Pressure Data Research Articles

Thermodynamics of (NH4)2SO4(aq) and Solubilities of (NH4)2MII(SO4)2·6H2O (M = Mg, Fe, Zn, Cu) Tutton Salts with Implications to Thermochemical Storage

Abstract Available thermodynamic data for (NH4)2SO4(aq) have been critically evaluated and used to parameterize an extended ion interaction (Pitzer) model. The model satisfactorily represents the available activity and thermal data from below the eutectic temperature to 110 °C. At near ambient temperatures (5–40 °C) the model accurately predicts the water activities in supersaturated solutions to about 30 mol·kg–1. The model has been used to determine the solubility products of (NH4)2SO4(s) from the eutectic temperature to 110 °C. Solubilities in the ternary Tutton salt forming systems (NH4)2SO4–MgSO4–H2O, (NH4)2SO4–FeSO4–H2O, (NH4)2SO4–ZnSO4–H2O, and (NH4)2SO4–CuSO4–H2O have been used to determine the ternary interaction parameters in the Pitzer model and to calculate the solubilities and deliquescence humidities of the Tutton salts (NH4)2MIISO4·6H2O (with M = Mg, Fe, Zn, Cu). Using additional literature data of decomposition vapor pressures, the phase diagrams of the Tutton salts have been established and the suitability of the salts as thermochemical heat storage materials has been critically evaluated.

Significant Wave Height Cluster Analysis to Understand the Spatial Variation of Ocean Waves in Low Energy Systems

Abstract Understanding spatial variation in ocean waves is critical for erosion planning and infrastructure projects. The study is aimed at (1) performing a cluster analysis to categorize the wave statistics over space and (2) determining the important drivers affecting spatial variations of wave statistics in a low energy, fetch limited environment. In this study, 29 wave gauges were deployed in Back Bay Biloxi, Mississippi. Raw pressure and processed wave height were clustered using two algorithms: Euclidian and Dynamic Time Warping. The Euclidean algorithm was applied to raw and processed data. However, due to the computationally expensive nature of Dynamic Time Warping, this algorithm could not be used on raw pressure data and was only applied to processed wave data. Therefore, three combinations of distance algorithms and data were compared: (1) Euclidean algorithm on raw pressure data, (2) Euclidean algorithm on processed wave height data, and (3) Dynamic Time Warping algorithm on processed wave height data. The results showed similar clustering for Euclidean and Dynamic Time Warping on processed data, with most gauges falling into one cluster. Results from this study reveal that the dendrogram trees of the Euclidean and Dynamic Time Warping algorithms on processed data are similar, where most of the wave gauges fall in one cluster. Conversely, the Euclidian algorithm on the raw pressure data distributed the wave gauges more evenly between the clusters. Additionally, the Euclidean algorithm on the raw pressure data showed that water depth significantly affects wave clustering.

The Relationship Between Physical Activity and Hypertension Prevention in Adolescents

Hypertension or high blood pressure is a serious health problem and is common among teenagers. Hypertension is not only a major cause of cardiovascular disease, but also contributes significantly to the global health burden. According to data from the 2023 Indonesian Health Survey (SKI), the prevalence of hypertension in Indonesia has reached an alarming figure. This research method uses quantitative methods by collecting data through questionnaires. This questionnaire is designed to measure the independent variable, namely physical activity, and the dependent variable, namely blood pressure. Based on the results of the questionnaire, physical activity and blood pressure data were obtained from 32 respondents. Data was collected through questionnaires distributed to 32 teenagers aged 18 to 22 years. Based on Table 2, the correlation between frequency of physical activity (∑x1) and blood pressure (∑y) is 0.413* with p 0.019. This shows that there is a significant positive relationship between how often adolescents engage in physical activity and their blood pressure. These results emphasize the importance of promoting physical activity among adolescents as a hypertension prevention strategy. Physical activity is not only beneficial for cardiovascular health but also plays an important role in maintaining overall health.

