Establishing tracer gas dilution as a potential reference method for in-stack CO2 emission metrology

The present study aimed to analyze the differences in psychopathological symptomatology between men and women who participate in online gambling, as well as to explore the relationship between this symptomatology and different risk profiles. The sample consisted of 382 participants, all university students from a province in Spain, of whom 261 were men (68.3%) and 121 were women (31.7%), with a mean age of 21.8 years (SD = 3.2; range = 18-30 years). Psychopathological symptomatology was assessed using the SAS-45, while gambling risk profiles were determined using an ad hoc questionnaire. The results of the risk profiles were formed by categorizing the SOG-RA Scale scores into non-risk gambler, at-risk gambler, and pathological gambler. The results evidenced that gender and risk profile are determining factors in the manifestation of psychopathological symptoms. It was observed that women tend to internalize their emotional problems, presenting higher levels of depression, anxiety, and interpersonal sensitivity, while men exhibit a greater propensity to externalize their symptoms, manifesting hostility, paranoid ideation, and psychoticism. Furthermore, gamblers with high-risk profiles showed higher scores in both internalizing and externalizing symptoms. Significant correlations were identified between risk profile, psychopathological symptomatology, and cognitive distortions, suggesting the need for comprehensive interventions differentiated by gender. These findings provide valuable information for the design of specific treatments that address the emotional and cognitive needs of problem gamblers, contributing to improving the effectiveness of therapeutic strategies in the context of problem gambling. University gambling is an emerging public health issue with consequences that extend beyond the individual, affecting educational, social, and economic well-being. This study addresses a critical gap by delineating gender-specific psychopathological profiles across gambling risk categories, providing actionable evidence to inform campus-based screening and targeted prevention strategies. The findings underscore the necessity of integrating gender-responsive interventions and upstream measures-such as early detection within student health services and harm-reduction messaging-to effectively mitigate gambling-related harm.

We present a novel method to derive rotation curves of the inner broad-line region (BLR) of lensed quasars with light-day spatial resolution.The approach exploits microlensing distortions of the broad emission lines (BELs), where the strength of the effect in the line wings traces the size of the emitting region at different velocities.We analyze the high-ionization lines Si IV and C IV in five gravitationally lensed quasars, measuring microlensing amplitudes across several velocity bins.Bayesian inference yields emission-region sizes, which we confront with a Keplerian disk model.We find a smooth, monotonic increase in microlensing with velocity, and the derived velocity-size relations are consistent with disk-like rotation.These results provide the first direct evidence for Keplerian motion in the innermost BLR of quasars.

To address the issues of imprecise user segmentation, inadequate handling of fuzzy evaluation information, and low recommendation accuracy in current electricity retail package recommendations, a novel recommendation method based on K-prototypes clustering and interval-valued intuitionistic fuzzy theory is proposed. First, a multi-dimensional user profile is constructed, incorporating five numerical tags—such as monthly average electricity consumption and monthly load factor—and two categorical tags: industry characteristics and value-added service demand. The K-prototypes algorithm is employed to cluster users, effectively resolving the profile distortion problem caused by the neglect of categorical features in traditional K-means clustering. Second, interval-valued intuitionistic fuzzy numbers are introduced to transform user linguistic evaluations into quantitative indicators. A projection measure-based model is established to objectively determine attribute weights, thereby eliminating subjective weighting bias. Finally, a comprehensive ranking of electricity retail packages is generated by integrating satisfaction levels of similar users and similar measures of new users. The recommendation performance is validated using Root Mean Square Error (RMSE), Kendall’s τ, Normalized Discounted Cumulative Gain (NDCG@5), and Discrimination Index (S). A case study involving users from a region in China demonstrates that the proposed method reduces the Root Mean Square Error (RMSE) to 0.32, which is 31.25% lower than the next best traditional method (K-prototypes + equal weight clustering with RMSE = 0.48), accurately addresses the core demands of diverse user groups, significantly improves recommendation precision and user satisfaction, and exhibits substantial practical application value.

