Effects of Temperature and Loading Characteristics on Mechanical and Stress-Relaxation Properties of Sea Buckthorn Berries. Part 2. Puncture Tests

Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is a paper from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 6 (2004): J. Khazaei and D. Mann. Effects of Temperature and Loading Characteristics on Mechanical and Stress-Relaxation Properties of Sea Buckthorn Berries. Part 2. Puncture Tests. (April 2004)

Altered pituitary hormone secretion in male rats exposed to Bisphenol A

Bisphenol A (BPA) is a xenobiotic estrogenic compound. This compound has been suspected to have estrogenic effects on reproductive system of males and females. In this present study we investigated possible low-dose effects of BPAon Luteinizing Hormone in rats. Male Wistar rats (12-13 weeks old) were administrated a daily intra peritoneal 10 μg/kgbw/day, 50 μg/kgbw/day, 100 μg/kgbw/ day dose of BPA for 6, 6, and 12 days, and one day after last injection, serum level of Luteinizing Hormone was examined by ELISA method. All data were expressed as means ± SE. Two-way ANOVA was performed. Analysis of data showed that in all dose groups, plasma level of Luteinizing Hormone significantly decreased compared to control group. The present study showed that BPA at low doses affects Luteinizing Hormone, one of main hormones in spermatogenesis in the adult Wistar rats, and subsequently alters the steroidgenesis in testicular Leydig cells

Influence of impact velocity and moisture content on mechanical damages of white kidney beans under loadings

Kidney beans are more susceptible to breakage under impact loading during harvesting and processing. This problem limited the mechanical harvesting. Mechanical damage decreased the commercial values of seeds. It also decreased the biological values of seeds. Improper harvesting of beans during harvesting may also result in severe seed vigour loss. The objective of this study was to study the effect of impact velocity (at 5, 7.5, 10, and 12 m/s) and beans moisture content (at 5, 10, 15 and 20% wet basis) on percentage of physically damaged beans. The device of assessing the impact damage was used to conduct the tests. All the tests were conducted in laboratory conditions at about 25 oC and 50% relative humidity. The results showed that impact velocity and moisture content significantly influenced the physical damages of kidney beans at 1% and 5% significant level, respectively. Increasing the impact velocity from 5 to 12 m/s caused an increase in the mean percent of physical damages from 3.25 to 37.5%. The corresponding data for beans at the moisture content of 5% were from 3.7% to 45.7%. With increasing the moisture content from 5 to 15%, the mean values of percentage of damaged beans decreased by 1.4 times. However, with higher increase in the moisture content from 15 to 20%, the mean values of physically damaged beans showed a nonsignificant increasing trend. The relationship between the percent of physical damage with impact velocity and beans moisture content was expressed mathematically. It was found that the model has provided satisfactory results over the whole set of values for the dependent variable

Characteristics of mechanical strength and water absorption in almond and its kernel

The rupture force and energy were measured at different loading velocities, loading direction and almond size for the Mamaei variety of almond. In addition to the rupture properties, the water absorption characteristic of almond kernels was determined. Three mathematical models (Weibull, Peleg and Exponential) for describing the water absorption kinetics of almond kernels were investigated. In this study, a new model based on the time dependent viscoelastic properties of food products was proposed to describe absorption behaviour of almond kernels. The results showed that loading velocity, loading direction and almond size had significant effects on cracking force and energy. The mean values of cracking force and energy were 539 N and 443 mJ, respectively. Almond size had increasing effects on cracking force and energy. Almonds loaded from side ruptured at a lower force and energy than the ones loaded in the front orientation. The studies on water immersion showed that the rate of water uptake was maximum during the initial phase of soaking, with the moisture content of kernel increasing from 5.26% to 22.1% (dry basis) after one hour of soaking. The determined water absorption capacity (WAC, %) of almond kernels was of 1338%. Peleg, the newly developed model, and Weibull models were more accurate for describing the water absorption characteristics of almond kernels. At the very beginning times of soaking, the water absorption velocity was of 0.32 (%/min). The rate of relaxation (Kret in the new developed model) was of 0.0082 (%/min)

Water absorption characteristics of three wood varieties

Water absorption process during wood soaking in water was studied on three varieties of wood. Two models were considered to describe the kinetics: the Peleg model and a new one based on the viscoelastic properties of materials. The soaking data were fitted to the Fick’s model to determine water diffusivity. The pattern of water uptake suggested a two stepprocess, in which more than half of the final absorbed water occurred in the first two days of liquid water contact with wood. This was followed by a period of very slow water uptake. The mean values of water absorption at initial stages of moisture sorption for Afra, Ojamalesh and Roosi genotypes were equal to 13.44, 6.05 and 5.44 (kg/m2 s1/2), respectively. The corresponding mean values of this parameter for the entire soaking process were equal to 6.8, 4.6 and 3.9 (kg/m2 s1/2), respectively. The calculated diffusion coefficients for Afra, Ojamlesh, and Roosi wood varieties were 1.38x10-3, 3.71x10-4, and 4.88x10-4 m2/s, respectively. The newly introduced model was more accurate for describing the water absorption characteristics of wood samples. The maximum value of root-mean-square deviation was 9.36, which demonstrated the suitability of the new model for modelling the experimental absorption characteristics of wood samples

