Search Results (2,452)

This research investigates the application of supercritical carbon dioxide (CO₂) within carbon capture, utilization, and storage (CCUS) technologies to enhance oil-well production efficiency and facilitate carbon storage, thereby promoting a low-carbon circular economy. We simulate the flow of supercritical CO₂ mixed with associated gas (flow rates 3–13 × 10⁴ Nm³/d) in a miniature venturi tube under high temperature and high-pressure conditions (30–50 MPa, 120–150 °C). Accurate fluid property calculations, essential for simulation fidelity, were performed using the R. Span and W. Wagner and GERG-2008 equations. A dual-parameter prediction model was developed based on the simulation data. However, actual measurements only provide fluid types and measurement data, such as pressure, temperature, and venturi differential pressure, to determine the liquid mass fraction (LMF) and total mass flow rate (m), presenting challenges due to complex nonlinear relationships. Traditional formula-fitting methods proved inadequate for these conditions. Consequently, we employed a Levenberg–Marquardt (LM) based neural network algorithm to address this issue. The LM optimizer excels in handling complex nonlinear problems with faster convergence, making it suitable for our small dataset. Through this approach, we formulated dual-parameter model equations to elucidate fluid flow factors, analyzing the impact of multiple parameters on the LMF and the discharge coefficient (C). The resulting model predicted dual parameters with a relative error for LMF of ±1% (Pc = 95.5%) and for m of ±1% (Pc = 95.5%), demonstrating high accuracy. This study highlights the potential of neural networks to predict the behavior of complex fluids with high supercritical CO₂ content, offering a novel solution where traditional methods fail. Full article

Revision total hip arthroplasty (rTHA) presents significant challenges, particularly in patients with severe acetabular bone defects. Traditional treatment options often fall short, leading to the emergence of custom-made 3D-printed acetabular implants. Accurate assessment of implant positioning is crucial for ensuring optimal postoperative outcomes and for providing feedback to the surgical team. This single-center, retrospective cohort study evaluates the accuracy of standard 2D radiographs versus 3D CT scans in assessing the positioning of these implants, aiming to determine if 2D imaging could serve as a viable alternative for the postoperative evaluation. We analyzed the implant positions of seven rTHA patients with severe acetabular defects (Paprosky ≥ Type IIIA) using an alignment technique that integrates postoperative 2D radiographs with preoperative CT plans. Two independent investigators, one inexperienced and one experienced, measured the positioning accuracy with both imaging modalities. Measurements included translational shifts from the preoperatively templated implant position in the craniocaudal (CC), lateromedial (LM), and ventrodorsal (VD) directions, as well as rotational differences in anteversion (AV) and inclination (INCL). The study demonstrated that 2D radiographs, when aligned with preoperative CT data, could accurately assess implant positions with precision nearly comparable to that of 3D CT scans. Observed deviations were 1.4 mm and 2.7 mm in CC and LM directions, respectively, and 3.6° in AV and 0.7° in INCL using 2D imaging, all within clinically acceptable ranges. For 3D CT assessments, mean interobserver variability was up to 0.9 mm for translational shifts and 1.4° for rotation, while for 2D alignment, observer differences were 1.4 mm and 3.2° for translation and rotation, respectively. Comparative analysis of mean results from both investigators, across all dimensions (CC, LM, AV, and INCL) for 2D and 3D matching, showed no significant differences. In conclusion, conventional anteroposterior 2D radiographs of the pelvis can sufficiently determine the positioning of custom-made acetabular implants in rTHA. This suggests that 2D radiography is a viable alternative to 3D CT scans, potentially enhancing the implementation and quality control of advanced implant technologies. Full article