In long-distance heavy-load transmission systems, the unique high load-bearing capacity and trajectory constraint characteristics of the double-idler rack-and-pinion mechanism can significantly improve the reliability of the transmission system. However, engineering practice has revealed that factors such as tooth profile distortion caused by residual stress from rack rolling, flatness errors of mounting surfaces, and linear expansion due to environmental temperature changes can markedly alter the dynamic meshing characteristics of the rack and pinion. During the meshing process of the double-idler rack-and-pinion, the deformation of the rack and pinion and installation errors can lead to meshing impacts, thereby generating significant impact noise. This paper analyzes abnormal meshing states influenced by changes in center distance and pitch, constructs a defective meshing model for the rack and pinion, and further identifies factors more sensitive to defective meshing impacts through dynamic simulations. Finally, the paper proposes a flexible floating idler shaft structure that effectively reduces meshing impacts. The results demonstrate that the proposed structure yields significant improvements, particularly in the direction of pitch variation, which is more sensitive to vibrations. Specifically, the effective vibration values for random pitch micro-variations and sudden rack pitch changes are reduced by 60.5% and 23.4%, respectively, while those for sudden changes in rack center distance are reduced by 57.01%. This research provides new methodological support for optimizing the dynamic characteristics of precision rack-and-pinion transmission systems.

Abstract Conventional metasurface‐based radar camouflage strategies are typically confined to single‐function designs, limiting their adaptability to complex and dynamic electromagnetic (EM) environments. Inspired by recent advances in metasurface technology, a multifunctional radar camouflage strategy is proposed by leveraging a broadband fully‐polarized spatio‐temporal modulation (STM) metasurface, which can achieve range profile distortion, geometric features obfuscation, and radar cross‐section reduction. Numerical simulations on satellite RadarSat‐1 data demonstrate the proposed device disrupts the intra‐pulse characteristics of echoes, thereby interfering with range profile imaging performance. Concurrently, the metasurface exhibits the capability to imitate high‐resolution range profiles of complex targets through an innovative spatially partitioned modulation approach, achieving effective concealment of salient geometric features. Additionally, the implementation of an aperiodic modulation scheme enhances the spectral uniformity of the EM scattered waves, leading to a significant reduction in radar cross‐section. Both simulation and measurement results have validated the great radar camouflage performance of the proposed STM metasurface, which can be developed for potential applications in radar jamming, secure wireless communication, and other pertinent fields.

The tooth surface geometry of harmonic gears directly affects the transmission accuracy and service life. Traditional design methods may cause tooth profile distortion when changing the radial deformation coefficient, which limits their application. This paper proposes a comprehensive tooth surface modification method that changes the radial deformation coefficient on the basis of traditional design methods. Firstly, the meshing trajectories and corresponding tooth profiles of gear teeth under different radial deformation coefficients are calculated and analyzed based on the rack approximation method. Secondly, a calculation method is proposed to eliminate the tooth profile distortion caused by changing the radial deformation coefficient, which not only expands the application of the rack approximation method but also eliminates interference during the meshing process. Subsequently, a comprehensive tooth surface modification method is proposed with the aim of increasing contact area and contact ratio, as well as reducing contact stress. Compared to traditional modification, it requires less material removal, which is beneficial for increasing the tooth strength. Furthermore, a finite element simulation model of a harmonic drive is established, and the tooth surface and contact performance of harmonic gears under three different radial deformation coefficients are designed and analyzed, verifying the effectiveness of the proposed tooth surface design method.