Does Mini-Percutaneous Nephrolithotomy Cause Increased Intrarenal Pressure During Percutaneous Nephrolithotomy and is This Mitigated by a Suctioning Sheath? A Randomized Control Trial.

Introduction: Intrarenal pressure (IRP) generated during percutaneous nephrolithotomy (PCNL) may have the potential to cause renal damage and/or sepsis. It has been suggested that mini-PCNL (mPCNL) can further increase IRP but that a suctioning sheath may mitigate this elevation. We sought to measure IRP throughout the PCNL process, randomizing patients getting mPCNL to receiving two different mPCNL sheaths, one suctioning and the other nonsuctioning, and then comparing them with patients undergoing standard PCNL (sPCNL) using a 24F sheath. Patients and Methods: Twenty patients meeting the eligibility criteria for mPCNL were randomized into two groups: suctioning mPCNL (s-mPCNL) with a single-step dilator and continuous suction sheath (ClearPetra™, 18F, n = 10) and nonsuctioning mPCNL (ns-mPCNL) with a metallic dilator and sheath (Storz MIP-M™, 17.5F, n = 10). A group of 10 patients undergoing sPCNL using a balloon dilator with a Polytetrafluoroethylene (PTFE) sheath (NephroMax™, 24F, n = 10) were included as a control. IRP was measured with a 0.014″ COMET™ II Pressure guidewire retrogradely positioned in the renal pelvis. Gravity irrigation was utilized. Pressure data captured include baseline IRPs, retrograde pyelogram (RPG), needle entry, fascial dilation, tract dilation, sheath insertion, nephroscopy, and lithotripsy. The primary outcome was differences in mean and peak IRP during each stage. Categorical data were compared using chi-square or Fisher's exact tests. Continuous variables were analyzed using one-way analysis of variance. Results: Peak and mean IRPs (millimeters of mercury or mm Hg) were similar at baseline and during RPG, needle insertion, and fascial dilation in the two experimental groups and in the control group. During tract dilation and sheath placement, both the mPCNL sheaths generated much higher peak IRP compared with the 24F balloon dilation control group but similar to each other (dilation: 36.6 and 38.6 vs 6.9, p < 0.001; sheath placement: 36.6 and 35.3 vs 13.8, p = 0.039). During nephroscopy, ns-mPCNL generated greater peak IRP compared with s-mPCNL and the control group (41.8 vs 19.09 and 24.15; p = 0.019). The highest peak IRP for each group occurred during RPG and when a nephroscope was placed through a narrow infundibulum. Conclusions: Compared with balloon dilation, coaxial dilation with mPCNL sheaths generates significantly higher IRP. During nephroscopy, ns-mPCNL sheaths generate higher IRP compared with standard and suctioning sheaths. Highest IRPs are generated during RPG and when a nephroscope goes through a narrow infundibulum. These findings can inform improved sheath and nephroscope design. Further research assessing the effect of high IRP on postoperative pain, sepsis, and renal injury is needed.

Detailed validation of LES for H[formula omitted]/CH[formula omitted]/Air deflagrations in an obstructed tube using PIV measurements

