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Orginal models of the basilar artery used in the scientific article containing: 1. Dicom files of the basilar artery performed on an industrial Nikkon CT Scanner 2. Basilar artery model in .stl format - raw model 3. Basilar artery model in .stl format - raw model extended Hounsfield scale 4. Basilar artery model prepared in Altair Inspire in .stmod format - after artery connections 5. Basilar artery model prepared in Altair Inspire in .stmod format - before artery connections 6. Basilar artery model prepared in Altair HyperMesh in .hm format - idealized case 7. Basilar artery model prepared in Altair HyperMesh in .hm format - real case 8. Basilar artery prepared in .msh.h5 format - idealized case 9. Basilar artery prepared in .msh.h5 format - real case 10. Basilar artery prepared in .msh.h5 format - hybrid case 11. The velocity curve used in the work in .txt format 12. Pressure curve used in the work in .txt format - BA outlet 13. Pressure curve used in the work in .txt format - perforators outlet 35/60 mmHg 14. Pressure curve used in the work in .txt format - perforators outlet 55/78 mmHg 15. User defined function for blood in .c format

Orginal data used in the scientific article containing: 1. Basilar artery model in .hm - Hypermesh model 2. Basilar artery model in .msh.h5 - Fluent model 3. The velocity curve used in the work in .txt format - BA_velocity_doppler 4. Pressure curve used in the work in .txt format - BA_pressure 5. User defined function for blood in .c format 6. Normalized velocity profile for BA 7. Middle cerebral artery model in .hm - Hypermesh model 8. Middle cerebral artery model in .msh.h5 - Fluent model 9. The velocity curve used in the work in .txt format - MCA_velocity_doppler 10. Pressure curve used in the work in .txt format - MCA_pressure 11. Pressure curve used in the work in .txt format - MCA_pressure_0.5_minus_mmHg 12. Normalized velocity profile for MCA 13. Stl. files of the middle cerebral artery performed on an industrial Nikkon CT Scanner (BA is in previous authors base) 14. Sample of porosity definition (screenshot form Ansys Fluent) 15. Named expression (velocity inlet transient profile - screenshot form Ansys Fluent) 16. Umax definition (screenshot form Ansys Fluent) 17. Paraview - automatic export to ensight format used in paraview (screenshot form Ansys Fluent) 18. Porosity zone calculator

This archive contains four data files providing different calculations of steric (SSL), thermometric (SSL), and ocean heat content (OHC) anomalies from 2003 through 2023: 1) a text file of SSL, TSL, and OHC anomalies for individual Argo float profiles at specific longitude, latitude, and times. 2) a netCDF file of monthly longwave SSL maps (1° resolution) computed by combining Argo floats with satellite altimetry and gravimetry (along with standard errors) 3) a netCDF file of monthly longwave TSL maps (1° resolution) computed by combining Argo floats with satellite altimetry and gravimetry (along with standard errors). 4) a netCDF file of monthly longwave OHC maps (1° resolution) computed by combining Argo floats with satellite altimetry and gravimetry (along with standard errors).

This dataset contains raw, replicate-level measurements generated in a multicenter study assessing the commutability of External Quality Assessment (EQA) control materials across routine clinical chemistry platforms. No post-processing, outlier removal, bias calculations, uncertainty propagation, or commutability classifications are included here; all values are as reported by the participating instruments in the single analytical run per site. Study design (for data context) Setting: Ten routine clinical laboratories participating in the Lombardy Regional EQA program. Analytes (measurands): ALP, ALT, AST, CK, LDH, CHE, creatinine, calcium. Specimens: Three lyophilized control materials (CM-1/CM-2/CM-3) and fifteen human serum pools. Each site performed one analytical run. CMs were measured in six replicates; pools in three replicates. Routine calibration and IQC preceded each run

