Time Parameters Research Articles

MOF-derived porous carbon microspheres Ni@C-acid as solid-phase microextraction coating for extraction of polycyclic aromatic hydrocarbons from tea infusions

The improvement of the stability and adsorption properties of materials on targets in sample pre-treatment has long been an objective. Extensive efforts have been made to achieve this goal. In this work, metal-organic framework Ni-MOF precursors were first synthesized by solvothermal method using polyvinylpyrrolidone (PVP) as an ideal templating agent, stabiliser and nanoparticle dispersant. After carbonization and acid washing, the nanoporous carbon microspheres material (Ni@C-acid) was obtained. Compared with the material without acid treatment (Ni@C), the specific surface area, pore volume, adsorption performance of Ni@C-acid were increased. Thanks to its excellent characteristics (high stability, abundant benzene rings), Ni@C-acid was used as fiber coatings in headspace solid-phase microextraction (HS-SPME) technology for extraction and preconcentration of polycyclic aromatic hydrocarbons (PAHs) prior to gas chromatography-flame ionization detector (GC-FID) analysis. The experimental parameters of extraction temperature, extraction time, agitation speed, desorption temperature, desorption time and sodium chloride (NaCl) concentration were studied. Under optimal experimental conditions, the wide linear range (0.01-30 ng mL−1), the good correlation coefficient (0.9916-0.9984), the low detection limit (0.003-0.011 ng mL−1), and the high enrichment factor (5273-13793) were obtained. The established method was successfully used for the detection of trace PAHs in actual tea infusions samples and satisfied recoveries ranging from 80.94-118.62 % were achieved. The present work provides a simple method for the preparation of highly stable and adsorbable porous carbon microsphere materials with potential applications in the extraction of environmental pollutants.

Dissolved gases analysis in transformer oil using TM (Pd, Ir, Au) modified MoSSe monolayer: A DFT study

This study applied density functional theory to investigate gas-sensitive devices based on transition metal-doped MoSSe (Pd-MoSSe, Ir-MoSSe, Au-MoSSe), exploring their adsorption and sensing performance towards three characteristic gases (CO, C2H2, C2H4) generated during the use or faults of transformer oil. The results indicate that Pd, Ir, and Au transition metal atoms preferentially anchor to the S surface of the pristine MoSSe monolayer. The doped monolayers exhibit significantly improved sensing characteristics in all aspects, suggesting chemical adsorption of the three characteristic gases. Through the analysis of band structures (BS), adsorption configurations, deformation charge densities (DCD), density of states (DOS), recovery time, and various adsorption parameters, the conclusion is drawn that while TM-MoSSe outperforms the pristine MoSSe monolayer in terms of adsorption and sensing performance, Pd-MoSSe and Au-MoSSe exhibit relatively good recovery times across a broader temperature range, whereas Ir-MoSSe is limited in this aspect. This study provides theoretical guidance for the potential application of transition metal-doped MoSSe monolayers as sensors for gases generated during the thermal runaway of transformer oil.

Excitation and manipulation of recurring rogue waves via nonlinear compression

We theoretically propose a feasible scheme to generate high-density waves and manipulate them quantitatively. We show that a wave with greater density compression called “recurring rogue wave” can be excited by first generating a rogue wave via quenching and Gaussian space modulation techniques followed by employing a nonlinear compression method. The formation of recurring rogue wave is verified to be a consequence of the combined interaction of nonlinear compression and “self compression”. We find that the maximal density of recurring rogue wave exhibits a nonmonotonic dependence on compression time, which allows us to manipulate recurring rogue waves quantitatively through changing compression time and modulation parameters within a certain range. The analytical results based on variational method qualitatively support the numerical simulation results. Our study provides potential strategies for efficiently generating high-density waves in Bose–Einstein condensate experiments.

Feasibility study comparing synthesized mammography with digital breast tomosynthesis and digital mammography for simulated first round screening in a single BreastScreen NSW centre.

