Search Results (4,856)

Outpatient neurosurgical oncology has expanded with advances in anesthesia, imaging, and minimally invasive techniques, enabling safe same-day discharge for selected patients undergoing procedures such as stereotactic biopsy and craniotomy. In this review, we find that across multiple international series, same-day discharge rates in several studies ranging from 85 to 95%, with low complication (3–6%) and readmission rates when structured pathways, including standardized selection criteria, enhanced recovery protocols, and routine 4-h postoperative CT imaging, are used. Studies on economic analyses demonstrate substantial cost savings driven by reduced inpatient bed utilization, with no increase in adverse events. Key challenges identified include medicolegal concerns amongst physicians, patient education, and limitations in organization adoption. Telemedicine and remote monitoring are increasingly incorporated to streamline preoperative evaluation and postoperative follow-up, improving access and continuity of care. Emerging technologies such as laser interstitial thermal therapy and focused ultrasound may further expand the outpatient neuro-oncology repertoire. Overall, current evidence supports outpatient neurosurgical oncology as a safe, efficient, and patient-centered model when applied with structured clinical pathways and patient selection. Full article

The canopy temperature of winter jujube serves as a direct indicator of plant water status and transpiration efficiency, making its accurate prediction a critical prerequisite for effective water management and optimized growth conditions in greenhouse environments. This study developed a data-driven model to forecast canopy temperature. The model serially integrates a Long Short-Term Memory (LSTM) network and a Random Forest (RF) algorithm, leveraging their complementary strengths in capturing temporal dependencies and robust nonlinear fitting. A three-stage framework comprising temporal feature extraction, multi-source feature fusion, and direct prediction was implemented to enable reliable nowcasting. Data acquisition and preprocessing were tailored to the greenhouse environment, involving multi-sensor data and thermal imagery processed with Robust Principal Component Analysis (RPCA) for dimensionality reduction. Key environmental variables were selected through Spearman correlation analysis. Experimental results demonstrated that the proposed LSTM–RF model achieved superior performance, with a determination coefficient (R²) of 0.974, mean absolute error (MAE) of 0.844 °C, and root mean square error (RMSE) of 1.155 °C, outperforming benchmark models including standalone LSTM, RF, Transformer, and TimesNet. SHAP (SHapley Additive exPlanations)-based interpretability analysis further quantified the influence of key factors, including the “thermodynamic state of air” driver group and latent temporal features, offering actionable insights for irrigation management. The model establishes a reliable, interpretable foundation for real-time water stress monitoring and precision irrigation control in protected winter jujube production systems. Full article

Infrared and visible image fusion (IVIF) integrates the thermal saliency of infrared images (IRs) with the structural details of visible images (VIs) to produce comprehensive scene representations. Existing methods often overemphasize one modality, leading to loss of temperature readability or visual details. To address this, we propose Wave-Cross, a wavelet-based fusion framework. Using the discrete wavelet transform (DWT), IR low-frequency sub-bands encode thermal distribution, while VI high-frequency sub-bands capture textural details. Cross-attention adaptively recombines these sub-bands, suppressing modality-specific noise and balancing complementary features. Additionally, we introduce a Heat-Consistency Loss, which enforces pixel-wise thermal ordering and local energy preservation in a self-supervised manner, ensuring the fused image retains IR interpretability while enhancing VI sharpness. Experiments on the TNO, MSRS, and M3FD datasets demonstrate the effectiveness of the proposed method. Compared with state-of-the-art baselines, Wave-Cross achieves superior performance on objective metrics such as SD, AG, SCD, SF, CC, EN, NABF, and MS-SSIM yielding clearer details and more stable thermal saliency under challenging interference conditions. These results highlight the framework’s potential for practical applications in surveillance, autonomous driving, and fault diagnosis. Full article

