Maximum Difference Research Articles

Short- and long-term stability of synovial fluid calprotectin.

Information about analyte stability is of crucial importance. The aims of this study were to determine the short- and long-term stability of synovial fluid calprotectin at various temperature conditions (4-8 °C for 7 days, - 20 °C and - 80 °C for 6 weeks). Eleven samples from patients were included in this study. The samples were promptly transported at room temperature (RT) to the laboratory immediately after arthrocentesis. Upon arrival, the samples were transferred into plastic tubes without additives and pretreated with hyaluronidase solution. After centrifugation at 1500xg for 10 minutes at RT, the baseline calprotectin concentrations were determined. Seven aliquots were stored in LoBind tubes (Eppendorf) at 4-8 °C and the calprotectin was measured every day. Six additional aliquots were stored at temperatures - 20 °C and - 80 °C and the concentration of calprotectin was measured weekly. Analysis was done using Buhlmann fCAL turbo reagent on analyzer Siemens Atellica Solution (Siemens Healthcare, Erlangen, Germany). Data were analyzed by Microsoft Excel and MedCalc statistical software. The percentage difference (PD%) was calculated. The maximum permissible difference (MPD) was 9.1% for PD%. The PD% with the corresponding 95% confidence intervals were inside the predefined MPD. The instability equations and correlation coefficient for storage temperatures were PD% = 0.1644 x time (day), r = 0.06, P = 0.614 for 4-8°C, PD% = 0.5190 x time (week), r = - 0.22, P = 0.080 for - 20°C, and PD% = 0.1316 x time (week), r = 0.08, P = 0.545 for - 80°C. The calprotectin in the synovial fluid is stable when stored long-term for 6 weeks at - 20 °C or at - 80 °C or short-term (7 days) at 4-8 °C.

The effect of solar thermal energy storage on natural gas heating systems: An experimental and techno-economic investigation

This study investigates the storage of solar thermal energy using thermal oils in Kilis, Türkiye, a region characterized by high solar potential. Both experimental and modeling studies were conducted. Mobiltherm 605 and PO Heat Transfer Oil 32 were tested as alternatives to commonly used oils. PO Heat Transfer Oil 32 was introduced to the literature for the first time. The impact of operating temperature, water flow rate, and outdoor temperature on the efficiency of stored thermal energy in the water heating system was examined. The findings revealed that system efficiency averaged 42 % at a nighttime outdoor temperature of 9 °C but decreased to 36 % at 13.5 °C. Efficiency was also 36 % at a flow rate of 0.7 m/s, decreasing to 24 % at 0.24 m/s. Mobiltherm 605 cooled down later than PO 32 in the thermal tank, indicating a higher heat transfer coefficient for PO 32. Based on experimental data, a model of the thermal storage system was developed, and its techno-economic feasibility was assessed. Using this model, a techno-economic analysis was performed and the potential for this clean energy to reduce reliance on natural gas combi boilers for heating was discussed. For a building with a maximum indoor-outdoor temperature difference of 20 °C and a heating requirement of 467 kWh over 14 h, the thermal energy cost was estimated to be $0.029/kWh. This implementation reduced carbon emissions by 130 kg/day. The total equipment cost for the thermal storage system, with a U-type Vacuum Tube Collector (U-VTC) area of approximately 380 m2, was $295,697. In conclusion, both Mobiltherm 605 and PO Heat Transfer Oil 32 demonstrated comparable price/performance ratios relative to common oils.

A Novel Paraffin Wax/Expanded Graphite/Bacterial Cellulose Powder Phase Change Materials for the Dependable Battery Safety Management

Although phase change materials (PCMs) exhibit effective performance in the thermal management of lithium-ion batteries (LIBs), their development is limited by low thermal conductivity and susceptibility to leakage during the solid–liquid phase transition. To address these challenges and enhance thermal management capabilities, this study introduces a novel composite phase change material (CPCM) synthesized by physically mixing paraffin (PA), expanded graphite (EG), and bacterial cellulose (BC). The thermal performance of CPCMs with varying BC proportions is evaluated, and their impact on temperature control in battery thermal management systems (BTMS) is assessed. The results show that the addition of EG and BC significantly improves the thermal conductivity of the CPCM, reaching a value of 1.39 W·m−1·K−1. This also enhances the uniformity of temperature distribution within the battery module and reduces CPCM leakage. By comparing temperature variations within the battery module under different operating conditions, it was found that the intricate network structure of the CPCM promotes uniform temperature distribution, effectively mitigating temperature rise. Consequently, the maximum temperature and maximum temperature difference within the battery module were maintained below 47 °C and 4 °C, respectively. Compared to a system without phase change material at a 3C discharge rate, the maximum cell temperature, maximum module temperature, and maximum temperature difference were reduced by 32.38%, 26.92%, and 34.94%, respectively. These findings provide valuable insights for the design and optimization of BTMS.

