Genital arousal and responsive desire among women with and without sexual interest/arousal disorder symptoms

BACKGROUND

Models depicting sexual desire as responsive to sexual arousal may be particularly apt for women experiencing arousal or desire difficulties, and the degree to which arousal triggers desire may depend on the relationship context and desire target and timing-yet, these associations have not been directly tested among women with and without sexual interest/arousal disorder (SIAD).

AIM

To assess the role of SIAD status and relationship satisfaction in the associations between genital arousal and 4 types of responsive desire.

METHODS

One hundred women (n = 27 meeting diagnostic criteria for SIAD) in romantic relationships with men viewed a sexual film (pleasurable intimate depiction of oral sex and penile-vaginal intercourse) while their genital arousal was recorded via vaginal photoplethysmography (n = 63) or thermal imaging of the labia (n = 37). Partner and solitary desire was assessed immediately before and after the film (immediate desire) and 3 days later (delayed desire).

OUTCOMES

Outcomes consisted of genital response (z scored by method) and associations between genital response and responsive sexual desire.

RESULTS

The key difference between women with and without SIAD was not in their ability to experience genital arousal but in how their genital responses translated to responsive sexual desire. Women with SIAD actually exhibited greater genital arousal than unaffected women. Associations between genital arousal and desire were significant only for women with SIAD and depended on relationship satisfaction and desire type. For women with SIAD with low relationship satisfaction, higher arousal predicted lower immediate desire for a partner; for those with high relationship satisfaction, arousal was either positively related (vaginal photoplethysmography) or unrelated (thermal imaging of the labia) to immediate desire for a partner. Associations with other desire types were not significant.

CLINICAL IMPLICATIONS

Patterns of genital arousal and partner-specific responsive desire among women affected with SIAD were indicative of an avoidance model in response to heightened genital arousal, unless relationship satisfaction was high; attending to genital arousal sensations could be a means of triggering sexual desire for women with SIAD who are satisfied in their relationships.

STRENGTHS AND LIMITATIONS

This is one of the first sexual psychophysiologic studies to connect relationship factors to patterns of sexual response. The differing arousal assessment procedures and lack of official diagnosis may have attenuated results. The homogeneous sample and in-person session requirement limit generalizability.

CONCLUSION

When compared with unaffected women, women affected by SIAD may exhibit stronger arousal responses with sufficiently incentivized sexual stimuli, and the connection between their genital arousal and responsive desire for their partners may be stronger and more dependent on relationship context.

Heritable variation in thermal profiles is associated with reproductive success in the world's largest bird

Organisms inhabiting extreme thermal environments, such as desert birds, have evolved spectacular adaptations to thermoregulate during hot and cold conditions. However, our knowledge of selection for thermoregulation and the potential for evolutionary responses is limited, particularly for large organisms experiencing extreme temperature fluctuations. Here we use thermal imaging to quantify selection and genetic variation in thermoregulation in ostriches (Struthio camelus), the world's largest bird species that is experiencing increasingly volatile temperatures. We found that females who are better at regulating their head temperatures ("thermoregulatory capacity") had higher egg-laying rates under hotter conditions. Thermoregulatory capacity was both heritable and showed signatures of local adaptation: females originating from more unpredictable climates were better at regulating their head temperatures in response to temperature fluctuations. Together these results reveal that past and present evolutionary processes have shaped genetic variation in thermoregulatory capacity, which appears to protect critical organs, such as the brain, from extreme temperatures during reproduction.

Biopolymeric 3D printed implantable scaffolds as a potential adjuvant treatment for acute post-operative pain management

BACKGROUND

Pain is characterized as a major symptom induced by tissue damage occurring from surgical procedures, whose potency is being experienced subjectively, while current pain relief strategies are not always efficient in providing individualized treatment. 3D printed implantable devices hold the potential to offer a precise and customized medicinal approach, targeting both tissue engineering and drug delivery.

RESEARCH DESIGN AND METHODS

Polycaprolactone (PCL) and PCL - chitosan (CS) composite scaffolds loaded with procaine (PRC) were fabricated by bioprinting. Geometrical features including dimensions, pattern, and infill of the scaffolds were mathematically optimized and digitally determined, aiming at developing structurally uniform 3D printed models. Printability studies based on thermal imaging of the bioprinting system were performed, and physicochemical, surface, and mechanical attributes of the extruded scaffolds were evaluated. The release rate of PRC was examined at different time intervals up to 1 week.

RESULTS

Physicochemical stability and mechanical integrity of the scaffolds were studied, while in vitro drug release studies revealed that CS contributes to the sustained release dynamic of PRC.

CONCLUSIONS

The printing extrusion process was capable of developing implantable devices for a local and sustained delivery of PRC as a 7-day adjuvant regimen in post-operative pain management.

Inside-out: Synergising leaf biochemical traits with stomatal-regulated water fluxes to enhance transpiration modelling during abiotic stress

As the global climate continues to change, plants will increasingly experience abiotic stress(es). Stomata on leaf surfaces are the gatekeepers to plant interiors, regulating gaseous exchanges that are crucial for both photosynthesis and outward water release. To optimise future crop productivity, accurate modelling of how stomata govern plant-environment interactions will be crucial. Here, we synergise optical and thermal imaging data to improve modelled transpiration estimates during water and/or nutrient stress (where leaf N is reduced). By utilising hyperspectral data and partial least squares regression analysis of six plant traits and fluxes in wheat (Triticum aestivum), we develop a new spectral vegetation index; the Combined Nitrogen and Drought Index (CNDI), which can be used to detect both water stress and/or nitrogen deficiency. Upon full stomatal closure during drought, CNDI shows a strong relationship with leaf water content (r2 = 0.70), with confounding changes in leaf biochemistry. By incorporating CNDI transformed with a sigmoid function into thermal-based transpiration modelling, we have increased the accuracy of modelling water fluxes during abiotic stress. These findings demonstrate the potential of using combined optical and thermal remote sensing-based modelling approaches to dynamically model water fluxes to improve both agricultural water usage and yields.

Use of thermal drone in detection and assessment of larval mass temperature in decomposed rabbit carcasses

Manual ground searches and cadaver dogs are traditional methods for locating remains, but they can be time- and resource-intensive, resulting in the decomposition of bodies and delay in victim identification. Therefore, thermal imaging has been proposed as a potentially useful tool for detecting remains based on their temperature. This study investigated the potential of a novel search technique of thermal drones to detect surface remains through the detection of maggot mass temperatures. Two trials were carried out at Selangor, Malaysia, each utilizing 12 healthy male Oryctolagus cuniculus European white rabbits and DJI Matrice 300 RTK drone China, equipped with a thermal camera; Zenmuse H20T to record the thermal imaging footage of the carcasses at various heights (15, 30, 60-100 m) for 14 days for each trial. Our results demonstrated that the larval masses and corresponding heat emissions were at their largest during the active decay stage; therefore, all the carcasses were observable in thermal images on day 5 and remained until day 7. Statistical analyses showed that (1) no statistically significant differences in thermal images between clothed and unclothed subjects (p > 0.05); (2) 15 m above ground level was proven to be the optimal height, as it showed the greatest contrast between the carcass heat signature and the background (p < 0.005). Our data suggested the potential window of detection of thermal signatures was detectable up to 7 days post-deposition. This could be an important guideline for the search and recovery teams for operational implementation in this tropical region.

AI-assisted image analysis and physiological validation for progressive drought detection in a diverse panel of Gossypium hirsutum L

Introduction

Drought detection, spanning from early stress to severe conditions, plays a crucial role in maintaining productivity, facilitating recovery, and preventing plant mortality. While handheld thermal cameras have been widely employed to track changes in leaf water content and stomatal conductance, research on thermal image classification remains limited due mainly to low resolution and blurry images produced by handheld cameras.