While digital breast tomosynthesis (DBT) has proven to enhance cancer detection and reduce recall rates (RR), its integration into BreastScreen Australia for screening has been limited, in part due to perceived cost implications. This study aims to assess the cost effectiveness of digital mammography (DM) compared with synthesized mammography and DBT (SM + DBT) in a first round screening context for short-term outcomes. Clients recalled for nonspecific density (NSD) as a single lesion by both readers at the Northern Sydney Central Coast BreastScreen service in 2019 were included. Prior images were excluded to simulate first-round screening. Eleven radiologists read DM and synthesized mammography with DBT (SM + DBT) images 4 weeks apart. Recall rates (RR), reading time, and diagnostic parameters were measured, and costs for screen reading and assessment were calculated. Among 65 clients studied, 13 were diagnosed with cancer, with concordant cancer recalls. SM + DBT reduced recall rates (RR), increased reading time, maintained cancer detection sensitivity, and significantly improved other diagnostic parameters, particularly false positive rates. Benign biopsy recalls remained equivalent. While SM + DBT screen reading cost was significantly higher than DM (DM AU$890 ± 186 vs SM + DBT AU$1279 ± 265; P < 0.001), the assessment cost (DM AU$29,504 ± 9427 vs SM + DBT AU$18,021 ± 5606; P < 0.001), and combined screen reading and assessment costs were significantly lower (DM AU$30,394 ± 9508 vs SM + DBT AU$19,300 ± 5721; P = 0.001). SM + DBT screen reading and assessment of 65 patients resulted in noteworthy cost savings (AU$11,094), equivalent to assessing 12 additional clients. In first round screening, DBT yields significant cost savings by effectively reducing unnecessary recalls to assessment while maintaining diagnostic efficacy.

Comparison of Paraglossal Technique of Miller Blade Insertion with McCoy and Macintosh Adult Laryngoscopes on the Cormack–Lehane Grade in Patients with Simulated Restricted Neck Mobility—A Randomized Control Trial

Abstract Background The paucity in round-the-clock availability of advanced tools like flexible bronchoscopes and video laryngoscopes makes it preferable to have alternative easily available gadgets for securing the airway in patients with cervical spine injuries where head and neck movements must be strictly avoided. This study compared the paraglossal technique of Miller blade insertion with the McCoy and Macintosh laryngoscope blades on the Cormack and Lehane grading (CLG) in patients with simulated restricted neck mobility. Methods We randomized 90 patients undergoing general anesthesia to be intubated either using Miller blade (Group-Mill), McCoy blade (Group-McCoy), or Macintosh blade (Group-Mac) following neck restriction using a soft cervical collar. CLG grade, the number of intubation attempts, use of bougie, intubation time, and hemodynamic parameters were noted. Nonparametric data were compared using the chi-squared test and parametric data using one-way analysis of variance. Results Group-MILL had significantly higher patients with Grade-1 CLG compared to Group-Mac (p = 0.02). The number of attempts, use of bougie, and intubation time were, however, comparable among the three groups. The hemodynamic parameters at intubation were not significantly different among the groups. Conclusion In adult patients with simulated restricted neck, the Miller laryngoscope blade, despite providing a better laryngeal view, showed no benefit in decreasing the intubation time when compared to the McCoy or Macintosh blades.

Effortful Swallow Maneuver and Modifications on Swallow Dynamics in Healthy Adults

