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Carbon nanotube (CNT) film is favored in structural health monitoring of advanced composite materials, primarily due to its commendable mechanical properties and piezoresistive properties. Nonetheless, floating catalytic chemical vapor deposition (FCCVD) is an attractive method for fabrication of CNT films, and the electrical response to strain of FCCVD‐prepared CNT films is impeded by high aspect ratio and lamellar packing structure. For this purpose, FCCVD CNT films were modified by HCl dissolving Fe impurities, nano‐SiO2 particles doping and freeze‐drying in combination to increase the spacing between CNTs and its networks as well as their strain sensitivities. It showed that the gauge factor (GF) according to the variation of resistance (ΔR/R0) of the co‐modified film (CNT‐HCl‐SiO2 film) was up to 15.6 for the tensile strain at the bottom surface of unidirectional carbon fiber reinforced plastic (CFRP) laminates during the process of bending tests. The bending cycle experiment of the CFRP showed relatively stable changes of ΔR/R0 with the strains for CNT‐HCl‐SiO2 film, while that of the pristine CNT film (CNT‐HCl‐0 film) displayed unstable non‐monotonic changes and that of HCl purified CNT film (CNT‐HCl‐10 film) revealed a gradual declining tendency. Moreover, the ΔR/R0 of CNT‐HCl‐SiO2 film exhibited excellent sensitivity to the strains of multiple bistable‐deformations of cross‐ply CFRP laminates. Strain gauge analysis indicated that a 51% increase of ΔR/R0 of CNT‐HCl‐SiO2 film at the 90° layer surface corresponded to the average strain of 434 με, meanwhile a 37% increase of ΔR/R0 of the CNT film at the 0° layer surface corresponded to the strain of averagely −173.9 με, and both exhibited super high GFs of 1175 and 2108, respectively. Based on this high sensitivity, CNT‐HCl‐SiO2 film also had the ability to predict the release of residual stress during the demoulding process of CFRP. Highlights: Even SiO2 dispersion in CNT film, increased the pristine film thickness by 10 timesGF of CNT‐HCl‐SiO2 film increased by 68% than CNT‐HCl‐0 film and by 164% than CNT‐HCl‐10 filmSiO2 doping significantly improved the stability of the CNT film's ΔR/R0 with temperature and strainCNT‐HCl‐SiO2 film has the ability to monitor the deformation and residual stress of CFRP [ABSTRACT FROM AUTHOR]

Objective: This study aims to assess the significance of monitoring temperature change trends at various wound sites in the healing process of diabetic foot ulcers after microcirculation reconstruction surgery. Methods: A retrospective analysis was conducted on individuals with diabetic foot ulcers who had been admitted to the Department of Orthopedics at the Second Hospital of Shanxi Medical University between July 2020 and February 2022. Temperature changes were regularly monitored at the center of the wound and the distal tibia of the ipsilateral lower leg to assess microcirculatory blood perfusion. Wound, ischemia, and foot infection (WIFi) grading was performed at admission and the final follow-up was to determine the value of temperature monitoring at various sites. Additionally, the formation of collateral microarterial vessels was monitored to determine their consistency with the observed trends in temperature differences. Follow-up assessments included the recurrence of ulcers, development of ulcers at different locations, re-amputation of the toe or limb, and diabetes-related mortality. Results: A total of 29 patients were included in the follow-up, with an average age of 57.14 ± 14.75 years and a follow-up period of 9.79 ± 4.13 months. Following microcirculation reconstruction surgery, as the microvascular network formed, the temperature difference between the center of the wound and the distal tibia on the same side gradually decreased, with no statistical difference observed at 4 weeks postoperatively. At both admission and the final follow-up, there was a significant reduction in the wound (W) and ischemia (I) grades within the WIFi classification. The temperature at the wound center showed progressive improvement as collateral microarterial vessels developed. During the follow-up period, there were 2 cases of ulcer recurrence, 1 case of an ulcer appearing at a different location, no cases of re-amputation of the toe or limb, and 2 diabetes-related fatalities. Conclusion: Skin temperature monitoring offers a direct and reliable indication of microcirculatory blood perfusion. Its simplicity and cost-effectiveness make it a valuable tool for widespread use in evaluating wound healing following microcirculation reconstruction surgery. [ABSTRACT FROM AUTHOR]

Introduction: The spiral tube heat storage tank is a highly efficient device designed for storing and releasing heat, utilizing a spiral tube structure. Its key advantages include efficiency, reliability, and flexibility, making it suitable for a wide range of conditions, from high temperatures and pressures to low temperatures and high vacuums. Methods: This study aims to analyze phase change heat storage in spiral tube heat storage tanks using numerical simulation. Results: It explores the impact of varying water supply temperatures on heat transfer efficiency and the melting behavior of phase change materials within the tanks. Proposed enhancements, informed by numerical simulation results, seek to improve heat transfer efficiency. Simulation findings indicate that charging efficiency rises with increased temperature differentials, akin to sleeve-type heat exchangers. Discussion: Calculations suggest faster melting of phase change materials at the central position of the tank's spiral tube, with slower melting near the vessel wall. Consequently, reducing the number of spiral tubes in the middle is suggested for future structural optimization. [ABSTRACT FROM AUTHOR]

