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A method is proposed to measure the in-plane thermal diffusivity of anisotropic solids along an arbitrary direction using laser-line lock-in thermography. In this method, the sample is heated by an intensity-modulated laser beam, which impinges on the sample surface with the shape of a narrow strip. The resulting temperature oscillations are recorded by a thermographic camera and a phase thermogram is obtained by lock-in processing the image sequence. The thermal diffusivity along the direction perpendicular to the laser line can be determined from the linear dependence of phase lag with the distance to the heating line using the slope method. Unlike laser-spot lock-in thermography, in which the slope method only provides the thermal diffusivity along the principal directions, in this configuration, the thermal diffusivity can be measured experimentally along any direction, just selecting the relative orientation of the sample with respect to the laser line. Moreover, this configuration allows averaging several parallel phase profiles leading to more reliable thermal diffusivity values. The experimental results are presented for a highly anisotropic material, namely, a unidirectional carbon fiber-reinforced polymer plate. [ABSTRACT FROM AUTHOR]

Artificial light at night (ALAN) changes animal behavior in multiple invertebrates and vertebrates and can result in decreased fitness. However, ALAN effects have not been studied in European honey bees (Apis mellifera), an important pollinator in which foragers show strong circadian rhythmicity. Colonies can be exposed to ALAN in swarm clusters, when bees cluster outside the nest on hot days and evenings, and, in limited cases, when they build nests in the open. We captured and maintained foragers in incubated cages and subjected them to constant light (LL), constant dark (DD), or 12 h light:12 h dark (LD) cycle, and observed them with infrared cameras. After 79 h, there was a significant interaction of treatment and time because LL bees slept less. In detail, the bees maintained a regular sleep pattern for three days but LL bees showed a shift on the fourth day. LL bees had the largest sleep differences from LD controls, with trends of lengthened periods and increased phase misalignment from both LD and DD bees. LL bees also experienced significantly more disturbances from their nestmates and preferred to sleep in the lower portion of the cages, which had significantly lower light intensity. These findings suggest that ALAN can disrupt the sleep of honey bee foragers, which has implications for their behavior and overall colony health. [ABSTRACT FROM AUTHOR]

Effective detection techniques are important for wildlife monitoring and conservation applications and are especially helpful for species that live in complex environments, such as arboreal animals like koalas (Phascolarctos cinereus). The implementation of infrared cameras and drones has demonstrated encouraging outcomes, regardless of whether the detection was performed by human observers or automated algorithms. In the case of koala detection in eucalyptus plantations, there is a risk to spotters during forestry operations. In addition, fatigue and tedium associated with the difficult and repetitive task of checking every tree means automated detection options are particularly desirable. However, obtaining high detection rates with minimal false alarms remains a challenging task, particularly when there is low contrast between the animals and their surroundings. Koalas are also small and often partially or fully occluded by canopy, tree stems, or branches, or the background is highly complex. Biologically inspired vision systems are known for their superior ability in suppressing clutter and enhancing the contrast of dim objects of interest against their surroundings. This paper introduces a biologically inspired detection algorithm to locate koalas in eucalyptus plantations and evaluates its performance against ten other detection techniques, including both image processing and neural-network-based approaches. The nature of koala occlusion by canopy cover in these plantations was also examined using a combination of simulated and real data. The results show that the biologically inspired approach significantly outperformed the competing neural-network- and computer-vision-based approaches by over 27%. The analysis of simulated and real data shows that koala occlusion by tree stems and canopy can have a significant impact on the potential detection of koalas, with koalas being fully occluded in up to 40% of images in which koalas were known to be present. Our analysis shows the koala's heat signature is more likely to be occluded when it is close to the centre of the image (i.e., it is directly under a drone) and less likely to be occluded off the zenith. This has implications for flight considerations. This paper also describes a new accurate ground-truth dataset of aerial high-dynamic-range infrared imagery containing instances of koala heat signatures. This dataset is made publicly available to support the research community. [ABSTRACT FROM AUTHOR]

This study presents a novel deep-learning framework for predicting the thermal appearance of building envelopes under varying weather conditions based on a new dataset collected using a thermal infrared camera at 10 min intervals over a one-and-a-half-year period. Unlike existing studies that rely on simulated data or physical models that do not always accurately reflect the complex heat transfer processes in real buildings, we have collected a large dataset showing how a building behaves under different climatic conditions. We propose a novel deep-learning approach that integrates weather data and thermal imagery to predict the temperature distribution on the building façade for the next 24 and 48 h. The model uses a state-of-the-art recurrent neural network architecture, PredRNN V2, with an action conditioning mechanism to incorporate weather forecasting data into the prediction process. We evaluate this approach in terms of average accuracy, prediction accuracy in specific regions, and visual-perceptual performance of the images. The proposed framework achieves a prediction accuracy of 1.5 °C (root mean square error—RMSE) for the 24 h prediction and 2.04 °C (RMSE) for the 48 h prediction, outperforming baseline models in terms of temperature prediction accuracy and structural similarity of the predicted images. [ABSTRACT FROM AUTHOR]

Depending on the obturation technique, the tooth and surrounding tissues may heat up during root canal filling, particularly with warm methods. This study aimed to analyze the temperature increase in the periradicular and -apical region during various warm obturation techniques with a present simulated periodontal blood flow. Seventy-five extracted human teeth were shortened to 11 mm (cut-grinder Primus diamond cutting device; Walter Messner GmbH, Oststeinbek, Germany) and prepared using the ProTaper Gold system (Dentsply Sirona Inc., Charlotte, NC, USA) ISO size 40/.06. Specimens were prepared to ensure stable fluid circulation in an artificially created periodontal space, and the procedure was recorded with a thermal infrared camera (VarioCAM HD; InfraTec GmbH Infrarotsensorik und Messtechnik, Dresden, Germany). The following obturation methods were applied: I, cold single-cone obturation (control group); II, gutta-percha-coated rigid carrier technique (GuttaFusion); III, squirting technique (injection technique); IV, continuous wave technique; and V, Schilder technique. Statistical analysis was performed using the Kruskal–Wallis test, followed by the Mann–Whitney pairwise test using the sequential Bonferroni procedure for significant differences (p < 0.05). The Schilder technique with 0 mL/min showed the lowest temperature change, with a median of 0.00 °C (max. 0.00 °C, min. 0.00 °C, IQR 0.00 °C). In contrast, the continuous wave technique at a circulation rate of 2.6 mL/min exhibited the highest temperature change, with a median of 3.76 °C (max. 5.33 °C, min. 2.42 °C, IQR 1.46 °C). Although warm obturation techniques can increase surface temperature, none of the methods produced changes that were potentially damaging to the periodontium or surrounding bone. [ABSTRACT FROM AUTHOR]

As wild boar populations and their distribution ranges increase, human–wild boar conflicts have become increasingly prevalent in numerous regions across the globe. These conflicts have a profound impact on human livelihoods, resulting in significant economic losses. Understanding the habitat requirements and relative abundance of wild boars is crucial prior to implementing any conservation measures. However, studies on wild boar habitat and population in the central and eastern regions of the Tianshan Mountains in China are lacking. We assessed the activity patterns and relative abundance of wild boars in these areas and evaluated habitat suitability using a combination of camera trapping, line transects, species distribution modeling (maximum entropy model), and hierarchical abundance modeling (Bayesian N‐mixture model). We used 311 infrared cameras and 280 field‐based line transects to cover approximately 31,000 km² from September 2022 to May 2023 in the east‐central Tianshan Mountains. We used 240 wild boar distribution locations and 13 environmental predictors in the development of species distribution models. We also used species counts and associated environmental predictors in the N‐mixture model to estimate the relative abundance of wild boar. Wild boars were most active during crepuscular hours (1800), and relatively active in the diurnal period compared to the nocturnal period. The probability of wild boar occurrence increased with higher normalized difference vegetation index (NDVI), the minimum temperature of the coldest month, and annual temperatures below 39°C. Boars were most likely to be found in closed deciduous‐coniferous forests. The relative abundance of wild boars was positively affected by NDVI and negatively affected by the minimum temperature of the coldest month and temperature annual range. Based on our results, we suggest areas of management priority. In particular, extensive and intact habitat with substantial wild boar populations, such as the Banfanggou, the South Mountain of Urumqi, and the Hutubi, should be prioritized for long‐term wild boar population monitoring and management so the adverse impacts of increasing wild boar populations in the study region can be minimized. [ABSTRACT FROM AUTHOR]

