Automated landmark-based cat facial analysis and its applications.

Facial landmarks, widely studied in human affective computing, are beginning to gain interest in the animal domain. Specifically, landmark-based geometric morphometric methods have been used to objectively assess facial expressions in cats, focusing on pain recognition and the impact of breed-specific morphology on facial signaling. These methods employed a 48-landmark scheme grounded in cat facial anatomy.

Spatio-temporal model of combining chemotherapy with senolytic treatment in lung cancer.

Senescent cells are cells that stop dividing but sustain viability. Cellular senescence is the hallmark of aging, but senescence also appears in cancer, triggered by cells stress, tumor suppression of gene activation, and oncogene activity. In lung cancer, senescent cancer cells secrete VEGF, which initiates a process of angiogenesis, enabling the cancer to grow and proliferate.

Automated video-based pain recognition in cats using facial landmarks.

Affective states are reflected in the facial expressions of all mammals. Facial behaviors linked to pain have attracted most of the attention so far in non-human animals, leading to the development of numerous instruments for evaluating pain through facial expressions for various animal species. Nevertheless, manual facial expression analysis is susceptible to subjectivity and bias, is labor-intensive and often necessitates specialized expertise and training.

Computational investigation of the social function of domestic cat facial signals.

There is growing interest in the facial signals of domestic cats. Domestication may have shifted feline social dynamics towards a greater emphasis on facial signals that promote affiliative bonding. Most studies have focused on cat facial signals during human interactions or in response to pain.

Economical-epidemiological analysis of the coffee trees rust pandemic.

Coffee leaf rust is a prevalent botanical disease that causes a worldwide reduction in coffee supply and its quality, leading to immense economic losses. While several pandemic intervention policies (PIPs) for tackling this rust pandemic are commercially available, they seem to provide only partial epidemiological relief for farmers. In this work, we develop a high-resolution spatiotemporal economical-epidemiological model, extending the Susceptible-Infected-Removed model, that captures the rust pandemic's spread in coffee tree farms and its associated economic impact.