Performance of Portland Limestone Cements: Cements Designed to Be More Sustainable That Include up to 15% Limestone Addition

In 2009, ASTM and AASHTO permitted the use of up to 5% interground limestone in ordinary portland cement (OPC) as a part of ASTM C150/AASHTO M85. When this project was initiated a new proposal was being discussed that would enable up to 15% interground limestone to be considered in ASTM C595/AASHTO M234 cement. This project was initiated to provide rapid feedback to INDOT for use in discussions regarding these specifications (this has become ASTM C595/AASHTO M240). PLC is designed to enable more sustainable construction which may significantly reduce the CO2 that is embodied in the built infrastructure while extending the life of cement quarries. The physical and chemical properties of the cementitious materials used in this study were examined. PLC is typically a finer cement (10 to 30% Blaine fineness) with a reduction in the coarse clinker particles (\u3e20µm) and an increase in fine particles which are primarily limestone. Isothermal calorimetry and chemical shrinkage results imply that these PLC materials have a similar or slight greater reaction and would be able to be used interchangeably with OPC in practice as it relates to the rate of reaction. The PLC mortars exhibited relatively similar activation energies compared to the corresponding OPCs allowing the maturity method to be used by INDOT for both the PLC and OPC systems. The mechanical properties of OPC and PLC were generally similar with the PLC typically having slightly higher early age strengths but similar 28 day strengths. No significant change in drying shrinkage or restrained shrinkage cracking was observed for the PLC when compared with OPC (Barrett et al. 2013). The PLC has similar volumes of permeable voids as the OPC. The chloride diffusion coefficients in the PLC systems may range from 0 to 30% higher than the OPCs. The PLC showed synergistic benefits when paired with fly ash. Based on the available literature and available testing results INDOT could consider PLC, as specified in accordance with ASTM C-595/AASHTO M 240, to be a suitable option for use in INDOT concrete applications

A Q-learning-based approach for deploying dynamic service function chains

As the size and service requirements of today’s networks gradually increase, large numbers of proprietary devices are deployed, which leads to network complexity, information security crises and makes network service and service provider management increasingly difficult. Network function virtualization (NFV) technology is one solution to this problem. NFV separates network functions from hardware and deploys them as software on a common server. NFV can be used to improve service flexibility and isolate the services provided for each user, thus guaranteeing the security of user data. Therefore, the use of NFV technology includes many problems worth studying. For example, when there is a free choice of network path, one problem is how to choose a service function chain (SFC) that both meets the requirements and offers the service provider maximum profit. Most existing solutions are heuristic algorithms with high time efficiency, or integer linear programming (ILP) algorithms with high accuracy. It’s necessary to design an algorithm that symmetrically considers both time efficiency and accuracy. In this paper, we propose the Q-learning Framework Hybrid Module algorithm (QLFHM), which includes reinforcement learning to solve this SFC deployment problem in dynamic networks. The reinforcement learning module in QLFHM is responsible for the output of alternative paths, while the load balancing module in QLFHM is responsible for picking the optimal solution from them. The results of a comparison simulation experiment on a dynamic network topology show that the proposed algorithm can output the approximate optimal solution in a relatively short time while also considering the network load balance. Thus, it achieves the goal of maximizing the benefit to the service provider

User-Defined Privacy Location-Sharing System in Mobile Online Social Networks

With the fusion of social networks and location-based services, location sharing is one of the most important services in mobile online social networks (mOSNs). In location-sharing services, users have to provide their location information to service provider. However, location information is sensitive to users, which may cause a privacy-preserving issue needs to be solved. In the existing research, location-sharing services, such as friends’ query, does not consider the attacks from friends. In fact, a user may not trust all of his/her friends, so just a part of his/her friends will be allowed to obtain the user’s location information. In addition, users’ location privacy and social network privacy should be guaranteed. In order to solve the above problems, we propose a new architecture and a new scheme called User-Defined Privacy Location-Sharing (UDPLS) system for mOSNs. In our scheme, the query time is almost irrelevant to the number of friends. We also evaluate the performance and validate the correctness of our proposed algorithm through extensive simulations

Performance Analysis of Non-ideal Wireless PBFT Networks with mmWave and Terahertz Signals

Due to advantages in security and privacy, blockchain is considered a key enabling technology to support 6G communications. Practical Byzantine Fault Tolerance (PBFT) is seen as the most applicable consensus mechanism in blockchain-enabled wireless networks. However, previous studies on PBFT do not consider the channel performance of the physical layer, such as path loss and channel fading, resulting in research results that are far from real networks. Additionally, 6G communications will widely deploy high frequency signals such as millimeter wave (mmWave) and terahertz (THz), while the performance of PBFT is still unknown when these signals are transmitted in wireless PBFT networks. Therefore, it is urgent to study the performance of non-ideal wireless PBFT networks with mmWave and THz siganls, so as to better make PBFT play a role in 6G era. In this paper, we study and compare the performance of mmWave and THz signals in non-ideal wireless PBFT networks, considering Rayleigh Fading (RF) and close-in Free Space (FS) reference distance path loss. Performance is evaluated by consensus success rate and delay. Meanwhile, we find and derive that there is a maximum distance between two nodes that can make PBFT consensus inevitably successful, and it is named active distance of PBFT in this paper. The research results not only analyze the performance of non-ideal wireless PBFT networks, but also provide an important reference for the future transmission of mmWave and THz signals in PBFT networks.Comment: IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom) 202