ABSTRACT Genomic selection (GS) and genome‐wide association studies (GWAS) have not been investigated in Vietnamese dairy cattle, even for basic milk production traits, largely due to the scarcity of individual phenotype recording in smallholder dairy farms (SDFs). This study aimed to estimate heritability (h2) and test the applicability of GS and GWAS for milk production, body conformation and novel heat tolerance traits using single test day phenotypic data. Thirty‐two SDFs located in either the north (a lowland vs. a highland) or the south (a lowland vs. a highland) of Vietnam were each visited for an afternoon and the next morning to collect phenotype data of all lactating cows (n = 345). Tail hair from each cow was sampled for subsequent genotyping with a 50K SNP chip at that same visit. Milk production traits (single‐test day) were milk yield (MILK, kg/cow/day), energy corrected milk yield adjusted for body weight (ECMbw, kg/100 kg BW/day), fat (mFA, %), protein (mPR, %) and dry matter (mDM, %). Conformation traits were body weight (BW, kg) and body condition score (BCS, 1 = thin to 5 = obese). Heat tolerance traits were panting score (PS, 0 = normal to 4.5 = extremely heat‐stressed) and infrared temperatures (IRTs, °C) at 11 areas on the external body surface of the cow (inner vulval lip, outer vulval surface, inner tail base surface, ocular area, muzzle, armpit area, paralumbar fossa area, fore udder, rear udder, forehoof and hind hoof), assessed by an Infrared Camera. Univariate linear mixed models and a 10‐fold cross‐validation approach were applied for GS. Univariate single SNP mixed linear models were applied for the GWAS. Estimated h2 (using the genotype information to build relationships among animals) were moderate (0.20–0.37) for ECMbw, mFA, mPR, mRE, BW, BCS and IRT at rear udder; low (0.08–0.19) for PS and other IRTs; and very low (≤ 0.07) for MILK, ECM and mDM. Accuracy of genomic estimated breeding values (GEBVs) was low (≤ 0.12) for MILK, ECM, mDM and IRT at hind hoof; and moderate to high (0.32–0.46) for all other traits. The most significant regions on chromosomes (BTA) associated with milk production traits were 0.47–1.18 Mb on BTA14. Moderate to high h2 and moderate accuracies of GEBVs for mFA, mPR, ECMbw, BCS, BW, PS and IRTs at rear udder and outer vulval surface suggested that GS using single test day phenotypic data could be applied for these traits. However, a greater sample size is required to decrease the bias of GEBVs by GS and increase the power of detecting significant quantitative trait loci (QTLs) by GWAS. [ABSTRACT FROM AUTHOR]

Brown adipose tissue (BAT) plays an important role in energy metabolism because it uses fatty acids for thermogenesis during cold exposure. Preclinical studies found that boysenberry anthocyanins (BoyACs) activate BAT. Therefore, the aim of this preliminary study was to evaluate how BoyAC intake affects BAT in humans. We performed an open-label single-arm nonrandomized study in healthy volunteers. Before and after 4 weeks of daily consumption of 100 ml boysenberry juice (BoyJ) containing 61 mg of BoyACs, participants were assessed at 24 °C and then after 1 h of mild cold exposure (18 °C). An infrared thermography camera was used to measure skin surface temperatures in the supraclavicular BAT region (Tscv) and the non-BAT region of the upper chest (Tch). Energy metabolism was measured by indirect calorimetry. For each endpoint, we calculated Δ as the difference between values before and after cold exposure and compared the values before and after BoyJ intake. 10 volunteers participated (age: 36.1 ± 4.1, body mass index (BMI): 20.9 ± 0.6). After BoyJ intake, ΔTscv-ch was significantly higher (p = 0.029), but Δ energy expenditure, Δ fat oxidation, and Δ carbohydrate oxidation were not significantly different. We found a significant positive correlation between BMI and Δfat oxidation with BoyJ intake. The results indicate that 4 weeks of BoyJ intake activates cold-induced thermogenesis in the scv-BAT but does not have a significant effect on energy metabolism. BoyJ intake may increase fat oxidation during cold exposure in individuals with higher BMI. Trial registry number: UMIN000043476, 05/03/2021. [ABSTRACT FROM AUTHOR]

Introduction: The tennis serve is a complex motion with numerous rotations which are important to manage for performance. The main aim of this study was to investigate kinematic parameters, including the evolution of the center of gravity, and kinetic parameters correlated with racket velocity over all phases of the tennis serve. The secondary objective was to find out which of the correlated parameters differed between a slow and a fast serve. The advantage of such an approach would be to propose biomechanical parameters that coaches and teachers could use to optimize performance or learn how to serve. Methods: Quantitative analysis was carried out on 5 flat serves performed by four ranked players using an optoelectronic system (82 markers located on whole body and racket) composed of 10 infrared cameras (150 Hz) and two force platforms (750 Hz). Results: A descriptive statistical analysis highlighted 11 very large and almost perfect correlations with racket velocity: vertical ground reaction force of back foot in release backward, trunk axial rotation during loading phase, back and front knee flexions, dominant shoulder and hip mediolateral rotation during cocking phase, and center of gravity vertical velocity, dominant shoulder medial rotation velocity, dominant elbow flexion, trunk flexion/extension and axial rotation during acceleration phase. Differences were observed for some of the correlated parameters between slow and fast serve. Discussion: Consequently, all these correlated kinematic and kinetics parameters constitute information that coaches, instructors and athletes can use to improve, optimize or teach the tennis serve. [ABSTRACT FROM AUTHOR]

Introduction: Studying the behavioral responses and movement trajectories of insects under different stimuli is crucial for developing more effective biological control measures. Therefore, accurately obtaining the movement trajectories and behavioral parameters of insects in three-dimensional space is essential. Methods: This study used the litchi pest Thalassodes immissaria as the research object. A special binocular vision observation system was designed for nighttime movement. A thermal infrared camera was used for video recording of T. immissaria in a lightless environment. Moreover, a multi-object tracking method based on the YOLOX-GMM and SORT-Pest algorithms was proposed for tracking T. immissaria in thermal infrared images. By obtaining the central coordinates of the two T. immissaria in the video, target matching and 3D trajectory reconstruction in the parallel binocular system were achieved. Results: Error analysis of the T. immissaria detection and tracking model, as well as the 3D reconstruction model, showed that the average accuracy of T. immissaria detection reached 89.6%, tracking accuracy was 96.9%, and the average error of the reconstructed 3D spatial coordinates was 15 mm. Discussion: These results indicate that the method can accurately obtain the 3D trajectory and motion parameters of T. immissaria. Such data can greatly contribute to researchers' comprehensive understanding of insect behavioral patterns and habits, providing important support for more targeted control strategies. [ABSTRACT FROM AUTHOR]

High-temperature furnaces and coal-fired boilers are widely employed in the petrochemical and metal-smelting sectors. Over time, the deterioration, corrosion, and wear of pipelines can lead to equipment malfunctions and safety incidents. Nevertheless, effective real-time monitoring of equipment conditions remains insufficient, primarily due to the interference caused by flames generated from fuel combustion. To address this issue, in this study, a through-flame infrared imager is developed based on the mid-wave infrared (MWIR) radiation characteristics of the flame. The imager incorporates a narrowband filter that operates within the wavelength range of 3.80 μm to 4.05 μm, which is integrated into conventional thermal imagers to perform flame filtering. This configuration enables the radiation from the background to pass through the flame and reach the detector, thereby allowing the infrared imager to visualize objects obscured by the flame and measure their temperatures directly. Our experimental findings indicate that the imager is capable of through-flame imaging; specifically, when the temperature of the target exceeds 50 °C, the imager can effectively penetrate the outer flame of an alcohol lamp and distinctly capture the target's outline. Importantly, as the temperature of the target increases, the clarity of the target's contour in the images improves. The MWIR through-flame imager presents considerable potential for the real-time monitoring and preventive maintenance of high-temperature furnaces and similar equipment, such as detecting the degradation of refractory materials and damage to pipelines. [ABSTRACT FROM AUTHOR]

