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Manipulating ferromagnetic particles using an alternating current (AC) magnetic field is a versatile method for quick, local, and on‐demand heat generation. These particles can be incorporated into various matrices as heating elements. Their heat release can be controlled by adjusting process or material parameters. Herein, a proof‐of‐concept for a flexible polymer composite with customizable magnetically triggered heat release due to prior object identification via fluorescence readout is presented. The maximum temperature resulting from this process can be determined through a second fluorescence readout ex post. This novel combination of functionalities results from the synergistic interaction of inductively heatable magnetic supraparticles (SPs) and luminescent communicating SPs in one polydimethylsiloxane composite. The surface of the composite can be heated to the maximum temperatures of choice in a range between 125 and 200 °C within 2 s. Heat release and temperature verification provide spatial resolution of millimeters. The identification signature and the working range of the temperature indication functionality of the composite are customizable by exploiting its modular material design. The temperature indication functionality of the composite offers spatial resolution and ex‐post readout at any point of interest, making it a versatile alternative to established optical thermometry methods. [ABSTRACT FROM AUTHOR]

Elevation‐dependent warming (EDW) has been a topic of intense debate due to limited observed data in global highland areas. This study aims to fill this gap by utilizing CRU and ERA5 datasets from 1981 to 2021 to explore the trends of climate change and its elevation dependency. The anomalies of temperature indicators (Tmean, Tmax, and Tmin) in both ERA5 and CRU showed significant warming trends over global highlands. Moreover, the response of temperature indicators to elevation across global highlands is not spatially uniform. The linear regression model based on the elevation showed significant warming signals for the temperature indicators at various elevations over the global highlands. On a regional scale, Tmean and Tmax predominantly showed linear EDW over EU highlands, while Tmean in Asian highlands exhibited EDW signals at 4–5 km. Tmin showed EDW at 2.5–5.5 km with ERA5 and 3–5 km with CRU. In the Andes, EDW was prominent at 2.5–4 km. Overall, EDW signals are evident in all studied regions but vary across them. While assessing the driving factors, the results of this study indicate that total column water vapour (TCWV), snow depth (SD), snow albedo, and normalized difference vegetation index (NDVI) correlated positively with the temperature indicators. These findings emphasize the significance of elevation‐specific interactions between environmental factors and temperature in forecasting temperature changes in mountainous areas. Additionally, temperature exhibited coherence with teleconnection indices from the Atlantic and Pacific Oceans. Asian and European (EU) highlands exhibited interzonal coherence with the Pacific and Atlantic Oceans, while North American (NA) highlands showed coherence, followed by South American (SA) highlands. These findings provide a comprehensive understanding of EDW and its implications for highland regions globally, including the potential for more severe depletion of snow/ice resources in a warmer future. [ABSTRACT FROM AUTHOR]

Most gas-based DRI (Direct Reduced Iron) furnaces use reformed natural gas as reductant which is richer in H2 than CO. The present study deals with the Midrex DRI plant at JSW Steel Ltd., Vijayanagar where the reducing gas is derived from the COREX furnace top gas which is richer in CO than H2. The thermo-kinetic behavior of the DRI furnace operated with COREX gas has been modeled. A mathematical framework was developed combining the heat and mass transfer equations with kinetic data for the gas-based reduction of pellets in a DRI furnace. Using the open-source CFD software, OpenFOAM, the equations were coupled and solved for steady state inside an axisymmetric 3D wedge. The model visualizes and quantifies the burden profiles, the gas composition, solid and gas temperatures for different operating conditions. The performance of the model was validated against plant scale-operating conditions and the process curves generated for different production rates. The obtained process curves highlighted lesser specific gas consumption at lower production rates and the importance of top gas CO2 pct and top gas temperature as indicators of metallization inside the furnace. [ABSTRACT FROM AUTHOR]

AimMethodologyResultsConclusionsTo evaluate the behaviour of the XP‐Endo Finisher and the variation in the intracanal temperature of the irrigant at rest and when activated over time.Differential scanning calorimetry (DSC) determined the transformation temperatures of XP‐Endo Finisher instruments. A digital thermocouple was used to measure the temperature of the irrigant inside the pulp chamber. Two measurements were performed for each tooth (n = 12): with the irrigant at rest and during XP‐Endo agitation for 60 s to observe the temperature evolution. The data were statistically analysed using a t‐test with a confidence level of 95%.DSC results suggested that the XP‐Endo Finisher had a mixed R‐phase and austenitic structure at room temperature. The temperature values at predetermined time points (0, 10, 40, 70, 120 and 240 s) were measured, and no statistical difference was observed between the values of the resting and activated solutions at any of the selected points (p > .05). For the protocol performed with the XP‐Endo file, the mean irrigant temperature observed at instrument insertion inside the root canal was 28.65°C. After 60 s of agitation, the temperature was 34.02°C. The solution temperature stabilized inside the canal only after 211 s at 35.5°C. The mean maximum irrigation solution temperature recorded inside the canal was 35.5°C without agitation and after XP‐endo agitation (p > .05).Although the XP‐Endo Finisher system does not promote heating of the irrigation solution, file expansion responsible for improved instrument cleaning starts at a temperature below the expected value. [ABSTRACT FROM AUTHOR]

The article in the journal "Oceanography" discusses a project-based learning activity that focuses on developing engineering skills through the creation of an Arduino-based submersible temperature and depth sensor. The project aims to teach students about sensors, circuits, hardware, and software design, as well as data collection and analysis. Students build, calibrate, and test the instrument, gaining hands-on experience in marine science engineering. The project is designed for undergraduates and graduate students with minimal engineering experience, allowing for customization based on students' interests and expertise levels. The course emphasizes problem-solving skills and critical thinking, preparing students for future research and career opportunities in marine science and engineering. [Extracted from the article]

Aim: This study was twofold: (i) it aimed to investigate the morphometric changes of three temperature‐sensitive nickel–titanium (NiTi) instruments at different temperatures, and (ii) to conduct an in vivo real‐time analysis of intracanal temperature changes. Methods: Changes in the shape and length of XP‐Endo Shaper, XP‐Endo Finisher, and XP‐Endo Finisher‐R were evaluated in real time whilst heated in a temperature‐controlled water bath from 22 to 45°C. Instruments were fixed to a laminated water‐resistant 1 mm graph paper attached to a stone block. Instruments were imaged whilst subjected to increasing temperature using a digital camera attached to an operating microscope. From recorded videos, still frames were extracted at 10‐s intervals and changes in the length and shape of each instrument were measured and changes were plotted against time. Moreover, the intracanal temperature of distal roots of lower molars was measured in vivo for patients attending the clinic for non‐surgical root canal treatments. The temperature was measured using a K‐type thermocouple probe inserted into the mid‐root level after irrigating the canal with a solution set at room temperature (22°C) or heated to 45°C. The intraoral and intracanal temperatures were recorded using a video camera for 180 s at 5‐s intervals to plot the change in the intraoral and intracanal temperature, after both irrigation solution temperatures, with time. Results: The shape transformation of XP‐Endo Shaper began at 31.5 ± 2.0°C and reached its optimal transformation at 35.1 ± 1.0°C. For the Finisher and Finisher‐R, shape transformations began at 29.2 ± 1.9 and 26.9 ± 2.2°C reaching the optimal transformation at 33.9 ± 1.4 and 32.7 ± 1.7°C, respectively. The average decreases in lengths of XP‐Endo Shaper, Finisher, and Finisher‐R after full transformation were 0.43 ± 0.23, 1.07 ± 0.22, and 1.15 ± 0.22 mm, respectively. The intracanal temperature reached 32.9 ± 0.8 and 33.2 ± 1.0°C after 3 min of application of irrigation solutions set at 22 or 45°C, respectively. Conclusion: The tested instruments exhibited diverse changes in their shapes and lengths at varying temperatures. Despite the temperature of the irrigation solution, the intracanal temperature consistently remained lower than the intracanal temperature once equilibrium was reached. This highlights the importance of considering the temperature of irrigation solution during in vitro testing of endodontic instruments. [ABSTRACT FROM AUTHOR]

