Search Results (3,489)

Disposable absorbent hygiene products (AHPs) contain plastics that are challenging to recycle and not biodegradable, making a significant contribution to landfill. Decreasing the nonbiodegradable mass of products could reduce this burden. Despite this, public data on how AHP design and material selection relate to performance is limited. In this work, fifteen commercial AHPs were characterised using dimensional measurement, infrared spectroscopy, and imaging. Simulated urination, air permeability, and moisture management testing were used to assess expected leakage and user comfort. Sustainable materials currently in use were identified, and their performance compared to typical plastics, informing opportunities to replace or reduce nonbiodegradable materials. Polybutylene adipate terephthalate-based leakproof layers replaced polyolefins. Commercial alternatives to polyacrylate superabsorbent polymers (SAPs), with comparable absorption, were not seen. Although absorbency correlated with the mass of absorbants, SAPs reduced surface moisture after absorption and are known for high absorption capacity under pressure, preventing rewetting. Channels and side guards were observed to prevent side leakage and guide fluid distribution, potentially reducing the need for nonbiodegradable nonwoven and absorbant content by promoting efficient use of the full product mass. While synthetic nonwovens typically outperformed cellulosics, apertured and layered nonwovens were associated with improved moisture transport; polylactic acid rivalled typical thermoplastics as a bio-derived, compostable alternative. Although the need for biopolymer-based SAPs and foams remains, it is hoped that these findings will guide AHP design and promote research in sustainable materials. Full article

Background/Objectives: Volatile organic compounds (VOCs) have emerged as promising non-invasive biomarkers for assessing metabolic and reproductive health. In the context of assisted reproductive techniques (ARTs), the volatilomic composition of follicular fluid (FF) may reflect the biochemical environment surrounding the oocyte, influencing fertilization success and embryo development. This study aimed to characterize the volatilomic profile of FF in women undergoing ARTs and to explore associations between specific VOCs and female fertilization-related parameters (FFRPs). Methods: A total of 54 Caucasian women aged 19–39 years, enrolled between October 2015 and July 2019, were recruited at the Assisted Reproduction Laboratory of the Local Health Unit of Cova da Beira, Covilhã. FF samples were analyzed via gas chromatography–mass spectrometry (GC–MS) in scan mode, identifying 136 VOCs, of which 72 were selected based on prevalence. Sixteen FFRPs were evaluated, including age, body mass index (BMI), smoking habits, infertility factor, oocyte yield, embryo quality, β-hCG levels, country of birth, and reproductive history. Associations between VOCs and FFRPs were assessed using the Chi-square (χ²) test. Results: Significant correlations (p ≤ 0.05) were identified between 45 VOCs and 11 FFRPs. The detected compounds comprised alkanes, siloxanes, aromatics, alcohols, ketones, aldehydes, carboxylic acids and esters, fatty acid derivatives, epoxides, acrylates, nitriles, and sterols. Several VOCs were associated with more than one FFRP, indicating overlapping metabolic pathways that may influence reproductive performance. Conclusions: The volatilomic profile of FF demonstrates significant variability linked to individual reproductive and metabolic factors. VOC analysis may provide novel insights into follicular physiology, representing a promising approach for identifying potential biomarkers of infertility and ART outcomes. Full article