Regular population monitoring of imperilled charismatic species such as large carnivores is critical for conservation. However, the role of monitoring in conservation is frequently diminished due to: 1) surveys being implemented in isolation, 2) limited on-ground-capacity leading to infrequent monitoring, and 3) inappropriate methods being applied. Wildlife monitoring is often resource-intensive and the utility and cost of different field protocols is rarely reported. In this study we deployed two standard field protocols aimed at collecting data on African lions within a spatial capture-recapture framework. For our first protocol, we trained Uganda Wildlife Authority rangers in search-encounter techniques, the industry gold standard for monitoring lions. The second protocol involved deploying 32 paired stations of state-of-the-art infra-red camera traps. During the search-encounter protocol, two rangers covered 2939 km in 76 days, recording 102 detections (30 individuals) in a ~ 256 km2 area. The resulting density estimates (13.91 lions/100 km2, posterior SD = 2.34) yielded acceptable precision. Conversely, 64 camera traps over 1601 trap nights yielded two usable lion detections. We argue that where wildlife tourism rangers exist, they could be a powerful addition to future lion and wildlife census attempts across the continent. Our results confirm that the current technology of store-bought infra-red camera traps is not suitable for individual identification of lions, and therefore cannot be applied to analytical models that require unambiguous individual identities. However, we encourage the continued testing and advancement of infra-red camera trap technology since in many instances, this may be preferable to white-flash camera traps, which can yield individual identities for lions. Our study also shows the immense importance of the Nile Delta for African lions in Uganda's Murchison Falls National Park, a protected area with both oil extraction and high rates of anthropogenic snaring pressure. A study on African lions in Uganda's Nile Delta shows wildlife tourism rangers, an often-forgotten group in the scientific process, deliver strong density estimates. The study also shows infrared camera traps are weak at detecting lions. [ABSTRACT FROM AUTHOR]

We identify the progenitor star of SN 2023ixf in Messier 101 using Keck/NIRC2 adaptive optics imaging and pre-explosion Hubble Space Telescope (HST)/Advanced Camera for Surveys (ACS) images. The supernova, localized with diffraction spikes and high-precision astrometry, unambiguously coincides with a progenitor candidate of |$m_\text{F814W}=24.87\pm 0.05$| (AB). Given its reported infrared excess and semiregular variability, we fit a time-dependent spectral energy distribution (SED) model of a dusty red supergiant (RSG) to a combined data set of HST optical, ground-based near-infrared, and Spitzer Infrared Array Camera (IRAC) [3.6], [4.5] photometry. The progenitor resembles an RSG of |$T_\text{eff}=3488\pm 39$| K and |$\log (L/\mathrm{L}_\odot)=5.15\pm 0.02$|⁠ , with a |$0.13\pm 0.01$| dex (⁠|$31.1\pm 1.7$|  per cent) luminosity variation at a period of |$P=1144.7\pm 4.8$| d, obscured by a dusty envelope of |$\tau =2.92\pm 0.02$| at |$1\, \mu \text{m}$| in optical depth (or |$A_\text{V}=8.43\pm 0.11$| mag). The signatures match a post-main-sequence star of |$18.2_{-0.6}^{+1.3}\, \mathrm{M}_\odot$| in zero-age main-sequence mass, among the most massive SN II progenitor, with a pulsation-enhanced mass-loss rate of |$\dot{M}=(4.32\pm 0.26)\times 10^{-4} \, \mathrm{M}_\odot \, \text{yr}^{-1}$|⁠. The dense and confined circumstellar material is ejected during the last episode of radial pulsation before the explosion. Notably, we find strong evidence for variations of |$\tau$| or |$T_\text{eff}$| along with luminosity, a necessary assumption to reproduce the wavelength-dependent variability, which implies periodic dust sublimation and condensation. Given the observed SED, partial dust obscuration remains possible, but any unobstructed binary companion over |$5.6\, \mathrm{ M}_\odot$| can be ruled out. [ABSTRACT FROM AUTHOR]

Wire Arc Additive Manufacturing (WAAM) is a metal arc welding additive process that allows the production of large parts. Managing the quality of produced parts is a key challenge to the adoption of this technology in the industry. A particular case of this is the production of aluminum thin walls and the management of their thicknesses. Literature supports that the use of a near-infrared camera is a good way to monitor the meltpool shape to predict the manufactured thickness. Nevertheless, the post-processing applied to the image has a big influence on the accuracy of the measure. That is why, this article proposes a method to qualify image post-processing for thin wall thickness prediction from near-infrared camera images of aluminum WAAM process. A dataset from the literature is used to evaluate the accuracy of different post-processes. First, a method is proposed to evaluate the accuracy of a given post-process. Secondly, two types of post-processing are presented: post-processing based on conventional image processing and post-processing based on neural networks. Their accuracy is evaluated with the proposed method. The article concludes that the proposed method is adapted to qualify post-processes and that the proposed post-processing based on neural networks gives significant results in terms of accuracy. [ABSTRACT FROM AUTHOR]

This study introduces AffectiVR, a dataset designed for periocular biometric authentication and emotion evaluation in virtual reality (VR) environments. To maximize immersion in VR environments, interactions must be seamless and natural, with unobtrusive authentication and emotion recognition technologies playing a crucial role. This study proposes a method for user authentication by utilizing periocular images captured by a camera attached to a VR headset. Existing datasets have lacked periocular images acquired in VR environments, limiting their practical application. To address this, periocular images were collected from 100 participants using the HTC Vive Pro and Pupil Labs infrared cameras in a VR environment. Participants also watched seven emotion-inducing videos, and emotional evaluations for each video were conducted. The final dataset comprises 1988 monocular videos and corresponding self-assessment manikin (SAM) evaluations for each experimental video. This study also presents a baseline study to evaluate the performance of biometric authentication using the collected dataset. A deep learning model was used to analyze the performance of biometric authentication based on periocular data collected in a VR environment, confirming the potential for implicit and continuous authentication. The high-resolution periocular images collected in this study provide valuable data not only for user authentication but also for emotion evaluation research. The dataset developed in this study can be used to enhance user immersion in VR environments and as a foundational resource for advancing emotion recognition and authentication technologies in fields such as education, therapy, and entertainment. This dataset offers new research opportunities for non-invasive continuous authentication and emotion recognition in VR environments, and it is expected to significantly contribute to the future development of related technologies. [ABSTRACT FROM AUTHOR]

This study proposes a UAV-based remote measurement method for accurately locating pedestrians and other small targets within small reservoir dams. To address the imprecise coordinate information in reservoir areas after prolonged operations, a transformation method for converting UAV coordinates into the local coordinate system without relying on preset parameters is introduced, accomplished by integrating the Structure from Motion (SfM) algorithm to calculate the transformation parameters. An improved YOLOv8 network is introduced for the high-precision detection of small pedestrian targets, complemented by a laser rangefinder to facilitate accurate 3D locating of targets from varying postures and positions. Furthermore, the integration of a thermal infrared camera facilitates the detection and localization of potential seepage. The experimental validation and application across two real small reservoir dams confirm the accuracy and applicability of the proposed approach, demonstrating the efficiency of the proposed routine UAV surveillance strategy and proving its potential to establish electronic fences and enhance maintenance operations. [ABSTRACT FROM AUTHOR]

Buildings consume 30% to 40% of all primary energy worldwide and are responsible for 50% of total greenhouse gas emissions. Canada has set a target of reducing greenhouse gas emissions by at least 80% by 2050. The aim of this paper is to investigate thermal bridging in four high-efficient buildings, such as those built to LEED standards. Thermal bridging is a major source of heat loss in many buildings, manifesting itself through exterior envelopes, particularly through studs and wall systems. LEED is an evaluation system that rates how sensitive buildings are to the environment, with one of its main objectives being the reduction of greenhouse gases (GHG) emissions through the implementation of highly efficient mechanical systems and the design of durable and efficient exterior wall systems with appropriate insulation. This research investigates and identifies the location of thermal bridging in high-efficiency buildings using non-destructive testing methods such as thermal imaging and THERM simulations. The study involves using infrared thermography to inspect surface temperature variations and detect irregular thermal patterns that correspond to thermal bridging. By collecting record drawings to identify the construction systems used in the external wall compounds, capturing thermal images with high-resolution infrared cameras, and comparing these images with simulation results, the research provides a comprehensive analysis of thermal performance. The findings from this research are significant, particularly in the context of window curtain walls, steel studs, brick shelf angles, timber frames, and roof hatches—all of which were identified as critical areas of concern due to their propensity to thermal bridges. For instance, window curtain walls, with their metal frames and large glass surfaces, showed temperature drops of up to 8°C. Steel studs, which are highly conductive of heat, resulted in temperature drops of up to 5°C, while brick shelf angles showed a temperature drop of 4°C due to heat conduction through the metal. In timber frame structure the building envelope connector showed temperature drops of up to 7°C. Additionally, roof hatches, necessary for rooftop access, were found to cause the most significant temperature drop of 10°C. The findings highlight the significant impact of thermal bridges on overall energy efficiency, emphasizing the need for careful design and construction practices to minimize heat losses. Addressing these thermal bridging issues is crucial for achieving the ambitious GHG reduction targets and enhancing the sustainability of high-performance buildings. [ABSTRACT FROM AUTHOR]