Thermochromic materials have garnered significant attention for their ability to change color in response to temperature fluctuations, offering innovative solutions for smart textiles, fashion, and functional clothing. This review provides a comprehensive overview of organic thermochromic materials and their potential in textile applications. It begins by explaining the fundamental principles and mechanisms of thermochromism, exploring various organic types such as leuco dyes, liquid crystals, and polymers, along with their advantages and limitations in textile applications. The paper delves into aspects such as synthesis methods, compatibility with textile substrates, durability, and washfastness. Recent advancements, including innovative manufacturing techniques and emerging materials, are highlighted, showcasing enhanced performance characteristics. The diverse applications of organic thermochromic textiles, from thermally responsive clothing for comfort and energy efficiency to visual indicators for temperature monitoring in industrial settings, are discussed. Finally, the review offers insights into future trends and prospects for organic thermochromic materials in textiles. This review serves as a valuable resource for researchers, textile engineers, and designers aiming to leverage organic thermochromic materials to create dynamic and functional textiles for the future. [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]

To address the challenges of slow curing speed and suboptimal microwave absorption during the paving of cold-mixed and cold-laid asphalt mixtures, this study introduces SiC-Fe3O4 composite material (SF) into emulsified asphalt mixtures to enhance microwave absorption and accelerate curing via microwave heating. Initially, based on the maximum density curve theory, an appropriate mineral aggregate gradation was designed, and the optimal ratio of emulsified asphalt mixture was determined through mixing tests, cohesion tests, wet wheel wear tests, and load wheel sand adhesion tests. Subsequently, the influence of SF content on the mixing performance of emulsified asphalt mixtures was analyzed through mixing and consistency tests. Finally, the microwave absorption performance of the mixture was evaluated by designing microwave heating tests under different conditions, using temperature indicators and quality indicators. The experimental results indicate that when SF content ranges from 0% to 4%, the mixing performance of the emulsified asphalt mixture meets specification requirements. The dosage of SF, SF composite ratio, and microwave power significantly impact microwave absorption performance, whereas environmental temperature has a relatively minor effect. The optimal mix ratio for the emulsified asphalt mixture is mineral aggregate:modified emulsified asphalt:water:cement = 100:12.8:6:1. The ideal SF dosage is 4%, with an optimal SiC to Fe3O4 composite ratio of 1:1, and a suitable microwave power range of 600–1000 W. [ABSTRACT FROM AUTHOR]

Sodium alginate (SA)–purple sweet potato peel extracts (PPE) from industrial waste indicator films were developed at different drying temperatures (25, 30, 35, 40, 45, 50, and 55 °C). The effects of drying temperatures on the film's structural, physical, and sensitive properties were investigated. On the structural properties, scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction indicated that compactness, intermolecular interactions, and crystallinity of indicator films were improved at a lower drying temperature. On the physical properties, with the drying temperature increasing, elongation at the break increased significantly (p < 0.05); ΔE and water-vapor permeability decreased significantly (p < 0.05); and thickness and tensile strength initially increased significantly (90.46 → 98.46, 62.99 → 95.73) and subsequently decreased significantly (98.46 → 71.93, 95.73 → 55.44) (p < 0.05), with the maximum values obtained at 30 °C. On sensitivity, the corresponding colors of the films became lighter as the drying temperature increased, and the films exhibited relatively excellent pH and NH3 sensitivity, with easily discernible color changes at lower temperatures. The results of this paper revealed that the overall film characteristics are improved at lower drying temperatures, which will provide valuable references for selecting the drying temperature for preparing indicator films as a guide for industrialized production. [ABSTRACT FROM AUTHOR]

The method of measuring temperature using luminescence by analyzing the emission spectra of Pr3+-doped YF3 using principal component analysis is presented. The Pr3+-doped YF3 is synthesized using a solid-state technique, and its single-phase orthorhombic crystal structure is confirmed using X-ray diffraction. The emission spectra measured within the 93–473 K temperature range displays characteristic Pr3+ f-f electronic transitions. The red emission from the 3P0,1→3H6,3F2 electronic transition mostly dominates the spectra. However, at low temperatures, the intensity of the green emissions from the 3P0,1→3H5, deep-red 3P0,1→3F4, and the deep-red emissions from the 3P0,1→3F4 transitions are considerably lower compared to the intensity of the red emissions. Temperature variations directly impact the photoluminescent spectra, causing a notable increase in the green and deep-red emissions from the 3P1 excited state. We utilized the entire spectrum as an input for principal component analysis, considering each temperature as an independent group of data. The first principal component explained 99.3% of the variance in emission spectra caused by temperature and we further used it as a reliable temperature indicator for luminescence thermometry. The approach has a maximum absolute sensitivity of around 0.012 K−1. The average accuracy and precision values are 0.7 K and 0.5 K, respectively. [ABSTRACT FROM AUTHOR]

Darwin proposed that blushing—the reddening of the face owing to heightened self-awareness—is 'the most human of all expressions'. Yet, relatively little is known about the underlying mechanisms of blushing. Theories diverge on whether it is a rapid, spontaneous emotional response that does not involve reflection upon the self or whether it results from higher-order socio-cognitive processes. Investigating the neural substrates of blushing can shed light on the mental processes underlying blushing and the mechanisms involved in self-awareness. To reveal neural activity associated with blushing, 16–20 year-old participants (n = 40) watched pre-recorded videos of themselves (versus other people as a control condition) singing karaoke in a magnetic resonance imaging scanner. We measured participants' cheek temperature increase—an indicator of blushing—and their brain activity. The results showed that blushing is higher when watching oneself versus others sing. Those who blushed more while watching themselves sing had, on average, higher activation in the cerebellum (lobule V) and the left paracentral lobe and exhibited more time-locked processing of the videos in early visual cortices. These findings show that blushing is associated with the activation of brain areas involved in emotional arousal, suggesting that it may occur independently of higher-order socio-cognitive processes. Our results provide new avenues for future research on self-awareness in infants and non-human animals. [ABSTRACT FROM AUTHOR]