Background: Although Total Ankle Arthroplasty (TAA) is primarily performed for post-traumatic ankle arthritis with joint disruption, anatomical landmarks for Joint Line (JL) level are typically preserved. However, severe Post-Traumatic Bone Loss (PTBL) or TAA revision may render some landmarks unidentifiable, challenging JL restoration. Methods: Patients undergoing customized TAA for severe PTBL or revision were enrolled. Custom-made implants, based on 3D CT scans, were designed to address bone defects and provide adequate bone support. Evaluated parameters, measured on bilateral ankle weight-bearing radiographs taken preoperatively and 6–8 months postoperatively, included JL Height Ratio (JLHR) and the distances from JL to the Lateral Malleolus apex (LM-JL), the posterior colliculus of the Medial Malleolus (MM-JL), and the Gissane Calcaneal Sulcus (CS-JL). Reproducibility and variability were assessed, and comparisons were made between radiological parameters measured at TAA and those at the contralateral ankle. Results: Thirteen patients were included. Intra- and interobserver reliability demonstrated excellent values. The least variability was observed in the LM-JL distance. Statistically significant correlations were found between CS-JL and MM-JL distances in the operated limb and between the CS-JL of the operated limb and the contralateral ankle. While TAA parameters did not show statistically significant differences compared with the contralateral ankle, a trend toward proximalization of the JL was noted. Conclusions: This study demonstrated good reproducibility of the analyzed parameters for evaluating JL in TAA among patients with severe PTBL or undergoing revision surgery. However, these parameters cannot be deemed fully reliable. Given their potential weaknesses, it is crucial to identify more reproducible values, preferably ratios. Full article

Estimating line impedance is relevant in transmission and distribution networks, in particular for planning and control. The large number of deployed PMUs has fostered the use of passive indirect methods based on network model identification. Electrified railways are a particular example of a distribution network, with moving highly dynamic loads, that would benefit from line impedance information for energy efficiency and optimization purposes, but for which many of the methods used in industrial applications cannot be directly applied. The estimate is carried out onboard using a passive method in a single-point perspective, suitable for implementation with energy metering onboard equipment. A comparison of two methods is carried out based on the non-linear least mean squares (LMS) optimization of an over-determined system of equations and on the auto- and cross-spectra of the pantograph voltage and current. The methods are checked preliminarily with a simulated synthetic network, showing good accuracy, within 5%. They are then applied to measured data over a 20 min run over the Swiss $16.7$ Hz railway network. Both methods are suitable to track network impedance in real time during the train journey; but with suitable checks on the significance of the pantograph current and on the values of the coefficient of determination, the LMS method seems more reliable with predictable behavior. Full article

Lung cancer is the leading cause of death among all the oncological diseases worldwide. This applies to both women and men; however, the incidence and mortality among women is on the rise. In 2020, lung cancer was responsible for 1.8 million deaths (18%). More than 90% of lung cancer cases and 77.1% of lung cancer deaths occur in countries with high and very high HDI (human development index) values. The aim of our study is to the present trends and most recent studies aimed at lung cancer screening. In the face of the persistently high mortality rate, conducting research aimed at extending already-implemented diagnostic algorithms and behavioural interventions focused on smoking cessation is recommended. Full article

To investigate the metabolomic mechanisms by which changes in cardiorespiratory fitness (CRF) levels affect metabolic syndrome (MetS) risk factors and to provide a theoretical basis for the improvement of body metabolism via CRF in people with MetS risk factors, a comparative blood metabolomics study of individuals with varying levels of CRF and varying degrees of risk factors for MetS was conducted. Methods: Ninety subjects between the ages of 40 and 45 were enrolled, and they were categorized into low-MetS (LM ≤ two items) and high MetS (HM > three items) groups, as well as low- and high-CRF (LC, HC) and LCLM, LCLM, LCHM, and HCHM groups. Plasma was taken from the early morning abdominal venous blood. LC-MS was conducted using untargeted metabolomics technology, and the data were statistically and graphically evaluated using SPSS26.0 and R language. Results: (1) There were eight common differential metabolites in the HC vs. LC group as follows: methionine (↓), γ-aminobutyric acid (↑), 2-oxoglutatic acid (↑), arginine (↑), serine (↑), cis-aconitic acid (↑), glutamine (↓), and valine (↓); the HM vs. LM group are contrast. (2) In the HCHM vs. LCLM group, trends were observed in 2-oxoglutatic acid (↑), arginine (↑), serine (↑), cis-aconitic acid (↑), glutamine (↓), and valine (↓). (3) CRF and MetS risk factors jointly affect biological metabolic pathways such as arginine biosynthesis, TCA cycle, cysteine and methionine metabolism, glycine, serine, and threonine metabolism, arginine and proline metabolism, and alanine, aspartate, and glutamate metabolism. Conclusion: The eight common differential metabolites can serve as potential biomarkers for distinguishing individuals with different CRF levels and varying degrees of MetS risk factors. Increasing CRF levels may potentially mitigate MetS risk factors, as higher CRF levels are associated with reduced MetS risk. Full article

