Analysis Of Parameters Research Articles

Design of a high-speed MCML D-Latch at 0.6 V in 45 nm CMOS technology

Metal oxide semiconductor (MOS) current mode logic (MCML) is generally preferred for high-speed circuit design. In this paper, a novel low voltage folded (LVF) MCML D-Latch is designed. The existing topologies of the MCML D-Latch consume more power and operate at 1 V. The proposed D-Latch can operate at 0.6V with better delay and power management. MCML circuits minimize delay and perform fast operations, hence it can be used in high-frequency applications. The proposed LVF MCML D–Latch is analyzed with the parameters such as power, delay, power delay product and output noise using cadence virtuoso in 45 nm complementary metal oxide semiconductor (CMOS) technology at a voltage of 0.6 V and a temperature of 27 °C. The proposed technique achieves 62.11% of power reduction, transient response speed improved by 51.23% and noise cancellation becomes 26.13% improvement over the existing circuit. It also achieves 96% of output swing which is more efficient compared to others. Finally, the parametric analysis is performed with different temperatures to verify the stability of the proposed circuit. From the simulated results, it is clear that the proposed LVF MCML D-Latch provides better performance in high-speed phase locked loop (PLL) applications.

Evaluation of cold plasma activated water composite reagent on kiwifruit plants with bacterial canker and the external qualities of kiwifruit after spray treatment

This study aimed to investigate the efficacy of cold plasma activated water (PAW) and its complex solution (PKC) in conjunction with kasugamycin copper oxychloride wettable powder (KC) against kiwifruit bacterial canker (KBC) caused by Pseudomonas syringae pv. actinidiae (PSA). Through morphological identification and 16S rDNA sequence analysis, Pantoea agglomerans was identified as the pathogen responsible for KBC in the 'Bairui' orchard. Results indicated that PKC exhibited the highest effectiveness in controlling KBC, particularly on mildly (II) infested plants, with a remarkable reduction of 63.64% in PKC II disease index and a control efficiency of 38.64%. Additionally, the application of PKC significantly increased fruit yield, improved fruit weight, and enhanced fruit morphology, resulting in a more uniform and refined fruit shape. Analysis of fruit skin conformational parameters revealed that KBC-affected fruit exhibited reduced hardness and brittleness, increased toughness, and thinner skin. These findings are pivotal for developing effective strategies to further prevent and manage KBC outbreaks. In future studies, further investigations could focus on elucidating the mechanism of action of PAW in complex solution with copper-based pesticides and the potential mechanism of inactivation of PSA.

CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the plane. Leveraging cell continuity in consecutive -stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process. The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.

Advancing hydrogen storage predictions in metal-organic frameworks: A comparative study of LightGBM and random forest models with data enhancement

The escalating consumption of fossil fuels has given rise to a substantial upsurge in greenhouse gas concentrations and global temperatures, which, in turn, has triggered severe climate-related consequences. The critical imperative to reduce CO2 emissions and combat global warming has spurred extensive investigations into clean energy alternatives, with hydrogen emerging as a compelling zero-emission energy source. As a pivotal component of clean energy strategies, hydrogen requires designing compact, lightweight, and efficient storage systems. This study focuses on the development and evaluation of machine learning models for predicting the efficiency of Metal-Organic Frameworks (MOFs) in hydrogen storage, a key aspect of advancing clean energy technologies. MOFs, a class of nanoporous materials, show remarkable potential for hydrogen storage due to their high surface area and porosity. However, selecting the most suitable MOF for this application from a vast array of possible structures is a daunting task. In this context, machine learning algorithms offer an efficient alternative for predicting MOF suitability by considering their structural and chemical properties. We used ensemble learning methods, specifically Light Gradient Boosting Machine (LightGBM) and Random Forest (RF), to predict hydrogen uptake of MOFs based on a dataset of 219 experimentally tested samples. Two modeling scenarios were considered: one using the entire dataset, and the other involving strategic data pre-processing, including outlier removal and feature engineering. The results demonstrate that the measures taken to refine the dataset significantly enhance the predictive performance of the developed models, reducing prediction errors and improving overall goodness of fit. Specifically, the Mean Absolute Error (MAE) values for both the LightGBM and random forest models were reduced from 0.48 and 0.94, respectively, to 0.16 for both models, and the coefficients of determination (R2) increased substantially from 0.84 and 0.72 to 0.95, in both cases. Moreover, feature importance analysis unveiled that pressure-related features make the most significant contributions to the formation of tree ensembles during the model training process. A parametric sensitivity analysis was conducted revealing that H2 uptake in MOFs is most sensitive to changes in adsorption enthalpy, followed by surface area and temperature, while showing lower sensitivity to variations in pressure, consistent with established literature. These results underscore the pivotal role of data enhancement methods in refining machine learning models and can be instrumental in accelerating the development and optimization of MOF materials for clean energy applications.

