Abstract: Purpose: Patients with cancer display reduced humoral responses after double-dose COVID-19 vaccination, whereas their cellular response is more comparable with that in healthy individuals. Recent studies demonstrated that a third vaccination dose boosts these immune responses, both in healthy people and patients with cancer. Because of the availability of many different COVID-19 vaccines, many people have been boosted with a different vaccine fromthe one used for double-dose vaccination. Data on such alternative vaccination schedules are scarce. This prospective study compares a third dose of BNT162b2 after double-dose BNT162b2 (homologous) versus ChAdOx1 (heterologous) vaccination in patients with cancer. Experimental Design: A total of 442 subjects (315 patients and 127 healthy) received a third dose of BNT162b2 (230 homologous vs. 212 heterologous). Vaccine-induced adverse events (AE) were captured up to 7 days after vaccination. Humoral immunity was assessed by SARS-CoV-2 anti-S1 IgG antibody levels and SARSCoV- 2 50% neutralization titers (NT50) against Wuhan and BA.1 Omicron strains. Cellular immunity was examined by analyzing CD4þ and CD8þ T-cell responses against SARS-CoV-2–specific S1 and S2 peptides. Results: Local AEs were more common after heterologous boosting. SARS-CoV-2 anti-S1 IgG antibody levels did not differ significantly between homologous and heterologous boosted subjects [GMT 1,755.90 BAU/mL (95% CI, 1,276.95–2,414.48) vs. 1,495.82 BAU/mL (95% CI, 1,131.48–1,977.46)]. However, homologous- boosted subjects show significantly higher NT50 values against BA.1 Omicron. Subjects receiving heterologous boosting demonstrated increased spike-specific CD8þ T cells, including higher IFNg and TNFa levels. Conclusions: In patients with cancer who received double-dose ChAdOx1, a third heterologous dose of BNT162b2 was able to close the gap in antibody response.

Abstract: It is standard practice in virtual reality applications to synthesize binaural audio based on a discrete set of directionally-dependent head-related impulse responses (HRIRs). This set of HRIRs is often time-aligned in a pre-processing step, to allow for high-fidelity interpolation between HRIRs corresponding with neighbouring directions. The fidelity of this operation depends on the similarity of neighbouring aligned HRIRs. The pairwise quality of similarity makes it a difficult criterion to optimize globally and consequently one often resorts to alignment methods based on a specific feature that can be extracted for each HRIR separately, e.g., the first-onset of the peak or the group delay. However, such proxies for similarity are very sensitive to noise and therefore require a high signal-to-noise ratio, which makes them less suitable for processing HRIRs acquired outside an anechoic room. In this paper, we advance a novel alignment method, which maximizes the similarity – defined as the correlation between the full-length HRIRs – between neighbouring aligned HRIRs for all directions at once. We show that this correlation-based alignment procedure outperforms the first-onset alignment with regards to the fidelity of the spherical harmonics representation of both the spectral and interaural time difference (ITD) information, when tested on the KEMAR HRIR and six human HRIRs. Finally, we show that the correlation-based alignment is more robust to noise.

Abstract: Electromagnetic design problems involve optimizing multiple parameters that are nonlinearly related to objective functions. Traditional optimization techniques require significant computational resources that grow exponentially as the problem size increases. Therefore, a method that can produce good results with moderate memory and computational resources is desirable. Bioinspired optimization methods, such as particle swarm optimization (PSO), are known for their computational efficiency and are commonly used in various scientific and technological fields. In this article we explore the potential of advanced PSO-based algorithms to tackle challenging electromagnetic design and analysis problems faced in real-life applications. It provides a detailed comparison between conventional PSO and its quantum-inspired version regarding accuracy and computational costs. Additionally, theoretical insights on convergence issues and sensitivity analysis on parameters influencing the stochastic process are reported. The utilization of a novel quantum PSO-based algorithm in advanced scenarios, such as reconfigurable and shaped lens antenna synthesis, is illustrated. The hybrid modeling approach, based on the unified geometrical description enabled by the Gielis Transformation, is applied in combination with a suitable quantum PSO-based algorithm, along with a geometrical tube tracing and physical optics technique for solving the inverse problem aimed at identifying the geometrical parameters that yield optimal antenna performance.

