Larger Mean Research Articles

Raindrop size distributions of summer monsoon rainfall observed over Eastern India

The present study aims to quantify the raindrop size distributions (RSDs) of Indian summer monsoon (ISM) rainfall over a tropical eastern Indian station, Rourkela using five years (2018–2021) of Thies disdrometer measurements. The RSD measurements of ISM rainfall at Rourkela are segregated into active and break spells using the standardized rainfall anomalies over the study area. The RSDs characteristics of active and break spells are analyzed and their empirical relations, which are appropriate for precipitation estimation algorithms, are also reported. A significant annual and monthly variations in RSDs is noticed between the active and break spells of the ISM rainfall over the study region. The probability distribution function (PDF) RSDs parameters (rainfall rate, liquid water content, mass-weighted mean diameter, and normalized intercept parameter) demonstrated clear distinctions between active and break spells. The active spells showed higher rainfall amounts, large mass-weighted mean diameter, and smaller normalized intercept parameters over the break spells. A further segregation of active and break spells into stratiform and convective types revealed more large size drops in convective (stratiform) precipitations of active (break) spells. Occurrence of higher rainfall amounts and large size raindrops in the active spells over the break spells can be attributed to the presence of abundant moisture and convective activity in active spells. Furthermore, the radar reflectivity-rainfall rate (Z–R), shape and slope (μ–Λ), and mass-weighted mean diameter-rainfall rate (Dm-R) relations established for the active and break spells could aid in improving the precipitation estimations of over the study region.

Pore-scale investigation of forced imbibition in porous rocks through interface curvature and pore topology analysis

Forced imbibition, the invasion of a wetting fluid into porous rocks, plays an important role in the effective exploitation of hydrocarbon resources and the geological sequestration of carbon dioxide. However, the interface dynamics influenced by complex topology commonly leads to non-wetting fluid trapping. Particularly, the underlying mechanisms under viscously unfavorable conditions remain unclear. This study employs a direct numerical simulation method to simulate forced imbibition through the reconstructed digital rocks of sandstone. The interface dynamics and fluid–fluid interactions are investigated through transient simulations, while the pore topology metrics are introduced to analyze the impact on steady-state residual fluid distribution obtained by a pseudo-transient scheme. The results show that the cooperative pore-filling process promoted by corner flow is dominant at low capillary numbers. This leads to unstable inlet pressure, mass flow, and interface curvature, which correspond to complicated interface dynamics and higher residual fluid saturation. During forced imbibition, the interface curvature gradually increases, with the pore-filling mechanisms involving the cooperation of main terminal meniscus movement and arc menisci filling. Complex topology with small diameter pores may result in the destabilization of interface curvature. The residual fluid saturation is negatively correlated with porosity and pore throat size, and positively correlated with tortuosity and aspect ratio. A large mean coordination number characterizing global connectivity promotes imbibition. However, high connectivity characterized by the standardized Euler number corresponding to small pores is associated with a high probability of non-wetting fluid trapping.

Antibunched N-photon bundles from dark states assisted by ac Stark shift

In this paper, we propose an interesting scheme to generate antibunched N-photon bundles from dark states by using a single-atom cavity quantum electrodynamics system. The dispersive coupling between the atom and cavity introduces a Stark shift to one of the ground states, while the resonant coupling, along with a control field, forms a coherent N-excitation dark state assisted by the shift. Consequently, super-Rabi oscillation is established between the vacuum state and the N-excitation dark state when a probe field weakly couples to two ground states, enabling antibunched N-photon bundle emission within long-lived atomic coherence. As a byproduct, the generated high-efficiency single-photon source with a large mean photon number and high fidelity is of great value in quantum information processing.

Comparative effects of Backward walking training and standing balance training on balance and risk of fall among parkinson patients.

