Spectroscopic and nonlinear optical investigations of biscinnamyl-sulfone derivatives: Computational and experimental insights.

Novel geometrically asymmetric biscinnamyl-sulfone compounds (6a-c) with donor-π-conjugated spacer-acceptor functionality were successfully synthesized. This was achieved by coupling cinnamaldehyde precursors with 3,3'-diaminodiphenyl sulfone in dry organic solvents, resulting in high yields. Several spectroscopic techniques were employed to identify the derivatives. The absorption spectra of these compounds exhibited broad bands that spanned up to 120 nm, which can be attributed to their extended conjugation systems. In order to explore the electronic transitions of these materials, Time-Dependent Density-Functional Theory (TD-DFT) with EIFPCM solvation mode was utilized. We computationally investigated the static nonlinear optical (NLO) parameters, including dipole moments (µ), polarizability (α), anisotropic polarizability (Δα), first-order hyperpolarization (ß), and second-order hyperpolarization (γ). Although the new structures possess different functional groups, they displayed similar electronic potentials when their molecular electrostatic potentials were plotted. These potentials are crucial in stabilizing the molecules in crystal systems through noncovalent forces such as C-H⋯π stacking and hydrogen bonding. They also provide insights into the electronic assessments and energetics of these individual forces. By estimating the frontier orbitals, we gained an understanding of the intramolecular charge transfer in the compounds. Energy gap values were determined using the orbitals of density of states method and experimentally via the Tauc method. The computational and experimental results were in good agreement. Lastly, we examined the influence of different protic and aprotic solvents on the absorption bands of compound 6b, as an example. This compound showed a significant bathochromic shift of 41 nm upon changing the solvent from acetic acid to dimethyl sulfoxide.

External evaluation of tacrolimus population pharmacokinetic models in adult lung transplant patients: How to enhance the predictive ability of the model?

PURPOSE: Tacrolimus is the cornerstone of current immunosuppressive strategies after lung transplantation. However, its narrow therapeutic range and considerable pharmacokinetic variability pose challenges for individualized treatment. Several tacrolimus population pharmacokinetic (popPK) models have been developed for precision dosing in adult lung transplant patients. However, their applicability across different clinical settings remains uncertain. The aim of this study was to evaluate the external predictability of these models and identify influential factors. METHODS: Published models were systematically retrieved and assessed based on an external dataset of 39 patients (1240 tacrolimus trough concentrations) using three approaches: (1) prediction-based diagnosis using dosing records and patient characteristics; (2) simulation-based diagnosis, with prediction- and variability-corrected visual predictive checks (pvcVPC) and normalized prediction distribution error tests (NPDE); and (3) Bayesian forecasting using one to four observations for posterior predictions. We also investigated the impact of model structure and covariates on predictability. RESULTS: The predictive performance of six published models was externally evaluated, but none demonstrated satisfactory accuracy in prediction- and simulation-based diagnosis. Bayesian forecasting yielded satisfactory results with only one prior observation and optimal predictive performance with 2-3 priors for all included models. The structural model parameterized on plasma tacrolimus concentration outperformed others. Significant correlations were observed between prediction-error and daily tacrolimus dose, postoperative day, and voriconazole co-administration. CONCLUSIONS: The overall predictive performance of all published models was unsatisfactory, making direct extrapolation inappropriate. However, Bayesian forecasting significantly improves predictive performance. Utilizing plasma tacrolimus concentration for parameter estimation can improve the predictive ability of tacrolimus popPK models.

Mechanisms of gait speed changes in middle-aged adults: Simultaneous analysis of magnitude and temporal effects.