Strategies to suppress methanogenesis must preserve the functional integrity of the rumen microbial ecosystem. Essential oils (EOs) have emerged as promising modulators of rumen microbial function, though their responses vary widely with chemical structure and inclusion level. This study evaluated the efficacy of selected EOs using detailed in vitro fermentation assays. Nine EOs—cinnamon, lavender, garlic (GAR), lemongrass (LEG), peppermint (PPM), eucalyptus, coriander, oregano, and ginger (GIN)—were evaluated for their effects on rumen fermentation and methane (CH₄) production using a 24 h in vitro batch culture system. Eight EOs were tested at two doses (Low and High) specific to each EO, while GIN was evaluated at a single dose. All treatments were incubated in a rumen fluid–buffer mix (1:1 for fermentation parameters and 1:4 for gas and CH₄ measurements) with a 55:45 forage-to-concentrate substrate (pH 6.9). Overall treatment effects were significant for all measured fermentation parameters (p < 0.01). Most treatments reduced total gas production, CH₄ emissions, and CH₄/total gas ratios compared with the control (p < 0.05), although several responses were dose-dependent or directly divergent. Essential oils showed clear, composition-dependent responses: non-terpenoid EOs produced the strongest but also the most variable antimethanogenic effects, with GAR, particularly at the lower dose, consistently achieving the greatest CH₄ inhibition while maintaining a favorable fermentation pattern. Conversely, terpenoid-based EOs induced moderate, dose-responsive CH₄ reductions with minimal effects on overall fermentation. At the higher dose, PPM suppressed CH₄ without altering major volatile fatty acid (VFA) patterns aside from increases in valerate and branched-chain VFA, whereas LEG reduced CH₄ only when accompanied by marked fermentation depression. Monensin validated its role as an effective positive control. Overall, GAR, characterized by sulfur-based bioactives, emerged as the most effective candidate for CH₄ mitigation under the tested in vitro conditions, highlighting the importance of chemical composition and inclusion level in determining efficacy and reinforcing the need for in vivo validation. Full article

The rapid evolution of coronaviruses (CoVs) requires researchers to develop specific yet broad-spectrum detection methods to monitor their constant genomic changes. The goal of the present study was to establish a current pan-coronavirus RT-PCR system capable of detecting a wide variety of CoVs and useful for the investigation of virus diversity and host spectrum. For optimization, one-step and two-step nested RT-PCRs with three RT enzymes were examined, amplifying a ~600 bp long product of the RNA-dependent RNA polymerase. As templates, the in vitro transcribed RNA of ten pathogenic CoVs (SARS-CoV, SARS-CoV-2, NL-63, OC43, feline CoV, porcine epidemic diarrhea virus or PEDV, transmissible gastroenteritis virus or TGEV, canine CoV, bat CoV, and infectious bronchitis virus) were applied instead of the often-used DNA standards. A limit of detection of 5–50 copies/reaction was achieved with a random hexamer-primed two-step RT-PCR and a touchdown cycling profile, representing a lower detection limit and higher specificity compared to previously published primer sets. Swine origin pooled samples (n = 121), collected from apparently healthy herds in Hungary, were tested with the novel RT-PCR system. Sequences of porcine respiratory CoV/TGEV and porcine hemagglutinating encephalomyelitis virus were identified in 24 oral fluid and nasal swab pools, demonstrating the circulation of these viruses in this country, as well as the suitability of the new PCR for their detection. The results highlighted the importance of adequate RT enzyme selection and the use of RNase inhibitors in sample preparation and conservation. Full article

Background/Objectives: SA001, a mofetil-ester prodrug of rebamipide, was developed to enhance gastrointestinal absorption and systemic exposure, which was confirmed in a prior Phase 1 study. Given the limited efficacy of current symptomatic therapies for primary Sjögren’s syndrome (pSS), this trial aimed to assess whether the improved bioavailability of SA001 could translate into clinical benefits. Methods: This multicenter, randomized, double-blind, placebo-controlled Phase 2a study enrolled adults who met the 2016 ACR–EULAR criteria for pSS. The participants were randomly assigned to one of four groups: SA001 at 360, 720, or 1080 mg/day (administered twice daily for 8 weeks) or placebo. Exploratory ocular assessments included tear break-up time, ocular surface staining, the Schirmer test, and the Standard Patient Evaluation of Eye Dryness. Oral endpoints included unstimulated whole salivary flow and the Xerostomia Inventory. Anti-SSA(Ro) antibodies were assessed both quantitatively and qualitatively. Safety evaluations comprised adverse events (AEs), ophthalmic examinations, laboratory tests, and vital signs. The efficacy outcomes were exploratory, and this study was not powered to formally test efficacy hypotheses. Results: Twenty-eight women (mean age 58.54 ± 9.29 years; range 41–75 years) were enrolled in this study and randomly assigned to one of the study groups. SA001 showed no statistically significant improvements versus placebo in ocular or oral endpoints, and no consistent dose–response relationship was observed. The anti-SSA(Ro) findings did not differ meaningfully across the groups. SA001 was generally well-tolerated, with infrequent, mostly mild-to-moderate AEs; however, one serious AE occurred in the placebo group. No clinically relevant ophthalmic or laboratory safety signals were detected. Conclusions: Despite the fact that markedly increased systemic exposure has been demonstrated previously, SA001 did not improve the dryness outcomes in pSS. These findings suggest that systemic exposure alone may be insufficient in established glandular disease and highlight the need for tissue-exposure-driven strategies and biomarker-informed patient selection in future studies. Predefined primary efficacy endpoints and objective, gland-proximal measures of target engagement (e.g., standardized salivary gland ultrasonography and salivary or tear fluid biomarker assessments) may help to better interpret local pharmacodynamic activity and the likelihood of a clinically meaningful benefit. Full article