Introduction: Effortful swallow (ES) is a widely used technique in dysphagia management, believed to strengthen oropharyngeal muscles and enhance swallowing safety and efficiency. Although its impact on the oral phase of swallowing is well documented, its effects on pharyngeal swallowing physiology remain inconsistent. This study aimed to elucidate the effects of ES on swallowing kinematics and timing, addressing existing inconsistencies in the literature. Methods: This study involved 22 healthy adults using archived videofluoroscopic swallowing studies. Participants performed three swallow trials of 10 mL puree under regular conditions and with the ES maneuver. The outcome measures comprised swallow timing and kinematic measures. Swallow timing parameters included time to maximum hyoid and laryngeal excursion, laryngeal vestibule closure (LVC) reaction and duration, pharyngeal constriction duration, pharyngoesophageal segment (PES) opening duration, and swallow duration. Swallow kinematic parameters encompassed hyoid and laryngeal excursions, pharyngeal constriction ratio, and maximum PES width. All variables were analyzed via videofluoroscopy. Paired t tests were used to examine the effect of ES on each outcome measure, with a significance threshold set at p < 0.004. Results: The ES maneuver significantly increased the duration of LVC, pharyngeal constriction, PES opening, and overall swallow duration. It also improved the pharyngeal constriction ratio. However, there were no significant changes in hyoid and laryngeal excursions. Submental muscle activity showed a notable increase during ES. Conclusion: The study demonstrates that ES can effectively modify certain temporal and kinematic aspects of swallowing, particularly by prolonging key phases and enhancing pharyngeal constriction. These findings suggest the potential utility of ES in dysphagia rehabilitation, especially in cases that require prolonged pharyngeal constriction, LVC, and PES opening. However, the limited impact on hyoid and laryngeal excursions along with LVC reaction time indicates that ES may not address all aspects of dysphagia. The findings highlight the need for tailored therapeutic approaches in dysphagia management, considering individual physiological impairment profiles.

Influence of physical and water quality parameters on residual chlorine decay in water distribution network

Chlorine is the most common disinfectant in drinking water distribution practice. World Health Organization recommends 0.2–5.0 mg/l of residual chlorine in drinking water. This paper analyzed influence of physical and water quality parameters on chlorine decay in drinking water distribution. Principal component analysis, directed tree and regression were used to investigate influence of these parameters on chlorine from water treatment plant to water consumption points. Results show that initial chlorine, electrical conductivity and distance explain 62 % of chlorine decay with estimated error of 0.045 mg/l. The decision-tree feature importance scores of initial chlorine and electrical conductivity were 0.47 and 0.23 respectively. The combined feature importance scores of physical parameters of distance (0.09), pipe diameter (0.06), flow velocity (0.03), pressure (0.02) and travel time (0.046) were less than that for initial chlorine concentration (0.47) alone. These results show that conventional chlorination at water treatment plants removes largely fast inorganic reactants leaving traces of slow organic reactants as the dominant secondary contaminants in water distribution system. The key policy recommendation is to use water quality parameters more than physical parameters in order to enable water utility managers maintain residual chlorine within safe public health standards.

Methodology for determining the design parameters of combined type plasma-chemical reactor for gasification of carbon-containing raw materials

The paper shows the advantages of combined type reactors for plasma-chemical allothermic processes of carbon-containing raw materials gasification. The methodology for determining the design parameters of combined type plasma-chemical reactor for gasification of carbon-containing raw materials is developed. Analytical dependences for determination of time and constructive parameters of the combined type plasma-chemical reactor are established. Dependences contain interrelation between the main technological parameters of the process of thermo-conversion of carbon-containing raw materials taking into account thermochemical reactions. Dependences of constructive parameters of reaction zone of combined type plasma-chemical reactor for steam plasma gasification of carbon-containing media are obtained. It is established that at steam gasification of carbon-containing raw materials with the maximum particle size of 150 microns and the temperature in the reaction zone of 5000 K the volume of the reaction zone depends on the productivity of carbon-containing raw materials, which has a significant effect on the design parameters of the reaction zone.

