Dimensions of online conflict: towards modeling agonism

Agonism plays a vital role in democratic dialogue by fostering diverse perspectives and robust discussions. Within the realm of online conflict there is another type: hateful antagonism, which undermines constructive dialogue. Detecting conflict online is central to platform moderation and monetization. It is also vital for democratic dialogue, but only when it takes the form of agonism. To model these two types of conflict, we collected Twitter conversations related to trending controversial topics. We introduce a comprehensive annotation schema for labelling different dimensions of conflict in the conversations, such as the source of conflict, the target, and the rhetorical strategies deployed. Using this schema, we annotated approximately 4,000 conversations with multiple labels. We then train both logistic regression and transformer-based models on the dataset, incorporating context from the conversation, including the number of participants and the structure of the interactions. Results show that contextual labels are helpful in identifying conflict and make the models robust to variations in topic. Our research contributes a conceptualization of different dimensions of conflict, a richly annotated dataset, and promising results that can contribute to content moderation

Observation of strong reflection of electron waves exiting a ballistic channel at low energy

Wave scattering by a potential step is a ubiquitous concept. Thus, it is surprising that theoretical treatments of ballistic transport in nanoscale devices, from quantum point contacts to ballistic transistors, assume no reflection even when the potential step is encountered upon exiting the device. Experiments so far seem to support this even if it is not clear why. Here we report clear evidence of coherent reflection when electron wave exits the channel of a nanoscale transistor and when the electron energy is low. The observed behavior is well described by a simple rectangular potential barrier model which the Schrodinger’s equation can be solved exactly. We can explain why reflection is not observed in most situations but cannot be ignored in some important situations. Our experiment also represents a direct measurement of electron injection velocity - a critical quantity in nanoscale transistors that is widely considered not measurable

PHYTOTOXIC ACTION OF Machaerium amplum BENTH. LEAVES EXTRACT

The indiscriminate use of herbicides can guide to some environmental damages. Thus, the search for alternative bioherbicides from natural sources with biodegradable properties and less toxicity to the microbiota is essential. The focus of this work is the chemistry and phytotoxic study of the hydroethanolic extract of Machaerium amplum Benth. leaves. The chemical study by FIA-ESIIT-MSn experiments allowed the detection of apigenin and luteolin C-glycoside derivatives, quinic acid, the A-type proanthocyanidin dimer and trimer, and a saponin Soyasapogenol B type. Phytotoxicity assays were performed with the extract and a group of fractions against tomato and onion seeds under the parameters of germination, hypocotyl growth, and root length. The extract showed a 70% of inhibition effect at 0.8 mg.mL-1 on tomato root length. For the onion seeds, the percentual of inhibition was 65% at 0.4 mg.mL-1 . All groups of fractions tested showed significant inhibition on tomato seedling root length at 0.8 mg.mL-1 . The flavonoids fraction showed interesting activity at 0.4 mg.mL-1 . The same fraction showed a percentage of inhibition above 50% at 0.2 mg.mL-1 on onion seedling root length. This activity may be associated with the C-flavones presence in this fraction. According to the ecotoxicity test with Artemia salina Leach, the extract presents no toxicity at the concentrations tested, and no antimicrobial activity against Fusarium graminearum, F. oxysporum and Aspergillus flavus, thus reinforcing the potential of the extract