Abstract Objective This study aims to assess the significance of monitoring temperature change trends at various wound sites in the healing process of diabetic foot ulcers after microcirculation reconstruction surgery. Methods A retrospective analysis was conducted on individuals with diabetic foot ulcers who had been admitted to the Department of Orthopedics at the Second Hospital of Shanxi Medical University between July 2020 and February 2022. Temperature changes were regularly monitored at the center of the wound and the distal tibia of the ipsilateral lower leg to assess microcirculatory blood perfusion. Wound, ischemia, and foot infection (WIFi) grading was performed at admission and the final follow-up was to determine the value of temperature monitoring at various sites. Additionally, the formation of collateral microarterial vessels was monitored to determine their consistency with the observed trends in temperature differences. Follow-up assessments included the recurrence of ulcers, development of ulcers at different locations, re-amputation of the toe or limb, and diabetes-related mortality. Results A total of 29 patients were included in the follow-up, with an average age of 57.14 ± 14.75 years and a follow-up period of 9.79 ± 4.13 months. Following microcirculation reconstruction surgery, as the microvascular network formed, the temperature difference between the center of the wound and the distal tibia on the same side gradually decreased, with no statistical difference observed at 4 weeks postoperatively. At both admission and the final follow-up, there was a significant reduction in the wound (W) and ischemia (I) grades within the WIFi classification. The temperature at the wound center showed progressive improvement as collateral microarterial vessels developed. During the follow-up period, there were 2 cases of ulcer recurrence, 1 case of an ulcer appearing at a different location, no cases of re-amputation of the toe or limb, and 2 diabetes-related fatalities. Conclusion Skin temperature monitoring offers a direct and reliable indication of microcirculatory blood perfusion. Its simplicity and cost-effectiveness make it a valuable tool for widespread use in evaluating wound healing following microcirculation reconstruction surgery.

Ultralow temperature storage has sparked considerable attention with the development of the economy, showing promising applications ranging from biomedical to national defense and other fields. However, the development of ultralow temperature detection is constrained by the brittleness of current materials at low temperatures and the complexity of detection techniques. Consequently, the challenge exists in finding efficient solutions to material tolerance issues and achieving rapid detection of ultralow temperature. Herein, a novel flexible cross–linked polymer TPTA@PU film with long afterglow, high phosphorescence quantum efficiency, and excellent mechanical properties are successfully fabricated. Interestingly, the obtained TPTA@PU films demonstrate a notable thermoresponsive behavior, with the afterglow color shifting rapidly from blue to green within the temperature ranges from 80 to 280 K. Additionally, there is a positive linear correlation between the RGB values of the afterglow color and the corresponding temperature. Based on these prominent features, an ultralow temperature sensor is realized by utilizing TPTA@PU films as thermoresponsive elements. This work can be expected to provide more inspiration and possibilities for using RTP materials in a more cutting‐edge field. [ABSTRACT FROM AUTHOR]

The development of smart synthetic materials that are sensitive, accurate, and visually responsive to changes in temperature is vital. Herein, a supramolecular luminescent hydrogel based on a glycine/terbium (Gly/Tb) complex, rhodamine B (RB), and gelatin is reported. The hydrogel exhibits responsive luminescence and undergoes a temperature‐induced phase transformation from hydrogel to sol. The electrospray ionization time‐of‐flight mass spectra, Fourier‐transform infrared spectra, and simulation results verifiy the coordination mode of the Gly/Tb complex. The Gly/Tb complex and RB emit green and orange luminescence, respectively. When the Gly/Tb complex and RB are co‐doped into the gel network of gelatin, the obtained Gly/Tb/RB hydrogel displays steady yellow luminescence by virtue of luminescence resonance energy transfer. Subsequently, a luminescent switch is constructed owing to the sensitive and reversible luminescence responsiveness of the Gly/Tb/RB hydrogel to temperature stimuli. Remarkably, the Gly/Tb/RB hydrogel undergoes a visual phase transformation from hydrogel to sol above 35 °C, allowing the ambient temperature variation to be monitored. This study establishes a novel and effective route for the construction of smart optical materials and visual temperature monitors. [ABSTRACT FROM AUTHOR]

