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Doctoral student Contact details Email: pablo [dot] pastor_vidal [at] jur [dot] lu [dot] se Phone: +46 46 222 11 89Organisation Department of Law Room number: 230 Service point: 56 WebpagePablo Pastor Vidals profile in Lund University research portalOther affiliations Researcher Human Rights Law Profile area member LU Profile Area: Human rights Researcher Public International Law Publications Disp
https://www.humanrights.lu.se/pablo-pastor-vidal - 2026-05-30
Flexible Energy LUND ENERGY WORKSHOP 2016 October 20th 2016, 9.00 – 16.15 Venue: Palaestra, Lundagård, Lund Welcome to an Energy Workshop in Lund on the theme ”Flexible energy” With the new climate agreement in Paris the transition towards an emissions free power system is clear and globally accepted. This transition has been ongoing for a while in Sweden, but with the new target for climate neutr
https://www.hallbarhet.lu.se/sites/hallbarhet.lu.se/files/lu_energy_workshop_20_oct_final.pdf - 2026-05-31
PowerPoint Presentation Social Capital & Youth Mental Health (SoCap-YMH) Funded by Familjen Kamprads Stiftelse The research team: Project Leader: Mikael Ahlborg, Ph.D. thesis on social capital and mental health among adolescents. Registered Nurse & Senior lecturer in Nursing at HU Katrin Häggström Westberg, Ph.D. thesis on help seeking behavior among adolescents with mental health problems. Psychi
Master’s thesis project 1(2) Towards autonomous microstructural characterization of materials Background and motivation: Microstructural characterization is a cornerstone of materials engineering because the microscopic structure of metals and alloys directly determines their mechanical, thermal, and tribological properties. Conventional characterization methodssuch as optical microscopy, SEM, and
Digitalization holds significant potential to improve the efficiency, flexibility, and sustainability of District Heating (DH) systems. However, the transition toward digitalized DH is often constrained by challenges beyond technology—such as regulatory uncertainty, unclear business models, fragmented organizational capacity, and misaligned stakeholder incentives. This paper offers a comparative,
It is a common practice for symmetric-key ciphers is to encode a cryptanalysis problem as an instance of the Mixed Integer Linear Programming (MILP) and then run the instance with an efficient solver. For this purpose, it is essential to model the components in a way that is compatible with the MILP formulation while preserving the characteristics of the cipher. In this work, we look at the proble
We propose data-driven surrogate models to solve systems of time-dependent differential equations coupled with noise. Using a feedforward neural network, we separately learn the noise and solution, tackling approximations across regimes with bifurcations and rare events. Focusing on irregular data generated by a stochastic noise model on a one-dimensional spatial lattice coupled to a differential
This chapter explores the intersection of authenticity, commercialization, and influencer culture in digital fashion media through the case study of Swedish retailer Ellos’ “Made by Women” campaign. Using a qualitative methodology, the study investigates how brands instrumentalize personal narratives to create emotional engagement while serving commercial interests. The findings reveal a paradox o
Improving energy efficiency in agriculture is key to reducing environmental impact. Lighting in animal buildings is one of the most cost‐effective energy saving measures. Lighting retrofit offers a short payback period, enhances animal welfare and production, and aligns with regulations for phasing out fluorescent lighting. The purpose of this study was to investigate the energy-saving potential o
Bio-based insulation materials, such as wood fiber, offer sustainable alternatives to conventional insulation but pose challenges due to their combustibility, particularly their smouldering behavior. This study investigates the heat release characteristics of wood fiber insulation using a combination of Simultaneous Thermal Analysis (STA) and Microscale Combustion Calorimetry (MCC) to assess both
Additive manufacturing (AM), particularly Laser Powder Bed Fusion, produces surfaces with unique, randomly distributed spherical roughness that significantly influences heat transfer and pressure loss. This study models AM roughness using a statistical distribution of spheres and performs high-fidelity simulations at a bulk Reynolds number of 12,000 to evaluate heat transfer on a rough pipe. Stati
This paper introduces a novel approach for transitioning from high-granularity Ray-Tracing (RT) channel simulations to channel emulation, accompanied by an over-the-air test. The RT simulation is performed on a Vehicle-to-Vehicle (V2V) communication drive scenario generating basis for channel emulation in a channel emulator. The channel simulation, and the accompanying channel emulation, also enab
We study applications of clustering (in particular the k-center clustering problem) in the design of efficient and practical deterministic algorithms for computing an approximate and the exact arithmetic matrix product of two 0-1 rectangular matrices A and B with clustered rows or columns, respectively. Let λA and λB denote the minimum maximum radius of a cluster in an ℓ-center clustering of the r
Abstract in French:Le système éducatif suédois met, depuis des décennies, l’accent sur l’importance de l’évaluation critique de l’information. Néanmoins, les approches d’évaluation de l’information mises en œuvre demeurent insuffisamment développées d’un point de vue analytique. Cet article porte sur deux défis essentiels auxquels sont confrontés les établissements scolaires pour préparer les jeunTeachers are now encouraged to use generative artificial intelligence (GenAI) tools to complete various school-related administrative tasks, with the promise of saving considerable amounts of time and effort. Drawing on interviews from 57 teachers across eight schools in Sweden and Australia, this paper explores teachers’ experiences when working with GenAI. In particular, it focuses on the large
In this paper, we propose an approach that combines Vision Language Models (VLMs) and Behavior Trees (BTs) to address failures in robotics. Current robotic systems can handle known failures with pre-existing recovery strategies, but they are often ill-equipped to manage unknown failures or anomalies. We introduce VLMs as a monitoring tool to detect and identify failures during task execution. Addi
