scholarly journals Customized yet Standardized Temperature Derivatives: A Non-Parametric Approach with Suitable Basis Selection for Ensuring Robustness

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3351
Author(s):  
Takuji Matsumoto ◽  
Yuji Yamada
Keyword(s):  
Prediction Error ◽  
Electric Utilities ◽  
Effect Of Temperature ◽  
Price Risk ◽  
Practical Applications ◽  
On Demand ◽  
Spline Basis ◽  
Squared Prediction Error ◽  
Selection For ◽  
Non Parametric

Previous studies have demonstrated that non-parametric hedging models using temperature derivatives are highly effective in hedging profit/loss fluctuation risks for electric utilities. Aiming for the practical applications of these methods, this study performs extensive empirical analyses and makes methodological customizations. First, we consider three types of electric utilities being exposed to risks of “demand,” “price,” and their “product (multiplication),” and examine the design of an appropriate derivative for each utility. Our empirical results show that non-parametrically priced derivatives can maximize the hedge effect when a hedger bears a “price risk” with high nonlinearity to temperature. In contrast, standard derivatives are more useful for utilities with only “demand risk” in having a comparable hedge effect and in being liquidly traded. In addition, the squared prediction error derivative on temperature has a significant hedge effect on both price and product risks as well as a certain effect on demand risk, which illustrates its potential as a new standard derivative. Furthermore, spline basis selection, which may be overlooked by modeling practitioners, improves hedge effects significantly, especially when the model has strong nonlinearities. Surprisingly, the hedge effect of temperature derivatives in previous studies is improved by 13–53% by using an appropriate new basis.

scholarly journals Review on the Influence of Temperature upon Hydrogen Effects in Structural Alloys

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 423
Author(s):  
Thorsten Michler ◽  
Frank Schweizer ◽  
Ken Wackermann
Keyword(s):  
Mechanical Properties ◽  
Mechanical Property ◽  
Temperature Effect ◽  
Statistical Approach ◽  
Austenitic Stainless Steels ◽  
Carbon Steels ◽  
Effect Of Temperature ◽  
Engineering Applications ◽  
Selection For ◽  
Typical Temperature

It is well-documented experimentally that the influence of hydrogen on the mechanical properties of structural alloys like austenitic stainless steels, nickel superalloys, and carbon steels strongly depends on temperature. A typical curve plotting any hydrogen-affected mechanical property as a function of temperature gives a temperature THE,max, where the degradation of this mechanical property reaches a maximum. Above and below this temperature, the degradation is less. Unfortunately, the underlying physico-mechanical mechanisms are not currently understood to the level of detail required to explain such temperature effects. Though this temperature effect is important to understand in the context of engineering applications, studies to explain or even predict the effect of temperature upon the mechanical properties of structural alloys could not be identified. The available experimental data are scattered significantly, and clear trends as a function of chemistry or microstructure are difficult to see. Reported values for THE,max are in the range of about 200–340 K, which covers the typical temperature range for the design of structural components of about 230–310 K (from −40 to +40 °C). That is, the value of THE,max itself, as well as the slope of the gradient, might affect the materials selection for a dedicated application. Given the current lack of scientific understanding, a statistical approach appears to be a suitable way to account for the temperature effect in engineering applications. This study reviews the effect of temperature upon hydrogen effects in structural alloys and proposes recommendations for test temperatures for gaseous hydrogen applications.

scholarly journals Effect of Temperature on Formaldehyde Diffusion in Cellulose Amorphous Region: A Simulation Study

BioResources ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. 3200-3213
Author(s):  
Wei Wang ◽  
Yancai Cao ◽  
Liyue Sun ◽  
Mingshuai Wu
Keyword(s):  
Shear Modulus ◽  
Bulk Modulus ◽  
Poisson’S Ratio ◽  
Amorphous Region ◽  
Poisson's Ratio ◽  
Effect Of Temperature ◽  
External Temperature ◽  
Practical Applications ◽  
Region Model ◽  
Materials Studio

A formaldehyde-cellulose amorphous region model at the micro-level was established using the molecular dynamics software Materials Studio to simulate the change of cellulose and formaldehyde molecules in an external temperature field. The diffusion coefficients of formaldehyde molecules increased as the temperature increased. Moreover, the total number of hydrogen bonds decreased, and the interaction energy in the formaldehyde-cellulose model was reduced, which confirmed this conclusion and indicated that temperature increase could enhance the diffusion of formaldehyde in cellulose. The mechanical parameters of cellulose were analyzed in terms of Young’s modulus, shear modulus, bulk modulus, Poisson’s ratio, and the ratio of bulk modulus to shear modulus (K/G), which were affected by the temperature. The elastic modulus (E, G, and K) of cellulose decreased as the temperature increased, while the Poisson’s ratio V and K/G values increased. The results of the research explain how elevated temperature can promote the release of formaldehyde in furniture from a microscopic perspective, which supports each other with the results of previous experimental data and practical applications in production.