BACKGROUND: Middle-aged adults represent the transition between younger and older adults, where some of the characteristic gait differences due to aging begins to surface. However, the gait characteristics of middle-aged adults across the whole gait cycle remains an understudied topic. As speed is a sensitive indicator of health, characterizing the effects of speed on the gait of middle-aged adults and differentiating it from the response of young adults will provide insights into the effects of aging on gait speed modulation mechanisms. RESEARCH QUESTION: What are the mechanisms of gait speed changes that are employed by middle-aged adults, and how are they different from younger adults? METHODS: A cohort of healthy young and middle-aged adults completed 60 second trials at three different speeds. Joint kinematics, kinetics, and surface electromyography data were analyzed and compared between the speed levels and age groups. Statistical Parametric Mapping along with a nonlinear curve registration algorithm was used to simultaneously assess the changes in both magnitude and timing of different metrics. RESULTS: When compared to the younger cohort, the middle-aged cohort had significantly lower ankle range of motion, dorsiflexion moment during loading response and plantarflexion moment during push-off. At the knee joint, the middle-aged adults had significantly lower knee flexion moment during stance. At the hip joint, the middle-aged adults had lower extension moment during terminal stance. SIGNIFICANCE: Time-continuous analysis showed that primary differences due to age were related to decreased joint range of motion and joint moment production capability in the middle-aged adults. Faster walking appears a safe method for middle-aged adults to increase joint range of motion and joint moment expression. However, targeted interventions that focus on improving capability are likely also needed. Suggested targets being improving ankle and knee joint moment capability, and increased range of motion at all joints.

Unveiling the non-linear effects of water and oil on hyperspectral imaging-based characterization of solid waste by hyperspectral unmixing.

Rapid characterization of solid waste using near-infrared hyperspectral imaging (HSI) coupled with machine learning models has been increasingly investigated to replace the traditional time- and labor-intensive methods. However, contamination by waste-derived leachates or other fractions etc., can cause the spectra evolutions and significantly influences the identification performance, which has not been investigated before. The first attempt was made by using hyperspectral unmixing (HU) to extract the endmember components and demonstrate their contributions (abundance) to solid waste, taking the non-linear reflectance changes due to the O-H vibration of water and unclear variation associated with oil and leachates as an example. The HSI spectra of various solid waste components influenced by pure water, oil and three kinds of leachates were acquired. A novel method based on HU models, including multivariate curve resolution with alternating least squares and state-of-the-art autoencoder architectures (deep learning models), was developed to estimate the spectra of endmembers as well as their abundances in individual pixel. Their spatial distribution overview in solid waste was then yielded. The selected models were validated via an independent test data set, with lower spectral angle distance, 12.3° ± 6.5°, indicating the similarity of the predicted endmembers with real components. And the lowest root of mean square error on endmember distribution maps was 0.17. The non-linear liquid's effects by water and oil on spectra variations of solid waste were clearly illuminated. Additionally, the proposed method can extract information from mixed spectroscopic images and generate reconstructed spectra.

Nonlinear Dynamics Research of Ground Undulatory Fin Robot with Flexible Deformation and Frictional Contact.

The unique rigid-flex connection between the fin-rays and fin-surface in a bionic undulatory fin robot endows the fin-surface with both active flexibility and load-bearing capacity, enabling this robot to perform amphibious motions in underwater, terrestrial, and even marshy environments. However, investigations into dynamic modeling problems for the undulatory fin robot, considering the impact of nonlinear deformation and frictional contact on ground locomotion performance, are scarce. Given this, based on the absolute nodal coordinate formulation (ANCF), this paper presents an efficient and accurate nonlinear dynamic model for this robot to elucidate the fin's flexible deformation and motion law. This model considers material, geometric, and boundary nonlinearities, utilizing ANCF thin plate elements and reference nodes to individually describe the fin-surface and fin-rays of the undulatory fin. Then, by using the master-slave technique, a frictional contact formulation for the fin and the ground is proposed. Furthermore, we conduct in-depth research and analysis on the formation and undulatory motion of the undulatory fin, encompassing its static deformation, static contact deformation, and frictional contact motion, and successfully obtain its responses under various conditions. Research indicates that during fin-surface motion, longitudinal sliding or a tendency for sliding at the contact points results in the undulatory fin moving in a crawling gait. The proposed theoretical model correctly captures the fin's complex nonlinear deformations and frictional characteristics and reveals its ground locomotion mechanism, whose effectiveness and superiority are validated through numerical examples and experiments.

The hidden impact: the rate of nicotine metabolism and kidney health.

