Importance of Social Networks for Knowledge Sharing and the Impact of Collaboration on Network Innovation in Online Communities

Innovation results from interactions between different sources of knowledge, where these sources aggregate into groups interacting within (intra) and between (inter) groups. Interaction among groups for innovation generation is defined as the process by which an innovation is communicated through certain channels over time among members of a social system. Apart from the discussion about knowledge management within organizations and the discussion about social network analysis of organizations on the topic of innovation and talks about various trade-offs between strength of ties and bridging ties between different organizational groups, within the topic of open source software (OSS) development researchers have used social network theories to investigate OSS phenomenon including communication among developers. It is already known that OSS groups are more networked than the most organizational communities; In OSS network, programmers can join, participate and leave a project at any time, and in fact developers can collaborate not only within the same project but also among different projects or teams. One distinguished feature of the open source software (OSS) development model is the cooperation and collaboration among the members, which will cause various social networks to emerge. In this chapter, the existing gap in the literature with regard to the analysis of cluster or group structure as an input and cluster or group innovation as an output will be addressed, where the focus is on “impact of network cluster structure on cluster innovation and growth” by Behfar et al., that is, how intra- and inter-cluster coupling, structural holes and tie strength impact cluster innovation and growth, and “knowledge management in OSS communities: relationship between dense and sparse network structures.” by Behfar et al., that is, knowledge transfer in dense network (inside groups) impacts on knowledge transfer in sparse network (between groups)

DEVELOPMENT STRATEGY AND MANAGEMENT OF AI-BASED VULNERABILITY DETECTION APPLICATIONS IN ENTERPRISE SOFTWARE ENVIRONMENT

Industries are now struggling with high level of security-risk vulnerabilities in their software environment which mainly originate from open-source dependencies. Industries’ percentage of open source in codebases is about 54% whereas ones with high security risks is about 30% (Synopsys 2018). While there are existing solutions for application security analysis, these typically only detect a limited subset of possible errors based on pre-defined rules. With the availability of open-source vulnerability resources, it is now possible to use data-driven techniques to discover vulnerabilities. Although there are a few AI-based solutions available, but there are some associated challenges: 1) use of artificial intelligence for application security (AppSec) towards vulnerability detection has been very limited and definitely not industry oriented, 2) the strategy to develop, use and manage such AppSec products in enterprises have not been investigated; therefore cybersecurity firms do not use even limited existing solutions. In this study, we aim to address these challenges with some strategies to develop such AppSec, their use management and economic values in enterprise environment

Design and development of cationic liposomes as DNA vaccine adjuvants

Cationic liposomes have been extensively explored for their efficacy in delivering nucleic acids, by offering the ability to protect plasmid DNA against degradation, promote gene expression and, in the case of DNA vaccines, induce both humoural and cellular immune responses. DNA vaccines may also offer advantages in terms of safety, but they are less effective and need an adjuvant to enhance their immunogenicity. Therefore, cationic liposomes can be utilised as delivery systems and/or adjuvants for DNA vaccines to stimulate stronger immune responses. To explore the role of liposomal systems within plasmid DNA delivery, parameters such as the effect of lipid composition, method of liposome preparation and presence of electrolytes in the formulation were investigated in characterisation studies, in vitro transfection studies and in vivo biodistribution and immunisation studies. Liposomes composed of 1,2-dioleoyl-sn-glycero 3-phosphoethanolamine (DOPE) in combination with 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) or 1,2-stearoyl-3- trimethylammonium-propane (DSTAP) were prepared by the lipid hydration method and hydrated in aqueous media with or without presence of electrolytes. Whilst the in vitro transfection efficiency of all liposomes resulted to be higher than Lipofectin, DSTAP-based liposomes showed significantly higher transfection efficiency than DOTAP-based formulations. Furthermore, upon intramuscular injection of liposomal DNA vaccines, DSTAP-based liposomes showed a significantly stronger depot effect at the injection site. This could explain the result of heterologous immunisation studies, which revealed DSTAP-based liposomal vaccines induce stronger immune responses compared to DOTAP-based formulations. Previous studies have shown that having more liposomally associated antigen at the injection site would lead to more drainage of them into the local lymph nodes. Consequently, this would lead to more antigens being presented to antigen presenting cells, which are circulating in lymph nodes, and this would initiate a stronger immune response. Finally, in a comparative study, liposomes composed of dimethyldioctadecylammonium bromide (DDA) in combination with DOPE or immunostimulatory molecule of trehalose 6,6-dibehenate (TDB) were prepared and investigated in vitro and in vivo. Results showed that although DDA:TDB is not able to transfect the cells efficiently in vitro, this formulation induces stronger immunity compared to DDA:DOPE due to the immunostimulatory effects of TDB. This study demonstrated, while the presence of electrolytes did not improve immune responses, small unilamellar vesicle (SUV) liposomes induced stronger humoural immune responses compared to dehydration rehydration vesicle (DRV) liposomes. Moreover, lipid composition was shown to play a key role in in vitro and in vivo behaviour of the formulations, as saturated cationic lipids provided stronger immune responses compared to unsaturated lipids. Finally, heterologous prime/boost immunisation promoted significantly stronger immune responses compared to homologous vaccination of DNA vaccines, however, a single immunisation of subunit vaccine provoked comparable levels of immune response to the heterologous regimen, suggesting more immune efficiency for subunit vaccines compared to DNA vaccines

