Search Results (188)

The paper presents the results of investigations of flow velocity field distribution downstream of the nanofibrous filter in a minichannel determined by the particle image velocimetry (PIV) method. The nonwoven nanofibrous filter was produced by electrospinning technology from a PVDF polymer dissolved in DMAC and acetone mixture. The nanofibers were deposited onto a mesh scaffold made of stainless steel wires 0.2 mm in diameter and with a 2 mm pitch. The gas velocity in the channel with the inserted nanofibrous filter was below 1.2 m/s. The flow field distribution in the channel was investigated by the Dantec FlowMap System. It was shown that the turbulence can be generated downstream of the filter, even for low Reynolds numbers smaller than 1300. This turbulence was attributed to the inhomogeneity of the fibrous filter structure. Another cause of this phenomenon could be the large area of the boundary layer at the channel walls compared to the channel cross section. Full article

Background: Pleural mesothelioma (PM) is a type of cancer that is difficult to diagnose and treat. Patients may have vastly varying prognoses, and prognostic factors may help guide the clinical approach. As a recently identified biomarker, the pan-Immune-Inflammation-Value (PIV) is a simple, comprehensive, and peripheral blood cell-based biomarker. Methods: The present study represents a retrospective observational analysis carried out within a single-center setting. Ninety-five patients with PM stages I–IV were enrolled in the study. We analyzed the correlation between patients’ demographic characteristics, clinicopathological factors such as histological subtypes, surgery status, tumor thickness, blood-based parameters, and treatment options with their prognoses. PIV was calculated by the following formula: (neutrophil count × monocyte count × platelet count)/lymphocyte count. Additionally, blood-based parameters were used to calculate the platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII). Results: We categorized the patients into two groups, low PIV group (PIV ≤ 732.3) and high PIV group (PIV > 732.3) according to the determined cut-off value, which was defined as the median. It was revealed that high PIV was associated with poor survival outcomes. The median follow-up period was 15.8 months (interquartile range, IQR, 7.1 to 29.8 months). The median overall survival (OS) was significantly longer in patients in the low PIV group (median 29.8 months, 95% confidence interval (CI), 15.6 to 44) than the high PIV group (median 14.7 months, 95% CI, 10.8 to 18.6 p < 0.001). Furthermore, the study revealed that patients with low PIV, NLR, and SII values were more likely to be eligible for surgery and were diagnosed at earlier stages. Additionally, these markers were identified as potential predictors of disease-free survival (DFS) in the surgical cohort and of treatment response across the entire patient population. Conclusions: In addition to well-established clinical factors such as stage, histologic subtype, resectability, and Eastern Cooperative Oncology Group (ECOG) performance status (PS), PIV emerged as an independent and significant prognostic factor of overall survival (OS) in patients with PM. Moreover, PIV also demonstrated a remarkable independent prognostic value for disease-free survival (DFS) in this patient population. Additionally, some clues are provided for conditions such as treatment responses, staging, and suitability for surgery. As such, in this cohort, it has outperformed the other blood-based markers based on our findings. Given its ease of calculation and cost-effectiveness, PIV represents a promising and practical prognostic tool in the clinical management of pleural mesothelioma. It can be easily calculated using routinely available laboratory parameters for every cancer patient, requiring no additional cost or complex procedures, thus facilitating its integration into everyday clinical practice. Full article

Background/Objectives: Although numerous prognostic biomarkers have been proposed for colorectal cancer (CRC), their longitudinal evaluation remains limited. The aim of this study was to investigate longitudinal changes in biomarkers calculated from routinely used laboratory markers and their relationships to common chronic diseases (comorbidities). Methods: A retrospective longitudinal observational study was completed with the inclusion of 817 CRC patients and a total of 4542 measurement points. Pan-immune inflammation value (PIV), prognostic nutritional index (PNI), and systemic immune-inflammation index (SII) were calculated based on complete blood count and albumin measurement data. Results: Longitudinal data analyses confirmed the different values and slopes of the parameters tested at the different endpoints. Survivors had the lowest and most constant PIVs and SII values, and the highest and most slowly decreasing PNI values. Those patients with non-cancerous death had similar values to the previous cohort, but an increase/decrease occurred towards the death event. Patients with CRC-related death had significantly higher PIVs and SII values and significantly lower PNI values (p < 0.0001), and a significant increase/decrease was observed at the early observational periods. The presence of lymph node and/or distant metastases, adjuvant chemotherapy, and hypertension significantly affected PIVs and SII and/or PNI values. The changes in PIVs and SII and PNI values toward pathological values are poor prognostic signs (p < 0.0001). Conclusions: Each of the three calculated markers demonstrates suitability for longitudinal patient follow-up, and their pathological alterations over time serve as valuable prognostic indicators. They may also be useful to detect certain clinicopathological parameters early. Full article