Objectives: The effects of nicotine metabolism on the kidneys of healthy individuals have not been determined. The nicotine metabolite ratio (NMR) indicates the rate of nicotine metabolism and is linked to smoking behaviors and responses to tobacco treatments. We conducted this study in order to investigated the relationship between nicotine metabolite ratio (NMR) and kidney function. Methods: An analysis of cross-sectional data of adults was conducted using a population survey dataset (National Health and Nutrition Examination Survey Data 2013/2018 of the United States). A weighted multivariate regression analysis was conducted to estimate the correlation between NMR and kidney function. Furthermore, we apply fitting smooth curves to make the relationship between NMR and estimated glomerular filtration rate (eGFR) more visualized. Results: The research included a total of 16153 participants. Weighted multivariate regression analyses adjusted for possible variables showed a negative relationship between NMR and estimated glomerular filtration rate (eGFR).The ß (95%CI) of the regression equation between NMR and eGFR was -2.24 (-2.92, -1.55), the trend testing showed consistent results. NMR is positively correlated with urinary albumin creatinine ratio (uACR), but it is not statistically significant. A stratified analysis found a negative correlation between NMR and eGFR in all age, gender and diabetes subgroups, the results were not statistically significant among Mexican Americans and other races. Notably, each unit rise in NMR corresponded to a 4.54 ml/min·1.73m² lower eGFR in diabetic participants and a 6.04 ml/min·1.73m² lower eGFR in those aged 60 and above. Conclusions: Our study shows that nicotine metabolite ratio is negatively associated with kidney function among most adults. It will be necessary to conduct more well-designed prospective clinical trials in order to determine the exact causal interactions between NMR and kidney function. Specific mechanisms also need to be further explored in basic experiments.

A joint analysis proposal of nonlinear longitudinal and time-to-event right-, interval-censored data for modeling pregnancy miscarriage.

Pregnancy in-vitro fertilization (IVF) cases are associated with adverse first-trimester outcomes in comparison to spontaneously achieved pregnancies. Human chorionic gonadotrophin ß subunit (ß-HCG) is a well-known biomarker for the diagnosis and monitoring of pregnancy after IVF. Low levels of ß-HCG during this period are related to miscarriage, ectopic pregnancy, and IVF procedure failures. Longitudinal profiles of ß-HCG can be used to distinguish between normal and abnormal pregnancies and to assist and guide the clinician in better management and monitoring of post-IVF pregnancies. Therefore, assessing the association between longitudinally measured ß-HCG serum concentration and time to early miscarriage is of crucial interest to clinicians. A common joint modeling approach is to use the longitudinal ß-HCG trajectory to determine the risk of miscarriage. This work was motivated by a follow-up study with normal and abnormal pregnancies where ß-HCG serum concentrations were measured in 173 young women during a gestational age of 9-86 days in Santiago, Chile. Some women experienced a miscarriage event, and their exact event times were unknown, so we have interval-censored data, with the event occurring between the last time of the observed measurement and ten days later. However, for those women belonging to the normal pregnancy group; that is, carrying a pregnancy to a full-term event, right censoring data are observed. Estimation procedures are based on the Stochastic Approximation of the Expectation-Maximization (SAEM) algorithm.

Breathing pattern alteration from weanling to old age in male Sprague-Dawley rats.

Respiratory patterns were investigated in male Sprague-Dawley rats throughout their lifespan, from weanling (1 month) to old age (24 months), under natural conditions. Both inter-breath interval (IBI) and respiratory volume (RV) were examined. Sample entropy suggested increasing irregularity in IBI but decreasing irregularity in RV until 12 months. According to detrended fluctuation analysis, alpha exponent of the IBI showed a bimodal pattern around the value 0.7. From 1 to 15 months, the alpha exponent for RV generally decreased to the value 0.5, but it increased again as the animals neared the end of their lifespan. Cross-sample entropy revealed increasing synchronization between IBI and RV until 12 months, then plateauing. Many measures demonstrated a transition around 12 months, potentially reflecting maturation of respiratory control mechanisms. The findings characterize complex dynamics of respiratory patterns across the rat lifespan, providing a normative foundation to identify deviations indicative of dysfunction or disease.

The effect of air pollutants on COPD-hospitalized patients in Lanzhou, China (2015-2019).