Population viability analysis on the Iranian endangered goat breeds

Because of the downward trend of breeding goats and flocks, habitat loss, using other breeds in reproduction, and the presence of survival-threatening factors, Iranian goat breeds, including Markhoz, Adani, and Najdi, are considered endangered populations. This research aims to investigate the current status and provide the necessary information to conserve these three endangered populations. For this purpose, the census data and the required parameters were collected from the available resources and flocks during the years of the project implementation. Then, two scenarios, the past and future dynamics of the population assuming continuing existing conditions, were simulated using the population viability analysis (PVA) method. Finally, the sensitivity analyses of parameters affecting the viability criteria were done. PVA was conducted using the Vortex simulation program version 10.5.6. The past dynamics simulation of the population showed that the biological parameters and assumptions used in the model have valid and reliable values and frequencies, and they can be used in the simulation of different management scenarios. Based on this scenario, the inbreeding rates (∆F) for the Markhoz and Adani populations have reached above the critical level of 0.5%. The future dynamics simulation of the population showed that the process of increasing inbreeding and decreasing genetic diversity would accelerate, and the breeds' extinction probability would start in 2026, 2033, and 2031 for Markhoz, Adani, and Najdi, respectively. The mean time to the first extinction was also 15.4 ± 2.53, 26.68 ± 3.75, and 13.96 ±1.78 years, respectively. The sensitivity analyses indicated that adult does overharvest, the frequency of feed limitation, and competition with other breeds had the highest effect on the population viability criteria of the investigated breeds. Markhoz, Najdi, and Adani goats need urgent conservation measures. The results obtained in this research may prepare a suitable framework for providing conservation programs.

Parametric Analysis of the Flexural Bearing Capacity and Ductility of Hybrid Steel I-Section Beams

Parametric Analysis of the Flexural Bearing Capacity and Ductility of Hybrid Steel I-Section Beams

A resolved CFD-DEM investigation into sand production under water flooding in unconsolidated reservoir

Excessive sand production in the wellbore can impede oil production from unconsolidated reservoirs. The study reports an investigation of numerical simulation of sand production in oil-water two-phase flow. The interaction between fluid and particles is achieved by coupling the discrete element method (DEM) with resolved computational fluid dynamics (CFD). By harnessing the advantages of the method, the numerical model can capture the movement of particles and the changes in fluid field at a scale smaller than fine particles. The model reveals the water flooding process in the granular matrix and effectively visualizes the microscopic mechanisms of particle migration. The results indicate that the model with water flooding exhibits higher produced mass compared to the model without water flooding. Parametric analysis shows that there is a critical fines content, which leads to the maximum sand production. With the increase of viscosity and the decrease of interfacial tension, the sand production increases.