This study offers a detailed validation of Large Eddy Simulation (LES) for lean H2/CH4/Air deflagrations in an obstructed tube. An exhaustive validation is conducted against detailed measurements from Li et al. (2019), which include pressure traces, flame speeds, and especially, Particle Image Velocimetry measurements of the deflagration-induced flow field. The exercise is performed without adjusting any model parameters, so that all simulations are executed using a unique numerical setup across all test cases. This approach provides a robust and unbiased assessment of LES capabilities in capturing the complex interactions between flame propagation, turbulence, and obstacles in explosion scenarios. Results demonstrate that LES accurately predicts the detailed evolution of the flow field in the recirculation zone behind the second obstacle, and the resulting over-pressure as well as flame speed and flame qualitative shape for various deflagration severities. Such results highlight the potential of LES for improving Safety Computational Fluid Dynamics predictive capabilities in industrial applications involving explosive environments. Once validated, LES is analyzed to unravel flame propagation dynamics: It is demonstrated that the flame remains laminar-like up to the second obstacle and then transitions to the turbulent combustion regime. Independently from the mixture blend, the maximum over-pressure is correlated to flame-turbulence interactions occurring in the wake of the second obstacle. While LES effectively captures these dynamics, it is noted that usual methods to quantify flows in pipes are inadequate for fully characterizing the transition to turbulence: Developing more refined indicators to detect this transition are required.Novelty and significance statementThis study presents a significant advancement in the validation of Large Eddy Simulation (LES) for complex deflagration scenarios within obstructed geometries. Unlike previous works that typically rely on pressure data, flame speeds, and basic visualizations, this research integrates comparisons to Particle Image Velocimetry measurements for a quantitative validation of LES deflagrations in obstructed channels. By leveraging the detailed experimental dataset from Li et al. (2019), this paper establishes a new benchmark for simulation accuracy, demonstrating LES ability to capture complex flame-turbulence interactions in confined spaces. This work not only addresses the critical gap in the literature but also opens the way for advancements in Safety Computational Dynamics, setting a higher standard for future simulation studies.

Experimental DMD Analysis of Combustion Modes and Instabilities in a Scramjet Combustor

The combustion characteristics of a gaseous hydrogen fueled scramjet combustor were experimentally investigated through single-shot micro-pulse detonation engine (μPDE) operations across a range of fuel injection pressures and corresponding equivalence ratios. This study utilized a lab-scale direct-connect scramjet combustor integrated with a μPDE, designed to simulate flight conditions at Mach numbers between 4.0 and 5.0 at altitudes of 20 to 25 km. Static wall pressure was measured using 16 pressure probes from the isolator to the scramjet combustor at a sampling rate of 500 Hz. Additionally, Z-fold type Schlieren and flame luminosity were captured using a high-speed camera in a test section equipped with a quartz visualization window. Experiments were conducted under five conditions with equivalence ratios ranging from 0.10 to 0.55, each performed three times to ensure repeatability. Fast Fourier transform (FFT) and dynamic mode decomposition (DMD) analyses were applied to the pressure and image data obtained. Although auto-ignition was not achieved in all cases, combustion persisted while fuel was injected following the single-shot μPDE ignition. This allowed for the identification of distinct combustion modes according to equivalence ratio, by observing the dominant flame types and the shock structure within the flow of the combustor. These combustion modes showed different types of instability.

Sloshing in tanks with an internal horizontal perforated plate based on an immersed-boundary generalized harmonic polynomial cell method

This study explores the challenges of sloshing in rectangular tanks, focusing on the use of an internal perforated plate to mitigate its adverse effects. A novel numerical flow model is developed to examine sloshing dynamics involving these plates. The Navier–Stokes equations are solved using the projection method on a Cartesian grid, while a newly adapted immersed-boundary generalized harmonic polynomial cell method is employed to solve the Poisson equation within this framework. The solver's accuracy is validated through comparisons of free surface profiles, pressure, and velocity data with experimental results, demonstrating reliable performance in simulating sloshing phenomena. The research emphasizes optimizing the placement of perforated plates within the tank to maximize energy dissipation and minimize structural forces. The findings demonstrate that strategically positioning perforated plates effectively mitigates violent resonant sloshing caused by horizontal excitation, highlighting the critical influence of plate location on tank performance. These insights are instrumental for enhancing tank stability in engineering applications such as liquid cargo transportation, offshore storage facilities, and fuel tank design for aerospace and automotive industries, where precise control of fluid dynamics is essential for safety and operational efficiency.

Human pressures threaten diet-specialized mammal communities.

