A reinforcement learning-based hybrid modeling framework for bioprocess kinetics identification.

Constructing predictive models to simulate complex bioprocess dynamics, particularly time-varying (i.e., parameters varying over time) and history-dependent (i.

Personal and narrative review of the current management of the injured anterior cruciate ligament of the knee in the UK with reference to surgical treatment versus rehabilitation.

Rupture of the anterior cruciate ligament of the knee is a common injury occurring mostly in young athletic individuals taking part in pivoting, cutting and jumping sports. It is demonstrated by anterolateral rotatory instability on clinical testing. As yet there are no clear guidelines as to whom will benefit from surgical reconstruction as opposed to rehabilitation alone, apart from elite athletes (defined as varsity players or those participating in sport at national or international level).

Integrating Autoencoder and Heteroscedastic Noise Neural Networks for the Batch Process Soft-Sensor Design.

Viscosity represents a key product quality indicator but has been difficult to measure in-process in real-time. This is particularly true if the process involves complex mixing phenomena operated at dynamic conditions. To address this challenge, in this study, we developed an innovative soft sensor by integrating advanced artificial neural networks.

Frontal fibrosing alopecia: survey of severity assessment methods in routine clinical practice and validation of the International Frontal Fibrosing Alopecia Cooperative Group measurement guidance.

Background: The lack of validated and responsive outcome measures in the management of frontal fibrosing alopecia (FFA) significantly limits assessment of disease progression and treatment response over time.

Aim: To understand how FFA extent and progression is currently assessed in UK specialist centres, to validate components of the International FFA Cooperative Group (IFFACG) statement on FFA assessment, and to identify pragmatic advice to improve FFA management in clinic.

Methods: Consultant dermatologists with a specialist interest in hair loss (n = 17) were invited to take part.

Moral Status for Malware! The Difficulty of Defining Advanced Artificial Intelligence.

The suggestion has been made that future advanced artificial intelligence (AI) that passes some consciousness-related criteria should be treated as having moral status, and therefore, humans would have an ethical obligation to consider its well-being. In this paper, the author discusses the extent to which software and robots already pass proposed criteria for consciousness; and argues against the moral status for AI on the grounds that human malware authors may design malware to fake consciousness. In fact, the article warns that malware authors have stronger incentives than do authors of legitimate software to create code that passes some of the criteria.