BackgroundThe integration of magnetic resonance imaging with linear accelerators (Linacs) enhances adaptive radiotherapy by providing real-time imaging for improved treatment precision. However, the long-term performance of MR-Linac systems, particularly in clinical settings, remains insufficiently studied. Traditional quality assurance (QA) methods, relying on binary pass/fail criteria, may overlook critical system variations. This study applies statistical process control (SPC) techniques to evaluate the long-term performance of a 1.5T MR-Linac, focusing on optimization in beam quality, MR-to-MV alignment, MR imaging, and geometric distortion.MethodsA dual-phase SPC framework was applied to 1 year of daily and weekly QA data from an Elekta Unity MR-Linac. Phase I established performance benchmarks, while Phase II monitored deviations online. Evaluated parameters included beam output, symmetry, MR-to-MV alignment, signal-to-noise ratio (SNR), spatial linearity, slice profile, and geometric distortion across spherical volumes (DSVs). Stability and variability were quantified using control charts and process performance indices (Ppk).ResultsBeam quality was stable overall (Ppk ≥ 1.33), though output dose and transverse symmetry showed increased variability in Phase II, with dose Ppk declining from 3.13 to 1.33. MR-to-MV alignment was consistent, but Phi rotational and Z translational offsets showed variability after system upgrades. Imaging metrics, including SNR and spatial linearity, achieved A + performance (Ppk ≥ 1.67) in Phase II, while vertical spatial resolution was lower (Ppk 1.04–1.10). Geometric distortion was well-controlled, though larger DSVs (≥ 500 mm) showed increased AP-axis distortion (2.44 mm) compared to RL (1.37 mm) and FH (0.93 mm).ConclusionsSPC techniques dynamically identified stable parameters and areas for improvement. Key recommendations include enhanced alignment protocols for beam quality and MR-to-MV offsets, as well as targeted strategies to address geometric distortion in larger volumes and along the AP axis.

Due to the complementary operational features, photovoltaic (PV) and fuel cell (FC) systems are increasingly being integrated into hybrid microgrids. PV systems provide clean energy during the day, while FCs provide continuous power supply throughout the day and night; thus, FCs can address PV’s incapacity during the night. However, voltage instability, frequency deviation, and enhanced harmonic distortion can result from the intrinsic intermittency of solar energy, switching errors in power electronic equipment, and varying load demands. Thus, a fuzzy logic-based current-controlled voltage source inverter (CC-VSI) is proposed in this paper to overcome these issues and enhance power quality in PV-FC hybrid microgrids. As per IEEE 1547 regulations, the fuzzy controller dynamically modifies the inverter current to maintain steady voltage and frequency profiles. MATLAB/Simulink (R2022a) is used to model and simulate the system, and its performance is evaluated under various reactive load scenarios. To test the efficacy of the proposed control technique, various power quality metrics, viz., voltage profiles (sag and swell), frequency profile, and total harmonic distortions, are plotted when subjected to large reactive load variations. The simulation results that are obtained with the proposed fuzzy-based current control technique are compared with the conventional artificial neural networks-based controller to verify the effectiveness. From the comparison study, it is found that the proposed technique shows superior power quality performance over the conventional technique. This encourages the development of renewable energy-based sustainable hybrid microgrids worldwide.

Microlensing by stars in the lens galaxy of a gravitationally lensed quasar is a phenomenon that can selectively magnify quasar subregions, producing observable changes in the continuum brightness or distortions in the emission line profiles. Hence, microlensing allows us to probe the inner quasar regions. In this paper, we report measurements of the ratio of the broad emission line region (BLR) radius to the continuum source radius in eight lensed quasars, for the C IV, Mg II, and Hα emission lines and their respective underlying continua at λλ 1550 Å, 2800 Å, and 6563 Å. The microlensing-induced line profile distortions and continuum magnifications were observed in the same single-epoch datasets, and simultaneously compared with microlensing simulations. We found that, on average, the inner radius of the BLR starts at the end of the UV-optical continuum source, independently of the line ionization and the wavelength of the continuum. The half-light radius of the BLR is, on average, a factor of six larger than the half-light radius of the continuum source, independently of the quasar’s bolometric luminosity. We also found a correlation between the BLR radius and the continuum source radius, supporting the idea that the dominant contribution to the UV-optical continuum may come from the BLR itself. Our results independently confirm the results of reverberation mapping studies, and extend them to higher-redshift, higher-luminosity quasars.

