Maximum Difference Research Articles

Effects of a Long-Term Supervised Schroth Exercise Program on the Severity of Scoliosis and Quality of Life in Individuals with Adolescent Idiopathic Scoliosis: A Randomized Clinical Trial Study

Background and Objectives: Adolescent Idiopathic Scoliosis (AIS) affects individuals aged 10–18 years and is characterized by spinal deformity, three-dimensional axis deformation, and vertebral rotation. Schroth method exercises and braces have been shown to reduce the Cobb angle and halt spinal deformity progression. The aim of this study was to investigate the impact of a 12-month, supervised Schroth exercise program on scoliosis severity and quality of life in adolescents with AIS. Materials and Methods: Eighty adolescents with AIS (aged 10–17 years) were prescribed a brace and were divided into two groups. The intervention group followed a supervised Schroth exercise program three times a week for 12 months in addition to wearing a brace. The control group used only the brace. Outcomes included the Cobb angle of the main curvature and the sum of curves using radiography, the maximum angle of trunk rotation (ATR maximum, using a scoliometer), and quality of life with the Scoliosis Research Society-22 (SRS-22) questionnaire. Evaluations were conducted at baseline, after 12 months, and 6 months post-intervention. A multivariate analysis of covariance (MANCOVA) was used for statistical analysis (p-Value < 0.05). Results: The intervention group showed statistically significant improvement compared to the control group in the 12th month in Cobb angle (mean differences, 95% CI: −3.65 (−5.81, −1.53), p-Value < 0.001, Cohen’s d = 0.30), ATR maximum (mean differences, 95% CI: −3.05 (−3.86, −2.23), p-Value < 0.001, Cohen’s d = 0.74), and SRS-22 score (mean differences, 95% CI: 0.87 (0.60, 1.13), p-Value < 0.001, Cohen’s d = 0.58). Differences in ATR maximum and SRS-22 score remained significant at the 18-month measurement. No significant differences were found between groups in the sum of curves (p-Value > 0.05). Conclusions: A 12-month supervised Schroth exercise program in AIS patients undergoing brace treatment significantly improves scoliosis severity (Cobb angle and ATR maximum) and quality of life. Improvements were greater than those in shorter-duration studies, suggesting a linear dose–response relationship. Further clinical studies are needed to clarify the impact of long-term Schroth programs.

Determination and Verification of the Johnson–Cook Constitutive Model Parameters in the Precision Machining of Ti6Al4V Alloy

Numerical simulations of the cutting process play a key role in manufacturing and cost optimization. Inherent in finite element analysis (FEA) simulations is the correct description of material behavior during machining. For this purpose, various material models are used to describe the behavior of the material in the range of high deformation, high temperature values, and high strain rates. Very often the Johnson–Cook (JC) material model is used for this purpose; however, the correct determination of the material constants of this model is a key aspect. Therefore, this paper presents a procedure for determining the material constants of the JC model using an analytical method based on normalized tensile and compression testing of the material for different strain rates over a wide temperature range. After determining the material constants, the authors conducted numerical simulations of the orthogonal turning of Ti6Al4V titanium alloy using the obtained constants. Validation of the obtained results with those obtained in experimental studies was also carried out. The outcomes demonstrated that the difference between FEM simulation and experimental tests did not exceed 0.02 mm (14%) in the case of chip thickness,. Much smaller differences were obtained for the temperature in the cutting zone, where the maximum difference was about 45 °C (4%). Comparing the components of the cutting force, we found that, in the case of the main cutting force, in most cases, the differences did not exceed 70 N (8%). After the verification of the obtained results, it was also found that the determined material constants of the Johnson–Cook model can be successfully used in FEM modeling of the cutting process of Ti6Al4V titanium alloy for the adopted range of values of technological parameters.