Methods

In this study, we introduce a computer vision pipeline to enhance the significance of leaf-level thermal images across 27 distinct cotton genotypes cultivated in a greenhouse under progressive drought conditions. Our approach involved employing a customized software pipeline to process raw thermal images, generating leaf masks, and extracting a range of statistically relevant thermal features (e.g., min and max temperature, median value, quartiles, etc.). These features were then utilized to develop machine learning algorithms capable of assessing leaf hydration status and distinguishing between well-watered (WW) and dry-down (DD) conditions.

Results

Two different classifiers were trained to predict the plant treatment-random forest and multilayer perceptron neural networks-finding 75% and 78% accuracy in the treatment prediction, respectively. Furthermore, we evaluated the predicted versus true labels based on classic physiological indicators of drought in plants, including volumetric soil water content, leaf water potential, and chlorophyll a fluorescence, to provide more insights and possible explanations about the classification outputs.

Discussion

Interestingly, mislabeled leaves mostly exhibited notable responses in fluorescence, water uptake from the soil, and/or leaf hydration status. Our findings emphasize the potential of AI-assisted thermal image analysis in enhancing the informative value of common heterogeneous datasets for drought detection. This application suggests widening the experimental settings to be used with deep learning models, designing future investigations into the genotypic variation in plant drought response and potential optimization of water management in agricultural settings.

Utilization of Infrared Thermography in Assessing Thermal Responses of Farm Animals under Heat Stress

Heat stress is a condition that can affect the health, performance, and welfare of farm animals. The perception of thermal stress leads to the activation of the autonomic nervous system to start a series of physiological and behavioral mechanisms to restore thermostability. One of these mechanisms is vasodilation of peripheral blood vessels to increase heat loss through the skin. Due to this aspect, infrared thermography has been suggested as a method to assess the thermal state of animals and predict rectal temperature values noninvasively. However, it is important to consider that predicting rectal temperature is challenging, and its association with IRT is not always a direct linear relationship. The present review aims to analyze the neurobiological response associated with heat stress and how thermal imaging in different thermal windows can be used to recognize heat stress in farmed ungulates.

The Effects of 2 Different Soft Tissue Mobilization Techniques on Delayed Onset Muscle Soreness in Male Recreational Athletes: A Single-Blinded Randomized Controlled Trial

CONTEXT

Soft tissue mobilization is frequently employed for delayed onset muscle soreness (DOMS) management. Foam roller and percussive massage are 2 popular soft tissue mobilization methods preferred by various professionals. However, their effects on DOMS symptoms are controversial and there are no studies comparing these 2 methods. The aim of the present study was to compare the acute effects of soft tissue mobilization with a foam roller or a percussive massage device on DOMS in young male recreational athletes.

DESIGN

A parallel, single-blinded, randomized controlled trial.

METHODS

Thirty-six participants (median [interquartile range 25/75]; age: 20.0 [19.3/21.0] y) were randomly allocated to percussive massage group (n = 12), foam roller group (n = 12), and control group (n = 12). First, a fatigue protocol targeting quadriceps femoris was performed. Then, participants received soft tissue mobilization with foam roller/percussive massage or rested for 10 minutes according to their groups. Pain and fatigue were evaluated by a visual analog scale, and the skin surface temperature of over the quadriceps femoris was measured with thermal camera imaging. Evaluations were performed at baseline, following fatigue protocol, at 24th hour, and at 48th hour. Changes from the baseline at 24th and 48th hours were compared between groups.

RESULTS

No significant between-group differences were observed at the assessments performed at 24th or 48th hour regarding the changes from baseline in pain (P value for 24th hour = .905, P value for 48th hour = .733), fatigue (P value for 24th hour = .895, P value for 48th hour = .606), or skin surface temperature measurements (P values for 24th hour = between .300 and .925, P values for 48th hour = between .311 and .750).

CONCLUSIONS

Soft tissue mobilizations applied with foam roller or percussive massage device do not seem to be superior to passive resting in alleviating DOMS symptoms in recreational athletes.

Rapid spatial assessment of leaf-absorbed irradiance

Image-based high-throughput phenotyping promises the rapid determination of functional traits in large plant populations. However, interpretation of some traits - such as those related to photosynthesis or transpiration rates - is only meaningful if the irradiance absorbed by the measured leaves is known, which can differ greatly between different parts of the same plant and within canopies. No feasible method currently exists to rapidly measure absorbed irradiance in three-dimensional plants and canopies. We developed a method and protocols to derive absorbed irradiance at any visible part of a canopy with a thermal camera, by fitting a leaf energy balance model to transient changes in leaf temperature. Leaves were exposed to short light pulses (30 s) that were not long enough to trigger stomatal opening but strong enough to induce transient changes in leaf temperature that was proportional to the absorbed irradiance. The method was successfully validated against point measurements of absorbed irradiance in plant species with relatively simple architecture (sweet pepper, cucumber, tomato, and lettuce). Once calibrated, the model was used to produce absorbed irradiance maps from thermograms. Our method opens new avenues for the interpretation of plant responses derived from imaging techniques and can be adapted to existing high-throughput phenotyping platforms.

Smartphone-based detection of COVID-19 and associated pneumonia using thermal imaging and a transfer learning algorithm

COVID-19-related pneumonia is typically diagnosed using chest x-ray or computed tomography images. However, these techniques can only be used in hospitals. In contrast, thermal cameras are portable, inexpensive devices that can be connected to smartphones. Thus, they can be used to detect and monitor medical conditions outside hospitals. Herein, a smartphone-based application using thermal images of a human back was developed for COVID-19 detection. Image analysis using a deep learning algorithm revealed a sensitivity and specificity of 88.7% and 92.3%, respectively. The findings support the future use of noninvasive thermal imaging in primary screening for COVID-19 and associated pneumonia.

Update on the Use of Infrared Thermography in the Early Detection of Diabetic Foot Complications: A Bibliographic Review

Foot lesions are among the most frequent causes of morbidity and disability in the diabetic population. Thus, the exploration of preventive control measures is vital for detecting early signs and symptoms of this disease. Infrared thermography is one of the complementary diagnostic tools available that has proven to be effective in the control of diabetic foot. The last review on this topic was published in 2015 and so, we conducted a bibliographic review of the main databases (PubMed, the Web of Science, Cochrane library, and Scopus) during the third quarter of 2023. We aimed to identify the effectiveness of infrared thermography as a diagnostic element in pre-ulcerous states in diabetic patients and to detect diabetic foot ulcer complications. We obtained a total of 1199 articles, 26 of which were finally included in the present review and published after 2013. After analyzing the use of infrared thermography in diabetic patients both with and without ulcers, as well as in healthy individuals, we concluded that is an effective tool for detecting early-stage ulcers in diabetic foot patients.

Evaluation of Non-Contact Device to Measure Body Temperature in Sheep

Non-contact devices have been used in the measurement of body temperature in livestock production as a tool for testing disease in different species. However, there are few studies about the variation and correlations in body temperature between rectal temperature (RT) and non-contact devices such as non-contact infrared thermometers (NCIT) and thermal imaging/infrared thermography (IRT). The objective of this work was to evaluate the accuracy of non-contact devices to measure the body temperature in sheep, considering six body regions and the possibility of implementing these systems in herd management. The experiment was carried out at the experimental farm of the Catholic University of Valencia, located in the municipality of Massanassa in July of 2021, with 72 dry manchega ewes, and we compared the rectal temperature with two types of non-contact infrared devices for the assessment of body temperature in healthy sheep. Except for the temperature taken by NCIT at the muzzle, the correlation between RT vs. NCIT or IRT showed a low significance or was difficult to use for practical flock management purposes. In addition, the variability between devices was high, which implies that measurements should be interpreted with caution in warm climates and open pens, such as most sheep farms in the Spanish Mediterranean area. The use of infrared cameras devices to assess body temperature may have a promising future, but in order to be widely applied as a routine management method on farms, the system needs to become cheaper, simpler in terms of measurements and quicker in terms of analyzing results.