To eliminate distortion caused by vertical drift and illusory slopes in atomic force microscopy (AFM) imaging, a lifting-wavelet-based iterative thresholding correction method is proposed in this paper. This method achieves high-quality AFM imaging via line-by-line corrections for each distorted profile along the fast axis. The key to this line-by-line correction is to accurately simulate the profile distortion of each scanning row. Therefore, a data preprocessing approach is first developed to roughly filter out most of the height data that impairs the accuracy of distortion modeling. This process is implemented through an internal double-screening mechanism. A line-fitting method is adopted to preliminarily screen out the obvious specimens. Lifting wavelet analysis is then carried out to identify the base parts that are mistakenly filtered out as specimens so as to preserve most of the base profiles and provide a good basis for further distortion modeling. Next, an iterative thresholding algorithm is developed to precisely simulate the profile distortion. By utilizing the roughly screened base profile, the optimal threshold, which is used to screen out the pure bases suitable for distortion modeling, is determined through iteration with a specified error rule. On this basis, the profile distortion is accurately modeled through line fitting on the finely screened base data, and the correction is implemented by subtracting the modeling result from the distorted profile. Finally, the effectiveness of the proposed method is verified through experiments and applications.

Microlensing-induced distortions of broad emission line profiles observed in the spectra of gravitationally lensed quasars can be used to probe the size, geometry, and kinematics of the broad-line region (BLR). To this end, single-epoch Mg II or Hα line profile distortions observed in five gravitationally lensed quasars, J1131-1231, J1226-0006, J1355-2257, J1339+1310, and HE0435-1223, have been compared with simulated ones. The simulations are based on three BLR models, a Keplerian disk (KD), an equatorial wind (EW), and a polar wind (PW), with different sizes, inclinations, and emissivities. The models that best reproduce the observed line profile distortions were identified using a Bayesian probabilistic approach. We find that the wide variety of observed line profile distortions can be reproduced with microlensing-induced distortions of line profiles generated by our BLR models. For J1131, J1226, and HE0435, the most likely model for the Mg II and Hα BLRs is either KD or EW, depending on the orientation of the magnification map with respect to the BLR axis. This shows that the line profile distortions depend on the position and orientation of the isovelocity parts of the BLR with respect to the caustic network, and not only on their different effective sizes. For the Mg II BLRs in J1355 and J1339, the EW model is preferred. For all objects, the PW model has a lower probability. As for the high-ionization C IV BLR, we conclude that disk geometries with kinematics dominated by either Keplerian rotation or equatorial outflow best reproduce the microlensing effects on the low-ionization Mg II and Hα emission line profiles. The half-light radii of the Mg II and Hα BLRs are measured in the range of 3 to 25 light-days. We also confirm that the size of the region emitting the low-ionization lines is larger than the region emitting the high-ionization lines, with a factor of four measured between the sizes of the Mg II and C IV emitting regions in J1339. Unexpectedly, the microlensing BLR radii of the Mg II and Hα BLRs are found to be systematically below the radius-luminosity (R − L) relations derived from reverberation mapping, confirming that the intrinsic dispersion of the BLR radii with respect to the R − L relations is large, but also revealing a selection bias that affects microlensing-based BLR size measurements. This bias arises from the fact that, if microlensing-induced line profile distortions are observed in a lensed quasar, the BLR radius should be comparable to the microlensing Einstein radius, which varies only weakly with typical lens and source redshifts.

Objectives: The major goal of the proposed article is to enhance the power quality of a wind-integrated radial distribution network utilizing D-STATCOM. It is done by the appropriate allocation of wind turbine-based DGs and D-STATCOM. Methods: The multi-objective optimization problem is implemented using a novel and effective Prairie Dog Optimization (PDO) to attain the best-compromised solutions. This optimization tool is well suited for solving complex, non-linear voltage stability problems. The proposed approach is validated for the modified IEEE-13 bus highly unbalanced system using MATLAB. Findings: The findings indicate enhancements in the voltage profile, system losses, and total harmonic distortion (THD). The THD for the load current is 18%, while the THD for the source current is 2.54% for nonlinear loads using the proposed methodology. The voltage profile of 3.25% is enhanced as compared with the existing method, which is 2.15% better than the other obtainable method. Novelty: Prairie Dog Optimization (PDO) was chosen over traditional algorithms for its nature-inspired approach, simplicity, and efficacy in exploring complicated search fields. Its robust exploration and exploitation skills make it excellent for multi-modal optimization challenges. Keywords: Radial distribution system (RDS), D-STATCOM, Power quality, Prairie Dog Optimization, THD

