Search

This article explores the application of Optical Coherence Tomography (OCT) in evaluating the temperature variations during the sintering process of dental prosthetics. The study utilized OCT to examine metal-ceramic restorations at different sintering temperatures and generated cross-sectional images to identify defects and structural changes. The findings demonstrate that OCT can provide valuable insights into the impact of temperature deviations on ceramic microstructure, making it a useful tool for quality control in dental laboratories. The article suggests that integrating OCT into routine practices can offer a rapid, accurate, and non-destructive means of assessing sintering temperatures and detecting defects in dental ceramics. [Extracted from the article]

In this paper, we present experimental findings related to the measurement of air temperature within an enclosure. We utilized both a conventional temperature sensor and a UOTS (ultra-sensitive oscillating temperature sensor) for this purpose. The UOTS's output frequency was measured using a microcontroller's timer and direct memory access. In one experiment, we subjected the air inside the enclosure to rapid heating to evaluate the responsiveness of both sensors. In another experiment, the air temperature was indirectly increased through the laboratory's heating system. The initial experiment reaffirmed the superior responsiveness of the UOTS, as observed in previous tests. The second experiment, conducted over a duration of more than 20 h, allowed us to establish a frequency-temperature curve for the UOTS. It also enabled us to determine that the UOTS exhibits sensitivity at approximately 45 Hz per degree Celsius. This assessment provided valuable insights into temperature underestimation by the conventional temperature sensor, revealing a discrepancy of 9 °C during the rapid heating experiment. This quantified the significant advantage offered by the UOTS in terms of accuracy and responsiveness. [ABSTRACT FROM AUTHOR]

Purpose: Temperature monitoring in the perioperative setting often represents a compromise between accuracy, invasiveness of probe placement, and patient comfort. Transcutaneous sensors using the Zero-Heat-Flux (ZHF) and Double-Sensor (DS) technology have been developed and evaluated in a variety of clinical settings. The present study is the first to compare the performance of both sensors simultaneously with temperature measured by a Swan-Ganz catheter (PAC) in patients admitted to the intensive care unit (ICU) after cardiac surgery. Methods: In this monocentric prospective observational study patients were postoperatively transferred to the ICU and both sensors were placed on the patients' foreheads. Core body temperature measured by intraoperatively placed PAC served as gold standard. Measurements were recorded at 5-minute intervals and up to 40 data sets per patient were recorded. Bland and Altman's method for repeated measurements was used to analyse agreement. Subgroup analyses for gender, body-mass-index, core temperature, airway status and different time intervals were performed. Lin's concordance correlation coefficient (LCCC) was calculated, as well as sensitivity and specificity for detecting hyperthermia (≥ 38 °C) and hypothermia (< 36 °C). Results: Over a period of six month, we collected 1600 sets of DS, ZHF, and PAC measurements, from a total of 40 patients. Bland-Altman analysis revealed a mean bias of -0.82 ± 1.27 °C (average ± 95% Limits-of-Agreement (LoA)) and − 0.54 ± 1.14 °C for DS and ZHF, respectively. The LCCC was 0.5 (DS) and 0.63 (ZHF). Mean bias was significantly higher in hyperthermic and hypothermic patients. Sensitivity and specificity were 0.12 / 0.99 (DS) and 0.35 / 1.0 (ZHF) for hyperthermia and 0.95 / 0.72 (DS) and 1.0 / 0.85 (ZHF) for hypothermia. Conclusion: Core temperature was generally underestimated by the non-invasive approaches. In our study, ZHF outperformed DS. In terms of agreement, results for both sensors were outside the range that is considered clinically acceptable. Nevertheless, both sensors might be adequate to detect postoperative hypothermia reliably when more invasive methods are not available or appropriate. Trial Registration: German Register of Clinical Trials (DRKS-ID: DRKS00027003), retrospectively registered 10/28/2021. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to analyse the obtained experimental data, which is advisable to use to verify the thermophysical model of the thermal regime of a separate premise while using ceramic electric heating panels for heating purposes. Design/methodology/approach: The experimental studies were carried out at the scientific thermophysics laboratory with the help of up-to-date equipment (including the design for these studies). After gathering experimental data, it was analysed, and with its help, a CFD model of the thermal regime of the laboratory premise would be verified. Findings: The conducted experimental studies showed that in the artificially created quasistationary thermal regime of the laboratory premise, the air temperature varied with height in a small interval. This makes it possible to state that when using ceramic electric heaters as heating devices, the air temperature is relatively evenly distributed over the height of the premise. Research limitations/implications: The research provides original experimental data and findings for further CFD modelling of the thermal regime of the premise while using heating ceramic panels. Practical implications: The mentioned in the paper research methods as well as obtained experimental data, could be used in further studies of modern heating systems. Another use of the results - during the validation of CFD models. Originality/value: The paper includes the design and methodology of creating the original experimental stand for research of the different heating systems types. [ABSTRACT FROM AUTHOR]

