Search Results (1,816)

Climate warming in Mediterranean vineyards accelerates grape ripening and increases the incidence of sunburn and berry shriveling, leading to imbalances in grape composition and wine quality. This study evaluated the combined effects of a non-positioned training system (asymmetric sprawl) and foliar application of kaolin particle film on vine microclimate, agronomic performance and wine aroma profile in a Syrah cv. vineyard under warm conditions. Vine canopy temperature was monitored by UAV thermography at veraison and harvest, while grape damage, yield components and vegetative balance were assessed at harvest. Wines obtained from each treatment were analysed for chemical composition, volatile compounds and sensory attributes. Kaolin application significantly reduced canopy temperature, particularly under water-limited conditions at veraison (up to 1.9 °C), and the combination with sprawl training decreased the proportion of sunburnt and shrivelled clusters. These microclimatic modifications were associated with higher ethanol content, improved colour intensity and increased total polyphenol index in wines. The combined strategy also enhanced the concentration of key aroma compounds, especially terpenes and fruity esters, resulting in higher values of citrus, floral and fruity aromatic series. Sensory evaluation confirmed a better overall appreciation of wines produced from vines managed with both practices. Overall, the integration of canopy architecture modification and reflective particle film represents an effective strategy to mitigate heat stress effects in warm viticultural regions, improving grape physiological performance and contributing to the preservation of wine aromatic quality under climate change scenarios. Full article

Small- and mid-sized municipalities increasingly need to assess the long-term effectiveness of urban greening projects under climate change, but typically lack the resources for extensive measurement campaigns or complex simulation infrastructure. We propose and demonstrate a practical three-component assessment framework that can be deployed with limited resources: one or two UAV thermal surveys to capture the spatial baseline, a small network of fixed monitoring stations for temporal context, and a single microscale model to project future scenarios. We apply this framework to a 0.5 ha parking-to-park conversion in Aalen, Germany (pop. 68,000). A diurnal drone survey (four flights over 14 h) established surface temperature contrasts of up to 34 K between sealed and tree-shaded areas. Six fixed stations operating over six weeks confirmed that an existing mature linden reduced hot days by nearly 50%. The ASMUS_green microscale model, evaluated against the drone observations (mean absolute difference 3.4 K across surface types), was then used to project Physiologically Equivalent Temperature (PET) under EURO-CORDEX scenarios for 2035 (+1.3 K) and 2055 (+2.5 K) combined with tree growth. The results show that young trees provide limited near-term relief, but mature canopy reduces PET by 6–8 K, offsetting the projected warming. We discuss how each component compensates for the limitations of the others, making the combined framework more robust than any single method. The approach is designed to be transferable to other municipalities facing similar planning decisions with comparable resource constraints. Full article

The integration of artificial intelligence (AI) into the diagnosis and prognosis of heart diseases is transforming cardiovascular and cardiac healthcare, improving predictive accuracy, and personalizing treatment plans. This review presents a novel contribution by providing a comprehensive overview of both diagnosis and prognosis in heart diseases through AI, covering ML and DL models. Following the PRISMA guidelines, a total of 84 recent research articles sourced from significant journals are reported. A bibliometric analysis using the VOSviewer tool was performed to map the impact of AI, enabling a detailed examination of academic connections and contributions. The findings reveal that DL models were employed 63% for diagnosis tasks, while ML models were utilized in 37% of the studies. Key recommendations include the incorporation of essential model evaluation metrics, as clinical validation indicators, integrating explainable artificial intelligence (XAI) to improve the transparency and interpretability of models, and adopting standardized frameworks to enable smooth clinical integration. This review highlights the potential of AI to improve cardiac and cardiovascular diagnosis and prognosis, providing an overview of its strengths, limitations, challenges and the possible application as AI-driven tools in patient monitoring and to support specialists in the decision-making process. Full article