7239 Natural history of cystic pituitary lesions

Abstract Disclosure: B. Graner: None. D.Z. Erickson: None. D. Donegan: None. Introduction: Pituitary lesions are a common incidental finding on brain MRI, the majority of which are cystic. The natural history and management of cystic pituitary lesions have not been clearly established. Purpose: The purpose of this study is to determine the natural history of incidentally identified cystic pituitary lesions, risk factors for growth and the proportion of patients who develop clinically significant symptoms requiring surgical intervention. Methods: Pituitary MRI reports between 01/01/2015 and 12/31/2022 in patients aged 18 years and older were searched for using Dig Our Radiology Information System (DORIS) using the words “cyst” or “cystic.” Additional inclusion criteria included a follow-up pituitary MRI of at least one year duration, clinical evaluation by Endocrinology, and the presence of a cystic pituitary lesion. Patients with non-contrast exams, excessive pituitary hormone secretion, and surgery within 1 year of presentation were excluded. Patient demographics, imaging characteristics of the lesion and clinical outcomes were collected. All pituitary MRI exams were reviewed by a single neuroradiologist. Results: A total of 157 MRIs in 56 patients with a mean age of 48 ±15 years were included, 39 (70%) were female. The mean follow-up was 2.3 ± 1.4 years. The most common indication for MRI was headache (n= 18, 32%). There was no significant difference in mean maximum (max) diameter at last follow-up compared to baseline (7.45 ±4.23 vs 7.04 ±4.35 mm, p=0.06) or mean cyst volume (197.08 ±252.68 vs 201.43 ±326.18 mm3). Nine (16%) of the lesions increased in volume with a mean change in volume of 105 ±133.64 mm3/yr, note 11 (20%) decreased volume and 36 (64%) remained the same size. Using univariate logistic regression, the odds of cyst growth was greater the larger the max diameter (p= 0.03) or volume was at baseline (p= 0.02)/ Female sex (p=0.32), age at diagnosis (p=0.70) or whether the lesion was thought to be a Rathke cleft cyst or a cystic adenoma (p=0.80) were not associated with increased odds of growth. The risk of growth was higher (42 vs 9%, p=0.016) and the volume change per year was greater (67.2 ±134 vs -7 ±28 mm3, p=0.04) in those with a baseline max diameter of >10 mm. Surgery was performed in 4 patients (7%), 3 of which demonstrated lesion growth (baseline size 12-15 mm and growth rates of 59-341mm3/yr). Pathology revealed one Rathke cleft cyst, one cystic adenoma and fibrotic pituitary changes. The fourth surgical patient opted for resection at an outside facility without a demonstrated increase in size (Rathke cleft cyst). Conclusion: The majority of incidentally found cystic pituitary lesions do not increase after an average follow-up 2-3 years. Growth necessitating surgical intervention was only required in 5% of patients over the study period. A pituitary cyst >10 mm at diagnosis was associated with an increased risk of growth and therefore warrants closer follow-up. Presentation: 6/1/2024

Numerical investigation on the heat dissipation of phase change materials used in the high-speed train brake system

The massive heat dissipation demands of the brake system in high-speed trains pose a significant obstacle to achieving higher operation speeds. Phase change material has attracted considerable attention in various fields due to their exceptional heat dissipation capabilities, yet their utilization in the brake system of high-speed trains remains unexplored. This study aims to investigate the feasibility of phase change material application in the brake system of high-speed train. Specifically, in Case A, the introduction of phase change material resulted in a notable 21% decrease in the average temperature and a remarkable 40% reduction in the maximum temperature difference within the brake system. The latent heat of the phase change material plays a crucial role in maintaining a substantial temperature differential between the cooling components and discs, thereby enhancing heat flux in the brake system. Phase change materials exhibit superior cooling performance compared to traditional air cooling methods in the brake system. To expedite the cooling process of phase change material and facilitate its transition from liquid to solid, an optimized brake system structure utilizing phase change material was proposed. This optimized design holds promise in enhancing the overall heat dissipation efficiency of the high-speed train brake system.