The work presented in this paper reports the shape memory effect characteristics of a CuAlFe high-temperature shape memory alloy (HTSMA) with a new composition and new martensitic transformation temperatures. In this context, casting via a vacuum arc melter produced the Cu-rich ternary CuAlFe high-temperature shape memory alloy (HTSMA). Both DSC and DTA measurement thermograms showed excellent martensitic phase transformation peaks while heating the alloy up and cooling it back. The forward and reverse martensitic phase transformation peaks at different DSC heating/cooling rates had high thermal stability, and the temperature range of these transformations was found above 100 °C between 220-340 °C circa. Therefore, this classifies the alloy as a high-temperature shape memory alloy. Moreover, the formation of the martensite phases, i.e. the microstructural base mechanism for the shape memory effect of the alloy, was confirmed by X-ray diffraction (XRD) pattern obtained at room temperature using CuKa radiation. The findings of this study can be helpful in the hightemperature shape memory alloy-related application areas, in which areas different shape memory properties are highly demanded. [ABSTRACT FROM AUTHOR]

In the current context of climate change, the increase in minimum temperatures recorded in recent decades has received special scientific attention due to its importance for the proper night's sleep and health of the population, among other considerations. One of the main indicators usually considered refers to the frequency of tropical nights (≥20°C), which have begun to become widespread in regions hitherto excluded from this type of event. This paper analyses tropical nights in Spain between 1970 and 2023, addressing their mean annual occurrence, their intensity, their monthly distribution and the average number of consecutive tropical nights recorded, as well as their relationship with relative humidity. The results, based on the analysis of 75 homogenized series located in 44 different provinces, allow us to differentiate seven large areas based on the minimum temperature in which there has been an increase in the frequency and intensity of tropical nights, which progressively extend the season in which they can appear. Similarly, a generalized increase in the maximum number of consecutive nights thermally above 20°C was identified, in addition to the presence of high relative humidity in coastal areas during these episodes. [ABSTRACT FROM AUTHOR]

Temperature indicators trace (un)desired thermal impacts across their thermal history upon readout at every point of interest via defined irreversible signal changes. Ratiometric luminescent temperature indicators are attractive due to their fast, sensitive, contactless, spatially‐resolved, and self‐referenced readout. However, they have a limited working range as commonly only one specific temperature‐induced physicochemical effect is exploited. Herein, dual‐threshold temperature indicator supraparticles (SPs) are introduced that expand the working range of individual luminescent probes and enhance the extractable information on the thermal history. These SPs derive their functionality from the synergistic interplay of three spectrally distinguishable luminescent species assembled in one multihierarchical, micrometer‐sized particle of hybrid organic‐inorganic nature. This engineered nanostructure enables the stepwise modulation of the physicochemical microenvironment of two incorporated coumarin species at programmable threshold temperatures, resulting in distinct changes in their emission. As these changes are based on dye‐specific mechanisms that are induced in consecutive temperature regimes, the SPs achieve a scarcely reported broad working range (60–200 °C) with temperature‐dependent response times of minutes to seconds. From a broader perspective, the conceptualized SPs pioneer in how multiple individual luminescent probes with different excitation‐emission properties and indicator mechanisms are synergistically united in one advanced indicator system by precise material engineering. [ABSTRACT FROM AUTHOR]

The purpose of this study was to evaluate and validate methylene blue migration from printed time–temperature indicators (TTIs) into food. It also highlights the importance of establishing regulatory measures and safety standards for food packaging, suggesting that this can contribute to improving food packaging safety. Liquid chromatography–mass spectrometry (LC-MS/MS) was used to quantify methylene blue migration in various food simulant and food matrix samples. The results show that the level of methylene blue migration varies significantly depending on the chemical properties of the food mimetic and the composition of the food matrix. The established method demonstrated a high sensitivity, with limits of detection (LODs) of 0.0019–0.0706 μg/L (kg) and limits of quantification (LOQs) of 0.0057–0.2138 μg/L (kg). This study highlights the need for a regulatory framework to mitigate the health risks associated with methylene blue in intelligent packaging systems and argues that regulatory thresholds should be set to ensure food safety and quality. [ABSTRACT FROM AUTHOR]

Quantum processor architectures must enable scaling to large qubit numbers while providing two-dimensional qubit connectivity and exquisite operation fidelities. For microwave-controlled semiconductor spin qubits, dense arrays have made considerable progress, but are still limited in size by wiring fan-out and exhibit significant crosstalk between qubits. To overcome these limitations, we introduce the SpinBus architecture, which uses electron shuttling to connect qubits and features low operating frequencies and enhanced qubit coherence. Device simulations for all relevant operations in the Si/SiGe platform validate the feasibility with established semiconductor patterning technology and operation fidelities exceeding 99.9%. Control using room temperature instruments can plausibly support at least 144 qubits, but much larger numbers are conceivable with cryogenic control circuits. Building on the theoretical feasibility of high-fidelity spin-coherent electron shuttling as key enabling factor, the SpinBus architecture may be the basis for a spin-based quantum processor that meets the scalability requirements for practical quantum computing. Semiconductor qubit architectures based on direct qubit coupling suffer from wiring fan-out and crosstalk as they scale up. Here the authors propose an architecture based on conveyor-mode shuttling of electron spins that tackles these issues and validate it numerically on quantum dot spin qubits in Si/SiGe. [ABSTRACT FROM AUTHOR]

The observation of the global 21 cm signal produced by neutral hydrogen gas in the intergalactic medium (IGM) during the Dark Ages, Cosmic Dawn, and Epoch of Reionization requires measurements with extremely well-calibrated wideband radiometers. We describe the design and characterization of the Mapper of the IGM Spin Temperature (MIST), which is a new ground-based, single-antenna, global 21 cm experiment. The design of MIST was guided by the objectives of avoiding systematics from an antenna ground plane and cables around the antenna, as well as maximizing the instrument's on-sky efficiency and portability for operations at remote sites. We have built two MIST instruments, which observe in the range 25–105 MHz. For the 21 cm signal, this frequency range approximately corresponds to redshifts 55.5 > z > 12.5, encompassing the Dark Ages and Cosmic Dawn. The MIST antenna is a horizontal blade dipole of 2.42 m in length, 60 cm in width, and 52 cm in height above the ground. This antenna operates without a metal ground plane. The instruments run on 12 V batteries and have a maximum power consumption of 17 W. The batteries and electronics are contained in a single receiver box located under the antenna. We present the characterization of the instruments using electromagnetic simulations and lab measurements. We also show sample sky measurements from recent observations at remote sites in California, Nevada, and the Canadian High Arctic. These measurements indicate that the instruments perform as expected. Detailed analyses of the sky measurements are left for future work. [ABSTRACT FROM AUTHOR]