Produced water (PW) generated from oil and gas operations poses a significant environmental challenge due to its high salinity and complex organic–inorganic composition. This study evaluates forward osmosis (FO) as an energy-efficient approach for PW treatment by comparing a commercial cellulose triacetate (CTA) membrane and a fabricated electrospun nanofibrous membrane, both modified with a zwitterionic sulfobetaine methacrylate/polydopamine (SBMA/PDA) coating. Fourier Transform Infrared Spectroscopy (FTIR) spectra verified the successful incorporation of SBMA and PDA through the appearance of characteristic sulfonate, quaternary ammonium, and catechol/amine-related vibrations. Scanning electron microscopy (SEM) imaging revealed the intrinsic dense surface of the CTA membrane and the highly porous nanofibrous architecture of the electrospun membrane, with both materials showing uniform coating coverage after modification. Complementary analyses supported these observations: X-ray Photoelectron Spectroscopy (XPS) confirmed the presence of nitrogen, sulfur, and chlorine containing functionalities associated with the zwitterionic layer; Thermogravimetric Analysis (TGA) demonstrated that surface modification did not compromise the thermal stability of either membrane; and contact-angle measurements showed substantial increases in surface hydrophilicity following modification. Gas chromatography–mass spectrometry (GC–MS) analysis of the Permian Basin PW revealed a chemically complex mixture dominated by light hydrocarbons, alkylated aromatics, and heavy semi-volatile organic compounds. FO experiments using hypersaline PW demonstrated that the fabricated membrane consistently outperformed the commercial membrane under both MgCl₂ and Na₃PO₄ draw conditions, achieving up to ~40% higher initial water flux and total solids rejection as high as ~62% when operated with 2.5 M Na₃PO₄. The improved performance is attributed to the nanofibrous architecture and zwitterionic surface chemistry, which together reduced fouling and reverse solute transport. These findings highlight the potential of engineered zwitterionic nanofibrous membranes as robust alternatives to commercial FO membranes for sustainable produced water treatment. Full article

Predicting internal quality parameters, such as Brix and water content, of apples, is essential for quality control. Existing near-infrared (NIR) and hyperspectral imaging (HSI)-based techniques have limited applicability due to their dependence on equipment and environmental sensitivity. In this study, a transportable quality assessment system was proposed using spatiotemporal domain analysis with long-wave infrared (LWIR)-based thermal diffusion phenomics, enabling non-destructive prediction of the internal Brix of apples during transport. After cooling, the thermal gradient of the apple surface during the cooling-to-equilibrium interval was extracted. This gradient was used as an input variable for multiple linear regression, Ridge, and Lasso models, and the prediction performance was assessed. Overall, 492 specimens of 5 cultivars of apple (Hongro, Arisoo, Sinano Gold, Stored Fuji, and Fuji) were included in the experiment. The thermal diffusion response of each specimen was imaged at a sampling frequency of 8.9 Hz using LWIR-based thermal imaging, and the temperature changes over time were compared. In cross-validation of the integrated model for all cultivars, the coefficient of determination (R²_cv) was 0.80, and the RMSEcv was 0.86 °Brix, demonstrating stable prediction accuracy within ±1 °Brix. In terms of cultivar, Arisoo (Cultivar 2) and Fuji (Cultivar 5) showed high prediction reliability (R²_cv = 0.74–0.77), while Hongro (Cultivar 1) and Stored Fuji (Cultivar 4) showed relatively weak correlations. This is thought to be due to differences in thermal diffusion characteristics between cultivars, depending on their tissue density and water content. The LWIR-based thermal diffusion analysis presented in this study is less sensitive to changes in reflectance and illuminance compared to conventional NIR and visible light spectrophotometry, as it enables real-time measurements during transport without requiring a separate light source. Surface heat distribution phenomics due to external heat sources serves as an index that proximally reflects changes in the internal Brix of apples. Later, this could be developed into a reliable commercial screening system to obtain extensive data accounting for diversity between cultivars and to elucidate the effects of interference using external environmental factors. Full article