Flow of magnetohydrodynamic blood-based hybrid nanofluids with double diffusion in the presence of Riga plate for heat optimization and drug applications

In a recent study, researchers investigated the flow behavior of Casson Hybrid nanofluids (HNFs) combination of single and multi-walled carbon nanotubes (SWCNTs), (MWCNTs) on a Riga plate for drug delivery applications. The study found that the Casson HNFs exhibited non-Newtonian behavior on the Riga plate, with the presence of nanoparticles causing an increase in viscosity and shear-thinning behavior. This rheological behavior is favorable for drug delivery applications as it improves the stability and dispersion of drug particles in the fluid. The similarity equations of the flow problem are easily tackled with the homotopy analysis method (HAM) built on fundamental homotopy mapping. In high-speed flows, Riga actuators are expected to achieve the requirements, since HNF is enhanced by modified Hartmann numbers. As the Eckert number, heat generation/absorption parameter, and thermal relaxation time parameter decrease the temperature, thermal transport increases. Furthermore, with the increments in paramount parameters, the skin friction coefficient and heat transfer rate are remarkably meliorated under higher modified Hartmann number. Furthermore, the study also found that the Casson Hybrid nanofluids showed enhanced heat transfer properties on the Riga plate, which is beneficial for localized drug delivery applications that require precise temperature control.

Design and implementation of intelligent anti-hail net system based on STM32

This research is dedicated to designing an intelligent anti-hail net system using STM32 microcontroller. The system integrates sensing technology and communication modules to monitor various environmental parameters in real time, analyzes the data through the STM32 processor, and realizes real-time intelligent control of the anti-hail network. The system design focuses on the collaboration of hardware and software, taking full advantage of the high performance and low power consumption of the STM32 microcontroller. Through actual tests, the feasibility of the system in improving hail prevention effect, real-time performance and automation was verified, providing reliable guarantee for agricultural production. This research provides a useful reference for the application and promotion of smart agricultural technology.

Short-Term Panax Ginseng Extract Supplementation Reduces Fasting Blood Triacylglycerides and Oxygen Consumption during Sub-Maximal Aerobic Exercise in Male Recreational Athletes.

Ginseng, a popular herbal supplement among athletes, is believed to enhance exercise capacity and performance. This study investigated the short-term effects of Panax ginseng extract (PG) on aerobic capacity, lipid profile, and cytokines. In a 14-day randomized, double-blind trial, male participants took 500 mg of PG daily. Two experiments were conducted: one in 10 km races (n = 31) and another in a laboratory-controlled aerobic capacity test (n = 20). Blood lipid and cytokine profile, ventilation, oxygen consumption, hemodynamic and fatigue parameters, and race time were evaluated. PG supplementation led to reduced total blood lipid levels, particularly in triacylglycerides (10 km races -7.5 mg/dL (95% CI -42 to 28); sub-maximal aerobic test -14.2 mg/dL (95% CI -52 to 23)), while post-exercise blood IL-10 levels were increased (10 km 34.0 pg/mL (95% CI -2.1 to 70.1); sub-maximal aerobic test 4.1 pg/mL (95% CI -2.8 to 11.0)), and oxygen consumption decreased during the sub-maximal aerobic test (VO2: -1.4 mL/min/kg (95% CI -5.8 to -0.6)). No significant differences were noted in race time, hemodynamic, or fatigue parameters. Overall, PG supplementation for 2 weeks showed benefits in blood lipid profile and energy consumption during exercise among recreational athletes. This suggests a potential role for PG in enhancing exercise performance and metabolic health in this population.

Why Sentiment Analysis-Based Metrics are Essential for Measuring Channel Performance on YouTube: An Experimental Study

YouTube is a universal social medium that lets its users share videos and write comments on shared videos. Comments of the users on Youtube videos can be useful for YouTube channel owners, and it is worth analyzing them in terms of sentiment. The rate of like/dislike on a YouTube video is not sufficient for estimating the attitude of users towards it. This study proposes a three-step method for this attitude: In the first step, a sentiment analysis task is applied to the user comments on the videos of the YouTube channel "iJustin". In the second step, a new metric named Sentiment Index (SI) has been proposed and the Sentiment Indexes of the videos have been calculated. In the third step, an analysis is performed to show if the SI metric is time-independent. As a result, it was seen that most of the comments left on the videos (89%) have been written within the first 30 days after the video was published. Our experiments revealed that comments left more than 30 days after publishing the videos change the average SI values of the videos by only 0.4%, and in this respect, the SI metric is negligibly affected by the time parameter.