Background: balance and risk of falls are common problems among People with Parkinson's disease (PD) which compromise their functional independence and quality of life. Various rehabilitation protocols are being used for these patients. Objective: To determine the effectiveness of backward walking training (BWT) and standing balance training (SBT) on balance, and risk of falls among Parkinson's patients. Methodology: A randomized controlled trial was conducted at General Hospital Lahore from June 2020 to March 2021. The Parkinson's Patients of stage 3 or 4 of lower extremity on Brunnstrom motor recovery and the ability to walk 14 m with or without a walking aid or orthosis were included in the study. The Berg Balance Scale was used to evaluate the balance and fall risk. Group A (n=15) received backward walking training and Group B (n=15), standing balance training. The participants were assessed at the baseline, after the 6th week, and after 12 weeks of intervention. Results: The mean age of participants was 50.03+8.36 years. A total of n=17 participants were male while 13 were female. The result showed that group A received backward walking training (BWT) had a significantly large mean difference (22.13+-2.35 vs. 18.20.3.58, 95%CI (1.64,6.22) in BSS score as compared to group B received standing balance training (SBT). Conclusion: The study concluded that standing balance training and backward walking training both are effective, but backward walking training is more effective in improving balance and the risk of falls in Parkinson's patients.

Validity, reliability, and the contributing physical characteristics of a modified 15m prone Yo-Yo Intermittent Recovery Test Level-1 test in elite female rugby league players.

This study aims to establish the validity and reliability of the prone Yo-YoIRL1 in elite female rugby league players (part one) and determine the anthropometric and physical characteristics contributing to 15m prone Yo-YoIRL1 performance (part two). Part one, 21 subjects completed one Yo-YoIRL1, one 20m and two 15m prone Yo-YoIRL1 tests over four sessions, with 7-14 days in-between. Part two, ten subjects completed a testing battery, including body mass, height, dual-energy x-ray absorptiometry, isometric mid-thigh pull, isometric bench-press, 10m and 20m sprints and an incremental treadmill test ([Formula: see text]). The 15m prone YoYoIRL1 demonstrated poor reliability with a typical error of 68m (21%) and a smallest worthwhile change of 54m (9%). Validity analysis found the prone versions of the YoYoIRL1 were not sensitive measures of intermittent running performance. Both prone YoYoIRL1 test distances demonstrated large mean bias (76% and -37% respectively) and typical error of the estimate (19% and 21%, respectively) in comparison to the YoYoIRL1. Body mass (r = -0.89), lean mass (r = -0.64), body fat % (r = -0.68), [Formula: see text] (l∙min-1) (r = -0.64), IMTP (r = -0.69), IBP (r = -0.15), 10m (r = -0.77) and 20m (r = -0.72) momentum displayed large negative relationships with 15m prone Yo-YoIRL1 performance. Due to the poor validity of the 20m prone YoYoIRL1, the poor validity and reliability of the 15m prone YoYoIRL1, and the anthropometric and physical characteristics which negatively impact performance, practitioners should reconsider the use of the prone YoYoIRL1 test to monitor high intensity intermittent running performance.

An eddy current sensor for end-point detection in chemical mechanical planarization using composition signal filtration and a digital potentiometer

End-point detection (EPD) is important for controlling the chemical mechanical polishing process to prevent underpolishing and overpolishing. One EPD method using the relative current density on a Cu wafer involves an eddy current, which has advantages of noncontact and a fast response speed. However, the eddy current method has a large mean error at a low relative current density. To overcome the disadvantage, composition signal filtration uses a high mean error and long delay time using a moving average and 1-D Kalman filtration. After applying composition filtration, the mean error improved by approximately 94.7 %. Still, it is difficult to measure a thickness of 4000 Å or less with existing systems. A digital potentiometer was developed that changed the resistance in real time and improved the detection range. The step number for changing the resistance was 120 steps in the resistance range of 100–5000 Ω at approximately 40 Ω/step. When a digital potentiometer was applied, the EPD detection range improved by 85.8 % over the existing system. In other words, the developed system could measure a Cu wafer thickness of 586 Å.

Designing an efficient adaptive EWMA model for normal process with engineering applications

Stability in process parameters is required to ensure the quality of the finished item. Control charts, as one of the critical parts of statistical process monitoring (SPM), have seen widespread use across many disciplines for detecting and responding to shifts in process parameters. The adaptive EWMA (AEWMA) control chartis a well-known scheme that detects both small and large process shifts by integrating the features of the Shewhart and classical EWMA charts. In this study, we propose an enhanced AEWMA chart, termed the EAEWMA chart, that efficiently monitors small and large process mean shifts simultaneously. The proposed EAEWMA chart enhances the existing AEWMA chart using the shift estimator, based on the hybrid EWMA (HEWMA) statistic. The Monte Carlo simulation approach is employed as the computational method to obtain the numerical findings for the various performance metrics. The EAEWMA chart is compared with various existing charts, including AEWMA, HEWMA, EWMA, ACSUM, and IACCUSUM, in zero- and steady-state scenarios. Conclusively, two practical applications of the EAEWMA chart are presented, demonstrating its value for practitioners and engineers and illustrating its efficacy in real-world scenarios.