Infrared thermography provides key information for a wide range of diagnostic applications within built and natural environments. As thermal states are changing with ambient conditions, it is important to deploy thermal imaging systems and operators opportunistically. It is therefore an attractive proposition to make these systems more affordable and accessible. Low-cost thermal sensors generally produce low-resolution outputs. To increase data density across large subjects, diagnosticians may create image mosaics from multiple overlapping thermographs. The registration of individual inputs into large mosaics is aided by the acquisition of additional sensor data (photographs and depthmaps), which can provide critical spatial references. In many cases, the materials inherent to the modern built environment present challenges to traditional data registration workflows between multiple sensor streams. Mobile devices offer an opportunity to innovate in the creation of these mosaics, integrating rapid geospatial mapping functionality with radiometric thermography within a 3D context. In this paper the authors evaluate the FLIR One Pro thermal camera module along with iOS/iPhone specific rapid mapping capabilities, and present a methodology: (1) introducing a workflow for the integration of short-range (within 0.3–5 m capture distance) iPhone mobile sensor data into modeling pipelines; (2) introducing a calibration model enabling effective registration and fusion of multi-modal inputs from the iPhone mobile sensor stack and FLIR One thermographic module; and (3) detailing an alternative open-source methodology for the evaluation and translation of thermographic imagery for multi-sensor fusion. The end product of this pipeline is a 3D radiometric thermographic mosaic: a spatially continuous, textured surface model in which hundreds of individual low-resolution thermographs are fused into a single queryable output retaining full 16-bit temperature values at every point. All datasets have been made openly available and the two case studies used in this paper have been made accessible at full resolution for interactive 3D online viewing. Full article

Artificial Intelligence of Things (AIoT) technologies shifted the structure of production systems, enabling the development of more intelligent, connected and sustainable manufacturing environments. However, some industrial sectors, such as aerospace manufacturing industry, fell behind in the adoption of these new technologies, mainly because of the high safety standards, strict reliability requirements and long lifespan of aircraft components. Due to low production volumes and complex manufacturing processes, this sector relies heavily on weakly automated legacy machines and production systems. This article proposes a methodology to ease the integration of AIoT technologies for retrofitting legacy industrial equipment in the aeronautical domain in order to achieve the requirements of modern industrial production systems, enabling the development of more flexible, efficient and interconnected manufacturing environments. The proposed methodology is validated through a case study where the Smart Retrofitting of a legacy aeronautical industrial machine is carried out. The case study focuses on the development of an AIoT-based architecture to implement a predictive maintenance system through vibration and infrared thermography monitoring. A three layer architecture is proposed based on Edge/Fog/Cloud Computing paradigms. A hybrid communication architecture is used, combining wired technologies for critical real-time control tasks and wireless technologies for enhanced flexibility and scalability. The results demonstrate the viability of the proposed methodology for retrofitting legacy aircraft manufacturing systems. Full article

Laser-based Powder Bed Fusion (LPBF) enables the fabrication of complex metal components but often results in high porosity and microdefect densities, compromising fatigue performance despite acceptable static properties. Standard fatigue characterisation methods are time-consuming and costly and yield scattered results due to defect-induced brittleness and residual stresses. This study investigates the application of thermographic techniques as a rapid alternative for evaluating the intrinsic fatigue behaviour of tensile coupons fabricated by LPBF employing AISI 316L steel. By monitoring surface temperature during stepwise static monotone and fatigue loading, thermographic methods aim to detect early hints of heat dissipation associated with microdamage initiation. Approaches based on temperature harmonic analysis have been implemented, allowing near-real-time and full-field mapping of stress distribution and damage development. Results show that harmonic metrics correlate with the material state and effectively track the thermoelastic effect-induced temperature changes. Some evidence is found regarding the onset of intrinsic heat dissipation, which needs to be confirmed by more focused and extensive experimental tests. Full article