Worldwide, environmental groups and policymakers are focusing on waste recycling to create economic value and on the decomposition of waste by leveraging on scarce resources. This work, therefore, explores the thermal decomposition of enhanced biodegradable polymer matrices made from a mixture of discarded Phoenix dactylifera L./high-density polyethylene (PD/HDPE) using the machine learning analysis of experimental data. The experimental results of these samples were obtained via thermogravimetric (TGA) analysis under an oxidation–free environment, with heating rates of 10, 20, and 40 °C·min−1 and a degradation temperature range from 25 to 600 °C. The TGA analyses revealed the continued dependence of the actual percentage weight loss by these materials as a test function of the degradation temperature, shifting thermograms to temperature maxima consistent with increasing heating rates. Although high-density polyethylene (HDPE) materials were found to be thermally more stable than Phoenix dactylifera L. (PD) materials, PD/HDPE composite materials contained a significant amount of residual ash. Using a machine learning deep neural network approach for this process, significantly improved learning algorithms have been developed, which reduces the overall cost function (residual error) to almost zero (0.025) after just over a million iterations (epochs) and provides predictions that overlap with the experimental results ( R 2 ~ 1 ). Learning algorithms, along with optimized synaptic weights and biases, were employed to predict the behaviour of PD materials based on experimental thermograms conducted at higher degradation temperatures, typically ranging between 600 and 1000 °C. Predicted data using the enhanced learning algorithms completely overlapped the experiments ( R 2 ~ 1 ) for these higher degradation temperatures with near unity correlation if the decomposition of the materials continued until the residue was attained. With this approach, it is possible to predict and optimize the thermal characteristics of PD and HDPE with greater efficiency, which reduces the need for multiple design iterations and experimentation. [ABSTRACT FROM AUTHOR]

High temperature warning indicators play a pivotal role in meteorological departments, serving as crucial criteria for issuing warnings that guide both social production and daily life. Despite their importance, limited studies have explored the relationship between different global warming levels and changes in high temperature warning indicators. In this study, we analyze data from 2,419 meteorological stations over China and utilize the Coupled Model Intercomparison Project Phase 6 (CMIP6) models to examine historical changes in high temperature warning indicators used by the China Meteorological Administration. We evaluate model performance and estimate future changes in these indicators using an annual cycle bias correction method. The results indicate that since 1961, the number of high temperature days (TX35d and TX40d) and length of season (TX40d and TX40l) with daily maximum temperature reaching or exceeding 35°C and 40°C have increased over China. The intensity of high temperatures (TXx) has strengthened and the geographical extent affected by high temperatures has expanded. In 2022, the occurrence of 40°C high temperatures surges, with Eastern China experiencing a two-day increase in TX40d and an extended seasonal length in TX40l by over five days. While CMIP6 models have underestimated the high temperature indictors associated with 35°C during historical periods, notable difference is not observed between the models and observations for TX40d and TX40l, given their rare occurrence. However, future projections, after bias correction, indicate that the increasing trends for 35°C and 40°C high temperature days and length of season become more pronounced than the raw projection, suggesting a more severe increase than that anticipated originally. As global warming intensifies, the high temperature days and length of season are projected to increase non-linearly, while the intensity of high temperatures is expected to increase linearly. For every 1°C increase in global temperature, the intensity is projected to rise by approximately 1.4°C. The impact of high temperatures is expanding, with the major hotspot for China located in the eastern and northwestern regions. Under 5°C global warming, certain regions in China may experience prolonged extreme high temperatures. For instance, 40°C high temperature days in areas like North China and the Yangtze River Basin could increase by about 32 d, and the length of season could extend by approximately 100 d. [ABSTRACT FROM AUTHOR]

Summary: The Optimization‐Driven Multispectral Gamma Correction (ODMGC) algorithm overcomes challenges in gathering subtle information and detecting cancer in dense breast thermograms. This algorithm enhances the accuracy of true positives and true negatives while minimising false negatives and false positives. The ODMGC involves a multi‐step optimisation process that categorises grey‐scale images of breast thermograms based on mean brightness. Then, based on the grey levels of the pixels, we grouped each categorisation into sub‐regions. Followed by each group has undergone individually optimised base enhancement. This process enhances the contrast between cancerous and normal tissues, eliminates over‐ and under‐enhancement, and supports breast tumour diagnosis. The optimised‐based enhancement images serve as a reference point for the histogram specification of the V component of the thermograms in the HSV (Hue, Saturation, and Value) model. Further, we evaluated the proposed model using both qualitative and quantitative measures. Finally, using dimension‐reduced significant Grey‐Level Co‐occurrence Matrix (GLCM) features, we validated the results with a Random Forest (RF) classifier. The algorithm was successfully implemented in MATLAB 2020a, and the classifier was developed in Jupyter Notebook using Python. The subjective comparison confirmed the proposed method's superior resolution in normal and malignant cases. The classifier results showed an accuracy of 96.4%, sensitivity of 98.1%, and specificity of 96.9%. [ABSTRACT FROM AUTHOR]

An important issue concerning the inspection of the technical condition of electrical power components and systems is thermal imaging investigation. This paper presents how the thermograms obtained from these measurements should be interpreted correctly according to different standards and how operators should react when detecting a specific anomaly. It is also a review article in which all currently applicable international standards are referred to. The motivation of the article relates to the fact that these standards seem to be too general and do not cover all practical situations, even though, in many countries, thermal imaging diagnostics of overhead lines or overhead outdoor and indoor power stations have been used for years based on industry standards or good practices. The article aims are precisely to encourage and provoke the global community of metrologists, scientists, and engineers involved in thermographic measurements to discuss, strengthen efforts, and establish relevant international standards for the interpretation of thermograms containing the relevant temperature anomalies. [ABSTRACT FROM AUTHOR]

Charging methods significantly affect the performance and lifespan of lithium-ion batteries. Investigating charging techniques is crucial for optimizing the charging time, charging efficiency, and cycle life of the battery cells. This study introduces a real-time charging monitoring platform based on LabVIEW, enabling observation of battery parameters such as voltage, current, and temperature. The proposed system allows the precise control of charging parameters via a user-friendly interface. Utilizing a programmable DC power supply, it delivers specific charging waveforms, while data acquisition instruments record temperature changes. Key performance metrics, including charging time, efficiency, and temperature rise, are analyzed. Moreover, this paper conducts in-depth research on the constant temperature–constant voltage (CT-CV) charging technique and applies the Taguchi method to identify key parameter configurations that achieve the objectives of the shortest charging time, highest charging efficiency, and lowest average temperature rise. A comprehensive evaluation compares the optimized CT-CV method with conventional constant current–constant voltage (CC-CV) charging. The results demonstrate a 10.7% reduction in charging time compared to the 1C CC-CV method, indicating the efficacy of CT-CV in shortening charging duration while managing temperature rise. [ABSTRACT FROM AUTHOR]