In sports science, thermal imaging is applied to investigate various questions related to exercise-induced stress response, muscle fatigue, anomalies, and diseases. Infrared thermography monitors thermal radiation from the skin's surface over time. For further analysis, regions of interest are extracted and statistically analyzed. Although computer vision algorithms have grown in recent years due to data-driven approaches, this is not the case for detailed segmentation in thermal images. In a supervised manner, machine learning optimizations require a large amount of training data with input and ground truth output data. Unfortunately, obtaining annotated data are a costly problem that increases with the complexity of the task. For semantic segmentation, pixel-wise label masks must be created by experts. Few datasets meet the needs of sports scientists and physicians to perform advanced applications of thermal computer vision during physical activity and generate new insights in their fields. In this paper, a new method is introduced to transfer segmentation masks from the vision domain to the thermal domain with a stereo-calibrated time-of-flight camera and high-resolution mid-wave infrared camera. A post-processing procedure is then utilized to obtain dense pixel masks for the posterior legs during walking and running on a treadmill. The developed StereoThermoLegs dataset is based on 14 participants and includes 11 subjects for training with 12,826 thermograms and the remaining three individuals for testing with 3433 images. A deep neural network was trained with the DeepLabv3+ architecture, the AdaBelief optimizer, and Dice loss as a benchmark. After 29 epochs, the test set achieved an average intersection over union of 0.66. The analysis of the posterior leg region, specifically the left and right calf, offered the most insights, with values of 0.83 and 0.83, respectively. The first multimodal stereo dataset containing synchronized visual and thermal images of a runner's back provides a starting point for data-driven segmentation tasks in sports science and medicine. Our technique allows for automatic production of customized datasets for deep learning, accelerating the implementation of baseline outcomes for newly identified areas of interest in thermal imaging, while bypassing the requirement for extensive manual annotation. The approach is not exclusive to stereo rig and segmentation tasks utilizing RGBD and thermal cameras, but can be applied to other imaging tasks and modalities. [ABSTRACT FROM AUTHOR]

There is a need to reduce human–wildlife conflicts in the area around Liupanshan Nature Reserve in Ningxia Hui Autonomous Region, China. This study investigated the financial losses caused by wild boar and their causes. A questionnaire investigation (n = 135) and a field test were conducted, which included 108 sample lines and 97 infrared cameras. A principal component analysis and generalised linear model was used to analyse the importance of the effect of the factors on wild boar damage. Based on an estimate of 17,049 wild boars in the study area, we found that in the agricultural land owned by the residents, the boar density of each county and distance from the village to the nature reserve were the most significant factors that affected crop damage. Then, financial losses in spring, summer, and autumn had a moderate effect on financial loss, and the crop type had the lowest effect. We recommend reducing the wild boar population by increasing leisure hunting and the number of leopards. Additionally, a focus on farmland protection is a practical way to prevent wild boar invasions. Meanwhile, it is also necessary to conduct long-term monitoring of wild boar population status and manage the relationship between the government, research teams, and local people to more efficiently and comprehensively reduce conflicts between humans and wild boars. [ABSTRACT FROM AUTHOR]

Addressing the risk of musculoskeletal disorders (MSDs) during a tennis serve is a challenge for both protecting athletes and maintaining performance. The aim of this study was to investigate the risk of MSD occurrence using the rapid whole-body assessment (REBA) ergonomic tool at each time step, using 3D kinematic analysis of joint angles for slow and fast serves. Two force platforms (750 Hz) and an optoelectronic system including 10 infrared cameras (150 Hz, 82 markers located on the whole body and on the racket) were used to capture the kinematics of the six REBA joint areas over five services in two young male and two young female ranked players. The mean REBA score was 9.66 ± 1.11 (ranging from 7.75 to 11.85) with the maximum value observed for the loading and cocking stage (REBA score > 11). The intermediate scores for each of the six joint areas ranged between 2 and 3 and the maximum value of their respective scales. The lowest scores were observed for the shoulder. Neck rotation and shoulder flexion are parameters that could be taken into account when analyzing performance in the context of MSD prevention. [ABSTRACT FROM AUTHOR]

Introduction: The study of facial profiles in the dental field is very important for the diagnosis and the dental and orthodontic treatment plan. The aim of this study is to analyze the three-dimensional morphology of the faces of 269 growing patients with Class I and II occlusions, focusing on children aged between 6 and 9 years old. The analysis was conducted using a non-invasive computerized system, which allowed for the automatic collection of facial landmarks and the subsequent reconstruction of three-dimensional coordinates. Materials and methods: The sample comprised 269 children within the specified age range. Each child's facial features were captured using the non-invasive computerized system, which utilized two infrared CCD cameras, real-time hardware for label recognition, and software for three-dimensional landmark reconstruction. Sixteen cutaneous facial landmarks were automatically collected for each participant. From these landmarks, 10 angular and 15 linear measurements, as well as five direct distance rates, were derived. The mean values for each age class were calculated separately for children with bilateral Angle Class I occlusion and compared with those for children with bilateral Class II occlusion. In all children, the left and right occlusal classes were measured as suggested by Katz. Results: The analysis revealed notable differences, primarily in the three-dimensional angular measurements between children with Class I and II occlusions. Specifically, Class II children exhibited more convex faces in the sagittal plane and a less prominent lower jaw compared to Class I children. However, no significant differences were observed in linear measurements, except for the lower facial height rate, which varied inconsistently across age groups between the two occlusion types. Discussion and Conclusions: the findings of this research highlight distinct three-dimensional facial morphological differences between children with Class I and II occlusions. While Class II children tended to have more convex facial profiles and less prominent lower jaws, linear measurements showed minimal variation between the two occlusion types. These results underscore the importance of three-dimensional analysis in understanding facial morphology in growing patients with different occlusal patterns. [ABSTRACT FROM AUTHOR]

To enable the operation of a mid-wave infrared (MWIR) camera under vacuum and low-temperature conditions for space-based Earth imaging optical systems, research was conducted on the optical system, mechanical structure, and vacuum and low-temperature testing methods employed in the MWIR optical system. A low-temperature MWIR camera was designed to operate under normal atmospheric pressure, vacuum, and low-temperature conditions. The camera comprises independent optical lenses, an MWIR dewar, an image processing unit, a vacuum refrigeration unit, and preset water cooling pipes. The MWIR lens consists of a front lens unit, a focusing lens unit with a two-stage reduction mechanism, and a rear lens. The assembly temperature of the MWIR camera is 293 K with an operational temperature of 100 K, and the temperature variation does not exceed 193 K. A structural thermal-optical performance analysis of the MWIR lens was conducted to evaluate the optical performance degradation caused by temperature changes. The measurement of the MWIR lens was described using an MWIR interferometer and a spherical standard MWIR mirror, providing on-axis and off-axis wave aberrations. One method was proposed to test the modulation transfer function of the MWIR camera under two different conditions. Experimental results confirmed that the overall design of the MWIR camera ensures normal operation in a vacuum low-temperature environment. [ABSTRACT FROM AUTHOR]

In this study, we developed a docking mechanism for drones that enables docking and undocking in the air for cargo transportation. This capability allows the drone configuration to be adapted depending on the cargo size and shape. We introduced a novel docking mechanism that incorporates magnetic adsorption and a newly engineered locking mechanism. We developed a drone detection system capable of estimating the relative position of a target drone by utilizing an onboard camera to identify the infrared LEDs on the target drone via image processing. Moreover, flight experiments, including detection, docking, and undocking, were performed using a mock drone to demonstrate the effectiveness of the developed system. [ABSTRACT FROM AUTHOR]

This paper presents aspects related to the indirect thermographic measurement of a C2M0280120D transistor in pulse mode. The tested transistor was made on the basis of silicon carbide and is commonly used in many applications. During the research, the pulse frequency was varied from 1 kHz to 800 kHz. The transistor case temperature was measured using a Flir E50 thermographic camera and a Pt1000 sensor. The transistor die temperature was determined based on the voltage drop on the body diode and the known characteristics between the voltage drop on the diode and the temperature of the die. The research was carried out in accordance with the presented measuring standards and maintaining the described conditions. The differences between the transistor case temperature and the transistor die temperature were also determined based on simulation work performed in Solidworks 2020 SP05. For this purpose, a three-dimensional model of the C2M0280120D transistor was created and the materials used in this model were selected; the methodology for selecting the model parameters is discussed. The largest recorded difference between the case temperature and the junction temperature was 27.3 °C. The use of a thermographic camera allows the transistor's temperature to be determined without the risk of electric shock. As a result, it will be possible to control the C2M0280120D transistor in such a way so as not to damage it and to optimally select its operating point. [ABSTRACT FROM AUTHOR]