Abstract: Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain.In this work, we generated a comprehensive hyperspectral dataset of intimate mineral powder mixtures by homogeneously mixing five different clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide). In total 325 samples were prepared. Among the 325 samples, 60 mixtures were binary, 150 were ternary, 100 were quaternary, and 15 were quinary. For each mixture (and pure clay powder), reflectance spectra are acquired by 13 different sensors, with a broad wavelength range between the visible and the long-wavelength infrared regions (i.e., between 350 nm and 15385 nm) and with a large variation in sensor types, platforms, and acquisition conditions. We will make this dataset public, to be used by the community for the validation of nonlinear unmixing methodologies (https://github.com/VisionlabUA/Multisensor_datasets)

Abstract: We calculate the contact resistance for an edge- and top-contacted 2D semiconductor. The contact region consists of a metal contacting a monolayer of MoS2 which is otherwise surrounded by SiO2. We use the quantum transmitting boundary method to compute the contact resistance as a function of the 2D semiconductor doping concentration. An effective mass Hamiltonian is used to describe the properties of the various materials. The electrostatic potentials are obtained by solving the Poisson equation numerically. We incorporate the effects of the image-force barrier lowering on the Schottky barrier and examine the impact on the contact resistance. At low doping concentrations, the contact resistance of the top contact is lower compared to edge contact, while at high doping concentrations, the edge contact exhibits lower resistance.

Abstract: De bijdrage gaat dieper in op de relatie tussen ruimte en gezondheidsongelijkheid, bespreekt gezondheidsongelijkheid vanuit een rechtenperspectief en illustreert een aantal praktijken waarin de aandacht voor ruimte en gezondheidsongelijkheid samenkomen.

Abstract: The EPS Antwerp Young Minds (AYM) invited Prof. Nir Navon (Yale University) to hold a colloquium for the physics department. For an audience of students and researchers, Prof. Navon presented recent advances in ultracold quantum matter and research from his own lab. His experimental work paves the way to make toy models used by theorists a reality. We sat down afterwards to discuss ultracold physics, box traps and setting up a lab from scratch.

Abstract: Natural deep eutectic solvents (NADES) show great promise as media for enzymatic reactions in areas where (bio)compatibility with natural or medicinal products is a must. While in theory they can be tailored to the intended reaction to ensure optimized yields, the knowledge to date is predominantly empirical, with some mechanistic reports providing a fragmented view at best. Therefore, it is not easy to explain experimental observations, let alone make predictions. The aim of this study was to develop a structured, holistic understanding of the effects of NADES media on enzymatic reactions, distinguishing between effects on solubility, solvation, viscosity, inhibition and denaturation. Experimental and computational chemistry methods were combined to separately study the interactions between enzyme, substrate, and NADES as reaction media. The initial enzyme activity and the final conversion of vinyl laurate transesterification by immobilized Candida antarctica lipase were studied experimentally. The direct effect of NADES on the same enzyme was modeled by molecular dynamics simulation. The effect of solubility was studied by both experimental and computational methods. To predict the solubility and viscosity of NADES, data-driven models were developed by combining group contribution and machine learning methods, based on the accumulated experimental knowledge on NADES found in the literature. Finally, the composed relationships and prediction models were applied to the practical example of deacetylation of mannosylerythritol lipids (MELs). The experimental findings show that the chosen NADES system has a significant effect on both the apparent initial activity and the final conversion. However, in the simulations, the enzyme retains its original structure; moreover, NADES has an additional stabilizing effect on the enzyme. In addition, changes in the molar ratio of the compounds in NADES do not show a significant effect on the stability of the enzyme. These results indicate that the main effect of NADES on the reaction is mainly related to the substrate-solvent interactions (solvation energy) and the viscosity of the system. On the other hand, the experimental results only confirmed the significance of solvation, viscosity did not show a clear correlation with the studied reaction parameters. The machine learning models built for solubility and viscosity gave quantitative predictions of these properties. The accumulated knowledge was used to optimize the yield in the deacetylation reaction of MELs. The combination of these methods provides fundamental knowledge about the effect of NADES on biocatalysis, but the results are also applicable to other uses of NADES.