Landfills are a significant source of atmospheric emissions associated with the decomposition of organic waste; however, conventional monitoring methods typically have limited spatial coverage. This study evaluates the use of an UAV-based system for the spatial characterization of gases associated with biogas emissions at a municipal landfill. A DJI Matrice 350 RTK platform equipped with a Sniffer4D Mini2 multi-gas station and a Zenmuse H20T thermal camera were used. Four flight campaigns were conducted at an altitude of 20 m, with an acquisition frequency of approximately 1 Hz, recording total hydrocarbons (C_xH_y) as an indirect indicator of methane (CH₄), carbon dioxide (CO₂), carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂), oxygen (O₂), temperature, and relative humidity. The results showed a marked transition around 13:10 h, characterized by a simultaneous increase in CH₄ equivalent and CO₂, along with a decrease in NO₂, O₃, and SO₂. Furthermore, CH₄ equivalent and CO₂ showed the highest positive correlation among the variables (r = 0.96). Spatial maps generated using ordinary kriging revealed more heterogeneous patterns, while the qualitative thermal orthophoto confirmed the site’s surface variability. Overall, the results demonstrate that the integration of multi-gas sensors and aerial thermography on UAVs is viable for the spatial monitoring of landfills. Full article

Thermal management is critical for maintaining the safety and performance of lithium-ion batteries. Phase change materials (PCMs) have been widely studied as passive cooling media due to their high latent heat capacity, but major technical challenges remain due to their relatively low thermal conductivity and nanoparticle sedimentation in composite systems. In this work, a composite phase change material (PCM) consisting of paraffin wax, a microencapsulated phase change material (MicroPCM 28D), and nano carbon black is developed to enhance thermal stability and suppress particle sedimentation through increased viscosity of the PCM matrix. Five capsule geometries fabricated by fused filament fabrication (FFF) 3D printing are experimentally investigated under airflow velocities ranging from 0 to 10 m s⁻¹. Wind tunnel experiments with infrared thermography are used to evaluate the thermal response of the PCM capsules. The results show that airflow velocity and capsule geometry strongly influence heat dissipation behavior. Compared with conventional wax composites, the MicroPCM 28D composite capsules reduce peak temperature by approximately 2–4 °C under airflow velocities of 0–10 m/s. These findings provide insights into geometry-regulated convection and stable composite PCM design for lithium-ion battery thermal management systems. Full article

Background/Objectives: Vasomotor symptoms (hot flashes) affect 70–80% of menopausal women, significantly impairing quality of life. Current treatments include hormone therapy, which is contraindicated for many patients, and non-hormonal alternatives with limited efficacy or adverse effects. Cannabidiol (CBD), a non-psychoactive phytocannabinoid, has emerged as a potential therapeutic candidate due to its interaction with the endocannabinoid system. This study aimed to investigate whether a standardized Cannabis sativa extract containing isolated CBD attenuates heat dissipation in ovariectomized rats, a preclinical model of estrogen deficiency. Methods: Female Wistar rats were randomly assigned to sham-operated vehicle-treated (SHAM-V), ovariectomized vehicle-treated (OVX-V), or ovariectomized CBD-treated (OVX-CBD; 10 mg/kg/day, oral gavage) groups. Treatment began on postoperative day 2 and continued for 21 days. Tail-skin temperature, a surrogate marker of heat dissipation, was assessed by infrared thermography on day 14. Energy metabolism was evaluated by indirect calorimetry on day 21. Uterine weight was measured as a biomarker of estrogen depletion. Results: Ovariectomy significantly increased tail temperature compared to SHAM-V. CBD treatment completely prevented this effect, with OVX-CBD animals exhibiting thermographic profiles similar to SHAM-V. Uterine atrophy was not reversed by CBD. No differences in the calorimetry parameter were observed among groups. Conclusions: This study provides novel preclinical evidence that cannabidiol attenuates ovariectomy-induced heat dissipation in rats, without detectable effects on uterine weight or metabolic parameters. These findings suggest that CBD may represent a potential non-hormonal approach for the management of menopausal vasomotor symptoms; however, further studies are required to elucidate the underlying mechanisms and to determine its translational and clinical relevance. Full article