Uncooled and shutterless microbolometer cameras are good candidates for infrared imaging systems installed on small satellites or small unmanned aerial vehicles: they are light and passive since no cooling system or mechanical shutter is required and they can be operated at ambient temperatures. However, the radiometric compensation has to be carefully performed to make the system compatible with applications where the radiometric accuracy of the images is mandatory. In this paper, we study the impact of the camera environment to the radiometric accuracy of the images. We propose and test hardware and software solutions to improve this accuracy and the quality of the radiometric images. We show that the radiometric calibration of the camera with our model is valid over a long time period— about 3 years—using in-door experiments. [ABSTRACT FROM AUTHOR]

The effect of entrained air bubbles on heat transfer enhancement inside 90° ribbed parallel channels has been experimentally studied to improve electrical efficiency inside future solar panels. In this work, the Reynolds number was measured from 200 to 600. The essential ratios of channel aspect, rib height, and rib pitch were all set to 0.4, 0.18, and 10, respectively. The volumetric flow fraction for all test conditions varied from 0.0 to 0.5. The overall heat transfer distributions on the surface were captured using an infrared thermography camera. The main finding showed that the average heat transfer rate and the thermal performance gained beyond 25–81% and 7–82% compared with the smooth wall. In addition, the volumetric flow fraction of 0.5 at the Reynolds number of 200 became the best. [ABSTRACT FROM AUTHOR]

Localizing security-relevant hard blocks on modern System-on-Chips for physical attacks, such as side-channel analysis and fault attacks, has become increasingly time-consuming due to ever-increasing chip-area and -complexity. While this development increases the effort and reverse engineering cost, it is not sufficient to withstand resolute attackers. This paper explores the application of camera-based lock-in thermography, a nondestructive testing method, for identifying and localizing security hard blocks on integrated circuits. We use a synchronous signal to periodically activate security-related functions in the firmware, which causes periodic temperature changes in the activated die areas that we detect and localize via an infrared camera. Using this method, we demonstrate the precise detection and localization of security-related hard blocks at the die level on a modern SoC. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate three experimental approaches to improve the performance of lock-in thermography (LIT). The infrared imaging (IR) technique is extensively used for failure analysis (FA) in the semiconductor industry. However, with the conventional LIT, low-contrast topography images can be obtained at room temperature due to the poor emissivity gradient in the devices and the limitation on the performance of the infrared camera. The grayscale topographical contrast is improved significantly when the device under test is heated from room temperature to 90 °C. A compact printed circuit board heater is designed and customized for this application. Furthermore, the heater can also be used in the lock-in loop to get the enhanced topography images. These methods are implemented experimentally, and the results are validated using finite element simulation. The thermal enhancement approaches proposed in this paper are demonstrated at die level on a defective silicon interposer sample. The topographical contrast and the signal intensity of the hotspot obtained are enhanced when compared to the classical LIT performed at room temperature. To reduce the thermal budget of the heat-assisted method, dual LIT is developed where the two consecutive lock-in measurements are performed to obtain hotspot amplitude and topography image with good contrast. In addition, the topography image obtained from this technique is less susceptible to input noise levels. To increase the throughput of the FA process, quadrature lock-in thermography, a dual-purpose measurement technique is shown. A high-contrast topography image and the hotspot location are obtained from the same lock-in thermogram by performing trigonometric conditioning. The throughput from this approach is the same as the classical LIT technique. [ABSTRACT FROM AUTHOR]

The introduction of remote sensing technologies, AI and big data analytics in the utility sector is warranted by the need to provide critical services with the least disruption to customers, but also to enable preventive maintenance, extend the life cycle of infrastructure components and reduce grid loss—or overall, to exhibit 'durability' and 'resilience' when faced with the certainty of breakage and decay. In this paper, we first explore the concept of 'resilience' and the nature of practice from a performativist perspective in order to set the scene for discussing the impact of 'datafication' on maintenance practices and infrastructure durability. We then describe an instance of introducing remote sensing technologies in district heating network surveillance and leak detection: drone-operated thermographic cameras and underground wire sensors. Based on insights from this case study, we discuss the specificity of data-driven infrastructure maintenance practices, and what it means to exhibit practical resilience in relation to how such practices unfold, interrelate and evolve over time. We reflect on how the use of remote sensing technologies and data analytics (1) potentially changes district heating workers' epistemic worlds (i.e., how knowledge emerges, is negotiated and ordered in practice) and (2) provides opportunities for 'messy' pipe repair work to tacitly adopt proactive and preventive logics to meet continuously evolving organizational and societal needs. [ABSTRACT FROM AUTHOR]

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Fatigue driving poses a serious threat to road safety, and research on how to effectively perceive driver fatigue and provide friendly reminders under the limited computing resources of vehicle-mounted platforms has attracted much attention. This study aims to address this limitation by developing edge computing-friendly operators and lightweight network structures. The proposed model, EMFastDet, enhances the efficiency and accuracy of driver fatigue detection. It integrates an attention module within edge computing-friendly operation blocks to capture features of the mouth and eyes. Anchor-free methods and a single detection head layer are employed for position and category predictions. The eye and mouth states in video streams are evaluated based on the metrics of Percentage of Eye Closure (PERCLOS) and Percentage of Yawning (POY). Extensive experiments were conducted using the YFDMS dataset collected in a real driving cabin environment with an infrared camera. Testing on the Qualcomm Snapdragon SA8155P chip, the DSP-accelerated EMFastDet 0.5 × version achieved an inference time of 3.02 ms and a quantized model size of 0.91 MB. The model achieved an mAP0.5 accuracy of 66.1 % , meeting the deployment requirements of in-vehicle platforms. [ABSTRACT FROM AUTHOR]

Historically, most insect chronoecological research has used direct observations, cameras or infrared beam‐based monitors to quantify movement across timed intervals. Although some alternative DIY systems are cheaper than the current standard locomotor activity monitor, these options remain complicated to build and/or computationally intensive.We developed the imaging Locomotor Activity Monitor (iLAM), an affordable (~$75 USD/unit) system for activity quantification. The iLAM utilizes a Raspberry Pi Zero W computer and night‐vision camera inside a flight cage to photograph a population of insects at user‐defined intervals. Open‐source, modular R‐scripts process the images and output a file containing the number, size, coordinate location and timestamp of all movements (blobs) identified between consecutive images. Output can be analysed directly or converted into the standard TriKinetics DAM format.We demonstrated the flexibility and power of the iLAM system by comparing diel and circadian activity of different insect species (fireflies: Photinus marginellus, P. greeni, P. obscurellus), ecotypes (moths: Ostrinia nubilalis) and sexes (moths: O. nubilalis). Data captured by only six iLAMs ($450) identified that peak activity of O. nubilalis females (AZT: 19.2 h) occurs significantly earlier than males (22.0 h). Additionally, male moths from a univoltine population exhibited a significantly shorter endogenous period length (AZT: 21.3 h) than males from a bivoltine genetic background (22.7 h).The iLAM will serve as a valuable tool for researchers seeking to measure locomotor activity across diverse species, sexes and populations in constant and changing environments. [ABSTRACT FROM AUTHOR]

Rapid urbanization has caused a series of environmental problems, but its influences on animal-related ecological functions (e.g., seed dispersal) have not been fully studied. Mammals are ideal models for studying the functional consequences of urbanization because they are sensitive to environmental changes. It is well known that large- and medium-sized mammals are vulnerable in fragmentation ecosystem. However, little is known about the functional responses of small mammals (e.g., rodents) to the rapid urbanization. Using infrared cameras and tagged seeds, here, we quantified mammals and mammal-mediated seed dispersal (i.e., Quercus variabilis) in 11 forest patches along city-suburb-exurban gradient in a rapidly urbanizing megacity, central China. We wanted to determine the effects of defaunation on seed dispersal in the isolated urban forests. The results showed that abundance of seed dispersers was higher in the natural exurban forests than in the city forests, while abundance of seed predators did not vary significantly along the city-suburb-exurban gradient. The percentage of seed dispersal was positively associated with the abundance seed dispersers, while the percentage of seed predation increased with the abundance of seed predators. Seed dispersers loss (e.g., small rodents) disrupted the mammal-mediated seed dispersal, possibly contributing to the degradation of urbanized forests. These results suggest that defaunation effects are obvious in the rapidly urbanizing cities, in that abundance of seed dispersers, and mammal-mediated seed dispersal are undergoing decline in the urbanized forests. In order to maintain seed dispersal and natural regeneration of urban forests, diversity of small mammals (e.g., rodents) and their ecological services should be considered in ecological-based urban planning and management. [ABSTRACT FROM AUTHOR]