Hypothermia during obstetric spinal anaesthesia is a common and important problem, yet temperature monitoring is often not performed due to the lack of a suitable, cost-effective monitor. This study aimed to compare a noninvasive core temperature monitor with two readily available peripheral temperature monitors during obstetric spinal anaesthesia. We undertook a prospective observational study including elective and emergency caesarean deliveries, to determine the agreement between affordable reusable surface temperature monitors (Welch Allyn SureTemp® Plus oral thermometer and the Braun 3-in-1 No Touch infrared thermometer) and the Dräger T-core© (using dual-sensor heat flux technology), in detecting thermoregulatory changes during obstetric spinal anaesthesia. Predetermined clinically relevant limits of agreement (LOA) were set at ± 0.5 °C. We included 166 patients in our analysis. Hypothermia (heat flux temperature < 36 °C) occurred in 67% (95% CI 49 to 78%). There was poor agreement between devices. In the Bland-Altman analysis, LOA for the heat flux monitor vs. oral thermometer were 1.8 °C (CI 1.7 to 2.0 °C; bias 0.5 °C), for heat flux monitor vs. infrared thermometer LOA were 2.3 °C (CI 2.1 to 2.4 °C; bias 0.4 °C) and for infrared vs. oral thermometer, LOA were 2.0 °C (CI 1.9 to 2.2 °C; bias 0.1 °C). Error grid analysis highlighted a large amount of clinical disagreement between methods. While monitoring of core temperature during obstetric spinal anaesthesia is clinically important, agreement between monitors was below clinically acceptable limits. Future research with gold-standard temperature monitors and exploration of causes of sensor divergence is needed. [ABSTRACT FROM AUTHOR]

Hyperthermia induces slight temperature increase of 4–8 °C inside the tumor, making it more responsive to radiation and drugs, thereby improving the outcome of the oncological treatment. To verify the level of heat in the tumor and to avoid damage of the healthy tissue, methods for non-invasive temperature monitoring are needed. Temperature estimation by means of microwave imaging is of great interest among the scientific community. In this paper, we present the results of experiments based on ultra-wideband (UWB) M-sequence technology. Our temperature estimation approach uses temperature dependency of tissue dielectric properties and relation of UWB images to the reflection coefficient on the boundary between tissue types. The realistic measurement setup for neck cancer hyperthermia considers three antenna arrangements. Data are processed with Delay and Sum beamforming and Truncated Singular Value Decomposition. Two types of experiments are presented in this paper. In the first experiment, relative permittivity of subsequently replaced tumor mimicking material is estimated, and in the second experiment, real temperature change in the tumor imitate is monitored. The results showed that the presented approach allows for qualitative as well as quantitative permittivity and temperature estimation. The frequency range for temperature estimation, preferable antenna configurations, and limitations of the method are indicated. [ABSTRACT FROM AUTHOR]

Acknowledging the significant impact of temperature deviations on vaccine efficacy, this study examines the prevalence of exposure to non-recommended temperatures, particularly focusing on freeze-sensitive vaccines. This study aims to identify critical points of temperature breaches during transportation from storage to last-mile delivery. In this cross-sectional study, the temperature integrity of vaccines has been examined during transportation across three states in India (Karnataka, Maharashtra, and Rajasthan), utilizing data loggers to track and record temperatures in real time. By analyzing instances of exposure to temperatures beyond the recommended 2–8 °C range, the study aims to identify the critical junctures within the vaccine supply chain susceptible to temperature excursions. The methodology entailed a systematic data logger analysis at each stage of transportation up to the last mile. In this study, descriptive statistics with the analysis of variance test has been applied to investigate the significance of variations in the duration of temperature breaches. The novelty of this study lies in its comprehensive examination of vaccine temperature integrity across critical transportation phases in India, utilizing real-time data-logging technology. Based on the results, the study provides recommendations using the ABCD strategic framework, encompassing awareness, best practices, continuous monitoring, and data management and documentation. This framework will be instrumental in addressing the identified challenges and significantly improving the temperature monitoring flexibility. The findings will inform targeted interventions, optimizing the cold chain to enhance the preservation of vaccine potency and identifying flexible solutions for maintaining the required temperatures from storage to transportation. [ABSTRACT FROM AUTHOR]

This research focuses on the development of thermochromic membranes made of cellulose acetate (CA) for temperature monitoring of sensitive food products. Two dual TC membranes developed for the control of different temperature ranges were formulated using a three‐component system: a leuco‐dye membrane (crystal violet lactone, CVL) integrated with an acidic membrane containing the color developer (salicylic acid) and the acidic solvent with different melting points (decanoic acid, DA, or methacrylic acid, MA). The CVL membrane, together with the DA membrane, showed an irreversible color change when exposed to 35°C, which was facilitated by the melting of DA. The CVL membrane also underwent an irreversible color change when exposed to 15°C together with the MA membrane. The membranes were characterized in detail using scanning electron microscopy. The evaluation of color changes, reproducibility, specificity, and stability ensured the practical suitability of these membranes. Overall, this innovative approach has proven to be a reproducible, sustainable, cost‐effective method to produce irreversible colorimetric temperature sensors. These sensors have significant potential for applications in the food and pharmaceutical industries and offer a promising way to improve product safety and quality. [ABSTRACT FROM AUTHOR]

Real-time monitoring of temperature changes in substation equipment is crucial for preventing failures and ensuring a stable power supply. Currently, temperature monitoring of substation equipment primarily relies on manual infrared thermometry, which has limitations such as strong operational dependence, susceptibility to interference, and difficulty in detecting internal faults. The luminous intensity ratio (LIR) is a stable optical parameter unaffected by factors such as spectral loss and environmental influences, making it suitable for temperature detection. The multi-emission characteristics of rare-earth-doped upconversion (UC) materials are highly compatible with LIR technology, demonstrating their potential in high-precision temperature monitoring. Here we introduces a non-contact temperature monitoring method for substation equipment based on NaErF4@ NaYF4 core-shell UC materials and LIR technique. Experiments show that the method has high accuracy and sensitivity within temperature range of 25 °C to 225 °C, with a sensitivity as high as 35 x 10-3 °C-1, effectively monitoring temperature changes both inside and outside the equipment. This provides a new technical solution for temperature monitoring of substation equipment. [ABSTRACT FROM AUTHOR]