Fatigue limit assessment methodologies based on the thermography technique are comprehensively studied in this work. Three fundamental indicators pertaining to temperature increase, intrinsic energy dissipation, and thermodynamic entropy are discussed in sequence. The main train of thought of thermo-based research is outlined. The main objective of this paper is, on the one hand, to describe some works that have been accomplished in this field and, on the other hand, to present further potential for future studies involving fatigue behaviors and thermography approaches. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs) have been recognized vastly as stimuli‐responsive materials owing to their extreme sensitivity toward the stimuli that make them flawless nominees for multifunctional device applications. However, MOFs are often oversensitive toward moisture, which significantly affects their stable responses and reproducibility. Herein, a MOF–polymer display (i.e., copper‐based MOF with polydimethylsiloxane) is developed that exhibits high sensitivity toward temperature changes without getting affected by moisture. In response to the thermal gradient, the display exhibits the change in color from sky blue to dark blue when the temperature varies from 30 to 100 ºC, which is attributed to the second‐order phase transition within the time interval 40 s and reversible in 60 s. To provide insights on the mechanism, ex situ UV–vis and temperature‐dependent operando X‐day diffraction are conducted, which unveils that the color change in the display is associated with reversible contraction/expansion of the unit cell parameters. In addition to that, the thermoresponse of the display remains unaffected under mechanical deformations, which indicates that the color display is mechanically and thermally stable. The as‐developed color display is mechanically robust and highly sensitive toward temperature change; it can be utilized as the color indicator in signaling temperature rise in smart mobiles or laptops during discharging to keep the user safe or applications in augmented intelligence. [ABSTRACT FROM AUTHOR]

One of the common causes of death for women worldwide is breast cancer which various screening and imaging techniques can reduce its mortality and treatment costs. Although mammography is the most common imaging modality for screening breast cancer, but it is expensive and uses radiation. As an emerging and promising technique, thermography offers numerous advantages, including the absence of radiation exposure, no discomfort, no invasiveness, and low cost. By recording and analyzing the temperature distribution in breast region, this type of thermography is able to detect abnormalities. Despite these advantages, thermography images may not be interpreted as easy as images obtained from other imaging modalities. This limitation has caused considerable increase in attention towards computer-aided diagnosis in parallel with applying artificial intelligence paradigm in order to interpretation of breast thermograms. Due to the breadth and diversity of these methods from various aspects, a framework is necessary for a better understanding, classification, and evaluation of these methods. In this article, we discuss two important aspects of breast thermogram processing including segmentation of Region of Interest and detection of abnormality. Additionally, to evaluate the existing methods in the two areas, advantages and disadvantages for each have been discussed and compared. The existing methods in two aspects can be divided into two groups, traditional and deep learning-based schemes, which the latter have become increasingly popular. Based on this, it can be said that a framework that is useful for any researcher who needs to gain an overview of breast thermograms and categorize problems and solutions is presented in this study. [ABSTRACT FROM AUTHOR]

Objective:To analyze the volatile components of Amomum viUosum(A.viUosum) Lour., Amomum villosum Lour. var.xanthioides T.L.Wu et Senjen and Amomum longiligular((A.longiligulare) T.L.Wu and their fake species Amomum chinense (A.chinense) Chun, and the gastric mucosal protective activity of the volatile oils of the four (Amomifructus) species. Methods: Headspace solid-phase microextraction-gaschromatography-mass spectrometry (HS-SPME-GC-MS) was used for the compositional analysis of the four (Amomifructus) species, and the chromatographic results were combined with NIST08 and NIST08s spectral libraries for comparative qualitative characterization, and the relative percentage contents of volatile components were calculated by the area normalization method with the principal component analysis and thermogram analysis. The in vitro activity of four (Amomi fruclus) species of volatile oils was evaluated by establishing an in vitro human gastric mucosal epithelial cell (GES-1 cell) injury model using the CCCK-8 method. Results: From A. villosum Lour., A. villosum Lour.var.xanthioides T.L. Wu et Senjen, A. longiligulare T.L. Wu and its fake Hainan fake species A. chinense Chun, a total of 114 chemical constituents were detected, and 57,,58,,58 and 58 volatile constituents were identified, each accounting for 93.23%, 88.79%, 90.87%, 91.40% of the total volatile constituents in terms of the relative percentage of the total volatile constituents content. 40.48%, 37.77%, 37.09% and 33.39% total sesquiterpene hydrocarbons accounted for 52.53%, 49.88%, 31.22%, 35.45% of the relative percentage content of total volatile components,respectively. The volatile oils of A. villosum Lour.^A. villosum Lour.var.xanthioides T.L.Wu et Senjen and A. longiligulare T.L.Wu had proctive activities on ethanol-induced GES-1 cell damage, and the counterfeit A. chinense Chun had no significant activity. Conclusion: The differences in volatile components and contents between A. villosum Lour. and A. villosum Lour.var.xanthioides T.L.Wu et Senjen are small, while the differences in volatile components and contents between A. longiligulare T.L.Wu,A. chinense Chu and A. villosum Lour., A. villosum Lour.var.xanthioides T.L.Wu et Senjen are large.Volatile oils of A. villosum Lour.,A. villosum Lour.var.xanthioides T.L.Wu et Senjen and A. longiligulare T.L.Wu showed protective effects against ethanol-induced damage in human GES-1 cells. [ABSTRACT FROM AUTHOR]

Based on numerical modeling of thermohydrodynamic processes in the wellbore under conditions of oil degassing, the possibility of estimating the coefficient of gas solubility in oil and the well flow rate is investigated based on an analysis of temperature distribution along the wellbore. It is shown that degassing of oil in the wellbore or in a bed leads to the formation of temperature cooling anomalies, which can be used to solve certain oilfield problems. The results obtained can be used in planning field-geophysical studies and interpreting the results of temperature studies of wells during the production of live crude. [ABSTRACT FROM AUTHOR]

Identifying ultrahigh-temperature (UHT) metamorphism in basic granulites is challenged by the uncertainty of peak temperatures. Consequently, available temperature indicators are desiderated all along. In this study, we investigated low-pressure basic granulites from the Daqingshan, North China Craton and determined a UHT peak condition around 1000–1050 °C and 0.8–0.9 GPa. This peak condition was constrained by combining the AlT of 0.10–0.12 in clinopyroxene (Cpx) cores, maximum Ti of 0.36–0.38 in amphibole (Amp) cores and anorthite proportion (X An) of 0.67–0.70 and 0.61–0.63 in plagioclase (Pl) cores/mantles analyzed in two selected samples. The P – T records obtained from several thermobarometers related to amphibole, plagioclase and/or clinopyroxene were also verified to be in agreement with the phase equilibria modeling results. Notably, AlT-in-Cpx is assessed to be a reliable temperature indicator in basic granulites with the Opx–Cpx–Pl–Amp assemblage, albeit could be influenced by bulk-rock compositions in some extent and has a temperature standard error of ~70 °C. Besides, the post-peak evolution was dominated by near-isobaric cooling at 1.94–1.93 Ga, to a fluid-absent solidus as high as ~940 °C. During the cooling process, plagioclase and amphibole grew together at the expense of Al-rich clinopyroxene and unsegregated melts, accompanied by the (rimward) decrease of AlT-in-Cpx, Ti-in-Amp and X An-in-Pl. A pre-peak process is inferred to be decompressional heating. The UHT metamorphism in Daqingshan is interpreted to result from asthenosphere upwelling and thermal advection from regional mantle-derived magmatism during post-orogenic extension, in a newly developed back-arc-related environment. [ABSTRACT FROM AUTHOR]