Environmental change is increasing worldwide and many animal species face anthropogenic threats, especially diet specialists. Yet the degree to which specialist species are currently impacted by environmental change remains poorly understood. We examine how anthropogenic pressures impact dietary specialist species. We calculated indices of diet specialization for mammal species, based on the Gini inequality coefficient, and combined these indices with human pressure data. We then used spatially explicit Mantel tests to examine global patterns in mammal diet specialization. We used a generalized linear mixed model to investigate correlations between the percentage of diet specialist species in mammal communities in an area and its total species richness, human pressure and protection status (mediated through an interaction with the continent). Findings revealed that areas with many diet specialists in mammal communities are also impacted by high human pressure. Additionally, we found that the global protected area system adequately covers habitat for many mammal diet specialists, but has lower effectiveness in South America, Oceania, North America and Europe compared with Africa and Asia. Finally, we identified potential reservoirs for specialist species-places containing many highly diet specialist species and that are subject to less human pressure-which may be important for conservation efforts.

Evaluating interface pressure in a lower-limb prosthetic socket: Comparison of FEM and experimental measurements on a roll-over simulator.

Improper socket fitting in lower-limb prostheses can lead to significant complications, including pain, skin lesions, and pressure ulcers. Current suspension and socket design practices rely predominantly on visual inspection of the residual limb and patient feedback. Monitoring stress distribution at the residual limb/socket interface offers a more objective approach. Finite Element Analysis (FEA) enables to estimate interface pressure distribution prior to manufacture to provide the orthoprosthetist with quantitative data during socket rectification and interface prosthetic components selection. However, although numerous FEA models are available, few have undergone rigorous validation against experimental pressure data. Indeed, limitations of commercial pressure sensors typically include cumbersomeness or imprecision, thereby hindering systematic measurements within the socket. In this study, we introduce a low-cost, accurate pressure sensing system integrated into 3D-printed sockets for FEA validation. The system is implemented on a roll-over simulator that uses a mock limb to mimic the interaction between a transtibial residual limb and socket during the unipodal stance phase. A FEA of the simulator was then conducted, and predicted interface pressures were compared to experimental measurements at seven discrete locations. The model demonstrated a high degree of sensitivity to the geometry of the mock limb; however, with an accurate shape description, it was able to predict pressure with an average absolute error of 12kPa. This work advances the validation of residual limb FEA for estimating residual limb/socket interface pressures. It highlights the potential of FEA for designing data-driven sockets and ultimately improve the comfort of prosthesis users.

Influence of internal fluid driving mechanisms on red bed bleaching in the Paradox Basin (Colorado Plateau, Utah and Colorado, USA)

While it has been known for some time that reducing fluids have bleached red beds adjacent to fault zones and regionally across the Colorado Plateau, the volumes of fluids expelled along faults have never been quantified. We have developed and applied a suite of one-dimensional hydrologic models to test the hypothesis that internally generated, reducing fluids migrated up sub-basin bounding faults across the Paradox Basin and bleached overlying red beds. The internal fluid driving mechanisms included are mechanical compaction, petroleum and natural gas generation, aquathermal expansion of water, and clay dewatering. The model was calibrated using pressure, temperature, porosity, permeability, and vitrinite reflectance data. Model results indicate that sediment compaction was the most important pressure generation mechanism, producing the majority of internal fluids sourced during basin evolution. Peak fluid migration occurred during the Pennsylvanian−Permian (325−300 Ma) and Cretaceous (95−65 Ma) periods, the latter being concurrent with simulated peak oil/gas generation (87−74 Ma), which likely played a role in the bleaching of red beds. Batch geochemical advection models and mass balance calculations were utilized to estimate the volume of bleaching in an idealized reservoir having a thickness (∼100 m) and porosity (0.2) corresponding to bleached reservoirs observed in the Paradox Basin. Bleaching volume calculations show that internal fluid driving mechanisms were likely responsible for fault-related alteration observed within the Wingate, Morrison, and Navajo Formations in four localities across the Paradox Basin in the Colorado Plateau, Utah and Colorado, USA. The volume calculation required that 33%−55% of the total basinal fluids, composed of hydrogen-sulfide and paleo-seawater, migrated into an overlying red bed reservoir (0.5 wt% Fe2O3).