This study examines the development of an Arduino-based real-time data acquisition system and its effect on secondary students’ STEM career interest (STEM-CIS). A total of 74 students were sampled from a prestigious private school in Jakarta, Indonesia, and a learning device was developed using the A.D.D.I.E. method. A one-group pretest-posttest research design was used to evaluate the effect of using the device during blended classroom activities. Data were collected through surveys using the STEM-CIS instrument and interviews. The study was based on the general practice of using Arduino software and hardware for practical purposes in Chemistry Laboratories and Sick Bay. The setup was successfully used in these different environments as a temperature monitoring system to record thermochemistry data and monitor a patient’s body temperature. The findings are consistent with prior research indicating that hands-on robotics activities can increase STEM interest and inspire students to pursue STEM careers. The results suggest that strong engagement in this activity facilitated the development of digital literacy and STEM skills. The STEM-CIS score at the 5% significance level was significantly increased after the experimentation with the device, with a paired t-test result of p<0.001. The effect size (Cohen’s d) showed a moderate effect of 0.74. [ABSTRACT FROM AUTHOR]

Objective: Understansding the changing patterns of in vivo electrical properties for the target tissue is crucial for the accurate temperature monitoring and the treatment efficacy in thermal therapy. Our research aims to investigate the changing patterns and the reversibility of in vivo electrical properties for both healthy livers and liver tumors in a mouse model over a frequency range of 1 Hz to 1 MHz at temperatures between 30 °C to 90 °C.Methods and materials: The mice were anesthetized and the target organ was exposed. An 808-nm near-infrared laser was employed as the heating source to heat the organ in vivo. The four-needle electrode, connected to an impedance analyzer, was utilized to obtain the impedance at varying temperatures, which were monitored by a thermocouple.Results: The findings indicated a gradual decline in impedance with an increase in temperature. Furthermore, the impedance was normalized to that at 30 °C, and the real part of the normalized impedance was defined as the k-values, which range from 0 to 1. The results demonstrated a linear correlation between k-values and temperatures (R2 > 0.9 for livers and R2 > 0.8 for tumors). Significant differences were observed between livers and tumors at 1, 10 and 50 kHz (p

Extreme low-temperature environments have been one of the important issues that need to be solved for outdoor travel as well as indoor activities. The development of smart heated clothing is receiving more and more attention. Previously reported graphene heating mostly uses thin films, so poor breathability, poor flexibility, and low electrical and thermal conversion rates become a challenge. Herein, a facile dip-drying process was employed to prepare composite graphene and CNT-based heated fabrics and provide an intelligent system with the function of sensing environmental temperature. After detecting the temperature data collected by the sensors, the system calculates a suitable temperature through algorithms in the main control chip. The control system automatically adjusts the temperature of the heated fabric to achieve adaptive temperature adaptation or autonomous adjustment. These composite graphene and CNT-based heated fabrics not only retain the inherent flexibility, comfort, washability, and breathability of textile substrates but also exhibit fast heating capabilities. It can rapidly increase the temperature to around 70 °C within 30 s at a voltage of 5 V, ensuring uniform heating. This intelligent composite graphene and CNT-based temperature control system provides a novel and cost-effective approach for achieving flexible, breathable, and stable temperature control in smart clothing, further promoting the development of thermoregulating textiles. It can be widely applied in various fields such as personal heating, physical therapy, wearable flexible electronic products, and more. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic creates more significant opportunities to develop more Internet of Things-based systems. IoT has been helpful in remote monitoring and control of connected devices. This research aims to develop a Room Temperature Remote Monitoring System using an Arduino Board and Cloud storage. It provides remote room temperature monitoring, real-time reports and graphs, and a 3-way alert/alarm system when the observed temperature is out of range. The prototype developed is compared to the room thermometer and provides accurate results. [ABSTRACT FROM AUTHOR]

A hardware and software complex designed to control the temperature of a permanent magnet of a magnetic resonance imaging system and to protect it from overheating in case of failures of the temperature-control system is described. The complex consists of several digital temperature sensors and a meter-recorder that measures temperatures, registers them in memory, and switches off the temperature-control system in case of overheating. Interaction with the computer is carried out with the help of a computer application that provides the setting of the meter, receiving recorded data, visualizing them in graphical and digital form, and saving them in files. The exchange between the meter and the computer is carried out through the local network using the Wi-Fi interface. The complex can also be used in other similar applications. [ABSTRACT FROM AUTHOR]

