An important consideration of multiobjective optimization (MOO) is the quantitative metrics used for defining the optimality of different solution sets, which is also the basic principle for the design and evaluation of MOO algorithms. Although a plethora of performance metrics have been proposed in the MOO context, there has been a lack of insights on the relationships between metrics. In this paper, we first group the major MOO metrics proposed to date according to four core performance criteria considered in the literature, namely, capacity, convergence, diversity, and convergence-diversity. Then, a comprehensive study is conducted to investigate the relationships among representative group metrics, including generational distance, ϵ-indicator (I(1)ϵ+), spread (∆), generalized spread (∆∗), inverted generational distance, and hypervolume. Experimental results indicated that these six metrics show high consistencies when Pareto fronts (PFs) are convex, whereas they show certain contradictions on concave PFs.
Infection prevention and control (IPC) programs form the basis of minimizing spread of pathogens in the healthcare setting and beyond. The COVID-19 pandemic amplified the demand for IPC. However, the environmental impact of IPC practices has yet to be addressed and attempts to quantify its climate implications have been sparse.
Background: Cerebrospinal fluid (CSF) motion and pulsatility has been proposed to play a crucial role in clearing brain waste. Although its driving forces remain debated, increasing evidence suggests that large amplitude vasomotion drives such CSF fluctuations. Recently, a fast blood-oxygen-level-dependent (BOLD) fMRI sequence was used to measure the coupling between CSF fluctuations and low-frequency hemodynamic oscillations in the human cortex.
Deep learning (DL) holds great promise to improve medical diagnostics, including pathology. Current DL research mainly focuses on performance. DL implementation potentially leads to environmental consequences but approaches for assessment of both performance and carbon footprint are missing.
Introduction: Aesthetic medicine has evolved towards minimally invasive procedures, with biostimulators like Poly-L-Lactic Acid (PLLA), Calcium Hydroxylapatite (CaHA), and Polycaprolactone (PCL) gaining attention for their role in collagen induction, improving skin texture, elasticity, and volume. Combining these agents with other treatments-such as botulinum toxin, dermal fillers, and energy-based devices (e.g.
The knowledge and attitude of researchers can affect the validity of laboratory animal (LAN) research. However, studies show that not all researchers possess the required knowledge and appropriate attitude for performing valid research on animals. This may have several reasons, such as high heterogeneity in the educational backgrounds of researchers in animal trials.
