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Focusing on the issue of thermal deformation in dry hobbing machine tools, the mechanisms of temperature change and the characteristics of temperature rise are thoroughly investigated. By analyzing heat generation through the energy conversion of various heterogeneous forms, including electrical, mechanical, and hydraulic energy, a comprehensive heat transfer model is developed to elucidate the complex thermal processes within the dry hobbing machine tool. The temperature at critical points of the machine tool during the dry hobbing of automotive gears is measured using a combination of infrared thermal imaging and online sensor technology. Experimental data are processed using Python to generate the machine tool's temperature rise curve. Based on this analysis, the temperature rise characteristics of the dry hobbing machine tool are further explored. The findings provide valuable insights for controlling thermal deformation and designing thermal balance systems for dry hobbing machine tools. [ABSTRACT FROM AUTHOR]

Infrared thermography techniques have proven to be very effective for assessing the fatigue limits of metallic materials with obvious temperature variations. But for some materials, it has been shown that the temperature variation is very limited, and the accuracy of infrared thermographic techniques is not verified. In this study, the fatigue properties of a high-strength steel (SAE52100) were evaluated with traditional fatigue-loading techniques and infrared thermographic methods. The traditional fatigue experiments were loaded at a frequency of 80 Hz with a stress ratio of R = −1, and the fatigue limit at the fatigue lifetime of N = 107 cycles was about 800 MPa. Besides, three additional specimens were loaded with step-by-step increasing stress-loading amplitude, where the maximum temperature increments and temperature distribution were recorded via infrared thermographic techniques. The infrared detections revealed that the maximum value of the temperature increase was only about 1 °C. The fatigue limit was first evaluated based on the maximum temperature variation, then the prediction was refined based on fatigue intrinsic dissipation. The fatigue limits predicted with maximum temperature variation were shown to be 841 MPa, 772 MPa, and 787 MPa, respectively, while the fatigue limits predicted based on fatigue intrinsic dissipation were 793 MPa, 791 MPa, and 789 MPa. Finally, an FEM simulation of temperature variation during fatigue loading was implemented to verify the experimental results. This study provides a solid foundation for the applications of infrared thermography techniques for materials with lower energy dissipations. [ABSTRACT FROM AUTHOR]

This study assessed the impact of various temperature indices, including mean temperature (MT), diurnal temperature range (DTR), and temperature changes between neighboring days (TCN) on hospitalization rates for cardiovascular system diseases among residents of Zhangye City, a typical western city in China. The Quasi-Poisson generalized additive regression model (GAM) in conjunction with a distributed lag nonlinear model (DLNM) was applied to estimate the association of temperature indices with CVD hospitalization rates in Zhangye City during the periods of 2015–2021. The exposure–response relationship and relative risk were discussed and stratified analyses by age and gender were conducted. We found that the hospitalization rates of cardiovascular disease (CVD) patients in Zhangye City was significantly related to different temperature indicators (MT, DTR, TCN). Both low and high MT, DTR, and TCN increased the risk of cardiovascular disease (CVD) among residents. Besides, different demographic populations exhibited distinct sensitivities to temperature conditions. Relevant authorities should devise corresponding preventive and control measures to protect vulnerable populations. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology 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.)

Air pollution caused by fine particles known as PM2.5 is a significant health concern worldwide, contributing to illnesses like asthma, heart disease, and lung cancer. To address this issue, this study focused on improving air purification systems using negative ions, which can attach to these harmful particles and help remove them from the air. This paper developed a novel mathematical model based on linear differential equations to study how PM2.5 particles interact with negative ions, making it easier to design more effective purification systems. The proposed model was validated in a small, controlled space, using common urban pollutants such as cigarette smoke, incense, coal, and gasoline. These tests were conducted at different temperatures and under two levels of ion generation. The results showed that the system could remove over  99 %  of PM2.5 particles in five minutes when temperatures were low or moderate. However, at higher temperatures, the system's performance dropped significantly. This research goes beyond earlier studies by examining how temperature affects the process, which had not been fully explored before. Furthermore, this approach aligns with global sustainability goals by promoting public health, reducing healthcare costs, and providing scalable solutions for sustainable urban living. [ABSTRACT FROM AUTHOR]

With the large-scale application of electrochemical energy storage, the safety of energy storage prefabricated cabin has become increasingly prominent. The study of the differences in energy storage prefabricated cabin fires under different thermal runaway positions in the energy storage prefabricated cabin can help to design more effective monitoring and fire extinguishing systems, and to improve the safety performance of the energy storage prefabricated cabin. Therefore, it is of great significance to simulate and study the change rule of smoke dispersion and temperature evolution in energy storage prefabricated cabin under different thermal runaway positions. Based on direct numerical simulation and vortex simulation, a numerical model of lithium iron phosphate energy storage prefabricated cabin based on the size of the actual energy storage prefabricated cabin is studied, and the t2 model which is more in line with the development of the fire situation compared with the stable fire model, and investigated the change rule of the smoke dispersion and temperature inside the prefabricated cabin by simulating the fire situation with different thermal runaway positions. The simulation results demonstrate that smoke displays distinct dynamic behaviors depending on the thermal runaway positions within the energy storage prefabricated cabin. When thermal runaway positions occur closer to the bottom, smoke exhibits swifter movement and the cabin fills up in a shorter time. Additionally, as the thermal runaway positions above 1.85 meters approach the top, accompanied by significant temperature fluctuations. Notably, there is a noticeable amplification in the temperature disparity along the horizontal axis of the energy storage prefabricated cabin. Moreover, the design scheme of the fire extinguishing system for a standard energy storage prefabricated cabin with a rated capacity of 1.2 MW ·h is analyzed. This perfluorohexane fire extinguishing system, with a sprinkler intensity of 20 L/(min ·m2), a sprinkler angle of 120°and a particle size of 50 μm, can successfully controls fires and mitigates fire damage. The research results in the article can provide theoretical guidance for the distributed deployment strategy in energy storage prefabricated cabin and fire safety design of monitoring and warning devices.