Background: Lanzhou is the largest heavy industrial city in northwest China and it is a typical geographical valley-like city. However, there are few studies on the relationship between air pollutants and COPD, and their respective sample sizes are small, resulting in inconsistent results. The aim of this study is to analyze the effects of air pollutants on COPD hospitalizations in Lanzhou, China. Methods: An ecological time series study with distributed lag non-linear model (DLNM) was used for analysis. Daily COPD hospitalization data in Lanzhou from 1 January 2015 to 31 December 2019 were collected from 25 hospitals, as well as air pollutant data and meteorological data. Results: A total of 18,275 COPD hospitalizations were enrolled. For 10 µg/m3 increase in PM2.5, PM10, SO2, NO2, and 1 mg/m3 increase in CO at lag 07 day, the RR95%CI of COPD hospitalizations were 1.048 (1.030, 1.067), 1.008 (1.004, 1.013), 1.091 (1.048, 1.135), 1.043 (1.018, 1.068), and 1.160 (1.084, 1.242), respectively. The exposure-response curves between air pollutants (except O3-8h) and COPD hospitalizations were approximately linear with no thresholds. Female, and the harmful effect of PM on aged <65 years, the effect of gaseous pollutant on those aged ≥65 years, were stronger, particularly in the cold season. Exposure to air pollutants (except O3-8h) might increase the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD. Conclusion: Exposure to air pollutants (except O3-8h) increases the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD hospital admissions. The harmful effect of gaseous pollutants (except O3-8h) on COPD-hospitalized patients was stronger than that of PM.

Finite element study on the mechanism of the influence of pretension force and block strength on the shear resistance of the anchor cable with C-shaped tube.

To prevent the early breakage of anchor cables under shear loads in support engineering, a combined structure of Anchor Cable with C-shaped Tube (ACC) has been proposed. The shear resistance enhancement mechanism of this structure and the mechanisms of various influencing factors have yet to be fully revealed. A refined nonlinear finite element model of ACC was original established using ABAQUS software, taking into account the actual structure of the steel strands and the interactions, such as contact and failure between the various components. Various anchor cable pretension forces and block strengths were set to investigate their effects on the shear mechanical response of ACC. The results successfully demonstrated a high correlation between peak shear load and pretension force. The results demonstrate that an increase in pretension force reduces the ACC's peak shear load and break displacement. Additionally, the structure exhibited higher flexural stiffness, the block strength was mobilized earlier, and the block failed locally more quickly. Under high pretension forces, the system exhibited higher shear stiffness in the early stages of shearing due to the influence of the axial force component. With low pretension forces, the ACC exhibited a larger break displacement due to the minor tensile deformation at the shear plane position for the same shear displacement. At low pretension forces, the structure's bending angle increased more rapidly during the middle and later stages of shearing, accompanied by a larger break displacement. Both of these factors led to a greater bending angle at the shear plane position at the point of failure. The results reveal the characteristic of the peak shear load initially increasing and then decreasing with the increase in test block strength, along with its underlying mechanism. As the block strength increased, the bending angle of the structure at the shear plane position increased more rapidly, resulting in higher shear stiffness. With high block strength, the combination of smaller break displacement and greater shear stiffness led to an initial increase followed by a decrease in peak shear load. A comprehensive RSSB (Relative Stiffness between Structure and Test Block) that considers both structural and test block stiffness was proposed. The deformation pattern of the structure was controlled by the RSSB. The higher the RSSB, the wider the plastic hinge extension range for the same shear displacement, the smaller the bending angle at the shear plane position, and the smaller the maximum curvature of the structure. The contact force of the C-shaped tube generally exhibited a "single peak" distribution. As the shear displacement increased, the peak position of the contact force moved away from the shear plane, and the maximum contact force increased rapidly and remained relatively stable. At the end of the shearing process, the contact force of the C-shaped tube exhibited a "double peak" distribution.

A novel mathematical model for modeling viscosity and temperature relationship for dead oils.