The core body temperature serves as a pivotal physiological metric indicative of sow health, with rectal thermometry prevailing as a prevalent method for estimating core body temperature within sow farms. Nonetheless, employing contact thermometers for rectal temperature measurement proves to be time-intensive, labor-demanding, and hygienically suboptimal. Addressing the issues of minimal automation and temperature measurement accuracy in sow temperature monitoring, this study introduces an automatic temperature monitoring method for sows, utilizing a segmentation network amalgamating YOLOv5s and DeepLabv3+, complemented by an adaptive genetic algorithm-random forest (AGA-RF) regression algorithm. In developing the sow vulva segmenter, YOLOv5s was synergized with DeepLabv3+, and the CBAM attention mechanism and MobileNetv2 network were incorporated to ensure precise localization and expedited segmentation of the vulva region. Within the temperature prediction module, an optimized regression algorithm derived from the random forest algorithm facilitated the construction of a temperature inversion model, predicated upon environmental parameters and vulva temperature, for the rectal temperature prediction in sows. Testing revealed that vulvar segmentation IoU was 91.50%, while the predicted MSE, MAE, and R2 for rectal temperature were 0.114 °C, 0.191 °C, and 0.845, respectively. The automatic sow temperature monitoring method proposed herein demonstrates substantial reliability and practicality, facilitating an autonomous sow temperature monitoring. [ABSTRACT FROM AUTHOR]

The problem of water pollution caused by antibiotics urgently needs to be solved urgently. In this study, the Bi5O7I:Er3+-Yb3+ (BOIEY) nanoflowers with a diameter of 600–900 nm loaded flexible fibrous membrane has been synthesized via a combined hydrothermal and electrospinning process. It is noteworthy that the composite fibers successfully achieved efficient catalytic purification under real-time temperature monitoring. The BOIE0.5Y1.5/PAN composite fibers displayed the highest photocatalytic performance in the degradation of tetracycline hydrochloride (TC-HCl), with a removal rate of 91.83% in 80 min, which is 1.76 times that of pure BOI. The efficient photocatalytic performance was mainly attributed to the doping of rare earth ions and the special structure of the composite fibers. Er3+ and Yb3+ ions played the role of broadening the absorption spectrum by upconverting near-infrared light into visible light and promoted the separation of electron and hole pairs, thereby improving the photocatalytic efficiency. In addition, the unique structure of the hollow spherical-flower-loaded flexible fibrous membrane exhibited a larger specific surface area and stronger photon absorption capacity compared with traditional nanocrystals (NCs). Furthermore, based on the 2H11/2/4S3/2 → 4I15/2 radiative transitions of Er3+, the real-time temperature feedback of the degradation process in the 303–433 K ranges is evaluated and the relative temperature sensitivity reaches 0.63% K–1 at 353 K. The dual-function composite fibers provide insight into antibiotic removal in complex environments and ecological restoration. [ABSTRACT FROM AUTHOR]

Caring for an infant is a tough and demanding task that presents various challenges for parents. This is especially true for parents who have physical disabilities, as they face unique obstacles in their caregiving journey. For parents with limited movement in their upper limbs, keeping track of important aspects of their baby's health, like weight and temperature, can be a difficult and exhausting task, necessitating innovative solutions to ensure that these parents can provide the best possible care for their child while also promoting their independence. While previous studies have established technology that enhance baby's comfort and safety in cradles and cots, and in contrast to existing products that may require separate monitoring devices or manual interventions, this work presents a significant shift by focusing on the specific needs of parents with phocomelia and upper limb amputation, to enable them to provide independent and attentive infant care. We developed a voice recognition-controlled smart baby cot equipped with real-time temperature and weight monitoring features, and a liquid-crystal display (LCD) feedback, to assist such parents in predicting their baby's well-being. We conducted both finite element analysis (FEA) and ten experimental performance evaluations on the prototype, with and without a load (baby) to assess the cot's load-bearing capacity across different positions, its sensitivity to household noise, and consistency in temperature and weight reading. Our findings demonstrated consistent load-bearing capability and precise weight and temperature measurements, with an overall standard error of 0.03. The voice activation system also performed effectively in environments with noise levels below 80 dB. This work promotes parental autonomy and has the potential to benefit infants and parents in various contexts, including resource-constrained settings. Additionally, it aligns with the global discourse on inclusive healthcare and technology, contributing to the objectives of Africa's Agenda 2063 and Sustainable Development Goal (SDG) 3.

In this paper, a novel distributed optical fiber temperature sensor based on Raman anti-Stokes scattering light is proposed and experimentally demonstrated. The Raman anti-Stokes scattering light is sensitive to temperature parameters that are detected by the fiber under test conditions (FUT), and this allowed the temperature demodulation algorithm to be obtained through the relationship between the temperature and the power of the back-scattered Raman anti-Stokes light. In addition, we propose a new temperature calibration method to ensure accurate temperature measurement, which is greatly affected by the stability of a pulse laser. The experimental system is constructed with an optical fiber length of approximately 3.5 km. The proposed system obtains a 24 dB dynamic range with a pulse width of 20 ns and temperature testing ranges of 30.0 °C to 80.0 °C. The results demonstrate that the maximum temperature deviation range is −1.5 °C to +1.6 °C and the root mean square (RMS) error of the whole temperature range is 0.3 °C, which means it has the potential for practical engineering applications. More importantly, it avoids the walk-off effect that must be corrected in commonly used temperature demodulation schemes adopting both Raman Stokes light and anti-Stokes light. It also saves a signal channel, which is more suitable for the integration of hybrid distributed optical fiber sensing systems for multi-parameter monitoring. [ABSTRACT FROM AUTHOR]