Visual colorimetric label for real-time monitoring of SO2 concentration change in grape and mango during storage

Sulfur dioxide (SO2) is widely utilized as a preservative in food transportation and storage, but excessive consumption poses health risks. This study presents a novel and efficient method for the real-time detection of SO2 using a sensor named TK, synthesized from triphenylamine and 2-cyanomethyl-1-methyl-quinolinium. The core mechanism involves the Michael addition reaction of the CC bond in TK with SO2, which disrupts the intramolecular charge transfer process, resulting in a significant color change and a blue shift in fluorescence emission. Methodologically, the sensor's response was quantified by the change in fluorescence intensity ratio (I425/I647) within a SO2 concentration range of 0–180 μM. The sensor exhibited high sensitivity and selectivity. For practical application, TK was incorporated into hydrophilic polyvinyl alcohol to create a smart label capable of visual colorimetry and fluorescence analysis. SO2 concentration changes were monitored by using this label, demonstrated by the color transition from burgundy red to colorless, yielding a maximum color difference (ΔE) of 73.6. The smart label was successfully used to monitor the quality of various grapes and mangoes during long-term storage, providing a reliable, equipment-independent method suitable for household use. The study offers a new tool for enhancing food safety and mitigating health risks associated with SO2 exposure.

Impact of metro vibrations on people: critical aspects of designing vibration mitigation interventions

A methodology for assessing and mitigating the impact of metro infrastructure generated vibration and ground-borne noise on people is described. This methodology combines techniques for analyzing vibration measurements and predictive modeling to identify effective mitigation interventions. These interventions require working on existing railway track systems and involve interruption of service, unlike noise mitigation interventions that can be implemented without interfering with rail and road infrastructure. For this reason, it is important to identify the most effective mitigation techniques to minimize the impact on the population and simplify on-site implementation. The methodology was applied in Milan metro lines where the vibration level was estimated, and a vibration mitigation system was designed. The vibration phenomenon was quantified through accelerometric measurements taken in several buildings affected by the disturbance from vibration. The measured vibration levels were compared with reference level established by standards. The maximum difference obtained from this comparison was used as input data for the design of the mitigation intervention. The vibration mitigation interventions involve increasing the total mass and elasticity of the existing system. Their effectiveness was verified through numerical calculation using parametric software confirming the required amount of mitigation.

Numerical and artificial neural network inspired study on step-like-plenum battery thermal management system

This study leverage numerical simulation (NS) and artificial neural network (ANN) capabilities to carry out additional investigations on step-like plenum battery thermal management system (BTMS). Different cooling strategies have been developed over the years in BTMSs’ design. Yet, air-cooling strategies still remains relevant, especially in battery-powered aircrafts, where light-weight is important and air is the preferred cooling fluid. Hence, additional study become necessary especially on the step-like plenum design to provide more insight on the performance of the design by considering several number of step, varied air inlet temperature and velocity. Computational fluid dynamics (CFD) approach was employed to obtained results for different number of step; Ns = 1, 3, 4, 7, 9, 15 and 19, varied air inlet temperature; Ti = 278, 298 and 318 K, and varied air inlet velocity; Vi = 3, 3.5, 4, 5 and 6 m/s. Artificial Neural Network (ANN) approach was then employed to predict the BTMSs’ performance for additional values of Ti and Vi. Minimum temperature (Tmin), maximum temperature (Tmax), maximum temperature difference (ΔTmax) and pressure drop (ΔP) were computed. By comparing the CFD results with the result predicted by the ANN, the percentage difference, for the entire dataset were 0.01 %, 0.005 %, 1 % and 0.14 % for Tmax, Tmin ΔTmax and ΔP, respectively. Based on the optimum design parameters predicted using ANN, for Tmax = 299.24 comprises Ns = 4, Vi = 6 m/s and Ti = 278 K, while for ΔP, comprises Ns = 1, Vi = 3 m/s and Ti = 318 K.

