Abstract
Background: The multimedia capturing of live lectures has increased within higher education institutions, even in the pre-COVID-19 period. Despite student satisfaction, the video lecture capture (VLC) influence on students' attainment and achievement of intended learning outcomes is controversial. Methods: To explore the impact of VLC, a cross-sectional study across 2016/17 (n=209 students) and 2017/18 (n=206 students) was conducted in the course of Mechanistic Toxicology in Pharmaceutical Education. Results: The results showed that 73% and 90% of the assessed students entirely viewed the videos of theoretical (550 minutes) and practical/laboratory classes (250 minutes), respectively. VLC impacted student attainment and the achievement of intended learning outcomes on the capacity to understand the subjects and apply knowledge. Conclusion: The effectiveness of VLC is to be considered under the framework of constructive alignment and the specificities of the course.

Abstract
Budgets are important management tools recognized for their help in planning, communication, monitoring the expense performance, and even motivating collaborators. However, recently there has been criticism of the traditional Budgeting Process due to its cumbersomeness, long duration, and eventual diversion of the focus from the day-to-day activities. Thus, improving the Budgeting Process by incorporating Expense component uncertainties is of uttermost importance to accelerate its approval. This paper presents a methodology for companies to assess their budget risk based on their historical Expense data by applying Monte Carlo Simulation and Time Series Bootstrapping Techniques. Besides, some state-of-the-art sensitivity Importance Measures are also implemented to help evaluate the relative importance of the Expense components. The methodology proposed, based on a real case study with data from a major Portuguese retailer, has the advantage of being objective and supported by data, thus not being subject to bias from the management. © 2023, Universidade do Porto - Faculdade de Engenharia. All rights reserved.

Abstract
This paper describes a new heuristic for the nesting problem based on a 2-exchange neighbourhood generation strategy. This mechanism guides the search through the solution space consisting of the sequences of pieces and relies on a low-level placement heuristic to actually convert one sequence in a feasible layout. The placement heuristic is based on a bottom-left greedy procedure with the ability to fill holes in the middle of the layout at a later stage. Several variants of the 2-exchange nesting heuristic were implemented and tested with different initial solution ranking criteria, different strategies for selecting the next solution, and different neighbourhood sizes. The computational experiments were based on data sets published in the literature. In most of the cases, the 2-exchange nesting algorithm generated better solutions than the best known solutions.

Abstract
The nesting problem is a two-dimensional cutting and packing problem where the small pieces to cut have irregular shapes. A particular case of the nesting problem occurs when congruent copies of one single shape have to fill, as much as possible, a limited sheet. Traditional approaches to the nesting problem have difficulty to tackle with high number of pieces to place. Additionally, if the orientation of the given shape is not a constraint, the general nesting approaches are not particularly successful. This problem arises in practice in several industrial contexts such as footwear, metalware and furniture. A possible approach is the periodic placement of the shapes, in a lattice way. In this paper, we propose three heuristic approaches to solve this particular case of nesting problems. Experimental results are-compared with published results in literature and additional results obtained from new instances are also provided.

Abstract
In this paper a hybrid algorithm to solve Irregular Strip Packing problems is presented. The metaheuristic simulated annealing is used to guide the search over the solution space while linear programming models are solved to generate neighbourhoods during the search process. These linear programming models, which are used to locally optimise the layouts, derive from the application of compaction and separation algorithms. Computational tests were run using instances that are commonly used as benchmarks in the literature. The best results published so far have been improved by this new hybrid packing algorithm.

Abstract
This paper presents a very special cutting path determination problem appearing in a high precision tools factory, and provides two new heuristics for its resolution. Particular features of both the cutting process, and of the material to be cut, bring in a set of unusual constraints, when compared with other cutting processes, which confer additional complexity and originality to the problem. In particular, this is a matter of practical and economic relevance, since the solution methods are intended to be implemented in a real-life industrial environment. The concept of dynamic graph is exploited to deal with the arc routing problem under study, which is modelled as a dynamic rural postman problem. The constructive heuristics developed, the "higher up vertex heuristic" (HUV) and the "minimum empty path heuristic" (MEP) are tested with real data sets.