The variation of temperature in the geomagnetic relative recording room can cause deviations in the relative recording data, thereby affecting the geomagnetic baseline value. This article uses observation data of annual and daily temperature differences in relative recording rooms from 40 geomagnetic reference stations in China from 2021 to 2023, and analyzes the relationship between the construction of relative recording rooms at each station and temperature changes based on the data results. The research results show that about 70% of the total statistics are stations have an annual temperature difference of less than 10℃ in the relative recording room, and about 85% of stations have a daily temperature difference of less than 0.3 ℃. The findings suggest that a well-insulated geomagnetic relative recording room has smaller impact on temperature. Fully underground recording rooms exhibit the best insulation performance, followed by the insulation effect of the semi underground type recording room. Conversely, fully above-ground structures have poorer insulation, although a thicker insulation layer can still meet regulatory requirements. In the construction or renovation of relative recording rooms, priority should be given to selecting a fully underground structure for geomagnetic stations with significant annual temperature changes. For semi-underground recording rooms or fully above-ground buildings, increasing the thickness of the insulation layer is recommended.

Abstract Background Climate change is driving increased extreme weather events that can impact ecology by moderating host–pathogen interactions. To date, few studies have explored how cold snaps affect disease prevalence and proliferation. Using the Daphnia magna–Ordospora colligata host-parasite system, a popular model system for environmentally transmitted diseases, the amplitude and duration of cold snaps were manipulated at four baseline temperatures, 10 days post-exposure, with O. colligata fitness recorded at the individual level. Results Cold snaps induced a fivefold increase or a threefold decrease in parasite burden relative to baseline temperature, with complex nuances and varied outcomes resulting from different treatment combinations. Both amplitude and duration can interact with the baseline temperature highlighting the complexity and baseline dependence of cold snaps. Furthermore, parasite fitness, i.e., infection prevalence and burden, were simultaneously altered in opposite directions in the same cold snap treatment. Conclusions We found that cold snaps can yield complicated outcomes that are unique from other types of temperature variation (for example, heatwaves). These results underpin the challenges and complexity in understanding and predicting how climate and extreme weather may alter disease under global change.

Salt expansion and frost heave are the main diseases of salted frozen soil roadbeds. Salt swelling and frost heave disease are closely related to the salted soil water–salt migration, temperature variation, and salt crystallization amount change. This article establishes a coupled model of water, heat, and salt fields based on the capillary model and the unfrozen water characteristic curve. The study shows that the different initial moisture contents have minimal effects on the location of soil salt migration and aggregation. The different initial salt concentrations have a substantial effect on the soil water–salt migration aggregation position; when the concentration of sodium sulfate increases, different from chloride saline soils, the position of the freezing front fluctuates up and down over time. The water–salt migration and aggregation are smaller in the closed condition, where they are reduced by 38% and 20%, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Progress in Earthquake Sciences is the property of China Earthquake Administration, Institute of Geophysics 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.)

Background: Climate change is driving increased extreme weather events that can impact ecology by moderating host–pathogen interactions. To date, few studies have explored how cold snaps affect disease prevalence and proliferation. Using the Daphnia magna–Ordospora colligata host-parasite system, a popular model system for environmentally transmitted diseases, the amplitude and duration of cold snaps were manipulated at four baseline temperatures, 10 days post-exposure, with O. colligata fitness recorded at the individual level. Results: Cold snaps induced a fivefold increase or a threefold decrease in parasite burden relative to baseline temperature, with complex nuances and varied outcomes resulting from different treatment combinations. Both amplitude and duration can interact with the baseline temperature highlighting the complexity and baseline dependence of cold snaps. Furthermore, parasite fitness, i.e., infection prevalence and burden, were simultaneously altered in opposite directions in the same cold snap treatment. Conclusions: We found that cold snaps can yield complicated outcomes that are unique from other types of temperature variation (for example, heatwaves). These results underpin the challenges and complexity in understanding and predicting how climate and extreme weather may alter disease under global change. [ABSTRACT FROM AUTHOR]

This study investigates the effects of a back plate preheating assistance system and deep rolling (DR) on axial force and tunnel defects during friction stir welding (FSW). Different preheating configurations—advancing side (AS), retreating side (RS), and both sides—were examined to evaluate their impact on axial force reduction, temperature distribution, and defect minimization. Axial force measurements were taken using a dynamometer, and temperature histories were recorded with a thermal camera. The results demonstrate that a preheating temperature of 200 °C is optimal, reducing axial force by 30.24% and enhancing material flow. This temperature also facilitated deeper tool penetration, especially when preheating was applied to both sides. Preheating on the AS resulted in the smallest tunnel defects, reducing defect size by 80.15% on the RS and 96.91% on the AS compared to the non-preheated condition. While DR further reduced tunnel defects, its effectiveness was limited by the proximity of defects to the surface. These findings offer significant insights for improving the FSW process. [ABSTRACT FROM AUTHOR]