The escalating biodiversity loss demands a paradigm shift in wildlife conservation. This paper proposes an innovative AI system for holistic wildlife management. The deep learning algorithms identify individual animals through biometrics in camera traps, drone footage, and bioacoustics. This surpasses traditional methods, enabling tracking across vast landscapes. The real-time animal tracking data, analyzed by machine learning, allows for early detection of poaching, habitat disturbances, and animal distress. Furthermore, the system integrates environmental sensors to provide a holistic understanding of ecological conditions. The correlating animal movement with environmental data helps identify crucial habitats and predict climate threats. This unified platform empowers proactive wildlife management, transitioning conservation from reactive to evidence-based practices for long-term biodiversity preservation. [ABSTRACT FROM AUTHOR]

This study addresses the pivotal challenge of enhancing power efficiency in tyre pressure and temperature monitoring systems (TPMS) for heavy vehicles and trailers. Employing field-programmable gate arrays (FPGA) and adaptive channel frequency hopping in Bluetooth low energy (BLE) communication, the research focuses on mitigating power consumption issues specific to heavy vehicles with multiple tyres. The proposed solution incorporates strategic BLE channel blocking and adaptive frequency hopping on the FPGA platform to alleviate channel congestion and interference, ultimately reducing TPMS power consumption. The FPGA's adaptability tailors frequency hopping strategies to automotive TPMS nuances, optimizing channel selection and minimizing energy-intensive processes. Empirical results showcase a significant reduction in power consumption, with the TPMS operating at 100 MHz during active mode consuming 66 mW, dropping to 11 mW in sleep mode, and reaching 0 mW in hibernate mode for the majority of operational time. This research establishes a practical FPGA-based approach for power optimization in commercial TPMS, promising heightened reliability, safety improvements, and environmental impact reduction in the automotive sector. [ABSTRACT FROM AUTHOR]

Determining the quality of gula apong is crucial to optimizing its production, with cooking temperature being a key factor affecting both taste and shelf life. The gula apong industry faced challenges due to the lack of reliable real-time temperature monitoring methods during the cooking process. Traditional approaches were inefficient and inaccurate, leading to difficulties in maintaining consistent product quality and meeting market demands. This highlights the necessity of monitoring the temperature throughout each cooking process. This research aims to develop an internet of things (IoT)- based cooking temperature monitoring system to enhance quality control measures in the production of gula apong. The IoT prototype collects temperature data from the thermocouple sensor, then transmits it to cloud storage through a Wi-Fi communication network, utilizing the Node-RED platform for data processing and analysis. Data obtained from the on-site measurement shows that the optimal temperature for producing standardquality gula apong is approximately around 165 °C. The recommended boiling temperature for Nipah sap is 140 °C. This IoT system can reduce the cooking time of gula apong to 3 hours from the traditional 4 to 6 hours. Utilizing the data acquired from this study helps the producers not only maintaining the quality of gula apong but also reduce the cooking time and cost. [ABSTRACT FROM AUTHOR]

Introduction: Diabetic foot ulcers (DFU) are a devastating complication of diabetes. There are numerous challenges with preventing diabetic foot complications and barriers to achieving the care processes suggested in established foot care guidelines. Multi-faceted digital health solutions, which combine multimodal sensing, patient-facing biofeedback, and remote patient monitoring (RPM), show promise in improving our ability to understand, prevent, and manage DFUs. Methods: Patients with a history of diabetic plantar foot ulcers were enrolled in a prospective cohort study and equipped with custom sensory insoles to track plantar pressure, plantar temperature, step count, and adherence data. Sensory insole data enabled patient-facing biofeedback to cue active plantar offloading in response to sustained high plantar pressures, and RPM assessments in response to data trends of concern in plantar pressure, plantar temperature, or sensory insole adherence. Three non-consecutive case participants that ultimately presented with pre-ulcerative lesions (a callus and/or erythematous area on the plantar surface of the foot) during the study were selected for this case series. Results: Across three illustrative patients, continuous plantar pressure monitoring demonstrated promise for empowering both the patient and provider with information for data-driven management of pressure offloading treatments. Conclusion: Multi-faceted digital health solutions can naturally enable and reinforce the integrative foot care guidelines. Multi-modal sensing across multiple physiologic domains supports the monitoring of foot health at various stages along the DFU pathogenesis pathway. Furthermore, digital health solutions equipped with remote patient monitoring unlock new opportunities for personalizing treatments, providing periodic self-care reinforcement, and encouraging patient engagement—key tools for improving patient adherence to their diabetic foot care plan. [ABSTRACT FROM AUTHOR]

In order to detect abnormal heat generation in time, a reversible color-changing coating temperature measurement method is proposed for self-detection of temperature by power equipment, and its adhesion characteristics and aging performance were analyzed. The results showed that the reversible color-changing coating prepared with crystalline violet lactone as the colorant, bisphenol A as the color developer, octadecanol as the solvent, and RTV-II as the base paint can meet the requirements of self-detection of temperature by power equipment with its adhesion performance. The accelerated aging tests using high temperature, light and humidity were carried out in the laboratory, and we concluded that the deterioration degree of the color-changing coating was positively correlated with the temperature. Light can accelerate the aging rate of reversible color-changing coatings, and the degradation process of the coating was significantly accelerated under UV light. The effect of humidity on the coating was not significant. The degradation of the coating after aging for 288 h under indoor conditions was small, while it was accelerated under outdoor natural conditions. This research can provide a reference for the on-site application of reversible color-changing coatings for self-detection of temperature by power equipment. [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 FROM AUTHOR]