ESCM: An Efficient and Secure Communication Mechanism for UAV Networks

UAV (unmanned aerial vehicle) is gradually entering various human activities. It has also become an important part of satellite-air-ground-sea integrated network (SAGS) for 6G communication. In order to achieve high mobility, UAV has strict requirements on communication latency, and it cannot be illegally controlled as weapons of attack with malicious intentions. Therefore, an efficient and secure communication method specifically designed for UAV network is required. This paper proposes a communication mechanism named ESCM for the above requirements. For high efficiency of communication, ESCM designs a routing protocol based on artificial bee colony algorithm (ABC) for UAV network to accelerate communication between UAVs. Meanwhile, we plan to use blockchain to guarantee the communication security of UAV networks. However, blockchain has unstable links in high mobility network scenarios, resulting in low consensus efficiency and high communication overhead. Therefore, ESCM also introduces the concept of the digital twin, mapping the UAVs from the physical world into Cyberspace, transforming the UAV network into a static network. And this virtual UAV network is called CyberUAV. Then, in CyberUAV, we design a blockchain system and propose a consensus algorithm based on network coding, named proof of network coding (PoNC). PoNC not only ensures the security of ESCM, but also further improves the performance of ESCM through network coding. Simulation results show that ESCM has obvious advantages in communication efficiency and security. Moreover, encoding messages through PoNC consensus can increase the network throughput, and make mobile blockchain static through digital twin can improve the consensus success rate

Hydrogen Sulfide Inhibits L-Type Calcium Currents Depending upon the Protein Sulfhydryl State in Rat Cardiomyocytes

Hydrogen sulfide (H2S) is a novel gasotransmitter that inhibits L-type calcium currents (I Ca, L). However, the underlying molecular mechanisms are unclear. In particular, the targeting site in the L-type calcium channel where H2S functions remains unknown. The study was designed to investigate if the sulfhydryl group could be the possible targeting site in the L-type calcium channel in rat cardiomyocytes. Cardiac function was measured in isolated perfused rat hearts. The L-type calcium currents were recorded by using a whole cell voltage clamp technique on the isolated cardiomyocytes. The L-type calcium channel containing free sulfhydryl groups in H9C2 cells were measured by using Western blot. The results showed that sodium hydrosulfide (NaHS, an H2S donor) produced a negative inotropic effect on cardiac function, which could be partly inhibited by the oxidant sulfhydryl modifier diamide (DM). H2S donor inhibited the peak amplitude of I Ca, L in a concentration-dependent manner. However, dithiothreitol (DTT), a reducing sulfhydryl modifier markedly reversed the H2S donor-induced inhibition of I Ca, L in cardiomyocytes. In contrast, in the presence of DM, H2S donor could not alter cardiac function and L type calcium currents. After the isolated rat heart or the cardiomyocytes were treated with DTT, NaHS could markedly alter cardiac function and L-type calcium currents in cardiomyocytes. Furthermore, NaHS could decrease the functional free sulfhydryl group in the L-type Ca2+ channel, which could be reversed by thiol reductant, either DTT or reduced glutathione. Therefore, our results suggest that H2S might inhibit L-type calcium currents depending on the sulfhydryl group in rat cardiomyocytes

Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources

Background: Data sharing has been a big challenge in biomedical informatics because of privacy concerns. Contextual embedding models have demonstrated a very strong representative capability to describe medical concepts (and their context), and they have shown promise as an alternative way to support deep-learning applications without the need to disclose original data. However, contextual embedding models acquired from individual hospitals cannot be directly combined because their embedding spaces are different, and naive pooling renders combined embeddings useless. Objective: The aim of this study was to present a novel approach to address these issues and to promote sharing representation without sharing data. Without sacrificing privacy, we also aimed to build a global model from representations learned from local private data and synchronize information from multiple sources. Methods: We propose a methodology that harmonizes different local contextual embeddings into a global model. We used Word2Vec to generate contextual embeddings from each source and Procrustes to fuse different vector models into one common space by using a list of corresponding pairs as anchor points. We performed prediction analysis with harmonized embeddings. Results: We used sequential medical events extracted from the Medical Information Mart for Intensive Care III database to evaluate the proposed methodology in predicting the next likely diagnosis of a new patient using either structured data or unstructured data. Under different experimental scenarios, we confirmed that the global model built from harmonized local models achieves a more accurate prediction than local models and global models built from naive pooling. Conclusions: Such aggregation of local models using our unique harmonization can serve as the proxy for a global model, combining information from a wide range of institutions and information sources. It allows information unique to a certain hospital to become available to other sites, increasing the fluidity of information flow in health care