Region-wise severity analysis of diabetic plantar foot thermograms

OBJECTIVES

Diabetic foot ulcers (DFU) can be avoided if symptoms of diabetic foot complications are detected early and treated promptly. Early detection requires regular examination, which might be limited for many reasons. To identify affected or potentially affected regions in the diabetic plantar foot, the region-wise severity of the plantar foot must be known.

METHODS

A novel thermal diabetic foot dataset of 104 subjects was developed that is suitable for Indian healthcare conditions. The entire plantar foot thermogram is divided into three parts, i.e., forefoot, midfoot, and hindfoot. The division of plantar foot is based on the prevalence of foot ulcers and the load on the foot. To classify the severity levels, conventional machine learning (CML) techniques like logistic regression, decision tree, KNN, SVM, random forest, etc., and convolutional neural networks (CNN), such as EfficientNetB1, VGG-16, VGG-19, AlexNet, InceptionV3, etc., were applied and compared for robust outcomes.

RESULTS

The study successfully developed a thermal diabetic foot dataset, allowing for effective classification of diabetic foot ulcer severity using the CML and CNN techniques. The comparison of different methods revealed variations in performance, with certain approaches outperforming others.

CONCLUSIONS

The region-based severity analysis offers valuable insights for targeted interventions and preventive measures, contributing to a comprehensive assessment of diabetic foot ulcer severity. Further research and development in these techniques can enhance the detection and management of diabetic foot complications, ultimately improving patient outcomes.

Comparison of Coupled Electrochemical and Thermal Modelling Strategies of 18650 Li-Ion Batteries in Finite Element Analysis-A Review

The specificities of temperature-dependent electrochemical modelling strategies of 18650 Li-ion batteries were investigated in pseudo-2D, 2D and 3D domains using finite element analysis. Emphasis was placed on exploring the challenges associated with the geometric representation of the batteries in each domain, as well as analysing the performance of coupled thermal-electrochemical models. The results of the simulations were compared with real reference measurements, where temperature data were collected using temperature sensors and a thermal camera. It was highlighted that the spiral geometry provides the most realistic results in terms of the temperature distribution, as its layered structure allows for a detailed realisation of the radial heat transfer within the cell. On the other hand, the 3D-lumped thermal model is able to recover the temperature distribution in the axial direction of the cell and to reveal the influence of the cell cap and the cell wall on the thermal behaviour of the cell. The effect of cooling is an important factor that can be introduced in the models as a boundary condition by heat convection or heat flux. It has been shown that both regulated and unregulated (i.e., natural) cooling conditions can be achieved using an appropriate choice of the rate and type of cooling applied.

How birds dissipate heat before, during and after flight

Animal flight uses metabolic energy at a higher rate than any other mode of locomotion. A relatively small proportion of the metabolic energy is converted into mechanical power; the remainder is given off as heat. Effective heat dissipation is necessary to avoid hyperthermia. In this study, we measured surface temperatures in lovebirds (Agapornis personatus) using infrared thermography and used heat transfer modelling to calculate heat dissipation by convection, radiation and conduction, before, during and after flight. The total non-evaporative rate of heat dissipation in flying birds was 12× higher than before flight and 19× higher than after flight. During flight, heat was largely dissipated by forced convection, via the exposed ventral wing areas, resulting in lower surface temperatures compared with birds at rest. When perched, both before and after exercise, the head and trunk were the main areas involved in dissipating heat. The surface temperature of the legs increased with flight duration and remained high on landing, suggesting that there was an increase in the flow of warmer blood to this region during and after flight. The methodology developed in this study to investigate how birds thermoregulate during flight could be used in future studies to assess the impact of climate change on the behavioural ecology of birds, particularly those species undertaking migratory flights.

Growth Light Quality Influences Leaf Surface Temperature by Regulating the Rate of Non-Photochemical Quenching Thermal Dissipation and Stomatal Conductance

Significant efforts have been made to optimise spectrum quality in indoor farming to maximise artificial light utilisation and reduce water loss. For such an improvement, green (G) light supplementation to a red-blue (RB) background was successfully employed in our previous studies to restrict both non-photochemical quenching (NPQ) and stomatal conductance (gs). At the same time, however, the downregulation of NPQ and gs had the opposite influence on leaf temperature (Tleaf). Thus, to determine which factor plays the most prominent role in Tleaf regulation and whether such a response is temporal or permanent, we investigated the correlation between NPQ and gs and, subsequently, Tleaf. To this end, we analysed tomato plants (Solanum lycopersicum L. cv. Malinowy Ozarowski) grown solely under monochromatic LED lamps (435, 520, or 662 nm; 80 µmol m-2 s-1) or a mixed RGB spectrum (1:1:1; 180 µmol m-2 s-1) and simultaneously measured gs and Tleaf with an infrared gas analyser and a thermocouple or an infrared thermal camera (FLIR) during thermal imaging analyses. The results showed that growth light quality significantly modifies Tleaf and that such a response is not temporal. Furthermore, we found that the actual adaxial leaf surface temperature of plants is more closely related to NPQ amplitude, while the temperature of the abaxial surface corresponds to gs.

Thermographic Changes following Short-Term High-Intensity Anaerobic Exercise

Current studies report thermographic changes following aerobic or resistance exercise but not short, vigorous anaerobic exercise. Therefore, we investigated body surface temperature changes using thermal imaging following a short session of anaerobic exercise. We studied three different regions of interest (ROIs): the legs, chest, and forehead. Thermal imaging for each participant was performed before and immediately after completing a Wingate anaerobic test and every minute during a 15 min recovery period. Immediately after the test, the maximum temperature was significantly higher in all ROIs (legs, p = 0.0323; chest, p = 0.0455; forehead, p = 0.0444) compared to pre-test values. During the recovery period, both legs showed a significant and continuous temperature increase (right leg, p = 0.0272; left leg, p = 0.0382), whereas a non-significant drop was noted in the chest and forehead temperatures. Additionally, participants with a lower anaerobic capacity exhibited a higher delta increase in surface leg temperature than participants with higher anaerobic capacities, with a minimal change in surface leg temperature. This is the first study to demonstrate body surface temperature changes following the Wingate anaerobic test. This temperature increase is attributed to the high anaerobic mechanical power outputs achieved by the leg muscles and the time taken for temperature reduction post-exercise.

Infrared thermography is a novel tool to assess small intestinal surface temperature in dogs undergoing laparotomy for foreign body obstruction

OBJECTIVE

To evaluate local temperature differences directly over and adjacent to small intestinal foreign body obstruction (FBO) using infrared thermography (IRT) in dogs.

ANIMALS

49 client-owned dogs were initially enrolled.

METHODS

In a prospective, clinical observational study, IRT was utilized to compare median small intestinal (SI) surface temperature differences at the site of FBO and segments oral and aboral before and after surgical resolution from April 24, 2019, to July 19, 2020. These differences were evaluated for correlation with canine acute patient physiologic and laboratory evaluation fast (APPLEfast) scoring, lactate, foreign body material (hard vs soft), and blood pressure.

RESULTS

There was not a significant surface temperature difference between SI segments at the site of FBO, oral or aboral. After resolution of obstruction, there was a significant decrease in median temperature directly over the FBO (2.4 °C; IQR, -2.55 to 10.6 °C; P = .0043). A decrease in surface temperature of the oral SI segment was appreciated with FBO due to hard material (-1.7 °C; IQR, -5.2 to 3.4 °C), whereas soft material had an increase in SI surface temperature oral to the FBO (+1.1 °C; IQR, 0.3 to 3.2 °C). This difference did not achieve significance (P = .08; Z = 1.75). No correlation was found between APPLEfast, lactate, or blood pressure and SI segment temperatures.

CLINICAL RELEVANCE

IRT may be useful diagnostic modality to identify changes in small intestinal surface temperature relating to FBO. Further evaluation is warranted to determine if IRT may be a clinically useful to evaluate intestinal perfusion.