The combination of no-till farming and green manure is key to nourishing the soil and increasing crop yields. However, it remains unclear how to enhance the efficiency of green manure under no-till conditions. We conducted a two-factor field trial of silage maize rotated with hairy vetch to test the effects of tillage methods and returning. Factor 1 is the type of tillage, which is divided into conventional ploughing and no-tillage; factor 2 is the different ways of returning hairy vetch as green manure, which were also compared: no return (NM), stubble return (H), mulching (HM), turnover (HR, for CT only), and live coverage (LM, for NT only). Our findings indicate that different methods of returning hairy vetch to the field will improve maize yield and quality. The best results were obtained in CT and NT in HM and LM, respectively. Specifically, HM resulted in the highest dry matter quality and yield, with improvements of 35.4% and 31.9% over NM under CT, respectively. It also demonstrated the best economic and net energy performance. However, other treatments had no significant effect on the beneficial utilization and return of nutrients. The LM improved yields under NT by boosting soil enzyme activity, promoting nitrogen transformation and accumulation, and increasing nitrogen use efficiency for better kernel development. Overall, NTLM is best at utilizing and distributing soil nutrients and increasing silage maize yield. This finding supports the eco-efficient cultivation approach in silage maize production in the region. Full article

Gallium (Ga)-based liquid metals (LMs), as an emerging functional material, stand out among many candidates due to their combination of fluidic and metallic attributes, and they have extensively attracted the attention of academic researchers. When fabricated into droplet form, these metals are imbued with many fantastic characteristics, such as a high specific surface area and self-healing properties. Additionally, Ga-based liquid metal droplets (LMDs) achieve higher response accuracy to external stimuli, satisfying the demands of many applications requiring micro-size and precise stimulus-responsivity. Herein, we focus on reviewing the properties of Ga-based LMs and their droplets, the fabrication strategies of metal droplets, their stimulus-response motion under different external fields, and their applications in microfluidic systems, biomedical applications, and micromachines. To further advance the development of responsive Ga-based LMDs, the future outlooks with key challenges related to their further applications are also presented here. Full article

Little is known about the changes in body composition (BC) in people with overweight or obesity. The aim of this study was to assess the differences in BC patterns in this population based on gender and age. A total of 2844 Italian adults of mixed gender and a body mass index (BMI) of ≥25 kg/m² underwent a BC assessment by means of dual-energy X-ray absorptiometry (DXA). The sample was categorized into three age groups: ‘young’ (20–39 years), ‘middle’ (40–59 years), and ‘older’ (60–80 years) adults, after being matched by body weight and BMI. Males showed higher total body fat percentage (BF%) and a lower total lean mass (LM), progressively from the young to the middle to the older age groups, while females showed similar values for these total compartments between the three age groups. However, in both genders, participants in the middle and older groups were more likely to have a higher trunk fat percentage by +1.23% to +4.21%, and lower appendicular lean mass (ALM) by −0.81 kg to −2.63 kg with respect to the young group, indicating expression of major central adiposity and sarcopenia. While our findings underscore the limitations of BMI to detect these differences between age groups, the identification of new tools suitable for this aim is greatly needed in this population. Moreover, further investigation that clarifies the impact of these differences in BC patterns between gender and age groups on health outcomes is also required. Full article

