Image 1_Disorders of acid-base balance promote rumen lipopolysaccharide biosynthesis in dairy cows by modulating the microbiome.jpeg by Guobin Hou (20207727)

“…Introduction<p>Disorders of acid-base balance in the rumen of dairy cows have a significant impact on their health and performance. …”

Coherence of SCN metabolic pathways changes during development. by Martin Sládek (130663)

“…<b>(D)</b> Chord plots showing highly significant (<i>P</i> < 0.001) positive correlations (with the number of individual correlations illustrated by the thickness of a ribbon) between polar metabolites and individual lipids clustered to major classes within the developing SCN. …”

The effect of HA digestion and HA replenishment alone or with CS on barrier function measured by TEER. by Charlotte J. van Ginkel (20790466)

“…In (B) and (C) each point represents a mean ± standard deviation. (B) Hyaluronidase treatment (n = 8) gradually increased TEER, this significantly differed from the untreated group (n = 8) and the PS treated group (n = 8) (p < 0,001). …”

Table 2_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Image 1_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 8_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Table 9_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Table 10_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Table 4_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Table 5_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Image 6_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 2_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 7_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Table 3_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Image 5_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Table 1_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Image 4_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Table 11_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Table 8_Burden of malaria in the Comoros, 1990–2021: findings from the global burden of disease study 2021.xlsx by Sheng Zhou (66217)

“…Between 1990 and 2021, the malaria burden in the Comoros declined substantially, with age-standardized incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY rates (ASDR) decreasing by over 85%. Decomposition analysis indicated that epidemiological changes played a pivotal role in reducing disease burden. …”

Image 3_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”