Background: Preventing foot ulcers in people with diabetes can increase quality of life and reduce costs. Despite the availability of various interventions to prevent foot ulcers, recurrence rates remain high. We hypothesize that a multimodal treatment approach incorporating various footwear, self-management, and education interventions that matches an individual person’s needs can reduce the risk of ulcer recurrence with beneficial cost-utility. The aim of this study is to assess the effect on foot ulcer recurrence, footwear adherence, and cost-utility of an integrated personalized assistive devices approach in high-risk people with diabetes. Methods: In a parallel-group multicenter randomized controlled trial, 126 adult participants with diabetes mellitus type 1 or 2, loss of protective sensation based on the presence of peripheral neuropathy, a healed plantar foot ulcer in the preceding 4 years, and possession of any type of custom-made footwear will be included. Participants will be randomly assigned to either enhanced therapy or usual care. Enhanced therapy consists of usual care and additionally a personalized treatment approach including pressure-optimized custom-made footwear, pressure-optimized custom-made footwear for indoor use, at-home daily foot temperature monitoring, and structured education, which includes motivational interviewing and personalized feedback on adherence and self-care. Participants will be followed for 12 months. Assessments include barefoot and in-shoe plantar pressure measurements; questionnaires concerning quality of life, costs, disease, and self-care knowledge; physical activity and footwear use monitoring; and clinical monitoring for foot ulcer outcomes. The study is powered for 3 primary outcomes: foot ulcer recurrence, footwear adherence, and cost-utility, the primary clinical, patient-related, and health-economic outcome respectively. Discussion: This is the first study to integrate multiple interventions for ulcer prevention into a personalized state-of-the-art treatment approach and assess their combined efficacy in a randomized controlled trial in people with diabetes at high ulcer risk. Proven effectiveness, usability, and cost-utility will facilitate implementation in healthcare, improve the quality of life of high-risk people with diabetes, and reduce treatment costs. Trial registration: ClinicalTrials.gov NCT05236660. Registered on 11 February 2022. [ABSTRACT FROM AUTHOR]

PURPOSE: The purpose of the study was to determine if the use of continuous temperature monitoring smart socks is feasible in adolescents with spina bifida (SB) by obtaining user feedback on comfort. METHODS: Participants were provided temperature monitoring socks and a 4 G hub. Follow-up phone calls were performed to answer questions or discuss barriers. Sock temperatures were monitored throughout four weeks. Following sock wear, participants were asked to complete a satisfaction survey. RESULTS: Seventeen of the 33 participants enrolled (eight males, nine females) with a mean age of 14.8 years completed the study. Average sock wear was 8.0 hours per day for four weeks. The mean temperature was 83.4°F with a mean temperature differential between feet of –0.74°F (left–right). The duration of sock wear varied from 14.6 to 595.9 hours over the four-week period. Lastly, eleven participants (84.6%) reported that the socks were comfortable and very easy to put on. CONCLUSION: Continuous temperature monitoring smart socks are an option for monitoring risk for developing pressure injuries in adolescents with SB. Future directions would include increasing sample size, obtaining normative data for temperature ranges in this population, and correlating to clinical outcomes. [ABSTRACT FROM AUTHOR]

Efficient and reliable university laboratory management requires precise monitoring and control of environmental conditions such as temperature, occupancy, and equipment use. However, traditional monitoring methods such as manual measurements can be time-consuming, labor-intensive, and prone to error. Additionally, there is often a need for remote monitoring and control, especially in large facilities or during off-hours. To address these challenges, this paper presents the design and implementation of a comprehensive monitoring and control system for a university laboratory. The system employs an Espressif 32 (ESP32) microcontroller board and various sensors to automate temperature, occupancy, and equipment monitoring. Temperature readings of people entering and leaving the university laboratory are taken to ensure safety during a pandemic. Face detection is used to monitor the number of people entering and exiting the laboratory and to authenticate individuals entering. An ESP32 microcontroller performs commands using a relay switch after password-based authentication through SMS. Furthermore, the system can be remotely controlled via SMS through a GSM network, providing an effective way to manage university laboratory conditions from a distance. The system's accuracy was evaluated by comparing temperature readings with those of a reference thermometer and testing face detection and relay control functions. The results of the tests demonstrate that the system is reliable and accurate in monitoring and controlling the university laboratory environment. Overall, this system provides an efficient and effective solution for university laboratory management, reducing the need for manual monitoring and improving the accuracy of environmental data collection. [ABSTRACT FROM AUTHOR]

