Slope Of Curve Research Articles

CeO2/SWCNT nanocomposite coating: A novel approach for corrosion application

AbstractThe coatings were prepared by blending different concentrations of SWCNTs and CeO2 particles with an epoxy resin by hydrothermal method, which was then applied to the substrate through the doctor blade technique. The mixtures were transferred into a 1‐L capacity autoclave with a teflon‐lined flange type and subjected to hydrothermal treatment at 100°C for 3 h. The surface coatings were applied using a doctor blade. Subsequently, the coated materials were placed in an oven and dried for 12 h at 50°C under vacuum conditions. The samples' structural analysis was examined through x‐ray diffraction (XRD). XRD analysis verified the CeO2/SWCNT composite coating, and Fourier transform infrared spectroscopy (FTIR) was utilized to assess the presence of functional groups. Thermodynamic properties and thermal stability of composite coatings that were modified with SWCNTs and CeO2 particles were studied by thermogravimetric analysis (TGA). The impact of the CeO2/SWCNT composite on the anticorrosion capabilities of the epoxy coating was examined through electrochemical impedance spectroscopy (EIS), Nyquist curve, and Tafel slope characterization. Corrosion tests were conducted on the CeO2/SWCNT composite coatings in a 3.5 wt% sodium chloride (NaCl) solution at 25°C to improve corrosion resistance. The concentration of 0.4 wt% CeO2 was found to be optimal for achieving effective corrosion resistance. The composite coating CNT0.6‐C0.4 exhibited significantly higher Ecorr (−426 V) and lower Icorr (2.96 × 10−6 A cm−2) values compared to samples from the CNT0, CNT0.2, and CNT0.6 groups. The paper presents a viable solution with CeO2/SWCNT composite coating for the engineering application of corrosive‐inhibiting coatings.

Development and Validation of a Bayesian Network Predicting Intubation Following Hospital Arrival Among Injured Children

BackgroundInadequate airway management can contribute to preventable trauma deaths. Current machine learning tools for predicting intubation in trauma are limited to adult populations and include predictors not readily available at the time of patient arrival. We developed a Bayesian network to predict intubation in injured children and adolescents using observable data available upon or immediately after patient arrival. MethodsWe obtained patient demographic, injury, resuscitation, and transportation characteristics from trauma registries from four American College of Surgeons-verified level 1 pediatric trauma centers from January 2010 through December 2021. We trained and validated a Bayesian network to predict emergent intubation after pediatric injury. We evaluated model performance using the area under the receiver operating and calibration curves. ResultsThe final model, TITAN (Timing of Intubation in Trauma Analysis Network), incorporated five factors: Glasgow Coma Scale, mechanism of injury, injury type (e.g., penetrating, blunt), systolic blood pressure, and age. The model achieved an area under the receiver operating characteristic curve of 0.83 (95% CI 0.80, 0.85) and had a calibration curve slope of 0.98 (95% CI 0.67, 1.29). TITAN had high specificity (98%), negative predictive value (97%), and accuracy (96%) at a binary probability threshold of 22.6%. ConclusionThe TITAN Bayesian network predicts the risk of intubation in pediatric trauma patients using five factors that are observable early in trauma resuscitation. Prospective validation of the model performance with patient outcomes is needed to assess real-life application benefits and risks. Level of EvidencePrognostic and Epidemiological, Level III.

Forest cover lessens hurricane impacts on peak streamflow

AbstractCyclonic storms (i.e., hurricanes) are powerful disturbance events that often cause widespread forest damage. Storm‐related canopy damage reduces rainfall interception and evapotranspiration, but impacts on streamflow regimes are poorly understood. We quantify streamflow changes in Puerto Rico following Hurricane Maria in September 2017, and evaluate whether forest cover and storm‐related canopy damage account for the differences. Streams are particularly vulnerable to flooding in early post‐disturbance stages during hurricane season, so we focus on 3 months (Oct–Dec) following the hurricane. To discern changes in rainfall responses, we partitioned streamflow into baseflow and quickflow using a digital filter. We collected 2010–2017 streamflow and rainfall data from 18 watersheds and compared the relative magnitude of post‐ to pre‐hurricane double mass curve slopes of baseflow and quickflow volumes against rainfall. Several watersheds displayed higher post‐hurricane quickflow and baseflow, however, the response was variable. The magnitude of quickflow increase was greater in watersheds with high forest damage. Under the same level of relative damage, watersheds with low initial forest cover had greater quickflow increases than highly forested ones. Conversely, baseflow generally increased, but increases were greater in highly forested watersheds and smaller in highly damaged watersheds. These results suggest that post‐storm baseflow increases were due to recharge of hurricane‐related rainfall, as well as forest transpiration interruption and soil disturbance enhancing recharge of post‐hurricane rainfall, while increases to quickflow are related to loss of canopy rainfall interception and higher soil saturation decreasing infiltration. Our research demonstrates that forest damage from disturbance lowers quickflow and elevates baseflow in highly forested watersheds, and elevates quickflow and lowers baseflow in less‐forested watersheds. Less‐forested watersheds may be closer to the forest cover loss threshold needed to elicit a streamflow response following disturbance, suggesting higher flooding potential downstream, and a lower storm‐related forest disturbance threshold than in heavily forested watersheds.