Nanoparticle-mediated photothermal conversion exploits the unique light-to-heat transduction properties of engineered nanomaterials to address challenges in energy, water, and healthcare. This review first examines fundamental mechanisms—localized surface plasmon resonance (LSPR) in plasmonic metals and broadband interband transitions in semiconductors—demonstrating how tailored nanoparticle compositions can achieve >96% absorption across 250–2500 nm and photothermal efficiencies exceeding 98% under one-sun illumination (1000 W·m⁻², AM 1.5G). Next, we highlight advances in solar steam generation and desalination: floating photothermal receivers on carbonized wood or hydrogels reach >95% efficiency in solar-to-vapor conversion and >2 kg·m⁻²·h⁻¹ evaporation rates; three-dimensional architectures recapture diffuse flux and ambient heat; and full-spectrum nanofluids (LaB₆, Au colloids) extend photothermal harvesting into portable, scalable designs. We then survey photothermal-enhanced thermal energy storage: metal-oxide–paraffin composites, core–shell phase-change material (PCM) nanocapsules, and MXene– polyethylene glycol—PEG—aerogels deliver >85% solar charging efficiencies, reduce supercooling, and improve thermal conductivity. In biomedicine, gold nanoshells, nanorods, and transition-metal dichalcogenide (TMDC) nanosheets enable deep-tissue photothermal therapy (PTT) with imaging guidance, achieving >94% tumor ablation in preclinical and pilot clinical studies. Multifunctional constructs combine PTT with chemotherapy, immunotherapy, or gene regulation, yielding synergistic tumor eradication and durable immune responses. Finally, we explore emerging opto-thermal nanobiosystems—light-triggered gene silencing in microalgae and poly(N-isopropylacrylamide) (PNIPAM)–gold nanoparticle (AuNP) membranes for microfluidic photothermal filtration and control—demonstrating how nanoscale heating enables remote, reversible biological and fluidic functions. We conclude by discussing challenges in scalable nanoparticle synthesis, stability, and integration, and outline future directions: multicomponent high-entropy alloys, modular photothermal–PCM devices, and opto-thermal control in synthetic biology. These interdisciplinary innovations promise sustainable solutions for global energy, water, and healthcare demands. Full article

The use of large-aperture scanning mirrors for high-resolution and wide-swath imaging represents a major trend in Earth observation technology. However, to improve dynamic response performance, scanning mirror assemblies are highly lightweighted, resulting in reduced overall stiffness. This makes the mirror surface susceptible to thermal and inertial loads during operation, leading to degraded surface accuracy and poor imaging quality. Moreover, dynamic scanning mirror has the multi-disciplinary coupling effects and non-circular structural characteristics. It poses significant challenges for surface figure analysis. To address these issues, this paper proposes a surface analysis method for high-dynamic scanning mirrors under multi-physics coupling in non-circular domains. First, a finite element model of the mirror assembly is established based on the minimum aperture and angular velocity parameters. Through finite element analysis, the surface response of the scanning mirror assembly under thermal loads, dynamic inertial loads, and their coupled effects is quantitatively investigated. Subsequently, an analytical approach, which combines rigid-body displacement separation and Gram–Schmidt orthogonalization, is developed to construct non-circular Zernike polynomials, enabling high-precision fitting and reconstruction of the mirror’s dynamic surface distortions. Numerical experiments validate the accuracy of the model. Results show that for a scanning mirror with an aperture of 466 mm × 250 mm under the coupled condition of a 5 °C temperature rise and 50 N·mm torque, the surface figure achieves RMS < 2 nm and PV < 22 nm, with a fitting accuracy achieves 10⁻⁶. These results verify the accuracy and reliability of the proposed method. The surface analysis approach presented in this study provides theoretical guidance and a design framework for subsequent image quality evaluation and assurance. Full article

Early and non-destructive detection of plant-parasitic nematodes is critical for implementing site-specific management in coffee production systems. This study evaluated the potential of unmanned aerial vehicle (UAV) multispectral and thermal imaging, combined with textural analysis, to detect Meloidogyne exigua infestation in Coffea arabica (Topázio variety). Field surveys were conducted in two contrasting seasons (dry and rainy), and nematode incidence was identified and quantified by counting root galls. Vegetation indices (NDVI, GNDVI, NGRDI, NDRE, OSAVI), individual spectral bands, canopy temperature, and Haralick texture features were extracted from UAV-derived imagery and correlated with gall counts. Under the conditions of this experiment, strong correlations were observed between gall number and the red spectral band in both seasons (R > 0.60), while GNDVI (dry season) and NGRDI (rainy season) showed strong negative correlations with gall density. Thermal imaging revealed moderate positive correlations with infestation levels during the dry season, indicating potential for early stress detection when foliar symptoms were absent. Texture metrics from the red and green bands further improved detection capacity, particularly with a 3 × 3 pixel window at 135°. These results demonstrate that UAV-based multispectral and thermal imaging, enhanced by texture analysis, can provide reliable early indicators of nematode infestation in coffee. Full article