During the operational process of natural gas gathering and transmission pipelines, the formation of hydrates is highly probable, leading to uncontrolled movement and aggregation of hydrates. The continuous migration and accumulation of hydrates further contribute to the obstruction of natural gas pipelines, resulting in production reduction, shutdowns, and pressure build-ups. Consequently, a cascade of risks is prone to occur. To address this issue, this study focuses on the operational process of natural gas gathering and transmission pipelines, where a comprehensive framework is established. This framework includes theoretical models for pipeline temperature distribution, pipeline pressure distribution, multiphase flow within the pipeline, hydrate blockage, and numerical solution methods. By analyzing the influence of inlet temperature, inlet pressure, and terminal pressure on hydrate formation within the pipeline, the sensitivity patterns of hydrate blockage risks are derived. The research indicates that reducing inlet pressure and terminal pressure could lead to a decreased maximum hydrate formation rate, potentially mitigating pipeline blockage during natural gas transportation. Furthermore, an increase in inlet temperature and terminal pressure, and a decrease in inlet pressure, results in a displacement of the most probable location for hydrate blockage towards the terminal station. However, it is crucial to note that operating under low-pressure conditions significantly elevates energy consumption within the gathering system, contradicting the operational goal of energy efficiency and reduction of energy consumption. Consequently, for high-pressure gathering pipelines, measures such as raising the inlet temperature or employing inhibitors, electrical heat tracing, and thermal insulation should be adopted to prevent hydrate formation during natural gas transportation. Moreover, considering abnormal conditions such as gas well production and pipeline network shutdowns, which could potentially trigger hydrate formation, the installation of methanol injection connectors remains necessary to ensure production safety. [ABSTRACT FROM AUTHOR]

Enhanced geothermal systems (EGSs) are expected to be one of the most promising methods of supplying energy to meet the world's increasing energy demand. However, little attention has been paid to the influence of the number of production wells on the heat extraction performance of an EGS. A series of numerical simulations is organized in this work with three cases: Case 1 (one production well), Case 2 (two production wells), and Case 3 (three production wells). The results indicate that a slight temperature difference exists among the three simulation cases at the planes X-Y (Z = 0) and Y-Z (X = 0), while Case 1 ensures a greater cooling area, and the more production wells, the smaller the cooling area during the heat extraction in plane X-Z (Y = 0). In addition, the continuous injection of cooling water from the injection well and its arrival at different reference points enable the temperature at each point to declining with a variable amplitude of variation. This work also sets an efficiency (ef) to investigate the temperature variation in the EGS, where Case 1 exhibits a similar variation as Case 2, which is also similar to Case 3. It is hoped that this work will play a guiding role in EGS-related exploration and exploitation. [ABSTRACT FROM AUTHOR]

Summary: In this study, the effect of short‐term storage at different temperatures (0, 4 and −8 °C) on the quality of Antarctic krill was investigated using the main quality indicators as a reference, combined with electronic nose and untargeted metabolomics. Antarctic krill stored at lower temperatures (−8 °C) were of better quality and had a flavour similar to that of the original Antarctic krill. Metabolomics analyses showed that differential metabolites (DMS) were more abundant in Antarctic krill at higher temperatures (4 °C), with sixty‐five metabolites having reduced expression and forty‐five metabolites having increased expression; Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that amino acid metabolism and nucleotide metabolism pathways were the Five DMS, including α‐ketoglutarate, glutamate, succinate, sucrose and glutarate, can be used as potential biomarkers to monitor quality changes during short‐term storage of Antarctic krill. In addition, the association between quality indicators and differential metabolites remains to be explored. [ABSTRACT FROM AUTHOR]

Terahertz (THz) spectroscopy has demonstrated significant potential for substance detection due to its low destructiveness and due to the abundance of molecular fingerprint absorption signatures that it contains. However, there is limited research on the fingerprint detection of substances at different temperatures. Here, we propose a THz metamaterial slit array sensor that exploits localized surface plasmons to enhance the electric field within the slit. The transmission peak frequency can be modulated via temperature adjustments. This method enables the detection of molecular absorption characteristics at multiple spectral frequency points, thereby achieving a specific and highly sensitive detection of characteristic analyte fingerprint spectra. Additionally, the sensor supports the detection of substances at multiple temperatures and sensitively identifies changes in their absorption properties as a function of temperature. Our research has employed temperature variation to achieve a highly sensitive and specific detection of trace analytes, offering a new solution for THz molecular detection. [ABSTRACT FROM AUTHOR]

IntroductionEpidemiological evidence suggests cerebrovascular disease (CVD) incidence is correlated to meteorological conditions. However, research on the primary meteorological factors influencing the incidence of CVD and their influence thresholds in low-latitude mountainous regions remains insufficient. We aimed to investigate the association between meteorological conditions and CVD occurrence in Guizhou province.MethodsUtilizing daily incidence cases for CVD alongside concurrent meteorological data from four microclimate representative stations in Guizhou Province during 2021-2022, we firstly performed random forest and decision tree analysis to identify the significant meteorological factors influencing the incidence of CVD, and then we applied distributed lag non-linear model (DLNM) to assess the effect of meteorological factors on CVD incidence.ResultsCritical meteorological factors associated with CVD incidence include diurnal temperature range (DTR), temperature change between neighboring days (TCN), diurnal pressure range (DPR), pressure change between neighboring days (PCN), and minimum temperature. The risk of CVD incidence markedly increased with narrow DTR, positive TCN, and colder conditions. The thresholds of minimum temperature and TCN droped with the decrease of annual average temperature in microclimate zone. In the middle subtropical region of Jiangkou, the northern subtropical region of Xishui, and the warm temperate region of Shuicheng, there was a risk of CVD when the minimum temperature falled below 12.2°C, 10.7°C, and 6.7°C, respectively. When TCN exceeded the critical threshold (0.2°C in Shuicheng, 0.3°C in Xishui, and 0.4°C in Jiangkou and Ceheng), the risk of CVD incidence increased linearly. DPR and PCN displayed varied thresholds across different microclimate without consistent patterns. DPR in middle subtropical region of Jiangkou and warm temperate region of Shuicheng played a protective role, while the risk of the disease increased linearly when DPR was lower than 3.2 hPa and 2.7 hPa in south subtropical region of Ceheng and north subtropical region of Xishui, respectively. The short-term effects within 5 days with small DTR and narrow positive TCN were more obvious. The thresholds and lag times of other meteorological environmental factors remained indistinct in the four microclimate zones.DiscussionOur findings delineated the common characteristics of the effect on the incidence of CVD of meteorological environments in various microclimate zones, and clarified the influence of minimum temperature and TCN exhibited spatial heterogeneity, Which may be assistance for meteorological risk forecasting in CVD prevention and control.