Respiratory Rate Estimation from Thermal Video Data Using Spatio-Temporal Deep Learning.

Thermal videos provide a privacy-preserving yet information-rich data source for remote health monitoring, especially for respiration rate (RR) estimation. This paper introduces an end-to-end deep learning approach to RR measurement using thermal video data. A detection transformer (DeTr) first finds the subject's facial region of interest in each thermal frame. A respiratory signal is estimated from a dynamically cropped thermal video using 3D convolutional neural networks and bi-directional long short-term memory stages. To account for the expected phase shift between the respiration measured using a respiratory effort belt vs. a facial video, a novel loss function based on negative maximum cross-correlation and absolute frequency peak difference was introduced. Thermal recordings from 22 subjects, with simultaneous gold standard respiratory effort measurements, were studied while sitting or standing, both with and without a face mask. The RR estimation results showed that our proposed method outperformed existing models, achieving an error of only 1.6 breaths per minute across the four conditions. The proposed method sets a new State-of-the-Art for RR estimation accuracy, while still permitting real-time RR estimation.

Thermomechanical characteristics of a thermally inactive neighboring pile of an energy soldier pile during constraint changes

This study aims to determine whether it is worth activating energy soldier piles during the excavation and construction phases by investigating the thermomechanical response of a thermally inactive neighboring pile subjected to thermal loads resulting from an energy soldier pile in a foundation pit support system. This was achieved through a field test utilizing constant-power heating. The energy soldier piles under investigation are susceptible to constraint changes due to the installation and removal of internal supports. The impacts of temperature and constraint changes during excavation and main structure construction on thermally inactive neighboring piles are analyzed and discussed. The results indicated that the maximum temperature difference along the depth direction of the thermally inactive neighboring pile during the construction of the main structure was 9.7 °C, whereas during the excavation, it was 13.9 °C. The constraint on the excavation side transitioned from a continuous state to a concentrated state with a point-like distribution, and finally to a continuous state of restraint for the large-stiffness main structure. The maximum thermally induced stress was 0.283 MPa/°C. During the excavation stage, the degree of freedom in the middle of the pile was approximately 0.8. Following backfilling, this value decreased to 0.3. Additionally, the maximum horizontal displacement moved to below the bottom elevation of the main structure, and none of the maximum values exceeded 3 mm. Since thermal activation during the excavation and construction processes can lead to issues with no real benefit, activation of the energy piles during these phases is not necessary, and better benefits are obtained by activating the energy soldier piles during the operation phases of the internal building.

Quantifying variation in the physical size of footwear test impressions

The analysis of forensic footwear evidence often requires the preparation of test impressions created under controlled laboratory conditions. When these test impressions are compared to questioned impressions, (dis)agreement in physical size is an important attribute that must be evaluated and documented. Integral to this comparison is an understanding of the variation that may exist between replicate test impressions, and test impressions created using different methods. The aim of this study was to empirically characterize the variation that exists within and between test impressions prepared using a static benchtop and a dynamic walking method, as well as explore the potential influence of the wearer’s foot size when using the walking method. To examine this variation, twenty-three participants were recruited to prepare test impressions of two different shoe makes and models in four different manufacturer’s sizes. Five replicate benchtop impressions per make/model/size and three replicate walking impressions per participant/make/model/size were created, resulting in approximately 550 test samples, to which an additional 150 quality control copies were blindly added, resulting in almost 700 processed test impressions. Using reproducible and reliable ground control points, the physical size of toe-to-heel length and medial-to-lateral ball of the toe width measurements were collected and compared. For the shoe make/models examined in this study, a systematic bias was observed between benchtop and walking impressions, such that benchtop impressions were almost always longer and narrower than walking impressions, and that within the walking method, physical size differences vary with foot/shoe size mismatch. Of the experimental shoes and groups examined in this study, the variation in toe-to-heel length measurements between benchtop and walking impressions was greatest when the shoe was two sizes smaller than the foot, resulting in a maximum physical size difference of 4.18 mm for a Nike® Downshifter 11 outsole. Similarly, when comparing the variation in toe-to-heel length measurements between walking impressions created using a correctly-fitted shoe versus a shoe that was two sizes smaller than the wearer’s foot, a maximum physical size difference of 3.25 mm was observed. Based on these findings, best practice suggests that footwear analysts document the foot size of the wearer preparing walking test impressions, refrain from using benchtop impressions to form opinions about physical size consistency/differences, and to be cognizant that a large mismatch between foot/shoe size when creating walking impressions can lead to length differences greater than 3.0 mm.