Viscosity is crucial in subsurface and surface transport, used in engineering domains like heat transfer and pipeline design. However, measurements are limited, necessitating predictive viscosity relationships. Existing models lack precision or pertain to limited fluids, and accurately forecasting dead oil viscosity remains challenging due to errors. The study presents a mathematical algorithm to accurately estimate viscosity values in hydrocarbon fluids. It uses a robust non-linear regression technique to establish a reliable relationship between fluid viscosity and temperature within a specific temperature range. The algorithm is applied to extra-heavy to light crude oil samples from Iranian oilfields, revealing viscosity values ranging from 0.29 cp to 5328.74 cp within a dataset of 243 viscosity data points. After modeling each of these five fluids, the highest values obtained for the maximum absolute error and relative error are related to the fluid with an API gravity of 12.92. The maximum absolute error and relative error for this fluid sample are 1.25 cp and 6.04%, respectively. The algorithm offers acceptable precision in outcome models, even with limited training data, demonstrating its effectiveness in training models with less than 30% of available data. Moreover, these models end up with a near-unity coefficient of determination in testing data, reaffirming their proficiency at reflecting empirical data with remarkable accuracy.

Third-order non-linear optical switching and threshold limiting of NiO thin films.

This study discusses the nonlinear optical properties of as-grown and annealed NiO thin films using the Z-scan technique utilizing the femtosecond laser pulses at a repetition rate of 100 kHz of wavelength 1030 nm with a pulse duration of 370 fs. In open aperture measurements, pristine reveal saturable absorption (SA) with a negative sign of nonlinearity, while annealed samples exhibit reverse saturable absorption (RSA) with a positive sign of nonlinearity. In closed aperture conditions, all samples show prefocal minima and postfocal maxima, indicating self-focusing behavior. The observed RSA phenomena are attributed to the indirect two-photon absorption (TPA) process. The influence of surface plasmon resonance on nonlinear absorption is successfully ruled out due to insufficient excitation energy (1.20 eV) to induce resonance in the samples. The increase in bandgap with annealing temperature, associated with indirect TPA, is elucidated with the shifting of Ni- d x 2 - y 2 and Ni- d z 2 orbitals in the conduction band, under the framework of Density Functional Theory (DFT). The DFT results are correlated with the observed nonlinear SA and RSA processes. The Ni d-d and Ni-d to O-p transitions contribute to the modulation of nonlinearity in the indirect TPA process. The study suggests that the sample annealed at 400 °C exhibits superior optical limiting properties with the highest nonlinear absorption coefficients compared to the other annealed sample, while the as-grown sample is suitable for passive Q-switching applications.

Solvent Polarity Dependent Ultrafast Relaxation Kinetics of ADS800AT Dye.

This work investigated the photoexcitation and relaxation kinetics of the ADS800AT dye dissolved in different solvents using transient absorption spectroscopy (TAS) with a white-light continuum probe. The dye was dissolved in various solvents, including dichloromethane (DCM), 1,2-dichlorobenzene (DCB), ethanol, and methanol, to study their impact on the dye's characteristics. The linear absorption peak varied from 835 to 809 nm, depending on the polarity of the solvent, and the pump wavelength for TAS was chosen accordingly. We observed ground-state bleaching and excited-state absorption after exciting the dye with the pump pulse. Global analysis was performed using Glotaran software to fit exponential decay curve models, allowing us to determine the relaxation time of the excited molecule. The relaxation time varied from 198 ps to 508 ps across the different solvents, decreasing as the polarity of the solvent increased. Additionally, we could experimentally correlate the dye molecule's nonlinear properties with the solvent's polarity.

Convergence of CO2 emissions among the selected countries on the Silk Road: evidence from nonlinear panel unit root tests.

This study analyzes the convergence of carbon dioxide (CO2) emissions by examining the stationarity of the relative per capita CO2 emissions of 18 selected countries on the Silk Road for the period 1990-2020. To examine the stationarity of relative per capita CO2 emissions for those 18 countries, we applied a large battery the newly proposed nonlinear panel unit root tests that allow for several forms of state-dependent and time-dependent nonlinearities. We also applied conventional linear panel unit root tests. The linear and nonlinear panel unit root tests account for cross-country dependencies, and the SPSM procedure is applied to these tests in order to see how many countries in the panel sample are converging to the steady state. The test results of linear and nonlinear panel unit root test reveal that the relative per-capita CO2 emissions of 10 out of 18 countries are stationary meaning that the CO2 emissions of these 10 countries converge to the steady-state level over time. Especially, size and sign nonlinearities better capture the convergence dynamics of per capita CO2 emissions towards the steady-state level for seven countries. As we have found that 56% of countries' per capita CO2 emissions are converging, this result has important policy implications.