Hydrogen is a promising zero-carbon fuel for internal combustion engines; however, the geometric optimization of injectors for low-pressure direct-injection (LPDI) systems under lean-burn conditions remains underexplored. This study presents a high-fidelity optimization framework that couples a validated computational fluid dynamics (CFD) combustion model with a surrogate-assisted multi-objective genetic algorithm (MOGA). The CFD model was validated using particle image velocimetry (PIV) data from non-reacting flow experiments conducted in an optically accessible research engine developed by Sandia National Laboratories, ensuring accurate prediction of in-cylinder flow structures. The optimization focused on two critical geometric parameters: injector hole count and injection angle. Partial indicated mean effective pressure (pIMEP) and in-cylinder NO_x emissions were selected as conflicting objectives to balance performance and emissions. Adaptive mesh refinement (AMR) was employed to resolve transient in-cylinder flow and combustion dynamics with high spatial accuracy. Among 22 evaluated configurations including both capped and uncapped designs, the injector featuring three holes at a 15.24° injection angle outperformed the baseline, delivering improved mixture uniformity, reduced knock tendency, and lower NO_x emissions. These results demonstrate the potential of geometry-based optimization for advancing hydrogen-fueled LPDI engines toward cleaner and more efficient combustion strategies. Full article

Background/Objectives: Tumor-infiltrating lymphocytes (TILs) and inflammation status are emerging prognostic markers in various cancers, but their significance in high-grade serous ovarian carcinoma (HGSC) remains unclear. Our objective was to evaluate different TIL subtypes and inflammation status in relation to progression-free survival (PFS) in primary HGSC. Methods: CD3⁺/CD4⁺/CD8⁺/PD-1+ stromal TILs (sTILs) and intraepithelial TILs (iTILs) were evaluated by manual assessment and digital image analysis (DIA), following TIL Working Group recommendations. Inflammation status was evaluated through the following scores: systemic immune-inflammation index (SII), pan-immune-inflammation value (PIV), CA125, and lactate dehydrogenase (LDH). Results: CD8⁺ TILs were the most prevalent subtype in both iTILs and sTILs. However, sTILs were significantly more abundant than iTILs (p < 0.001) among all subsets, except for PD-1+ cells. DIA results of TIL assessments were in agreement with manual assessments. High stromal CD3⁺ and CD8⁺ TILs, PIV, CA125, and LDH, were associated with improved PFS. Potential independent prognostic factors for PFS in manual assessment were PIV (HR = 0.32, CI 95% = 0.12–0.82) and CD8⁺ sTILs (HR = 0.30, CI 95% = 0.12–0.79), whereas in DIA assessment they were CD3⁺ sTILs (HR = 0.31, CI 95% = 0.15–0.67), PIV (HR = 0.35, 95% CI 0.13–0.96), and residual disease (HR = 0.21 95% CI 0.08–0.53). Conclusions: CD3⁺/CD8⁺ sTILs and PIV are promising prognostic indicators in HGSC; however, further research is needed to confirm their clinical utility. Full article

Fuel electro-hydraulic servo valves are core components in the fuel control system of aero-engines, and their performance directly affects thrust regulation and power output precision. Due to the combustibility of the working medium in fuel systems and the lack of effective circulation filtration, the retention of micron-sized particles within the valve gap can lead to valve spool jamming, which is a critical reliability issue. This study, based on fractal theory and the liquid–solid two-phase flow model, proposes a parametric model for non-ideal surface valve gaps and analyzes the dynamics of particles subjected to drag, lift, and buoyant forces on rough surfaces. By numerically analyzing flow field models with different roughness levels and comparing them with an ideal smooth gap model, the migration characteristics of particles were studied. To verify the accuracy of the model, an upscaled experimental setup was built based on similarity theory, and PIV experiments were conducted for validation. Experimental results show that the particle release position and valve surface roughness significantly affect particle migration time. The weight of the release position on particle migration time is 63%, while the impact of valve surface roughness is 37%. In models with different roughness levels, the particle migration time increases more rapidly for roughness values greater than Ra0.4, while for values less than Ra0.4, the increase in migration time is slower. Furthermore, the study reveals that particle migration trajectories are independent of flow velocity, with velocity only affecting particle migration time. This research provides theoretical support for enhancing the reliability of fuel electro-hydraulic servo valves and offers a new perspective for the design of highly reliable hydraulic components. Full article

