Comparative study of trastuzumab modification analysis using mono/multi-epitope affinity technology with LC-QTOF-MS.

Dynamic tracking analysis of monoclonal antibodies (mAbs) biotransformation is crucial, as certain modifications could inactivate the protein and reduce drug efficacy. However, a particular challenge (i.e.

Bridging the Micro and Macro: Calibration of Agent-Based Model Using Mean-Field Dynamics.

Calibration of agent-based models (ABM) is an essential stage when they are applied to reproduce the actual behaviors of distributed systems. Unlike traditional methods that suffer from the repeated trial and error and slow convergence of iteration, this article proposes a new ABM calibration approach by establishing a link between agent microbehavioral parameters and systemic macro-observations. With the assumption that the agent behavior can be formulated as a high-order Markovian process, the new approach starts with a search for an optimal transfer probability through a macrostate transfer equation.

On Iterative Proportional Updating: Limitations and Improvements for General Population Synthesis.

Population synthesis is the foundation of the agent-based social simulation. Current approaches mostly consider basic population and households, rather than other social organizations. This article starts with a theoretical analysis of the iterative proportional updating (IPU) algorithm, a representative method in this field, and then gives an extension to consider more social organization types.

TiDEC: A Two-Layered Integrated Decision Cycle for Population Evolution.

Agent-based simulation is a useful approach for the analysis of dynamic population evolution. In this field, the existing models mostly treat the migration behavior as a result of utility maximization, which partially ignores the endogenous mechanisms of human decision making. To simulate such a process, this article proposes a new cognitive architecture called the two-layered integrated decision cycle (TiDEC) which characterizes the individual's decision-making process.

A Survey of Cognitive Architectures in the Past 20 Years.

Building autonomous systems that achieve human level intelligence is one of the primary objectives in artificial intelligence (AI). It requires the study of a wide range of functions robustly across different phases of human cognition. This paper presents a review of agent cognitive architectures in the past 20 year's AI research.

A negative feedback loop between miR-200b and the nuclear factor-κB pathway via IKBKB/IKK-β in breast cancer cells.

MicroRNAs (miRNAs) act as important post-transcriptional regulators of gene expression in diverse signalling pathways. However, the relationship between miR-200b and the nuclear factor-κB (NF-κB) signalling pathway remains poorly understood in breast cancer cells. In the current study, we show that IKBKB is a direct target of miR-200b, and that miR-200b downregulates IKBKB expression via directly binding to its 3'-UTR.