Search Results (6,078)

The global atmospheric concentration of carbon dioxide (CO₂) has exceeded 420 ppm. Adsorption-based carbon capture technologies, offer energy-efficient, sustainable solutions. Relying on classical adsorption models like Langmuir to predict CO₂ uptake presents limitations due to the need for case-specific parameter fitting. To address this, the present study introduces a universal machine learning (ML) framework using multiple algorithms—Generalized Linear Model (GLM), Feed-forward Multilayer Perceptron (DL), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosted Trees (GBT)—to reliably predict CO₂ adsorption capacities across diverse zeolite structures and conditions. By compiling over 5700 experimentally measured adsorption data points from 71 independent studies, this approach systematically incorporates critical factors including pore size, Si/Al ratio, cation type, temperature, and pressure. Rigorous Cross-Validation confirmed superior performance of the GBT model (R² = 0.936, RMSE = 0.806 mmol/g), outperforming other ML models and providing comparable performance with classical Langmuir model predictions without separate parameter calibration. Feature importance analysis identified pressure, Si/Al ratio, and cation type as dominant influences on adsorption performance. Overall, this ML-driven methodology demonstrates substantial promise for accelerating material discovery, optimization, and practical deployment of zeolite-based CO₂ capture technologies. Full article

Studying nonlinear oscillations in mechanical systems is fundamental to understanding complex dynamic behavior in engineering applications. While classical analytical methods remain valuable for systems with limited complexity, they become increasingly inadequate when nonlinearities are strong and geometrically induced, as in the case of large-amplitude oscillations. This paper presents a combined numerical and experimental investigation of a mechanical system composed of two coupled pendulums, exhibiting significant nonlinear behavior due to elastic deformation throughout their motion. A mathematical model of the system was developed using the MatLab/Simulink ver.6.1 environment, considering gravitational, inertial, and nonlinear elastic restoring forces. One of the major challenges in accurately modeling such systems is accurately representing damping, particularly in the absence of dedicated dampers. In this work, damping coefficients were experimentally identified through decrement measurements and incorporated into the simulation model to improve predictive accuracy. The simulation outputs, including angular displacements, velocities, accelerations, and phase trajectories over time, were validated against experimental results obtained via high-precision inertial sensors. The comparison shows a strong correlation between numerical and experimental data, with minimal relative errors in amplitude and frequency. This research represents the first stage of a broader study aimed at analyzing forced and parametrically excited oscillations. Beyond validating the model, the study contributes to the design of a robust experimental framework suitable for further exploration of nonlinear dynamics. The findings have practical implications for the development and control of mechanical systems subject to dynamic loads, with potential applications in automation, vibration analysis, and system diagnostics. Full article

The coffee-ring effect, while harnessed in diverse fields such as biosensing and printing, poses challenges for achieving uniform particle deposition. Controlling this phenomenon is thus essential for precision patterning. This study proposes a novel method to regulate coffee-ring formation by tuning surface wettability via integrated nanoporous and hexagonal microstructures. Four distinct surface types were fabricated using UV nanoimprint lithography: planar, porous planar, hexagonal wall, and porous hexagonal wall. The evaporation behavior of colloidal droplets and subsequent particle aggregation were analyzed through contact angle measurements and confocal microscopy. Results demonstrated that nanoscale porosity significantly increased surface wettability and accelerated evaporation, while the hexagonal pattern enhanced droplet stability and suppressed contact line movement. The porous hexagonal surface, in particular, enabled the formation of connected dual-ring patterns with higher particle accumulation near the contact edge. This synergistic design facilitated both stable evaporation and improved localization of particles. The findings provide a quantitative basis for applying patterned porous surfaces in evaporation-driven platforms, with implications for enhanced sensitivity and reproducibility in surface-enhanced Raman scattering (SERS) and other biosensing applications. Full article