In hydropower tunnel systems, unlined pressurized tunnels in competent rock are commonly used for cost-effective construction. Incorporating pressurized sand traps at the downstream end of these tunnels can increase plant capacity and improve energy efficiency. The present work focuses on optimizing the performance of existing pressurized sand traps. Hydraulic scale models were developed and tested at the Hydraulic Laboratory of NTNU, Within the 960 MW Tonstad Hydropower Plant in southern Norway as a case study. This study compares 1:1 velocity/sediment scaling with Froude scaling through physical experiments, analyzing velocity profiles via Particle Image Velocimetry (PIV) and sediment trap efficiency. Results show that Froude scaling, combined with geometric sediment scaling, provides superior accuracy in trap efficiency scaling across varying factors. However, in many practical hydropower applications, the large scaling factor required for laboratory models results in very small model sediments, leading to cohesion limitations. In such cases, Froude scaling may not be feasible. The 1:1 scaling method provides a conservative alternative. Hence, for practical applications, 1:1 scaling may be more cost-effective and sufficient for designing pressurized sand traps. This study emphasizes the importance of accounting for unscaled parameters and flow phenomena in hydraulic model design. Full article

Background/Objectives: Given the increasing interest in the predictive role of inflammation in oncology, we aimed to assess the association between inflammatory factors (IFs) and the histopathological characteristics of bladder cancer (BC). Our objective was to correlate some of these IFs with BC progression and recurrence, identifying possible new diagnostic tools. Methods: We retrospectively analyzed 285 patients (79.8% male, 20.4% female; median age 73) who underwent transurethral resection of the bladder (TURB) between January 2016 and January 2022. The preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), pan-immune-inflammation value (PIV), systemic inflammation response index (SIRI), and standard clinical variables were collected one month before TURB and evaluated as predictors of recurrence and progression. Patients were stratified using the Youden Index and ROC analysis. Cox regression models were applied to identify independent predictors. Results: High-grade tumors were present in 74.6% of cases, and 34% were recurrent. Carcinoma in situ was found in 5%. After 72 months, 53% underwent radical cystectomy, and 13.7% died within 5 years. The optimal cutoffs were PLR 139, SIRI 1.12, PIV 248.49, NLR 2, SII 327. Smoking, primary MIBC, age, and lymph node status were significantly associated with recurrence. Elevated PLR correlated with recurrence and T2 progression (p = 0.004). Higher SIRI, PIV, and PLR levels were significantly associated with lymphovascular invasion and nodal metastasis (p < 0.05). PLR was linked to recurrence in tumors ≥ 3 cm post-BCG (p = 0.004); high SIRI predicted recurrence within 48 months (p = 0.05). Conclusions: High PLR and SIRI levels were associated with recurrence. Our findings support the emerging role of IFs in predicting BC outcomes and suggest their potential inclusion in future prognostic models. Full article

As the core components of geophysical dynamic system, oceans and atmospheres are dominated by the Coriolis force, which governs complex dynamic phenomena such as internal waves, gravity currents, vortices, and others involving multi-scale spatiotemporal coupling. Due to the limitations of in situ observations, large-scale rotating tanks have emerged as critical experimental platforms for simulating Earth’s rotational effects. This review summarizes recent advancements in rotating tank applications for studying oceanic flow phenomena, including mesoscale eddies, internal waves, Ekman flows, Rossby waves, gravity currents, and bottom boundary layer dynamics. Advanced measurement techniques, such as particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF), have enabled quantitative analyses of internal wave breaking-induced mixing and refined investigations of vortex merging dynamics. The findings demonstrate that large-scale rotating tanks provide a controllable experimental framework for unraveling the physical essence of geophysical fluid motions. Such laboratory experimental endeavors in a rotating tank can be applied to more extensive scientific topics, in which the rotation and stratification play important roles, offering crucial support for climate model parameterization and coupled ocean–land–atmosphere mechanisms. Full article