Cross-feature fusion speech emotion recognition based on attention mask residual network and Wav2vec 2.0

Speech Emotion Recognition (SER) has received widespread attention as a crucial way for understanding human emotional states. However, the impact of irrelevant information on speech signals and data sparsity limit the development of SER system. To address these issues, this paper proposes a framework that incorporates the Attentive Mask Residual Network (AM-ResNet) and the self-supervised learning model Wav2vec 2.0 to obtain AM-ResNet features and Wav2vec 2.0 features respectively, together with a cross-attention module to interact and fuse these two features. The AM-ResNet branch mainly consists of maximum amplitude difference detection, mask residual block, and an attention mechanism. Among them, the maximum amplitude difference detection and the mask residual block act on the pre-processing and the network, respectively, to reduce the impact of silent frames, and the attention mechanism assigns different weights to unvoiced and voiced speech to reduce redundant emotional information caused by unvoiced speech. In the Wav2vec 2.0 branch, this model is introduced as a feature extractor to obtain general speech features (Wav2vec 2.0 features) through pre-training with a large amount of unlabeled speech data, which can assist the SER task and cope with data sparsity problems. In the cross-attention module, AM-ResNet features and Wav2vec 2.0 features are interacted with and fused to obtain the cross-fused features, which are used to predict the final emotion. Furthermore, multi-label learning is also used to add ambiguous emotion utterances to deal with data limitations. Finally, experimental results illustrate the usefulness and superiority of our proposed framework over existing state-of-the-art approaches.

Numerical and experimental study of thermal stabilization system for satellite electronics with integrated phase-change capacitor

In this paper experimental and numerical investigations were conducted to analyze the application of phase change material (PCM) for temperature stabilization of small satellite electronics. The reference electronic equipment is a data processing unit generating a nominal power of 9.6 W during its operation. To stabilize its temperature, an integrated PCM module was designed, built, and tested experimentally in a thermal–vacuum chamber. The experimental results were then used to validate a numerical model, developed using commercial software Simcenter FloEFD. The results showed good agreement between measured and predicted temperature evolution in critical locations of the unit. The model predictions were further improved by conducting analysis of uncertain input data, model settings, and by inclusion of the effect of natural convection in the PCM. The improved model showed better agreement between the model predictions and experiments. The comparison showed that the maximum difference between the measured and calculated temperature at the most important location (the heater) was 1.6 °C and difference of the peak values was 0.8 °C. Finally, the model was used to compare the constructed module containing the PCM with a system consisting of an aluminum block of the same volume as PCM. The comparison showed that the use of PCM allows for a reduction of the maximum temperature by 6.2 °C while reducing the mass almost 3.5 times. The results demonstrate that the developed numerical model allows for accurate predictions of temperature distributions in the designed device, and can be effectively used to design PCM modules dedicated to in-space electronics, thereby increasing their peak capabilities and lifetime.