Optimization of Batch Cooling Crystallization of Sodium Phosphite Through Genetic Algorithm

AbstractIn this paper, the seeded batch cooling crystallization of sodium phosphite (SP) is simulated and optimized through a coupled method of the genetic algorithm and nonlinear programming. At first, the modeling and simulation test methods of the crystallization process are applied for the crystallization of SP, which expands the relevant study of SP from the experiment to the simulation. A comprehensive model is established in MATLAB/Simulink, and based on this model, the results of the common cooling strategy (linear cooling) on the process are investigated. Meanwhile, the process sensitivity to the change of seeding conditions is analyzed. Then, the coupled optimization method based on the genetic algorithm and nonlinear programming is applied to optimize the crystallization process for the first time, and the obtained optimized cooling strategy is compared to the result of the traditional nonlinear programming method (NLPM). The traditional NLPM has more significant effects on large seeding mass and small mean size, while the coupled method has better adaptability. When the coefficient of variation is almost fixed, the cooling strategy obtained by the coupled method could produce more crystals with large mean size. In addition, the end of the process can be reached earlier. The results show that the coupled method is more suitable for the optimization of the batch cooling crystallization of SP.

Shape completion in the dark: completing vertebrae morphology from 3D ultrasound

PurposeUltrasound (US) imaging, while advantageous for its radiation-free nature, is challenging to interpret due to only partially visible organs and a lack of complete 3D information. While performing US-based diagnosis or investigation, medical professionals therefore create a mental map of the 3D anatomy. In this work, we aim to replicate this process and enhance the visual representation of anatomical structures.MethodsWe introduce a point cloud-based probabilistic deep learning (DL) method to complete occluded anatomical structures through 3D shape completion and choose US-based spine examinations as our application. To enable training, we generate synthetic 3D representations of partially occluded spinal views by mimicking US physics and accounting for inherent artifacts.ResultsThe proposed model performs consistently on synthetic and patient data, with mean and median differences of 2.02 and 0.03 in Chamfer Distance (CD), respectively. Our ablation study demonstrates the importance of US physics-based data generation, reflected in the large mean and median difference of 11.8 CD and 9.55 CD, respectively. Additionally, we demonstrate that anatomical landmarks, such as the spinous process (with reconstruction CD of 4.73) and the facet joints (mean distance to ground truth (GT) of 4.96 mm), are preserved in the 3D completion.ConclusionOur work establishes the feasibility of 3D shape completion for lumbar vertebrae, ensuring the preservation of level-wise characteristics and successful generalization from synthetic to real data. The incorporation of US physics contributes to more accurate patient data completions. Notably, our method preserves essential anatomical landmarks and reconstructs crucial injections sites at their correct locations.

Estimation of adaptability parameters of collection hulled oats varieties according to productivity in the Kirov region