To ensure the safety of the hogs in large-scale pig farming, the hog transfer truck needs to be cleaned and disinfected at high temperatures. This paper proposes a model of the transfer truck drying room based on spherical air outlets, using RC-4HC temperature and humidity measuring instruments, electronic scale, and other devices to measure the drying process of the transfer trucks at different outdoor ambient temperatures, different deck placement techniques, and different degrees of preheating, and explores the problem of excessive energy consumption in the transfer truck drying room. The outcome demonstrates that the transfer truck drying chamber has the fastest drying time—3137 s. The drying room's energy use is also significantly influenced by the transfer truck leaching effect, deck positioning, which has the second-highest impact, and the outdoor ambient temperature, which has a negligible effect. The fuel consumption of the drying room is decreased by 5.19% and 25.78%, respectively, when the second truck is preheated for 600 s and 1500 s utilizing the leftover heat from the drying of the first truck. The resultant energy savings are astounding. [ABSTRACT FROM AUTHOR]

In this study, we evaluated extreme climate indicators for precipitation and temperature in the Brazilian Legal Amazon (BLA) from 1961 to 2021. Data from 38 National Institute of Meteorology (INMET) weather stations with a record failure rate less than 12% were used, and RClimDex software and the Mann–Kendall test, Pettitt test, standard normal homogeneity test (SNHT), and Buishand test were employed to analyse the data. The results showed increased extreme rainfall events, including the annual total rainfall divided by wet days (SDII). More frequent discontinuities were observed in the 1980s (SNHT) and 1990s (Pettitt and Buishand tests). The extreme temperature climate indicators also significantly increased, particularly in the 1990s. These increases are likely linked to changes in local climate conditions due to agricultural expansion, intensified industrial activities, and regional urbanization. This study underscores the need for proactive measures to curb illegal deforestation and reduce CO2 emissions and further research to better understand and mitigate the adverse impacts of these changes on the BLA environment and local communities. [ABSTRACT FROM AUTHOR]

Atmospheric temperature is fundamental information for various industries, such as production, life, and scientific research. The temperature error induced by the solar rays can reach 1 °C or even higher. A hemispherical shell-shaped atmospheric temperature measuring instrument that can reduce heat pollution and increase air velocity was designed. First, the instrument was optimized using computational fluid dynamics (CFD) software packages. Then, the CFD software packages were employed to quantify the temperature errors of the instrument with varying situations. A neural network model was employed to develop a temperature error correction model that can be targeted for multi-variable changes. This model provides accurate correction data when the influencing factors change continuously. Finally, field experiments were performed. The experimental data analysis indicates that the mean temperature error and the maximum error of the instrument before correction are 0.08 and 0.25 °C, respectively. The root mean square error, the mean absolute error, and the correlation coefficient between measured temperature errors from experiments and corrected temperature errors from the correction model are 0.099, 0.016, and 0.952 °C, respectively. By utilizing a temperature error correction model, the measuring error of the instrument can be minimized to a range between −0.05 and 0.04 °C. Consequently, the instrument is anticipated to enhance temperature measurement accuracy to ∼0.1 °C. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal 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.)

Copyright of Current Research in Dental Sciences is the property of Ataturk University Coordinatorship of Scientific Journals 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.)

Climate indicators are useful tools to synthesise climate information from multiple station time-series into a single national indicator. The method applied should be spatially representative and robust over time. We introduce a new method, based on Empirical Orthogonal Functions (EOF) during the calibration period 1961–2018, in order to reconstruct the climate indicator for temperature in Sweden for the full 1860–2020 period of available observations. The new method delivers results in good overall agreement with the reference method (i.e. arithmetic mean from selected stations in the reference network). Discrepancies are found prior to 1900, primarily related to the reduced number of active stations: the robustness of the indicator estimation is assessed by an ensemble computation with added random noise, which confirms that the ensemble spread increases significantly prior to 1880. The present study establishes that the 10-year running averaged temperature indicator rose from −1.03 °C in 1903 to +1.19 °C in 2010 (with respect to a mean value of 4.64 °C over the 1961–2018 calibration period), i.e. an increase by +2.22 °C in a century. The temperature difference between 1860 and 2020 was largest for winter (DJF) averages (+3 °C) and minimal for summer (+2 °C). The leading EOF patterns illustrate the spatial modes of variability for climate variability, with a predominantly homogeneous, mono-modal distribution for temperature. For precipitation, the first EOF pattern displays more pronounced regional features (maximum over the West coast), which is completed by a north-south seesaw pattern for the second EOF. We illustrate that EOF patterns calculated from observation data reproduce the major features of EOF calculated from GridClim, a gridded data-set over Sweden, for annual and seasonal averages. The leading EOF patterns vary significantly for seasonal averages (DJF, MAM, JJA, SON) for temperature. Finally, future developments of the EOF-method are discussed for calculating regional aggregated climate indicators, their relationship to synoptic circulation patterns and the benefits of homogenisation of observation series. The EOF-based method to compute a spatially aggregated indicator for precipitation is presented in a companion article (Sturm, 2024a). The code and data for this study is available on Zenodo (Sturm, 2024b). [ABSTRACT FROM AUTHOR]

The detection of water quality indicators such as Temperature, pH, Turbidity, Conductivity, and TDS involves five national standard methods. Chemically based measurement techniques may generate liquid residue, causing secondary pollution. The water quality monitoring and data analysis system can effectively address the issues that conventional methods require multiple pieces of equipment and repeated measurements. This paper analyzes the distribution characteristics of the historical data from five sensors at a specific time, displays them graphically in real time, and provides an early warning of exceeding the standard; It selects four water samples from different sections of the Li River, based on the national standard method, the average measurement errors of Temperature, PH, TDS, Conductivity and Turbidity are 0.98%, 2.23%, 2.92%, 3.05% and 3.98%.;It further uses the quartile method to analyze the outlier data over 100,000 records and five historical periods are selected. Experiment results show the system is relatively stable in measuring Temperature, PH and TDS, and the proportion of outlier is 0.42%, 0.84% and 1.24%. When Turbidity and Conductivity are measured, the proportion is 3.11% and 2.92%. In the experiment of using 7 methods to fill outlier, K nearest neighbor algorithm is better than others. The analysis of data trends, outliers, means, and extreme values assists in making decisions, such as updating and maintaining equipment, addressing extreme water quality situations, and enhancing regional water quality oversight. [ABSTRACT FROM AUTHOR]