We present the joint astrometric and direct imaging discovery, mass measurement, and orbital analysis of HD 63754 B (HIP 38216 B), a companion near the stellar-substellar boundary orbiting |$\sim$| 20 au from its Sun-like host. HD 63754 was observed in our ongoing high-contrast imaging survey targeting stars with significant proper-motion accelerations between Hipparcos and Gaia consistent with wide-separation substellar companions. We utilized archival High Resolution Echelle Spectrograph and High Accuracy Radial Velocity Planet Searcher radial velocity (RV) data, together with the host star's astrometric acceleration extracted from the Hipparcos – Gaia Catalog of Accelerations, to predict the location of the candidate companion around HD 63754 A. We subsequently imaged HD 63754 B at its predicted location using the Near Infrared Camera 2 (NIRC2) in the |$L^{\prime }$| band at the W. M. Keck Observatory. We then jointly modelled the orbit of HD 63754 B with RVs, Hipparcos – Gaia accelerations, and our new relative astrometry, measuring a dynamical mass of |${81.9}_{-5.8}^{+6.4} {M_{\rm Jup}}$|⁠ , an eccentricity of |${0.260}_{-0.059}^{+0.065}$|⁠ , and a nearly face-on inclination of |$174.\!\!^\circ 81_{-0.50}^{+0.48}$|⁠. For HD 63754 B, we obtain an |$L^{\prime }$| -band absolute magnitude of |$L^{\prime } = 11.39\pm 0.06$| mag, from which we infer a bolometric luminosity of |$\rm{log(L_{\rm bol}/{\rm{L}_{\odot}})= -4.55 \pm 0.08}$| dex using a comparison sample of L and T dwarfs with measured luminosities. Although uncertainties linger in age and dynamical mass estimates, our analysis points towards HD 63754 B's identity as a brown dwarf on the L/T transition rather than a low-mass star, indicated by its inferred bolometric luminosity and model-estimated effective temperature. Future RV, spectroscopic, and astrometric data such as those from JWST and Gaia Data Release 4 will clarify HD 63754 B's mass, and enable spectral typing and atmospheric characterization. [ABSTRACT FROM AUTHOR]

Context. The nature of the close-in rocky planet 55 Cnce is puzzling, despite it having been observed extensively. Its optical and infrared occultation depths show temporal variability, in addition to a phase curve variability observed in the optical. Aims. We wish to explore the possibility that the variability originates from the planet being in a 3:2 spin–orbit resonance, and thus showing different sides during occultations. We proposed and were awarded Cycle 1 time at the James Webb Space Telescope (JWST) to test this hypothesis. Methods. JWST/NIRCam (Near Infrared Camera) observed five occultations (secondary eclipses) of the planet – of which four were observed within a week – simultaneously at 2.1 and 4.5 µm. While the former gives band-integrated photometry, the latter provides a spectrum between 3.9–5.0 µm. Results. We find that the occultation depths in both bandpasses are highly variable and change between a non-detection (−5 ± 6 ppm and 7 ± 9 ppm) to 96 ± 8 ppm and 119−19+34 ppm at 2.1 µm and 4.5 µm, respectively. Interestingly, the variations in both bandpasses are not correlated and do not support the 3:2 spin-orbit resonance explanation. The measured brightness temperature at 4.5 µm varies between 873–2256 K and is lower than the expected day-side temperature of bare rock with no heat redistribution (2500 K), which is indicative of an atmosphere. Our atmospheric retrieval analysis of occultation depth spectra at 4.5 µm finds that different visits statistically favour various atmospheric scenarios including a thin outgassed CO/CO2 atmosphere and a silicate rock vapour atmosphere. Some visits even support a flat line model. Conclusions. The observed variability could be explained by stochastic outgassing of CO/CO2, which is also hinted at by retrievals. Alternatively, the variability observed at both 2.1 and 4.5 µm could be the result of a circumstellar patchy dust torus generated by volcanism on the planet. [ABSTRACT FROM AUTHOR]

Among materials produced as colloidal quantum dots (CQDs), HgTe has a special status being the only material covering the whole infrared range from the visible to the THz (0.7–100 µm). This unique property resulting from its electronic structure, combined with an air stability and a capacity for charge conduction has generated consistent and massive efforts to produce and improve HgTe CQDs over the past two decades. Meanwhile, HgTe CQDs offer an infrared platform more advanced than any other colloidal alternatives in the mid‐wave infrared regarding their integration into advanced photonic and optoelectronic applications. Here, the latest developments of HgTe CQDs relative to the material's growth, electron structure modelling, its integration into photonic structures and its transfer as the active material from single element devices toward complex sensors and infrared imagers are reviewed. Finally, a discussion about the potential of this material for industry, rising new challenges beyond economical and production considerations at low technological readiness level, relative to the material and device design, is also included. [ABSTRACT FROM AUTHOR]

Juno has allowed clear, high‐resolution imaging of Io's polar volcanoes using the Jovian Infrared Auroral Mapper (JIRAM) instrument. We have used data from JIRAM's M‐band (4.78 μm) imager from 11 Juno orbits to construct a global map of volcanic flux. This map provides short‐term insight into the spatial distribution of volcanoes and the ways in which high‐ and low‐latitude volcanoes differ. Using spherical harmonic analysis, we quantitatively compare our volcanic flux map to the surface heat flow distribution expected from models of Io's tidal heat deposition (summarized in de Kleer, Park, et al. (2019, https://doi.org/10.26206/d4wc‐6v82). Our observations confirm previously detected systems of bright volcanoes at high latitudes. Our study finds that both poles are comparably active and that the observed flux distribution is inconsistent with an asthenospheric heating model, although the south pole is viewed too infrequently to establish reliable trends. Plain Language Summary: Our study uses data from an infrared camera on Juno called the Jovian Infrared Auroral Mapper (JIRAM) to image Io, the innermost Galilean moon of Jupiter. Io is the most volcanically active body in the Solar System. Io's volcanoes are powered by both the extreme tides from Jupiter and the gravitational interactions between it and Jupiter's other moons. These tides generate friction inside Io. Simulations of Io's interior suggest that, depending on how deep that friction is being generated, the surface heat flow will be higher in certain areas (de Kleer, Park, et al., 2019, https://doi.org/10.26206/d4wc‐6v82). Using JIRAM, we have mapped where volcanoes are producing the most power and compared that to where we expect higher heat flow from the interior models. Our map doesn't agree with any of these models very well. JIRAM observed more volcanic activity at the poles than we expected to see based on previous observations. However, since the south pole was only observed twice, it's possible that these observations don't represent the average volcanic activity of the south pole. Very bright volcanoes that may have been continuously active for decades were also imaged during these Juno fly‐bys, some of which are nearer the poles than the equator. Key Points: We have produced a global volcanic flux map of Io using data from 11 Juno fly‐bysOur flux map doesn't agree well with tidal heat flow models reported in de Kleer, Park, et al. (2019, https://doi.org/10.26206/d4wc‐6v82)The M‐band flux is anti‐correlated with the asthenospheric heating model and has only very weak agreement with the global magma ocean model [ABSTRACT FROM AUTHOR]

Due to the increase in 3D printing popularity, optimizing the procedure has become an important aspect of fused deposition modeling (FDM) research. As such, a numerical framework that captures the effect of all parameters involved in the process can aid in manufacturing optimization by overcoming the cost and time limitations of experimental methods. In this work, a numerical physics-based model is created that takes as input process parameters, simulates the phenomenon, and identifies the temperature history and developed mechanical stresses during printing. Initially, this model is validated through images taken from an infrared camera. Then, a design of experiments (DOE) sequence that covers the range of each input variable is created and multiple designs are evaluated. Correlations are examined and factor analysis on each output is performed indicating that material and bed temperature are the most important parameters affecting mechanical stresses, while fan speed dominates cooling. The simulation data are fed into data-driven models to provide accurate estimations on cooling duration, plastic strain, and von Misses stress and in turn aid in optimal parameter selection. This work improves existing numerical approaches by incorporating multiple process parameters and aids in digital twinning of FDM. [ABSTRACT FROM AUTHOR]