Background and Objectives: this study aimed to evaluate the prognostic significance of systemic immune-inflammatory markers, particularly the pan-immune-inflammation value (PIV) and systemic immune-inflammation Index (SII), in predicting overall survival among patients with hematologic malignancies. Materials and Methods: This retrospective cohort study included 300 patients diagnosed with various hematologic malignancies between January 2020 and January 2025 at the Department of Hematology, Faculty of Medicine, Mersin University. Baseline laboratory data, including neutrophil, lymphocyte, platelet, and monocyte counts, were collected to calculate SII, NLR, PLR, and PIV. Patients were stratified into high and low groups based on the median values of these markers. Overall survival was analyzed using Kaplan–Meier curves and Cox proportional hazards models, adjusted for age, sex, malignancy type, and disease stage. Results: High levels of PIV and SII were significantly associated with poorer overall survival. In univariate analysis, high PIV (HR: 2.35, 95% CI: 1.68–3.28, p < 0.001) and high SII (HR: 2.12, 95% CI: 1.53–2.95, p < 0.001) were strong predictors of mortality. After multivariate adjustment, PIV (adjusted HR: 2.14, 95% CI: 1.47–3.11, p < 0.001) and SII (adjusted HR: 1.88, 95% CI: 1.32–2.67, p = 0.001) remained independent prognostic factors. Subgroup analyses demonstrated that the predictive power of PIV and SII was consistent across different malignancy types, particularly in acute myeloid leukemia and multiple myeloma patients. Conclusions: Our findings indicated that systemic immune-inflammatory markers, particularly PIV and SII, are valuable prognostic tools in hematologic malignancies. These markers, derived from routine blood counts, offer a simple cost-effective means for improving risk stratification. Incorporating these indices into clinical practice could enhance individualized management strategies. Further prospective studies are warranted to validate these findings. Full article

The present article offers a detailed analysis of helium jet velocity and vorticity intensity distribution using the particle image velocimetry (PIV) technique. A gaseous fuel injector featuring an interchangeable tip was implemented. The test campaign involved the use of three nozzle patterns characterized by different orifices shape and orientations. The helium was injected into a constant volume chamber (CVC) and the delivery pressure varied, as well as that inside the chamber, in order to obtain pressure ratios (PRs) ranging from 2 to 20. The synchronization system was set to record two consecutive frames at different time-instants after the start of energizing (aSOE). Green light from a dual cavity Nd:YAG laser was used for illumination and a 4-megapixel PIV-camera for image capture. Vegetable oil particles were seeded into the chamber to trace the helium jet structure and cross-correlation methodology employed to measure their instantaneous displacements. The role of orifices size and orientations has been deeply scrutinized and related to the morphological outcomes. The least-oriented nozzle (first) exhibited the highest values of jet penetration and well-defined vortex structures. In contrast, the more the orifices are oriented, the wider the regions interacting with surrounding environment. Specifically, geometry with smaller orifice sizes (third) returned an overall absence of localized significant vortex structures. This deficiency is counterbalanced by a large distribution of small vortices that were observed to replace the main rings for each condition examined. Full article

It is important to understand which bacterial taxa are most abundant during SARS-CoV-2 infection and to promote mitigation strategies for conditions subsequent to infection. Nasopharyngeal swab samples were collected from patients infected with SARS-CoV-2 and their family contacts (uninfected and asymptomatic) during the outbreak of the P.1 variant of SARS-CoV-2 in Parintins, Amazonas–Brazil, in March 2021. The samples were investigated by a shotgun sequencing metagenomic approach using the NextSeq 500 Illumina® system. The samples were stratified according to the presence or absence of SARS-CoV-2, household group, sex, and age. Of the total of 63 individuals, 37 (58.73%) were positive for SARS-CoV-2 and 26 (41.27%) were negative for SARS-CoV-2 and other respiratory viruses (FLU, AdV, HBoV, HCoV, HMPV, RSV, PIV, HRV). The alpha diversity indexes Chao1, species observed, Simpson, and Inv Simpson demonstrated a significant difference (p < 0.05) in both the diversity of observed species and the abundance of some taxa between positive and negative individuals. We also observed an abundance of opportunists such as Klebsiella pneumoniae, Staphylococcus spp, and Shigella sonnei, previously associated with the severity of COVID-19. Our results suggest that SARS-CoV-2 infection causes changes in the microenvironment of the nasopharyngeal region, allowing greater proliferation of opportunistic bacteria and decreased abundance of commensal bacteria. Full article