In Portoviejo, the current use of electric vehicles (EVs) is limited compared to conventional vehicles. However, due to the implementation of laws, regulations, and policies promoting electric mobility in Ecuador, a significant increase in the integration of EVs into the city's electrical system is anticipated in the coming years. To anticipate the impact on the electrical infrastructure, a simulation is conducted using CYMDIST software on an electrical distribution feeder operated by the Public Company Corporación Nacional de Electricidad (CNEL EP), Manabí Business Unit (Portoviejo). The simulation considers three scenarios projected for 2030: 1. Baseline scenario without EV integration, 2. Unrestrained EV integration, and 3. Managed EV integration. This research aims to simulate the integration of up to 230 EVs into the network to provide benchmark data for understanding the potential impacts on the feeder as EV adoption increases, with vehicles being charged over extended periods. The investigation will highlight the importance of demand management with EV integration, demonstratingsignificant effects on the demand curve, voltage profile, and total harmonic distortion rate (THD%) of a 13.8 kV distribution feeder.

The characteristics of gust flow are essential for gust response and alleviation. To investigate the influence of control parameters on gusts with different velocity profiles, four vertical gust profiles were designed. Methods were proposed to generate them with two pitching airfoils in a low-speed water tunnel. The velocity field was measured via phase-locked particle image velocimetry. The coefficient of determination R2 was proposed to evaluate the generated gust profile quality, which referred to the quality of the vertical velocity profile. The influence of control parameters on different gust profiles was investigated, and the cause of the profile distortion was explored. For continuous sine gusts, the gust ratio GR increased approximately linearly with the pitching amplitude, while the gust ratio initially increased and then decreased with increasing frequency. As the two control parameters increased, the flow uniformity decreased because the airfoil wakes disturbed the measured flow field. In terms of continuous 1-cosine gusts, the gust ratio increased nonlinearly with pitching amplitude. Compared with those of the sine gusts, the GR values of the 1-cosine gusts were higher, whereas the R2 values were lower. In addition, the discrete and continuous gust profiles had similar distortion near the peaks. However, discrete gusts had lower R2 values than continuous gusts because the starting and stopping vortices of the pitching airfoils disturbed the gust flow. Based on these findings, a method to improve the profile quality and field uniformity by increasing the spacing of the pitching airfoils was proposed. This work can support further studies of gust response and alleviation during complex gust encounters.

Differential-geometry-based multi-dimensional joint position-velocity estimation using Crab pulsar profile distortion

Tunnel excavation slag volume measurement using triple-line structured-light vision: Rectification and optimization