IntroductionThe spiral tube heat storage tank is a highly efficient device designed for storing and releasing heat, utilizing a spiral tube structure. Its key advantages include efficiency, reliability, and flexibility, making it suitable for a wide range of conditions, from high temperatures and pressures to low temperatures and high vacuums.MethodsThis study aims to analyze phase change heat storage in spiral tube heat storage tanks using numerical simulation.ResultsIt explores the impact of varying water supply temperatures on heat transfer efficiency and the melting behavior of phase change materials within the tanks. Proposed enhancements, informed by numerical simulation results, seek to improve heat transfer efficiency. Simulation findings indicate that charging efficiency rises with increased temperature differentials, akin to sleeve-type heat exchangers.DiscussionCalculations suggest faster melting of phase change materials at the central position of the tank’s spiral tube, with slower melting near the vessel wall. Consequently, reducing the number of spiral tubes in the middle is suggested for future structural optimization.

Aim of the study: To evaluate the efficacy of Optical Coherence Tomography (OCT) in non-invasively monitoring temperature variations during ceramic sintering for dental prosthetics, emphasizing the importance of precise temperature control for optimal material properties and structural integrity. Materials and Methods: The study utilized OCT to examine 17 metal-ceramic restorations at various sintering temperatures (standard, 80°C below, and 50°C above the standard). The method involved generating 61 cross-sectional images per prosthesis to identify defects and structural changes. Results: OCT revealed significant insights into the impact of temperature deviations on ceramic microstructure, including uniform grain sizes at standard temperatures and areas of reduced retention at elevated temperatures, highlighting the technology’s potential in quality control. Conclusions: OCT offers a rapid, accurate, and non-destructive means to assess sintering temperatures and detect defects in dental ceramics, facilitating improvements in dental prosthetics’ fabrication process. The study advocates for OCT’s integration into routine dental laboratory practices to enhance prosthesis quality and reliability.

As relict features of coal mines, carbonaceous spoil, waste and tailing dumps remain susceptible to coal oxidation and thermal decomposition, together with spontaneous combustion. Modern methods for monitoring surface thermal signatures regularly include the use of UAV's, equipped with suitably sensitive infrared cameras. Detection of sub-surface thermal anomalism includes Vegetation Index Monitoring and/or the use of in-ground probes. Research across thermally active tailings offers insights into how best apply these two techniques, and increasingly the required scheduling of UAV surveys. [ABSTRACT FROM AUTHOR]

Ultrasonic guided waves offer a promising method of monitoring the online temperature of plate-like structures in extreme environments, such as aero-engine nozzle guide vanes (NGVs), and can provide the resolution, response rate, and robust operation that is required in aerospace. Previous investigations have shown the potential of such a system but the effect of the complex physical environment on wave propagation is yet to be considered. This article uses a numerical approach to investigate how thermal barrier coatings (TBCs) applied to the surface of many components designed for extreme thermal conditions will affect ultrasonic guided wave propagation, and how a system can be employed to monitor through-thickness temperature changes. The top coat/bond coat boundary in NGVs has been shown to be a temperature critical point that is difficult to monitor with traditional temperature sensors, which highlights the potential of ultrasonic guided waves. Differences in application method and layer thickness are considered, and analysis of through-thickness displacement profiles and dispersion curves are used to predict signal response and determine the most suitable mode of operation. Heat transfer simulations (COMSOL) have been used to predict temperature gradients within a TBC, and dispersion curves have been produced from the temperature dependant material properties. Time dependant simulations of wave propagation are in good agreement with dispersion curve predictions of wave velocity for the two lowest order modes in three thicknesses of TBC top coat (100, 250, and 500 μ m ). When wave velocity measurements from the simulations are compared to dispersion curves generated at isotropic temperatures, the corresponding temperature represents the average temperature of a gradient system well. Such a measurement system could, in principle, be used in conjunction with surface temperature measurement systems to monitor through-thickness temperature changes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study investigates the thermal generation dynamics in the spindle unit of a CNC milling machine. The main objective is to analyze the heat transfer from the bearings to the housing during operation, using simulations and experiments. An air-oil-cooled lubrication system is employed, which enables the airflow to dissipate some of the heat produced. Before conducting the experiment, heat generation and transfer are accurately predicted. The air-oil mixture, formed by pressurized air atomizing oil droplets, is effective in cooling high-temperature regions. A spindle ER16-80SK 24k is integrated with a CNC machine for realtime data acquisition, including parameters such as spindle speed and temperature. The results show significant temperature rises in all bearings, which reach a steady state after an hour of operation. There are noticeable differences in range, from 6.1% to 43.4%, between the experimental and simulated maximum temperatures, indicating possible real factors not considered in the simulation. The environmental impacts of oil particle emission are also discussed, which require proper ventilation management during operations. This research provides valuable insight into the thermal dynamics of CNC milling machine spindles and establishes a solid basis for further research and development in this important field of machining technology. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Tourism is a growing concern for the conservation of heritage sites. In the Dordogne, the Cap Blanc shelter attracts many visitors and their presence may affect its parietal frieze by altering the thermal environment. To assess this impact, a study is carried out using numerical simulation, a non-intrusive conservation tool that can model the thermal behaviour of the cavity during tourist visits. We validate the numerical model with the temperature measurements taken inside the shelter during three tourist visits. We show that the heat emitted by the tourists is mostly absorbed by the walls, resulting in a small increase in air temperature (between 1°C and 2°C) and a large temperature gradient near the walls during the visits, which favours condensation and possible conservation problems. [ABSTRACT FROM AUTHOR]