Testing Similarity of Parametric Competing Risks Models for Identifying Potentially Similar Pathways in Healthcare.

The identification of similar patient pathways is a crucial task in healthcare analytics. A flexible tool to address this issue are parametric competing risks models, where transition intensities may be specified by a variety of parametric distributions, thus in particular being possibly time-dependent. We assess the similarity between two such models by examining the transitions between different health states. This research introduces a method to measure the maximum differences in transition intensities over time, leading to the development of a test procedure for assessing similarity. We propose a parametric bootstrap approach for this purpose and provide a proof to confirm the validity of this procedure. The performance of our proposed method is evaluated through a simulation study, considering a range of sample sizes, differing amounts of censoring, and various thresholds for similarity. Finally, we demonstrate the practical application of our approach with a case study from urological clinical routine practice, which inspired this research.

Cost-effectiveness of follow-up algorithms for chronic thromboembolic pulmonary hypertension in pulmonary embolism survivors

IntroductionAchieving an early diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH) in pulmonary embolism (PE) survivors results in better quality of life and survival. Importantly, dedicated follow-up strategies to achieve an earlier CTEPH diagnosis involve costs that were not explicitly incorporated in the models assessing their cost-effectiveness. We performed an economic evaluation of 11 distinct PE follow-up algorithms to determine which should be preferred.Materials and methods11 different PE follow-up algorithms and 1 hypothetical scenario without a dedicated CTEPH follow-up algorithm were included in a Markov model. Diagnostic accuracy of consecutive tests was estimated from patient-level data of the InShape II study (n=424). The life-long costs per CTEPH patient were compared and related to Quality-Adjusted Life-Years (QALYs) for each scenario.ResultsCompared to not performing dedicated follow-up, the integrated follow-up algorithms are associated with an estimated increase of 0.89–1.2 QALY against an incremental cost-effectiveness ratio (ICER) of 25 700–46 300 € per QALY per CTEPH patient. When comparing different algorithms with each other, the maximum differences were 0.27 QALY and €27 600. The most cost-effective algorithm was the InShape IV algorithm, with an ICER of €26 700 per QALY compared to the next best algorithm.ConclusionSubjecting all PE survivors to any of the currently established dedicated follow-up algorithm to detect CTEPH is cost-effective and preferred above not performing a dedicated follow-up, evaluated against the Dutch acceptability threshold of €50 000 per QALY. The model can be used to identify the locally preferred algorithm from an economical point-of-view within local logistical possibilities.

Radiation shielding transmission data for modern digital radiography.

Radiography is one of the most widely used x-ray imaging modalities. In National Council on Radiation Protection and Measurements (NCRP) Report No. 147, transmission data for radiographic systems were evaluated on those installed before 2000. For x-ray systems (except intraoral dental) manufactured on or after June 10, 2006, the U.S. required minimum half-value layer (HVL) was increased; for example, 2.9 (2.3) mm Al at 80kV, where the value in parenthesis denotes the earlier requirement before the above date. To calculate the transmission of the broad x-ray beam of modern digital radiography (DR) through shielding materials. X-ray beam HVLs on two DR systems (Agfa DR 600, GE Revolution XR/d) were measured in 10kV increments between 60 and 120kV, with a calibrated ionization chamber (Radcal model 10×5-60) and varying thickness of aluminum 1100 plates. Monte Carlo (Geant4) simulation was performed to calculate the transmission of broad x-ray beams through lead, concrete, gypsum, and steel, with x-ray HVLs matching those of the DR 600 at two beam filtrations (default, 1mm Al plus 0.1mm Cu added filtration). The transmission data were fitted to the Archer equation. HVLs on two DR systems with default beam filtration were consistent (median difference, 2.1%; maximum difference, 5.5%). An additional beam filtration option (1mm Al plus 0.1mm Cu) on the DR 600 substantially increased HVLs by 45.2%-61.2%. Transmission fitting parameters were provided for seven tube voltages (60-120kV) at two beam filtrations. This work presents transmission data for modern DR systems, indicating increased x-ray beam filtration compared to the primary x-ray beam in NCRP Report No. 147. The updated transmission data can enhance structural shielding evaluations at individual tube voltages or with a workload distribution.

