in LN2 occurred in 0.8 h. Warming to −185 °C occurred in 3.7 - 4.8 hours, approximately 3 hours after the weight-based alarm was triggered. For the fast rate-loss simulation, a 10% weight loss occurred within 15 seconds and tanks were completely depleted in under 3 minutes. Tank temperatures began to rise immediately and at a relatively constant rate of 43.9 °C/hour and 51.6 °C/hour. Temperature alarms would have sounded within 0.37 and 0.06 hours after the breech.ConclusionsThis study demonstrates that a weight-based, automated alarm system can detect tank failures prior to a temperature-based alarm system, in some cases over a month in advance. In combination with existing safety mechanisms such as temperature probes, a weight-based monitoring system could serve as a redundant safety mechanism for added protection of cryopreserved reproductive tissues.


2019 ◽  
pp. 1-11
Author(s):  
Zhi Cheng ◽  
Minoru Nakatsugawa ◽  
Xian Chong Zhou ◽  
Chen Hu ◽  
Stephen Greco ◽  
...  

PURPOSE To evaluate the utility of a clinical decision support system (CDSS) using a weight loss prediction model. METHODS A prediction model for significant weight loss (loss of greater than or equal to 7.5% of body mass at 3-month post radiotherapy) was created with clinical, dosimetric, and radiomics predictors from 63 patients in an independent training data set (accuracy, 0.78; area under the curve [AUC], 0.81) using least absolute shrinkage and selection operator logistic regression. Four physicians with varying experience levels were then recruited to evaluate 100 patients in an independent validation data set of head and neck cancer twice (ie, a pre-post design): first without and then with the aid of a CDSS derived from the prediction model. At both evaluations, physicians were asked to predict the development (yes/no) and probability of significant weight loss for each patient on the basis of patient characteristics, including pretreatment dysphagia and weight loss and information from the treatment plan. At the second evaluation, physicians were also provided with the prediction model’s results for weight loss probability. Physicians’ predictions were compared with actual weight loss, and accuracy and AUC were investigated between the two evaluations. RESULTS The mean accuracy of the physicians’ ability to identify patients who will experience significant weight loss (yes/no) increased from 0.58 (range, 0.47 to 0.63) to 0.63 (range, 0.58 to 0.72) with the CDSS ( P = .06). The AUC of weight loss probability predicted by physicians significantly increased from 0.56 (range, 0.46 to 0.64) to 0.69 (range, 0.63 to 0.73) with the aid of the CDSS ( P < .05). Specifically, more improvement was observed among less-experienced physicians ( P < .01). CONCLUSION Our preliminary results demonstrate that physicians’ decisions may be improved by a weight loss CDSS model, especially among less-experienced physicians. Additional study with a larger cohort of patients and more participating physicians is thus warranted for understanding the usefulness of CDSSs.


2021 ◽  
Vol 9 ◽  
Author(s):  
Huimin Yun ◽  
Ziliang Wang ◽  
Ruixu Wang ◽  
Xiaotao Bi ◽  
Weihsin Chen

Auto-thermal operation of biomass torrefaction can help avoid additional heat investment and the associated costs to the system. This work provides a general method for relating the feedstock-specific parameters to the energy balance and pre-diagnosing the potential of auto-thermal for different biomass torrefaction and pyrolysis systems. Both solid and gas thermal properties under various torrefaction conditions and their influences to the torrefaction system energy balances are considered. Key parameters that influence the process auto-thermal operation are analyzed, which include torrefaction reaction heat, torrefaction conditions, drying method, biomass species, and inert N2 flowrate. Equations of torgas and biomass higher heating values (HHVs), as well as the torrefaction reaction heat at different operating conditions are developed. It is found that torgas and biomass HHVs increase with torrefaction temperature and biomass weight loss. Torrefaction reaction heat has a linear relationship with the biomass weight loss, with a positive slope at 250–260°C, and a negative slope at 270–300°C, which indicates that torrefaction shifts from endothermic to exothermic at ∼270°C. Applying advanced drying technology and avoiding the use of N2 can help the system achieve auto-thermal operation at lower torrefaction temperature and residence time, thus leading to a higher process energy efficiency and product yield. This is the first work to relate the micro level element changes of biomass to the macro level process energy balances of the torrefaction system. This work is important in design and operation of the torrefaction system in both pilot and industrial scales to improve process efficiency and predict product quality in a reliable and economic manner.


Meat Science ◽  
1980 ◽  
Vol 5 (1) ◽  
pp. 5-15 ◽  
Author(s):  
A.N. Califano ◽  
A. Calvelo
Keyword(s):  

Author(s):  
Hong Nam Nguyen ◽  
Toshiki Tsubota

Abstract A complete parametric study of bagasse pellets under high-temperature steam gasification in relevant industrial operating conditions was investigated. Regarding thermal behaviors, the maximum rate of weight loss (Rmax = 0.55%/°C) occurred at the temperature Tmax = 305 °C. The final pyrolysis temperature and heating rate were proportional to the mechanical strength, the bulk density, as well as the char yield and energy yield. However, the changes were not significant after 600 °C. Regarding steam gasification kinetics, an increase from 850 to 1000 °C and from 0.1 to 0.4 atm accelerated 10 times and two times the conversion rate of bagasse pellet char, respectively. Gasification kinetics of a pellet char produced at 2000 °Cmin−1 was 1.4 higher compared with a pellet char produced at 5 °C min−1. An empirical model that takes into account all the changes in the reactive surface could successfully predict the conversion of the bagasse pellet char during high-temperature steam gasification. Experimental results and the kinetic model proposed could be useful for the calculation of industrial or academic codes, necessary for the conception of new efficient gasifiers.


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