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Selective Regulation of B-Raf Dependent K-Ras/Mitogen-Activated Protein by Natural Occurring Multi-kinase Inhibitors in Cancer Cells

Introduction: Cancer is one of the most difficult challenges faced by humanity due to its many associated issues, such as inability to prevent diseases, treatment safety, and high mortality rate. In cancer, a variety of cellular signaling is activated to ensure malignancy transformation, angiogenesis and metastasis. The most efficient signaling pathway in cancer is mitogen-activated protein kinase
Healthcare

A Deep Learning Approach for Vehicle Detection

The autonomous driving needs some several features to achieve driving without human interference. One of these features is vehicle classification and detection since the target of this process is to help the CPU ''Central Processing Unit" of the vehicle to see what is around the vehicle, in order to evaluate the situation to take the best decision for each situation in real time. This paper is

Artificial Intelligence

User Privacy in Legacy Mobile Network Protocols

Current security issues in mobile networks have great impact on user privacy. With the focus directed to signaling protocols security, network security and air interface encryption, critical configurations and design flaws that would impact user privacy can be overlooked. The leakage of IMSI on the broadcast channels during network paging is a privacy issue worth considering. In this paper, we

Artificial Intelligence

Enriched environmental conditions modify the gut microbiome composition and fecal markers of inflammation in parkinson’s disease

Recent findings suggest an implication of the gut microbiome in Parkinson’s disease (PD) patients. PD onset and progression has also been linked with various environmental factors such as physical activity, exposure to pesticides, head injury, nicotine, and dietary factors. In this study, we used a mouse model, overexpressing the complete human SNCA gene (SNCA-TG mice) modeling familial and

Artificial Intelligence

NONYM!ZER: Mitigation Framework for Browser Fingerprinting

Not only recent compelled cookies regulations have radically restrained their threats but also increased people awareness has played a fundamental part. This has placed huge pressure on enterprises to find alternatives to bridge this gap and satisfy business demands. Since then fingerprinting has gained enormous popularity. In this paper, we introduce 'nonym!zer' as a mitigation framework for

Software and Communications

Security Perspective in RAMI 4.0

Cloud Computing, Internet of Things (IoT) are the main technologies contributing to the adoption of the fourth revolution in manufacturing, Industry 4.0 also known as smart manufacturing or digital manufacturing. Smart manufacturing facilitates and accelerates the process of manufacturing with the connection of all the systems related to the manufacturing process starting with the Enterprise

Artificial Intelligence
Software and Communications

Cyber Threats and Policies for Industrial Control Systems

Modern Industrial Control Systems (ICS) are very important in our life as we use information and communication technology (ICT) to manage, monitor and improve ICS usage. This continually exposes it to new threats due to the vulnerabilities and architectural weaknesses introduced by the extensive use of ICT. Different types of ICSs have common attacks in which these attacks are very sophisticated

Artificial Intelligence

A Novel Vehicle Detection System

Histogram of oriented gradient (HOG) feature has been widely used in vehicle detection. In this paper, a modified version of HOG is proposed by introducing compass gradient into the HOG calculation. Three different versions of the modified HOG features are used as an input for linear and nonlinear support vector machine (SVM). The modified HOG variants proved to have better classification

Artificial Intelligence

Using Molecular Fingerprints as Descriptors in Toxicity Prediction: A Survey

During humans' lifetime, their bodies deal with different chemicals through various sources. Chemical toxicity is a challenging problem that needs rapid and efficient methods for evaluation of environmental chemicals, or medications development. Computer science helps in toxicity prediction through building models from pre-tested compounds by learning from data. These models raise a flag to avoid

Artificial Intelligence

A Real-Time Social Network- Based Traffic Monitoring Vehicle Tracking System

Social networking has become an essential part of our daily lives. tTe integration of social networking communication model and Internet of Things (IoT) provides the users with a greater advantage than the benefit of using each one alone. This paper presents a real-time traffic monitoring and vehicle tracking for the public or private transportation sectors. The proposed system uses a social

Artificial Intelligence