Optimization of thermal shock response spectrum as infrared thermography post-processing methodology using Latin hypercube sampling and analytical thermal N-layer model

In this work, we continue to develop and investigate the Thermal Shock Response Spectrum (TSRS) method as an alternative data processing method for infrared thermography (IRT). We focus on improving the current TSRS algorithm and present an optimization methodology for finding the optimal thermal Q-factor and characteristic frequency pair, which is based on the widely applied random sampling method. We show the qualitative relationship between the determined optimal characteristic frequency and the corresponding maximum difference in diffusion length between reference and defective models, as calculated by selecting a specific one-dimensional thermal N-layer model The investigations were performed on an inhomogeneous plate made of carbon fiber reinforced polymer (CFRP) with artificial square defects at different depths. Furthermore, two different heat sources were used: a xenon flash lamp and a laser. These sources are not only distinct by their underlying physics but also generate inherently different pulse shapes. To quantitatively estimate the contrast between defect and non-defect areas, and to compare these results with commonly used infrared thermography (IRT) data post-processing methods such as Pulse Phase Thermography (PPT) and Thermographic Signal Reconstruction (TSR), the Tanimoto criterion (TC) and signal-to-noise ratio (SNR) were used.

Evaluating the predictive efficacy of real-time 3D echocardiography in cardiac resynchronization therapy

BackgroundThe aim of this study is to assess the predictive efficacy of real-time three-dimensional echocardiography (RT-3DE) and QRS wave duration in determining the response to cardiac resynchronization therapy (CRT) and assessing left ventricular systolic function pre- and post-CRT device implantation.MethodA total of 51 patients with heart failure undergoing CRT at the Second Affiliated Hospital of Nantong University between January 1, 2013, and October 31, 2020, were enrolled in this study. Traditional two-dimensional echocardiography and RT-3DE were performed pre and post-CRT, with QRS wave width data from electrocardiograms and additional clinical information collected. Patients were categorized into CRT responder (n = 36) and CRT non-responder (n = 15) groups based on their response to CRT device implantation. Comparative analyses were conducted on the general characteristics of both groups, as well as the predictive efficacy of RT-3DE and QRS wave width for CRT responsiveness and left ventricular systolic function. Data on the standard deviation (Tmsv16-SD, Tmsv12-SD, Tmsv6-SD) and maximum difference (Tmsv16-Dif, Tmsv12-Dif, Tmsv6-Dif) of left ventricular end-systolic volume (LVESV) at segments 16, 12, and 6, as well as QRS wave width, were collected and analyzed.ResultsThe indicators Tmsv6-Dif, Tmsv12-Dif, Tmsv16-Dif, Tmsv6-SD, Tmsv12-SD, Tmsv16-SD, and QRS wave width exhibited significantly higher values in the CRT responder group when compared to the CRT non-responder group (P < 0.05). Among these, Tmsv16-SD demonstrated superior predictive performance for post-CRT response, with a sensitivity of 88.9%, specificity of 80.0%, and a diagnostic cut-off value of 6.19%. This predictive capability exceeded that of the conventional indicator, QRS wave width.ConclusionRT-3DE enables accurate prediction of post-CRT patient response and significantly facilitates quantitative assessment of CRT therapy efficacy.

An Evidential Multi-Target Domain Adaptation Method Based on Weighted Fusion for Cross-Domain Pattern Classification.

For cross-domain pattern classification, the supervised information (i.e., labeled patterns) in the source domain is often employed to help classify the unlabeled target domain patterns. In practice, multiple target domains are usually available. The unlabeled patterns (in different target domains) which have high-confidence predictions, can also provide some pseudo-supervised information for the downstream classification task. The performance in each target domain would be further improved if the pseudo-supervised information in different target domains can be effectively used. To this end, we propose an evidential multi-target domain adaptation (EMDA) method to take full advantage of the useful information in the single-source and multiple target domains. In EMDA, we first align distributions of the source and target domains by reducing maximum mean discrepancy (MMD) and covariance difference across domains. After that, we use the classifier learned by the labeled source domain data to classify query patterns in the target domains. The query patterns with high-confidence predictions are then selected to train a new classifier for yielding an extra piece of soft classification results of query patterns. The two pieces of soft classification results are then combined by evidence theory. In practice, their reliabilities/weights are usually diverse, and an equal treatment of them often yields the unreliable combination result. Thus, we propose to use the distribution discrepancy across domains to estimate their weighting factors, and discount them before fusing. The evidential combination of the two pieces of discounted soft classification results is employed to make the final class decision. The effectiveness of EMDA was verified by comparing with many advanced domain adaptation methods on several cross-domain pattern classification benchmark datasets.