Pressure effects on the structural, electronic, elastic, optical, and vibrational properties of YMg intermetallic compounds: a first-principles study

The properties of YMg in B2 structure have been comprehensively analysed using the first-principles plane-wave pseudopotential method. Specifically, the structural, electronic, elastic, vibrational, and optical properties were investigated using the generalized gradient approximation (GGA) method in the context of density functional theory. The Vienna ab initio simulation package (VASP) was utilized for these calculations. The computed lattice parameter (3.803 Å) and bulk modulus (41.33 GPa) are consistent with the earlier data on ambient pressure. The electronic band structure and energy-dependent density of states reveal the metallic nature of the titled compounds. The Born stability requirements confirmed the mechanical stability. The analysis of Pugh’s and Poisson’s ratios and Cauchy’s pressure reveals that YMg is ductile under the pressures in consideration. According to several anisotropy indices, the compound is noticeably anisotropic both in ambient and under pressure. Our investigation includes an analysis of several fundamental mechanical parameters of the material, including the bulk modulus, the pressure derivative of the Zener anisotropy factor, Poisson’s ratio, isotropic shear modulus and Young’s modulus with a particular focus on their dependence on pressure. We have determined that the elastic constants obtained remain mechanically stable, satisfying the Born Stability conditions even at high pressures of up to 60 GPa. To explore the dynamic stability of YMg, we analysed the material’s phonon dispersion curves. The examined compound displays stability under dynamic conditions from 0 GPa to 30 GPa, as evidenced by its positive vibration frequencies. However, this stability is not sustained under higher pressure, as the compound becomes unstable after 30 GPa to 70 GPa. The electronic band structure and density of states diagrams demonstrate YMg’s metallic properties. At atmospheric pressure (0 GPa), the total density of states (TDOS) near the Fermi level is approximately 1.63 states/eV, with pressure application reducing DOS. The dielectric function, refractive index, and energy loss spectra are examined within the 0–20 eV energy range. YMg exhibits its highest absorption between 4 and 11 eV. The peak optical conductivity is observed around 0.78 eV (equivalent to 1589.5409 nm), while the most significant energy loss occurs at 11.90 eV, roughly corresponding to 2.8 Hz in the ultraviolet spectrum. Moreover, we extensively analyzed the material’s phonon thermodynamic and optical properties, providing insights into its behavior under various conditions. The outcomes acquired at zero pressure are generally coherent with the current theoretical values.

Bearing Behavior of Engineered Cementitious Composite and Ultra-High-Performance Concrete Filled-In Double Steel Tubular Composite Columns Subjected to Eccentrical Load

To study the eccentric compression mechanical properties of ECC and UHPC filled-in double steel tubular (EUFDST) composite columns, 35 full-scale EUCFDST composite column specimens were designed by ABAQUS software with the slenderness ratio (λ), UHPC cylinder compressive strength (fcu), inner and outer steel tubular strength (fy1, fy2), inner and outer steel tubular thickness (t1, t2), inner and outer steel tubular diameter ratio (Ω), eccentricity (e), and fiber content (γ) as the main parameters. By comparison with the simulation of the existing test, the correctness of the finite element modeling is verified. The parameter analysis of 35 full-scale EUFDST composite columns was carried out to obtain the eccentric load-mid-span deflection curve of the specimens. The failure mechanism, ductility coefficient, and stiffness degradation of the composite columns under different parameters were analyzed, and the section of the composite column was verified to satisfy the plane section assumption. The variation trend of maximum load-bearing capacity and the ductility of composite columns under different parameter conditions was obtained. By introducing the eccentricity correction coefficient and slenderness ratio correction coefficient, the calculation equation of the eccentric maximum load-bearing capacity of EUCFDST composite columns is statistically regressed, which provides a basis for the practical use of these columns.