Dynamic balance control in healthy young women during stair descent: a plantar pressure-based study

BackgroundWomen are more likely to fall or even die when the ladder falls, which seriously affects the quality of daily life. It is necessary to better understand the plantar mechanism of the ladder falls and put forward reasonable suggestions.MethodTwenty healthy young women volunteered to participate in the experiment. The study used the F-scan plantar pressure to explore the difference in the plantar pressure in the dominance of the leading foot across four step descent height conditions. The landing strategy employed was recorded during the experiment. The Center of Pressure (COP), along with its medial-lateral (ML) and anterior-posterior (AP) adjustment velocities, and the VCOP, RCOP-ML, and RCOP-AP were analyzed.ResultWith an increase in the step height, significant enhancements were observed in the VCOP-ML (p &amp;lt; 0.001), VCOP-AP (p &amp;lt; 0.001), RCOP-ML (p &amp;lt; 0.001), and RCOP-AP (p &amp;lt; 0.001) during landing. There was no significant difference in the kinematic parameters of plantar pressure during stair descent, regardless of whether the dominant foot or non-dominant foot was the leading foot.ConclusionThis study found that among young women, an increase in step height during descent significantly affected the plantar pressure and led to greater COP adjustment in the directions of ML and AP, increasing the risk of injury. At a step height of 5 cm, the first choice of the landing strategy for female subjects began to change from the hindfoot to the forefoot. Although there were no significant differences in plantar pressure data and landing strategies between subjects using the dominant side and nondominant side as the forefoot, the dominant side forefoot exhibited better postural balance control than the nondominant side forefoot.

The Effect of Warm Water Foot Soaking Therapy on Reducing Blood Pressure in Elderly with Hypertension

A person's old age will experience a decrease in the function and structure of body organs so that it has an impact on the reduced ability to respond to stimuli that come from inside or outside his body. One of the health problems that tends to occur in the elderly is hypertension. Hypertension is abnormal blood pressure where the systolic pressure is more than 140 mmHg and the diastolic pressure is more than 90 mmHg. The management of hypertension is divided into two, namely pharmacological and non-pharmacological therapy, one of which is foot soaking therapy with warm water to lower blood pressure in the elderly which is easy and effective to be done independently at home. The purpose of this study is to determine the effect of foot soaking therapy with warm water on the reduction of blood pressure in the elderly suffering from hypertension in the working area of the Batudaa Health Center.The design of this study uses a pre-experiment with one group pre and post test given an intervention to the subjects. The population in this study is 116 elderly people who are recorded as hypertension sufferers in the working area of the Batudaa Health Center. The total sample in this study is 16 respondents. The results of the Paired Test of the T-test sample showed a difference in the values in the pre-test and post-test blood pressure data before and after the intervention of foot bath therapy with warm water where a p-value of 0.000 was obtained. It is hoped that the Health Center can provide input on non-pharmacological therapies to the elderly that can prevent, control, and lower blood pressure in addition to consuming anti-hypertensive drugs.

Detection of Pipe Ruptures in Shipboard Firefighting Systems Using Machine Learning and Deep Learning Techniques

In this paper, the application of machine learning and deep learning algorithms for fault and failure detection in maritime systems is examined, specifically focusing on the detection of pipe ruptures in a ship’s saltwater firefighting (FiFi) system using pressure sensor data. Neural network models were developed to distinguish between normal operational states and anomalies, as well as to accurately locate pipe faults within the ship. Data were collected using real-world tests with FiFi system sensors, capturing both normal operations and simulated pipe ruptures, and were meticulously labeled to facilitate neural network training. Two neural network models were introduced: one for classifying system states (normal or anomalous) based on time-series pressure data, and another for identifying the location of anomalies related to pipe ruptures. Experimental results demonstrated the efficacy of these models in detecting and localizing pipe faults, with performance evaluated using mean squared error (MSE) across different network configurations. The successful implementation of these machine learning and deep learning algorithms highlights their potential for enhancing maritime safety and operational efficiency.