Field study on the temperature uniformity of containerized batteries using a two-phase liquid cooling system under mismatched conditions

The conventional liquid cooling system carries the risk of dew condensation and air cooling has poor thermal management performance for battery energy storage systems. To address these issues, a novel two-phase liquid cooling system was developed for containerized battery energy storage systems and tested in the field under mismatched conditions. The thermal management performance and safety during the charging and discharging processes were analyzed by investigating the main influencing factors, including battery temperature and cooling system characteristics (battery temperature variation, temperature uniformity, supply liquid temperature, cold plate temperature distribution, and compressor status). The results showed that the novel system can maintain a maximum cell temperature difference of less than 3°C at the rack level and less than 2°C at the pack level, resulting in a 60% reduction compared to the traditional air cooling system. Relative to a supply liquid temperature of 15∼25°C, a relatively high supply temperature of 20∼30°C for two-phase liquid cooling can not only reduce the running time of the compressor but also enhance its start-stop consistency. Compared to other studies, this novel system is reliable and safe for containerized energy storage batteries, even in capacity mismatch and direct return pipeline conditions.

Coupled CFD modeling and thermal analysis of multi-layered insulation structures in liquid hydrogen storage tanks for various vapor-cooled shields

The present study aims to propose a coupled numerical model for analyzing the influence of the configuration of the vapor-cooled shield tubes on insulation performance. The numerical model is developed to calculate the effective thermal conductivity of multi-layer insulation (MLI) and rigorously evaluated. Specifically, the tank evaporation simulation software BoilFAST is manually coupled with the CFD commercial software of ANSYS FLUENT (2020 R2) to accurately determine the mass flow rate and temperature of boil-off gas in a tank, which is then used as inputs for the CFD simulations. This coupling methodology can be used for reliable calculations of boil-off losses for liquid hydrogen and heat transfer inside the MLI structures. Results demonstrate that the estimated effective thermal conductivity agrees with the earlier published data and that increasing the diameter and number of tubes enhances heat exchange between the VCS tubes and MLI structures. Also, the heat flux into the tank is relatively reduced by 32.04 % by increasing the diameter of the tube and 49.14 % by adding the number of tubes. Moreover, the maximum temperature difference of the VCS is estimated to be less than 1 K, indicating nearly uniform distributions of the VCS.

Machine learning-based climate zoning and asphalt selection for pavement infrastructure under changing climate: A focused study of Ningxia, China

Climate change poses significant challenges to the durability and performance of asphalt pavements. This study presents a comprehensive analysis of climatic factors in Ningxia, China, to establish a robust climate zoning framework for asphalt pavements. Utilizing machine learning techniques, specifically the Fuzzy C-means (FCM) algorithm, three distinct climate zones within Ningxia were divided considering climatic features such as maximum temperature, minimum temperature, average temperature, maximum temperature difference, cumulative precipitation, and cumulative radiation. Based on the historical climate data and LTPP model, five asphalt PG zones were classified in Ningxia Province. Besides, six climate sub-zones, which integrated the asphalt PG zones into climate zones, provided a more refined strategy for the asphalt selection. The study also projected future climate scenarios using the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset to assess the impact of climate change on asphalt selection in Ningxia. The significant changes in pavement temperature indicated the necessity to adapt asphalt pavement designs to future climate scenarios. Overall, this research contributed to the construction of more climate-resilient pavement infrastructures and provided an analysis framework for other regions facing similar climate-induced challenges.