Effect of ARB process on the plane stress fracture toughness, creep properties and forming limit diagram of Aluminum/BN/Copper composite strips

Abstract In the present study, Al/BN/Cu bimetal composite strips were fabricated via the accumulative roll bonding (ARB) process. Then, fracture toughness, mechanical properties, bonding strength, forming limit diagram (FLD), and creep properties have been studied via experimental techniques. The study of creep behavior and mechanical properties showed a formation of a 17 μm atomic diffusion layer at the interface during ARB under three creep loading conditions namely 35 MPa at 225 °C, 35 MPa at 275 °C, and 30 MPa at 225 °C. The tensile strength of samples improved to 144 MPa which was about 234% in comparison with the primary Al monolithic sample. It was observed by the SEM that the fracture types changed to shear kind after higher passes including prominent effects on the fracture morphology. FLD curve dropped severely after the first ARB pass and then began to enhance at higher passes. The fracture toughness value of 30 MPa m1/2 was achieved after ten ARB passes. An intermetallic composition was created near Al. The creep failure time did decline by 44% and the stress level decreased by 13% at a constant temperature. It can be concluded that applied temperature and stress effect on creep properties especially leads to increasing the slope of creep curves with higher stresses. This trend was opposite for the creep temperature at higher temperature levels. Moreover, dynamic recrystallization was observed through the crystalline structure of samples.

The energy-limited water loss of an alpine shrubland on the northeastern Qinghai-Tibetan Plateau, China

Study regionAlpine shrubland on the northeastern Qinghai-Tibetan Plateau. Study focusWater provision ability is a pivotal ecological service of high-altitude alpine regions and is controlled by precipitation, evapotranspiration (ET), and soil water storage whereas the underlying ecohydrological processes remain highly unquantified. Here, we investigated continuous 19-year flux measurements to quantify the temporal patterns of ET and water budget (precipitation minus ET, P−ET), as well as 0-20 cm soil water storage change (ΔSWS). New hydrological insights for the regionAt a monthly scale, ET peaked in July (96.7 ± 26.4 mm, Mean ± S.D.) and averaged 41.7 ± 31.9 mm, whose variations were determined by the slope of the saturation vapor pressure curve at air temperature, air and soil temperatures, regardless of vegetation growth stage. P−ET averaged 18.3 ± 26.3 mm in August and September while stayed deficit during the other months. The variations in P−ET were controlled by precipitation in the May-October growing season whereas by ET in the non-growing season from November to April. ΔSWS peaked in May (28.8 ± 11.2 mm) and September (3.0 ± 2.7 mm) and almost accumulated to zero over the whole season. At annual scales, none of ET, P−ET, and ΔSWS changed significantly. ET averaged 512.2 ± 68.4 mm and exceeded precipitation (459.1 ± 58.4 mm), likely due to the lateral flow supply of uphill locations. The variations in ET were regulated directly by bulk canopy resistance and indirectly by net radiation. P−ET averaged −53.2 ± 95.4 mm and demonstrated a clear water deficit (−51.6 ± 21.0 mm) during the non-growing season. The variations of P−ET were driven jointly by precipitation and ET, with opposite but equivalent effects. The dominance of thermal conditions and energy availability on ET variability manifested an energy-limited feature of water loss in the alpine shrubland. The temporal patterns in P−ET elucidated that the alpine shrubland plays the water retention rather than water provision function through transforming variable precipitation input into stable ET loss.