Extracellular vesicles (EVs) are crucial for intercellular communication and are found in various biological fluids. The identification and immunophenotyping of such small particles continue to pose significant challenges. Here, we have developed a workflow for the optimisation of a next-generation panel for in-depth immunophenotyping of circulating plasma EVs using spectral flow cytometry. Our data collection followed a multistep optimisation phase for both instrument setup and 21-colour panel design, thus maximising fluorescent signal recovery. This spectral approach enabled the identification of novel EV subpopulations. Indeed, besides common EVs released by erythrocytes, platelets, leukocytes and endothelial cells, we observed rare and poorly known EV subsets carrying antigens related to cell activation or exhaustion. Notably, the unsupervised data analysis of major EV subsets revealed subpopulations expressing up to five surface antigens simultaneously. However, the majority of EVs expressed only a single surface antigen, suggesting they may not fully represent the phenotype of their parent cells. This is likely due to the small surface area or the biogenesis of EVs rather than antibody steric hindrance. Finally, we tested our workflow by analysing the plasma EV landscape in a cohort of systemic lupus erythematosus (SLE) patients. Interestingly, we observed a significant increase in CD54+ EVs, supporting the notion of elevated circulating ICAM under SLE conditions. To our knowledge, these are the first data highlighting the importance of a spectral flow cytometry approach in deciphering the heterogeneity of plasma EVs paving the way for the routine use of a high-dimensional immunophenotyping in EV research.

The dataset (Experimental Validation of S809 Airfoil) compares the experimental data of S809 airfoil with the data obtained from CFD analysis. The experimental data is taken from Colorado State University, and the selected Reynolds number is 500,000 at a wind speed of 7.3 m/s. This experimental data is taken from the article "Unsteady Aerodynamics Experiment Phase VI: Wind Tunnel Test Configurations and Available Data Campaigns". The CFD data is in good agreement with the experimental data. The data is present in both tabular and in graphical form. The datset (Comparison of lift and drag coefficients of Owl, Seagull and S809 Airfoils) compares the lift and drag coefficients of Owl, Seagull and S809 airfoil obtained from CFD to find out which airfoil will have higher lift to drag ratio, and hence which one can serve better when used in the design of wind turbine. The data is present in both tabular and in graphical form. Contributors: Raja Walied and Raja Moiz.

CD4+ T cells were isolated from human umbilical cord blood samples collected from Turku University Hospital from full-term normal delivery. Mononuclear cells were isolated using Ficoll density gradient centrifugation. CD4+ cells were then enriched using bead-based positive isolation (Dynal CD4 Positive Isolation Kit; Invitrogen, Cat. no. 11331D). LINC01871 was silenced using two LNAs targeting different regions of the gene (LNA1: 5´-TTCGGCCTTTGGTAGT-3´; LNA2: 5´-ACAGATCGTCCACGGC-3´) or non-targeting LNA (NT) (5´-AACACGTCTATACGC-3´). Cells were transfected with LNAs as described before (Andrabi et al., 2024). Briefly, 4 million cells, resuspended in 100 µl OptiMEM medium (Gibco by Life Technologies, Cat. no. 31985-047), were transfected with 300 pmol of LNA) using Amaxa nucleofector system (Nucleofector 2C / U-014 program) (Lonza). After nucleofection, cells were rested in RPMI medium, supplemented with pen/strep, 2 mM L-glutamine and 10% FCS, for 24 h at 37°C followed by their activation, as described above. LINC01871-deficient T cells were activated for 48 h, harvested and reactivated for 30 minutes, followed by RNA-seq and MS analyses. Cells were activated using plate-bound α-CD3 (3.75 μg/ml; Beckman Coulter, Cat. no. IM1304) and soluble α-CD28 (1 μg/ml; Beckman Coulter, Cat. no. IM1376) in RPMI 1640 medium (Sigma-Aldrich) supplemented with L-glutamine (2 mM, Sigma-Aldrich), antibiotics (50 U/ml penicillin plus 50 μg/ml streptomycin; Sigma-Aldrich) and 10% FCS. All cultures were maintained at 37°C in a humidified atmosphere of 5% (v/v) CO2 incubator. The RNA-seq and mass spectrometry (MS) data were of good quality. The principal component analysis (PCA) revealed low variability within biological replicates and high variability between the sample groups NT, LNA1 and LNA2 across the two main principal components (Fig. 2I). Hundreds of genes were DE upon LINC01871 silencing both in RNAseq and MS data (FDR<0.05), but the effect sizes were small (Table S2-3).