Aiming at the wind-blown snow disasters plaguing tunnel portals along the China-Tajikistan Highway Phase II Project, this study optimizes the protective parameters of wind deflectors through numerical simulation to improve the disaster prevention efficiency of tunnel portals in alpine mountainous areas. Three core control parameters of wind deflectors, namely horizontal distance from the tunnel portal (L), plate inclination angle (β), and top installation height (h), were selected as the research objects. Single-factor numerical simulation scenarios were designed for each parameter, and an L9(3³) orthogonal test was further adopted to formulate 9 groups of multi-parameter combination scenarios, with the snow phase volume fraction at 35 m on the leeward side of the tunnel portal set as the core evaluation index. A computational fluid dynamics (CFD) model was established to systematically investigate the influence laws of each parameter on the wind field structure and snow drift deposition characteristics at tunnel portals and clarify the flow field response rules under different parameter configurations. Single-factor simulation results show that the wind deflector exerts distinct regulatory effects on the wind-snow flow field with different parameter settings: when L = 6 m, the disturbance zone of the wind deflector precisely covers the main wind flow development area in front of the tunnel portal, which effectively lifts the main incoming flow path, compresses the recirculation zone (length reduced from 45.8 m to 22.3 m), and reduces the settlement of snow particles, achieving the optimal comprehensive prevention effect; when β = 60°, the leeward wind speed at the tunnel portal is significantly increased to 10–12 m/s (from below 10 m/s), which effectively promotes the transport of snow particles and mitigates the accumulation risk, being the optimal inclination angle; when h = 2 m, the wind speed on both the windward and leeward sides of the tunnel portal is significantly improved, and the snow accumulation risk at the portal reaches the minimum. Orthogonal test results further quantify the influence degree of each parameter on the snow prevention effect, revealing that the horizontal distance from the tunnel portal is the most significant influencing factor. The optimal parameter combination of the wind deflector is determined as L = 6 m, β = 60°, and h = 2 m. Under this optimal combination, the snow phase volume fraction at 35 m on the leeward side of the tunnel portal is 0.0505, a 12.3% reduction compared with the non-deflector condition; the high-concentration snow accumulation zone is shifted 25 m leeward, and the high-value snow phase volume fraction area (>0.06) disappears completely, which can effectively alleviate the adverse impact of wind-blown snow disasters on the normal operation of tunnel portals. The research results reveal the regulation mechanism of wind deflector parameters on the wind-snow flow field at alpine tunnel portals and determine the optimal protective parameter combination, which can provide important theoretical reference and technical support for the prevention and control of wind-blown snow disasters at tunnel portals in similar alpine mountainous areas. Full article