Microlensing of the broad emission line region (BLR) in gravitationally lensed quasars produces line profile distortions that can be used to probe the BLR size, geometry, and kinematics. Based on single-epoch spectroscopic data, we analyzed the C IV line profile distortions due to microlensing in two quasars, SDSS J133907.13+131039.6 (J1339) and SDSS J113803.73+031457.7 (J1138), complementing previous studies of microlensing in the quasars Q2237+0305 and J1004+4112. J1339 shows a strong, asymmetric line profile deformation, while J1138 shows a more modest, symmetric deformation, confirming the rich diversity of microlensing-induced spectral line deformations. To probe the C IV BLR, we compared the observed line profile deformations to simulated ones. The simulations are based on three simple BLR models, a Keplerian disk (KD), an equatorial wind (EW), and a polar wind (PW), of various sizes, inclinations, and emissivities. These models were convolved with microlensing magnification maps specific to the microlensed quasar images, which produced a large number of distorted line profiles. The models that best reproduce the observed line profile deformations were then identified using a Bayesian probabilistic approach. We find that the line profile deformations can be reproduced with the simple BLR models under consideration, with no need for more complex geometries or kinematics. The models with disk geometries (KD and EW) are preferred, while the PW model is definitely less likely. In J1339, the EW model is favored, while the KD model is preferred in Q2237+0305, suggesting that various kinematical models can dominate the C IV BLR. For J1339, we find the C IV BLR half-light radii to be r1/2 = 5.1−2.9+4.6 light-days and r1/2 = 6.7−3.8+6.0 light-days from spectra obtained in 2014 and 2017, respectively. They do agree within uncertainties. For J1138, the amplitude of microlensing is smaller and more dependent on the macro-magnification factor. From spectra obtained in 2005 (single epoch), we find r1/2 = 4.9−2.7+4.9 light-days and r1/2 = 12−8+13 light-days for two extreme values of the macro-magnification factor. Combining these new measurements with those previously obtained for the quasars Q2237+0305 and J1004+4112, we show that the BLR radii estimated from microlensing do follow the C IV radius–luminosity relation obtained from reverberation mapping, although the microlensing radii seem to be systematically smaller, which could indicate either a selection bias or a real offset.

Recent developments in the field of machine learning have found their application in a wide range of design processes. They have particular use where numerical simulations are involved and fast, more accurate predictions and optimized models are very much needed. In order to speed up experiments on a device or system model, it is necessary to speed up its execution (simulation). Instead of detailed models, you can create a surrogate. Its main task is fast execution, small amount of occupied memory and preservation of the specified error threshold in relation to the detailed model. This article demonstrates the integration of machine learning into the flow measurement process using ultrasonic flowmeters. The main source of errors in the application of the modern ultrasonic principle of flow measurement arises from the difficulty of taking into account the actual velocity profile of the measuring flow. In practice, the distribution of velocities in the cross-section of the pipeline differs from the theoretical one introduced in the calculation algorithm. However, if the velocity profile is known, an appropriate correction can be estimated and taken into account during calibration. This will increase the accuracy of measurements. In this study, an intelligent compensation of errors caused by profile distortion was presented to improve the accuracy of using multipath meters in such ultrasonic conditions. The purpose of such an intelligent correction arises in the search for the optimal layout and the minimum sufficient number of chords in the measuring transducer for various installation conditions. The adoption of a new approach based on a surrogate model with a neural network made it possible to take an approximate flow profile that has a certain distortion. So, for the chosen topology of the acoustic flow sensing channels, programmatically, by changing the location angle of the measuring system, instead of the local resistance, add such a position of the chords for which it is possible to set maximum admissible measurement accuracy. This means using a neural network for the required input correction model, especially in an environment characterized by a change in the velocity profile under the influence of different flow distortions.

ABSTRACT To evaluate the latest generation of satellite wind speed from AMSR2, ASCAT, GMI, SSMIS, SMAP, and WindSat, buoy measurements were obtained from buoys in coastal and tropical open ocean areas. Root mean square errors were calculated, resulting in values of 1.19 m/s for AMSR2, 1.25 m/s for ASCAT, 1.37 m/s for GMI, 1.38 m/s for SSMIS, 2.48 m/s for SMAP, and 1.18 m/s for WindSat. Numerous data pairs fall above the 45-degree line, mainly due to decreased buoy ac-curacy during high winds. Factors contributing to this include underestimation of buoy readings due to rough sea states and wind profile distortion. Satellite biases exhibit unimodal fluctuations over a one-year cycle, aligning with annual sea surface temperature variations. Statistical effects in extreme wind speed range cause abnormal fluctuations in statistics. Higher latitudes experi-ence larger deviations due to rough sea state. Ocean currents affect satellite wind speed observa-tions, particularly when aligned with wind direction. Coastal wind speed gradients primarily influenced from land contamination like rugged mountainous terrain along the West Coast of North America. Coastal upwelling also contributes to bias, with the west coast showing higher bias. A global comparison between SMAP and WindSat retrieval wind speeds demonstrates SMAP’s poor ability to monitor general wind speeds and validates the satellite-buoy experiment.