Numerical Simulation of Fault Impacts for Commercial Walk-in Freezers

Refrigeration systems can undergo many faults that could negatively affect their operation and performance. This paper describes a modeling process to simulate the fault impacts on the operation of a commercial walk-in freezer using semi-empirical models. These models often require less modeling effort than full forward models and could be used in scenarios where detailed information is missing, such as in field-measured systems. An important characteristic of a typical walk-in refrigeration system is the existence of a liquid-line receiver after the condenser, which significantly changes the behavior of the cycle, in comparison to a receiver-less system. Component models described in this paper consist of: a compressor, two heat exchangers, pipelines, receiver, and thermostatic expansion valve. The semi-empirical component models are partially based on physics, and partially based on some empirical coefficients. They are able to predict several dependent variables, including mass flow rates, heat transfer rates, power consumption, and pressures. In this paper, the individual component models are presented and trained with a limited set of faulted and fault-free experimental data. The faults are: heat exchanger fouling, liquid-line restriction, and compressor valve leakage. The results show that models for major components, such as compressor and heat exchangers, give good predictions for some of the most important performance indices. Modeling challenges and future research are outlined

Analysis of Information Propagation in Ethereum Network Using Combined Graph Attention Network and Reinforcement Learning to Optimize Network Efficiency and Scalability

Blockchain technology has revolutionized the way information is propagated in decentralized networks. Ethereum plays a pivotal role in facilitating smart contracts and decentralized applications. Understanding information propagation dynamics in Ethereum is crucial for ensuring network efficiency, security, and scalability. In this study, we propose an innovative approach that utilizes Graph Convolutional Networks (GCNs) to analyze the information propagation patterns in the Ethereum network. The first phase of our research involves data collection from the Ethereum blockchain, consisting of blocks, transactions, and node degrees. We construct a transaction graph representation using adjacency matrices to capture the node embeddings; while our major contribution is to develop a combined Graph Attention Network (GAT) and Reinforcement Learning (RL) model to optimize the network efficiency and scalability. It learns the best actions to take in various network states, ultimately leading to improved network efficiency, throughput, and optimize gas limits for block processing. In the experimental evaluation, we analyze the performance of our model on a large-scale Ethereum dataset. We investigate effectively aggregating information from neighboring nodes capturing graph structure and updating node embeddings using GCN with the objective of transaction pattern prediction, accounting for varying network loads and number of blocks. Not only we design a gas limit optimization model and provide the algorithm, but also to address scalability, we demonstrate the use and implementation of sparse matrices in GraphConv, GraphSAGE, and GAT. The results indicate that our designed GAT-RL model achieves superior results compared to other GCN models in terms of performance. It effectively propagates information across the network, optimizing gas limits for block processing and improving network efficiency