The short‐wave infrared (SWIR) photoluminescence lifetimes of rare‐earth doped nanoparticles (RENPs) have found diverse applications in fundamental and applied research. Despite dazzling progress in the novel design and synthesis of RENPs with attractive optical properties, existing optical systems for SWIR photoluminescence lifetime imaging are still considerably restricted by inefficient photon detection, limited imaging speed, and low sensitivity. To overcome these challenges, SWIR photoluminescence lifetime imaging microscopy using an all‐optical streak camera (PLIMASC) is developed. Synergizing scanning optics and a high‐sensitivity InGaAs CMOS camera, SWIR‐PLIMASC has a 1D imaging speed of up to 138.9 kHz in the spectral range of 900–1700 nm, which quantifies the photoluminescence lifetime of RENPs in a single shot. A 2D photoluminescence lifetime map can be acquired by 1D scanning of the sample. To showcase the power of SWIR‐PLIMASC, a series of core‐shell RENPs with distinct SWIR photoluminescence lifetimes is synthesized. In particular, using Er3+‐doped RENPs, SWIR‐PLIMASC enables multiplexed anti‐counterfeiting. Leveraging Ho3+‐doped RENPs as temperature indicators, this system is applied to SWIR photoluminescence lifetime‐based thermometry. Opening up a new avenue for efficient SWIR photoluminescence lifetime mapping, this work is envisaged to contribute to advanced materials characterization, information science, and biomedicine. [ABSTRACT FROM AUTHOR]

We present analysis on two X-ray bright points observed over several hours during the recent solar minimum (2020 February 21 and 2020 September 12–13) with the Nuclear Spectroscopic Telescope Array (NuSTAR), a sensitive hard X-ray imaging spectrometer. This is so far the most detailed study of bright points in hard X-rays, emission which can be used to search for faint hot and/or non-thermal sources. We investigate the bright points' time evolution with NuSTAR, and in extreme ultraviolet (EUV) and soft X-rays with Solar Dynamic Observatory/Atmospheric Imaging Assembly (SDO/AIA) and Hinode/X-Ray Telescope. The variability in the X-ray and EUV time profiles is generally not well matched, with NuSTAR detecting spikes that do not appear in EUV. We find that, for the 2020 February bright point, the increased X-ray emission during these spikes is due to material heated to ∼ 4.2–4.4 MK (found from fitting the X-ray spectrum). The 2020 September bright point also shows spikes in the NuSTAR data with no corresponding EUV signature seen by SDO/AIA, though in this case, it was due to an increase in emission measure of material at ∼ 2.6 MK and not a significant temperature change. So, in both cases, the discrepancy is likely due to the different temperature sensitivity of the instruments, with the X-ray variability difficult to detect in EUV due to cooler ambient bright point emission dominating. No non-thermal emission is detected, so we determine upper limits finding that only a steep non-thermal component between 3 and 4 keV could provide the required heating whilst being consistent with a null detection in NuSTAR. [ABSTRACT FROM AUTHOR]

Breast thermography is a non-invasive, painless, affordable, and safer method of detecting breast abnormalities. Thermal imaging techniques used for detecting breast anomalies rely on precise breast boundary segmentation. However, the segmentation accuracy of the breast boundary region is affected by unclear boundaries, a low signal-to-noise ratio, and poor contrast of the thermal images. To mitigate this, this paper proposes a novel Distance-based Metrics and High-Temperature Region-based Adaptive Thresholding (DM-HTRAT) method for breast boundary region segmentation and dissecting left and right breasts precisely. In the first section, the Upper Region Boundary (URB) and the intersection point of the breast are segmented using the Distance-based Metrics (DM) method. In the second section, a High-Temperature Region-based Adaptive Thresholding (HTRAT) method is used to segment the Lower Region Boundary (LRB). The result of the segmentation is analysed both quantitatively and qualitatively, also it is compared with the state-of-the-art methods. The proposed method has a significantly better accuracy of 96.5% than the other methods. This segmented image is then fed into the abnormality detection system developed via the asymmetrical analysis of segmented breast boundary regions. The proposed DM-HTRAT-based breast boundary segmentation is robust in segmenting all types of breast thermal images and aids in the more reliable and effective detection of breast abnormalities. [ABSTRACT FROM AUTHOR]

In order to study the effects of relaxation characteristics of asphalt binders on its low-temperature performance, beam bending relaxation test was conducted through dynamic thermomechanical analyzer (DMA) at low temperatures. The relaxation characteristics of four asphalt binders were further evaluated by relaxation rate and relaxation time. In addition, the low temperature performance of asphalt binders was evaluated by bending beam rheometer (BBR) and single notch beam bending (SENB) tests. The correlation between the relaxation characteristics of asphalt binders and their low-temperature cracking resistance was evaluated based on Person's correlation coefficient and Spearman rank correlation coefficient. The results showed that the lower the temperature is, the worse was the relaxation performance of asphalt binders. Meanwhile, there was an excellent correlation between the relaxation rates and the low temperature property indexes. However, the relaxation time presented a poor correlation with low-temperature performance indexes. The maximum displacement of asphalt binders during fracture process and λ at the corresponding temperature showed a desired correlation with the relaxation performance indexes. Therefore, the relaxation characteristic indexes can be further utilized to investigate the low-temperature performance of asphalt binders. [ABSTRACT FROM AUTHOR]

The article introduces the Human Library, a non-profit initiative where individuals share their stories to challenge stereotypes and promote empathy. It also discusses the Future Library in Norway, which plants trees to create a collection of unread books to be published in 2114. Guidelines for physicians responding to in-flight medical emergencies are provided, emphasizing the importance of checking medical equipment and providing proper care to passengers. The text showcases works of authors from diverse backgrounds and stresses the significance of accurate medical record-keeping in healthcare. [Extracted from the article]

A unique End-of-Life (EOL) Deep Space View Test (DSVT) was performed on 27 November 2021 for the Advanced Microwave Sounding Unit-A (AMSU-A) and the Microwave Humidity Sounder (MHS) onboard the first EUMETSAT MetOp-A satellite in the deorbiting process. The purpose of this test is to recalibrate the antenna sidelobe, to derive antenna emission, and to quantify the in-orbit asymmetric scan biases of AMSU-A and MHS to, ultimately, improve Near Real-Time (NRT) products for MetOp-B and -C and the entire Fundamental Climate Data Records (FCDR). In this study, MetOp-A AMSU-A and MHS EOL DSVT data on 27 November 2021 have been analyzed. The deep space scene antenna temperatures were first applied for the antenna pattern correction; then, the antenna reflector channel emissivity values were derived from the corrected temperatures. For the MHS, the observed scan-angle-dependent brightness temperatures (BTs) for all channels were well behaved after the antenna pattern correction, except for channel 1. The derived antenna reflector emissivity values from this test are 0.0016, 0.0036, 0.0036, and 0.0019 for channels 1, 3, 4, and 5, respectively. For AMSU-A, the deep space view counts were not homogeneous during the test period, exhibiting large variations in the along-track and cross-track directions, mainly due to the instrument temperature's rapid change during the test period. The large relative noise in the deep space view observations negatively impacted the data quality and limits the value of this test. The large relative noise may contribute to the different emissivity values derived from the same frequency for channels 9 to 14. We also found unexpected scan-angle-dependent BT after antenna pattern correction for quasi-vertical (QV) channels 1 and 2 when compared to the emission model. Further investigation using a simulation confirmed that channels 1 and 2 are QV channels, as designed. [ABSTRACT FROM AUTHOR]