Optimization of Support and Relief Parameters for Deep-Buried Metal Mine Roadways

The management of rock mass deformation in high-stress roadways is a pivotal aspect of deep geotechnical engineering. Given the fruitful outcomes of research in rock mechanics regarding traditional confining pressure control methods, scholars have increasingly turned their attention to exploring pressure-relieving techniques, including borehole pressure relief and blasting pressure relief. However, there is limited research on pressure relief methods for deep-buried hard rock tunnels. This article commences with an overview of pressure relief in the roadway and conducts a detailed study on the parameters and methods of pressure relief in the roadway. To address safety and mining efficiency challenges, such as severe deformation leading to support failures, this study conducted a parameter analysis using the Sanshandao Gold Mine as a case study. Based on existing support methods, a strategy for arranging pressure relief roadways at varying distances from the main roadway is proposed, significantly enhancing the stress environment there. Numerical simulation software was employed to model two scenarios: (1) excavating the pressure relief roadway, main roadway, and maintenance roadway simultaneously and (2) first excavating the pressure relief roadway, followed by the main roadway and the maintenance roadway simultaneously. Simulation results indicated that the first pressure relief approach outperforms the second. The optimal position for both pressure relief roadways is 15 m from the main roadway, resulting in maximum deformation of the main roadway within 100 mm. These findings align with on-site stress monitoring data and satisfy safety production criteria. The research offers a theoretical foundation for similar pressure relief techniques in deeply buried, high-stress roadways.

The Impact of Upstream Static Deformation on Flow Past a Cylinder/Flare

Reynolds-averaged Navier–Stokes simulations are performed for supersonic turbulent flow over a cylinder/flare with upstream surface distortion representative of structural deformation induced via fluid–structural and fluid–thermal–structural behavior. Broad parametric analysis is carried out through the generation of Kriging-response surfaces from a database of general simulations. A posteriori simulations are then carried out at parametric combinations that correspond to extrema in the Kriging response surfaces to gain deeper insights into the interaction between the surface distortion and flow responses. Upstream distortions tend to decrease, rather than increase, the peak pressure and heat flux loads on the flare compared to an undeformed cylinder. Furthermore, decreases in these quantities reach up to O(10%) compared to up to O(1%) for increases. Integrated quantities over the flare are relatively insensitive to upstream distortion. The corner separation length is the most sensitive quantity to upstream distortion, with protrusions tending to increase the separation length and recessions reducing the separation length. Modifications in the separation length of up to 40% are observed. Reductions in peak loads tend to correspond to increases in the corner separation length. The movement of the surface distortion relative to the corner indicates a negligible impact beyond 1.5 distortion lengths from the corner, and the largest impact on the corner separation length occurs when distortion is directly adjacent. These results are an important step toward understanding and quantifying the impact of surface deformations on downstream components.

Seismic analysis of gravity dam-foundation systems using stochastic spectral finite element method

Seismic analysis of dam-foundation systems is inherently complex due to uncertainties in material properties. This study investigates the effects of material randomness and heterogeneity on the seismic response of gravity dam-foundation systems using the stochastic spectral finite element method (SSFEM) based on the Karhunen Loève expansion and the polynomial chaos expansion. The Pine Plane dam is taken as an analysis example. First, the appropriate Karhunen Loève expansion modes and polynomial chaos order are determined for SSFEM by comparing them with the Monte-Carlo simulations. Subsequently, the seismic response of the dam is analyzed in the stochastic and deterministic models, respectively. Results indicate that material randomness and heterogeneity may reduce the seismic response of gravity dams, and the deterministic model may overestimate dynamic responses. Subsequently, the parametric analysis of the correlation length, which measures the spatial correlation between variables in different positions and indicates the size of heterogeneity material patches, is conducted. It is demonstrated that the correlation length would not significantly affect the mean responses, but a larger correlation length leads to greater dispersions in responses. Finally, the effects of randomness in the foundation are investigated. The heterogeneities in the foundation affect the response of the dam in the high-frequency range. Therefore, the uncertainty in material properties should be fully considered in a structural assessment and risk analysis.

Optimizing recombinant antibody fragment production: A comparison of artificial intelligence and statistical modeling.