Comparative analysis of computer-programmed versus artificial right arm blood pressure measurement in detecting hypertension among elderly individuals

Objective: To compare the impact of manual right arm blood pressure measurement with computer-controlled blood pressure meter (CCBPM) on the detection rate of hypertension among elderly individuals. Method: This was a cross-sectional study. Elderly residents undergoing routine health check-up in a village in Jiangxi Province from April to June 2024 were enrolled. Manual blood pressure measurements were performed on the right arm using an electronic sphygmomanometer, while standardized dual-arm synchronized blood pressure assessments were conducted using the CCBPM. Blood pressure data were recorded from three sources: manual measurement on the right arm; the first CCBPM measurement on the arm with higher systolic blood pressure (CCBPM single); and the mean blood pressure of the arm with higher systolic blood pressure from two (if the difference between the first two measurements was less than 5 mmHg, 1 mmHg=0.133 kPa) or three (if the difference exceeded 5 mmHg) CCBPM measurements (CCBPM mean). Hypertension detection rates from these three datasets were compared. Subgroup analysis was performed according to age (60-74 years old as the elderly group,≥75 years old as the senior group) and gender. Intra-group correlation coefficient (ICC) was analyzed to evaluate the consistency of blood pressure data of different blood pressure measurement methods, and Kappa value was analyzed to evaluate the consistency of hypertension classification determined by different blood pressure measurement methods. Results: A total of 1 498 participants were enrolled, aged (71.30±6.83) years old, including 678 males (45.26%). The blood pressure and heart rate measured by the artificial right arm blood pressure measurement were higher than those measured by CCBPM single (blood pressure: (140.09±17.19)/(82.40±10.93) mmHg vs. (135.31±18.98)/(81.23±10.51) mmHg; heart rate: (75.76±11.72) beats/min vs.(72.94±11.21) beats/min) and CCBPM mean (blood pressure: (140.09±17.19)/(82.40±10.93) mmHg vs. (134.64±18.39)/(80.28±9.78) mmHg; heart rate: (75.76±11.72) beats/min vs. (72.87±10.70) beats/min, all P<0.05). The detection rate of hypertension determined by CCBPM mean was significantly lower than that of artificial right arm (40.25% (603/1 498) vs.54.34% (814/1 498)) and CCBPM single (40.25% (603/1 498) vs. 44.79% (671/1 498), all P<0.05). Subgroup analysis showed that that the detection rate of hypertension determined by CCBPM mean was lower than that measured by artificial right arm regardless of gender and age (all P<0.05). The consistency of blood pressure data between artificial right arm and the CCBPM mean was moderate (systolic blood pressure: ICC=0.70; diastolic blood pressure: ICC=0.62), with less consistent classification (Kappa=0.37). The consistency of blood pressure data between CCBPM single and CCBPM mean is extremely high (systolic blood pressure: ICC=0.94; diastolic blood pressure: ICC=0.91), with highly consistent classification (Kappa=0.74). Conclusions: Artificial right arm blood pressure measurement in physical examinations may overestimate the hypertension detection rate, and the standardized dual-arm synchronized blood pressure measurement using CCBPM can reduce irregular blood pressure measurement.

Use of Pressure Transient Analysis Method to Assess Fluid Soaking in Multi-Fractured Shale Gas Wells

Multi-stage hydraulic fracturing is a key technology adopted in the energy industry to make shale gas and shale oil fields profitable. Post-frac fluid soaking before putting wells into production has been found essential for enhancing well productivity. Finding the optimum time to terminate the fluid-soaking process is an open problem to solve. Post-frac shut-in pressure data from six wells in two shale gas fields were investigated in this study based on pressure transient analysis (PTA) to reveal fluid-soaking performance. It was found that pressure-derivative data become scattering after 1 day of well shut in. The overall trend of pressure-derivative data after the first day of well shut in should reflect the effectiveness of fluid soaking. Two wells exhibited flat (zero-slope) pressure derivatives within one week of fluid soaking, indicating adequate time of fluid soaking. Four wells exhibited increasing pressure derivatives within one week of fluid soaking, indicating inadequate time of fluid soaking. This observation is consistent with the reported well’s Estimated Ultimate Recovery (EUR). This study presents a new approach to the assessment of post-frac fluid-soaking performance with real-time shut-in pressure data.