Enzootic nasal adenocarcinoma is a contagious neoplasm of goats for which early antemortem diagnosis remains challenging under field conditions. This study evaluated the diagnostic accuracy of infrared nasal thermography for detecting the disease using histopathology as the reference standard. Eighty-six goats from a dairy herd with confirmed enzootic nasal adenocarcinoma were examined by infrared thermography one day prior to slaughter under standardized environmental conditions. Thermal images of the ethmoidal region were qualitatively assessed for asymmetry or focal hyperthermia. Following slaughter, all heads underwent systematic necropsy and bilateral histopathological examination. Twenty-three goats (26.7%) were histologically confirmed as positive with confirmation by RT-PCR (Reverse Transcriptase Polymerase Chain Reaction) from tissue samples. Infrared thermography showed a sensitivity of 82.6% and a specificity of 90.5%, with an overall diagnostic accuracy of 88.4%. Positive and negative predictive values were 76.0% and 93.4%, respectively. Agreement between thermography and histopathology was substantial (Cohen’s κ = 0.711; p < 0.001). Although thermography did not achieve the specificity of macroscopic post-mortem examination, its non-invasive and rapid nature supports its potential as a preliminary complementary antemortem screening approach, although its applicability at herd level requires validation in broader and more representative populations. Full article

Infrared thermography is a non-contact tool for monitoring inflammatory processes in the diabetic foot, but quantitative bedside use remains challenging with low-cost thermal infrared cameras due to radiometric drift, non-uniformity (vignetting), geometric distortions, and visible–thermal parallax. This paper presents an end-to-end clinical and instrumental framework built around a cheap thermal camera to ensure reproducible acquisition and physically consistent temperature estimation. The approach combines a standardized mobile acquisition setup and measurement protocol, extraction of embedded radiometric data from raw images, radiometric inversion with atmospheric correction, vignette correction performed in the radiometric domain, and geometric calibration of both visible and infrared sensors using dedicated (thermal) calibration targets. Accurate visible–infrared registration is obtained from hybrid heated markers, enabling reliable overlay and downstream analysis. The full processing chain yields quantitative thermograms with radiometric errors below 0.15 °C and sub-pixel multimodal alignment, supporting the detection of clinically relevant plantar temperature asymmetries and paving the way for routine calibrated low-cost thermography in diabetic foot care. Full article

The Qianlong Stone Classics are the largest and best-preserved ensemble of officially commissioned stone inscriptions of Confucian classics extant, yet their stele bases are currently threatened by salt efflorescence. Fluctuations in ambient temperature and humidity contribute significantly to this deterioration. Taking Stele 17 as a representative case, this study assesses the risks of surface condensation and moisture-induced salt phase transitions through integrated temperature–humidity monitoring, infrared thermography, and soluble salt analysis. The risk of condensation remains low under typical conditions, as the stele base surface temperature exceeds the dew point by at least 0.5 °C. However, risks of salt deliquescence and hydration are substantial. The stone surface contains elevated levels of soluble salts, including four highly soluble species (sodium sulfate, calcium nitrate, sodium nitrate, and sodium chloride) and one moderately soluble species (calcium sulfate). Deliquescence phase transition humidities are approximately 50.5% for calcium nitrate, 74.3% for sodium nitrate, and 75.4% for sodium chloride, while sodium sulfate exhibits a hydration phase transition near 81%. Exhibition Hall humidity fluctuates around these critical thresholds, driving repeated dissolution–crystallization and hydration–dehydration cycles that progressively erode the stone microstructure. These hygrothermal cycles exhibit pronounced seasonal patterns, with frequent air-conditioning operation in summer amplifying thermal and humidity impacts. This study elucidates an air-moisture-driven salt deterioration mechanism distinct from classical capillary rise, clarifies the persistent progression of efflorescence in transitional seasons, and provides a scientific basis for optimizing environmental control strategies. Full article

