Table 1_Linkage of living microbial biomass, function, and necromass to soil organic carbon storage along a chronosequence of Larix principis-rupprechtii plantation in North China.... by Mengyun Yang (5747186)

“…Notably, the increased stand ages (i.e., 34a and 44a) or decreased aggregate sizes (<0.25 mm) enhanced SOC stability (as indicated by the recalcitrance index) and oxidative exo-enzymatic activities, as well as enlarged MRC (especially fungal residue C) contribution to SOC. …”

Image 2_Computed tomography and magnetic resonance imaging features of primary liver perivascular epithelioid cell tumor with renal angiomyolipoma: a case report and literature rev... by Ruoling Gao (12201178)

“…The disease has few specific clinical symptoms and imaging manifestations, making its accurate diagnosis an intractable clinical challenge. This is a report of a female patient diagnosed with lesions and a mass in the left lobe of the liver. …”

Image 1_Computed tomography and magnetic resonance imaging features of primary liver perivascular epithelioid cell tumor with renal angiomyolipoma: a case report and literature rev... by Ruoling Gao (12201178)

“…The disease has few specific clinical symptoms and imaging manifestations, making its accurate diagnosis an intractable clinical challenge. This is a report of a female patient diagnosed with lesions and a mass in the left lobe of the liver. …”

Major hyperparameters of RF-SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Pseudo code for coupling model execution process. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Major hyperparameters of RF-MLPR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Results of RF algorithm screening factors. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Scree plot curve for five sets of models for the upper auricle. by Hitoshi Biwasaka (19923867)

Histograms of changes in pattern diversity by Selim Haj Ali (21222613)

“…The negative criterion predicts pattern diversity decreases for 15749 cases ( of all observations, <i>blue histogram</i>) of average (blue dashed vertical line) which translates into a negative predictive value of 0.86. …”

Chromosomal partitioning is maintained during intracellular UPEC coccobacilli divisions. by Alaska Pokhrel (9566813)

“…Statistical significance was determined by student <i>T</i> test, where **** stars indicate p values less than 0.0001., n.s. = not significant. …”

DataSheet1_Causal effects of serum calcium, phosphate, and 25-hydroxyvitamin D on kidney function: a genetic correlation, pleiotropic analysis, and Mendelian randomization study.zi... by Yanjun Liang (4394089)

“…Genetic correlations were observed between serum Ca and urine albumin-to-creatinine ratio (UACR) (rg = 0.202, P-value = 5.0E−04), between serum 25(OH)D and estimated glomerular filtration rate using serum creatinine (eGFRcrea) (rg = -0.094; P-value = 1.4E−05), and between serum 25(OH)D and blood urea nitrogen (BUN) (rg = 0.127; P-value = 1.7E−06). …”

Data_Sheet_1_A randomized double-blinded study assessing the effect of different doses of transnasal dexmedetomidine on the median effective concentration of ropivacaine for a caud... by Fu Wang (10556)

“…Compared to group IN-NS, the EC50 value of ropivacaine in IN-DEX2 was significantly decreased by 21.4% (p = 0.001), while there was no significant difference between group IN-NS and IN-DEX1 (p = 0.125). …”

Risk of Urogenital Infections in People with Type 2 Diabetes Initiating SGLT2i versus GLP-1RA in Routine Clinical Care: A Danish Cohort Study by Christine Ljungberg (20880865)

“…However, early GTI risk is up-to 3-fold larger in SGLT2i users. </p>…”

Supplementary file 1_Clinical application of combined anticoagulation therapy in anti-MDA5 antibody-positive associated interstitial lung disease-a retrospective study.docx by Ting Zhang (102583)

Data Sheet 1_Reduced pulmonary arterial compliance predicts poor short-term outcome in children with pulmonary arterial hypertension independent of pulmonary vascular resistance.pd... by Eva Gouwy (21408626)

“…Therefore, PACi is of additional prognostic value to PVRi, especially for short term prediction.…”

Data Sheet 1_In vivo quantification of superficial cortical veins on susceptibility-weighted imaging with artificial intelligence image segmentation and the potential mechanism of... by Qi Xie (230608)

Data Sheet 1_Community dynamics influencing commercial tobacco control policy development on California American Indian lands: a qualitative analysis of baseline CAITIE data.docx by Jeremiah Wiebe-Anderson (21684716)

Data Sheet 1_Targeted UDP-glucose ceramide glucosyltransferase stable overexpression induces a metabolic switch improving cell performance at high cell density.pdf by Marzia Rahimi (22419976)

“…Intensification of TGE processes to high cell densities is hampered by the cell density effect (CDE), characterized by decreased cell-specific productivity as cell density increases. …”

Table 1_Differential brain activity in patients with disorders of consciousness: a 3-month rs-fMRI study using amplitude of low-frequency fluctuation.docx by Xuewei Qin (20426600)