A vision-inertial interaction-based autonomous UAV positioning algorithm

Abstract In wartime scenarios where global navigation satellite system (GNSS) may be compromised, the cumulative errors associated with inertial navigation systems (INSs) can lead to significant positional deviations during long-distance navigation of drones. To address this issue, this study proposes an innovative vision-inertial interactive autonomous positioning algorithm that integrates visual positioning with inertial measurement unit-based methods, aiming to achieve enhanced system robustness and optimal positioning accuracy. The algorithm first implements an adaptive tile map level selection mechanism based on prior positional information from INS and onboard barometric pressure data, thereby mitigating the impact of inconsistent image scales. Subsequently, the proposed feature point extraction algorithm (Super Point V) effectively filters out invalid and interfering feature points from aerial images and tile maps. Finally, a novel matching mechanism for map expansion based on direction weights is employed to facilitate image matching and positioning, ensuring real-time accuracy and precision. Experimental results across various terrain conditions demonstrate that this approach not only enables accurate real-time computation of latitude and longitude but also effectively corrects the accumulated positioning errors of INS, achieving an average positioning accuracy error of only 4.94 m, comparable to that of conventional civilian GNSS, while maintaining excellent robustness.

Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis.

Plantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design. A sample of 30 healthy young male subjects with normal feet were recruited (age 23.56 ± 3.28years, height 1.76 ± 0.04m, weight 72.21 ± 5.69kg). Plantar pressure data were collected during 5 trials at the subjects' preferred walking speed (1.15 ± 0.04m/s). Foot soft tissue stiffness was recorded using a MyotonPRO biological soft tissue stiffness meter before each walking trial. A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. Mean impact value analysis was conducted in parallel to investigate the relative importance of different plantar pressure features. The predicted values for the training set are slightly higher than the actual values (MBE = 0.77N/m, RMSE = 11.89N/m), with a maximum relative error of 7.82% and an average relative error of 1.98%, and the predicted values for the test set are slightly lower than the actual values (MBE = -4.43N/m, RMSE = 14.73N/m), with a maximum relative error of 7.35% and an average relative error of 2.55%. Regions with highest contribution rates to foot soft tissue stiffness prediction were the third metatarsal (13.58%), fourth metatarsal (14.71%), midfoot (12.43%) and medial heel (12.58%) regions, which accounted for 53.3% of total contribution. The pressure features in the medial heel, midfoot area, and lateral mid-metatarsal regions during walking can better reflect plantar soft tissue stiffness. Future studies should ensure measurement stability of this region and refine insole designs to mitigate plantar soft tissue fatigue in the specified areas.

Metabolic Status and Hypertension: The Impact of Insulin Resistance-Related Indices on Blood Pressure Regulation and Hypertension Risk