With the growing trend toward insulator hybridization, higher requirements are imposed on the synergistic improvement of interfacial durability and pollution flashover performance. Machining annular grooves at the green-body stage and embedding silicone rubber enables the construction of an embedded structure with improved durability, forming hydrophilic/hydrophobic alternating surfaces. However, the outdoor insulation characteristics of such hybrid surfaces remain insufficiently investigated, and their engineering feasibility requires further validation. In this study, a series of hydrophilic/hydrophobic alternating surfaces were fabricated, and artificial pollution tests were conducted. The results show that the AC pollution flashover voltage exhibits a saturated increasing trend as the hydrophobic interfaces become more dispersed. When twenty 4 mm wide hydrophobic interfaces were distributed along a 16 cm creepage distance, the flashover voltage was 12.4% higher than that of a fully hydrophobic surface. These results indicate that appropriate design of hydrophobic interface distribution can achieve excellent pollution flashover performance even at relatively low hydrophobic coverage (≤50%). High-speed imaging combined with infrared thermography reveals the discharge mechanism governed by hydrophobic interface distribution from an electro–thermal coupling perspective. The coexistence of multiple dry bands induced by discrete hydrophobic interfaces is identified as the key factor enhancing flashover withstand capability. A static pollution flashover model was established to quantitatively estimate the AC flashover voltage, confirming the external insulation feasibility of the embedded hybrid concept. Full article

The growing demand for energy-efficient buildings and the urgent need to retrofit aging infrastructure have driven increased interest in advanced diagnostic technologies. Among these, unmanned aerial vehicle (UAV)-based infrared thermography (IRT) has emerged as a promising non-destructive technique for assessing the thermal performance of building envelopes. This review examines recent developments and applications of dynamic infrared thermography (IRT) in the building sector for both qualitative and quantitative thermal assessment, based on previously conducted studies. It highlights the increasing adoption of integrated UAV-based IRT for building inspection and diagnostics, and critically reviews the operational, technical, and methodological advancements in dynamic thermography achieved over the past decade. Furthermore, the review presents a comprehensive framework for operational planning, encompassing environmental conditions, infrared camera configuration, and optimal UAV flight parameters. The key findings identify major challenges associated with dynamic IRT applications, particularly those related to measurement accuracy that currently limit its use for quantitative assessments and synthesize proposed methodologies to address these limitations. The review also highlights the absence of standardized procedures for determining emissivity and reflected apparent temperature in dynamic measurement setups and discusses potential approaches to overcome these gaps. Finally, it outlines priority directions for future research to support the reliable and consistent application of dynamic IRT in quantitative analysis and provides a reference for energy auditors and thermography practitioners to inform the selection of appropriate procedures for accurately quantifying heat loss in building envelopes. Full article

This study aimed to describe how to train dromedary camels to self-load and unload using positive-reinforcement-based training and to examine its effects on behavior and welfare. Twelve camels, six unbroken male camels (group A) and six broken mixed-gender camels (group B), underwent nine days of positive reinforcement training, after an initial day of behavioral tests. The training session included six phases: loading the clicker, approaching the truck, ramp, truck, unloading, and returning to the station. Eye temperature was measured before and after training using infrared thermography, and training was recorded for further behavioral analysis. Overall, eight camels (66.7%) loaded and unloaded successfully at least once. The average total and daily training duration were 72 and 8.5 min per camel, respectively, with the fastest camel able to load taking only 30 min of total training over five days. Loading the clicker phase decreased by 41% per additional training day (p < 0.001) and was higher in camels that completed the training session compared to unsuccessful individuals (p = 0.027). Similarly, the time required to approach the truck decreased significantly across training days (p < 0.001). Training day had no effect on the duration of the ramp phase; however, this phase was overall shorter in the group of successful camels (p = 0.038). Loading inside the truck increased by 50% with each additional training day (p = 0.007). Camels in group B had significantly lower maximum eye temperatures than those in group A (p = 0.019), with no significant effect of day or time (p = 0.373). In conclusion, our study shows that training dromedary camels to self-load and unload is possible and does not increase eye temperature. It could mitigate transport stress, improving the safety of handlers and camels. Full article