The Collaborative Research Center 1153 is investigating a novel process chain for manufacturing high-performance hybrid components. The combination of aluminum and steel can reduce the weight of components and lead to lower fuel consumption. During the welding of aluminum and steel, a brittle intermetallic phase is formed that reduces the service life of the component. After welding, the workpiece is heated inhomogeneously and hot-formed in a cross-wedge rolling process. Since the intermetallic phase grows depending on the temperature during hot forming, temperature control is of great importance. In this paper, the possibility of process-integrated contact temperature measurement with thin-film sensors is investigated. For this purpose, the initial temperature distribution after induction heating of the workpiece is determined. Subsequently, cross-wedge rolling is carried out, and the data of the thin-film sensors are compared to the temperature measurements after heating. It is shown that thin-film sensors inserted into the tool are capable of measuring surface temperatures even at a contact time of 0.041 s. The new process monitoring of the temperature makes it possible to develop a better understanding of the process as well as to further optimize the temperature distribution. In the long term, knowledge of the temperatures in the different materials also makes it possible to derive quality characteristics as well as insights into the causes of possible process errors (e.g., fracture of the joining zone). [ABSTRACT FROM AUTHOR]

Objective: Solve the problem of inaccurate temperature control of liquor entering the cellar. Methods: Based on the embedded platform, a ZigBee wireless sensor network for cellar parameter aggregation is constructed. The cellar environmental data transmission, storage and display were realized through NB-IOT and cloud platform. Algorithm, real-time optimization of output parameters Kp, Ki, Kd, to achieve precise control of cellar temperature. Finally verify the performance of the temperature control system. Results: The maximum deviation between the measured temperature and the set temperature by the fuzzy PID control algorithm is 0.25 ℃, the overshoot is 1.6%, and the error is within 5% by comparing the manual measurement data with the data collected by the monitoring system. Conclusion: The temperature of entering the cellar can be controlled quickly and accurately by using the fuzzy PID control strategy.

Qualitative microwave imaging methods provide a fast and accurate reconstruction of the shapes of the targets from scattered electric field measurements. In this paper, a qualitative imaging method, the singular sources method (SSM), is analyzed for two-dimensional transverse magnetic electromagnetic (2D-TM EM) inverse scattering scenarios. The contribution of the paper can be briefly summarized as: (i) The SSM was previously proposed for the far-field scenario, here we extend the SSM in the near field - inhomogeneous background setup. While making the extension each step (which includes an integral equation) is explained by exploiting the linearity and reciprocity principles to give physical insights. (ii) The relation between the electrical parameters of the scatterers and the indicator of SSM is derived. (iii) To analyze the performance of SSM in real-world problems, the proposed method is tested for monitoring hyperthermia treatment problems with a realistic breast model. Obtained results show that the SSM can handle realistic breast phantoms for monitoring hyperthermia problems.

Microwave hyperthermia (MH) treatment for breast cancer is a research interest due to its capability to initiate cell necrosis in malignant tumor or to enhance the effect of other treatment modalities such as chemotherapy. The goal of MH treatment is to increase temperature of malignant tumor up to $45^{\circ} \text{C}$ based on the treatment plan; however, microwave energy focusing is a challenging problem and may cause unwanted hotspots on healthy tissues; therefore, there is a need to monitor the temperature. In this paper, an iterative differential microwave imaging algorithm for temperature monitoring is presented. The algorithm is based on Born iterative method (BIM) and Tikhonov regularization. Feasibility of the algorithm is shown by a large computational study using realistic digital breast phantoms via TMz polarized 2-D scattered fields. Also, some results are given for calibrated scattering parameters, which are obtained from both a 3-D electromagnetic simulation program and a simple measurement setup. An approach for selection of matching medium in hyperthermia monitoring applications is also presented. The reconstructions are performed with scattered field data collected at 11 discrete frequency points uniformly taken from the 0.5-1.5 GHz range. For a specific heating scenario in 2-D problem, reconstruction error is lower than 0.3% with ±10% noise on reference dielectric property distribution and 40 dB signal to noise ratio (SNR). The results show that the proposed approach provides up to $3^{\circ} \text{C}$ and $0.1^{\circ} \text{C}$ resolution in temperature estimation with ±10% noise on reference dielectric property distribution for 30 dB and 60 dB SNR values, respectively.

The construction of shafts of potash mines in flooded and unstable soils is usually carried out with the help of artificial ground freezing. The freezing process aims to form a waterproof frozen wall (FW) around the shaft and is monitored throughout the construction of the mine shaft. This paper describes the results of the temperature monitoring of the FW around the skip shaft of a potash mine under construction. The data on temperature measurements in control-thermal boreholes were used to parameterize the mathematical model of heat transfer, which allowed for the reconstruction of the temperature field throughout the entire cooled and frozen soil volume. The resulting temperature distribution in the FW zone for greater than one year was used to determine the distribution of the strength properties and calculate the temporary change in the limiting value of the external lateral load on an FW of a given thickness and specified thermomechanical properties. The obtained dependencies of the maximum external load on the FW can be used to optimize the operation mode of the freezing station at the ice holding stage (or passive freezing) to increase the energy efficiency of the system and ensure the structural integrity of the FW.