This paper presents a structured and experimentally validated approach to the parameter identification, modeling, and real-time speed control of a brushless DC (BLDC) motor. Electrical parameters, including resistance and inductance, were measured through DC and AC testing under controlled conditions, respectively, while mechanical and electromagnetic parameters such as the back electromotive force (EMF) constant and rotor inertia were determined experimentally using an AVL dynamometer. The back EMF was obtained by operating the motor as a generator under varying speeds, and inertia was identified using a deceleration method based on the relationship between angular acceleration and torque. The identified parameters were used to construct a transfer function model of the motor, which was implemented in MATLAB/Simulink R2024b and validated against real-time experimental data using sinusoidal and exponential input signals. The comparison between simulated and measured speed responses showed strong agreement, confirming the accuracy of the model. A proportional–integral (PI) controller was developed and implemented for speed regulation, using a low-cost National Instruments (NI) USB-6009 data acquisition (DAQ) and a Kelly controller. A first-order low-pass filter was integrated into the control loop to suppress high-frequency disturbances and improve transient performance. Experimental tests using a stepwise reference speed profile demonstrated accurate tracking, minimal overshoot, and robust operation. Although the modeling and control techniques applied are well known, the novelty of this work lies in its integration of experimental parameter identification, real-time validation, and practical hardware implementation within a unified and replicable framework. This approach provides a solid foundation for further studies involving more advanced or adaptive control strategies for BLDC motors. Full article

In response to increasing sustainability demands, the packaging industry is shifting toward paper-based alternatives to replace polymer packaging. However, achieving complex, three-dimensional geometries comparable to plastics remains challenging due to the limited stretchability of paper. This study investigates advanced preconditioning techniques to enhance the formability of paper materials for deep-draw packaging applications. A custom-built test rig was developed at Syntegon Technology GmbH to systematically evaluate the effects of ultrasound-assisted moistening and segmented radiative heating. Under optimized conditions, 2.67 s moistening, 70.00 °C punch temperature, and 2999 W radiation power, maximum stretchability increased from 13.00% to 26.93%. The results confirm the effectiveness of ultrasound in accelerating moisture uptake and radiation heating in achieving uniform thermal distribution across the paper substrate. Although prototype constraints, such as the absence of inline conditioning and real-time measurement, limit process stability and scalability, the findings provide a strong foundation for developing industrial 3D paper forming processes that support sustainable packaging innovation. Full article

Unbalanced accelerations occurring during tram travel have a significant impact on passenger comfort and safety, as well as on the rate of wear and tear on infrastructure and rolling stock. Ideally, these dynamic forces should be monitored continuously in real-time; however, traditional systems require high-precision accelerometers and proprietary software—investments often beyond the reach of municipally funded tram operators. To this end, as part of the research project “Accelerometer Measurements in Rail Passenger Transport Vehicles”, pilot measurement campaigns were conducted in Poland on tram lines in Gdańsk, Toruń, Bydgoszcz, and Olsztyn. Off-the-shelf smartphones equipped with MEMS accelerometers and GPS modules, running the Physics Toolbox Sensor Suite Pro app, were used. Although the research employs widely known methods, this paper addresses part of the gap in affordable real-time monitoring by demonstrating that, in the future, equipment equipped solely with consumer-grade MEMS accelerometers can deliver sufficiently accurate data in applications where high precision is not critical. This paper presents an analysis of a subset of results from the Gdańsk tram network. Lateral (x) and vertical (z) accelerations were recorded at three fixed points inside two tram models (Pesa 128NG Jazz Duo and Düwag N8C), while longitudinal accelerations were deliberately omitted at this stage due to their strong dependence on driver behavior. Raw data were exported as CSV files, processed and analyzed in R version 4.2.2, and then mapped spatially using ArcGIS cartograms. Vehicle speed was calculated both via the haversine formula—accounting for Earth’s curvature—and via a Cartesian approximation. Over the ~7 km route, both methods yielded virtually identical results, validating the simpler approach for short distances. Acceleration histograms approximated Gaussian distributions, with most values between 0.05 and 0.15 m/s², and extreme values approaching 1 m/s². The results demonstrate that low-cost mobile devices, after future calibration against certified accelerometers, can provide sufficiently rich data for ride-comfort assessment and show promise for cost-effective condition monitoring of both track and rolling stock. Future work will focus on optimizing the app’s data collection pipeline, refining standard-based analysis algorithms, and validating smartphone measurements against benchmark sensors. Full article