Achilles Tendon Stiffness: Influence of Measurement Methodology

ObjectiveMechanical stiffness derived from force-elongation curves is fundamentally different from shear wave (SW) elastography-based tissue properties. We compared these techniques, with a total of five methods of assessing Achilles tendon (AT) stiffness. MethodsSeventeen participants (12 male and 5 female) with unilateral AT rupture performed submaximal contractions at 30% and 10% maximal isometric contraction torque of the un-injured limb. SW velocity was acquired at rest. Force-elongation curves were assessed from the free AT and the medial gastrocnemius (MG) tendon. Mechanical stiffness was determined near the end of the linear region of the force-elongation curve and from the toe region. Bivariate correlations between mechanical stiffness and SW velocity, as well as pairwise t-tests between limbs, were computed. ResultsIn the injured limb, SW velocity correlated with MG tendon and free AT toe-region stiffness during 10% (r = 0.59, p = 0.020 and r = 0.60, p = 0.011, respectively) and 30% of submaximal contractions (r = 0.56, p = 0.018 and r = 0.67, p = 0.004, respectively). The un-injured limb showed no associations. In both limbs pooled together, SW velocity correlated with MG tendon toe-region stiffness in 30% of submaximal contractions (r = 0.43, p = 0.012). Free tendon mechanical stiffness was lower in the injured limb, with a mean difference of 148.5 Nmm⁻¹ (95% CI: 35.6–261.3, p = 0.013), while SW velocity was higher in the injured limb (1.67 m × s⁻¹, 95% CI; -2.4 to -0.9, p < 0.001). ConclusionSW elastography may reflect AT viscoelastic properties at the initial slope of the force-length curve with strains <1% but cannot offer insight into AT mechanics at higher loads. Extended toe regions in the injured limb could have caused the association between mechanical stiffness and SW-based stiffness.

Dispersive micro Solid-Phase extraction with Bimetallic Ni, Zn-MOF sorbent and gas chromatography method for Organophosphorus pesticide determination in environmental water samples

A dispersive micro solid-phase extraction coupled with the GC-FID method was developed to determine three Organophosphorus pesticides: Fenitrothion, Chlorpyrifos, and Diazinon. Various sorbents, including Fe3O4 NPs, Zn-MOF, Ni-MOF, Bimetallic Ni, Zn-MOF, and Fe3O4 NPs@SiO2@ Bimetallic Ni, Zn-MOF, were synthesized and evaluated for their extraction efficiency of OPPs. Fe3O4 NPs@SiO2@ Bimetallic Ni, Zn-MOF was identified as the optimal sorbent based on its performance. The affective factors in the procedure were optimized using one factor of the time and experimental design methods. The significant factors in this method included sorbent amount, extraction time, and desorption solvent volume with an optimum value of 37 mg, 8.3 min, and 231 µL, respectively. Under optimized conditions, the method exhibited distinct linear ranges for Fenitrothion, Chlorpyrifos, and Diazinon, ranging from 0.24 to 259, 0.17–234, and 0.25–247 ng mL−1, respectively, with high corresponding R2 values (0.9947, 0.9929, and 0.9943). The limits of detection (LOD) were determined based on three times the standard deviation of the blank sample divided by the slope of the calibration curve for each OPP to be 0.07, 0.05, and 0.07 ng mL−1 for Fenitrothion, Chlorpyrifos, and Diazinon, respectively, while the limits of quantification (LOQ) were 0.24, 0.17, and 0.25 ng mL−1. Precision was assessed by calculating intra-day and inter-day relative standard deviation (RSD%) values in one day and three consecutive days with three replicates of each analysis for three concentrations of 10, 25, and 50 ng mL−1, which were found to be below 4.27 %, 4.35 %, and 4.32 % for Fenitrothion, Chlorpyrifos, and Diazinon, respectively, for intra-day analysis, and below 5.43 %, 5.11 %, and 5.29 % for inter-day analysis, respectively. Additionally, the enrichment factor (EF) values for Fenitrothion, Chlorpyrifos, and Diazinon with a concentration of 20 ng mL−1 were determined to be 78.6, 82.4, and 75.7, respectively. Analysis of spiked real samples in two concentrations of 5.0 or 25.0 ng mL−1, such as tap water, river water, dam water, and well water, revealed recovery percentages in the range of 91.2 % to 97.7 %, with relative standard deviations ranging from 3.79 % to 4.98 %, further validating the method’s reliability for practical applications. Overall, the method provides wide linearity, low LODs and LOQs, responsible RSDs, high EFs, and proper recovery percentages for determining OPPs.