The current paper has presented the study results conducted on the experimental plot of the Falenskaya breeding station of the branch of the FSBI FANC of the North-East in 2021–2023. The purpose of the study was to evaluate the collection hulled oat varieties according to grain productivity and adaptability parameters in the soil and climatic conditions of the Kirov region. The materials for the study were 9 collection oat varieties and the standard variety ‘Krechet’. According to the trait ‘productivity’, there have been estimated adaptability parameters. During the testing years, the studied variety samples differed significantly in productivity variability (V = 16.8–30.0 %). The factor ‘year’ had the greatest effect on the formation of oat yields (90.3 %). In the arid year of 2021, the varieties’ productivity was low (276–401 g/m2), with a negative index of environmental conditions (Ij = -163), in the most favorable year of 2022, it was 463–682 g/m2 and Ij = 104, respectively. The variety samples ‘k-3967 0144’ (-190 g/m2) and ‘15584 Mutant 258’ (-214 g/m2) were characterized by high stress resistance. High genetic flexibility of mean productivity under contrasting conditions was established in the variety samples ‘15472 Sumphony’ (504 g/m2), ‘k-3967 0144’ (496 g/m2) and ‘15340 Uran’ (487 g/m2). There have been identified such gene sources as plastic ‘k-3967 0144’, ‘15472 Sumphony’, ‘15340 Uran’, ‘k-3951 0146’, ‘k-3954 0149’ (IEP = 1.13–1.0), and with high stability of the trait ‘productivity’ ‘k-3967 0144’, ‘15584 Mutant 258’, ‘k-3954 0149’ (SF = 1.47–1.78). Low variability and high homeostaticity were found in the variety samples ‘k-3967 0144’, ‘15584 Mutant 258’, ‘k-3954 0149’ (V = 16.8–22.8 %; Hom = 31.31–20.75) with a high stability index (Is = 5.95–4.38). The adaptability coefficient has confirmed the high adaptability of variety samples ‘k-3967 0144’, ‘15472 Sumphony’ and ‘15340 Uran’ (KA =112.3–108 %). In adaptive breeding for further work, the varieties ‘k-3967 0144’, ‘15584 Mutant 258’, ‘k-3954 0149’, ‘15472 Sumphony’, ‘15340 Uran’ are of great interest, since they are the most adaptive in terms of the sum of ranks. Based on a comprehensive estimation of productivity and adaptability parameters, ‘k-3967 0144’ was recognized as the best variety sample, which can give a large mean productivity (526 g/m2) in changing weather conditions.

Stoichiometric control of electron mobility and 2D superconductivity at LaAlO3-SrTiO3 interfaces

SrTiO3-based conducting interfaces, which exhibit coexistence of gate-tunable 2D superconductivity and strong Rashba spin-orbit coupling (RSOC), are candidates to host topological superconductive phases. Yet, superconductivity is usually in the dirty limit, which tends to suppress nonconventional pairing and therefore challenges these expectations. Here we report on LaAlO3/SrTiO3 (LAO/STO) interfaces with large mobility and mean free paths comparable to the superconducting coherence length, approaching the clean limit for superconductivity. We further show that the carrier density, mobility, and formation of the superconducting condensate are controlled by the fine-tuning of La/Al chemical ratio in the LAO film. We find a region in the superconducting phase diagram where the critical temperature is not suppressed below the Lifshitz transition, at odds with previous experimental investigations. These findings point out the relevance of achieving a clean-limit regime to enhance the observation of unconventional pairing mechanisms in these systems.

Improved Equivalent Strain Method for Fatigue Life of Automobile Aluminum Alloy

Improved Equivalent Strain Method for Fatigue Life of Automobile Aluminum Alloy

Photon blockade with high photon occupation via cavity electromagnetically induced transparency

Photon blockade (PB) is one of the effective methods to generate single-photon sources. In general, both the PB effect with the significant sub-Poissonian statistics and a large mean photon number are desired to guarantee the brightness and the purity of single-photon sources. Here, we propose to obtain the PB effect at the cavity dark-state polariton (DSP) using a cavity Λ-type electromagnetically induced transparency (EIT) system with and without the two-photon dissipation (TPD). In the Raman resonance case, the PB effect at the DSP could by realized by using the TPD process in the weak or intermediate coupling regime, which accompanies with near unity transmission, i.e., very high photon occupation. In the slightly detuned Raman resonance case, the excited state is induced into the components of the DSP, and the atomic dissipation path is added into the two-photon excitation paths. Thus, the PB effect at the DSP can be obtained due to the quantum destructive interference (QDI) in the strong coupling regime, which can be further enhanced using the TPD process. Due to the slight detuning, the PB effect still remains high photon occupation and has highly tunability. This work provides an alternative way to manipulate the photon statistics by the PB effect and has potential applications in generating single-photon sources with high brightness and purity.

Influence of ceramic crown design (translucent monolithic zirconia vs. bilayered) of implant-supported single crowns after mechanical cycling.

