Mechanisms Software [UPDATED]
Small-molecule drugs and toxicants commonly interact with more than a single protein target, each of which may have unique effects on cellular phenotype. Although untargeted metabolomics is often applied to understand the mode of action of these chemicals, simple pairwise comparisons of treated and untreated samples are insufficient to resolve the effects of disrupting two or more independent protein targets. Here, we introduce a workflow for dose-response metabolomics to evaluate chemicals that potentially affect multiple proteins with different potencies. Our approach relies on treating samples with various concentrations of compound prior to analysis with mass spectrometry-based metabolomics. Data are then processed with software we developed called TOXcms, which statistically evaluates dose-response trends for each metabolomic signal according to user-defined tolerances and subsequently groups those that follow the same pattern. Although TOXcms was built upon the XCMS framework, it is compatible with any metabolomic data-processing software. Additionally, to enable correlation of dose responses beyond those that can be measured by metabolomics, TOXcms also accepts data from respirometry, cell death assays, other omic platforms, etc. In this work, we primarily focus on applying dose-response metabolomics to find off-target effects of drugs. Using metformin and etomoxir as examples, we demonstrate that each group of dose-response patterns identified by TOXcms signifies a metabolic response to a different protein target with a unique drug binding affinity. TOXcms is freely available on our laboratory website at .
Mechanisms Software
Software defined network (SDN) decouples the network control and data planes. Despite various advantages of SDNs, they are vulnerable to various security attacks such anomalies, intrusions, and Denial-of-Service (DoS) attacks and so on. On the other hand, any anomaly and intrusion in SDNs can affect many important domains such as banking system and national security. Therefore, the anomaly detection topic is a broad research domain, and to mitigate these security problems, a great deal of research has been conducted in the literature. In this paper, the state-of-the-art schemes applied in detecting and mitigating anomalies in SDNs are explained, categorized, and compared. This paper categorizes the SDN anomaly detection mechanisms into five categories: (1) flow counting scheme, (2) information-based scheme, (3) entropy-based scheme, (4) deep learning, and (5) hybrid scheme. The research gaps and major existing research issues regarding SDN anomaly detection are highlighted. We hope that the analyses, comparisons, and classifications might provide directions for further research.
Software failures may be due to bugs, ambiguities, oversights or misinterpretation of the specification that the software is supposed to satisfy, carelessness or incompetence in writing code, inadequate testing, incorrect or unexpected usage of the software or other unforeseen problems.
One difference is that in the last stage, the software does not have an increasing failure rate as hardware does. In this phase, the software is approaching obsolescence; there are no motivations for any upgrades or changes to the software. Therefore, the failure rate will not change.
The second difference is that in the useful-life phase, the software will experience a radical increase in failure rate each time an upgrade is made. The failure rate levels off gradually, partly because of the defects create and fixed after the updates.
The upgrades in above figure signify feature upgrades, not upgrades for reliability. For feature upgrades, the complexity of software is possible to be increased, since the functionality of the software is enhanced. Even error fixes may be a reason for more software failures if the bug fix induces other defects into the software. For reliability upgrades, it is likely to incur a drop in software failure rate, if the objective of the upgrade is enhancing software reliability, such as a redesign or reimplementation of some modules using better engineering approaches, such as clean-room method.
Built with standard components: Well-understood and extensively tested standard element will help improve maintainability and reliability. But in the software industry, we have not observed this trend. Code reuse has been around for some time but to a minimal extent. There are no standard elements for software, except for some standardized logic structures.
An analysis mechanism represents a pattern that constitutes a common solutionto a common problem. They may show patterns of structure, patterns of behavior,or both. They are used during analysis to reduce the complexity of analysis, andto improve its consistency by providing designers with a short-handrepresentation for complex behavior. Mechanisms allow the analysis effort tofocus on translating the functional requirements into software concepts withoutbogging-down in the specification of relatively complex behavior needed tosupport the functionality but not central to it. Analysis mechanisms oftenresult from the instantiation of one or more analysispatterns.
Analysis mechanisms are primarily used to represent 'placeholders' forcomplex technology in the middle and lower layers of the architecture. By usingthe mechanisms as 'placeholders' in the architecture, the architecting effort isless likely to become distracted by the details of mechanism behavior. As anexample, the need to have object lifetimes span use cases, process lifetimes, orsystem shutdown and start-up defines the need for object persistence.Persistence is a particularly complex mechanism, and during analysis we do notwant to be distracted by the details of how we are going to achieve persistence.This gives rise to a 'persistence' analysis mechanism which allows us to speakof persistent objects and capture the requirements we will have on thepersistence mechanism without worrying about what exactly the persistencemechanism will do or how it will work.
Analysis mechanisms are typically, but not necessarily,unrelated to the problem domain, but instead are "computer science"concepts; as a result they typically occupy the middle and lower layers of thearchitecture. They provide specific behaviors to a domain-related class orcomponent, or correspond to the implementation of cooperation between classesand/or components. They may be implemented as a
Other typical mechanisms include: Message routing
Process control and synchronization
Transaction management
Information Exchange
Security
Redundancy
Error reporting
Format conversion
DescribingAnalysis Mechanisms
Analysis mechanisms are documented in the Artifact: Software Architecture Document includes a relationship (or mapping) of analysis mechanisms to design mechanisms to implementation mechanisms, and the associated rationale for these choices.
Software update is an important mechanism by which security changes and improvements are made in software, and this seemingly simple concept encompasses a wide variety of practices, mechanisms, policies, and technologies. To explore the landscape further, the Forum on Cyber Resilience hosted a workshop featuring invited speakers from government, the private sector, and academia. This publication summarizes the presentations and discussions from the workshop.
The Principal Software Engineer, Perception Safety Mechanisms will report within the Safety Software Engineering organisation and support the creation of reliable, safety-critical software that monitors the vehicle and the environment.
Given your background developing software for autonomous vehicles and/or mobile robotics applications, you'll have a major, positive impact on the performance, reliability, and safety of the Outrider System.
This position requires exceptional software engineering skills, understanding of the full development life cycle, attention to detail, and ability to learn in unstructured environments. You will be responsible for helping build and support autonomous vehicle systems that redefine large enterprise supply chains and boast safe, error-free, and effective operational performance.
This role is ideal for someone who wants to be a part of an elite, impactful development unit pushing confined-area, heavy-vehicle autonomy into the mainstream. We're a team of builders that's passionate about start-to-finish, production-oriented development and rapidly introducing our software to the real world of logistics.
The opportunity offers a technical, hands-on, software engineer the chance to help develop a market-defining, enterprise-grade robotics product that combines autonomous vehicle technologies with a software-as-a-service (SaaS) business model. 041b061a72