Background/Objectives: An initial COVID-19 candidate vaccine containing a purified ancestral SARS-CoV-2 spike antigen was characterized with an ELISA using recombinant monoclonal antibodies (mAbs) generated against this variant. Upon the emergence of a new Beta (B.1.351) spike variant early in the pandemic, the assessment of a bivalent vaccine containing ancestral and Beta spike antigens began. Due to accelerated project timelines, mAbs generated specifically against the Beta spike antigen were not available at the time to address assay development and vaccine testing requirements. Methods: Using only the initial mAb panel raised against the ancestral spike antigen, an epitope-blocking ELISA strategy was developed to independently measure Beta spike antigen in bivalent vaccine formulations. To facilitate this, epitope profiling of spike antigens from both ancestral and Beta variants was performed with biolayer interferometry and hydrogen–deuterium exchange mass spectrometry using the original panel of mAbs. Results: The resulting blocking ELISA was precise and specific for the Beta spike antigen and detected the expected amount of this antigen in bivalent vaccine formulations. The specific amount of ancestral spike protein in the bivalent vaccine was also confirmed using the original ELISA developed at the onset of the pandemic. Conclusions: This epitope-blocking strategy helped to overcome key reagent availability issues and could be applied to other projects involving related proteins. Full article

Although PLA is an attractive biodegradable polymer, its degradation under natural conditions is often slow. This study investigates whether incorporating pounamu (New Zealand jade) particles into PLA can enhance its biodegradation rate under composting conditions at room temperature. PLA composites containing 0 to 15 wt% pounamu were fabricated using both compression molding and 3D printing. A simple, reproducible protocol based on residual mass measurement was developed to monitor the biodegradation process over a 12-month period. The results showed that increasing pounamu content consistently accelerated mass loss of the composite in the compost, indicating enhanced biodegradation. The 3D-printed samples degraded more rapidly than compression-molded ones. This was attributed to the layered structure, internal microcavities, and lower crystallinity of the 3D-printed samples, which provided greater surface area and accessibility for microbial activity. These findings highlight the dual role of pounamu as both a crystallization promoter and a facilitator of biodegradation and underscore the importance of the processing method when designing biodegradable polymer composites for real-world applications. Full article

The aim of this study was to examine the relationship between the external load (EL) and internal load among U15, U17, and U19 youth soccer players and to identify the factors best influencing the rating of perceived exertion (RPE) and session-RPE (s-RPE) from Global Positioning System-derived variables. Data were collected from 50 male youth soccer players over an 11-week in-season period, encompassing a total of 1386 observations (145 training sessions and 33 matches). The findings indicate that during training sessions, the relationship between EL-derived volume variables and s-RPE exhibited moderate-to-very-strong correlations (U15—r ranging from 0.23 to 0.52; U17—r ranging from 0.51 to 0.78; U19—r ranging from 0.34 to 0.61, p < 0.001). The strongest relationships were observed with the total distance, acceleration, deceleration, and player load variables (p < 0.001). However, perceived wellness measures showed weak correlations with almost every EL parameter. Considering matches for all age groups, total distance showed moderate-to-large correlation with s-RPE (ranging from 0.41 to 0.59, p < 0.001). Additionally, RPE and s-RPE were significantly influenced by the variables of total distance, acceleration, deceleration, medium-speed running per minute, sprint distance per minute, and deceleration per minute. Full article