Effect of annealing on the corrosion-fatigue strength and hot salt corrosion resistance of fine-grained titanium near-α alloy Ti-5Al-2V obtained using Rotary Swaging

The corrosion-fatigue strength in 3 % aqueous NaCl solution and the resistance against hot salt corrosion (HSC) of the fine-grained near-α alloy Ti-5Al-2V (Russian analogue of Grade 9 titanium alloy with increased aluminium content) have been studied. The properties of the Ti-5Al-2V alloy in the coarse-grained state, in the fine-grained state after cold Rotary Swaging (RS), in the partly recrystallized state and in the fully recrystallized state have been investigated. The mechanical properties of the alloy were characterised using compression tests and microhardness measurements. The effects of RS, the annealing temperature, the time on the characteristics of corrosion destruction of the surface and the composition of the products of the HSC were studied. RS was shown to increase the depth of the intergranular corrosion defects, whereas recrystallization annealing promoted an increase in the corrosion resistance of the Ti-5Al-2V titanium alloy. The parameters of the Basquin equation for the corrosion-fatigue curves for the near-α Ti-5Al-2V alloy in the coarse-grained state, in the severely strained state and after recrystallization annealing were determined for the first time. An effect of non-monotonous dependencies of the slopes of the corrosion-fatigue curves for the strained near-α Ti-5Al-2V alloy on the recrystallization annealing temperature has been observed.

Learning Curve in Posterior Segment Ophthalmic Diagnostic Endoscopy: Implications for Budding Enthusiasts and Fellows-In-Training

ABSTRACT Purpose To elucidate the learning curve for posterior segment diagnostic endoscopy (DE) based on the results of a self-trained (ST) and a supervised (SUP) vitreoretinal surgeon. Methods Retrospective review of medical records of DE performed between 2017 and 2023 by one ST and one SUP vitreoretinal surgeon at a tertiary eye care institute. Data were collected and the serial number of cases was plotted against the time taken for the procedure. A comparative regression plot was created for both the surgeons to know the slope of the learning curve. The start time was noted as that of attachment of the endoscope and the stop time was noted as the end of diagnostic evaluation. Procedures were divided into blocks of 10 cases each and the time taken for the procedures was calculated. Results Total of 106 eyes (58 by ST surgeon and 48 by SUP surgeon) were included. For ST surgeon, the time taken for the surgery correlated inversely (reduced sequentially) with the serial number of the case till the 20th case (correlation coefficient = −0.5, p = .01), for SUP surgeon, the time taken for the surgery correlated inversely with the serial number of the case till the 10th case (correlation coefficient = −0.9, p = <0.0001) and then stabilized. Neither of the groups had any adverse events. Conclusion About 20 cases for a self-trained and about 10 cases for a supervised vitreoretinal surgeon are required to get stable with DE. These observations have implications in creating a training module for DE with appropriate number of training cases.

Frictional resistance and delamination mechanisms in 2D tungsten diselenide revealed by multi-scale scratch and in-situ observations

Friction phenomena in two-dimensional (2D) materials are conventionally studied at atomic length scales in a few layers using low-load techniques. However, the advancement of 2D materials for semiconductor and electronic applications requires an understanding of friction and delamination at a few micrometers length scale and hundreds of layers. To bridge this gap, the present study investigates frictional resistance and delamination mechanisms in 2D tungsten diselenide (WSe2) at 10 µm length and 100–500 nm depths using an integrated atomic force microscopy (AFM), high-load nanoscratch, and in-situ scanning electron microscopic (SEM) observations. AFM revealed a heterogenous distribution of frictional resistance in a single WSe2 layer originating from surface ripples, with the mean increasing from 8.7 to 79.1 nN as the imposed force increased from 20 to 80 nN. High-load in-situ nano-scratch tests delineated the role of the individual layers in the mechanism of multi-layer delamination under an SEM. Delamination during scratch consists of stick-slip motion with friction force increasing in each successive slip, manifested as increasing slope of lateral force curves with scratch depth from 10.9 to 13.0 (× 103) Nm−1. Delamination is followed by cyclic fracture of WSe2 layers where the puckering effect results in adherence of layers to the nanoscratch probe, increasing the local maximum of lateral force from 89.3 to 205.6 µN. This establishment of the interconnectedness between friction in single-layer and delamination at hundreds of layers harbors the potential for utilizing these materials in semiconductor devices with reduced energy losses and enhanced performance.