Abstract: Singlet molecular oxygen (1O2) has continuously attracted researchers' interest because of its involvement in various processes, such as in photodynamic reactions in biological and chemical systems. 1O2 is an effective electrophile and potent oxidizing agent and can be easily generated by photosensitization via the illumination of organic dyes with visible light. As described in Chapter 1, 1O2 has gained prominence in various applications such as wastewater treatment, photodynamic therapy of cancer, organic synthesis, and recently developed 1O2-based photoelectrochemical (PEC) sensing of phenolic compounds. Phenolic compounds are a potential source of contaminants that originates from industrial effluents and waste products of chemical and pharmaceutical industries. These phenolic compounds pose severe threats to humans and aquatic life after reaching the environment. Therefore, it is imperative to develop photoactive materials that efficiently generate 1O2 and oxidize phenolic compounds and antibiotics. The existing 1O2 generating photosensitizers (PSs) include porphyrins, phthalocyanines (Pcs), subphthalocyanines (SubPcs), and other dyes such as derivatives of xanthene (e.g., Rose Bengal (RB)), and fluorinated boron-dipyrromethene (BODIPYs), and phenothiazinium dyes (e. g. Methylene Blue (MB)) which display long-lived triplet excited state and can be used in 1O2-based applications. This thesis focuses on preparing efficient hybrid materials based on newly synthesized Pcs, different surface area titanium dioxide (TiO2) and plasmonic gold nanoparticles (AuNPs) for their use in the PEC detection of phenolic compounds. The first focus was on developing a fast amperometric method to test the photo-electrocatalytic activity of 1O2 producing PSs dissolved in MeOH based on the redox cycling of an electroactive phenolic compound, hydroquinone (HQ) (Chapter 2). This method of testing PSs does not require the accumulation of a reaction product since the amperometric signal develops near instantly when the light is on, which enables dynamic monitoring of a PSs activity at varying conditions in a single experiment. This method was crucial to measure high 1O2 quantum yield and low yield in the same experimental conditions. Moreover, the obtained results revealed a range of working parameters affecting the PEC activity of PSs. The next goal was to immobilize tert-butyl substituted aluminum Pc (t-BuPcAlCl) on the solid support, which showed a high 1O2 quantum yield. However, before immobilizing Pc on a solid support such as TiO2, it is essential to know the electronic energy level of Pcs for the possible electron transfers from Pcs to TiO2. Therefore, Chapter 3 explored the (spectro)electrochemical properties of t-BuPcAlCl Pc. Next, in Chapter 4, t-BuPcAlCl Pc and other tert-butyl substituted Pcs with Zn central metal, t-BuPcZn, and its metal-free derivative t-BuPcH2 were immobilized on different surface area TiO2. The PEC activity of immobilized Pcs on TiO2 toward different phenols and antibiotics was studied, and the action mechanism was revealed and compared with sterically hindered fluorinated Pc F64PcZn. In the final part of this thesis plasmonic AuNPs were introduced combined with trimethylsilane-protected acetylene functionalized ZnPc (TMSZnPc) to study the synergistic effect that boosts the overall activity toward the detection of phenols under visible light illumination (Chapter 5) . The TMSZnPc was coupled with AuNPs via a click chemistry approach. The 1O2 quantum yield of TMSZnPc improved significantly after conjugating with AuNPs, and, subsequently, the PEC activity for detecting HQ. The theoretical and experimental investigation demonstrated that the plasmonic enhancement of TMSZnPc is driven by the near-field mechanism. This shows the importance of plasmonic AuNPs with other photoactive species for their use in 1O2-based applications. The fundamental knowledge obtained in this doctoral study will ultimately deepen the understanding of developing 1O2-based PEC sensors for detecting phenolic compounds and pharmaceuticals in the wastewater stream, helping to choose efficient materials and, in the last instance, a more sustainable future especially access to clean water for everyone.

Abstract: Air pollution is proclaimed by the World Health Organiaation (WHO) as the biggest environmental threat to human health. Street canyons, or urban roads flanked by a continuous row of high buildings on both sides, are perceived as typical bottleneck areas for air quality due to their lack of natural ventilation. This doctoral thesis aims to integrate expert knowledge on in-canyon flow fields and pollution dispersion in street canyons from the specialized field of (bio)engineering into the field of urban planning and vice versa. In Chapter 1, a Geospatial Information System (GIS) method was developed to detect exposure zones and hotspot street canyons. A critical combination between aspect ratio (AR > 0.65) and traffic volume (TVmax > 300) was detected and subsequently used to detect hotspot street canyons in three major European cities (Antwerp, London and Paris). Chapter 2 focusses on acquiring in-depth knowledge on flow and concentration fields in street canyons by conducting an extensive literature review on over 200 studies and translates this knowledge into nineteen guidelines and eleven spatial tools, comprised in a toolbox for urban planning. Subsequently, computational fluid dynamics (CFD) was used into a research trough design process (Chapter 4) to illustrate how the design tools can be applied to a specific case study (Belgiëlei, Antwerp). Alternations to traffic lanes (traffic lane reduction and lateral displacement) combined with low boundary walls (LBWs), were found to reduce NO2 levels in the entire pedestrian area up to – 3.6 % and peak pollutions were reduced by -8 %. A maximum NO2 reduction was reached by combining a traffic lane displacement with hedges, adjustments to the tree planting pattern and an increased ground-level permeability, leading to reductions up to – 4.5 % in the pedestrian areas. In conclusion, urban design was found to be a valuable tool to enhance the effect of emission reduction strategies and draw in-canyon concentrations closer to the value of the background concentration. However, the background concentration seemed to dominate the efficiency of the urban design interventions and therefore, additional measures should be taken to reduce background pollution levels. This dissertation aims to contribute to the awareness of air pollution in street canyons, as well as support local governments in taking action by delivering spatial tools and guidelines applicable for urban planning and represents a framework for the dissemination of expert information on air quality in street canyons to the field of urban planning.