Sökning: "chemical information"
Visar resultat 1 - 5 av 404 uppsatser innehållade orden chemical information.
1. Application of Fourier Transforms to time-resolved ambient pressure spectroscopy operando studies of CO oxidation over Pt(111)
Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/SynkrotronljusfysikSammanfattning : The study of heterogeneous catalysis has important implications in increasing the efficiency of industrial processes and in reducing the emissions of greenhouse gases from sources such as automobiles. A reaction with high industrial relevance is the oxidation of CO on noble metal catalysts. LÄS MER
2. Virtual H&E Staining Using PLS Microscopy and Neural Networks
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. LÄS MER
3. Jetbrandtester och vätgas : En litteratur- och intervjustudie om försök med vätgasjetflammor
Uppsats för yrkesexamina på grundnivå, Luleå tekniska universitet/Institutionen för samhällsbyggnad och naturresurserSammanfattning : Vätgas är en energibärare som kan vara en av pusselbitarna i omställningen till en mer klimatneutral värld. Infrastrukturen byggs ut, industrin växer och vätgasfordon blir vanligare. LÄS MER
4. Predicting Chemical-Gene Interactions
Master-uppsats, Göteborgs universitet / Institutionen för biologi och miljövetenskapSammanfattning : Pesticide use in agriculture has become a growing concern as it can have detrimental effects on the environment. The excessive use of these chemicals often leads to them seeping into nearby water bodies, causing harm to aquatic organisms. LÄS MER
5. Combining Cell Painting, Gene Expression and Structure-Activity Data for Mechanism of Action Prediction
Master-uppsats, Uppsala universitet/Nationellt resurscentrum för biologi och bioteknikSammanfattning : The rapid progress in high-throughput omics methods and high-resolution morphological profiling, coupled with the significant advances in machine learning (ML) and deep learning (DL), has opened new avenues for tackling the notoriously difficult problem of predicting the Mechanism of Action (MoA) for a drug of clinical interest. Understanding a drug's MoA can enrich our knowledge of its biological activity, shed light on potential side effects, and serve as a predictor of clinical success. LÄS MER