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Monitoring ocean surface temperature is critical to infer the variability of the upper layers of the ocean, from short temporal scales to climatic change scales. Analysis of the climatological trends and anomalies is fundamental to comprehend the long-term effects of climate change on marine ecosystems and coastal regions. The original data for the dataset presented was collected by the Portuguese Hydrographic Institute (Instituto Hidrográfico) using seven Ondograph and Meteo-oceanography buoys anchored offshore along the Portuguese coast to acquire ocean surface temperatures. The original raw data was pre-processed to provide averages over 3-hour periods and daily averages, and this cleaned data constitutes the provided dataset. The 3-hour temperature averages were obtained mainly between 2011 and 2015, and the daily temperature averages were obtained in intervals that vary with the considered buoy, having an average interval of 14 years per buoy. The data gathered provides a considerable temporal window, enabling the creation of data series and the implementation of data mining algorithms to develop decision support systems. Collecting data in situ makes it possible to validate simulated results obtained using approximation models. This allows for more accurate temperature readings and facilitates testing and correcting created models.

This paper presents an exploration of facial skin temperature responses while the subject’s head posture is simultaneously varied in indoor environment settings by using benchmark datasets that include thermal and RGB images from healthy groups. The selection of gender-balanced was considered in the experiment, and thus an image enhancement algorithm was proposed before the image quality assessment is performed to characterize the quality score for individual images. For automatically extracting facial skin temperature, two sets of the labeled region of measurements are consistently detected across both image spectrums for all subjects. The mean temperature is then calculated in each labeled region and found to be statistically different due to the correlation of color temperature produced by each image group. In this work, the utilization of large image datasets containing a range of temperature trends may considerably improve temperature estimation for early detection of health issues. Although the findings may not be as accurate as the use of biosensor methods to represent actual body temperature, the designated algorithms manage to improve the analysis success by showing warm or cold temperature values as a quick screening of human spontaneous that may be correlated to emotional discomfort for contactless use. The experiments demonstrate that a statistically significant change in the temperature measurements can be found between the selection of facial regional, gender-related and asymmetry analysis on similar facial anatomy. Recent studies indicate that these parameters continue to be a significant basis for instigating of the risks associated with cardiovascular disease (CVD) in clinical settings.

Excessive temperatures can lead to accelerated aging and irreversible damage in electric machines. Therefore, real-time temperature monitoring is vital for highly utilized electric machines in automotive drives to ensure that temperatures are within safe operating limits during operation. Installing temperature sensors on all critical parts would incur too much cost. Hence, model-based real-time temperature monitoring is a preferred solution. Recent publications typically utilize low-dimensional lumped-parameter thermal networks. This article presents a modeling method for a permanent magnet synchronous machine (PMSM), where the thermal model is derived using the finite-volume method. The model is calibrated with measurement data. A model-order reduction method is applied, which significantly reduces the computational costs of the model while preserving important (uncertain) parameters, such as heat transfer coefficients. Experimental results for different load cycles of the considered machine validate the feasibility and accuracy of the proposed model. Finally, comparing the model with measured temperatures at positions not used for calibration shows that the proposed method accurately captures the temperature distribution in the whole machine without changing the model structure.

Hyperthermia induces slight temperature increase of 4–8 °C inside the tumor, making it more responsive to radiation and drugs, thereby improving the outcome of the oncological treatment. To verify the level of heat in the tumor and to avoid damage of the healthy tissue, methods for non-invasive temperature monitoring are needed. Temperature estimation by means of microwave imaging is of great interest among the scientific community. In this paper, we present the results of experiments based on ultra-wideband (UWB) M-sequence technology. Our temperature estimation approach uses temperature dependency of tissue dielectric properties and relation of UWB images to the reflection coefficient on the boundary between tissue types. The realistic measurement setup for neck cancer hyperthermia considers three antenna arrangements. Data are processed with Delay and Sum beamforming and Truncated Singular Value Decomposition. Two types of experiments are presented in this paper. In the first experiment, relative permittivity of subsequently replaced tumor mimicking material is estimated, and in the second experiment, real temperature change in the tumor imitate is monitored. The results showed that the presented approach allows for qualitative as well as quantitative permittivity and temperature estimation. The frequency range for temperature estimation, preferable antenna configurations, and limitations of the method are indicated.