Power cable is a piece of major transmission equipment, and its operating temperature as a major factor determines whether the cable system can operate safely and reliably and the current-carrying capacity. Therefore, it is of great significance to master the real-time temperature and the distribution of the power cable core. During the aging of cable insulation, temperature, as a major factor, directly determines the aging rate. One of the basic parameters on the power cable is the ampacity. If the ampacity is high, the cable will be overloaded. In this paper, the thermal circuit method is used to construct and calculate the cable, and the whale algorithm is used to estimate the temperature of the cable conductor. The conductor is estimated accurately within the allowable error range. The results are compared with the results of finite element simulation to verify the effectiveness of the finite element method. Through the experimental analysis, the model is established according to the cable trench on the spot. The steady-state temperature field is calculated through parameter setting. The average packet loss rate is 0.066 %, and the relative error is 0.32 %, which proves that this study can optimize the communication mode of the network and achieve a better monitoring effect. The method realizes the real-time temperature rise prediction of the cable core conductor by using the temperature rise of the outer skin. It can provide a certain theoretical basis for the online monitoring and engineering practical application of the cable core temperature and has practical significance. [ABSTRACT FROM AUTHOR]

Environmental and geomorphological processes in the mountainous areas of Eastern Siberia is strongly conditioned by the thermal state of permafrost (permanently frozen ground). However, the scarce data about climate and weak of permafrost study have led to the unclarity of mountain permafrost condition in this region. The increase in the mean annual air temperature over the past 50 years in the northeastern Siberia by various estimates is from 1.1°C to 3.3°C. So far, almost no information is available on the permafrost response to climatic changes in the region. The Kolyma Route (around 2000 km length), connecting Yakutsk and Magadan that crosses 5 climatic types and more than 10 permafrost landscapes, so it seems a suitable path for establishing basic (reference) monitoring sites. From 12 target boreholes, on the first stage 5 boreholes up to 30 m in depth were drilled and instrumented for measuring temperature at sites adjacent to weather stations in the Verkhoyansk Range from 283 to 1288 m a.s.l. Here we present conception, purpose, and methods for permafrost study project with first preliminary results from the highest weather station of the East Siberia Mountain. The following research about geophysical investigations, permafrost landscape description, mapping and spatial modelling, numerical computing, physical modelling of permafrost thickness might be initiated by the Eastern Siberia Permafrost Transect (ESPT)-project. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The work described herein details the deployment of an optical fibre strand with five fibre Bragg grating (FBG) sensors for individual cell-level temperature monitoring of a three-cell lithium-ion battery pack. A polymer guide tube with 3D printed plinths is employed, resulting in high precision temperature readings with an average error of 0.97 °C, 1.33 °C, and 1.27 °C for FBG sensors on each battery cell, surpassing traditional thermocouple and platinum resistance sensors in some circumstances. The temperature response of FBGs positioned between battery cells demonstrates that, in addition to sensing temperature at the cell level, temperature data can be effectively acquired between cells, suggesting that FBGs may be used to monitor the heat radiated from individual cells in a battery pack. [ABSTRACT FROM AUTHOR]

Monitoring the temperature of the coal gangue mountains is fundamental to preventing their spontaneous combustion. However, the existing temperature monitoring systems fail to achieve stable, pollution-free temperature monitoring without affecting vegetation growth in these mountains. To address this issue, this work proposes a flexible thermoelectric device (FTD) based on a protrusion-structured liquid metal elastomer (LME). Utilizing a high-thermal-conductivity LME, the FTD adheres closely to the surface of the gravity heat pipe (GHP), ensuring compatibility between FTD and the curved surface of the GHP. Simultaneously, employing a low-thermal-conductivity elastomer helps concentrate heat onto FTD, thereby enhancing thermoelectric power generation efficiency. Additionally, the impact of the shape, size, and height of the protrusion structure at the cold end of the GHP on its efficiency was also investigated. The practical application of FTD on GHP was demonstrated.

Abstract Background Body temperature is a vital sign, and temperature monitoring during liver transplantation is important. Tracheal temperature can be measured via an endotracheal tube with a temperature sensor on the cuff of the tube. This study aimed to investigate the accuracy and trending ability of tracheal temperature measurement compared to those of the core temperature measured at the esophagus and pulmonary artery (PA) in living donor liver transplant recipients. Methods Twenty-two patients who underwent living donor liver transplantation (LDLT) were enrolled. Patients were intubated using an endotracheal tube with a temperature sensor placed on the inner surface of the tube cuff. Tracheal, esophageal, and PA temperatures were recorded at five time points corresponding to the different phases of liver transplantation. The tracheal and esophageal, tracheal and PA, and esophageal and PA temperatures were compared using Bland–Altman analysis, four-quadrant plot/concordance analysis, and polar plot analysis. Results Bland–Altman analysis showed an overall mean bias (95% limits of agreement) between tracheal and esophageal temperatures of -0.10 °C (-0.37 °C to 0.18 °C), with a percentage error of 0.27%; between tracheal and PA temperatures, -0.05 °C (-0.91 °C to 0.20 °C), with a percentage error of -0.15%; and between esophageal and PA temperatures, 0.04 °C (-0.27 °C to 0.35 °C), with a percentage error of 0.12%. The concordance rates between tracheal and esophageal temperatures, tracheal and PA temperatures, and esophageal and PA temperatures were 96.2%, 96.2%, and 94.94%, respectively. The polar plot analysis showed a mean angular bias (radial limits of agreement) of 4° (26°), -3° (13°), and 2° (21°). Conclusions Monitoring core temperature at the inner surface of the endotracheal tube cuff is accurate in all phases of LDLT with good trending ability; thus, it can be an excellent alternative for monitoring during LDLTs.