Maximizing the recombinant protein yield necessitates optimizing the production medium. This can be done using a variety of methods, including the conventional "one-factor-at-a-time" approach and more recent statistical and mathematical methods such as artificial neural network (ANN), genetic algorithm, etc. Every approach has advantages and disadvantages of its own, yet even when a technique has flaws, it is nevertheless used to get the best results. Here, one categorical variable and four numerical parameters, including post-induction time, inducer concentration, post-induction temperature, and pre-induction cell density, were optimized using the 232 experimental assays of the central composite design. The direct and indirect effects of factors on the yield of anti-epithelial cell adhesion molecule extracellular domain fragment antibody were examined using statistical methods. The analysis of variance results indicate that the response surface methodology (RSM) model is effective in predicting the amount of produced single-chain fragment variable (p-value = 0.0001 and R2 = 0.905). For ANN modeling, the evaluation using normalized root mean square error (NRMSE) and R2 values shows a good fit (R2 = 0.942) and accurate predictions (NRMSE = 0.145). The analysis of error parameters and R2 of a dataset, which contained 30 data points randomly selected from the complete dataset, showed that the ANN model had a higher R2 value (0.968) compared to the RSM model (0.932). Furthermore, the ANN model demonstrated stronger predictive ability with a lower NRMSE (0.048vs. 0.064). Induction at the cell density of 0.7 and an isopropyl β-D-1-thiogalactopyranoside concentration of 0.6mM for 32 h at 30°C in BW25113 was the ideal culture condition leading to the protein yield of 259.51mg/L. Under the optimum conditions, the output values predicted by the ANN model (259.83mg/L) were more in line with the experimental data (259.51mg/L) than the RSM (276.13mg/L) expected value. This outcome demonstrated that the ANN model outperforms the RSM in terms of prediction accuracy.

Dual-function of energy harvesting and vibration isolation via quasi-zero stiffness piezoelectric mechanism

Industry 4.0 realizes intelligent interconnection through the sensor group of the Internet of Things. A key challenge is to achieve the self-powering of sensors and stable operation of precision instruments. This paper introduces a dual-functional structure (VIPEH) integrating energy harvesting (EH) and vibration isolation (VI) based on the quasi-zero stiffness (QZS) piezoelectric mechanism. The paper analyzes the nonlinear statics of piezoelectric flexible beams under large deformations and conducts parametric analysis. A nonlinear dynamic model with electromechanical coupling was developed to investigate the impact of mechanical and electrical parameters on the system's dynamic bifurcation behavior, EH, and VI performance. Finally, an experimental setup is created to evaluate the VIPEH's characteristics. Sweep frequency excitation experiments demonstrate that the initial isolation frequency of VIPEH is lower than 1.4 Hz. The important thing is that VIPEH can still power the sensor based on the isolation frequency, and the output power of a single piezoelectric material can reach 3.19 mW. This not only enables the isolation of low-frequency vibrations but also presents a highly promising application for achieving self-powering in sensor clusters within the context of Industry 4.0 and the IoTs.

Evaluating the effect of ambient air temperature on the sustainability aspect of naphtha‐based gas turbine power plant

AbstractThe exergy‐based sustainability indices have been a cause of concern for gas turbine power plant as its performance is very sensitive to air temperature. Hence, the present study evaluates the impact of atmospheric air temperature on exergy sustainability and ecological function of a naphtha‐based gas turbine power plant using EES. The outcome of the study shows that combustion chamber (CC_1) needs more attention compared with other components present, and it has least improvement potential as compared with other components. Further while carrying out parametric analysis with respect to ambient air, it was observed that for a 1.1°C increase in atmospheric air temperature a reduction in sustainability index about 0.66% was observed respectively, for GT_1. Thus, this study established that the power plant's exergy sustainability performance has a negative impact at high ambient air temperatures on exergy sustainability indices.