This study aimed to assess the influence of translucent monolithic versus bilayered crowns and whether the use of a CoCr base abutments affects the fatigue and fracture resistance of screwed implant-supported single crowns with external connections under mechanical cycling. Fifty specimens were divided into groups: (1) metal-ceramic (MC) crown, (2) veneered zirconia crown (Zr), (3) veneered zirconia crown with a CoCr base abutment (ZrB), (4) monolithic translucent zirconia crown (MZr), and (5) monolithic translucent zirconia crown with a CoCr base abutment (MZrB). Specimens underwent mechanical cycling (5 × 106 cycles; 150 N) evaluating fatigue resistance (number of failures) and those that failed were subsequently subjected to fractographic analyses (stereomicroscope and scanning electron microscope) to evaluate failure location and area, and maximum fracture load was also measured. The failure-related survival rate (100%) and maximum fracture resistance of the MZrB were significantly higher than those of MC and Zr (50%; p < 0.05). There were no significant differences in the failure rate and fracture resistance when a CoCr base abutment was used or not in the translucent monolithic Zr groups (p > 0.05;MZrB vs. MZr). Failure location, with MC crowns' fractures, noted at the screw area (p = 0.043), while all-ceramic crowns were mostly in the cuspid and to failure area, the Zr group had the largest mean (15.55 ± 9.17 mm2) among the groups, significant difference only when compared with MC (1.62 ± 0.81 mm2) (p = 0.025). Translucent monolithic zirconia crowns exhibited significantly higher fatigue and fracture resistance compared with conventional MC and bilayered crowns. The appropriate choice of material and manufacturing technique is crucial for predicting the higher clinical performance of single crowns. Enhanced mechanical resistance in terms of fatigue and fracture resistance can be achieved by replacing MC and bilayered restorations with computer-aided design and computer-aided manufacturing monolithic zirconia.

Effects of the geometric characteristics of graphene nanoplatelets on the physico-rheological properties of asphalt binder

While graphene nanoplatelets (GnPs) have emerged as promising nano-modifiers of asphalt binder in recent years, much is still unknown in terms of the existing correlations between the physical, chemical, and geometric characteristics of this nanofiller and observed asphalt binder properties. In this work, we investigate the important correlation between the geometric characteristics of GnPs and the rheological properties of the GnP-modified asphalt binder at high temperatures. Our results indicate that, in general, incorporating GnPs with large mean particle diameters (> 14 μm) and thicknesses (> 8 nm) enhances the high-temperature performance of the asphalt binder. The results of the multiple stress creep and recovery tests confirm that including GnPs in asphalt binder can decrease its permanent deformation by 33.2% and enhance its elastic recovery by 53.9%. Phase contrast images obtained by atomic force microscopy further indicate that the presence of GnPs with large mean particle diameters alters the morphology of the asphalt binder, leading to improved temperature stability and less susceptibility to permanent deformation.

Design of High-Performance Inorganic-Organic Hybrid Nonlinear Optical Materials Using Superhalogen Al13 and Dianhydrides.

Novel inorganic-organic hybrid complexes Al13-X (X represents the dianhydrides PMDA, NTCDA, and PTCDA) are theoretically designed and studied using density functional theory (DFT) and time-dependent DFT. These conjugated dianhydrides containing four acceptor carbonyl groups are commonly used as electron acceptor materials. These compounds possess large binding energies, reflecting the sufficient binding of Al13 to the dianhydride molecule. The binding nature of the complexes is of charge transfer type, i.e., electrons are transferred from the aluminum cluster to the dianhydride. All of the aimed complexes have large mean polarizability (α0) and first hyperpolarizability (β0). The β0 values are explained on the basis of electronic transitions in crucial excited states using the TD-DFT method. Additionally, the hole-electron distribution was analyzed, revealing the nature of electronic excitation. Absorption spectra analysis shows that these complexes have an excellent infrared (IR) transparent region (1000-5000 nm). Therefore, these inorganic-organic hybrid complexes with high stability can be considered as potential candidates for new IR nonlinear optical molecules.