Physical analysis and thermal case of magnetized fluid flow and heat transfer via stretchable cylinder: Hall impact and entropy generation

The study of fluid flow in cylindrical shapes under the effect of electric fields is of utmost importance because of its vast applications in industrial, agricultural, and biomedical domains, as well as in drilling machines, equipment, transport brakes, and vehicles. The purpose of this research is to analyze the influence of Hall impacts, slippage effects, and thermal relaxation time on the magnetohydrodynamic flow near an extended cylinder or flat plate. An assessment of entropy generation is carried out. Results are determined by the process of elongating a planar surface and a cylindrical object. The velocity field and entropy production are greater in the case of a stretched cylinder compared to a stretching flat plate. The choice of an appropriate stretching surface may have an impact on the thermal conductivity of the boundary layer. Velocity, temperature, and entropy are influenced by several factors including the Eckert number, thermal relaxation time, transverse curvature, magnetic field, Hall effect, molecular slip, and mixed convection parameters. These characteristics influence the movement of fluid, the transfer of heat, the measure of disorder (entropy), and the Bejan number. The variables mentioned cause changes in skin friction and Nusselt values. The Hall effect has advantages in reducing friction and enhancing heat transfer in industrial and technical processes.

Wistar Rat Pneumonia Model: Bacterial Dose, Incubation Time, Inoculation Technique and Laboratory Examination Parameters

Background: Making animal models is important before research involving human diseases. This study aimed to prepare animal models of pneumonia through the intranasal technique with a focus on the effect of the dose of Klebsiella pneumoniae (Kp) and incubation period on diagnosing pneumonia. We use male Wistar rats 6-8 weeks, 200-300 grams as much as 64 that appropriate the inclusion and exclusion criteria. Methods: The research method was the pre-posttest group design to prove the creation of a Wistar Rat pneumonia model based on the dose and incubation time for diagnosing Pneumonia. There were On days 1 to 5, each of the 4 rats underwent a thoracic radiography (CXR) 64 rats model divided into 4 groups, N: 4 healthy; T1, T2 and T3 groups of rats were inoculated with 25, 50 and 100 µL of 0.5 McFarland intranasal Kp solution. A group of rats was then sacrificed, followed by retrobulbar blood collection (leukocyte-neutrophil count) and bacterial count/NaCL and lung tissue was taken histopathology and bacterial count/Brain Heart Infusion (BHI). The independent variables were the dose of Klebsiella pneumoniae (Kp) and the incubation period. The statistical analysis of the correlation of dose of bacteria, incubation time with leucocyte and neutrophils used One Way Anova, Kruskal Wallis if the data were abnormally distributed. The correlation is the dose of Kp, incubation period with chest radiography, histopathology, blood bacterial count (BBC) and pulmonary bacterial count (PBC) using the Chi-square test. Result: The results showed that the dose of Kp was positively and significantly correlated with the neutrophil count (p=0.030) and the histopathology (p=0.000). Similarly, the incubation period was positively and significantly correlated with chest radiography (p=0.000) and histopathology (p=0.013).

An Improved Fourier-Based Method for Path Generation of Planar Four-Bar Linkages without Prescribed Timing

Four-bar linkages are critical fundamental elements of many mechanical systems, and their design synthesis is often mathematically complicated with iterative numerical solutions. Analytical methods based on Fourier coefficients can circumvent these difficulties but have issues with time parameters assignment for path generation without prescribed time in previous studies. In this paper, an improved Fourier-based point-to-point combination method is presented, which generates more points by Fourier approximation and assigns the time parameters to the given points while allowing discarding solutions with order defects. This method relies on the Fourier coefficients, improving the accuracy of synthesis solutions, and simplifying the computational procedure. Time parameters are assigned directly to the given points, which avoids the complex calculations to find intersection points in the given path, eliminates combinations that would lead to solutions with order defects, and simplifies the assessment process of synthesis results. The parameters obtained by the point-to-point combination method can be used as the parameters of the input dyad, skipping the first set of design equations for faster calculation. Several examples are presented to demonstrate the advantages of the proposed synthesis method, which is easy-understanding, computationally efficient, and yields more accurate solutions than available synthesis methods.