Lithium-ion batteries are essential to modern technology, requiring accurate estimation of the state of charge (SOC) for optimal performance. Traditional methods such as Coulomb Counting (CC) are ineffective in the face of temperature variations, leading to inaccuracies in SOC estimation, which in turn cause obvious deformation of hysteresis curves. To address this, this paper introduces a novel method called Polynomial Fit State of Charge (FPSOC), for effective SOC estimation. This method incorporates a fifth-degree polynomial fitting that accounts for a wide range of temperature variations (from -10 °°C to +80 °°C), a feature that, according to the authors, has not been offered by all previously published methods. A series of simulation tests using the MATLAB/Simulink tool are conducted under various temperature profiles to evaluate the effectiveness of the FPSOC method. The results demonstrate the notable superiority of the FPSOC model compared to the CC method, with a significantly reduced RMSE of only 0.93 % compared to 6.77 % of the CC model. Particularly effective at low SOC levels (30 %), the FPSOC model demonstrates precision up to six times higher compared to the CC model. Additionally, when evaluated against other recent SOC estimation techniques such as CM, RLSF, EKF, DST, BBDST, ASMO, LPM_H, LSTM-SA Group A and B, and baseline ECM-ID, The FPSOC method proves extremely accurate, with the lowest average error under different temperature conditions.

Salt expansion and frost heave are the main diseases of salted frozen soil roadbeds. Salt swelling and frost heave disease are closely related to the salted soil water–salt migration, temperature variation, and salt crystallization amount change. This article establishes a coupled model of water, heat, and salt fields based on the capillary model and the unfrozen water characteristic curve. The study shows that the different initial moisture contents have minimal effects on the location of soil salt migration and aggregation. The different initial salt concentrations have a substantial effect on the soil water–salt migration aggregation position; when the concentration of sodium sulfate increases, different from chloride saline soils, the position of the freezing front fluctuates up and down over time. The water–salt migration and aggregation are smaller in the closed condition, where they are reduced by 38% and 20%, respectively.

The revolutionary future of proton-exchanging membrane fuel cells (PEMFC) has recently garnered a great deal of excitement, as has their green energy source. Maximizing the production of electricity from PEMFC is crucial to maintaining effectiveness. This research article thoroughly analyzes a research study using a strategy known as MPPT, or maximum power point tracking that uses the neuro-fuzzy method for PEMFC operating under diverse temperatures, pressures, and joining constraints. The neuro-fuzzy controller cleverly regulates the point of maximal operation of a hydrogen fuel cell system, allowing exact adherence to the highest possible power scale. According to simulation results, the neuro-fuzzy MPPT technique improves PEMFC validity across a wide range of operating scenarios.

Octreotide is the first synthetic peptide hormone, consisting of eight amino acids, that mimics the activity of somatostatin, a natural hormone in the body. During the past decades, advanced instrumentation and crystallographic software have established X-Ray Powder Diffraction (XRPD) as a valuable tool for extracting structural information from biological macromolecules. The latter was demonstrated by the successful structural determination of octreotide at a remarkably high d-spacing resolution (1.87 Å) (PDB code: 6vc1). This study focuses on the response of octreotide to different humidity levels and temperatures, with a particular focus on the stability of the polycrystalline sample. XRPD measurements were accomplished employing an Anton Paar MHC-trans humidity-temperature chamber installed within a laboratory X’Pert Pro diffractometer (Malvern Panalytical). The chamber is employed to control and maintain precise humidity and temperature levels of samples during XRPD data collection. Pawley analysis of the collected data sets revealed that the octreotide polycrystalline sample is remarkably stable, and no structural transitions were observed. The compound retains its orthorhombic symmetry (space group: P212121, a = 18.57744(4) Å, b = 30.17338(6) Å, c = 39.70590(9) Å, d ~ 2.35 Å). However, a characteristic structural evolution in terms of lattice parameters and volume of the unit cell is reported mainly upon controlled relative humidity variation. In addition, an improvement in the signal-to-noise ratio in the XRPD data under a cycle of dehydration/rehydration is reported. These results underline the importance of considering the impact of environmental factors, such as humidity and temperature, in the context of structure-based drug design, thereby contributing to the development of more effective and stable pharmaceutical products.

