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      <title><![CDATA[Renewable Energy Transitions in Sub-Saharan Africa: Techno-Economic Assessment of Hybrid Solar–Wind Systems for Rural Electrification]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.ajes.003</link>
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      <pubDate>Mon, 01 Jun 2026 10:00:00 GMT</pubDate>
      <dc:creator><![CDATA[Dr. Priya Sharma, Thomas Müller, Dr. Fatima Al-Mansouri]]></dc:creator>
      <description><![CDATA[We present a techno-economic optimization model for hybrid solar photovoltaic–wind turbine–battery storage systems across 47 rural communities, achieving levelized cost of electricity of /bin/sh.08–0.14/kWh, undercutting diesel generators by 52–68%.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.ajes.003</dc:identifier>
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      <title><![CDATA[Self-Healing Polymer Composites Incorporating Microencapsulated Dicyclopentadiene for Aerospace Applications]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.ijamr.003</link>
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      <pubDate>Wed, 20 May 2026 11:00:00 GMT</pubDate>
      <dc:creator><![CDATA[Thomas Müller, Dr. Aisha Bello, Sakura Tanaka]]></dc:creator>
      <description><![CDATA[We developed epoxy-based composites with microencapsulated dicyclopentadiene and Grubbs catalyst showing 78% healing efficiency at 10 wt% loading and 92% compressive strength restoration after indentation damage.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.ijamr.003</dc:identifier>
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      <title><![CDATA[Graph Neural Networks for Predicting Metabolic Pathway Flux in Engineered Escherichia coli]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.jcbb.003</link>
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      <pubDate>Sun, 10 May 2026 09:00:00 GMT</pubDate>
      <dc:creator><![CDATA[Sakura Tanaka, Carlos Mendes, Thomas Müller]]></dc:creator>
      <description><![CDATA[We introduce FluxGNN, a graph neural network framework that models metabolic networks as heterogeneous graphs and predicts flux distributions under genetic perturbations, achieving a mean absolute error of 0.087 mmol/gDCW/h and outperforming constraint-based methods by 34%.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.jcbb.003</dc:identifier>
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      <title><![CDATA[Assessment of Microplastic Contamination in Major African River Systems: The Nile, Niger, and Zambezi]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.ajes.002</link>
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      <pubDate>Wed, 15 Apr 2026 13:00:00 GMT</pubDate>
      <dc:creator><![CDATA[Dr. Elena Kovacs, Carlos Mendes, Wei Zhang]]></dc:creator>
      <description><![CDATA[We conducted a comprehensive assessment of microplastic abundance in surface waters and sediments of the Nile, Niger, and Zambezi river systems, finding mean concentrations from 1.8 to 48.3 particles/L with polyethylene and polypropylene as dominant polymer types.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.ajes.002</dc:identifier>
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      <title><![CDATA[Room-Temperature Synthesis of Perovskite Quantum Dots with Enhanced Photoluminescence Quantum Yield]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.ijamr.002</link>
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      <pubDate>Thu, 02 Apr 2026 15:00:00 GMT</pubDate>
      <dc:creator><![CDATA[Wei Zhang, Carlos Mendes, James Odhiambo]]></dc:creator>
      <description><![CDATA[We report a room-temperature synthesis method for CsPbBr₃ perovskite quantum dots exhibiting photoluminescence quantum yield of 94.7% with narrow emission bandwidth of 18 nm and 92% stability retention after 1,000 hours of continuous excitation.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.ijamr.002</dc:identifier>
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      <title><![CDATA[Genome-Wide Association Study of Drug Resistance in Plasmodium falciparum Using Machine Learning]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.jcbb.002</link>
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      <pubDate>Sun, 22 Mar 2026 14:30:00 GMT</pubDate>
      <dc:creator><![CDATA[Dr. Aisha Bello, James Odhiambo, Dr. Fatima Al-Mansouri]]></dc:creator>
      <description><![CDATA[We performed a genome-wide association study combined with random forest and XGBoost classifiers to identify genetic markers associated with artemisinin resistance in 1,247 P. falciparum isolates from sub-Saharan Africa, identifying 17 novel SNPs significantly associated with delayed parasite clearance.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.jcbb.002</dc:identifier>
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      <title><![CDATA[Impact of Climate Variability on Smallholder Maize Production in East Africa: A 30-Year Retrospective Analysis]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.ajes.001</link>
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      <pubDate>Sun, 08 Feb 2026 11:00:00 GMT</pubDate>
      <dc:creator><![CDATA[James Odhiambo, Dr. Aisha Bello, Dr. Fatima Al-Mansouri]]></dc:creator>
      <description><![CDATA[We analyzed a 30-year dataset combining satellite-derived rainfall records, temperature anomalies, and maize yield surveys from 12,500 smallholder farms across Kenya, Tanzania, and Uganda, finding each 1°C increase reduces maize yields by 8.7%.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.ajes.001</dc:identifier>
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      <title><![CDATA[Graphene Oxide–Polyvinyl Alcohol Nanocomposite Hydrogels with Tunable Mechanical Properties for Biomedical Applications]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.ijamr.001</link>
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      <pubDate>Wed, 28 Jan 2026 09:30:00 GMT</pubDate>
      <dc:creator><![CDATA[Sakura Tanaka, Dr. Priya Sharma, Dr. Elena Kovacs]]></dc:creator>
      <description><![CDATA[We synthesized graphene oxide–polyvinyl alcohol nanocomposite hydrogels with varying GO concentrations. Incorporation of 2.0 wt% GO increased compressive modulus by 340% and tensile strength by 280%, with >90% cell viability in osteoblast assays.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.ijamr.001</dc:identifier>
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      <title><![CDATA[Deep Learning Approaches for Predicting Protein–Protein Interactions from Sequence Data]]></title>
      <link>https://onejournal.cc/articles/10.5281-zenodo.2024.jcbb.001</link>
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      <pubDate>Thu, 15 Jan 2026 10:00:00 GMT</pubDate>
      <dc:creator><![CDATA[Dr. Elena Kovacs, Wei Zhang, Dr. Priya Sharma]]></dc:creator>
      <description><![CDATA[Protein–protein interactions (PPIs) govern most cellular processes, yet experimental characterization remains costly and time-consuming. We present DeepPPI-3D, a novel deep learning architecture that integrates transformer-based sequence embeddings with predicted structural features to predict PPIs with 94.7% accuracy on human proteome data, achieving a 12% improvement over state-of-the-art methods on the STRING database benchmark.]]></description>
      <dc:identifier>doi:10.5281/zenodo.2024.jcbb.001</dc:identifier>
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