Evidence of Xylella fastidiosa Infection and Associated Thermal Signatures in Southern Highbush Blueberry (Vaccinium corymbosum Interspecific Hybrids)

Xylella fastidiosa, a gram-negative bacterium vectored to plants via feeding of infected insects, causes a number of notorious plant diseases throughout the world, such as Pierce's disease (grapes), olive quick decline syndrome, and coffee leaf scorch. Detection of Xf in infected plants can be challenging because the early foliar disease symptoms are subtle and may be attributed to multiple minor physiological stresses and/or borderline nutrient deficiencies. Furthermore, Xf may reside within an infected plant for one or more growing seasons before traditional visible diagnostic disease symptoms emerge. Any method that can identify infection during the latent period or pre-diagnostic disease progress state could substantially improve the outcome of disease control interventions. Because Xf locally and gradually impairs water movement through infected plant stems and leaves over time, infected plants may not be able to effectively dissipate heat through transpiration-assisted cooling, and this heat signature may be an important pre-diagnostic disease trait. Here, we report on the association between thermal imaging, the early stages of Xf infection, and disease development in blueberry plants, and discuss the benefits and limitations of using thermal imaging to detect bacterial leaf scorch of blueberries.

Non-invasive assessment of positive affective state using infra-red thermography in rats

With recent increased focus on positive welfare in animal welfare science, there is demand for objective positive welfare indicators. It is unclear whether changes in body surface temperature can be used to non-invasively identify and quantify positive states in mammals. We recorded continuous measurements of tail surface temperature using infra-red thermography (IRT) and concurrent behavioural observations in male and female Wistar rats (Rattus norvegicus). If tail surface temperature can differentiate between positive and negative experiences, we expect a qualitatively different response compared to negative experiences. Three groups of rats were presented with increasing magnitudes of food rewards (neutral/none, one and three rewards). The rats were placed in an arena to which they were habituated and filmed for 30 s before and 30 min after exposure to different rewards. Tail temperature initially decreased from the pre-reward baseline and subsequently returned towards baseline temperature. The overall pattern of the change was the same as for rats subjected to negative stimuli in previous studies. Nevertheless, dynamic changes in tail temperature, specifically the rate of recovery and the behavioural response (exploration), differed between neutral and rewarded rats but failed to distinguish reward magnitude. Sex differences were found in both thermal and behavioural responses, unrelated to reward magnitudes. Female rats exhibited a greater initial response with a slower recovery than male rats, emphasising the value of using of both sexes in animal welfare research. This study improves our understanding of the effects of positive emotions induced by food reward on peripheral body temperature and behaviour.

Microscale Imaging of Thermal Conductivity Suppression at Grain Boundaries

Grain-boundary engineering is an effective strategy to tune the thermal conductivity of materials, leading to improved performance in thermoelectric, thermal-barrier coatings, and thermal management applications. Despite the central importance to thermal transport, a clear understanding of how grain boundaries modulate the microscale heat flow is missing, owing to the scarcity of local investigations. Here, thermal imaging of individual grain boundaries is demonstrated in thermoelectric SnTe via spatially resolved frequency-domain thermoreflectance. Measurements with microscale resolution reveal local suppressions in thermal conductivity at grain boundaries. Also, the grain-boundary thermal resistance - extracted by employing a Gibbs excess approach - is found to be correlated with the grain-boundary misorientation angle. Extracting thermal properties, including thermal boundary resistances, from microscale imaging can provide comprehensive understanding of how microstructure affects heat transport, crucially impacting the materials design of high-performance thermal-management and energy-conversion devices.

Assessment of the activity of secondary caries lesions with short-wavelength infrared, thermal, and optical coherence tomographic imaging

Significance: Leakage in the interfaces between restorative materials and tooth structure allows for fluid and bacterial acid infiltration, causing restoration failure due to secondary caries. Dentists spend more time replacing composite restorations than placing new ones. Previous in vitro and in vivo studies on enamel and root surfaces using shortwave-infrared (SWIR) and thermal imaging during dehydration with forced air have been promising for assessing lesion activity. Aim: We hypothesized that SWIR reflectance and thermal imaging methods can be used to monitor the activity of secondary caries lesions around composite restorations. The objective of this study was to employ these methods to measure the rate of fluid loss from lesions during dehydration with forced air to assess lesion activity. Approach: Sixty-three extracted human teeth with total of 109 suspected secondary lesions were examined using SWIR and thermal imaging during dehydration. The thickness of the highly mineralized transparent surface layer (TSL) at lesion interfaces indicative of lesion activity was measured by optical coherence tomography (OCT). Micro-computed tomography (MicroCT) was used to further confirm lesion severity and structure. OCT and MicroCT measurements of lesion structure, depth, and severity were correlated with fluid loss rates measured with SWIR reflectance and thermal imaging. Results: TSL thickness measured with OCT correlated with both SWIR reflectance and thermal measurements of rates of fluid loss ( p < 0.05 ). Increasing TSL thickness led to decreased permeability of lesions, potentially indicating full lesion arrest at TSL ≥ 70    μ m . SWIR performed better than thermal imaging for secondary lesion activity assessment, although both methods performed best on smooth surface lesions. Conclusions: Nondestructive SWIR reflectance and OCT imaging methods are promising for clinically monitoring the activity of secondary caries lesions.

Short-Term Thermal Effect of Continuous Ultrasound from 3 MHz to 1 and 0.5 W/cm2 Applied to Gastrocnemius Muscle

Continuous ultrasound is recognized for its thermal effect and use in the tissue repair process. However, there is controversy about its dosage and efficacy. This study used infrared thermography, a non-invasive technique, to measure the short-term thermal effect of 3 MHz continuous ultrasound vs. a placebo, referencing the intensity applied. It was a single-blind, randomized clinical trial of 60 healthy volunteers (19-24 years old) divided into three equal groups. Group 1:1 W/cm2 for 5 min; Group 2: 0.5 W/cm2 for 10 min; and Group 3: the placebo for 5 min. The temperature was recorded through five thermographic images per patient: pre- and post-application, 5, 10, and 15 min later. After statistical analysis, a more significant decrease in temperature (p<0.05 ) was observed in the placebo group compared with the remaining groups after the application of continuous ultrasound. Group 1 was the one that generated the highest significant thermal effect (p<0.001), with an increase of 3.05 °C at 15 min, compared with the other two groups. It is concluded that to generate a thermal effect in the muscle, intensities of ≥1 W/cm2 are required, since the dosage maintained a temperature increase for more than 5 min.

Terrain Characterization via Machine vs. Deep Learning Using Remote Sensing

Terrain traversability is critical for developing Go/No-Go maps for ground vehicles, which significantly impact a mission's success. To predict the mobility of terrain, one must understand the soil characteristics. In-situ measurements performed in the field are the current method of collecting this information, which is time-consuming, costly, and can be lethal for military operations. This paper investigates an alternative approach using thermal, multispectral, and hyperspectral remote sensing from an unmanned aerial vehicle (UAV) platform. Remotely sensed data combined with machine learning (linear, ridge, lasso, partial least squares (PLS), support vector machines (SVM), and k nearest neighbors (KNN)) and deep learning (multi-layer perceptron (MLP) and convolutional neural network (CNN)) are used to perform a comparative study to estimate the soil properties, such as the soil moisture and terrain strength, used to generate prediction maps of these terrain characteristics. This study found that deep learning outperformed machine learning. Specifically, a multi-layer perceptron performed the best for predicting the percent moisture content (R²/RMSE = 0.97/1.55) and the soil strength (in PSI), as measured by a cone penetrometer for the averaged 0-6" (CP06) (R²/RMSE = 0.95/67) and 0-12" depth (CP12) (R²/RMSE = 0.92/94). A Polaris MRZR vehicle was used to test the application of these prediction maps for mobility purposes, and correlations were observed between the CP06 and the rear wheel slip and the CP12 and the vehicle speed. Thus, this study demonstrates the potential of a more rapid, cost-efficient, and safer approach to predict terrain properties for mobility mapping using remote sensing data with machine and deep learning algorithms.