Octreotide is the first synthetic peptide hormone, consisting of eight amino acids, that mimics the activity of somatostatin, a natural hormone in the body. During the past decades, advanced instrumentation and crystallographic software have established X-Ray Powder Diffraction (XRPD) as a valuable tool for extracting structural information from biological macromolecules. The latter was demonstrated by the successful structural determination of octreotide at a remarkably high d-spacing resolution (1.87 Å) (PDB code: 6vc1). This study focuses on the response of octreotide to different humidity levels and temperatures, with a particular focus on the stability of the polycrystalline sample. XRPD measurements were accomplished employing an Anton Paar MHC-trans humidity-temperature chamber installed within a laboratory X'Pert Pro diffractometer (Malvern Panalytical). The chamber is employed to control and maintain precise humidity and temperature levels of samples during XRPD data collection. Pawley analysis of the collected data sets revealed that the octreotide polycrystalline sample is remarkably stable, and no structural transitions were observed. The compound retains its orthorhombic symmetry (space group: P212121, a = 18.57744(4) Å, b = 30.17338(6) Å, c = 39.70590(9) Å, d ~ 2.35 Å). However, a characteristic structural evolution in terms of lattice parameters and volume of the unit cell is reported mainly upon controlled relative humidity variation. In addition, an improvement in the signal-to-noise ratio in the XRPD data under a cycle of dehydration/rehydration is reported. These results underline the importance of considering the impact of environmental factors, such as humidity and temperature, in the context of structure-based drug design, thereby contributing to the development of more effective and stable pharmaceutical products. [ABSTRACT FROM AUTHOR]

Heat shock proteins (HSPs) are a group of molecular chaperones that are crucial for the proper folding and assembly of proteins and the protection of somatic and germ cells from damage caused by temperature changes. However, the localization and seasonal variation patterns of HSPs in stallions' testes remain unclear. Thus, we investigated the expression and seasonal variations in the localization of HSP60 and HSP90 in the testes of stallions. Testes from nine Thoroughbred stallions collected following castration during the non-breeding season (NBS) and two different environmental temperature conditions (normal temperature, NT; March-May and hot temperature, HT; June-August) during the breeding season (BS) were used. Testis tissues were subjected to Reverse transcription-quantitative polymerase chain reaction, Western Blot (WB) analysis and immunofluorescence (IF) assay. The results revealed that the relative abundance of HSP60 and HSP90 mRNA transcripts was significantly upregulated under NT and HT conditions during BS compared with that during NBS conditions. The WB analysis showed that the relative intensity of protein bands was significantly higher in NT and HT conditions during the BS than that of those during the NBS. Immunofluorescence assay showed localization of HSP60 in the cytoplasm of the Leydig cells during both seasons. HSP90 primarily showed immunostaining in undifferentiated spermatogonia and primary spermatocytes in NT and HT conditions and was additionally expressed in the spermatids during the NBS. The spermatogenesis was not monitored in the present study; however, findings of this study suggest that the localization of HSP60 and HSP90 varies in different seasons depending on the temperature, providing insight into the potential mechanisms influencing spermatogenesis during breeding and non-breeding seasons in stallions. [ABSTRACT FROM AUTHOR]

Simple Summary: The seabass, Dicentrarchus labrax (D. labrax) is a gonochoristic species that shows clearly sex-linked growth. In fact, females grow faster and reach larger sizes than males. The expression of acid-sensing ion channels (ASICs) 2 and 4 (ASIC2 and ASIC4) in the gonads of Dicentrarchus labrax subjected to water temperature increased from 15 °C to 20 °C during the gonadal development. Water temperature during gonadal develepment modified both gonadal differentiation and growth in Dicentrarchus labrax. The incidence of intratesticular oocytes highlights intersexual cases, strengthening the possibility that water temperature could modulate sex differentiation in D. labrax. The results gathered in the study suggest the possible role of acid-sensing ion channels in gonad differentiation and gamete development in D. labrax. In this study, the expression and implication of acid-sensing ion channels 2 and 4 (ASIC2 and ASIC4) in the gonadal sex differentiation of Dicentrarchus labrax (D. labrax), subjected to increasing water temperatures during gonadal development, were evaluated. Two groups were selected: a control group (CG), in which the average water temperature was maintained at 15 °C and increased to 20 °C in 20 days until weaning; and an experimental group (EG), in which the water temperature was retained at 15 °C for 60 days; thereafter, the temperature was increased daily by 0.5 °C until it reached 20 °C up to the weaning time. Ten fish from the CG and 13 fish from the EG were sampled randomly on the 335th day after hatching (dph). A higher percentage of gonad differentiation in ovaries rather than in testes was observed in the EG compared to the CG (p = 0.01). ASIC2 and ASIC4 were detected for the first time in D. labrax ovaries by indirect immunofluorescence. Both ASIC2 and ASIC4 were expressed in previtellogenic oocytes of ovaries and in scattered cells within some testes, and were most likely intratesticular previtellogenic oocytes in both the CG and EG groups. The CG group showed a higher expression of ASIC4 than the EG cohort (p < 0.05). The results gathered in this study revealed the capacity of water temperature to influence both gonadal differentiation and growth in this gonochoristic fish species, and suggests the possible role of ASIC2 and ASIC4 in gonad differentiation and gamete development in D. labrax. [ABSTRACT FROM AUTHOR]

In this paper, the firing process and structural failure behavior of outdoor mechanical car parks are innovatively investigated under diverse conditions, leveraging fire experiments, FDS fire simulation, and finite element simulation. The fire experiments reveal the intricate interplay between flame spread and airflow, highlighting the enhanced risk of fire propagation among adjacent spaces. The temperature profile, mirroring the fire's lifecycle, is delineated into three distinct stages: initial growth, full development, and eventual decay. Notably, full-scale fire simulation in FDS validates the experimental outcomes, underscoring the scalability and reliability of our scaled-down experiments. Furthermore, finite element simulations offer a profound understanding of structural safety in various parking spaces during a fire. Critically, the susceptibility of columns to failure underscores the imperative need for enhanced fire prevention measures in column design, representing a significant advancement in fire protection engineering. [ABSTRACT FROM AUTHOR]

