The performance of S-YOFEO model on MOT17. by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”

Table5_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

Table 1_Evaluating the Implementation of fan-beam CT-guided online adaptive re-planning in definitive cervical cancer radiotherapy.docx by Shuai Sun (775057)

“…This approach has shown significant improvements in dose distribution and the potential to provide clinical benefits by reducing acute toxicity.…”

Five multi-target tracking evaluation indexes. by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”

Genetic and structural factors contributing to the dominance and persistence of goose astrovirus type 2 by Peng Jiang (16544)

“…<p>Goose astrovirus (GoAstV) has emerged as a significant pathogen affecting the goose industry in China, with GoAstV-2 becoming the dominant genotype since 2017. …”

Image 1_Dysfunctional β-cell autophagy induces β-cell stress and enhances islet immunogenicity.tiff by Matthew C. Austin (20633168)

“…Gene ontology analysis revealed a significant upregulation of pathways involved in inflammatory processes, response to ER stress, and the ER-associated degradation pathway. …”

Algorithm flowchart of OFEO. by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”

Image 1_Kidney sparing surgery versus radical nephroureterectomy in upper tract urothelial carcinoma: a meta-analysis and systematic review.tif by Leqing Zhou (20981021)

“…In the comparison between the endoscopic management (EM) and RNU groups, EM was associated with worse overall survival outcomes (HR,1.40; 95%CI,1.08-1.82; P=0.01) based on multivariable Cox regression analysis, and the upper tract recurrence rate (OR,39.06; 95%CI, 14.55-104.85; P<0.00001) was significantly higher in the EM group. On the other hand, in patients treated with KSS, postoperative renal function as measured by eGFR increased by 0.4ml/min/1.73 m², while it decreased by 11.4ml/min/1.73 m² in the RNU group (WMD, 11.81 ml/min/1.73 m²; 95%CI,9.06-14.56; P<0.0001).…”

Data Sheet 1_The impact of immune checkpoint inhibitors on prognosis in unresectable hepatocellular carcinoma treated with TACE and lenvatinib: a meta-analysis.zip by Wei Zhang (405)

“…The TACE+L+I group had a significantly higher incidence of hypothyroidism compared to the TACE+L group (RR = 1.81, 95%CI:1.20, 2.71, p<0.05), but there was no significant difference in other adverse events, such as hypertension, diarrhea, hand-foot syndrome, fatigue, elevated AST, elevated ALT, decreased appetite, hypothyroidism, abdominal pain, thrombocytopenia, rash, and nausea.…”

Table10_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

Table1_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

Data sources and descriptions. by Zeduo Zou (21672789)

“…As the results show, during the study period: (1) Temporal Trends: annual PM2.5 concentrations exhibited significant declines, with BTH decreasing from 1004.71 μg/m³ (2006) to 528 μg/m³ (2020), YRD from 1434.81 μg/m³ (2008) to 621 μg/m³, and PRD from 405.02 μg/m³ (2007) to 292 μg/m³. …”

Image 3_Dysfunctional β-cell autophagy induces β-cell stress and enhances islet immunogenicity.tiff by Matthew C. Austin (20633168)

“…Gene ontology analysis revealed a significant upregulation of pathways involved in inflammatory processes, response to ER stress, and the ER-associated degradation pathway. …”

Partial tracking results of MOT17 dataset. by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”

Replication package for "Measuring trade costs and analyzing the determinants of trade growth between Cambodia and major trading partners: 1993-2019" by Borin Keo (20919743)

“…Despite their practical significance and increasing policy attention in the country, little is known about these costs.…”

Improved detection layer. by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”

The performance of S-YOFEO model on MOT16. by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”

Table4_Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.xlsx by Yifang He (18126257)

“…</p>Conclusions<p>Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.…”

Image 4_Dysfunctional β-cell autophagy induces β-cell stress and enhances islet immunogenicity.tif by Matthew C. Austin (20633168)

“…Gene ontology analysis revealed a significant upregulation of pathways involved in inflammatory processes, response to ER stress, and the ER-associated degradation pathway. …”

The matching process of EIOU. by Wenshun Sheng (21485393)

“…OSA is highly sensitive to information of different scales, and its one-time aggregation property substantially decreases the computational overhead of the model. …”