Low-permeability waterflooding reservoirs face numerous challenges, including low productivity per well, inadequate formation pressure maintenance, poor waterflood response, and low water injection utilization efficiency. Illustrated by Bai 153 Block in the Changqing Oilfield, the primary concern has shifted in recent years from fracture water breakthrough to formation blockages. Currently, low-yield wells (≤0.5 t) constitute a significant proportion (27.5%), with a recovery factor of only 0.41%. The effectiveness of stimulation treatments is influenced by reservoir properties, treatment types, process parameters, and production performance. Selecting candidate wells requires collecting and analyzing data such as individual well block characteristics. Evaluating treatment effectiveness involves substantial effort and complexity. Early fracturing treatments exhibited significant variations in effectiveness, and the primary controlling factors influencing fracturing success remained unclear. This paper proposes a big data analysis-based method for evaluating stimulation effectiveness in low-permeability waterflooding reservoirs. Utilizing preprocessed geological, construction, and production data from the target block, an integrated application of the Random Forest algorithm and Recursive Feature Elimination ranks the importance of factors affecting treatments and identifies the block’s main controlling factors. Using these factors as target parameters, a multivariate quantitative evaluation model for fracturing effectiveness is established. This model employs the Pearson correlation coefficient method, Recursive Feature Elimination, and the Random Forest algorithm. Results from the quantitative model indicate that the primary main controlling factors that significantly affect post-fracturing oil increment are production parameters, geological parameters such as vertical thickness, fracture pressure, and oil saturation; engineering parameters such as sand ratio, blowout volume, and fracturing method; and production parameters such as pre-measure cumulative fluid production, production months, and pre-measure cumulative oil production, which are most closely related to post-fracturing oil increment. These parameters show the strongest correlation with incremental oil production. The constructed quantitative model demonstrates a linear correlation rate exceeding 85% between predicted fracturing stimulation and actual well test production, verifying its validity. This approach provides a novel method and theoretical foundation for the post-evaluation of oil increment effectiveness from stimulation treatments in low-permeability waterflooding reservoirs. Full article

Characterization of propeller blade vibrations is essential to ensure aerodynamic performance, minimize noise emissions, and maintain structural integrity in aerospace and unmanned aerial vehicle applications. Conventional high-fidelity finite-element and fluid–structure simulations yield precise modal predictions but incur prohibitive computational costs, limiting rapid design exploration. This paper introduces a data-driven surrogate modeling framework based on a feedforward neural network to predict natural vibration frequencies of propeller blades with high accuracy and a dramatically reduced runtime. A dataset of 1364 airfoil geometries was parameterized, meshed, and analyzed in ANSYS 2024 R2 across a range of rotational speeds and boundary conditions to generate modal responses. A TensorFlow/Keras model was trained and optimized via randomized search cross-validation over network depth, neuron counts, learning rate, batch size, and optimizer selection. The resulting surrogate achieves $R^2>0.90$ and $NRMSE<0.08$ for the second and higher-order modes, while reducing prediction time by several orders of magnitude compared to full finite-element workflows. The proposed approach seamlessly integrates with CAD/CAE pipelines and supports rapid, iterative optimization and real-time decision support in propeller design. Full article

Passive micromixers can be used in a wide range of chemical applications for reagent preparation as well as chemical analysis. To investigate a micromixer with high performance under various Re conditions, based on the research of previous scientists, we hereby parameterize three influential factors on the structural design of the micromixer. In this study, we chose five distinct level values from a set of three influential factors of the micromixer, based on the results of a one-way impact analysis to ascertain their degree of influence. For five different Re cases, the Taguchi orthogonal test was performed using the selected five-level values, the fluid mixing efficiency was examined numerically, and we used the orthogonal table L₂₅5⁶. Finally, a set of optimization parameters was selected. An optimized micromixer structural model with high mixing efficiency under different Re conditions has been achieved. The degree of stirring of the optimized micromixer and the comparison curves before and after the optimization were also analyzed. We have also manufactured and tested the micromixer of this design. The simulation results show that the mixing efficiency of “the After Optimized Y-shaped channel Koch fractal Cesàro construction” micromixer (AOYKC) designs in this paper is increased by 15.99%, 21.19%, 19.34%, 11.41%, and 0.04% at Re = 0.1, 1, 10, 20, and 100. Full article

Multiphase flow in porous media is ubiquitous in physical processes, yet modeling it consistently remains difficult, and sometimes it can be coupled with solid-phase decomposition and phase change, such as in hydrate dissociation or internal erosion processes. Recent code comparison studies have highlighted this difficulty, revealing clear inconsistencies in numerical results across different research groups for the same benchmark problem. This paper presents a new, reliable benchmark test and a hybrid explicit-implicit finite element method adaptable to various scenarios. In our mathematical framework, the solid decomposition is described by a rate equation for porosity that depends on the fluid pressure, and the phase change is modeled via mass source terms. The hybrid explicit-implicit finite element method features a novel three-stage updating strategy, which incorporates an artificial diffusion term and carefully selects the transport equation for the final saturation update. Validation results demonstrate that our proposed method achieves substantial agreement with those of the fully implicit finite volume method, confirming its reliability. Furthermore, our analysis confirms that the saturation update must use the transport equation of the incompressible fluid phase, and that the artificial diffusion term is critical for capturing physically correct saturation profiles, even when advection is not dominant. Overall, this work provides a consistent and effective tool for simulating complex multiphase flow scenarios and serves as a valuable complement to future benchmark studies. Full article