Camera Trap Methods and Drone Thermal Surveillance Provide Reliable, Comparable Density Estimates of Large, Free-Ranging Ungulates

Camera traps and drone surveys both leverage advancing technologies to study dynamic wildlife populations with little disturbance. Both techniques entail strengths and weaknesses, and common camera trap methods can be confounded by unrealistic assumptions and prerequisite conditions. We compared three methods to estimate the population density of white-tailed deer (Odocoileus virgnianus) in a section of Pilot Mountain State Park, NC, USA: (1) camera trapping using mark-resight ratios or (2) N-mixture modeling and (3) aerial thermal videography from a drone platform. All three methods yielded similar density estimates, suggesting that they converged on an accurate estimate. We also included environmental covariates in the N-mixture modeling to explore spatial habitat use, and we fit models for each season to understand temporal changes in population density. Deer occurred in greater densities on warmer, south-facing slopes in the autumn and winter and on cooler north-facing slopes and in areas with flatter terrain in the summer. Seasonal density estimates over two years suggested an annual cycle of higher densities in autumn and winter than in summer, indicating that the region may function as a refuge during the hunting season.

A Workflow for Studying the Stump-Socket Interface in Persons with Transtibial Amputation through 3D Thermographic Mapping

The design and fitting of prosthetic sockets can significantly affect the acceptance of an artificial limb by persons with lower limb amputations. Clinical fitting is typically an iterative process, which requires patients' feedback and professional assessment. When feedback is unreliable due to the patient's physical or psychological conditions, quantitative measures can support decision-making. Specifically, monitoring the skin temperature of the residual limb can provide valuable information regarding unwanted mechanical stresses and reduced vascularization, which can lead to inflammation, skin sores and ulcerations. Multiple 2D images to examine a real-life 3D limb can be cumbersome and might only offer a partial assessment of critical areas. To overcome these issues, we developed a workflow for integrating thermographic information on the 3D scan of a residual limb, with intrinsic reconstruction quality measures. Specifically, workflow allows us to calculate a 3D thermal map of the skin of the stump at rest and after walking, and summarize this information with a single 3D differential map. The workflow was tested on a person with transtibial amputation, with a reconstruction accuracy lower than 3 mm, which is adequate for socket adaptation. We expect the workflow to improve socket acceptance and patients' quality of life.

The detection of clandestine graves in an arid environment using thermal imaging deployed from an unmanned aerial vehicle

The Middle East is one of the world regions that has frequently suffered from armed conflicts that resulted in mass burials. However, the detection of clandestine graves in such an arid environment by deploying remote sensing payload on unmanned aerial vehicles (UAVs) has received little attention. The present study used a UAV equipped with a thermal sensor aimed at narrowing down the search area of possible gravesites in the arid climate of Kuwait. The enclosed research area, which includes both control and experimental mass graves, was imaged for 18 months. The variation in topsoil temperature and soil moisture between the graves and their surroundings was evaluated. The results of the analysis demonstrated the effectiveness of thermal imaging techniques in detecting heat produced from buried sheep carcasses and detecting the change in grave soil moisture for our research environment for 7 and 10 months, respectively. The buried animals significantly influenced the topsoil temperature (p = 0.044), while the height from which the images were captured had an insignificant effect on the measured temperature within the range tested (p = 0.985). Furthermore, there was a negative correlation (-0.359) between grave temperature and the calculated soil moisture. The results from these cost- and time-effective search methods presented in this study confirm their potential for the detection of burial sites in an arid environment.

The Development of a Cost-Effective Imaging Device Based on Thermographic Technology

Thermal vision-based devices are nowadays used in a number of industries, ranging from the automotive industry, surveillance, navigation, fire detection, and rescue missions to precision agriculture. This work describes the development of a low-cost imaging device based on thermographic technology. The proposed device uses a miniature microbolometer module, a 32-bit ARM microcontroller, and a high-accuracy ambient temperature sensor. The developed device is capable of enhancing RAW high dynamic thermal readings obtained from the sensor using a computationally efficient image enhancement algorithm and presenting its visual result on the integrated OLED display. The choice of microcontroller, rather than the alternative System on Chip (SoC), offers almost instantaneous power uptime and extremely low power consumption while providing real-time imaging of an environment. The implemented image enhancement algorithm employs the modified histogram equalization, where the ambient temperature sensor helps the algorithm enhance both background objects near ambient temperature and foreground objects (humans, animals, and other heat sources) that actively emit heat. The proposed imaging device was evaluated on a number of environmental scenarios using standard no-reference image quality measures and comparisons against the existing state-of-the-art enhancement algorithms. Qualitative results obtained from the survey of 11 subjects are also provided. The quantitative evaluations show that, on average, images acquired by the developed camera provide better perception quality in 75% of tested cases. According to qualitative evaluations, images acquired by the developed camera provide better perception quality in 69% of tested cases. The obtained results verify the usability of the developed low-cost device for a range of applications where thermal imaging is needed.

Using Thermal Imaging to Track Cellulitis

Background

Cellulitis is a common soft tissue infection and a major cause of morbidity. The diagnosis is based almost exclusively on clinical history and physical exam. To improve the diagnosis of cellulitis, we used a thermal camera to track how skin temperature of the affected area changed during a hospital stay for patients with cellulitis.

Methods

We recruited 120 patients admitted with a diagnosis of cellulitis. Daily thermal images of the affected limb were taken. Temperature intensity and area were analyzed from the images. Highest daily body temperature and antibiotics administered were also collected.We estimated a longitudinal linear mixed-effects model with a random intercept for the affected body area. All observations on a given day were included, and we used an integer time indicator indexed to the initial day (ie, t = 1 for the first day the patient was observed, etc.). We then analyzed the effect of this time trend on both severity (ie, normalized temperature) and scale (ie, area of skin with elevated temperature).

Results

We analyzed thermal images from the 41 patients with a confirmed case of cellulitis who had at least 3 days of photos. For each day that the patient was observed, the severity decreased by 1.63 (95% CI, -13.45 to 10.32) units on average, and the scale decreased by 0.63 (95% CI, -1.08 to -0.17) points on average. Also, patients' body temperatures decreased by 0.28°F each day (95% CI, -0.40 to -0.17).

Conclusions

Thermal imaging could be used to help diagnose cellulitis and track clinical progress.

Shell Engineering on Thermal Sensitivity of Lifetime-Based NIR Nanothermometers for Accurate Temperature Measurement in Murine Internal Liver Organ

Lifetime-based NIR luminescent nanothermometry is ideally suited for temperature detection in living cells and in vivo, but the thermal sensitivity (S_r) modulation remains elusive. Herein, a thorough investigation is performed to unveil the shell effect on lifetime-based S_r by finely controlling the shell thickness of lanthanide-doped core-shell-shell nanoparticles. Owing to the space-dependent energy transfer and back energy transfer between Nd³⁺ and Yb³⁺ as well as the energy migration to surface quenchers, both active and inert shells can regulate the thermal-dependent nonradiative decays and NIR luminescence lifetime of Yb³⁺, which in turn modulates the S_r from 0.56% to 1.54% °C^-1. After poly(acrylic acid) modification of the optimal architecture, the tiny nanoprobes possess robust stability to fluctuations in the microenvironment, which enables accurate temperature mapping of inflammation in the internal liver organ of living mouse. This work will provide new insights for optimizing S_r and guidance for precise temperature measurements in vivo.

Thermo-SPT: A new skin prick test evaluation framework based on low-cost, portable smartphone thermography

BACKGROUND

Although the skin prick test (SPT) is a reliable procedure to confirm IgE-dependent allergic sensitization in patients, the interpretation of the test is still performed manually, resulting in an error-prone procedure for the diagnosis of allergic diseases.

OBJECTIVE

To design and implement an innovative SPT evaluation framework using a low-cost, portable smartphone thermography, named Thermo-SPT, to significantly improve the accuracy and reliability of SPT outcomes.

