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The purpose of this study is to examine the predictive value of psychopathy features on crime-related emotional states in forensic male patients with offence histories who were mandated to Dutch clinical care.

The study had a retrospective design in which psychopathy features were assessed using the Psychopathy Checklist-Revised. For each patient, information on the events leading up to the crime and a description of the crime itself were extracted from the hospital record to assess emotional states. These crime-related emotional states were assessed using the mode observation scale. The sample consisted of 175 patients with offence histories.

Multiple regression analyses indicated that affective features of psychopathy were a negative predictor for feelings of vulnerability in the events leading up to the crime but not predictive of loneliness. The interpersonal features were predictive of deceit during criminal behaviour.

This study leads to a better, more nuanced and substantiated understanding of which emotional states play a prominent role in criminal behaviour and how these states are affected by psychopathic traits. This knowledge can influence existing treatment programmes for patients with offence histories.

Several studies have examined the relationship between emotional states and criminal behaviour and between psychopathy and emotions, but less is known about the predictive relationship between psychopathy features and crime-scene-related emotional states.

Using building information modelling (BIM) technology, a conventional structure in this study was converted into a green building to measure its energy usage and CO2 emissions.

Digital images of the existing building conditions were captured using unmanned aerial vehicle (UAV), and were fed into Meshroom to generate the building’s geometry for 3D parametric model development. The model for the existing conventional building was created and converted to an energy model and exported to gbXML in Autodesk Revit for a whole building analysis which was carried out in the Green Building Studio (GBS). In the GBS, the conventional building was retrofitted into a green building to explore their energy consumption and CO2 emission.

By comparing the green building model to the conventional building model, the research found that the green building model saved 25% more energy while emitting 46.8% less CO2.

The study concluded that green building reduces energy consumption, thereby reducing the emission of CO2 into the environment. It is recommended that buildings should be simulated at the design stage to know their energy consumption and carbon emission performance before construction.

Occupant satisfaction, operation cost and environmental safety are essential for sustainable or green buildings. Green buildings increase the standard of living and enhance indoor air quality.

This investigation aided in a pool of information on how to use BIM methodology to retrofit existing conventional buildings into green buildings, showing how green buildings save the environment as compared to conventional buildings.

This paper aims to explore the protective and risk factors involved in student loneliness after the lockdown measures taken limiting social contact during the COVID-19 pandemic in France.

Using a cross-sectional survey methodology, the authors collected data on a sample of 546 students pursuing management education in a French business school in several campuses. Loneliness was measured by the three-item UCLA loneliness scale. Logistic regression analysis examined the factors influencing student loneliness.

The prevalence of loneliness was 23.4%. Risk factors for loneliness were social isolation especially in terms of intensity and isolation from friends (OR: 5.40), having a regular paid activity (OR: 1.62) and not getting academic help from other students (OR: 2.11) or taking meals alone during the lockdowns (OR: 1.94). Being a male student (OR: 0.47), practicing a sport (OR: 0.64) and studying at a specific campus (OR: 0.43) were protective factors.

Understanding protective and risk factors affecting student loneliness helps higher education decision-makers to take the necessary actions to enhance student well-being which have an effect on learning processes.

Loneliness is a major public health concern among students. Knowledge of the determinants for loneliness are limited and this article attempts to augment this by exploring several protective and risk indicators of loneliness among French students.