Result of comparison of different lightweight. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

DyHead Structure. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

The parameters of the training phase. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Structure of GSConv network. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Improved model distillation structure. by Zhongjian Xie (4633099)

“…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. …”

Data Sheet 1_Impact of large-scale oceanic variability on Adriatic fisheries evidenced through the ‘mean temperature of the catch’ approach.docx by Elvis Kamberi (22759586)

“…Our results show that after an initial decreasing trend until the late 1980s at a rate of 0.48°C per decade, the MTC subsequently increased at a rate of 0.24°C per decade. …”

A-E. The participants’ VAS pain scores, walking distance covered during the 6-Minute Walk Test, Short Form-12 sum scores and Western Ontario and McMaster Universities Osteoarthriti... by Lex D. de Jong (22138778)

Identification of VHL as a novel E3 ubiquitin ligase for Vpx. by Kei Miyakawa (255697)

“…Data are presented as mean ± standard deviation (SD) (n = 2). Statistical significance was evaluated using a two-tailed unpaired <i>t</i>-test. …”

Supplementary file 1_Source apportionment and ecological risk of heavy metals in Taihu lake from 2020 to 2022.docx by Guangjing Bao (21837749)

“…Furthermore, the potential ecological risk exhibited a significant decreasing trend, with Z-values passing the 95% confidence interval significance test, except for S3. …”

Table 1_GLP1 receptor agonists and SGLT2 inhibitors for the prevention or delay of type 2 diabetes mellitus onset: a systematic review and meta-analysis.docx by Farah Ghobar (22480732)

“…Moreover, HbA1c levels were assessed in seven studies, where significant reductions in treatment groups were reported with a standardized mean difference of -6.95 (95% CI: [-14.24, 2.98], p-value= 0.06) for the overall effect size. …”

Serum metabolomic response to aging. by Gwangho Yoon (5771678)

“…<b>(B)</b> Metabolites that decreased with aging. Statistical significance is indicated in the heatmap with asterisks. …”

Variability in performance and response to task dynamics. by Daniel Ramandi (10047543)

“…(E) When focusing on five consecutive successful trials, WT mice showed a significant reduction in trajectory variability, whereas zQ175 mice exhibited only a slight decrease, predominantly in the last trial, hinting at genotype-specific differences in optimizing performance following success (RM two-way ANOVA, genotype p = 0.746 F(1, 22) = 0.1074, trial p = 0.012 F(2.836, 62.38) = 4.045, interaction p = 0.018 F(3, 66) = 3.561). …”

European study sites. by Graeme T. Swindles (7192745)

“…We find that summer temperature is a significant climatic control on aPAR across our European sites. …”

Location of study sites. by Graeme T. Swindles (7192745)

“…We find that summer temperature is a significant climatic control on aPAR across our European sites. …”

Map showing the intervention and control LGAs. by Chinwe C. Eze (8787503)

“…At baseline, respondents in the intervention group had a significantly higher adjusted mean total score on the SARI Stigma Scale compared to the control group, with an adjusted mean difference of 10.75 (95% CI: 8.05–13.46, p < 0.000). …”

Consort diagram. by Chinwe C. Eze (8787503)

“…At baseline, respondents in the intervention group had a significantly higher adjusted mean total score on the SARI Stigma Scale compared to the control group, with an adjusted mean difference of 10.75 (95% CI: 8.05–13.46, p < 0.000). …”

VisAccel complete data_redacted2.xlsx by Miguel A. Yakouma (21439852)

“…When the velocity profile of the visual stimulus matched the velocity profile of inertial motion, the inertial stimulus was biased 10.0 ± 1.8° (mean ± SE) with a 45° visual offset, 8.9 ± 1.7° with a 60° offset, and 9.3° ± 2.5 ± with a 75° offset. …”

Barnes maze testing in animals on post-injury day 1. by Ghaith A. Bahader (21387572)

“…(A) Briefly, animals received acclimation and then four days of acquisition with expected decreasing mean times to escape. …”

Modulation of performance during learning. by Daniel Ramandi (10047543)

“…The ‘W_exp’ value shows the weight of the exponential component in each distribution. (B) A longitudinal comparison of the average exponential fit weight between WT and zQ175 mice reveals that while WT mice show a decreasing trend, indicating a shift towards longer duration (“timed”) trials, zQ175 mice maintain a consistently high exponential weight, demonstrating no significant change over time (b; RM two-way ANOVA, genotype p = 0.0106 F(1, 22) = 7.795, days p < 0.0001 F(5.262, 115.4) = 7.616, interaction p < 0.0001 F(57, 1250) = 2.834). …”