Background/Objectives: Recent changes in obstetric practices and population demographics have prompted a re-evaluation of labor patterns. This study aimed to characterize labor patterns in a Greek pregnant population using ultrasound and compare them with established labor curves. Methods: A prospective cohort study was conducted at the Third Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, over a two-year period (December 2022 to June 2024). Transabdominal ultrasound was used to determine the fetal head position and transperineal ultrasound was used to measure angle of progression (AoP) and head–perineum distance (HPD) during labor. Maternal and labor characteristics, including body mass index (BMI), parity, labor duration, and mode of delivery, were recorded. Statistical analysis included mixed linear models to assess the relationship between AoP, HPD, and cervical dilatation. Results: In total, 500 parturients were included in this study. Women entered the active phase of labor approximately 5 h before delivery, with AoP increasing sharply and HPD decreasing rapidly at this point. Cesarean section (CS) cases showed a slower increase in AoP compared to vaginal deliveries (VDs), with CS cases having a mean AoP of 117.9° (95% CI: 111.6–124.2°) at full dilation, compared to 133.4° (95% CI: 130.6–136.2°) in VD. HPD values declined more slowly in CS cases, with a mean HPD of 45.1 mm (95% CI: 40.6–49.6 mm) at full dilation, compared to 36.4 mm (95% CI: 34.3–38.5 mm) in VD. Epidural analgesia was associated with steeper increases in AoP and decreases in HPD in the final 2.5 h before delivery, while oxytocin administration accelerated these changes in the last 3–4 h. The mean time to delivery was 3.19 h (95% CI: 2.80–3.59 h) when AoP reached 125° and 3.92 h when HPD was 40 mm (95% CI: 3.53–4.30 h). BMI in women who gave birth via CS was significantly higher compared to VD (32.03 vs. 29.94 kg/m², p-value: 0.008), and the total duration of labor was shorter in VD compared to CS and operative vaginal delivery (OVD) (8 h vs. 15 h, p-value < 0.001 and 8 h vs. 12 h, p-value < 0.001, respectively). Birthweight was also lower in VD compared to CS (3103.09 g vs. 3267.88 g, p-value: 0.05). Conclusions: This study provides the first ultrasonographic characterization of labor patterns in a Greek population, highlighting the utility of ultrasound in objectively assessing labor progression. Full article

The influence of the copper (Cu) content on the corrosion resistance of 3.5%Ni low-carbon weathering steel was investigated using periodic dry–wet cycle accelerated corrosion tests. The mechanical properties of the steels were assessed via tensile and low-temperature impact tests, while corrosion resistance was evaluated based on weight loss measurements. Surface oxide layers were characterized using three-dimensional laser confocal microscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and electrochemical methods. Electron probe microanalysis (EPMA) was employed to examine the cross-sectional morphology of the oxide layer after 72 h of accelerated corrosion tests. The results indicate that the solution state of Cu increased the strength of 3.5%Ni steels but significantly damaged the low-temperature toughness. As the Cu content increased from 0.75% to 1.25%, the corrosion rate decreased from 4.65 to 3.74 g/m² h. However, when there was a further increase in the Cu content to 2.15%, there was little decrease in the corrosion rate. With the increase in the Cu content from 0.75% to 2.15%, the surface roughness of 3.5%Ni weathering steel after corrosion decreased from 5.543 to 5.019 μm, and the corrosion behavior was more uniform. Additionally, the α/γ protective factor of the oxide layer of the surface layer increased from 2.58 to 2.84 with an increase in the Cu content from 0.75% to 1.25%, resulting in the oxide layer of the surface layer being more protective. For 1.25%Cu steel, the corrosion current density of rusted samples is lower (ranging from 1.2609 × 10⁻⁴ A/cm² to 3.7376 × 10⁻⁴ A/cm²), and the corrosion potential is higher (ranging from −0.85544 V to −0.40243 V). Therefore, the rusted samples are more corrosion resistant. The Cu in the oxide layer of the surface layer forms CuO and CuFeO₂, which are helpful for increasing corrosion resistance, which inhibits the penetration of Cl⁻. Full article

Using recycled concrete (RC) created from building debris to capture, utilize, and sequester CO₂ is a green and sustainable development strategy. Before CO₂ curing, pretreatment can provide a suitable environment for the carbonation reaction of the RC, accelerate the carbonation rate of the RC, and enhance its performance. The effects of the pre-curing time and residual water–cement ratio (Re) on the carbon sequestration rate, carbon sequestration, carbonation depth, and mechanical strength of RC were investigated and validated through X-ray diffraction (XRD) and scanning electron microscopy (SEM). The study demonstrated optimal carbon sequestration properties at a pre-curing time of 5 days. The corresponding carbon sequestration rate, unit carbon sequestration, carbonation depth, and compressive strength were 23.17%, 19.88 g/kg, 15.79 mm, and 28.7 MPa, respectively. Optimal carbon sequestration performance occurred at a Re of 0.26. The measured values were 20.15% (carbon sequestration rate), 17.38 g/kg (unit carbon sequestration), 12.55 mm (carbonation depth), and 31.1 MPa (compressive strength). According to the XRD and SEM results, the effects of pre-curing time and Re were mainly seen in the conversion rate of CaCO₃ and a denser microstructure. This implies that improving the CO₂ curing effect by controlling the pre-curing time and Re can both alleviate the pressure of greenhouse gas emissions and increase the utilization efficiency of RC. Full article