The application of a plethora of wireless technologies to support real-time food quality monitoring during transportation has significantly improved the performance of fresh food delivery systems. However, deployment of these technologies increases the capital and operational costs of food delivery and, hence, not all food delivery operations need to employ them. This paper looks at the trade-off of the costs involved in utilizing these technologies with the nature of food delivered, the length of transportation, and the perceived costs of food wasted using a linear programming model. The problem is formulated over a bi-echelon network with the possibility of transporting the fresh produce through dry vans, vans with temperature control but without monitoring capability, and vans with temperature control and monitoring capability. Results indicate that under situations of infinite vehicle resource availability, the optimal choice of the van type is independent of the demand levels; however, the optimal choice changes for different travel distances and the value of penalty costs (of allowing food to go waste). For example, technologies that maintain and monitor the temperature of storage conditions will be useful for food items that quickly become waste, especially when transported over longer distances and when the penalty costs are higher. [ABSTRACT FROM AUTHOR]

A forward estimate of mango (Mangifera indica L.) harvest timing is required for farm management (e.g., for organization of harvest labour and marketing). This forward estimate can be based on accumulated growing degree days (GDD) from an early stage of flowering to fruit harvest maturity, with fruit maturity judged on a destructive assessment of flesh colour and dry matter content. The current study was undertaken to improve GDD targets for Australian mango cultivars, to improve estimation of harvest maturity, and to document a methodology recommended for future work characterizing fruit maturation GDD for other mango cultivars. An alternate algorithm on GDD calculation involving use of a function that penalizes high temperatures as well as low temperatures was demonstrated to better predict harvest maturity in warmer climates. Across multiple locations and seasons, the required heat units (GDD, Tb = 12 °C, TB = 32 °C; where TB is upper base temperature of 32 °C and Tb is lower base temperature of 12 °C) to achieve maturity from asparagus stage of flowering was documented as 2185, 1728, and 1740 for the cultivars Keitt, Calypso and Honey Gold, respectively. GDD difference between the asparagus and two-thirds floral opening stages of flowering was 188 ± 18 for Calypso, 184 ± 12 for Honey Gold, 238 ± 21 for Keitt and 175 ± 10 for KP. Colour specifications for a colour card set suitable for maturity assessment of all cultivars was also proposed. A flesh colour harvest maturity card specification of 9 was proposed for the cultivar Honey Gold and 13 for the cultivar Keitt. [ABSTRACT FROM AUTHOR]

Simple Summary: Non-invasive temperature monitoring during hyperthermia cancer treatment is of paramount importance. It allows physicians to verify the therapeutic temperature is reached in the treated area. Currently, only superficial or invasive thermometry is performed on a clinical level. Magnetic resonance thermometry has been proposed as a a non-invasive alternative but its applicability is limited. Conversely, microwave imaging based thermometry is a potential low cost candidate for non-invasive temperature monitoring. This works presents a computational study in which the use of deep learning is proposed to face the challenges related to the use of microwave imaging in hyperthermia monitoring. The paper deals with the problem of monitoring temperature during hyperthermia treatments in the whole domain of interest. In particular, a physics-assisted deep learning computational framework is proposed to provide an objective assessment of the temperature in the target tissue to be treated and in the healthy one to be preserved, based on the measurements performed by a microwave imaging device. The proposed concept is assessed in-silico for the case of neck tumors achieving an accuracy above 90%. The paper results show the potential of the proposed approach and support further studies aimed at its experimental validation. [ABSTRACT FROM AUTHOR]

During the concrete pouring of arch dams in the high-temperature season, solar radiation significantly influences the surface of concrete pouring blocks. In this study, optical fibres were embedded throughout the pouring block of the Baihetan arch dam. Furthermore, a temperature gradient monitoring test for surface concrete of the floor and sidewall of the orifice was carried out in the high-temperature season to obtain the actual temperature of the orifice concrete. For the convenience of calculation, the heat flux caused by solar radiation heat is converted into air temperature. The solar radiation heat is regarded as the virtual air temperature increment, which is superimposed with the measured air temperature to form a comprehensive equivalent air temperature. Taking the comprehensive equivalent air temperature as the third boundary condition and considering the influencing factors, such as the pouring schedule, water cooling, and ambient temperature, this study uses finite element software to simulate the temperature field during the construction of orifice concrete. The results show that solar radiation heat has little influence on the concrete temperature in the middle of the pouring block. After the influence of solar radiation heat is considered, the accuracy of the finite element model of the orifice pouring block is significantly improved, and the influence of solar radiation heat on the floor concrete is smaller than that on the sidewall concrete. [ABSTRACT FROM AUTHOR]