Online Estimation of Three-Phase Induction Motor Parameters Using an Extended Kalman Filter for Energy Saving

In this paper, the online estimation of three-phase induction motor parameters using an extended Kalman filter for energy saving is proposed. The optimal value of the stator current on the d-axis is calculated to obtain the minimum power loss. Accurate motor parameters are required to calculate the optimal stator current value for energy saving. Hence, to estimate motor parameters in real time, an online estimator known as the extended Kalman filter is applied. The energy consumption results for the motor using the proposed approach (estimated parameters with extended Kalman filter) are compared with those obtained using the conventional approach and energy saving (fixed parameters without parameter estimation) approach. As revealed by the comparison results from implementation in a laboratory, the proposed approach can provide minimum power losses for the three-phase induction motor drive, and the maximum energy-saving percentage is 60.18% compared with using the conventional drive approach.

Experimental Analysis of Smart Drilling for the Furniture Industry in the Era of Industry 4.0.

The fact is that hundreds of holes are drilled in the assembly process of furniture sets, so intelligent drilling is a key element in maximizing efficiency. Increasing the feed rate or the cutting speed in materials characterized by a higher machinability index is necessary. Smart drilling, that is, the real-time adjustment of the cutting parameters, requires the evolution of cutting process variables. In addition, it is necessary to control and adjust the processing parameters in real time. Machinability is one of the most important technological properties in the machining process, enabling the determination of the material's susceptibility to machining. One of the machinability indicators is the unit cutting resistance. This article proposes a method of material identification using the short-time Fourier transform in order to automatically adjust cutting parameters during drilling based on force signals, cutting torque and acceleration signals. In the tests, four types of wood-based materials were used as the processed material: medium-density fiberboard, chipboard, plywood board and high-pressure laminate. Holes with a diameter of 10 mm were drilled in the test materials, with variable feed rate, cutting speed and thickness of cutting layer. An innovative method for determining the value of unit cutting resistance was proposed. The results obtained were used to determine the machinability index. Based on the test results, it was shown that both the selected signal measures in the time and frequency domains and the unit cutting resistance are constant for a given material of a workpiece and do not depend on the drilling process parameters. In this article, the methodology is proposed, which can be used as an intelligent technique to support the drilling process to detect the material being machined using data from sensors installed on the machine tool. The work proposes the fundamentals for material identification based on the analysis of force signals and the magnitude of force derivatives. The proposed methodology shows effectiveness, which proves that it can be used in intelligent drilling processes. Hybrid wood-based material structures consisting of different materials are becoming more and more common in building structures for strength, economic and environmental reasons. Due to the difference in the machinability of interconnected materials, cutting parameters must be optimized in real time during machining. Currently, with the rapid development of Industry 4.0, the on-line identification of parameters is becoming necessary to improve the process flow in industrial reality. The proposed methodology can be used as an intelligent technique to support the drilling process in order to detect the material being processed using data from sensors installed on the machine tool.

Pre-Stack Fracture Prediction in an Unconventional Carbonate Reservoir: A Case Study of the M Oilfield in Tarim Basin, NW China