Accurate measurement of wall shear stress (WSS) is essential for both fundamental and applied fluid dynamics, where it governs boundary-layer behavior, drag generation, and the performance of flow-control systems. Yet, existing WSS sensing methods remain limited by low spatial resolution, complex instrumentation, or the need for user-dependent calibration. This work introduces a method based on artificial intelligence (AI) and Oil-Film Interferometry, referred to as AI-OFI, that transforms a classical optical technique into an automated and sensor-like platform for local WSS detection. The method combines the non-intrusive precision of Oil-Film Interferometry with modern deep-learning tools to achieve fast and fully autonomous data interpretation. Interference patterns generated by a thinning oil film are first segmented in real time using a YOLO-based object detection network and subsequently analyzed through a modified VGG16 regression model to estimate the local film thickness and the corresponding WSS. A smart interrogation-window selection algorithm, based on 2D Fourier analysis, ensures robust fringe detection under varying illumination and oil distribution conditions. The AI-OFI system was validated in the high-Reynolds-number Long Pipe Facility at the Centre for International Cooperation in Long Pipe Experiments (CICLoPE), showing excellent agreement with reference pressure-drop measurements and conventional OFI, with an average deviation below 5%. The proposed framework enables reliable, real-time, and operator-independent wall shear stress sensing, representing a significant step toward next-generation optical sensors for aerodynamic and industrial flow applications. Full article

The fate of a selection of linear and cyclic silicone oil formulations in heavy-duty fluid dampers is studied from molecular dynamics simulations. Mimicking cyclic agitation to all-atom simulation models, we elaborate oscillatory compression/decompression runs that feature degradation reactions within only hundreds of loading cycles. This enables the assessment of chain scission, reassembly and cyclization mechanisms from ns-scale molecular dynamics simulations. Using analogous testing scenarios, we compare the degradation reactions of linear and cyclic silicone chains and demonstrate the importance of silicone ring formation. In turn, cyclic silicone moieties show relative persistence in our compression/decompression runs. We conclude that long-term degradation finally leads to a manifold of cyclic silicone molecules, featuring rings of up to tens of monomeric units. The underlying molecules are not inert to Si-O bond cleavage and reformation, but feature reactivity in terms of the fusion of small to large rings and vice versa. Full article

Between 2015 and 2022, we evaluated a novel broad-range (BR) 16S PCR rDNA PCR/Sanger sequencing assay to improve diagnosis of invasive infections in culture-negative specimens. Using dual-priming oligonucleotides (DPO), this assay analyzed ribosomal DNA from sterile fluids or tissues. A total of 762 specimens were analyzed from 661 patients: 61% had negative cultures and BR 16S PCR tests; 35% had negative cultures but positive BR 16S PCR tests; and only 4% had negative cultures with indeterminate BR 16S PCR results. After resolution of indeterminate BR 16S PCR results (i.e., 29 negative, 1 false-positive, and 1 positive) the assay showed a sensitivity of 98.26% (95% CI = 96.00–99.43%), specificity of 99.79% (95% CI: 99.82–99.99%), positive predictive value of 99.65% (95% CI: 97.56–99.95%), negative predictive value of 98.94% (95% CI: 97.51–99.55%), and accuracy of 99.21% (95% CI: 98.28–99.71%) for a disease prevalence of 38.10% (95% CI: 34.62–41.66%). Gram stain purulence predicted the BR 16S PCR result better (69.4%) than organisms (24.6%), but the latter had a higher PPV (78.5%). Increased peripheral WBC (86.1%) or CRP (71.8%) predicted positive BR 16S PCR results. Our DPO BR 16S PCR assay improved pathogen detection over culture and minimized contamination. Broad range 16S rDNA PCR/sequencing (BR 16S PCR) is an important diagnostic technique in cases with invasive infection due to fastidious or uncultivatable pathogens. However, appropriate case selection, the quality of clinical specimen, and the specific assay primers affect its performance. Our novel BR 16S PCR assay uses unique dual-priming oligonucleotides (DPO) primers and fast protocols for rapid, optimal detection of bacterial pathogens, while minimizing contamination. Fast BR 16S PCR assay reports occurred within 24–48 h. BR 16S PCR and culture analyzed a diverse range of clinical specimens from patients with invasive infections. BR 16S PCR demonstrated a high performance for accurately detecting pathogens, ruling out infections, and minimizing contamination. BR 16S PCR detection of a pathogen allowed the appropriate clinical management of one-third of patients in this cohort. BR 16S PCR is an essential tool for the clinical management of patients with invasive infection when primary cultures are negative or contaminated. Full article