Background and Objectives: Sarcopenia is frequently observed in cancer patients and is associated with short survival. In this study, the aim was to research the sarcopenia risk factors, the correlation of sarcopenia with inflammatory biomarkers, and the prognostic significance of sarcopenia and inflammation markers in patients with metastatic gastric cancer. Material and Method: The study included 177 patients diagnosed with metastatic gastric cancer attending Dokuz Eylül University Faculty of Medicine (DEUFM) Medical Oncology clinic from 2016 to 2022. The skeletal muscle area at L3 vertebral level was identified on abdominal computed tomography (CT) images, and the skeletal muscle index (SMI, cm²/m²) was calculated. Additionally, PLR, MLR, NLR, dNLR, SIRI, SII, PIV, PNI, CAR, and LAR were assessed among systemic inflammatory biomarkers. Cut-off values were determined with ROC curve analysis. Survival analyses were performed with the Kaplan–Meier method, and risk factors were investigated with Cox regression analysis. For all statistical analyses, p < 0.05 was accepted as significant. Results: Among patients, 71.8% were identified to have sarcopenia. Significant levels of difference were identified for median SIRI, NLR, MLR, PLR, SII, PNI, and dNLR values between patients with and without sarcopenia (p < 0.05). The sarcopenia risk was assessed between groups created according to the cut-off values for inflammation markers. Univariate regression analysis found that SIRI, PIV, NLR, MLR, PLR, SII, PNI, and dNLR were statistically significant (p < 0.05). Multivariate analysis identified SIRI and PNI as independent risk factors. For all patients, median overall survival was identified to be 12.4 ± 0.8 months (CI 95%, 10.8–13.9). For patients with sarcopenia, overall survival duration was 11.5 ± 0.8 months, while survival duration for patients without sarcopenia was 17.5 ± 4.6 months (p = 0.010). Elevation in the inflammatory biomarkers of SIRI, NLR, SII, LAR, and CAR and low PNI values appear to be associated with short survival (p < 0.05). Conclusions: In this study, sarcopenia was frequently observed in patients with metastatic gastric cancer and sarcopenia was associated with shorter survival. A significant correlation was observed between sarcopenia and inflammatory biomarkers, with SIRI and PNI identified to be independent risk factors for sarcopenia. Our study emphasizes the prognostic importance of sarcopenia and inflammatory markers for the management of patients with metastatic gastric cancer. Full article

In this study, a particle image velocimetry (PIV) system was used in a large circulating water tank to investigate the wake of a horizontal-axis tidal turbine model, focusing on minor blockage effects and scale influence. A wake map of the turbine was constructed based on PIV measurements, using velocity deficit, turbulence intensity (TI), and turbulence kinetic energy (TKE) as key indicators. The results showed that TKE developed later than TI, forming a plateau-like shape. This plateau was considered the decay region, with the transition and far-wake regions located before and after it, respectively. Additionally, the power law exponent of TI decreased from −0.731 in the decay region to −0.765 in the far wake, indicating a steeper decay further downstream. Overall, the wake map of the tidal stream turbine model exhibited similarities to that of a previously reported wind turbine model. Full article

Background: Inflammatory indices have been proposed as simple and routinely obtainable markers of systemic inflammation in cardiac disease. This study investigated whether the neutrophil-to-lymphocyte ratio (NLR), the monocyte-to-lymphocyte ratio (MLR), and the pan-immune inflammation value (PIV) serve as biomarkers for risk stratification and outcomes measures in patients with severe aortic stenosis (AS) following valve replacement (AVR). Methods: In this retrospective analysis (January 2017–June 2022), patients with AS underwent pre-procedural cardiovascular magnetic resonance (CMR) imaging and were assigned a treatment strategy by a multidisciplinary Heart Team: (1) transcatheter AVR, (2) surgical AVR, or (3) no valvular intervention. Kaplan–Meier estimates and regression analyses were used to demonstrate associations between the NLR, MLR, and PIV with myocardial fibrosis—assessed by late gadolinium enhancement (LGE) and extracellular volume (ECV) on CMR—and a combined endpoint of heart failure hospitalizations and all-cause mortality. Results: A total of 356 patients (median age: 80 years, 50% male) were followed for a median of 40 months, during which 162 (46%) reached the combined endpoint. Linear regression identified C-reactive protein, but not the presence of LGE or elevated ECV, as the only independent predictor of all three inflammatory indices (p for all <0.001). After multivariable adjustment for clinical (EuroSCORE II), laboratory (baseline N-terminal prohormone of brain natriuretic peptide [NT-proBNP] and C-reactive protein), and imaging parameters (AV mean pressure gradient, right ventricular ejection fraction, and ECV), the above-the-upper-quartile NLR (adjusted hazard ratio [aHR]: 1.45, 95%-confidence interval [CI]: 1.01–1.92, p = 0.042), MLR (aHR: 1.48, 95%-CI: 1.05–2.09, p = 0.025), and PIV (aHR: 1.56, 95%-CI: 1.11–2.21, p = 0.011) remained significantly associated with adverse outcomes. Following AVR, the median NLR (3.5 to 3.4) and PIV (460 to 376) showed a significant post-procedural decline compared to baseline (p ≤ 0.019 for both). Conclusions: Inflammatory indices are readily available biomarkers independently associated with adverse outcomes in severe AS following AVR. However, no significant relationship was observed between the NLR, MLR, PIV, and myocardial fibrosis on CMR. Full article