Combustion Characteristics, Kinetics and Thermodynamics of Peanut Shell for Its Bioenergy Valorization

To realize the utilization of peanut shell, this study investigates the combustion behavior, chemical kinetics and thermodynamic parameters of peanut shell using TGA under atmospheric air at the heating rates of 10, 20, and 30 K/min. Results indicate that increasing the heating rate leads to higher ignition, burnout, and peak temperatures, as observed in the TG/DTG curves shifting to the right. Analysis of combustion performance parameters suggest that higher heating rates can enhance combustion performances. Kinetic analysis using two model-free methods, KAS and FWO, shows that the activation energy (Eα) ranges from 93.30 to 109.65 kJ/mol for FWO and 89.72 to 103.88 kJ/mol for KAS. The data fit well with coefficient of determination values (R2) close to 1 and the mean squared error values (MSE) less than 0.006. Pre-exponential factors using FWO range from 2.19 × 106 to 8.08 × 107 s–1, and for KAS range from 9.72 × 105 to 2.25 × 107 s–1. Thermodynamic analysis indicates a low-energy barrier (≤±6 kJ/mol) between activation energy and enthalpy changes, suggesting easy reaction initiation. Furthermore, variations in enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) upon conversion (α) suggest that peanut shell combustion is endothermic and non-spontaneous, with the generation of more homogeneous or well-ordered products as combustion progresses. These findings offer a theoretical basis and data support for the further utilization of agricultural biomass.

Synoptic-scale Meteorological Patterns Associated with Heavy Rainfall in the Minnesota Region

Abstract Situated in the Upper Midwest, Minnesota’s mid-continental location places it in a climate transition zone between eastern U.S. humid conditions and western semi-arid conditions as well as between warm, moist air from the Gulf of Mexico to the south and drier, polar air to the north. Potential adverse impacts on ecosystems due to changing climate and precipitation patterns, together with ongoing flash flooding risks, indicate that heavy rainfall occurrence and distribution are important considerations for Minnesota. This research used ERA5 reanalysis data with 0.25° grid spacing during May-September 1959-2021 to investigate the synoptic-scale drivers of Minnesota heavy rainfall. The study utilized a neural-network, self-organizing map (SOM) technique to identify sea-level pressure patterns and precipitation patterns associated with heavy rainfall and used composite analysis to explore the relationships between synoptic-scale conditions and environmental parameters during heavy rain hours. Six sea level pressure patterns were identified, three of which represented advancing surface cyclones and accounted for >70% of the heavy rain hours. The spatial distribution of heavy rainfall was represented by six precipitation patterns. The greatest frequency of heavy rain hours was associated with the northwest precipitation pattern, followed by the southwest and southeast patterns. Analysis of the frequency of pressure and heavy rain precipitation pattern pairs revealed that the top five most frequent pairs were associated with advancing surface cyclones and >26% of the total heavy rain hours. Composite analysis of environmental parameters showed favorable conditions related to moisture and lift were associated with heavy rainfall.

Changes in the indicators of hemodynamics and oxygen transport in patients with idiopathic pulmonary arterial hypertension depending on their survival