METHODS

Thermographical images were captured every 60 s for a duration of 0 to 15 min using the FLIR One app, and then analysed with the FLIR Tool^® . The definition of 'Skin Sensitization Region' area was introduced to analyse the time-lapse thermal changes in skin reactions over several time periods during the SPT. The Allergic Sensitization Index (ASI) and Min-Max Scaler Index (MMS) formulae were also developed to optimize the identification of the peak allergic response time point through the thermal assessment (TA) of allergic rhinitis patients.

RESULTS

In these experimental trials, a statistically significant increase in temperature was detected from the fifth minute of TA for all tested aeroallergens (all p $$ p $$ values < .001 $$ <.001 $$ ). An increase was observed in the number of false-positive cases, where patients with clinical symptoms not consistent with SPT were evaluated as positive on TA assessment, specifically for patients diagnosed with Phleum pratense and Dermatophagoides pteronyssinus. Our proposed technique, the MMS, has demonstrated improved accuracy in identifying P. pratense and D. pteronyssinus compared with other SPT evaluation metrics, specifically starting from the fifth minute. For patients diagnosed with Cat epithelium, although not statistically significant initially, an increasing trend was determined in the results at the 15 min (ΔT (T₁₅  - T₀ ), p = .07 $$ p=.07 $$ ; ASI_T15 , p < .001 $$ p<.001 $$ ).

CONCLUSIONS

This proposed SPT evaluation framework utilizing a low-cost, smartphone-based thermographical imaging technique can enhance the interpretability of allergic responses during the SPT, potentially reducing the need for extensive manual interpretation experience as standard SPTs.

Sensing Technologies for Extravasation Detection: A Review

Peripheral intravenous catheters are administered for various purposes, such as blood sampling or the infusion of contrast agents and drugs. Extravasation happens when the catheter is unintentionally directed outside of the vein due to movement of the intravascular catheter, enhanced vascular permeability, or occlusion of the upstream vein. In this article, extravasation and its mechanism are discussed. Subsequently, the sensorized devices (e.g., single sensor and multimodal detection) to identify the extravasation phenomena are highlighted. In this review article, we have shed light on both physiological and engineering points of view of extravasation and its detection approaches. This review provides an overview on the most recent and relevant technologies that can help in the early detection of extravasation.

Readout IC Architectures and Strategies for Uncooled Micro-Bolometers Infrared Focal Plane Arrays: A Review

InfraRed Focal Plane Arrays (IRFPAs) are crucial components in a wide range of applications, including night vision, thermal imaging and gas sensing. Among the various types of IRFPAs, micro-bolometer-based ones have gained significant attention due to their high sensitivity, low noise and low cost. However, their performance is heavily dependent on the readout interface, which converts the analog electrical signals provided by the micro-bolometers into digital signals for further processing and analysis. This paper briefly introduces these kinds of devices and their function, reporting and discussing a list of key parameters used to evaluate their performance; after that, the focus is shifted to the readout interface architecture with particular attention to the different strategies adopted, across the last two decades, in the design and development of the main blocks included in the readout chain.

Wide-Field-of-View Multispectral Camera Design for Continuous Turfgrass Monitoring

Sustainably using resources, while reducing the use of chemicals, is of major importance in agriculture, including turfgrass monitoring. Today, crop monitoring often uses camera-based drone sensing, offering an accurate evaluation but typically requiring a technical operator. To enable autonomous and continuous monitoring, we propose a novel five-channel multispectral camera design suitable for integrating it inside lighting fixtures and enabling the sensing of a multitude of vegetation indices by covering visible, near-infrared and thermal wavelength bands. To limit the number of cameras, and in contrast to the drone-sensing systems that show a small field of view, a novel wide-field-of-view imaging design is proposed, featuring a field of view exceeding 164°. This paper presents the development of the five-channel wide-field-of-view imaging design, starting from the optimization of the design parameters and moving toward a demonstrator setup and optical characterization. All imaging channels show an excellent image quality, indicated by an MTF exceeding 0.5 at a spatial frequency of 72 lp/mm for the visible and near-infrared imaging designs and 27 lp/mm for the thermal channel. Consequently, we believe our novel five-channel imaging design paves the way toward autonomous crop monitoring while optimizing resource usage.

A New Perspective on the Diagnosis of Septic Arthritis: High-Resolution Thermal Imaging

AIMS

An increase in temperature in an area suspected of septic arthritis is a clinically important finding. The aim of this study is to evaluate temperature changes in septic arthritis with a high-resolution thermal camera.

METHODS

A total of 49 patients, who were evaluated with a prediagnosis of arthritis (septic or non-septic), were included in this study. A temperature increase in the knee with suspected septic arthritis was evaluated by using thermal imaging and compared with the opposite-side joint. Then, in order to confirm the diagnosis, a culture was taken using routine intra-articular aspiration.

RESULTS

The thermal measurements were compared in 15 patients with septic arthritis and 34 patients with non-septic arthritis. The mean temperature was 37.93 °C in the septic group, while it was 36.79 °C in the non-septic group (p < 0.000 *). The mean temperature difference in both joints was 3.40 °C in the septic group, while it was 0.94 °C in the non-septic group (p < 0.000 *). While the mean temperature was 37.10 °C in the group with septic arthritis, it was measured to be 35.89 °C in the group non-septic arthritis (p < 0.020). A very strong positive correlation was found between the difference in the mean temperatures of both groups and the values of the hottest and coldest points (r = 0.960, r = 0.902).

CONCLUSIONS

In the diagnosis of septic arthritis, thermal imagers can be used as a non-invasive diagnostic tool. A quantitative value can be obtained to indicate to a local temperature increase. In future studies, specially designed thermal devices can be developed for septic arthritis.

Application of Synchrotron Radiation-Based Fourier-Transform Infrared Microspectroscopy for Thermal Imaging of Polymer Thin Films

The thermal imaging of surfaces with microscale spatial resolution over micro-sized areas remains a challenging and time-consuming task. Surface thermal imaging is a very important characterization tool in mechanical engineering, microelectronics, chemical process engineering, optics, microfluidics, and biochemistry processing, among others. Within the realm of electronic circuits, this technique has significant potential for investigating hot spots, power densities, and monitoring heat distributions in complementary metal-oxide-semiconductor (CMOS) platforms. We present a new technique for remote non-invasive, contactless thermal field mapping using synchrotron radiation-based Fourier-transform infrared microspectroscopy. We demonstrate a spatial resolution better than 10 um over areas on the order of 12,000 um² measured in a polymeric thin film on top of CaF₂ substrates. Thermal images were obtained from infrared spectra of poly(methyl methacrylate) thin films heated with a wire. The temperature dependence of the collected infrared spectra was analyzed via linear regression and machine learning algorithms, namely random forest and k-nearest neighbor algorithms. This approach speeds up signal analysis and allows for the generation of hyperspectral temperature maps. The results here highlight the potential of infrared absorbance to serve as a remote method for the quantitative determination of heat distribution, thermal properties, and the existence of hot spots, with implications in CMOS technologies and other electronic devices.

Species identity and behavior of cave-dwelling tree hyraxes of the Kenyan coast

We surveyed tree hyrax populations living in forests, limestone rocky formations, and caves in coastal Kenya to identify the species and estimate the threat-level populations are in. Tree hyrax vocalizations were recorded in three different habitats with passive acoustic monitoring (PAM) for a total of 84 h in January and February 2022. We also observed tree hyrax behavior with thermal imaging camera and photographed individuals. Tree hyraxes in coastal Kenya are vocally active throughout the night, with most calls emitted between 23.00 and 04.00. We identified four different calls: snort, hac, hac ping-pong, and wheeze. Their calling range is between 220 and 15,000 Hz. Calls of tree hyraxes from the coast of Kenya were compared with calls stored by the Oxford Brookes University's Nocturnal Primate Research Group and identified as eastern tree hyrax, previously recorded from Tanzania. Here, we present what are, to our knowledge, the first photographs of live D. validus from Kenya. These tree hyraxes live in social groups. Due to strong pressure from humans, conservation measures are necessary to prevent the extinction of these isolated D. validus populations in Kenya.

