Proposal and Validation of a Scale of Composite Measure Reactivity Score to Characterize the Reactivity in Horses During Handling

This study aimed to identify the parameters related to the expression of the reactivity in horses during handling and based on that proposed and validated a scale of composite measure reactivity score to characterize horse's reactivity. To this end, the first stage (S1) proposed the scale and the second (S2) validated it. In S1, 364 Lusitano horses were evaluated, 188 were adult breeding mares (4–12 years old), and 176 were foals (males/females, aged from 2 months to 2 years). During hooves trimming, vermifuge application, palpation scores were assigned to behaviors of movement, ears and eyes position, breathing, vocalization, and urination. A response parameter called reactivity was attributed to each animal, ranging from score 1 (nonreactive/calm) to score 4 (very reactive/aggressive). The verification of the possible parameters (age, behavior), which explains the response parameter (reactivity), was taken using ordinal proportional odds model. Movement, breathing, ears and eyes position, vocalization, and age appear to explain the reactivity of horses during handling (P < .01). Therefore, based on these parameters, it was possible to propose two scales of composite measure reactivity score: one to characterize the mares and another the foals. On S2, the proposed scale was validated by the simultaneous application of Forced Human Approach Test, another commonly used test to evaluate the reactivity in horses, with a correlation of 0.97 (P < .05). The assessment of the reactivity of horses during handling by a composite measure reactivity score scale is valid, and easy to apply, without disrupting daily routine and override the impact of individual differences.

A crowd of pedestrian dynamics – the perspective of physics.

Walking is the most basic form of transportation. A good understanding of pedestrian’s dynamics is essential in meeting the mobility and accessibility needs of people by providing a safe and quick walking flow. Advances in the dynamics of pedestrians in crowds are of great theoretical and practical interest, as they lead to new insights regarding the planning of pedestrian facilities, crowd management, or evacuation analysis. As a physicist, I would like to put forward some additional theoretical and practical contributions that could be interesting to explore, regarding the perspective of physics on about human crowd dynamics (panic as a specific form of behavior excluded).

Experiments on identification of argumentative sentences

The main purpose of this study is to evaluate the best set of features that automatically enables the identification of argumentative sentences from unstructured text. As corpus, we use case laws from the European Court of Human Rights (ECHR). Three kinds of experiments are conducted: Basic Experiments, Multi Feature Experiments and Tree Kernel Experiments. These experiments are basically categorized according to the type of features available in the corpus. The features are extracted from the corpus and Support Vector Machine (SVM) and Random Forest are the used as Machine learning algorithms. We achieved F1 score of 0.705 for identifying the argumentative sentences which is quite promising result and can be used as the basis for a general argument-mining framework.