Cardiogenic pulmonary edema (CPE) is a life-threatening manifestation of acute heart failure characterized by rapid accumulation of fluid in the interstitial and alveolar spaces, leading to severe dyspnea, hypoxemia, and respiratory failure. The condition arises from elevated left-sided filling pressures that increase pulmonary capillary hydrostatic pressure, disrupt alveolo-capillary barrier integrity, and impair gas exchange. Neurohormonal activation further perpetuates congestion and increases myocardial workload, creating a vicious cycle of hemodynamic overload and respiratory compromise. Respiratory support is a cornerstone of management in CPE, aimed at stabilizing oxygenation, reducing the work of breathing, and facilitating ventricular unloading while definitive therapies, such as diuretics, vasodilators, inotropes, or mechanical circulatory support (MCS), address the underlying cause. Among available modalities, non-invasive ventilation (NIV) with continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP) has the strongest evidence base in moderate-to-severe CPE, consistently reducing the need for intubation and providing rapid relief of dyspnea. High-flow nasal cannula (HFNC) represents an emerging alternative in patients with moderate hypoxemia or intolerance to mask ventilation, and should be considered an adjunctive option in selected patients with less severe disease or NIV intolerance, although its efficacy in severe presentations remains uncertain. Invasive mechanical ventilation is reserved for refractory cases, while extracorporeal membrane oxygenation (ECMO) and other advanced circulatory support modalities may be necessary in cardiogenic shock. Integration of respiratory strategies with hemodynamic optimization is essential, as positive pressure ventilation favorably modulates preload and afterload, synergizing with pharmacological unloading. Future directions include personalization of ventilatory strategies using advanced monitoring, novel interfaces to improve tolerability, and earlier integration of MCS. In summary, respiratory support in CPE is both a bridge and a decisive therapeutic intervention, interrupting the cycle of hypoxemia and hemodynamic deterioration. A multidisciplinary, individualized approach remains central to improving outcomes in this high-risk population. Full article

The flow around circular cylinders is a classic problem in fluid mechanics with significant implications for offshore engineering. While extensive numerical and experimental research has focused on the subcritical and critical Reynolds regimes, the supercritical and postcritical regimes remain challenging and relatively unexplored, primarily due to the complex nature of turbulence and the high computational requirements. In this study, we perform three-dimensional detached eddy simulations using the finite volume method in OpenFOAM v1906, employing Menter’s k-$\omega$ SST turbulence model, to systematically investigate the flow past an infinitely long smooth cylinder from the subcritical through the postcritical regimes. The numerical setup ensures accurate near-wall resolution and reliable representation of unsteady flow features. We present a detailed analysis of vortex shedding patterns, wake evolution, and statistical properties of lift and drag coefficients for selected Reynolds numbers representative of each regime. The simulation results are benchmarked against experimental data from the literature, demonstrating good agreement for Strouhal number and mean drag. Special emphasis is placed on the evolution of wake topology and force coefficients as the flow transitions from laminar to fully turbulent conditions. The findings contribute to the limited numerical literature on flow around circular cylinders across subcritical, critical, supercritical, and postcritical Reynolds number regimes, providing insights that are fundamentally relevant to the broader scope of understanding vortex shedding phenomena. Full article