Delineating and classifying individual cells in microscopy tissue images is a complex task, yet it is a pivotal endeavor in various medical and biological investigations. We propose a new deep learning framework (CISCA) for automatic cell instance segmentation and classification in histological slices to support detailed morphological and structural analysis or straightforward cell counting in digital pathology workflows and brain cytoarchitecture studies. At the core of CISCA lies a network architecture featuring a lightweight U-Net with three heads in the decoder. The first head classifies pixels into boundaries between neighboring cells, cell bodies, and background, while the second head regresses four distance maps along four directions. The network outputs from the first and second heads are integrated through a tailored post-processing step, which ultimately yields the segmentation of individual cells. A third head enables simultaneous classification of cells into relevant classes, if required. We showcase the effectiveness of our method using four datasets, including CoNIC, PanNuke, and MoNuSeg, which are publicly available H\&E datasets. Additionally, we introduce CytoDArk0, a novel dataset consisting of Nissl-stained images of the cortex, cerebellum, and hippocampus from mammals belonging to the orders Cetartiodactyla and Primates. We evaluate CISCA in comparison to other state-of-the-art methods, demonstrating CISCA's robustness and accuracy in segmenting and classifying cells across diverse tissue types, magnifications, and staining techniques.

Growing polarisation in society caught the attention of the scientific community as well as news media, which devote special issues to this phenomenon. At the same time, digitalisation of social interactions requires to revise concepts from social science regarding establishment of trust, which is a key feature of all human interactions, and group polarisation, as well as new computational tools to process large quantities of available data. Existing methods seem insufficient to tackle the problem fully, thus, we propose to approach the problem by investigating rhetorical strategies employed by individuals in polarising discussions online. To this end, we develop multi-topic and multi-platform corpora with manual annotation of appeals to ethos and pathos, two modes of persuasion in Aristotelian rhetoric. It can be employed for training language models to advance the study of communication strategies online on a large scale. With the use of computational methods, our corpora allows an investigation of recurring patterns in polarising exchanges across topics of discussion and media platforms, and conduct both quantitative and qualitative analyses of language structures leading to and engaged in polarisation.

David Cage scoffs at the notion that videogames are fun. "They should trouble you, move you, make you react," he says. As founder of the studio Quantic Dream, the French developer has been stunning and confounding players for two decades with cinematic games that tackle heady issues of love, death, domestic abuse, oppression, and the afterlife. "Some people are shocked when a game evokes real-world issues," he says. "But this platform is about becoming the characters, not just seeing them from the outside like in a film."

An overemphasis on logic often thwarts the efforts of enthusiastic but naive leaders who are trying to build a data-driven culture; however, an underemphasis on logic can be just as damaging to success. Aristotle's rhetorical triangle teaches us that persuasion comes in three forms: ethos (credibility), pathos (emotion), and logos (logic). Although I encourage you to focus heavily on ethos and pathos, without logos, your organization may have a tough time making the transformation. Data-driven concepts must make logical sense before your organization fully adopts them. SEE: SAP's new big data service can give you a big shortcut to the mother lode of customer insights To build a logical foundation for your data-driven culture, you must answer the question, "why is it better to trust a data system over my own judgment?"

Under the auspices of “being green,” we have given our printed word over to a cyber-medium that cannot be touched or felt or folded. Our information is as volatile as the authority protecting our storage devices. Eliminating a book or changing its text can be done by literally pressing a button -- without a fire or an erasure marking, without smoke, without evidence. Our data is ephemeral along with the web in which we weave it. This paper considers the current ease of censorship, and that the non-permanence of data and links can wreak havoc on our societal infra-structure if the wrong entities (human or machine) with the wrong motives have the control to determine its fate.