Food Image Segmentation Using Multi-Modal Imaging Sensors with Color and Thermal Data

Sensor-based food intake monitoring has become one of the fastest-growing fields in dietary assessment. Researchers are exploring imaging-sensor-based food detection, food recognition, and food portion size estimation. A major problem that is still being tackled in this field is the segmentation of regions of food when multiple food items are present, mainly when similar-looking foods (similar in color and/or texture) are present. Food image segmentation is a relatively under-explored area compared with other fields. This paper proposes a novel approach to food imaging consisting of two imaging sensors: color (Red-Green-Blue) and thermal. Furthermore, we propose a multi-modal four-Dimensional (RGB-T) image segmentation using a k-means clustering algorithm to segment regions of similar-looking food items in multiple combinations of hot, cold, and warm (at room temperature) foods. Six food combinations of two food items each were used to capture RGB and thermal image data. RGB and thermal data were superimposed to form a combined RGB-T image and three sets of data (RGB, thermal, and RGB-T) were tested. A bootstrapped optimization of within-cluster sum of squares (WSS) was employed to determine the optimal number of clusters for each case. The combined RGB-T data achieved better results compared with RGB and thermal data, used individually. The mean ± standard deviation (std. dev.) of the F1 score for RGB-T data was 0.87 ± 0.1 compared with 0.66 ± 0.13 and 0.64 ± 0.39, for RGB and Thermal data, respectively.

Automated thermal imaging monitors the local response to cervical cancer brachytherapy

Malignant tumors have high metabolic and perfusion rates, which result in a unique temperature distribution as compared to healthy tissues. Here, we sought to characterize the thermal response of the cervix following brachytherapy in women with advanced cervical carcinoma. Six patients underwent imaging with a thermal camera before a brachytherapy treatment session and after a 7-day follow-up period. A designated algorithm was used to calculate and store the texture parameters of the examined tissues across all time points. We used supervised machine learning classification methods (K Nearest Neighbors and Support Vector Machine) and unsupervised machine learning classification (K-means). Our algorithms demonstrated a 100% detection rate for physiological changes in cervical tumors before and after brachytherapy. Thus, we showed that thermal imaging combined with advanced feature extraction could potentially be used to detect tissue-specific changes in the cervix in response to local brachytherapy for cervical cancer.

Postural, pilo-erective and evaporative thermal windows of the short-beaked echidna (Tachyglossus aculeatus)

We identify for wild, free-living short-beaked echidnas (Tachyglossus aculeatus) a novel evaporative window, along with thermal windows, and demonstrate the insulating properties of the spines, using infrared thermography. The moist tip of their beak, with an underlying blood sinus, functions as a wet bulb globe thermometer, maximizing evaporative heat loss via an evaporative window. The ventral surface and insides of the legs are poorly insulated sites that act as postural thermal windows, while the spines provide flexible insulation (depending on piloerection). These avenues of heat exchange likely contribute to the higher-than-expected thermal tolerance of this species. Our study highlights how technological advances that allow for non-contact measurement of thermal variables allow us to better understand the physiological capacity of animals in their natural environment.

Physical parameters in thermal imaging of basal cell cancer patients treated with high-dose-rate brachytherapy - first study

Background

The basal cell carcinoma (BCC) is often treated by surgery or radiotherapy using ionizing radiation. While there is an established diagnostic path before treatment and also for the follow-up there are no good noninvasive methods objectifying irradiated area evolution during treatment. The main goal of preliminary studies was to try to answer if there are any useful information that can be derived from temperature effects of high-dose-rate (HDR) brachytherapy in treatment of BCC. Moreover, the temperature gradient was introduced as a physical parameter characterizing the thermal map of the lesion, its surroundings and reference area, which provided information about cancer tissue thermal reaction to brachytherapy.

Materials and methods

Thirty-three patients suffering from BCC were monitored with thermovision during the brachytherapy treatment. All lesions were diagnosed as superficial and were confirmed with histopathology examination.

Results

Results of the study showed two groups of patients characterized with two thermal maps and temperature gradient describing the lesion and surrounding area of BCC. The first group was characterized by higher temperature of the lesion than the surrounding tissue temperature (mean dT = 0,41°) whereas the other one, with lower lesion temperature (mean dT = -0.42°). It seems that the temperature changes observed in designated areas before and after therapy may provide physicians with additional information which could be useful in planning the treatment process, especially when considering temperature gradient changes during therapy.

Conclusions

Although the data obtained indicate the possibilities of temperature distribution in pre-irradiation cases, further research is required for estimation of clinical effects of treatment.

Automated Identification of Overheated Belt Conveyor Idlers in Thermal Images with Complex Backgrounds Using Binary Classification with CNN

Mechanical industrial infrastructures in mining sites must be monitored regularly. Conveyor systems are mechanical systems that are commonly used for safe and efficient transportation of bulk goods in mines. Regular inspection of conveyor systems is a challenging task for mining enterprises, as conveyor systems' lengths can reach tens of kilometers, where several thousand idlers need to be monitored. Considering the harsh environmental conditions that can affect human health, manual inspection of conveyor systems can be extremely difficult. Hence, the authors proposed an automatic robotics-based inspection for condition monitoring of belt conveyor idlers using infrared images, instead of vibrations and acoustic signals that are commonly used for condition monitoring applications. The first step in the whole process is to segment the overheated idlers from the complex background. However, classical image segmentation techniques do not always deliver accurate results in the detection of target in infrared images with complex backgrounds. For improving the quality of captured infrared images, preprocessing stages are introduced. Afterward, an anomaly detection method based on an outlier detection technique is applied to the preprocessed image for the segmentation of hotspots. Due to the presence of different thermal sources in mining sites that can be captured and wrongly identified as overheated idlers, in this research, we address the overheated idler detection process as an image binary classification task. For this reason, a Convolutional Neural Network (CNN) was used for the binary classification of the segmented thermal images. The accuracy of the proposed condition monitoring technique was compared with our previous research. The metrics for the previous methodology reach a precision of 0.4590 and an F1 score of 0.6292. The metrics for the proposed method reach a precision of 0.9740 and an F1 score of 0.9782. The proposed classification method considerably improved our previous results in terms of the true identification of overheated idlers in the presence of complex backgrounds.

Implementation of Non-Contact Temperature Distribution Monitoring Solutions for Railway Vehicles in a Sustainability Development System Transport

The implementation of temperature sensors represented by thermal imaging cameras is becoming increasingly rational. It is playing an important role in the socio-economic environment, in industry, scientific-research work. The main objective of the work is to assess the quality of the railway vehicles in exploitation and their thermal insulation, localise thermal bridges, and the tightness of the body using the FLIR-E6390 thermal inspection camera. An integration of test methods (research methods) was used including a diagnostic method based on a thermographic study integrated with the system approach method and system failure mode effects analysis (SFMEA). The scientific-research work included studies of seven types of railway vehicles in exploitation. A number of conclusions were reached. Specifically providing implementation of innovative and non-contact temperature distribution monitoring solutions for railway vehicles in a sustainability development system transport. Demonstrated the disparities between the different types of vehicles. Next, the identification of critical elements of their thermal insulation, the location of thermal bridges, and the tightness of the body of the rail vehicles, particularly the doors and inter-unit connections. The study covered the state of consumption of stationary electricity (for non-traction needs), implementing innovative indicators for stationary electricity consumption of railway vehicles as a new approach.

A Study on the Effectiveness of Spatial Filters on Thermal Image Pre-Processing and Correlation Technique for Quantifying Defect Size

Thermal imaging plays a vital role in structural health monitoring of various materials and provides insight into the defect present due to aging, deterioration, and fault during construction. This study investigated the effectiveness of spatial filters during pre-processing of thermal images and a correlation technique in post-processing, as well as exploited its application in non-destructive testing and evaluation of defects in steel structures. Two linear filters (i.e., Gaussian and Window Averaging) and a non-linear filter (i.e., Median) were implemented during pre-processing of a pulsed thermography image sequence. The effectiveness of implemented filters was then assessed using signal to noise ratio as a quality metric. The result of pre-processing revealed that each implemented filter is capable of reducing impulse noise and producing high-quality images; additionally, when comparing the signal to noise ratio, the Gaussian filter dominated both Window Averaging and Median filters. Defect size was determined using a correlation technique on a sequence of pulsed thermography images that had been pre-processed with a Gaussian filter. Finally, it is concluded that the correlation technique could be applied to the fast measurement of defect size, even though the accuracy may depend on the detection limit of thermography and defect size to depth ratio.