The disconnector fault in gas insulated switchgear (GIS) is commonly caused by the combined effects of mechanical, thermal, and electrical factors. Throughout the progression from defect development to a severe fault, various signals, including abnormal vibration, temperature changes, and partial discharge, are generated. The simultaneous measurement and analysis of multi-parameter information pertaining to the GIS disconnector are crucial for accurately determining its operating condition. This study focuses on simulating typical defects in a 220 kV GIS disconnector to investigate the evolution patterns of vibration signals, temperature variations, and partial discharge signals under different contact states. The aim is to establish the correlation between these signals and the condition of the GIS disconnector. Additionally, the study proposes a comprehensive evaluation method for GIS disconnector by incorporating the health index theory and an improved analytic hierarchy process. The proposed method is subsequently applied to practical GIS, demonstrating consistency between the identified fault and the analysis results obtained through the multi-parameter comprehensive evaluation approach. Overall, this research introduces a highly feasible new method for the detection of GIS disconnector conditions.

Manufacturing of valves generally uses brass alloy materials and is carried out using a forging process. In this research, the aim is to determine the effect of variations in heating temperature in the valve manufacturing process on the hardness value, microstructure, and shape changes that occur. This research method uses this research method, using an experimental method with temperature variations tested of (300˚, 400˚, and 500 ˚Celsius) with an unchanged compressive force and brass raw material with specifications Cu = 57%. Results of observations that occurred namely Hardness Testing, the lower the heating temperature, the higher the resulting hardness value, which is 69 HRb, 66 HRb, and 59 HRb. When the shape changes, the higher the temperature, the more flash you get, and the lighter the forging force on the forging tool. In the microstructure, as a result of temperature differences, each grain structure characteristic will be different, increasing temperature and forging pressure will change the grain structure.

To accurately identify the deterioration degree of the surfaces of stone cultural relics and determine how various diseases affect each other, the deterioration research combined with infrared thermography and ultrasonic technology was used to effectively detect the deterioration and current situation of the internal structure of rocks and investigate the different states of limestone specimens. The temperature change laws of surface heating and cooling were examined using the distribution of heat and the conduction phenomenon. Infrared thermography was applied to detect the surface deterioration of stone cultural relics and disease development. Results show the limestone specimen surface's temperature change rule during heating and cooling. During the aging process of the limestone specimen, the original disease area deteriorates faster and more seriously than the fresh and unweathered area. The 3D map of the temperature distribution processed by infrared thermography can be used to quickly determine the disease area and semiquantitatively measure the degree of disease development, which is essential to the protection of cultural relics. The obtained conclusions in this study can provide the reference for the protect of stone cultural relics. [ABSTRACT FROM AUTHOR]

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

The rapid advancement of integrated circuit (IC) technology has revolutionized various industries, but it has also introduced challenges in detecting faulty ICs. Traditional testing methods often rely on manual inspection or complex equipment, resulting in time-consuming and costly processes. In this work, a novel approach is proposed which uses a thermal camera and an Internet of Things (IoT) physical device, namely a Raspberry PI microcontroller, for the detection of faulty and non-faulty ICs. Further, a deep learning algorithm, namely You Only Look Once (YOLO), is coded inside the Raspberry PI controller using Python programming software to detect faulty ICs efficiently and accurately. Also, the various images of faulty and non-faulty ICs are used to train the algorithm and once the algorithm is trained, the thermal camera along with the Raspberry PI microcontroller is used for the real-time detection of faulty ICs and the YOLO algorithm analyzes the thermal images to identify regions with abnormal temperature patterns, indicating potential faults. The proposed approach offers several advantages over traditional methods, including increased efficiency and improved accuracy. [ABSTRACT FROM AUTHOR]

In this study, urea-doped titanium dioxide (urea-TiO2) nanoparticles were synthesized through an in situ heat-assisted sol–gel technique using titanium (IV) isopropoxide as the precursor for titanium dioxide and urea as a nitrogen source. The nanoparticles were calcined at 300, 500, and 700 °C to study the effect of the calcination temperature on their function as self-cleaning material. The nanoparticles were characterized using a scanning electron microscope and a transmission electron microscope for morphology, X-ray diffraction, Raman spectroscopy, and Fourier transformed infrared spectroscopy for structure, UV–Vis, and photoluminescence spectroscopy for optical analysis. The self-cleaning study was carried out by letting samples degrade methylene blue and Rhodamine-B under UV irradiation. The morphological analysis reveals particle size distribution with more disparity at higher calcination temperatures. At lower calcination temperatures, the dopant caused high clustering of particles, keeping them linked together in muddy form and layers. Structural analysis showed that the particles were nanostructured with average crystallite sizes ranging from 2.35 to 16.13 nm and phase transformation from anatase to rutile after calcining at 700 °C. The nitrogen presence created a lattice disorder in the TiO2 structure, and the impact of higher calcination temperature on the nanoparticles further shifted the band toward a higher wavenumber under FTIR analysis. The optical bandgap reduced from 3.29 eV at 300 °C to 3.09 eV at 700 °C. The determined values of the rate constant from the photodegradation test showed that the highest rate was obtained at 700 °C, indicating enhanced self-cleaning functionality with an increase in calcination temperature of urea-TiO2. [ABSTRACT FROM AUTHOR]