Understanding the IKEA Warehouse Processes and Modeling using Modular Petri Nets

Nowadays, large warehouses handle a huge number of products. Handling the enormity and different types of (range) products also demand complex warehouse processes. In this paper, the IKEA warehouse in Stavanger, Norway, is taken as an example, which stores, manages, and sells ready-to-assemble furniture, kitchen appliances and home accessories. The focus of this paper is to understand the warehouse processes that make the warehouse popular with the customers. Petri net is used to model the processes, and by simulation, the effect of the processes are understood. This paper shows how the processes integrate the large range of products, customer service, and the supply chain. The logistics flow is represented with a modular Petri Net model using the tool known as the General-purpose Petri Net Simulator (GPenSim). The goal of this paper is also to determine and propose any changes for a more efficient warehouse performance.publishedVersio

Genomic chart guiding embryonic stem cell cardiopoiesis

Gene expression analysis of embryonic stem cells undergoing guided cardiogenic differentiation reveals the molecular fingerprint for committing to cardiac cell fate

1,7-Sigmatropic rearrangement in 1,2-dihydro and 1,2,3,4-tetrahydroquinoline synthesis using marine sponge/H2C2O4 as a catalyst

AbstractMarine sponge/oxalic acid was found to be an efficient catalyst for the imino Diels–Alder reaction of synthesized N-aryl-substituted aldimines and various alkenes to provide 1,2-dihyro and 1,2,3,4-tetrahydro-quinolines using 1,7-sigmatropic rearrangement with induction of chirality. Mild reaction conditions, simple experimental procedure, good yields of products, and optical active induction render this new method attractive for 1,7-sigmatropic rearrangement of imino Diels–Alder reaction

Biotelemetric Wireless Intracranial Pressure Monitoring: An In Vitro

Assessment of intracranial pressure (ICP) is of great importance in management of traumatic brain injuries (TBIs). The existing clinically established ICP measurement methods require catheter insertion in the cranial cavity. This increases the risk of infection and hemorrhage. Thus, noninvasive but accurate techniques are attractive. In this paper, we present two wireless, batteryless, and minimally invasive implantable sensors for continuous ICP monitoring. The implants comprise ultrathin (50 μm) flexible spiral coils connected in parallel to a capacitive microelectromechanical systems (MEMS) pressure sensor. The implantable sensors are inductively coupled to an external on-body reader antenna. The ICP variation can be detected wirelessly through measuring the reader antenna’s input impedance. This paper also proposes novel implant placement to improve the efficiency of the inductive link. In this study, the performance of the proposed telemetry system was evaluated in a hydrostatic pressure measurement setup. The impact of the human tissues on the inductive link was simulated using a 5 mm layer of pig skin. The results from the in vitro measurement proved the capability of our developed sensors to detect ICP variations ranging from 0 to 70 mmHg at 2.5 mmHg intervals

Protective effect of Sildenafil on contralateral epididymal sperm concentration and motility following unilateral blunt testicular trauma in pre-pubertal male mice

Background and aims: Blunt testicular trauma adversely affects fertility in later periods. The purpose of the present study was to examine the effect of sildenafil on contralateral epididymal sperm count and motility following unilateral blunt testicular trauma in mice. Methods: In this randomized controlled experimental study, 24 pre-pubertal male mice were distributed into four groups of six mice each. In two groups of mice, the abdomen was opened and the right testis was placed on a sterile firm surface and 5 g sterile weight was dropped on to the testis from a height of 10 cm. One of these groups received sildenafil (0.1 mg/kg per day) intraperitoneally for 7 days starting from the day of induction of trauma. A control group and a sildenafil control group were also included. The left epididymal sperm characteristics of all animals were evaluated after 7 weeks. Results: Trauma caused a significant decrease in the sperm concentration and motility as compared to control mice (P<0.05). Sildenafil administration markedly ameliorated all changes in the above-mentioned parameters (P<0.05). Conclusion: Sildenafil administration could attenuate blunt testicular trauma-induced contralateral epididymal sperm impairment