Copyright of Food & Machinery is the property of Food & Machinery Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Prediction and analysis of temperature‐based quality evolution of those perishables subjected to extreme temperatures in a shipment can guide the stakeholders and decision‐makers regarding the final quality of shipment and export mode. This study aims to forecast the temperature heterogeneity among the perishables packed in a standard ventilated carton for sea‐borne cold chain and airways export, using Computational Fluid Dynamics (CFD) simulation. The biochemical processes affecting the fruit quality are also evaluated, and the overall quality is predicted with the help of the Kinetic rate law model. The case of an Indian mango export to United States is considered for the present study, and a preferable export mode is suggested. The model is experimentally validated with a discrepancy of 1.516 K (RMSE) and 9.504% (MAPE), respectively. The findings indicate more heterogeneous temperature distribution in the case of seaways export (nearly 3 K) compared to airways (1.5 K). The temperature‐dependent quality attributes, following different kinetics, decays by 46% and 89.6% on the 10th day of seaways export. This observation indicates that the mangoes will be spoiled in transit as seaways export to United States takes around 28 days. From these observations, under the given transit conditions, it is recommended to export mangoes via airways to the United States from India, which takes about 3 days. Practical Applications: Monitoring the temperature of perishables is an indispensable part of cold chain export for maintaining their quality and extending their shelf life. This study proposes a virtual or simulation‐based approach to analyze the cooling behavior of individual mangoes and hence predict the evolution of its various quality attributes, passing through different stages of the cold chain. The technique used is quite promising in predicting the export potential and export mode of the produce before the actual export process takes place, thus preventing excessive in‐transit loss. The method mentioned above is applied in an illustrative case study of Indian mango export to the United States. Its application can be further extended to the export of other perishables to various importing countries. [ABSTRACT FROM AUTHOR]

Copyright of Smart Rail Transit is the property of Smart Rail Transit Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rail temperature is the main effector of train operation. High rail temperature induces rail deformation and because of limited space for rail deformation, rails are under compressive pressure. When rail deformation is exceeded, rail buckling occurs, and this causes rail derailment. Although such a rail derailment is infrequent, the casualties of human lives and properties are catastrophic. To prevent this, the rail industry has been monitoring rail temperature. However, existing representative rail temperature measurement points (RMPs) are selected without considering thermal deformation, and there is no sufficient information for selecting RMPs. In this study, we suggest a novel advanced RMP (ARMP) considering rail installation orientation and meteorological conditions. We designed a measurement system for rail temperature and obtained 1-year data of rail temperature at multiple internal, external rail points and the surrounding environments. We validated our measured data with field data similar to the climate in which the measurement system was installed. The maximum error and Mean Absolute Error (MAE) were 3.3 °C and 0.97 °C respectively. We calculated average deformation points (ADPs) and analyzed them with respect to the energy that the rail receives from the meteorological conditions, which are represented by the cumulative amount of solar irradiance and installation orientation. Based on the tendency of ADPs, we suggested a simple equation of ARMP with only one variable, month. ARMP showed high accuracy in measuring rail temperature at two installation orientations than previous RMPs (R-square: 0.9255, 0.8577 and MAE: 0.21 °C, 0.33 °C). We expect that this study would contribute to efficient train operation for the precise measurement of rail temperature. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries (LIBs), known for their high energy density and excellent cycling performance, are widely utilized in electronic devices, electric vehicles and energy storage systems. However, the safety concerns associated with LIBs, such as overcharging, over-discharging, mechanical damage, and exposure to high temperatures, cannot be overlooked. These risks can potentially lead to the uncontrolled chemical reactions within the battery, generating excessive heat and even triggering thermal runaway and combustion. It is therefore essential to monitor certain parameters throughout the operation of LIBs. This review provides a comprehensive summary of recent advances in sensing technologies for LIBs, with a particular focus on stress/strain, temperature and gas monitoring. The discussion focuses on the performance characteristics as well as the strengths and limitations of these sensing technologies. Considering the current state of research and existing issues, the future of more integrated and intelligent monitoring technology of LIBs is further discussed and prospected in this work. • Various methods for monitoring Lithium-ion batteries are explored in this review. • This review details stress, temp, and gas sensors for Lithium-ion batteries. • The merits and demerits of diverse sensing technologies is deeply analyzed. • The future of lithium-ion battery monitoring gets novel perspectives. [ABSTRACT FROM AUTHOR]

Accurate temperature measurement of the pulverized coal powder is crucial in detecting and preventing coal spontaneous combustion. Compared to other temperature measurement techniques, acoustic tomography using low frequency sound waves has the advantage of high penetration ability for non-intrusive temperature measurement inside the pulverized coal powder. Additionally, by employing an array of acoustic transducers mounted around the coal powder, the entire sensing area can be covered, enabling a comprehensive temperature distribution analysis through tomographic reconstructions. However, the main drawback of the acoustic temperature measurement is the model complexity in describing the dependence of acoustic sound speed on temperature in the porous pulverized coal powder. Accurate calibration is required to determine the model parameters for temperature retrieval, however, which is difficult for in situ industrial application. To solve this problem, we proposed a calibration-free temperature monitoring method based on the dual-mode acoustic tomography for pulverized coal. The three-parameter JCAL model is used to characterize the acoustic propagation in coal powder. The temperature and micro-structure parameters can be jointly retrieved from the reconstructed sound slowness and attenuation distributions at different frequencies. The feasibility and effectiveness of the proposed method are validated in the simulation study. Results show that the dual-mode acoustic tomography can provide calibration-free simplicity for pulverized coal temperature measurement, which has a great potential for industrial applications. [Display omitted] • A calibration-free temperature measurement technique for pulverized coal. • 3-parameter JCAL model is used to characterize acoustic property of coal powder. • Multi-frequency dual-mode acoustic tomography is used for data acquisition. • Jointly retrieval of temperature and micro-structure parameters. • Good qualitative accuracy in imaging the temperature distribution. [ABSTRACT FROM AUTHOR]