Noninvasive Detection of the Skin Structure and Inversed Retrieval of Chromophore Information Based on Diffuse Reflectance Spectroscopy.

The detection of skin's structure lays the foundation for personalized laser surgery of vascular skin disease, which can be noninvasively achieved by diffuse reflectance spectroscopy (DRS). A two-step inverse Monte Carlo radiation method based on DRS under two source-detector separations was proposed to quantify the skin structure, including chromophore concentration (melanin fm and hemoglobin fb), epidermal thickness tepi, average vessel diameter Dves, depth dpws and thickness tpws of the vascular layer for diseased skin. The method fitted the simulated DRS to the measured DRS iteratively, differences between which were described by a specific objective function to amplify blood absorption at 500-600 nm, and Dves, dpws, and tpws were estimated based on fm, fb, and tpws fitted in the first step. The results showed that the two-step method dramatically improve the inversion accuracy with mean errors of fm, fb, tpws, and dpws less than 5%.

Trajectory Modeling and Response Prediction in Transcranial Magnetic Stimulation for Depression.

Background: Repetitive transcranial magnetic stimulation (rTMS) therapy could be improved by more accurate and earlier prediction of response. Latent class mixture (LCMM) and non-linear mixed effects (NLME) modeling have been applied to model the trajectories of antidepressant response (or non-response) to TMS, but it is not known whether such models are useful in predicting clinically meaningful change in symptom severity, i.e. categorical (non)response as opposed to continuous scores. Methods: We compared LCMM and NLME approaches to model the antidepressant response to TMS in a naturalistic sample of 238 patients receiving rTMS for treatment resistant depression, across multiple coils and protocols. We then compared the predictive power of those models. Results: LCMM trajectories were influenced largely by baseline symptom severity, but baseline symptoms provided little predictive power for later antidepressant response. Rather, the optimal LCMM model was a nonlinear two-class model that accounted for baseline symptoms. This model accurately predicted patient response at 4 weeks of treatment (AUC = 0.70, 95% CI = [0.52 - 0.87]), but not before. NLME offered slightly improved predictive performance at 4 weeks of treatment (AUC = 0.76, 95% CI = [0.58 - 0.94], but likewise, not before. Conclusions: In showing the predictive validity of these approaches to model response trajectories to rTMS, we provided preliminary evidence that trajectory modeling could be used to guide future treatment decisions.

Quantifying attention in children with intellectual and developmental disabilities through multicenter electrooculogram signal analysis.

In a multicenter case-control investigation, we assessed the efficacy of the Electrooculogram Signal Analysis (EOG-SA) method, which integrates attention-related visual evocation, electrooculography, and nonlinear analysis, for distinguishing between intellectual and developmental disabilities (IDD) and typical development (TD) in children. Analyzing 127 participants (63 IDD, 64 TD), we applied nonlinear dynamics for feature extraction. Results indicated EOG-SA's capability to distinguish IDD, with higher template thresholds and Correlation Dimension values correlating with clinical severity. The template threshold proved a robust indicator, with higher values denoting severe IDD. Discriminative metrics showed areas under the curve of 0.91 (template threshold) and 0.85/0.91 (D2), with sensitivities and specificities of 77.6%/95.9% and 93.5%/71.0%, respectively. EOG-SA emerges as a promising tool, offering interpretable neural biomarkers for early and nuanced diagnosis of IDD.

Empirical modelling of 2205 DSS flow curves using strain-compensated Arrhenius rate-type constitutive model.