The reservoir of the M oilfield in Tarim Basin is an unconventional fracture-cave carbonate rock, encompassing various reservoir types like fractured, fracture-cave, and cave, exhibiting significant spatial heterogeneity. Despite the limited pore space in fractures, they can serve as seepage pathways, complicating the connectivity between reservoirs. High-precision fracture prediction is critical for the effective development of these reservoirs. The conventional post-stack seismic attribute-based approach, however, is limited in its ability to detect small-scale fractures. To address this limitation, a novel pre-stack fracture prediction method based on azimuthal Young’s modulus ellipse fitting is introduced. Offset Vector Tile (OVT) gather is utilized, providing comprehensive information on azimuth and offset. Through analyzing azimuthal anisotropies, such as travel time, amplitude, and elastic parameters, smaller-scale fractures can be detected. First, the original OVT gather data are preprocessed to enhance the signal-to-noise ratio. Subsequently, these data are partially stacked based on different azimuths and offsets. On this basis, pre-stack inversion is carried out for each azimuth to obtain the Young’s modulus in each direction, and, finally, the ellipse fitting algorithm is used to obtain the orientation of the long axis of the ellipse and the ellipticity, indicating the fracture orientation and density, respectively. The fracture prediction results are consistent with the geological structural features and fault development patterns of the block, demonstrating good agreement with the imaging logging interpretations. Furthermore, the results align with the production dynamics observed in the production wells within the block. This alignment confirms the high accuracy of the method and underscores its significance in providing a robust foundation for reservoir connectivity studies and well deployment decisions in this region.

The NANOGrav 12.5-Year Data Set: Dispersion Measure Misestimations with Varying Bandwidths

Noise characterization for pulsar-timing applications accounts for interstellar dispersion by assuming a known frequency dependence of the delay it introduces in the times of arrival (TOAs). However, calculations of this delay suffer from misestimations due to other chromatic effects in the observations. The precision in modeling dispersion is dependent on the observed bandwidth. In this work, we calculate the offsets in infinite-frequency TOAs due to misestimations in the modeling of dispersion when using varying bandwidths at the Green Bank Telescope. We use a set of broadband observations of PSR J1643−1224, a pulsar with unusual chromatic timing behavior. We artificially restricted these observations to a narrowband frequency range, then used both the broad- and narrowband data sets to calculate residuals with a timing model that does not account for time variations in the dispersion. By fitting the resulting residuals to a dispersion model and comparing the fits, we quantify the error introduced in the timing parameters due to using a reduced frequency range. Moreover, by calculating the autocovariance function of the parameters, we obtained a characteristic timescale over which the dispersion misestimates are correlated. For PSR J1643−1224, which has one of the highest dispersion measures (DM) in the NANOGrav pulsar timing array, we find that the infinite-frequency TOAs suffer from a systematic offset of ∼22 μs due to incomplete frequency sampling, with correlations over about one month. For lower-DM pulsars, the offset is ∼7 μs. This error quantification can be used to provide more robust noise modeling in the NANOGrav data, thereby increasing the sensitivity and improving the parameter estimation in gravitational wave searches.

Lie group analysis on EMHD Jeffrey nanofluid flow with exponential heat source: Heat transfer optimization using RSM

The present research examines the behavior of a Jeffrey nanofluid flow across a stretching sheet under the effect of electric and magnetic fields. It comprises the Buongiorno model as well as an exponential heat source. The impact of chemical reaction has also been taken into consideration. While assuming no mass flux, the study considers boundary conditions for thermal convection and velocity slip. Lie group transformations are employed to transform the set of governing equations into a dimensionless system and later simulated using the finite difference scheme. It is found that the velocity profile rises as the Deborah number is enhanced whereas the ratio of relaxation to retardation time parameter has an inverse effect on the velocity profile. It is noted that per unit change in the Deborah number descends the drag coefficient by 31.29%. In this study, the response surface methodology and sensitivity analysis have been conducted by choosing heat transport as the dependent variable and the electric-field parameter ( 0.01 ≤ E ≤ 0.03 ) , exponential heat source parameter ( 0.02 ≤ Qe ≤ 0.06 ) , and Biot number ( 0.15 ≤ Bi ≤ 0.25 ) as the independent variables. The Nusselt number escalates when the Bi number is increased and drops as the E values are raised. In the instance of the Biot number, the Nusselt number exhibits the maximum sensitivity.