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  <channel rdf:about="https://www.um.edu.mt/library/oar/handle/123456789/906">
    <title>OAR@UM Community:</title>
    <link>https://www.um.edu.mt/library/oar/handle/123456789/906</link>
    <description />
    <items>
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        <rdf:li rdf:resource="https://www.um.edu.mt/library/oar/handle/123456789/144069" />
        <rdf:li rdf:resource="https://www.um.edu.mt/library/oar/handle/123456789/143309" />
        <rdf:li rdf:resource="https://www.um.edu.mt/library/oar/handle/123456789/141614" />
        <rdf:li rdf:resource="https://www.um.edu.mt/library/oar/handle/123456789/140715" />
      </rdf:Seq>
    </items>
    <dc:date>2026-04-09T22:49:25Z</dc:date>
  </channel>
  <item rdf:about="https://www.um.edu.mt/library/oar/handle/123456789/144069">
    <title>Modelling indoor household PM2.5 using positive matrix factorization and machine learning algorithms</title>
    <link>https://www.um.edu.mt/library/oar/handle/123456789/144069</link>
    <description>Title: Modelling indoor household PM2.5 using positive matrix factorization and machine learning algorithms
Abstract: People tend to spend most of their time indoors, yet the concentration and composition of &#xD;
indoor fine particulate matter (PM2.5) remain poorly understood in the Maltese Islands, with &#xD;
existing receptor modelling studies focusing solely on ambient air. The first objective of this &#xD;
study was to carry out long-term indoor air sampling of PM2.5 followed by chemical &#xD;
characterisation, in order to identify and quantify the main natural and anthropogenic sources &#xD;
of indoor PM2.5 at an urban background site in Malta using Positive Matrix Factorisation &#xD;
(PMF). The second objective was to explore the use of Machine Learning (ML) algorithms to &#xD;
model and predict indoor PM2.5 concentrations in several households in Malta and Gozo. &#xD;
PMF was used to identify and quantify the major sources of indoor PM2.5. Quartz and PTFE &#xD;
filters were collected and analysed gravimetrically and chemically using ICP-MS, IC, and an &#xD;
OC-EC aerosol analyser to determine concentrations of PM2.5, 18 elements, 5 ions, organic &#xD;
carbon (OC), and elemental carbon (EC). Eight contributing factors were identified, seven &#xD;
outdoor sources and one indoor source, contributing 68% and 26% to indoor PM2.5, &#xD;
respectively. Cooking and e-cigarette use were the main contributors to the indoor factor. &#xD;
Uniquely for Malta, a fireworks factor was isolated indoors, responsible for most of the &#xD;
measured Sb and Ba, raising concerns due to the toxicity of these elements. An RF-SHAP &#xD;
model was integrated with the indoor PMF model to investigate the influence of key drivers on &#xD;
indoor PM2.5 concentrations. An outdoor PMF analysis was also conducted, and a &#xD;
corresponding RF-SHAP model (CV RMSE: 2.79 µg m−3; R²: 0.80) was used to refine the &#xD;
outdoor source contributions. Transboundary contributions (Saharan dust and ammonium &#xD;
sulfate) were higher outdoors (58%) than indoors (33%) due to reduced infiltration when &#xD;
windows are closed. Local anthropogenic sources (Industrial, Fireworks, Traffic, Shipping) &#xD;
contributed more to outdoor PM2.5 (33%) than indoor (25%), with increased indoor infiltration &#xD;
during warmer months coinciding with peak fireworks activity. &#xD;
For the second objective, continuous PM measurements were taken using aerosol &#xD;
spectrometers at seven non-smoking residences. RF and XGBoost models were developed to &#xD;
predict indoor PM2.5 at six-hourly intervals. At sites with low indoor PM generation, &#xD;
predictions were mainly influenced by outdoor PM1 levels. At a site with high indoor &#xD;
emissions, indoor relative humidity was a key predictor, especially during cooking. The RF &#xD;
model performed best overall (RMSE: 30.65 µg m−3; IOA: 0.66).
Description: Ph.D.(Melit.)</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://www.um.edu.mt/library/oar/handle/123456789/143309">
    <title>Storage stability and antioxidant activity of astaxanthin and beta-carotene as affected by the architecture of O/W emulsions of milk proteins</title>
    <link>https://www.um.edu.mt/library/oar/handle/123456789/143309</link>
    <description>Title: Storage stability and antioxidant activity of astaxanthin and beta-carotene as affected by the architecture of O/W emulsions of milk proteins
Authors: Habtegebriel, Haileeyesus; Tazart, Zakaria; Farrugia, Claude; Valdramidis, Vasilis
Abstract: Astaxanthin and β-carotene are among the potential anti-oxidant carotenoids with strong health promoting features. However, their sensitivity to light, heat and mechanical forces limit their application in food processing and storage conditions. The design of food matrix system, such as emulsions, that could prevent them from exposure to environmental factors will be utmost importance to slow down their degradation. In this study, O/W emulsion systems containing sunflower oil were prepared by applying ultrasound treatment and using different stabilizers (i.e. whey protein isolate (WPI) and sodium caseinate; NaCAS), co-surfactants (pectin and lecithin) while their performance against physical and chemical stability were investigated. The WPI– lecithin system produced emulsion droplets with Average diameter in the range of 560–2900 nm with a zeta-potential in the range of (−31) – (−34) mV, whereas the NaCAS – lecithin systems produced emulsion droplets with average diameter in the range of 230–240 nm and zeta potential of (−44) – (−48) mV. These values have a direct effect on the physical stability and chemical stability of the carotenoids in the emulsions. Astaxanthin was found to be more sensitive than β-carotene to ultrasound processing conditions. The designed emulsion systems slowed down the degradation of the carotenoids and maintained their DPPH scavenging properties during storage with astaxanthin loaded emulsions exhibiting better DPPH activity than β-carotene loaded emulsions.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://www.um.edu.mt/library/oar/handle/123456789/141614">
    <title>Molecular logic gates as fluorescent markers and DNA binding agents</title>
    <link>https://www.um.edu.mt/library/oar/handle/123456789/141614</link>
    <description>Title: Molecular logic gates as fluorescent markers and DNA binding agents
Abstract: N/A
Description: Ph.D.(Melit.)</description>
    <dc:date>2023-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://www.um.edu.mt/library/oar/handle/123456789/140715">
    <title>N-unsubstituted dihydropyridines and pyridones via multicomponent synthesis under a bio-derived heterogeneous catalyst</title>
    <link>https://www.um.edu.mt/library/oar/handle/123456789/140715</link>
    <description>Title: N-unsubstituted dihydropyridines and pyridones via multicomponent synthesis under a bio-derived heterogeneous catalyst
Authors: Bosica, Giovanna; Abdilla, Roderick
Abstract: In our exploration of metal-free and cost-effective heterogeneous catalysts for MCRs, we identified a novel system: piperazine immobilized within an agar matrix, functioning as a recyclable and reusable catalyst. This system efficiently facilitates the synthesis of dihydropyridines (DHPs) via one-pot condensation of dimedone, aldehydes, ammonium acetate, and various active methylene compounds—specifically malononitrile, acetophenone, or Meldrum's acid. A broad range of products was obtained, underscoring the versatility of the methodology. Notably, our prior investigations demonstrated this catalyst's efficacy in synthesizing N-aryl-substituted DHPs, affirming its general applicability. Additionally, fluorescence and UV absorption studies, along with in-depth characterization using 2D NMR spectroscopy, were conducted to confirm the structure and peak assignments of the synthesized products.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </item>
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