Statistical Study on Human Temperature Measurement by Infrared Thermography

Increased temperature in humans is the symptom of many infectious diseases and it is thus an important diagnostic tool. Infrared temperature measurement methods have been developed and applied over long periods due to their advantage of non-contact and fast measurements. This study deals with a statistical evaluation of the possibilities and limitations of infrared/thermographic human temperature measurement. A short review of the use of infrared temperature measurement in medical applications is provided. Experiments and statistics-based evaluation to confirm the expected accuracy and limits of thermography-based human temperature measurement are introduced. The results presented in this study show that the standard deviation of the thermographic measurement of the eyes maximum temperature was 0.4-0.9 °C and the mean values differences from the armpit measurement were up to 0.5 °C, based on the used IR camera, even though near ideal measurement conditions and permanent blackbody correction were used. It was also shown that a certain number of outliers must be assumed in such measurements. Extended analyses including simulations of true negative/false positive, sensitivity/specificity and receiver operating characteristics (ROC) curves are presented. The statistical evaluation as well as the extended analyses show that maximum eyes temperature is more relevant than a forehead temperature examination.

Determination of Changes in Tissue Perfusion at Home with Hyperspectral and Thermal Imaging in the First Six Weeks after Endovascular Therapy in Patients with Peripheral Arterial Disease

The aims of this study were to assess changes in tissue perfusion up to 6 weeks after endovascular therapy (EVT), in hospital and at home, and to determine differences in tissue perfusion between patients with and without clinical improvement or good angiographic result. This single-center prospective cohort study included patients undergoing EVT for Rutherford stages two to six. Hyperspectral and thermal imaging were performed at the dorsal and plantar sides of the foot. These measurements consisted of a baseline measurement pre-EVT, and six follow-up measurements obtained at 1 and 4 h and 6 weeks in hospital, and 1 day, 7 days, and 14 days at home. Clinical improvement was defined as a decrease of one or more Rutherford class or decrease in the wound surface area and a good angiographic result was accomplished when a Transatlantic Inter-Society Consensus for the Management of PAD II C or D lesion was treated and uninterrupted flow continued in at least one below-the-knee artery in continuation with the inframalleolar arteries. The study included 34 patients with 41 treated limbs. Deoxyhemoglobin values were lower 1 h post-EVT compared with baseline and increased over time up to 6 weeks post-EVT. Significant differences in deoxyhemoglobin levels at 7 and 14 days post-EVT were determined between patients with and without clinical or angiographic success. This prospective pilot study shows the feasibility of hyperspectral imaging and thermal imaging post-EVT at home, which may decrease the need for hospital visits.

Coatable 2D Conjugated Polymers Containing Bulky Macromolecular Guests for Thermal Imaging

Dynamic properties are derived from the structural flexibility of 2D polymers. Softening layered structures has the potential for tuning and enhancing the dynamic properties. In the present work, the flexibility of layered polydiacetylene (PDA) is tuned by the interlayer polymeric guests with different branching structures. PDA shows thermoresponsive color-change properties through shortening the effective conjugation length with molecular motion. Whereas the blue-to-red color transition is observed at certain threshold temperatures for the layered PDA without the interlayer guest, the intercalation of the bulky polymer guests lowers the starting temperature and widens the temperature range for the thermoresponsive color changes. The resultant layered composite of PDA and bulky polymer affords the homogeneous coating on substrates on the centimeter scale. The thermoresponsive color-change coating is applied to temperature-distribution imaging. The specific heat of liquids is colorimetrically estimated using the coating on the bottle. The coating on a silk cloth visualizes the temperature distribution on a simulated tissue during surgical operation using an ultrasonic coagulation cutting device. The coating can be applied to thermal imaging in a variety of fields. Moreover, the softening strategy contributes to explore dynamic properties of soft 2D materials.

Dual-Channel Mid-Infrared Toroidal Metasurfaces for Wavefront Modulation and Imaging Applications

In this paper, we propose a dual-channel mid-infrared toroidal metasurface that consists of split equilateral triangular rings. The electromagnetic responses are analyzed by the finite-difference-time-domain (FDTD) method and temporal coupled-mode theory (TCMT). The results show that one channel of the metasurface is insensitive to the polarization angle of the incident light and temperature, while the other channel is sensitive. The reflectance and resonance wavelength can be manipulated by the polarization angle and temperature independently. Based on such a mechanism, we propose metasurfaces for two-bit programmable imaging and thermal imaging. The metasurfaces are believed to have potential applications in information processing and thermal radiation manipulation.

Development of an Early Embryo Detection Methodology for Quail Eggs Using a Thermal Micro Camera and the YOLO Deep Learning Algorithm

Poultry production utilizes many available technologies in terms of farm-industry automation and sanitary control. However, there is a lack of robust techniques and affordable equipment for avian embryo detection and sexual segregation at the early stages. In this work, we aimed to evaluate the potential use of thermal micro cameras for detecting embryos in quail eggs via thermal images during the first 168 h (7 days) of incubation. We propose a methodology to collect data during the incubation period. Additionally, to support the visual analysis, YOLO deep learning object detection algorithms were applied to detect unfertilized eggs; the results showed its potential to distinguish fertilized eggs from unfertilized eggs during the incubation period, after filtering radiometric images. We compared YOLOv4, YOLOv5 and SSD-MobileNet V2 trained models. The mAP@0.50 of the YOLOv4, YOLOv5 and SSD-MobileNet V2 was 98.62%, 99.5% and 91.8%, respectively. We also compared three testing datasets for different intervals of rotation of eggs, as our hypothesis was that fewer turning periods could improve the visualization of fertilized egg features, and applied three treatments: 1.5 h, 6 h, and 12 h. The results showed that turning eggs in different periods did not exhibit a linear relation, as the F1 Score for YOLOv4 of detection for the 12 h period was 0.569, that for the 6 h period was 0.404 and that for the 1.5 h period was 0.384. YOLOv5 F1 Scores for 12 h, 6 h and 1.5 h were 1, 0.545 and 0.386, respectively. SSD-MobileNet V2 performed F1 scores of 0.60 for 12 h, 0.22 for 6 h and 0 for 1.5 h turning periods.

Automated vascular analysis of breast thermograms with interpretable features

Purpose: Vascular changes are observed from initial stages of breast cancer, and monitoring of vessel structures helps in early detection of malignancies. In recent years, thermal imaging is being evaluated as a low-cost imaging modality to visualize and analyze early vascularity. However, visual inspection of thermal vascularity is challenging and subjective. Therefore, there is a need for automated techniques to assist physicians in visualization and interpretation of vascularity by marking the vessel structures and by providing quantified qualitative parameters that helps in malignancy classification Approach: In the literature, there are very few approaches for vascular analysis and classification of breast thermal images using interpretable vascular features. One major challenge is the automated detection of breast vascularity due to diffused vessel boundaries. We first propose a deep learning-based semantic segmentation approach that generates heatmaps of vessel structures from two-dimensional breast thermal images for quantitative assessment of breast vascularity. Second, we extract interpretable vascular parameters and propose a classifier to predict likelihood of breast cancer purely from the extracted vascular parameters. Results: The results of the cancer classifier were validated using an independent clinical dataset consisting of 258 participants. The results were encouraging as the proposed approach segmented vessels well and gave a good classification performance with area under receiver operating characteristic curve of 0.85 with the proposed vascularity parameters. Conclusions: The detected vasculature and its associated high classification performance show the utility of the proposed approach in interpretation of breast vascularity.