Accurately mapping the temperature during ablation is crucial for improving clinical outcomes. While various sensor configurations have been suggested in the literature, depending on the sensors’ type, number, and size, a comprehensive understanding of optimizing these parameters for precise temperature reconstruction is still lacking. This study addresses this gap by introducing a tool based on a theoretical model to optimize the placement of fiber Bragg grating sensors (FBG) within the organ undergoing ablation. The theoretical model serves as a general framework, allowing for adaptation to various situations. In practical application, the model provides a foundational structure, with the flexibility to tailor specific optimal solutions by adjusting problem-specific data. We propose a nonlinear and nonconvex (and, thus, only solvable in an approximated manner) optimization formulation to determine the optimal distribution and three-dimensional placement of FBG arrays. The optimization aims to find a trade-off among two objectives: maximizing the variance of the expected temperatures measured by the sensors, which can be obtained from a predictive simulation that considers both the type of applicator used and the specific organ involved, and maximizing the squared sum of the distances between the sensor pairs. The proposed approach provides a trade-off between collecting diverse temperatures and not having all the sensors concentrated in a single area. We address the optimization problem through the utilization of approximation schemes in programming. We then substantiate the efficacy of this approach through simulations. This study tackles optimizing the FBGs’ sensor placement for precise temperature monitoring during tumor ablation. Optimizing the FBG placement enhances temperature mapping, aiding in tumor cell eradication while minimizing damage to surrounding tissues.

Underground cable installation in historical areas, natural protected areas, narrow streets, or residential areas with high traffic flows is very difficult due to both legal permits and the conditions of the work sites. The trefoil layout requires a smaller channel than the flat layout. However, the trefoil layout carries some risks, such as damage to the cables together in the event of short circuit faults and reduced ampacity in single-side-bonded systems. This study’s scope examines the current carrying capacities and thermal effects of directly buried underground cables in trefoil and vertical layouts using CYMCAP power cable analysis software. A field investigation was also carried out to verify the analysis results. The performance of the recommended method was evaluated by considering current and temperature measurements from the fieldwork and analysis. According to the studied cable design, the current carrying capacities of the cables in flat and vertical layouts are similar and higher than in the trefoil layout. However, it should be taken into consideration that these results will vary depending on a cable system’s design parameters. As a result, this article emphasizes that a vertical layout can be considered as a layout option in certain areas.

The temperature of a lithium-ion battery is a crucial parameter for understanding the internal processes during various operating and failure scenarios, including thermal runaway. However, the internal temperature is comparatively higher than the surface temperature. This particularly affects cells with a large cross-section, which is due to heat development within the cell and lower heat dissipation due to a poorer ratio of volume to surface area. This paper presents an approach that enables real-time monitoring of the behavior of a commercial prismatic high-energy battery cell (NMC811/C, 95 Ah, Contemporary Amperex Technology Co., Limited (Ningde, China)) in the event of thermal runaway induced by overcharging. The internal cell temperature is investigated by the subsequent integration of two hard sensors between the two jelly rolls and additional sensors on the surface of the aluminum housing of the battery cell. The sensor’s signals show a significant increase in the temperature gradient between the temperature in the core of the cell and the cell casing surface until the onset of venting and thermal runaway of the battery. The data enable a detailed investigation of the behavior of the battery cell and the comparatively earlier detection of the point of no return in the event of thermal runaway.

The core body temperature serves as a pivotal physiological metric indicative of sow health, with rectal thermometry prevailing as a prevalent method for estimating core body temperature within sow farms. Nonetheless, employing contact thermometers for rectal temperature measurement proves to be time-intensive, labor-demanding, and hygienically suboptimal. Addressing the issues of minimal automation and temperature measurement accuracy in sow temperature monitoring, this study introduces an automatic temperature monitoring method for sows, utilizing a segmentation network amalgamating YOLOv5s and DeepLabv3+, complemented by an adaptive genetic algorithm-random forest (AGA-RF) regression algorithm. In developing the sow vulva segmenter, YOLOv5s was synergized with DeepLabv3+, and the CBAM attention mechanism and MobileNetv2 network were incorporated to ensure precise localization and expedited segmentation of the vulva region. Within the temperature prediction module, an optimized regression algorithm derived from the random forest algorithm facilitated the construction of a temperature inversion model, predicated upon environmental parameters and vulva temperature, for the rectal temperature prediction in sows. Testing revealed that vulvar segmentation IoU was 91.50%, while the predicted MSE, MAE, and R2 for rectal temperature were 0.114 °C, 0.191 °C, and 0.845, respectively. The automatic sow temperature monitoring method proposed herein demonstrates substantial reliability and practicality, facilitating an autonomous sow temperature monitoring.