The standard genetic code (SGC) plays a fundamental role in encoding biological information, but its evolutionary origins remain unresolved and widely debated. Thus, we used a methodology based on the evolutionary algorithm to investigate the emergence of stable coding systems. The simulation began with a population of varied primitive genetic codes that ambiguously encoded only a limited set of amino acids (labels). These codes underwent mutation, modeled by dynamic reassignment of labels to codons, gradual incorporation of new amino acids, and information exchange between themselves. Then, the best codes were selected using a specific fitness function F that measured the accuracy of reading genetic information and coding potential. The evolution converged towards stable and unambiguous coding systems with a higher coding capacity facilitating the production of more diversified proteins. A crucial factor in this process was the exchange of encoded information among evolving codes, which significantly accelerated the emergence of genetic systems capable of encoding 21 labels. The findings shed light on key factors that may have influenced the development of the current genetic code structure. Full article

The realization of agricultural modernization inevitably requires the improvement of agricultural land productivity. Rural public science and technology services is an important driving force to improve agricultural land productivity. However, can rural public science and technology services accelerate the process of agricultural modernization by improving land productivity? This paper innovatively constructs an evaluation index system and an mediating mechanism model, measures the comprehensive index of agricultural modernization and rural public science and technology services through the global entropy method, and empirically tests the mediating effect of the mechanism of “land productivity” with the help of measurement methods such as the Sobel–Goodman test and Bootstrap test. The research results find that rural public science and technology services can positively promote agricultural modernization and pass the 1% significance level test. There is a significant mediating effect of “increasing production” in the impact of rural public science and technology services on agricultural modernization, that is, rural public science and technology services can significantly promote agricultural modernization through the mechanism of “improving land productivity”. Government intervention and economic growth are significantly positive, which can significantly promote agricultural modernization. These findings have clear policy implications: Chinese government should accelerate the filling of gaps in rural public technology services between urban and rural areas in the southwest region, empower land productivity through science and technology, and promote the transformation of agricultural scientific and technological achievements into real productive forces. This research is helpful to provide policy reference and case experience for similar areas to speed up agricultural modernization by giving full play to the mechanism of “improving land productivity” of agricultural science and technology services. Full article

Secure communication is critically dependent on high-speed and high-security quantum random number generation (QRNG). In this work, we present a responsive approach to enhance the efficiency and security of QRNG by leveraging polarization-controlled heterodyne detection to simultaneously measure the quadrature amplitude and phase fluctuations of vacuum shot noise. To address the practical non-idealities inherent in QRNG systems, we investigate the critical impacts of imbalanced heterodyne detection, amplitude–phase overlap, finite-size effects, and security parameters on quantum conditional min-entropy derived from the entropy uncertainty principle. It effectively mitigates the overestimation of randomness and fortifies the system against potential eavesdropping attacks. For a high-security parameter of ${10}^{-20}$, QRNG achieves a true random bit extraction ratio of 83.16% with a corresponding real-time speed of 37.25 Gbps following a 16-bit analog-to-digital converter quantization and 1.4 GHz bandwidth extraction. Furthermore, we develop a deep convolutional neural network for rapid and accurate entropy evaluation. The entropy evaluation of 13,473 sets of quadrature data is processed in 68.89 s with a mean absolute percentage error of 0.004, achieving an acceleration of two orders of magnitude in evaluation speed. Extracting the shot noise with full detection bandwidth, the generation rate of QRNG using dual-quadrature heterodyne detection exceeds 85 Gbps. The research contributes to advancing the practical deployment of QRNG and expediting rapid entropy assessment. Full article