The escalating volume of waste electrical and electronic equipment (WEEE) poses a significant global environmental challenge. The disassembly of printed circuit boards (PCBs), a critical step for resource recovery, remains inefficient due to limitations in the adaptability and dexterity of existing automated systems. This paper proposes an intelligent disassembly system for PCB components that integrates a multimodal large language model (MLLM) with a multi-agent framework. The MLLM serves as the system’s cognitive core, enabling high-level visual-language understanding and task planning by converting images into semantic descriptions and generating disassembly strategies. A state-of-the-art object detection algorithm (YOLOv13) is incorporated to provide fine-grained component localization. This high-level intelligence is seamlessly connected to low-level execution through a multi-agent framework that orchestrates collaborative dual robotic arms. One arm controls a heater for precise solder melting, while the other performs fine “probing-grasping” actions guided by real-time force feedback. Experiments were conducted on 30 decommissioned smart electricity meter PCBs, evaluating the system on recognition rate, capture rate, melting rate, and time consumption for seven component types. Results demonstrate that the system achieved a 100% melting rate across all components and high recognition rates (90–100%), validating its strengths in perception and thermal control. However, the capture rate varied significantly, highlighting the grasping of small, low-profile components as the primary bottleneck. This research presents a significant step towards autonomous, non-destructive e-waste recycling by effectively combining high-level cognitive intelligence with low-level robotic control, while also clearly identifying key areas for future improvement. Full article

High-power-density LED devices have emerged as a prominent focus in current research and industrial development, largely due to their role in advancing LED lighting technologies. At high power and high current, the structure and area of the thermoelectrically separated copper substrate connected to the LEDs significantly influence the device’s optoelectronic performance, yet detailed studies in this area remain limited. To address this issue, blue and white LED devices with a maximum power rating of 400 W were fabricated and soldered onto copper substrates with diameters of 20 mm, 25 mm, and 32 mm. The influence of substrate area on the I–V and I–L characteristics of the LEDs was systematically measured and analyzed at different operating temperatures. Additionally, variations in operating voltage and luminous intensity with temperature were investigated under specific driving currents. Infrared thermal imaging was employed to examine the thermal field distribution under varying substrate sizes and current levels. The results show that increasing the copper substrate diameter from 20 mm to 25 mm and further to 32 mm leads to a significant improvement in LED optoelectronic performance. To determine the diameter threshold beyond which performance gains diminish, a 3D COMSOL 6.1. model was developed. The model reveals that expanding the diameter from 32 mm to 35 mm results in only a marginal improvement, while further increasing it to 40 mm offers a negligible additional benefit, thereby identifying the optimal substrate area for performance saturation. Full article

(1) Background: Gastroretentive systems are an interesting option for enhancing the bioavailability of weak bases and poorly soluble drugs. The aim of this study was to formulate supramolecular organogels based on cinnarizine (CIN) as a potential gastroretentive system. (2) Methods: The organogels were prepared with different oils in different ratios. Thereafter, their pharmaceutical characteristics and in vitro gastric retention were evaluated through in vitro and in silico simulations. (3) Results: Organogels with different proportions of CIN to oils were successfully obtained. The DSC thermal analysis results demonstrated that all organogels showed gel–sol temperature transitions. The frequency sweep test verified that all organogels presented frequency-independent behavior. Optical imaging revealed longitudinal spherulites of the 1:4 CIN in organogels in all oils. The CIN organogels in all oils (1:4) were observed to float in gastric media during the entire release study. The pharmacokinetic parameters of CIN in peppermint oil (1:4) revealed a close Cmax value to that of the 25 mg immediate-release tablet, but a different AUC. (4) Conclusions: The organogels in all oils floated throughout the release study, establishing their potential as a gastroretentive system. Furthermore, these dosage forms were assessed as a gastric-controlled system through in silico simulations, which enabled prediction of their pharmacokinetic parameters. Full article

