Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

A hybrid homogeneously weighted moving average control chart for process monitoring: Discussion

The sensitivity of a monitoring scheme depends on many factors including the variance of the charting statistic which is very important in the computation of the control limits. This paper discusses the computation of the variance of the recently proposed hybrid homogeneously weighted moving average (HHWMA) $\overline{X}$ scheme which was based on an incorrect assumption. The correct variance is used to evaluate the run-length characteristics of the HHWMA $\overline{X}$ scheme. It is observed that the incorrect variance has a significant impact on the sensitivity (or performance) of the HHWMA $\overline{X}$ scheme.     

Full AC analysis of value of DER to the grid and optimal DER scheduling

This paper presents part of the work ComEd and Quanta Technology have performed to quantify the locational and temporal value of DER to avoid distribution grid upgrade investments. It focuses on the formulation of a robust and efficient algorithm for DER optimal dispatch on a distribution feeder to mitigate the violation of current and voltage limits using the allocated cost of capacity and locational marginal value of real and reactive DER injection/withdrawal.     

The dynamic effect of Micro-MHD convection on bubble grown at a horizontal microelectrode

Relatively low efficiency is the biggest obstacle to the popularization of water electrolysis, which is a particularly feasible way to produce super-pure hydrogen. Imposing a magnetic field can increase the hydrogen production efficiency of water electrolysis. However, the enhancement's detailed mechanism still lacks an insightful understanding of the bubbles' micro vicinity. Our recent work aims to understand why the micro-magnetohydrodynamic (MHD) convection hinders single bubbles' detachment on the microelectrode. A water electrolysis experiment by microelectrode is performed under an electrode-normal magnetic field, and dynamic analysis of the single bubble growing on microelectrodes is performed. The variation of bubble diameter with time in the presence or absence of the magnetic field was measured, and the forces acting on the bubble were quantified. The result shows that the micro-MHD convection, induced by Lorentz force, can give rise to a downward hydrodynamic pressure force that will not appear in large-scale MHD convection. This force can be of the same magnitude as the surface tension, so it dramatically hinders bubbles' detachment. Besides, the Kelvin force provides a new potential way for further improving the efficiency of water electrolysis.     

Thermodynamic modeling of gas solubility in aqueous sodium chloride solution

An electrolyte Equation of State is presented by combining the Cubic Plus Association Equation of State,Mean Spherical Approximation and the Born equation.This new model uses experimental relative static permittivity,intend to predict well the activity coefficients of individual ions (ACI) and liquid densities of aqueous solutions.This new model is applied to model water + NaCl binary system and water + gas +NaCl ternary systems.The cation/anion-water interaction parameters of are obtained by fitting the exper-imental data of ACI,mean ionic activity coefficients (MIAC) and liquid densities of water + NaCl binary system.The cation/anion-gas interaction parameters are obtained by fitting the experimental data of gas solubilities in aqueous NaCl solutions.The modeling results show that this new model can correlate well with the phase equilibrium and volumetric properties.Without gas,predictions for ACI,MIAC,and liquid densities present relative average deviations of 1.3％,3.6％ and 1.4％ compared to experimental ref-erence values.For most gas-containing systems,predictions for gas solubilities present relative average deviations lower than 7.0％.Further,the contributions of ACI,and salting effects of NaCl on gases are ana-lyzed and discussed.     

Cyberbullying: Effect of emergency perception on the helping tendencies of bystanders

The effect of the emergency perception of bystanders of cyberbullying victims on helping behaviors is often neglected in research on cyberbullying. In this study, we explored the influence of this cognitive factor on cyber-bystanders’ helping tendencies as well as elucidated possible underlying processes. The results of two studies were reported. In Study 1, 150 undergraduates read a true case of a girl experiencing cyberbullying. The results indicated that when the participants perceived the victim’s situation to be more critical (i.e., higher emergency perception), their helping tendencies were stronger, partly through increased state empathy followed by feelings of responsibility to help. In Study 2, we randomly assigned 300 undergraduates to two groups. The low emergency group read the same cyberbullying case as Study 1, whereas the cyberbullying case read by the high emergency group contained additional emergency information of the victim. The results indicated that the high emergency group expressed stronger helping tendencies than did the low emergency group. This effect was caused by a stronger perception that the victim was in an emergency situation, which not only strengthened the participants’ helping tendencies directly but also indirectly through increasing their state empathy and feelings of responsibility to help.     

Microbial susceptibility of various polymers and evaluation of thermoplastic elastomers with antimicrobial additives

The incursion of microbial growth on polymeric products can deteriorate their performance and lead to the development of undesirable staining and odors. A growing trend in the industry has aimed to reduce microbial populations on high-touch surfaces via the use of antimicrobials to protect material aesthetics and durability or to prevent the spread of pathogenic microorganisms. In this study, a variety of plastic substrates (30 unique polymer compounds), including poly(acrylonitrile-co-butadiene-co-styrene), poly(butylene terephthalate), poly(etherimide), various thermoplastic elastomers (TPEs), poly(carbonates), and poly(amides), were screened for susceptibility to microbial attack using American Society for Testing and Materials (ASTM) G21 (fungi susceptibility), Japanese Industrial Standard (JIS) Z2801, and modified ASTM E1428-15a (bacterial susceptibility) test standards. TPEs were determined to be most susceptible to microbial attack under the appropriate environmental conditions. Subsequent studies assessed the use of an antimicrobial additive, zinc pyrithione (ZPT), for potential efficacy in a variety of TPE blends for diverse target market applications. ZPT proved to be very effective in protecting TPEs, reducing Staphylococcus aureus and Escherichia coli populations by 99.9% or more in JIS Z2801 testing and inhibiting fungal growth (rating = 0) according to the ASTM G21 standard.     

The Age-Sensitive Efficacy of Calorie Restriction on Mitochondrial Biogenesis and mtDNA Damage in Rat Liver

Calorie restriction (CR) is the most efficacious treatment to delay the onset of age-related changes such as mitochondrial dysfunction. However, the sensitivity of mitochondrial markers to CR and the age-related boundaries of CR efficacy are not fully elucidated. We used liver samples from ad libitum-fed (AL) rats divided in: 18-month-old (AL-18), 28-month-old (AL-28), and 32-month-old (AL-32) groups, and from CR-treated (CR) 28-month-old (CR-28) and 32-month-old (CR-32) counterparts to assay the effect of CR on several mitochondrial markers. The age-related decreases in citrate synthase activity, in TFAM, MFN2, and DRP1 protein amounts and in the mtDNA content in the AL-28 group were prevented in CR-28 counterparts. Accordingly, CR reduced oxidative mtDNA damage assessed through the incidence of oxidized purines at specific mtDNA regions in CR-28 animals. These findings support the anti-aging effect of CR up to 28 months. Conversely, the protein amounts of LonP1, Cyt c, OGG1, and APE1 and the 4.8 Kb mtDNA deletion content were not affected in CR-28 rats. The absence of significant differences between the AL-32 values and the CR-32 counterparts suggests an age-related boundary of CR efficacy at this age. However, this only partially curtails the CR benefits in counteracting the generalized aging decline and the related mitochondrial involvement.