Natural drying characteristics of sesame seeds

Since sesame seeds (SS) are more sensitive to high drying temperature, seeds are dried naturally indoor with either natural or forced convection air. In this study, SS with the initial moisture content of around 50.8% (d.b.) were dried until the final moisture content of about 3.0-3.7% (d.b.). The drying characteristics of SS were investigated under indoor conditions with both forced convection (FC) and natural convection (NC) of air. Modelling the correlation between moisture content with drying time and drying method was carried out by using mathematical and artificial neural networks (ANN). During the FC and NC experiments, the time to reach the final moisture content was found to be 400 and 900 min, respectively. The FC drying times were around 55% shorter than the NC drying times. The effective water diffusion coefficients of SS, under FC and NC conditions, were 3.1×10-11 and 1.1×10-11 m2/s, respectively. The corresponding values for the overall resistance to diffusion were 70.8×105 and 19.6×106 m2 s/kg, respectively. The ANN model was capable of predicting the moisture content with a R2 of 0.999, RMSE of less than 0.0116 and MRE of about 1.73%. It was found that both the Khazaei and Peleg’s models were suitable for predicting the moisture content of sesame seeds. However, the Khazaei model gave better fit to the drying data. It was concluded that ANN represented the drying characteristics better than the mathematical models

ADAPT: a price-stabilizing compliance policy for renewable energy certificates: the case of SREC markets

Currently most Renewable Energy Certificate (REC) markets are defined based on targets which create an artificial step demand function resembling a cliff. This target policy produces volatile prices which can make investing in renewables a risky proposition. In this paper, we propose an alternative policy called Adjustable Dynamic Assignment of Penalties and Targets (ADAPT) which uses a sloped compliance penalty and a self-regulating requirement schedule, both designed to stabilize REC prices, helping to alleviate a common weakness of environmental markets. To capture market behavior, we model the market as a stochastic dynamic programming problem to understand how the market might balance the decision to use a REC now versus holding it for future periods (in the face of uncertain new supply). Then, we present and prove some of the properties of this market, and finally we show that this mechanism reduces the volatility of REC prices which should stabilize the market and encourage long-term investment in renewables

Evaluation of low-complexity supervised and unsupervised NILM methods and pre-processing for detection of multistate white goods

According to recent studies by the BBC and the Scottish Fire and Rescue Service, malfunctioning appliances, especially white goods, were responsible for almost 12,000 fires in Great Britain in just over 3 years, and almost everyday in 2019. The top three “offenders” are washing machines, tumble dryers and dishwashers, hence we will focus on these, generally challenging to disaggregate, appliances in this paper. The first step towards remotely assessing safety in the house, e.g., due to appliances not being switched off or appliance malfunction, is by detecting appliance state and consumption from the NILM result generated from smart meter data. While supervised NILM methods are expected to perform best on the house they were trained on, this is not necessarily the case with transfer learning on unseen houses; unsupervised NILM may be a better option. However, unsupervised methods in general tend to be affected by the noise in the form of unknown appliances, varying power levels and signatures. We evaluate the robustness of three well-performing (based on prior studies) low-complexity NILM algorithms in order to determine appliance state and consumption: Decision Tree and KNN (supervised) and DBSCAN (unsupervised), as well as different algorithms for preprocessing to mitigate the effect of noisy data. These are tested on two datasets with different levels of noise, namely REFIT and REDD datasets, resampled to 1 min resolution

Making Code Voting Secure against Insider Threats using Unconditionally Secure MIX Schemes and Human PSMT Protocols

Code voting was introduced by Chaum as a solution for using a possibly infected-by-malware device to cast a vote in an electronic voting application. Chaum's work on code voting assumed voting codes are physically delivered to voters using the mail system, implicitly requiring to trust the mail system. This is not necessarily a valid assumption to make - especially if the mail system cannot be trusted. When conspiring with the recipient of the cast ballots, privacy is broken. It is clear to the public that when it comes to privacy, computers and "secure" communication over the Internet cannot fully be trusted. This emphasizes the importance of using: (1) Unconditional security for secure network communication. (2) Reduce reliance on untrusted computers. In this paper we explore how to remove the mail system trust assumption in code voting. We use PSMT protocols (SCN 2012) where with the help of visual aids, humans can carry out $\mod 10$ addition correctly with a 99\% degree of accuracy. We introduce an unconditionally secure MIX based on the combinatorics of set systems. Given that end users of our proposed voting scheme construction are humans we \emph{cannot use} classical Secure Multi Party Computation protocols. Our solutions are for both single and multi-seat elections achieving: \begin{enumerate}[i)] \item An anonymous and perfectly secure communication network secure against a $t$-bounded passive adversary used to deliver voting, \item The end step of the protocol can be handled by a human to evade the threat of malware. \end{enumerate} We do not focus on active adversaries