Determining egg freshness is critical for ensuring food safety and security and as such, different methods have been evaluated and implemented to accurately measure and predict it. In this study, a portable near-infrared (NIR) instrument combined with chemometrics was used to monitor and predict the storage time of eggs under two storage conditions—room temperature (RT) and cold (CT) storage—from two production systems: cage and free-range. A total of 700 egg samples were analyzed, using principal component analysis (PCA) and partial least squares (PLS) regression to analyze the NIR spectra. The PCA score plot did not show any clear separation between egg samples from the two production systems; however, some egg samples were grouped according to storage conditions. The cross-validation statistics for predicting storage time were as follows: for cage and RT eggs, the coefficient of determination in cross validation (R2CV) was 0.67, with a standard error in cross-validation (SECV) of 7.64 days and residual predictive deviation (RPD) of 1.8; for CT cage eggs, R2CV of 0.84, SECV of 5.38 days and RPD of 3.2; for CT free-range eggs, R2CV of 0.83, SECV of 5.52 days and RPD of 3.2; and for RT free-range eggs, R2CV of 0.82, SECV of 5.61 days, and RPD of 3.0. This study demonstrated that NIR spectroscopy can predict storage time non-destructively in intact egg samples. Even though the results of the present study are promising, further research is still needed to further extend these results to other production systems, as well as to explore the potential of this technique to predict other egg quality parameters associated with freshness. [ABSTRACT FROM AUTHOR]

Temperature as an important indicator of climate change, accurate temperature prediction has important guidance and application value for agricultural production, energy management and disaster warning. Based on the advantages of CEEMDAN model in effectively extracting the time–frequency characteristics of nonlinear and nonsmooth signals, BO algorithm in optimizing the objective function within a limited number of iterations, and BiLSTM model in revealing the connection between the current data, the previous data and the future data, a monthly average temperature prediction model based on CEEMDAN–BO–BiLSTM is established. A CEEMDAN–BO–BiLSTM-based monthly average temperature prediction model is developed and applied to the prediction of monthly average temperature in Jinan City, Shandong Province. The results show that the constructed monthly mean temperature prediction model based on CEEMDAN–BO–BiLSTM is feasible; the constructed CEEMDAN–BO–BiLSTM model has an average absolute error of 1.17, a root mean square error of 1.43, an average absolute percentage error of 0.31%, which is better than CEEMDAN–BiLSTM, EMD–BiLSTM, and BiLSTM models in terms of prediction accuracy and shows better adaptability; the constructed CEEMDAN–BO–BiLSTM model illustrates that the model is not over-modeled and adds complexity using Friedman's test and performance comparisons between model run speeds. The model provides insights for effective forecasting of monthly mean temperatures. [ABSTRACT FROM AUTHOR]

Between 2019 and 2020, the Gambier lagoon was instrumented over a period of 9 months with a large array of autonomous oceanographic instruments measuring temperature, pressure, and current. Two deployments were conducted from June to October 2019 (Leg1) and from late October 2019 to late February 2020 (Leg2). A total of 16 instrumented locations were spread across the lagoon and on the forereef. Physical parameters were measured to characterize the wave climate, tide and surges, lagoonal circulation, and spatial and vertical temperature variabilities. Those observations were part of the ANR-funded MANA project (2017–2022) and its derivatives that were aimed at improving knowledge of processes influencing the spat collection of Pinctada margaritifera oysters that are used for black pearl farming and production. This dataset was a prerequisite for the development of a high-resolution biophysical model on the Gambier lagoon that is aimed at understanding the connectivity of oyster larvae (Bruyère et al., 2023a). The sampling strategy focused on the northern region of the Gambier lagoon and especially on the sub-lagoon of Rikitea, which is a prime spat collection site. The dataset was post processed, quality controlled, and is archived in a dedicated repository with a permanent DOI via the SEANOE marine data platform (10.17882/94148, Andréfouët et al., 2023b). [ABSTRACT FROM AUTHOR]

The temperature measuring instrument was utilized to monitor the welding temperature field at designated points along steel rectangular hollow sections (RHSs) during welding. A total of 32 temperature monitoring points were established on the four surfaces of the RHS branch. Additionally, the welding process was simulated using finite element software to calculate the temperature distribution. The calculated temperature results were then compared with the experimental results obtained from the temperature measuring instrument. The relative errors between the numerical simulation and the experimental temperature results remained within 10%, indicating a reasonable agreement between the two. Once the temperature field was determined, it was used as an input load to calculate the welding residual stress. The longitudinal and transverse residual stresses were analyzed for two paths on the four surfaces of the RHS-to-RHS Y-shaped connection branch. By analyzing the residual stresses, it is possible to evaluate the structural integrity and performance of the welded RHS connection. The analysis process in this paper is crucial for ensuring the safety and reliability of tubular steel structure projects. [ABSTRACT FROM AUTHOR]

Whether brain temperature noninvasively extracted by magnetic resonance imaging has a role in identifying brain changes in the later phases of mild to moderate traumatic brain injury (TBI) is not known. This prospective study aimed to evaluate if TBI patients in subacute and chronic phases had altered brain temperature measured by whole-brain magnetic resonance spectroscopic imaging (WB-MRSI) and if the measurable brain temperature had any relationship with cognitive function scores. WB-MRSI was performed on eight TBI patients and fifteen age- and sex-matched control subjects. Brain temperature (T) was extracted from the brain's major metabolites and compared between the two groups. The T of the patients was tested for correlation with cognitive function test scores. The results showed significantly lower brain temperature in the TBI patients (p < 0.05). Brain temperature derived from N-acetylaspartate (TNAA) strongly correlated with the 2 s paced auditory serial addition test (PASAT-2s) score (p < 0.05). The observation of lower brain temperature in TBI patients may be due to decreased metabolic activity resulting from glucose and oxygen depletion. The correlation of brain temperature with PASAT-2s may imply that noninvasive brain temperature may become a noninvasive index reflecting cognitive performance. [ABSTRACT FROM AUTHOR]

We present a methodology to estimate quantitatively the area and depth of horizontal defects that generate heat in non-destructive tests such as burst vibrothermography or inductive thermography, without previous knowledge of the shape of the heat source. The method is based on extracting the temporal evolution of the temperature at the centre of the heated region, together with the thermogram obtained at the end of the excitation. The temperature displayed in this thermogram is averaged in circumferences concentric with the centre of the heated region to obtain an averaged radial profile which is fitted, together with the temporal evolution of the temperature, to a circular heat source model. By fitting synthetic data corresponding to rectangular heat sources with added noise, we analyse the accuracy of the method to retrieve the area and depth of the heat source for different depths and aspect ratios. Experimental results show that the method is able to estimate the area and depth of heat sources with aspect ratios below 1/1.5 with accuracy of about 10%. [ABSTRACT FROM AUTHOR]