Transparent conductive oxide (TCO) thin films are highly sought-after for their unique characteristics of conducting electricity and transmitting visible light, making them ideal conductive coating materials for electronic devices. We carried out a comprehensive analysis of the deposition, optical, electrical, and structural properties of ITO and Ag/ITO thin films on glass substrates in this study. The weight ratio of the deposited metals was 1:10, 2:10, and 4:10 wt.% (Sn:In) for ITO films and 1:1:10 wt.% (Ag:Sn:In) for Ag–ITO film. The films were annealed at 300°C using a program controller furnace. We employed infrared cameras to analyze the surface temperature profiles of these thin films under external voltage supply. We also investigated the resistivity behavior of both ITO and Ag–ITO films, analyzing them with regard to Mott's variable range hopping (VRH) model and the fluctuation-induced tunneling model. Scanning electron microscope images revealed that adding Ag increased the grain size of ITO thin films. The average grain size for ITO thin film was determined as 186 nm, while it was found to be 270 nm for Ag–ITO thin film. Furthermore, incorporating Ag into the ITO thin film resulted in a reduction of 21.5% in transmittance over the complete visible range of the electromagnetic spectrum when compared to the ITO thin film without Ag as measured by ultra-visible spectrophotometer. The figure of merit was obtained as 0. 3 4 4 × 1 0 − 3 Ω − 1 for ITO and 0. 0 5 2 4 × 1 0 − 3 Ω − 1 for Ag–ITO thin films. However, the resistance of the ITO thin film was calculated to be 9.58 k Ω , while that of the Ag–ITO film was found to be 6.99 k Ω. The ITO thin film that included Ag exhibited a lower electrical resistivity due to the larger grain size caused by doped Ag atoms in the structure, leading to less electron scattering at the grain boundaries and a resulting decrease in resistivity as determined by four-point probe system. Thermal imaging camera measurements revealed that the surface temperature of the ITO thin film decreased with the addition of Ag under high voltage application, but not under low voltage. When a voltage of 350 V and 250 V was applied to the thin films, the ITO film exhibited a surface temperature of 73.9°C and 50.4°C, whereas under identical conditions, the Ag–ITO film showed a surface temperature of 62°C and 44.1°C, respectively. Furthermore, both films exhibited exponentially increasing surface temperature behavior under a certain voltage, suggesting that they have potential for transparent heaters and high-voltage/low-current applications. [ABSTRACT FROM AUTHOR]

We surveyed Cudjoe and Sugarloaf keys in Florida to estimate Odocoileus virginianus clavium (Key Deer) numbers using 14 motion-detecting infrared cameras to determine population numbers after deer had been translocated to these keys in 2005. We activated 6 cameras deployed on Sugarloaf Key and 8 cameras on Cudjoe Key on 11 March 2023 and retrieved them on 1 April 2023. We obtained 1340 and 2192 photos of Key Deer on Sugarloaf and Cudjoe keys, respectively. We individually identified 8 males on Sugarloaf Key and 15 males on Cudjoe Key by their antler configuration and considered them "marked" for a Lincoln–Petersen mark–resight population estimate. The Lincoln–Petersen method estimated 36 Key Deer on Sugarloaf Key and 74 Key Deer on Cudjoe Key. These estimates indicate the translocation thus far has been effective, but there is a need to monitor the efficacy of translocations over time to ensure the long-term viability of the species. [ABSTRACT FROM AUTHOR]

Simple Summary: Varroa destructor is a significant global honey bee parasite and the primary threat to bee health. Due to its latent lifestyle, detecting the mite in a brood requires invasive techniques. Enhancing detection methods is critical for advanced research on mite population dynamics, spread, selection efforts, and control methodologies. In this study, we employed infrared thermal imaging, a less-explored technique in apicultural studies, to detect parasitism in Apis mellifera broods. Our findings indicate that handheld infrared thermal cameras can generate adequately detailed heat maps of the hive. These maps distinctly separate cells containing honey, pollen, and brood, with stable, reproducible temperature measurements observable in late autumn. Notably, mite parasitism induces a sustained temperature increase in developing honey bee pupae, consistently detected regardless of mite numbers in the cell. This study reveals an advanced thermoregulatory behavior in the honey bee colony, manifesting as a social fever phenomenon. Further research is necessary to explore the health benefits of this behavior for bees and the negative effects on the mite. Our method, combined with the development of AI-based image evaluation software, could provide beekeepers and researchers with a valuable tool for Varroa research and bee biological studies. The Varroa destructor is the most significant bee parasite and the greatest threat to bee health all around the world. Due to its hidden lifestyle, detection within the brood cell is only possible through invasive techniques. Enhancing detection methods is essential for advancing research on population dynamics, spread, selection efforts, and control methodologies against the mite. In our study, we employed infrared imaging to measure the thermal differences in parasite and intact Apis mellifera worker broods. Experiments were conducted over two years at the MATE Kaposvár Campus in Hungary involving five beehives in 2022 and five beehives in 2023. A FLIR E5-XT WIFI handheld infrared camera was used to create a heat map of capped brood frames. Our results indicate that the resolution of these cameras is sufficient to provide detailed IR images of a bee colony, making them suitable to detect temperature differences in intact and Varroa parasitized capped brood cells. Mite parasitism causes a time-dependent and sustained temperature increase in developing bee pupae, observable regardless of mite number. Our work demonstrates two different heating patterns: hotspot heating and heating cells that are responsible for the elevated temperature of the Varroa-infested cells as a social fever response by the worker bees. Based on our results, future research combined with AI-based image evaluation software could offer beekeepers and researchers practical and valuable tools for high-throughput, non-invasive Varroa detection in the field. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to demonstrate heat transfer within oral soft tissues using different lasers under the effect of local anesthetics (LA). Methods: Bovine tongue slices were placed in between two glass slides and at a distance from a thermographic camera. In total, 2-cm-long 240 incisions were made along the surface of the tissue parallel to glass slides and the camera capture field. Incisions were performed using 445-nm and infrared (IR) lasers (970 nm and 980 nm on a continuous wave at 2W) with 320 μm-initiated (concentrated energy at the tip provided by a blue articulated paper and laser irradiation) and noninitiated (defused energy) fiber (30-sec irradiation period). LA was injected into the specimens before irradiation. The temperature changes in℃ (DT) and vertical and lateral heat transfer (in mm) were recorded at 10-sec intervals for 30 sec, using thermographic images. The amount of lateral and vertical heat transfer was measured. A repeated analysis of variance statistical comparison test was used to analyze differences between the lateral (width) and the vertical (height) heat transfer for initiated and noninitiated lasers and different lasers. Results: The maximum DT in℃ utilizing initiated tips of 970, 980, or 445 nm were 11.82 - 3.46, 7.66 - 3.24, and 18.94 - 7.01 and using noninitiated tips were 8.27 - 1.69, 8.87 - 2.40, and 12.31 - 8.65, respectively. Heat transfers (height/width) for initiated were 40.65 - 10.40/90.65 - 10.77 mm, 41.50 - 11.83/83.95 - 11.20 mm, and 33.70 - 9.10/95.10 - 11.17 mm and for noninitiated lasers were 52.95 - 6.89/96.10 - 11.17 mm, 47.75 - 7.41/93.75 - 14.96 mm, and 31.35 - 11.40/75.20 - 19.68 mm, respectively. A statistically significant difference was found between all lasers (p < 0.05) for initiated and noninitiated lasers (except for 970/980 nm for noninitiated lasers). Lower penetration depth (p < 0.05) at 445-nm diode and greater lateral heat spreading (p < 0.05) were identified under LA especially utilizing noninitiated tips without significant difference in IR lasers. Conclusions: LA might negatively influence soft tissues creating scattering when noninitiated tips are used and IR diode laser technology. [ABSTRACT FROM AUTHOR]