Olink Data of 40 Healthy Individuals and 144 Patients with Chronic Liver Disease, including Chroniv Viral Hepatitis, Alcohol-related Liver disease, and Metabolic Dysfunction-associated Steatotic Liver Disease. Inclusion and exclusion criteria: The study included adults aged 18-80 years who can provide informed consent and have a confirmed diagnosis of chronic liver disease through clinical evaluation, imaging, and histopathological findings. General exclusion criteria encompassed the presence of acute liver disease and other chronic liver diseases, such as Budd-Chiari syndrome, Wilson’s disease, autoimmune hepatitis, and drug-induced liver disease. Additional exclusion criteria include concurrent severe systemic illnesses, such as advanced cardiovascular disease, sepsis, or any malignancy other than HCC. Participants who were pregnant or lactating and had a history of organ transplantation were also excluded. For patients with MASLD and ARLD, diagnosis-specific inclusion and exclusion criteria are determined following guidelines outlined by Rinella et. al., 2023 2. For those with CVH, inclusion criteria involve a diagnosis of chronic viral hepatitis confirmed by serological tests. Patients diagnosed with hepatocellular carcinoma (HCC) met the general background etiology criteria of MASLD, ARLD, or CVH and had histologically or radiologically confirmed HCC.

Orthogonal test design table is a standardized table made on the basis of practical experience and theoretical understanding, this experiment uses L25 (56) type Tanioka orthogonal test table, 25 groups of tests are expected to be conducted. the orthogonal test examined the effects of moisture content (factor A), proportion (factor B), and heating temperature (factor C) on the particle density of molded particles to find the optimal combination of molding parameters, so as to obtain the best molding results.

The data stem from two democratic participatory processes (Structured Democratic Dialogues), which were organized in Cyprus in 2024; the first under the auspices of the Presidency aimed to develop a roadmap for introducing SDD in the school curricula; the second aimed to explore reforms that would render the educational experience more relevant and joyful. More information regarding the process and results is available: https://futureworlds.eu/wiki/Citizens_Commissioner%27s_Dialogue_to_Introduce_SDD_in_the_School_Curriculum https://futureworlds.eu/wiki/Ευτυχισμένοι_μαθητές_σε_ακμάζοντα_σχολεία_EN:_Happy_learners_in_thriving_schools The files include: (i) The questionnaire that has been used to evaluate the SDD in Education workshop (Original in Greek with an English translation: SDD_in_Education_Evaluation_Form_GR.pdf and SDD_in_Education_Evaluation_Form_EN.pdf). (ii) The raw data (in Excel) of the 1st and 2nd voting for both SDDs (SDD_HappyKids_1st_2nd_Vote_20250618.xlsx and SDD_in_Education_1st_2nd_Vote_20250618.xlsx). (iii) The processed data, along with charts generated (SDD_Edu_Politis_Charts_02.xlsx and SDD_Edu_Politis_Phases_Charts_02.xlsx). The first result from the Questionnaires (in response to the question, "Which, in your opinion, of the following skills can be developed through student participation in SDD? ") revealed that the abilities that develop the most through participating in SDD are expressive skills, critical thinking, problem solving, collaboration, flexibility, adaptability, and communication skills. Skills that develop moderately include emotional intelligence, creativity, and innovation. The second result (in response to "Which of the following skills can be developed in which of the stages of the SDD,") revealed that the first stages of the SDD (i.e., Idea Generation -Gene and Idea Clarification -Clar) promote active listening and expressive skills, while critical thinking and the ability to tackle and deal with stereotypes are favored in the latter stages (i.e., Clustering -Clu and Mapping -Map). The ability to change one's opinion, adapt, and become flexible in considering diverse viewpoints, tackle stereotypes, and engage in public debate appears to develop the most during the Clustering stage. The charts for the 1st and 2nd voting tested the hypothesis that participants' priorities shift as they clarify the meaning of each idea. Specifically, the results highlight the shift in priorities between the participants' preference voting before and after the Clustering. Note that before clustering the top ideas were #3, #29, #6, #2, #12, etc (Fig. 6), while, after Clustering, not only the ranking has changed, but also ideas that were not considered a priority now receive more votes (e.g., #6 shifts to 2nd place, #29 to 6th annd #13, #17, #9, etc. make it to the top six). The two files, named Charts_02, simply include the processed data used to generate the final charts.