BackgroundMany persons with active SARS-CoV-2 infection experience mild or no symptoms, presenting barriers to COVID-19 prevention. Regular temperature screening is nonetheless used in some settings, including university campuses, to reduce transmission potential. We evaluated the potential impact of this strategy using a prospective university-affiliated cohort.MethodsBetween June and August 2020, 2912 participants were enrolled and tested for SARS-CoV-2 by PCR at least once (median: 3, range: 1-9). Participants reported temperature and symptoms daily via electronic survey using a previously owned or study-provided thermometer. We assessed feasibility and acceptability of daily temperature monitoring, calculated sensitivity and specificity of various fever-based strategies for restricting campus access to reduce transmission, and estimated the association between measured temperature and SARS-CoV-2 test positivity using a longitudinal binomial mixed model.ResultsMost participants (70.2%) did not initially have a thermometer for taking their temperature daily. Across 5481 total person months, the average daily completion rate of temperature values was 61.6% (median: 67.6%, IQR: 41.8-86.2%). Sensitivity for SARS-CoV-2 ranged from 0% (95% CI 0-9.7%) to 40.5% (95% CI 25.6-56.7%) across all strategies for self-report of possible COVID-19 symptoms on day of specimen collection, with corresponding specificity of 99.9% (95% CI 99.8-100%) to 95.3% (95% CI 94.7-95.9%). An increase of 0.1 °F in individual mean body temperature on the same day as specimen collection was associated with 1.11 increased odds of SARS-CoV-2 positivity (95% CI 1.06-1.17).ConclusionsOur study is the first, to our knowledge, that examines the feasibility, acceptability, and effectiveness of daily temperature screening in a prospective cohort during an infectious disease outbreak, and the only study to assess these strategies in a university population. Daily temperature monitoring was feasible and acceptable; however, the majority of potentially infectious individuals were not detected by temperature monitoring, suggesting that temperature screening is insufficient as a primary means of detection to reduce transmission of SARS-CoV-2.

Vaccines are a unique category of drugs sensitive to temperature and humidity and whose effectiveness directly impacts public health. There has been an increase in vaccine-related adverse events worldwide, particularly in developing countries, attributed to suboptimal temperatures during transport and storage. At the same time, the Internet of Things (IoT) has ushered in a paradigm shift in vaccine information and storage monitoring, enabling continuous 24/7 tracking. This further reduces the dependence on limited human resources and significantly reduces the associated errors and losses. This paper presents an IoT-driven framework that aims to improve the sustainability of medical cold chain management. The framework promotes trust and transparency in vaccine surveillance data by accessing and authenticating IoT devices. The proposed system aims to improve the safety and sustainability of vaccine management. Moreover, we provide detailed insights into the design and hardware components of the proposed framework. In addition, the specific use of the framework in a particular province is highlighted, covering the design of the software platform and the analysis of the hardware equipment.

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. [ABSTRACT FROM AUTHOR]

Objective: Understansding the changing patterns of in vivo electrical properties for the target tissue is crucial for the accurate temperature monitoring and the treatment efficacy in thermal therapy. Our research aims to investigate the changing patterns and the reversibility of in vivo electrical properties for both healthy livers and liver tumors in a mouse model over a frequency range of 1 Hz to 1 MHz at temperatures between 30 °C to 90 °C. Methods and materials: The mice were anesthetized and the target organ was exposed. An 808-nm near-infrared laser was employed as the heating source to heat the organ in vivo. The four-needle electrode, connected to an impedance analyzer, was utilized to obtain the impedance at varying temperatures, which were monitored by a thermocouple. Results: The findings indicated a gradual decline in impedance with an increase in temperature. Furthermore, the impedance was normalized to that at 30 °C, and the real part of the normalized impedance was defined as the k-values, which range from 0 to 1. The results demonstrated a linear correlation between k-values and temperatures (R2 > 0.9 for livers and R2 > 0.8 for tumors). Significant differences were observed between livers and tumors at 1, 10 and 50 kHz (p < 0.05). Additionally, it was demonstrated that the electrical properties could be reversed when the temperature was below or equal to 45 °C. Conclusion: We believe that these results will contribute to the advancement of radiofrequency ablation systems and the development of techniques for temperature monitoring during liver thermal treatment. [ABSTRACT FROM AUTHOR]

Based on that, the Internet of Things (IoT) is used in industrial applications for monitoring and controlling various sensor operations. In existing work, IoT-based monitoring and controlling operations for industries are proposed. But, in this, real-time monitoring of the data is performed to take necessary actions. This may fail at a fraction of a second when the device crossed its breakpoint or threshold value. Hence, in this, an optimized deep learning approach (Convolutional Neural Network) is proposed for monitoring and controlling the temperature in electrical motors. Here, the controlling is performed by predicting the temperature using a deep learning approach. This helps to improve the controlling operations in the IoT environment and protect the device from Malfunctioning. The proposed approach is tested on the Kaggle Sensor dataset for electrical motors. The optimal hyperparameters for the CNN are determined through the hybrid particle swarm and genetic algorithm by minimizing the cost function. The cost function is to reduce the RMSE rate. This method's presentation is evaluated and the fidelity of root mean square merits. The whole process is implemented using MATLAB R2020a version under Windows 10 environment. [ABSTRACT FROM AUTHOR]