This study investigates the densification/granulation of activated sludge with poor settleability, treating real industrial wastewater from a tank truck cleaning company. The wastewater is low in nutrients, acidic in nature, and high and variable in chemical oxygen demand (COD, ranging from 2770 mg·L⁻¹ to 14,050 mg·L⁻¹). A microbial selection strategy was applied to promote slow-growing glycogen-accumulating microorganisms (GAO) by the implementation of an anaerobic feast/aerobic famine strategy in a sequencing batch reactor (SBR). After 60 to 70 days, the uptake of carbon during the anaerobic phase exceeded 80%, the sludge morphology improved, and the sludge volume index (SVI) dropped below 50 mL·g⁻¹. 16S rRNA gene sequencing showed the enrichment of the GAOs Defluviicoccus and Candidatus Competibacter. Stable sludge densification was maintained when using a constant organic loading rate (OLR) of 0.85 ± 0.05 gCOD·(L·d)⁻¹, but the sludge quality deteriorated when switching to a variable OLR. In view of the integration of densified/granular sludge in a membrane bioreactor configuration, the filtration properties of the densified SBR sludge were compared to the seed sludge from the full-scale plant. The densified sludge showed a significantly lower resistance due to pore blockage and a significantly higher sustainable flux (45 vs. 15 L·(m²·h)⁻¹). Full article

We propose a bandpass/bandstop-switchable frequency-selective metasurface (FSM) designed for high-speed vehicles that generate high temperatures during flight, based on a high-temperature-resistant dielectric substrate and liquid metal (LM). We fabricated a cavity structure by utilizing a high-temperature-resistant dielectric substrate to form a metal FSM element by introducing LM, enabling specific electromagnetic functions. The flow state of the LM can be controlled to achieve the switching of the FSM’s bandpass/bandstop performance. The bandstop characteristic has a resonance frequency of 6.1 GHz and the bandpass interval is 5.53–6.51 GHz. The bandpass characteristic has a resonance frequency of 5.41 GHz and the bandstop interval is 5.30–5.76 GHz, achieving a bandpass/bandstop switching range of 5.53–5.76 GHz. LM fluidity can aid in high-temperature heat dissipation. When the LM reaches a certain flow rate, the FSM structure’s average temperature can be reduced by an order of magnitude from a thousand to less than a hundred degrees. The FSM exhibits low RCS, with 22.35 dB and 36.79 dB reductions in bandstop and bandpass properties, respectively, compared with that of sheet metal. A prototype was developed and tested, validating the design of the FSM structure with high-temperature resistance, bandpass/bandstop switchability, and low RCS characteristics, and is expected to be applied in high-speed aircraft. Full article

This study explored the incidence of metaphorical virtual classrooms and interactive learning objects in the interaction of students in online mode. The main objective was to analyze how these digital tools, driven by a set of strategies to promote their use, affect the interaction of students in the virtual classroom system and their derived effects. To this end, the latest version of Moodle was implemented in conjunction with gamification plugins and interactive tools in the higher education institution used as a case study. The methodology consisted of data collection through ordinal instruments applied to the teachers and student performance metrics gathered using a plugin developed to extract accurate metrics of each student’s usage and performance through direct queries to the Moodle database and its processing through a neural network. This facilitated the collection of standardized data on the actual metrics of each virtual classroom at the end of the teaching of each subject from both the previous LMS and the newly implemented one. This data was then analyzed using advanced statistical techniques, including Mahalanobis distances, confirmatory factor analysis, and the Wilcoxon signed-rank test. These methods provided a compelling comparison between the old and new systems, revealing significant improvements in the metrics and factors evaluated. The results showed a significant improvement in teachers’ perceptions of the usability of the virtual classroom system and an increase in students’ academic performance, interaction, progress, and time spent learning in virtual contexts. These results provide solid empirical evidence of the added value of these educational tools as effective strategies for improving student interaction, performance, and motivation in online education. Full article