An experimental study of a novel external fixator based on universal joints for the rapid initial stabilization of mandibular comminuted fractures

PurposeShaping and assembling contemporary external fixators rapidly for the severe mandibular fractures remains a challenge, especially in emergency circumstance. We designed a novel external fixator that incorporates universal joints to provide the stabilization for mandibular comminuted fractures. This study aims to confirm the efficacy of this novel external fixator through biomechanical tests in vitro and animal experiments. MethodsIn vitro biomechanical tests were conducted using 6 fresh canine with mandibular defect to simulate critical comminuted fractures. Three mandibles were stabilized by the novel external fixator and other mandibles were fixed by 2.5 mm reconstruction plates. All fixed mandibles were subjected to loads of 350 N on the anterior regions of teeth and 550 N on the first molar of the unaffected side. The stability was evaluated based on the maximum displacement and the slope of the load-displacement curve. In animal experiments, 9 beagles with comminuted mandibular fractures were divided into 3 groups, which were treated with the novel external fixation, reconstruction plate, and dental arch bar, respectively. The general observation, the changes in animals’ weight, and the surgical duration were recorded and compared among 3 groups. The CT scans were performed at various intervals of 0 day (immediately after the surgery), 3 days, 7 days, 14 days, 21 days, and 28 days to analyze the displacement of feature points on the canine mandible and situation of fracture healing at 28 days. The statistical significance was assessed by the two-way analysis of variance test followed by the Bonferroni test, enabling multiple comparisons for all tests using GraphPad Prism10.1.0 (GraphPad Inc, USA). ResultsThe outcomes of the biomechanical tests indicated that no statistically significant differences were found in terms of the maximum displacement (p = 0.496, 0.079) and the slope of load displacement curves (p = 0.374, 0.349) under 2 load modes between the external and internal fixation groups. The animal experiment data showed that there were minor displacements of feature points between the external and internal fixation groups without statistic difference, while the arch bar group demonstrated inferior stability. The CT analysis revealed that the best fracture healing happened in the internal fixation group, followed by the external fixation and arch baring at 28 days after fixation. The external fixation group had the shortest fixation duration (25.67 ± 3.79) min compared to internal fixation ((70.67 ± 4.51) min, p < 0.001) and arch baring ((42.00 ± 3.00) min, p = 0.046). ConclusionThe conclusion of this study highlighted the efficacy and reliability of this novel external fixator in managing mandibular fractures rapidly, offering a viable option for the initial stabilization of comminuted mandibular fractures in the setting of emergency rescue.

Multi-segmented fifth-order polynomial–shaped shells under hydrostatic pressure

The design and construction of submerged complex shells for new applications in offshore structures are increasingly popular. Therefore, the purpose of this study is to present the analytical model and Lagrange multipliers associated with the constraint equation for large displacement analysis of a fifth-order polynomial–shaped shell under hydrostatic pressure for the first time. The shell geometry can be computed using differential geometry with a fifth-order polynomial. The energy functional of the fifth-order polynomial–shaped shell is derived based on the principle of virtual work and written in the appropriate form. The nonlinear static responses of the fifth-order polynomial–shaped shell under hydrostatic pressure can be calculated using the nonlinear finite element method via the fifth-order polynomial shape function. This study develops the model using one-dimensional beam elements divided along the shell radius. To avoid the slope of a meridian curve at the equatorial plane approaching infinity, the shell is divided into two regions defined by different surface parameters. At the junction of two adjacent regions, the continuity requirements are established as the constraint conditions using Lagrange multipliers. The numerical results from the proposed methods are demonstrated and discussed, along with the effects of varied seawater depth, thickness, and elastic modulus on the deformed configuration and principal curvature at the deformed state. The results show that the nonlinear displacement is higher than the linear one in the case of the hydrostatic pressure, whereas the case of the internal pressure has an opposite result. For principal curvatures at the apex, the principal curvatures increase as the seawater depth increases, whereas the principal curvatures decrease when the thickness and elastic modulus increase.

Mechanical characterization of tablets using post compression in-die cyclic loading

The purpose of this work is to use post compression in-die cyclic loading as an analytical powder compression tool. Cyclic loading experiments (partial unloading followed by reloading) were performed on tablets formed from three relatively coarse powders (∼100μm) comprised of microcrystalline cellulose (MCC), ibuprofen (IBU) and lactose monohydrate (LAC). The reloading curve was always linear initially, irrespective of the shape of the unloading curve. Hence, nonlinearities in the unloading curve should be attributed to inelastic phenomena rather than to nonlinear elasticity. The slope of the reloading curve generally decreased with increasing degree of unloading, indicating a progressive damage of the contact network upon unloading. For MCC and IBU, consistent unloading curves following primary and secondary loading were obtained. For LAC, the secondary unloading curves were displaced towards smaller tablet heights, suggesting that that particle fragmentation occurs during unloading and reloading, also when the maximal tableting pressure is not exceeded.

Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging

ObjectivesThis study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using a 3D multi-echo in-phase sequence. Materials and methodsIn this retrospective study, 29 patients who underwent lumbar spine MRI, including an MR bone imaging sequence between January and April 2023, were analyzed. Images were reconstructed with and without SR-DLR (Matrix sizes: 960 × 960 and 320 × 320, respectively). The signal-to-noise ratio (SNR) of the vertebral body and spinal canal and the contrast and contrast-to-noise ratio (CNR) between the vertebral body and spinal canal were quantitatively evaluated. Furthermore, the slope at half-peak points of the profile curve drawn across the posterior border of the vertebral body was calculated. Two radiologists independently assessed image noise, contrast, artifacts, sharpness, and overall image quality of both image types using a 4-point scale. Interobserver agreement was evaluated using weighted kappa coefficients, and quantitative and qualitative scores were compared via the Wilcoxon signed-rank test. ResultsSNRs of the vertebral body and spinal canal were notably improved in images with SR-DLR (p < 0.001). Contrast and CNR were significantly enhanced with SR-DLR compared to those without SR-DLR (p = 0.023 and p = 0.022, respectively). The slope of the profile curve at half-peak points across the posterior border of the vertebral body and spinal canal was markedly higher with SR-DLR (p < 0.001). Qualitative scores (noise: p < 0.001, contrast: p < 0.001, artifact p = 0.042, sharpness: p < 0.001, overall image quality: p < 0.001) were superior in images with SR-DLR compared to those without. Kappa analysis indicated moderate to good agreement (noise: κ = 0.56, contrast: κ = 0.51, artifact: κ = 0.46, sharpness: κ = 0.76, overall image quality: κ = 0.44). ConclusionSR-DLR, which is based on k-space data, has the potential to enhance the image quality of lumbar spine MR bone imaging utilizing a 3D gradient echo in-phase sequence.Clinical relevance statement: The application of SR-DLR can lead to improvements in lumbar spine MR bone imaging quality.

Differentiation of benign and malignant lesions in Bethesda III and IV thyroid nodules via dual-energy computed tomography quantitative parameters and morphologic features.

Thyroid nodules (TNs) cytologically defined as category Bethesda III and IV pose a major diagnostic challenge before surgery, demanding new methods to reduce unnecessary diagnostic thyroid lobectomies for patients with benign TNs. This study aimed to assess whether a model combining dual-energy computed tomography (DECT) quantitative parameters with morphologic features could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs. Data from 77 patients scheduled for thyroid surgery for Bethesda III and IV TNs (malignant =48; benign =29) who underwent DECT scans were reviewed. DECT quantitative parameters including normalized iodine concentration (NIC), attenuation on the slope of spectral Hounsfield unit (HU) curve, and normalized effective atomic number (Zeff) were measured in the arterial phase (AP) and venous phase (VP). DECT quantitative parameters and morphologic features were compared between the malignant and benign cohorts. The receiver operating characteristic curve was performed to compare the performances of significant DECT quantitative parameters, morphologic features, or the models combining the DECT parameters, respectively, with morphologic features. A nomogram was constructed from the optimal performance model, and the performance was evaluated via the calibration curve and decision curve analysis. The areas under the receiver operating characteristic curve with 95% confidence interval (CI) of the NIC in the AP (AP-NIC), slope of spectral HU curve in the AP, and NZeff in the AP were 0.749 (95% CI: 0.641-0.857), 0.654 (95% CI: 0.530-0.778), and 0.722 (95% CI: 0.602-0.842), respectively. The model combining AP-NIC with enhanced blurring showed the highest diagnostic performance, with an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of 0.808, 0.854, and 0.655, respectively; it was then used to construct a nomogram. The calibration curve showed that the discrepancy between the prediction of the nomogram and actual observations was less than 5%. The decision curve analysis indicated the nomogram had a positive net benefit in threshold risk ranges of 14% to 58% or 60% to 91% for malignant Bethesda III and IV TNs. The model combining AP-NIC with enhanced blurring could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs.

Tropical and montane Apis cerana show distinct dance-distance calibration curves.