To investigate the effect of a pulsed Nd:YAG laser on the forearm local skin temperature (LST) and electrophysiology in healthy adults. A total of 30 healthy subjects with a mean age of 21 ± 0.74 years, mass of 63 ± 9.97 kg, and height of 163.7 ± 6.24 cm participated in this study. The anterior surface of the left non-dominant forearm was scanned with a pulsed Nd:YAG laser at 20 Jcm−2 for a total of 2000 J in 15 min. The right forearm was considered as the control and was scanned with a placebo laser for the same time as the active laser. Forearm minimal, average, and maximum LST were measured using a thermographic camera. Electrophysiological assessment of the median nerve [distal motor latency (DML), motor nerve conduction velocity (MNCV), and sensory nerve conduction velocity (SNCV)] was performed on both forearms before and after the application of the pulsed Nd:YAG laser. Paired and unpaired t tests were used to compare within and between groups, respectively. The level of significance was set at p > 0.05. There were significant increases in the minimum, average, and maximum LST, as well as the MNCV and SNCV with a significant decrease in DML after laser application compared to the control. The average increase in LST and nerve conduction velocity post-treatment was 275.55 K and 4.8 ms−1, respectively. The application of a pulsed Nd:YAG laser significantly increased the forearm LST, MNCV, and SNCV and significantly decreased the DML in healthy subjects. The average increase in the LST was 275.55 K with an average increase of 5 ms−1 in the motor and 4 ms−1 in the sensory NCVS. [ABSTRACT FROM AUTHOR]

Inspecting and maintaining power lines is essential for ensuring the safety, reliability, and efficiency of electrical infrastructure. This process involves regular assessment to identify hazards such as damaged wires, corrosion, or vegetation encroachment, followed by timely maintenance to prevent accidents and power outages. By conducting routine inspections and maintenance, utilities can comply with regulations, enhance operational efficiency, and extend the lifespan of power lines and equipment. Unmanned Aerial Vehicles (UAVs) can play a relevant role in this process by increasing efficiency through rapid coverage of large areas and access to difficult-to-reach locations, enhanced safety by minimizing risks to personnel in hazardous environments, and cost-effectiveness compared to traditional methods. UAVs equipped with sensors such as visual and thermographic cameras enable the accurate collection of high-resolution data, facilitating early detection of defects and other potential issues. To ensure the safety of the autonomous inspection process, UAVs must be capable of performing onboard processing, particularly for detection of power lines and obstacles. In this paper, we address the development of a deep learning approach with YOLOv8 for power line detection based on visual and thermographic images. The developed solution was validated with a UAV during a power line inspection mission, obtaining mAP@0.5 results of over 90.5% on visible images and over 96.9% on thermographic images. [ABSTRACT FROM AUTHOR]

Geoffroy's spider monkeys, an endangered, fast-moving arboreal primate species with a large home range and a high degree of fission–fusion dynamics, are challenging to survey in their natural habitats. Our objective was to evaluate how different flight parameters affect the detectability of spider monkeys in videos recorded by a drone equipped with a thermal infrared camera and examine the level of agreement between coders. We used generalized linear mixed models to evaluate the impact of flight speed (2, 4, 6 m/s), flight height (40, 50 m above ground level), and camera angle (−45°, −90°) on spider monkey counts in a closed-canopy forest in the Yucatan Peninsula, Mexico. Our results indicate that none of the three flight parameters affected the number of detected spider monkeys. Agreement between coders was "substantial" (Fleiss' kappa coefficient = 0.61–0.80) in most cases for high thermal-contrast zones. Our study contributes to the development of standardized flight protocols, which are essential to obtain accurate data on the presence and abundance of wild populations. Based on our results, we recommend performing drone surveys for spider monkeys and other medium-sized arboreal mammals with a small commercial drone at a 4 m/s speed, 15 m above canopy height, and with a −90° camera angle. However, these recommendations may vary depending on the size and noise level produced by the drone model. [ABSTRACT FROM AUTHOR]

In addition to sportswear and outdoor equipment, moisture-absorbent quick-drying fabrics are also widely used in everyday clothing and home textiles. In this study, three types of weft-knitted fabrics were designed using Coolmax fiber and polypropylene fiber. The Coolmax/PP fabric exhibits good stretchability with a strain of 180.5% and achieves a high cumulative individual transfer capability of 691.6%, with a water absorption rate of 50.2%/s. The moisture conductivity gradient presented good moisture and heat conductivity in a simulated human body temperature environment using an infrared camera. Furthermore, mathematical modeling was constructed and visual simulation analysis was conducted to explore moisture–thermal transfer behavior. The simulation results closely align with experimental data, providing insights into designing flexible and wearable quick-drying fabrics for thermal management. [ABSTRACT FROM AUTHOR]

High Test Peroxide (HTP) is a well-known green and energetic material, widely used in propulsion systems in a variety of applications, including hypergolic systems. This experimental work mixed fumed silica with liquid HTP to synthesize Gelled HTP (GHTP). A high-speed camera and a time-resolved infrared camera were employed to analyze liquid/gel phase mixing, ignition, and flame spread through drop tests, adopting a promising low toxicity liquid fuel as a GHTP hypergolic pair. Liquid/gel impinging jets in ambient air were also performed, simulating a basic element of a hybrid liquid/gel propulsion system. Prior to ignition, GHTP revealed a lower mixing ratio compared to HTP, which ultimately led to an ignition delay time of 20.6 ±6.4 ms, while HTP reached 14.6 ±3.7 ms when 1 wt% of catalyst was used. The flame area, used as a parameter to quantify gas-phase reaction, also showed sensitivity to liquid/gel phase mixing. Using a less concentrated HTP solution, ignition of GHTP/liquid fuel seemed to occur around 6 s faster than liquid HTP/liquid fuel in impinging jets, probably due to differences in propellant residence time and the vapor formation process. A theoretical performance analysis considering GHTP as an oxidizer in a hybrid liquid/gel hypergolic system revealed that the gelled propellant, made with the addition of 6 wt% of fumed silica, can achieve 96% of liquid HTP's specific impulse with the selected fuel. Furthermore, the theoretical density specific impulse of the hybrid gel/liquid system would significantly surpass that of the liquid/liquid system if 10 wt% of aluminum were mixed with GHTP. To take advantage of the hybrid system, a new propulsion system composed of pistons coupled to propellant tanks is proposed to properly infuse the gelled and liquid propellants. The results from this experimental work, together with theoretical analysis, suggest that the hybrid liquid/gel system may be suitable for military applications. [Display omitted] • Use of gelled hydrogen peroxide as oxidizer in hypergolic propulsion systems. • Drop and impinging jets test reveals vapor and ignition delay times with green fuel. • Analysis before and after ignition using visible and infrared high-speed cameras. • Infrared data quantifies mixing prior to ignition and flame spread. • Gelled hydrogen peroxide may ignite faster than its liquid counterpart. [ABSTRACT FROM AUTHOR]

This article discusses the use of 3D camera systems and accompanying software in physics instruction. The authors describe a Python program that can track and analyze the momentum of a midair collision between two playground balls. The program is freely available for instructors and can be used in student lab settings or as an instructor-led exercise. The article provides detailed information on the camera system used, the data collection and analysis process, and the results obtained. The authors conclude that the use of 3D cameras and tracking software expands the possibilities for physics experiments and enhances students' understanding of complex systems. [Extracted from the article]

This study analyses behavioural adaptations in a recently discovered European cave fish. Navigation in standardized labyrinth conditions was compared between this cave fish, its epigean ancestor, the European stone loach, Barbatula barbatula , and hybrid specimens. Loach behaviour was tracked and recorded using an infrared camera. In open field tests, in both dark and light conditions, cave loaches showed reduced thigmotaxis compared to the other two groups. Hybrid loaches generally showed strong avoidance of the open field, whereas epigean loaches avoided the open field more in light than in dark conditions. Other tests were performed in darkness only. Cave loaches showed more consistent lateralization in turning behaviour during exploration of the Y-maze than the other two groups, indicating a search strategy optimized for nonvisual navigation. In all groups, complex maze learning was evident in the first half of the 15 trials, with a reduction in latency of departure from the starting chamber, and in both time and track length to reach the food chamber. However, cave loaches were far more successful in finding food than were epigean loaches and hybrid loaches. When the path to the food chamber was altered, epigean loaches generally responded by changing their route, whereas cave loaches tended to continue following a previously learned path and hybrid loaches exhibited intermediate behaviours. In conclusion, the enhanced ability of cave loaches to navigating labyrinths in the dark compared to their epigean ancestor suggests the evolution of behavioural traits that optimize survival in caves. • Cave loaches showed less open field avoidance in darkness than epigean loaches. • Cave loaches showed most consistent lateralization of exploration in Y-maze test. • Cave loaches achieved greatest foraging success in darkness in complex maze. • In darkness, epigean loaches were least able to learn a complex pattern to navigate. • Hybrids' behaviours in darkness were often not intermediate of cave × epigean fish. [ABSTRACT FROM AUTHOR]