A novel five-surface phosphor-in-glass (FS-PiG) structure for high illumination and excellent color uniformity in large-view scale LEDs for sensor light source application is demonstrated. YAG phosphor (Y₃Al₅O₁₂:Ce³⁺) was uniformly mixed with ceramic and sintered at 680 °C to form a phosphor wafer. Sophisticated laser engraving was employed on the phosphor wafer to form saddle-shaped large-view scale FS-PiG LEDs. The performance of the FS-PiG LEDs exhibited an illumination of 401 lm, average color temperature (CCT) of 5488 K ± 110 K, and color coordinates (CIE) of (0.3179 ± 0.003, 0.3352 ± 0.003). In contrast to convention single-surface phosphor-in-glass (SS-PiG) LEDs, the performance exhibited an illumination of 380 lm, average CCT of 5830 K ± 758 K, and CIE of (0.3083 ± 0.07, 0.3172 ± 0.07). These indicated that the performance of the FS-PiG LEDs was higher than the SS-PiG LEDs for illumination, CCT, and CIE by 1.7, 7, and 23 times, respectively. Furthermore, the FS-PiG LEDs demonstrate a lower lumen loss of 2% and a reduced chromaticity shift of 5.4 × 10⁻³ under accelerated aging at 350 °C for 1008 h, owing to the high ceramic melting temperature of up to 510 °C. In this study, the proposed FS-PiG large-view scale LEDs with excellent optical performance and high reliability may be promising candidates to replace the conventional phosphor-in-organic silicone material used in high-power LEDs for the next generation of sensor light sources, display, and headlight applications. Full article

Directed enzyme prodrug therapy (DEPT) strategies show promise in mitigating chemotherapy side effects during cancer treatment. Among these, the use of immobilized enzymes on solid matrices as prodrug activating agents (IDEPT) presents a compelling delivery strategy, offering enhanced tumor targeting and reduced toxicity. Herein, we report a novel IDEPT strategy by employing a His-tagged Leishmania mexicana type I 2′-deoxyribosyltransferase (His-LmPDT) covalently attached to glutaraldehyde-activated magnetic iron oxide nanoparticles (MIONPs). Among the resulting derivatives, PDT-MIONP3 displayed the most favorable catalyst load/retained activity ratio, prompting its selection for further investigation. Substrate specificity studies demonstrated that PDT-MIONP3 effectively hydrolyzed a diverse array of 6-oxo and/or 6-amino purine 2′-deoxynucleosides, including 2-fluoro-2′-deoxyadenosine (dFAdo) and 6-methylpurine-2′-deoxyribose (d6MetPRib), both well-known prodrugs commonly used in DEPT. The biophysical characterization of both MIONPs and PDT-MIONPs was conducted by TEM, DLS, and single particle ICPMS techniques, showing an ideal nanosized range and a zeta potential value of −47.9 mV and −78.2 mV for MIONPs and PDT-MIONPs, respectively. The intracellular uptake of MIONPs and PDT-MIONPs was also determined by TEM and single particle ICPMS on HeLa cancer cell lines and NIH3T3 normal cell lines, showing a higher intracellular uptake in tumor cells. Finally, the selectivity of the PDT-MIONP/dFAdo IDEPT system was tested on HeLa cells (24 h, 10 µM dFAdo), resulting in a significant reduction in tumoral cell survival (11% of viability). Based on the experimental results, PDT-MIONP/dFAdo presents a novel and alternative IDEPT strategy, providing a promising avenue for cancer treatment. Full article

The problem of the insufficient accuracy performance of industrial robots in high-precision manufacturing is addressed in this paper. Firstly, a kinematic error model based on an M-DH model was presented. Secondly, a hybrid observability index O₆ was proposed to select the optimal poses for parameter identification. O₆ is the combination of O₁ and O₃. The optimal poses were obtained by using the IOOPS algorithm. Thirdly, the fitness function for parameter identification was established, and the Levenberg–Marquardt (LM) algorithm was applied for the accurate identification of kinematic parameter errors. Finally, several experiments were conducted to evaluate the performance of the proposed hybrid observability index O₆. The average position error and average attitude error of Staubli TX60 robot were reduced by 89% and 49%. The results show that the proposed hybrid observability index O₆ has great stability and effectiveness for robot calibration. Full article