In order to improve the drilling performance of polycrystalline diamond compact bit and prolong its service life during drilling in coal rock under the action of wind cycle, the theoretical calculation model of polycrystalline diamond compact bit cutting teeth temperature was derived based on the theory of tribology and heat transfer. The theoretical temperature field of polycrystalline diamond compact bit-cutting teeth was analyzed. Using the joint simulation of EDEM–FLUENT, the temperature variation law of polycrystalline diamond compact bit cutting teeth under the thermo-fluid–solid coupling was analyzed to verify the validity of the theoretical calculation model of polycrystalline diamond compact bit cutting teeth temperature. By building a rotary drilling test platform and conducting drilling experiments on polycrystalline diamond compact bit under different drilling parameters respectively, the correctness of the theoretical model and the simulation data were verified. In addition, a response surface analysis model was established to study the influence of different drilling parameters on the polycrystalline diamond compact bit cutting teeth temperature during drilling in coal rock. The analysis results show that the influence degree of various drilling parameters on the polycrystalline diamond compact bit cutting teeth temperature from large to small is drilling pressure, drilling speed, coal rock properties, and wind speed. Compared with the working condition without wind cycle, the drilling efficiency of polycrystalline diamond compact bit can be increased by 14.38% and the temperature is reduced by 8% when it drills in coal. The drilling efficiency of polycrystalline diamond compact bit can be increased by 17.79% and the temperature is reduced by 10.5% when it drills in coal gangue. [ABSTRACT FROM AUTHOR]

Abstract In ecology, there is an emerging emphasis on the importance of capturing temperature variation at relevant scales. Temperature fluctuates continuously in nature but is sampled at discrete time points, so how often should ecologists measure temperature to capture its variation? A recent development in thermal ecology is the use of spectral analysis of temperature time series to determine at what frequencies important temperature fluctuations occur. Building on this, I borrow from signal processing theory to show how continuous thermal regimes can be effectively reconstructed from discrete, regular, measurements, and provide a rule of thumb for designing temperature sampling schemes that capture ecologically relevant temporal variation. I introduce sinc interpolation, a method for reconstructing continuous waveforms from discrete samples. Furthermore, I introduce the Nyquist–Shannon sampling theorem, which states that continuous complex waveforms can be perfectly sinc‐interpolated from discrete, regular, samples if sampling intervals are sufficiently short. To demonstrate the power of these concepts in an ecological context, I apply them to several published high‐resolved (15‐min intervals) temperature time series used for ecological predictions of insect development times. First, I use spectral analysis to illuminate the fluctuation frequencies that dominate the temperature data. Second, I employ sinc interpolation over artificially thinned versions of the temperature time series. Third, I compare interpolated temperatures with observed temperatures to demonstrate the Nyquist–Shannon sampling theorem and its relation to spectral analysis. Last, I repeat the ecological predictions using sinc‐interpolated temperatures. Daily, and less frequent, fluctuations dominated the variation in all the temperature time series. Therefore, in accordance with the Nyquist–Shannon sampling theorem, 11‐h measurement intervals consistently retrieved most 15‐min temperature variation. Moreover, previous predictions of insect development times were improved by using sinc‐interpolated, rather than averaged, temperatures. By identifying the highest frequency at which ecologically (or otherwise) relevant temperature fluctuations occur and applying the Nyquist–Shannon sampling theorem, ecologists (or others doing climate‐related research) can use sinc interpolation to produce remarkably accurate continuous thermal regimes from sparse but regular temperature measurements. Surprisingly, these concepts have remained largely unexplored in ecology despite their applicability, not least in thermal ecology.

Kai Yue,1,2 Chao Yang,1 Yu You,1,2 Xueying Wang,3 Xinxin Zhang1 1School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, People’s Republic of China; 2Shunde Graduate School of University of Science and Technology Beijing, Shunde, Guangdong Province, 528399, People’s Republic of China; 3School of Chemistry and Chemical Engineering, University of Jinan, Jinan, Shandong Province, 250022, People’s Republic of ChinaCorrespondence: Kai Yue, Email yuekai@ustb.edu.cnBackground: A good understanding of the adhesion behaviors of the nanocarriers in microvessels in chemo-hyperthermia synergistic therapy is conducive to nanocarrier design for targeted drug delivery.Methods: In this study, we constructed an artificial blood vessel system using gelatins with a complete endothelial monolayer formed on the inner vessel wall. The numbers of adhered NPs under different conditions were measured, as well as the interaction forces between the arginine–glycine–aspartic acid (RGD) ligands and endothelial cells.Results: The experimental results on the adhesion of ligand–coated nanoparticles (NPs) with different sizes and morphologies in the blood vessel verified that the gelatin-based artificial vessel possessed good cytocompatibility and mechanical properties, which are suitable for the investigation on NP adhesion characteristics in microvessels. When the temperature deviated from 37 °C, an increase or decrease in temperature resulted in a decrease in the number of adhered NPs, but the margination probability of NP adhesion increased at high temperatures due to the enhanced Brownian movement and flow disturbance. It is found that the effect of cooling was less than that of heating according to the observed changes in cell morphology and a decrease in cell activity under the static and perfusion culture conditions within the temperature range of 25 °C– 43 °C. Furthermore, the measurement results of change in the RGD ligand-cell interaction with temperature showed good agreement with those in the number of adhered NPs.Conclusion: The Findings suggest that designing ligands that can bind to the receptor and are least susceptible to temperature variation can be an effective means to enhance drug retention.Keywords: artificial vessel, drug delivery, nanoparticle, temperature variation, particle–wall adhesion