Social bees have evolved sophisticated communication systems to recruit nestmates to newly found food sources. As foraging ranges can vary from a few hundred meters to several kilometers depending on the environment or season, populations of social bee species living in different climate zones likely show specific adaptations in their recruitment communication. Accordingly, studies in the western honey bee, Apis mellifera, demonstrated that temperate populations exhibit shallower dance-calibration curves compared with tropical populations. Here, we report the first comparison of calibration curves for three Indian Apis cerana lineages: the tropical Apis indica, and the two montane Himalayan populations Apis cerana cerana (Himachal Pradesh) and Apis cerana kashmirensis (Jammu and Kashmir). We found that the colonies of the two montane A. cerana populations show dance-distance calibration curves with significantly shallower slopes than those of the tropical A. indica. Next, we transferred A. c. cerana colonies to Bangalore (∼ 2600 km away) to obtain calibration curves in the same location as A. indica. The common garden experiment confirmed this difference in slopes, implying that the lineages exhibit genetically fixed differences in dance-distance coding. However, the slopes of the calibration curves of the transferred A. c. cerana colonies were also significantly higher than those of the colonies tested in their original habitat, indicating an important effect of the environment. The differences in dance-distance coding between temperate and tropical A. cerana lineages resemble those described for Apis mellifera, suggesting that populations of both species independently evolved similar adaptations.

Concomitant Procedures, Black Race, Male Sex, and General Anesthesia Show Fair Predictive Value for Prolonged Rotator Cuff Repair Operative Time: Analysis of the National Quality Improvement Program Database Using Machine Learning

PurposeThe purpose of this study is to develop machine learning models using the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database to predict prolonged operative time (POT) for rotator cuff repair (RCR). Furthermore, this study aims to use the trained machine learning (ML) models, cross-referenced with traditional multivariate logistic regression (MLR), to determine the key perioperative variables that may predict POT for RCR. MethodsData were obtained from a large, national database (NSQIP) from 2021. Patients with unilateral RCR procedures were included. Demographic, preoperative, and operative variables were analyzed. A multivariable logistic regression (MLR) model and various other machine learning techniques, including random forest (RF) and artificial neural network (ANN), were compared using area under the curve (AUC), calibration, Brier score, and decision curve analysis. Feature importance was identified from the overall best-performing model. ResultsA total of 6,690 patients met inclusion criteria. The random forest (RF) ML model had the highest AUC upon internal validation (0.706) and the lowest Brier score (0.15), outperforming the other models. The RF model also demonstrated strong performance upon assessment of the calibration curves (Slope = 0.86, Intercept = 0.08) and decision curve analysis. The model identified concomitant procedure, specifically labral repair and biceps tenodesis, as the most important variable for determining POT, followed by age <30 years, Black or African American race, male sex, and general anesthesia. ConclusionsDespite the advanced machine learning models used in this study, the NSQIP dataset was only able to fairly predict POT following RCR. The RF model identified concomitant procedures, specifically labral repair and biceps tenodesis, as the most important variables for determining POT. Additionally, demographic factors such as age <30 years, Black race, and general anesthesia were significant predictors. While male sex was identified as important in the RF model, the MLR model indicated that its predictive value is primarily in conjunction with specific procedures like biceps tenodesis and subacromial decompression.

High-Lift Aerodynamics of Integrated Distributed Propulsion Systems with Thrust Vectoring

Recent interest in distributed electric propulsion in aeronautics has motivated the exploration of novel approaches for integrating this technology into fixed-wing aircraft. Quasi-two-dimensional wind tunnel experiments were conducted with an aeropropulsive airfoil model, which included 10 integrated electric ducted fans and trailing-edge thrust vectoring capability. The experimental model was designed based on a reference aeropropulsive system originally optimized for transonic flight conditions. The model incorporated flow conditioners to separate the capture streamtubes of each fan and transition the circular internal flow into a rectangular nozzle exit. The system angle of attack, thrust coefficient, and nozzle deflection angle were all varied throughout the study. Surface pressure data, aggregate lift, drag, and pitching moment performance, and individual fan thrust data were all collected. Experimental results show an increased lift curve slope and maximum lift coefficient with larger fan thrust alongside larger aerodynamic contributions to drag and pitching moment. Deflection of hinged flaps to vector thrust reduces the airfoil zero-lift and stall angles of attack, similar to traditional trailing-edge flaps. Finally, thrust-drag bookkeeping methods demonstrate how jet momentum and airfoil aerodynamics interact. This experiment intends to highlight the aerodynamic mechanisms through which integrated propulsors couple with airfoils to achieve high-lift performance.