Thermodynamic and economic analysis of a novel compressed air energy storage system coupled with solar energy and liquid piston energy storage and release

Compressed air energy storage (CAES) is one of the important means to solve the instability of power generation in renewable energy systems. To further improve the output power of the CAES system and the stability of the double-chamber liquid piston expansion module (LPEM) a new CAES coupled with liquid piston energy storage and release (LPSR-CAES) is proposed. The coupled LPEM conducts suction stage B at the end of the expansion stage, ensuring stable exhaust pressure and temperature for the module. By establishing the thermodynamic and economic models of LPSR-CAES, the effect laws of key node parameters on the system performance are investigated. The results show that the heat transfer between liquid droplets and air dominates the heat transfer in LPEM. The proposed LPEM exhibits excellent isothermal performance and stability, with a maximum temperature difference of about 20 K during the cycle, and stable exhaust temperature changes within 10 K. Under the design conditions, the converted electrical efficiency, round-trip efficiency, exergy efficiency and net present value of the system are 68.31 %, 58.86 %, 66.99 % and 12.25 M$ respectively. The higher the solar supplement temperature, the more outstanding the thermal and economic performance of the system. The short-term energy storage system performance of the proposed system is more prominent. Based on the actual light data, the system can achieve 72.09 % and 69.41 % of converted electrical efficiency and exergy efficiency, respectively, at the 219th day. The results of this study provide theoretical support for the engineering application of the proposed system.

Multi-UAV Cooperative Pursuit of a Fast-Moving Target UAV Based on the GM-TD3 Algorithm

Recently, developing multi-UAVs to cooperatively pursue a fast-moving target has become a research hotspot in the current world. Although deep reinforcement learning (DRL) has made a lot of achievements in the UAV pursuit game, there are still some problems such as high-dimensional parameter space, the ease of falling into local optimization, the long training time, and the low task success rate. To solve the above-mentioned issues, we propose an improved twin delayed deep deterministic policy gradient algorithm combining the genetic algorithm and maximum mean discrepancy method (GM-TD3) for multi-UAV cooperative pursuit of high-speed targets. Firstly, this paper combines GA-based evolutionary strategies with TD3 to generate action networks. Then, in order to avoid local optimization in the algorithm training process, the maximum mean difference (MMD) method is used to increase the diversity of the policy population in the updating process of the population parameters. Finally, by setting the sensitivity weights of the genetic memory buffer of UAV individuals, the mutation operator is improved to enhance the stability of the algorithm. In addition, this paper designs a hybrid reward function to accelerate the convergence speed of training. Through simulation experiments, we have verified that the training efficiency of the improved algorithm has been greatly improved, which can achieve faster convergence; the successful rate of the task has reached 95%, and further validated UAVs can better cooperate to complete the pursuit game task.

The current status of nurses’ psychological experience as second victims during the reconstruction of the course of event after patient safety incident in China: a mixed study

BackgroundPatient safety incidents are unavoidable and nurses, as parties involved, become second victims due to the incident itself and the way it is handled. In China, reconstructing the course of events is a crucial step in the aftermath of the incident; however, its impact on the emotional well-being of the second victim remains unclear.PurposeThe purpose of this study is to gain insight into the psychological experiences and current conditions of nurses who act as second victims during the process of reconstructing the sequence of events. Additionally, the study aims to provide justifications for supporting these individuals.MethodsAn exploratory mixed research method was adopted to understand the emotional experience of the second victim when reconstructing the passage of the incident through qualitative research. Fourteen nurses with experience as second victims were selected for semi-structured interviews using purposive sampling according to the maximum difference sampling strategy. Through quantitative research, we explored the negative psychology and support needs of the second victims when they reverted to the incident, and a self-developed questionnaire (the Cronbach’s alpha coefficient was 0.895) was used to survey 3,394 nurses with experiences as second victims in 11 tertiary hospitals in Shanxi Province.ResultsIn the qualitative part of the study, the emotional experience of the second victim’s reconstruction of the course of events after a patient safety incident could be categorized into 3 themes: negative views as initial psychological impact, avoidance as part of psychological impact, and expectations and growth in overcoming negative psychological impact. The quantitative part of the study revealed that the emotions of guilt and self-blame accounted for the highest percentage after a patient safety incident. The second victim presented a high score of 39.58 ± 5.45 for support requirements.ConclusionThis study provides a better understanding of the true emotional experiences and the need for support of the second victim in the process of reconstructing the course of events. Following a patient safety incident, nursing administrators and healthcare institutions should consider the adverse psychological effects on the second victim, prioritize their support needs during the incident’s reconstruction, create a positive safety culture, and reduce the risk of secondary victimization for these individuals.

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 shoe/foot 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.