Entomopathogenic fungi-derived copper nanoparticles (CuNPs) exhibited minimal toxicity effects against <i>A</i>. <i>salina</i> at 24 and 48h post treatment. by Perumal Vivekanandhan (4863484)

After 8 weeks of treatment, body fat analysis and bone mineral density testing of mice in each group. by Xueqin lu (22250795)

Pharmacological efficacy of Kylo-0603 in MASH mouse models (F2 ~ 3). by Xueqin lu (22250795)

Plasma cholesterol and LDL-C levels. by Xueqin lu (22250795)

The Chol and TG content in liver homogenates of the mice in each group after 2 and 10 weeks of drug intervention. by Xueqin lu (22250795)

Hematoxylin and eosin (H&E) staining, Sirius Red staining, and Oil Red staining of liver tissues from mice in each group after 8 weeks of treatment with either vehicle or Kylo-0603... by Xueqin lu (22250795)

(A) Time spent in closed arm, (B) Time spent in open arm, (C) Number of entries in closed arm, (D) Number of entries in open arm, and (E) Latency time to enter open arm for elevate... by Hammad Ismail (4227988)

Effects of menstrual cycle on MST performance. by Mateja Perović (21238182)

“…There is a distinct non-linear effect of cycle point on accuracy for lures, but not for foils or targets, showing a decrease in accuracy in the ML phase of the cycle. …”

Flowchart of CNNBLSTM algorithm. by Guozhu Sui (21672798)

“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”

Comparison of TL and VL of different algorithms. by Guozhu Sui (21672798)

“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”

Analysis of ST characteristics of TF. by Guozhu Sui (21672798)

“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”

Schematic diagram of STTFP model. by Guozhu Sui (21672798)

“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”

Summary of the methods in current research. by Guozhu Sui (21672798)

“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”

Diagram of the improved CNNBLSTM model. by Guozhu Sui (21672798)

“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”

LA is a more potent inhibitor of HIV-1 virion-associated RT activity compared to acetic acid or low pH (HCl) alone. by Muriel Aldunate (22411177)

Shedding patterns of the top 30 most abundant individual barcodes found in each mouse during the time course of infection. by Sylvain Blois (663852)

Modeling the relationship between cancer level in hemolymph and MarBTN in tank eDNA. by Rachael M. Giersch (22331947)

Complexity comparison of different models. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”

Dynamic window based median filtering algorithm. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”

Flow of operation of improved KMA. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”