Techniques for quantification of organochlorine pesticides from a validated method by using gas chromatography-electron capture detector

Organochlorine pesticides (OCPs) are persistent organic compounds found in aquatic environments worldwide. A well-validated and well-established analytical method is crucial for detecting OCPs in the environment. In this study, an analytical method for quantifying OCPs in water was developed and evaluated. Here, the range of linearity, reproducibility, uncertainty, specificity, method detection limits (MDL), and special emphasis on detection and quantitation limits were assessed. Recovery studies were performed to measure the accuracy and precision of the method. This method exhibited excellent linearity in the range of 2.5–20 μg/L for all compounds. As none of the targeted compounds was detected in the chromatograms of the blank sample with no baseline noise, the limits of detection (LOD) and limits of quantification (LOQ) were determined using the linear regression method, external calibration curve slope, and laboratory fortified blank-based detection. All compounds showed different LOD and LOQ values, depending on the approach used. In particular, endosulfan sulfate, methoxychlor, endrin ketone, H. epoxide, heptachlor, and 4,4ʹ-DDT exhibited high detection limits. The recovery percentage of the 15 compounds at 5 μg/L spiked concentration was between 50 and 150 %, which is consistent with the accuracy of the APHA method. Except for endosulfan sulfate, the relative standard deviations of all other compounds were below 20 %, indicating good precision. This method has also been applied to real water samples. This validation technique is reliable, sensitive, simple, rapid, easy to comprehend, and reproducible. The application of this method in the real water samples was also conducted. Only α-BHC and γ-Chlordane were detected in the water sample.

Prediction and analysis of albumin-bilirubin score combined with liver function index and carcinoembryonic antigen on liver metastasis of colorectal cancer.

Colorectal cancer (CRC) is a common malignant tumor, and liver metastasis is one of the main recurrence and metastasis modes that seriously affect patients' survival rate and quality of life. Indicators such as albumin bilirubin (ALBI) score, liver function index, and carcinoembryonic antigen (CEA) have shown some potential in the prediction of liver metastasis but have not been fully explored. To evaluate its predictive value for liver metastasis of CRC by conducting the combined analysis of ALBI, liver function index, and CEA, and to provide a more accurate liver metastasis risk assessment tool for clinical treatment guidance. This study retrospectively analyzed the clinical data of patients with CRC who received surgical treatment in our hospital from January 2018 to July 2023 and were followed up for 24 months. According to the follow-up results, the enrolled patients were divided into a liver metastasis group and a nonliver metastasis group and randomly divided into a modeling group and a verification group at a ratio of 2:1. The risk factors for liver metastasis in patients with CRC were analyzed, a prediction model was constructed by least absolute shrinkage and selection operator (LASSO) logistic regression, internal validation was performed by the bootstrap method, the reliability of the prediction model was evaluated by subject-work characteristic curves, calibration curves, and clinical decision curves, and a column graph was drawn to show the prediction results. Of 130 patients were enrolled in the modeling group and 65 patients were enrolled in the verification group out of the 195 patients with CRC who fulfilled the inclusion and exclusion criteria. Through LASSO regression variable screening and logistic regression analysis. The ALBI score, alanine aminotransferase (ALT), and CEA were found to be independent predictors of liver metastases in CRC patients [odds ratio (OR) = 8.062, 95% confidence interval (CI): 2.545-25.540], (OR = 1.037, 95%CI: 1.004-1.071) and (OR = 1.025, 95%CI: 1.008-1.043). The area under the receiver operating characteristic curve (AUC) for the combined prediction of CRLM in the modeling group was 0.921, with a sensitivity of 78.0% and a specificity of 95.0%. The H-index was 0.921, and the H-L fit curve had χ2 = 0.851, a P value of 0.654, and a slope of the calibration curve approaching 1. This indicates that the model is extremely accurate, and the clinical decision curve demonstrates that it can be applied effectively in the real world. We conducted internal verification of one thousand resamplings of the modeling group data using the bootstrap method. The AUC was 0.913, while the accuracy was 0.869 and the kappa consistency was 0.709. The combination prediction of liver metastasis in patients with CRC in the verification group had an AUC of 0.918, sensitivity of 85.0%, specificity of 95.6%, C-index of 0.918, and an H-L fitting curve with χ 2 = 0.586, P = 0.746. The ALBI score, ALT level, and CEA level have a certain value in predicting liver metastasis in patients with CRC. These three criteria exhibit a high level of efficacy in forecasting liver metastases in patients diagnosed with CRC. The risk prediction model developed in this work shows great potential for practical application.