This work predicts, hot flow curves of 2205 DSS using strain-compensated Arrhenius rate-type constitutive model. Twenty-five (25) × Ø10 diameter × 15 mm height cylindrical samples were hot compressed at a temperature between 850 and 1050 °C at an interval of 50 °C and strain rates between 0.001 and 5 s-1, using Gleeble 1500D. After the tests, corrected flow curves were plotted followed by computation of deformations constants at various deformation conditions using steady state stress. The values of the constants were (α = 0.009708, Q = 445 kJ/mol and n = 3.7) and seemed comparable to the previous studies of DSS. Steady state predictive model was then constructed using the calculated constants and showed a reasonably good accuracy with low value of MARE = 7.78%. Furthermore, calculated strain compensated Arrhenius rate type model was used to predict flow curves at various deformation. The model had a good estimation of flow curves of flow curves at 900-1050 °C across all strain rates as reflected by MARE = 5.47%. A notable discrepancy between predicted and experimental flow stress was observed at 850 °C and across all the strain rates. A model refinement using generalised reduced gradient improved the accuracy of the model by 34.7% despite deformation conditions at 850 °C and low strain rates (0.01/ 0.1) s-1 showing minimum improvement. Further modification of Z-parameter by compensating for the strain rate improved the accuracy of the model at 850 °C/0.01 s-1/0.1 s-1. Lastly, a comparison of the current model with the other non-linear model showed that the latter was more accurate in estimation of flow curves since it relied on characteristics flow stress points controlled by underlying active deformation mechanisms.

Two-dimensional hyperchaos-based encryption and compression algorithm for agricultural UAV-captured planar images.

This study presents an approach that integrates compressed sensing technology with two-dimensional hyperchaotic coupled Fourier oscillator systems (2D-HCFOS) to address the challenge of slow encryption speeds in agricultural unmanned aerial vehicles (UAVs). The primary challenge in enhancing encryption speed lies in the limited capacity inherent in traditional chaotic-based systems and the computational complexity of their processes. The 2D-HCFOS utilizes a complex two-dimensional hybrid chaotic system, which significantly enhances the security of agricultural UAV image data. Notably, the image encryption process is performed on a personal computer connected to the drone, ensuring efficient processing. By integrating advanced Fourier series and nonlinear coupled oscillators, the model surpasses existing chaotic-based methods, improving both the pseudo-randomness and robustness of encryption. Additionally, incorporating Bonouille functions into the discrete cosine transform (DCT) domain results in a sparser measurement matrix, which is essential for efficient encryption on personal computers. The effectiveness of 2D-HCFOS in securely encrypting agricultural drone images has been rigorously validated through simulations and analytical evaluations using sophisticated row, rotation, and matrix encryption techniques. The improved security performance is further verified by comparative analysis. Compared with other models, the Lyapunov index of 2D-HCFOS is 15.1039, and the sample entropy is 2.4987, indicating that it possesses superior chaotic performance and encryption reliability.

Platelet count has a nonlinear association with 30-day in-hospital mortality in ICU end-stage kidney disease patients: a multicenter retrospective cohort study.

This study addresses the relationship between platelet count and 30-day in-hospital mortality in End-Stage Kidney Disease (ESRD) patients in the intensive care unit (ICU), a topic with limited existing evidence. Utilizing data from the US eICU-CRD v2.0 database (2014-2015), a retrospective cohort study was conducted involving 3700 ICU ESRD patients. We employed binary logistic regression, smooth curve fitting, and subgroup analyses to explore the association between platelet count and 30-day in-hospital mortality. The 30-day in-hospital mortality rate was 13.27% (491/3700), with a median platelet count of 188 × 109/L. After adjusting for covariates, we observed a relationship between platelet count and 30-day in-hospital mortality (OR = 0.98, 95% CI 0.97, 0.99). Subgroup analyses supported these findings. More importantly, a nonlinear association was detected, with an inflection point at 222 × 109/L. The effect sizes (OR) on the left and right sides of the inflection point were 0.94 (0.92, 0.96) and 1.03 (1.00, 1.05), respectively. The most significant finding of this study is the revelation of a nonlinear relationship between baseline platelet count and 30-day in-hospital mortality in ICU patients with ESRD. This discovery explicitly suggests that when ESRD patients are admitted to the ICU, a platelet level closer to 222 × 109/L may predict a lower 30-day in-hospital mortality risk.