Prediction of entrainment fraction in two-phase gas-liquid co-current annular flow-A machine learning approach

Entrainment fraction is a crucial parameter to determine liquid holdup, pressure drop, and dryout in two-phase annular flow. It determines the fraction of liquid flows as liquid droplets in the gas core. Usually, empirical correlations are used to predict entrainment fraction. However, these correlations forecast entrainment fractions with large Mean Absolute Percentage Error (MAPE), especially when one correlation is used to predict entrainment fractions for different operating conditions. For instance, existing models considered in this study predict entrainment with MAPE of as much as 120.7 %. Besides around 40 % and 24 % of data were outside of ±30 % and ±50 % ranges. In the framework of this study, a Deep Neural Network (DNN model) has been developed to predict entrainment fraction in annular flow that is applicable for different operating conditions with good accuracy. The neural network is trained and tested for around 1213 entrainment fraction data points extracted from 7 different literature studies. It covers pressure ranges 0.1–20 MPa, tube diameter 5–32 mm with working fluid- air/water, steam/water, and Freon-113. The developed DNN model predicts entrainment fraction with the lowest MAPE compared to the existing models on unseen 155 data from 6 authors that are not used to train or test the model. Furthermore, only 17.61 % and 30.81 % of data remain outside of ±30 % and ±20% limits respectively whereas these values are at least 35.66 % and 52.86 % for existing models that are examined for comparison here.

The community background alters the evolution of thermal performance.

Microbes are key drivers of global biogeochemical cycles, and their functional roles arey dependent on temperature. Large population sizes and rapid turnover rates mean that the predominant response of microbes to environmental warming is likely to be evolutionary, yet our understanding of evolutionary responses to temperature change in microbial systems is rudimentary. Natural microbial communities are diverse assemblages of interacting taxa. However, most studies investigating the evolutionary response of bacteria to temperature change are focused on monocultures. Here, we utilize high-throughput experimental evolution of bacteria in both monoculture and community contexts along a thermal gradient to determine how interspecific interactions influence the thermal adaptation of community members. We found that community-evolved isolates tended toward higher maximum growth rates across the temperature gradient compared to their monoculture-evolved counterparts. We also saw little evidence of systematic evolutionary change in the shapes of bacterial thermal tolerance curves along the thermal gradient. However, the effect of community background and selection temperature on the evolution of thermal tolerance curves was variable and highly taxon-specific,with some taxa exhibiting pronounced changes in thermal tolerance while others were less impacted. We also found that temperature acted as a strong environmental filter, resulting in the local extinction of taxa along the thermal gradient, implying that temperature-driven ecological change was a key factor shaping the community background upon which evolutionary selection can operate. These findings offer novel insight into how community background impacts thermal adaptation.

Low disorder and high valley splitting in silicon

The electrical characterisation of classical and quantum devices is a critical step in the development cycle of heterogeneous material stacks for semiconductor spin qubits. In the case of silicon, properties such as disorder and energy separation of conduction band valleys are commonly investigated individually upon modifications in selected parameters of the material stack. However, this reductionist approach fails to consider the interdependence between different structural and electronic properties at the danger of optimising one metric at the expense of the others. Here, we achieve a significant improvement in both disorder and valley splitting by taking a co-design approach to the material stack. We demonstrate isotopically purified, strained quantum wells with high mobility of 3.14(8) × 105 cm2 V−1 s−1 and low percolation density of 6.9(1) × 1010 cm−2. These low disorder quantum wells support quantum dots with low charge noise of 0.9(3) μeV Hz−1/2 and large mean valley splitting energy of 0.24(7) meV, measured in qubit devices. By striking the delicate balance between disorder, charge noise, and valley splitting, these findings provide a benchmark for silicon as a host semiconductor for quantum dot qubits. We foresee the application of these heterostructures in larger, high-performance quantum processors.

Phonon-drag in a graphite channel buried in diamond

While the phonon-drag effect can induce large Seebeck coefficients, it is associated with large mean free path phonons present in the vicinity of the maximum in temperature of the lattice thermal conductivity. In this paper, we initiate a new route by searching for the mutual drag between the electron and phonon-drag gases at the interface between two different media. In that respect, the temperature studies of the conductance and Seebeck coefficient of a model system consisting of an electrically conductive graphitic channel buried beneath the surface of a diamond crystal are shown. The observed behaviour is very similar to that of graphite, with a typical negative peak associated with the phonon-drag effect. Interestingly, this phonon-drag peak of the buried graphitic channel appears at a significantly higher temperature than that in pure graphite.