Background Diabetes is closely related to hypertension, and insulin resistance-related indices are novel metrics used to evaluate the risk of diabetes and cardiovascular diseases. This study aims to explore the relationships between the TyG index, METS-IR, TG/HDL-C, and HOMA-IR with hypertension. Methods Data from the NHANES spanning ten consecutive survey cycles from 1998 to 2018 were utilized, focusing on adults with complete blood pressure data and comprehensive information for calculating the TyG index, METS-IR, TG/HDL-C, and HOMA-IR. A multivariable logistic regression model was employed to examine the relationship between insulin resistance indices and hypertension as well as blood pressure levels, while subgroup analyses were conducted to explore potential influencing factors. RCS curves were used to describe both linear and non-linear relationships. Results This NHANES-based study included 16,062 adults. Regardless of the adjustment for covariates, significant associations were found between the TyG index, METS-IR, TG/HDL-C, HOMA-IR and hypertension risk. The ROC curve demonstrated the stability of the TyG index, METS-IR, TG/HDL-C, and HOMA-IR in predicting hypertension risk. The RCS curves uncovered a linear relationship between the TyG index, METS-IR, and hypertension, whereas TG/HDL-C and HOMA-IR exhibited a non-linear association with hypertension. Subgroup analyses indicated that smoking and diabetes may influence the relationship between insulin resistance-related indices and hypertension. Conclusion Elevated levels of the insulin resistance indices TyG index, METS-IR, TG/HDL-C, and HOMA-IR are closely associated with hypertension risk. These indices can serve as effective markers for monitoring hypertension risk in clinical practice. However, larger-scale prospective cohort studies are needed to validate these findings and further explore the clinical application potential of the TyG index, METS-IR, TG/HDL-C, and HOMA-IR as tools for cardiovascular risk assessment. Such studies will help elucidate the specific causal relationships between these insulin resistance-related indices and hypertension and advance their practical application in clinical settings.

Fishing for Ocean Data in the East Australian Current

Knowledge of the three-dimensional structure and variability of ocean temperature is critical for understanding ocean circulation, heat uptake, marine extremes, and the abundance and distribution of marine life. While satellite technology offers near-global coverage of surface ocean temperatures, subsurface observations represent a big gap in the coastal ocean record. Here we present the first results from FishSOOP (Fisheries Ships of Opportunity), Australia’s pilot program that uses commercial fishing gear to collect subsurface ocean data. Since early 2023, temperature and pressure data have been collected through the FishSOOP project across the Australian continental shelf and upper-slope waters. These new data provide insights into the development of marine heatwaves throughout the water column and new understanding of how the East Australian Current interacts with shelf water to produce nonuniform temperature changes. Comparison with the South East Australian Coastal Ocean Forecasting System (SEA-COFS) model indicates potential for improving forecasts of upper ocean heat content and subsurface temperatures by filling large gaps in observational data coverage. FishSOOP already provides a step change in the amount of open access temperature data available as well as ocean information critical to marine industries for operational decision-making, showing the value of using fishing vessels to observe challenging western boundary current regions.

Unlocking the multidimensionality of plantar pressure measurements for the evaluation of footwear in people with diabetes.

The offloading effectiveness of custom-made footwear for people with diabetes is assessed using plantar pressure measurements. While such pressure data is multidimensional, it is mostly analyzed using a scalar - maximum peak plantar pressure (PMax). We aimed to investigate the associations between multiple peak plantar pressure parameters for footwear assessment and determine whether this assessment depends on the chosen parameter. In-shoe plantar pressure was measured in 77 participants with diabetes, peripheral neuropathy, and a recent ulcer or amputation history, while walking in their own custom-made footwear. Six peak plantar pressure parameters were extracted, both scalar (i.e. Pmax, time integral and gradient) and multidimensional (i.e. time curve, map and time map). Footwear was ranked from highest to lowest outcome for each parameter and associations with Pmax were compared using Spearman's rank correlation coefficient. A footwear comparison within subjects using Fleiss' Kappa analysis determined the agreement between parameters using two pairs of footwear of each participant. The rank correlation coefficient was moderate to strong between PMax and the other scalar parameters (ρ=0.46-0.70), and negligible to weak between PMax and the multidimensional parameters (ρ=0.03-0.25). Percentage agreement between parameters for the within-subject footwear comparison was poor (47.5%, κ=0.0652). We conclude that the association and agreement between in-shoe peak pressure parameters is low and the assessment of offloading effectiveness depends on the chosen parameter. This is the first step in unlocking the potential of a multidimensional approach in plantar pressure analysis, possibly changing how we evaluate footwear offloading effectiveness.