Implementation, Characterization and Application of Path Changing Switch based Arbiter PUF on FPGA as a lightweight Security Primitive for IoT

2022 ◽  
Vol 27 (3) ◽  
pp. 1-26
Author(s):  
Mahabub Hasan Mahalat ◽  
Suraj Mandal ◽  
Anindan Mondal ◽  
Bibhash Sen ◽  
Rajat Subhra Chakraborty
Keyword(s):  
Complete Characterization ◽  
Effect Of Temperature ◽  
Practical Applications ◽  
Gate Arrays ◽  
Heterogeneous Technologies ◽  
Field Programmable ◽  
Arbiter Puf ◽  
Programmable Gate Arrays ◽  
Secure Authentication

Secure authentication of any Internet-of-Things (IoT) device becomes the utmost necessity due to the lack of specifically designed IoT standards and intrinsic vulnerabilities with limited resources and heterogeneous technologies. Despite the suitability of arbiter physically unclonable function (APUF) among other PUF variants for the IoT applications, implementing it on field-programmable gate arrays (FPGAs) is challenging. This work presents the complete characterization of the path changing switch (PCS) 1 based APUF on two different families of FPGA, like Spartan-3E (90 nm CMOS) and Artix-7 (28 nm CMOS). A comprehensive study of the existing tuning concept for programmable delay logic (PDL) based APUF implemented on FPGA is presented, leading to establishment of its practical infeasibility. We investigate the entropy, randomness properties of the PCS based APUF suitable for practical applications, and the effect of temperature variation signifying the adequate tolerance against environmental variation. The XOR composition of PCS based APUF is introduced to boost performance and security. The robustness of the PCS based APUF against machine learning based modeling attack is evaluated, showing similar characteristics as the conventional APUF. Experimental results validate the efficacy of PCS based APUF with a little hardware footprint removing the paucity of lightweight security primitive for IoT.

Accuracy of predicting the vancomycin concentration in Japanese cancer patients by the Sawchuk–Zaske method or Bayesian method

2019 ◽  
Vol 26 (3) ◽  
pp. 543-548
Author(s):  
Toshihisa Nakashima ◽  
Takayuki Ohno ◽  
Keiichi Koido ◽  
Hironobu Hashimoto ◽  
Hiroyuki Terakado
Keyword(s):  
Cancer Patients ◽  
Prediction Error ◽  
Bayesian Method ◽  
Predictive Accuracy ◽  
Pharmacokinetic Parameters ◽  
Population Pharmacokinetic ◽  
Squared Prediction Error ◽  
Trough Concentrations ◽  
The Mean ◽  
Mean Prediction Error

Background In cancer patients treated with vancomycin, therapeutic drug monitoring is currently performed by the Bayesian method that involves estimating individual pharmacokinetics from population pharmacokinetic parameters and trough concentrations rather than the Sawchuk–Zaske method using peak and trough concentrations. Although the presence of malignancy influences the pharmacokinetic parameters of vancomycin, it is unclear whether cancer patients were included in the Japanese patient populations employed to estimate population pharmacokinetic parameters for this drug. The difference of predictive accuracy between the Sawchuk–Zaske and Bayesian methods in Japanese cancer patients is not completely understood. Objective To retrospectively compare the accuracy of predicting vancomycin concentrations between the Sawchuk–Zaske method and the Bayesian method in Japanese cancer patients. Methods Using data from 48 patients with various malignancies, the predictive accuracy (bias) and precision of the two methods were assessed by calculating the mean prediction error, the mean absolute prediction error, and the root mean squared prediction error. Results Prediction of the trough and peak vancomycin concentrations by the Sawchuk–Zaske method and the peak concentration by the Bayesian method showed a bias toward low values according to the mean prediction error. However, there were no significant differences between the two methods with regard to the changes of the mean prediction error, mean absolute prediction error, and root mean squared prediction error. Conclusion The Sawchuk–Zaske method and Bayesian method showed similar accuracy for predicting vancomycin concentrations in Japanese cancer patients.

scholarly journals Microdroplet-guided intercalation and deterministic delamination towards intelligent rolling origami

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Borui Xu ◽  
Xinyuan Zhang ◽  
Ziao Tian ◽  
Di Han ◽  
Xingce Fan ◽  
...  
Keyword(s):  
Low Cost ◽  
Rolling Direction ◽  
Three Dimensional ◽  
Van Der Waals Interaction ◽  
Creative Design ◽  
General Strategy ◽  
Practical Applications ◽  
On Demand ◽  
Vapor Sensing ◽  
Fundamental Research

Abstract Three-dimensional microstructures fabricated by origami, including folding, rolling and buckling, gain great interests in mechanics, optics and electronics. We propose a general strategy on on-demand and spontaneous rolling origami for artificial microstructures aiming at massive and intelligent production. Deposited nanomembranes are rolled-up in great amount triggered by the intercalation of tiny droplet, taking advantage of a creative design of van der Waals interaction with substrate. The rolling of nanomembranes delaminated by liquid permits a wide choice in materials as well as precise manipulation in rolling direction by controlling the motion of microdroplet, resulting in intelligent construction of rolling microstructures with designable geometries. Moreover, this liquid-triggered delamination phenomenon and constructed microstructures are demonstrated in the applications among vapor sensing, microresonators, micromotors, and microactuators. This investigation offers a simple, massive, low-cost, versatile and designable construction of rolling microstructures for fundamental research and practical applications.

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