Ultrashort Oncologic Whole-Body [18F]FDG Patlak Imaging Using LAFOV PET.

Methods to shorten [18F]FDG Patlak PET imaging procedures ranging from 65-90 to 20-30 min after injection, using a population-averaged input function (PIF) scaled to patient-specific image-derived input function (IDIF) values, were recently evaluated. The aim of the present study was to explore the feasibility of ultrashort 10-min [18F]FDG Patlak imaging at 55-65 min after injection using a PIF combined with direct Patlak reconstructions to provide reliable quantitative accuracy of lung tumor uptake, compared with a full-duration 65-min acquisition using an IDIF. Methods: Patients underwent a 65-min dynamic PET acquisition on a long-axial-field-of-view (LAFOV) Biograph Vision Quadra PET/CT scanner. Subsequently, direct Patlak reconstructions and image-based (with reconstructed dynamic images) Patlak analyses were performed using both the IDIF (time to relative kinetic equilibrium between blood and tissue concentration (t*) = 30 min) and a scaled PIF at 30-60 min after injection. Next, direct Patlak reconstructions were performed on the system console using only the last 10 min of the acquisition, that is, from 55 to 65 min after injection, and a scaled PIF using maximum crystal ring difference settings of both 85 and 322. Tumor lesion and healthy-tissue uptake was quantified and compared between the differently obtained parametric images to assess quantitative accuracy. Results: Good agreement was obtained between direct- and image-based Patlak analyses using the IDIF (t* = 30 min) and scaled PIF at 30-60 min after injection, performed using the different approaches, with no more than 8.8% deviation in tumor influx rate value (Ki ) (mean difference ranging from -0.0022 to 0.0018 mL/[min × g]). When direct Patlak reconstruction was performed on the system console, excellent agreement was found between the use of a scaled PIF at 30-60 min after injection versus 55-65 min after injection, with 2.4% deviation in tumor Ki (median difference, -0.0018 mL/[min × g]; range, -0.0047 to 0.0036 mL/[min × g]). For different maximum crystal ring difference settings using the scan time interval of 55-65 min after injection, only a 0.5% difference (median difference, 0.0000 mL/[min × g]; range, -0.0004 to 0.0013 mL/[min × g]) in tumor Ki was found. Conclusion: Ultrashort whole-body [18F]FDG Patlak imaging is feasible on an LAFOV Biograph Vision Quadra PET/CT system without loss of quantitative accuracy to assess lung tumor uptake compared with a full-duration 65-min acquisition. The ultrashort 10-min direct Patlak reconstruction with PIF allows for its implementation in clinical practice.

Does Intralesional Steroid Injection Effectively Mitigate Vocal Fold Scarring in A Rabbit Model?

To assess the efficacy of intralesional steroid treatment in preventing vocal fold scarring following vocal fold surgery using a rabbit model. The research involved 42 male New Zealand white rabbits. Fourteen rabbits underwent vocal fold scar surgery using a 532nm laser and served as controls (control group). The remaining rabbits were divided into two groups of 14: one group received vocal fold scar surgery followed by dexamethasone injection (Dexa group) and the other received the same surgery followed by triamcinolone injection (Triam group). Four weeks after surgery, histological examinations and high-speed video analyses of vocal fold vibration were conducted. The maximum amplitude of vibration was the primary measure for assessing vocal fold function. In addition, real-time polymerase chain reaction (PCR) studies were undertaken to analyze scar regeneration and remodeling. The maximum amplitude differences were notably higher in the Dexa and Triam groups than in controls. Histologically, the collagen density (CD) ratios in both the Dexa and Triam groups were significantly reduced compared with controls. Real-time PCR analysis indicated marked elevations of Has-2 and Mmp-9 in the Dexa and Triam groups relative to controls. Intralesional steroid injections after vocal fold surgery are effective for reducing vocal fold scarring in a rabbit model. NA Laryngoscope, 2024.