Lubrication is a crucial tool for industrial maintenance. By reducing friction between components, it also reduces wear on equipment. Industrial lubricants have specific properties and can operate efficiently within their operating temperature range. The aim of this study is therefore to forecast the temperature variation of lubrication oil using simple exponential smoothing. In this paper, we discuss one of the most popular forecasting methods in engineering and mechanical fields. The exponential smoothing method has been successful due to the quality of the results it presents. The present contribution aims to model the temperature variation of lubricating oil in a mechanical contact by the simple exponential smoothing method. The analysis and examination of the set of results made it possible to compare the smoothing models for different values of α and to choose the model closest to the actual temperature curve, the choice of the closest model serves to calculate the optimization criteria for the forecast; this method consists in choosing the α minimizing. The forecast results obtained by the SES model with α=0.9 are judged very satisfactory, and they prove the dominance of the SES model. [ABSTRACT FROM AUTHOR]

The oil film separates the shaft-bearing system to reduce the frictional force of contact surfaces with large temperature variations owing to thermal conduction. Multiple impact factors seriously affected the lubrication behavior of the bearing during actual working process. An applicable model regarding the lubrication analysis of a hydrodynamic-static hybrid bearing with deep-shallow chambers is proposed and validated with published literature. The lubrication behavior includes film pressure, load capacity, bearing stiffness and flow rate is numerically calculated with centered finite difference method by solving the Reynolds equation. The influence of film thickness and working temperature are considered, over a range of eccentricity ratio. Moreover, the temperature variation caused by thermal conduction is analyzed in details. To investigate the influence of thermal conduction on the lubrication behavior, the results show that the load capacity, bearing stiffness, friction power, and flow power significantly decline with the consideration of thermal conduction. This study proposes an accurate model that is helpful for the design of hydrodynamicstatic hybrid bearings with deep-shallow chambers under low rotational speed, heavy load, and high temperature conditions. [ABSTRACT FROM AUTHOR]

Terahertz (THz) spectroscopy has demonstrated significant potential for substance detection due to its low destructiveness and due to the abundance of molecular fingerprint absorption signatures that it contains. However, there is limited research on the fingerprint detection of substances at different temperatures. Here, we propose a THz metamaterial slit array sensor that exploits localized surface plasmons to enhance the electric field within the slit. The transmission peak frequency can be modulated via temperature adjustments. This method enables the detection of molecular absorption characteristics at multiple spectral frequency points, thereby achieving a specific and highly sensitive detection of characteristic analyte fingerprint spectra. Additionally, the sensor supports the detection of substances at multiple temperatures and sensitively identifies changes in their absorption properties as a function of temperature. Our research has employed temperature variation to achieve a highly sensitive and specific detection of trace analytes, offering a new solution for THz molecular detection.

Enhanced geothermal systems (EGSs) are expected to be one of the most promising methods of supplying energy to meet the world’s increasing energy demand. However, little attention has been paid to the influence of the number of production wells on the heat extraction performance of an EGS. A series of numerical simulations is organized in this work with three cases: Case 1 (one production well), Case 2 (two production wells), and Case 3 (three production wells). The results indicate that a slight temperature difference exists among the three simulation cases at the planes X-Y (Z = 0) and Y-Z (X = 0), while Case 1 ensures a greater cooling area, and the more production wells, the smaller the cooling area during the heat extraction in plane X-Z (Y = 0). In addition, the continuous injection of cooling water from the injection well and its arrival at different reference points enable the temperature at each point to declining with a variable amplitude of variation. This work also sets an efficiency (ef) to investigate the temperature variation in the EGS, where Case 1 exhibits a similar variation as Case 2, which is also similar to Case 3. It is hoped that this work will play a guiding role in EGS-related exploration and exploitation.

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In ecology, there is an emerging emphasis on the importance of capturing temperature variation at relevant scales. Temperature fluctuates continuously in nature but is sampled at discrete time points, so how often should ecologists measure temperature to capture its variation? A recent development in thermal ecology is the use of spectral analysis of temperature time series to determine at what frequencies important temperature fluctuations occur. Building on this, I borrow from signal processing theory to show how continuous thermal regimes can be effectively reconstructed from discrete, regular, measurements, and provide a rule of thumb for designing temperature sampling schemes that capture ecologically relevant temporal variation.I introduce sinc interpolation, a method for reconstructing continuous waveforms from discrete samples. Furthermore, I introduce the Nyquist–Shannon sampling theorem, which states that continuous complex waveforms can be perfectly sinc‐interpolated from discrete, regular, samples if sampling intervals are sufficiently short. To demonstrate the power of these concepts in an ecological context, I apply them to several published high‐resolved (15‐min intervals) temperature time series used for ecological predictions of insect development times. First, I use spectral analysis to illuminate the fluctuation frequencies that dominate the temperature data. Second, I employ sinc interpolation over artificially thinned versions of the temperature time series. Third, I compare interpolated temperatures with observed temperatures to demonstrate the Nyquist–Shannon sampling theorem and its relation to spectral analysis. Last, I repeat the ecological predictions using sinc‐interpolated temperatures.Daily, and less frequent, fluctuations dominated the variation in all the temperature time series. Therefore, in accordance with the Nyquist–Shannon sampling theorem, 11‐h measurement intervals consistently retrieved most 15‐min temperature variation. Moreover, previous predictions of insect development times were improved by using sinc‐interpolated, rather than averaged, temperatures.By identifying the highest frequency at which ecologically (or otherwise) relevant temperature fluctuations occur and applying the Nyquist–Shannon sampling theorem, ecologists (or others doing climate‐related research) can use sinc interpolation to produce remarkably accurate continuous thermal regimes from sparse but regular temperature measurements. Surprisingly, these concepts have remained largely unexplored in ecology despite their applicability, not least in thermal ecology. [ABSTRACT FROM AUTHOR]