Background. Idiopathic pulmonary arterial hypertension (IPAH) is a severe disease that affects the vessels of the pulmonary circulation and leads to right ventricular failure and death of patients. Indicators of hemodynamics and oxygen transport play central role in the progression and development of the disease. Objective: to evaluate indicators of hemodynamics, oxygen transport. Materials and methods. The study included 124 patients with IPAH. They were divided into two groups: alive patients (group 1) and those who died (group 2). All of them underwent general clinical examinations, a 6-minute walk test, transthoracic and speckle tracking echocardiography, right heart catheterization, blood gas analysis and calculation of hemodynamic parameters. Results. We calculated and compared the right (RVSWI) (19.93 ± 7.84 vs. 16.47 ± 4.67 g·m·m–2, p = 0.009) and left ventricular stroke work index (LVSWI) (39.47 ± 10.53 vs. 35.92 ± 11.19 g·m·m–2, p = 0.036) and their ratio (RVSWI/LVSWI) (0.59 ± 0.16 vs. 0.46 ± ± 0.13, p = 0.008), right (RVPC) (97.00 ± 2.16 vs. 1.82 ± 1.04 g·m, p = 0.001) and left ventricular pump coefficient (LVPC) (5.36 ± 4.84 vs. 4.41 ± 2.15 g·m, p = 0.04) and their ratio (RVPC/LVPC) (0.54 ± 0.19 vs. 0.44 ± 0.11, p = 0.05) in both groups of patients. Also, we found differences in partial pressure of carbon dioxide (PaCO2) of venous blood (34.5 ± 5.1 vs. 40.2 ± 6.9 mm Hg, p = 0.02), partial pressure of oxygen (PaO2) of arterial blood (90.2 ± 15.1 vs. 78.9 ± 11.2 mm Hg; p = 0.01), arteriovenous oxygen difference (A-vO2) (4.5 ± 1.2 vs. 5.0 ± 0.8 ml/dL, p = 0.02) between both groups. Conclusions. RVSWI, LVSWI, RVSWI/LVSWI, RVPC, LVPC, RVPC/LVPC were significantly different between the groups. The use of the above hemodynamic parameters can help in a deeper understanding of the prognosis in IPAH patients. Performance of oxygen transport indicators (PaCO2, PaO2) and A-vO2 in IPAH patients provides a broader understanding of the status and prognosis of this disease.

Deterioration and imperfection of the ship structural components and its effects on the structural integrity: A review

Abstract The design of ship structural safety is crucial to ensure the ship’s survivability during the operation. Extensive research has been conducted on ship structural components, including box girders, stiffened panels, and plates, beyond the ideal conditions by considering the implication of manufacturing processes, vessel usage, and aging in the form of defects like cracks, corrosion, and imperfections, both locally and globally. Previous research has also explored various methodologies, conditions, and parameters to understand the impact of damages and imperfections on ship structure and strength. However, there is a significant need to bridge the gap in prior research to advance technology and ship structural strength analysis. A comprehensive benchmark study specifically focused on improving ship structural component needs, identifying differences and gaps among existing studies as challenging. This article thoroughly reviews ship structural components, such as box girders, stiffened panels, and plates, while examining the effects of structural defects like corrosion, cracks, and imperfections on ship structural integrity. It synthesizes the influence of various defect parameters, including crack length, angle, position, corrosion severity, pit corrosion, pit diameter, and pit models, using finite element modeling and experimental investigations, particularly emphasizing ship structural components. The comparative analysis of methods and parameters presented in this review will serve as a valuable reference for future investigations and studies related to ship structural strength and design. The article’s contribution is expected to enhance the understanding of ship structural strength, contributing to the sustainability and effectiveness of vessel design in the global maritime industry.

Peri-Ultrasound Modeling to Investigate the Performance of Different Nonlinear Ultrasonic Techniques for Damage Monitoring in Plate Structures

Abstract Peri-ultrasound modeling which is based on nonlocal peridynamics is found and proven to be effective for modeling nonlinear waves propagating and interacting with damages in structures. This work presents the peri-ultrasound modeling to investigate the performance of three commonly used nonlinear ultrasonic (NLU) techniques—wave mixing, higher harmonic generation (HHG), and sideband peak count-index (or SPC-I) for monitoring damages (or cracks) in three-dimensional (3D) plate structures. Cracks can be defined as “thin cracks” and “thick cracks” according to the horizon size mentioned in peridynamics. Peri-ultrasound modeling results reveal that the SPC-I results are consistent with other reported numerical modeling and experimental results available in the literature. However, the modulation indicator (MI) from the wave mixing model only shows consistent trends for thin cracks but not for thick cracks and its reliability is affected by the initial excitation bandwidth. The relative acoustic nonlinearity factor β from the HHG technique shows consistent trends for thick cracks but not for thin cracks. It can be concluded from the obtained parametric analysis results that the SPC-I technique is more robust and reliable for monitoring damages in engineering structures.