Pair housing has been proven to improve calves’ welfare during the pre-weaning phase, potentially promoting positive emotions. Based on the emotional valence hypothesis, according to which positive emotions are mainly processed in the left brain hemisphere, infrared thermography (IRT) may detect changes in eye temperature, particularly thermal asymmetries. This study aimed to evaluate whether pair-housed calves presented ocular thermal asymmetry, compared to individually housed calves during the pre-weaning phase. Fifty-six Friesian female calves from two commercial dairy farms were enrolled and housed either individually or in pairs from birth until 8 weeks of age. IRT images of the lacrimal caruncle of both eyes were collected at 7, 21, 35, and 56 days of age. A linear mixed model tested the effects of housing, farm, year, and timepoint. No significant effect of pair housing on ocular asymmetry emerged, while absolute eye temperatures were significantly higher in pair-housed calves. Moreover, eye temperature declined over time, suggesting reduced arousal and habituation with age. Although the lateralization hypothesis was not confirmed, the study offers insights into IRT for assessing calf emotions and supports further investigation in positive contexts to better explore links between housing, emotional valence, and brain activity. Full article

Accurate modelling of reflection, transmission, absorption, and emission at material interfaces is essential for infrared imaging, rendering, and the simulation of optical and sensing systems. This need is particularly pronounced across the short-wave to long-wave infrared (SWIR–LWIR) spectrum, where many materials exhibit dispersion- and wavelength-dependent attenuation described by complex refractive indices. In this work, we introduce a unified formulation of the full Fresnel equations that directly incorporates wavelength-dependent complex refractive-index data and provides physically consistent interface behaviour for both dielectrics and conductors. The approach reformulates the classical Fresnel expressions to eliminate sign ambiguities and numerical instabilities, resulting in a stable evaluation across incidence angles and for strongly absorbing materials. We demonstrate the model through spectral-rendering simulations that illustrate realistic reflectance and transmittance behaviour for materials with different infrared optical properties. To assess its suitability for thermal-infrared applications, we also compare the simulated long-wave emission of a heated glass sphere with measurements from a LWIR camera. The agreement between measured and simulated radiometric trends indicates that the proposed formulation offers a practical and physically grounded tool for wavelength-parametric interface modelling in infrared imaging, supporting applications in spectral rendering, synthetic data generation, and infrared system analysis. Full article

Under the influence of engineering disturbances, the loading rate of surrounding rock is in a state of continuous adjustment. This study conducts experimental investigations on the mechanical response characteristics under different strain rates (10⁻⁵ s⁻¹, 10⁻⁴ s⁻¹, and 10⁻³ s⁻¹). During the uniaxial loading process of coal–rock composite specimens, multi-parameter monitoring was implemented, and a systematic study was carried out on the ring-down count induced by microcracks, the energy values of acoustic emission (AE) events, the stage-dependent strain characteristics on the specimen surface, and the surface temperature variation characteristics. Additionally, the stress–strain curve characteristics under different strain rates were comparatively analyzed in stages. The loading process of the coal–rock composite specimens was reproduced using the Particle Flow Code (PFC3D 6.0) simulation software. The simulation results indicate that the stress–strain results obtained from the simulation are in good agreement with the laboratory test results; based on these simulation results, the energy accumulation and dissipation characteristics of the coal–rock composite specimens under the influence of strain rate were revealed. Furthermore, a microscopic damage model considering strain rate was constructed based on the Weibull probability statistics theory. The results show that strain rate has a significant impact on the strength, elastic modulus, and failure mode of the coal–rock composite specimens. At low strain rates, the specimens exhibit obvious progressive failure characteristics and strain localization phenomena, while at higher strain rates, they show brittle sudden failure characteristics. Meanwhile, the thermal imaging results reveal that at high strain rates, the overall temperature rise in the composite specimens is rapid, whereas at low strain rates, the overall temperature rise is slow—but the temperature rise in the coal portion is faster than that in the rock portion. The peak temperature at high strain rates is approximately 2 °C higher than that at low strain rates. The PFC simulation results demonstrate that the larger the strain rate, the faster the growth rate of plastic energy in the post-peak stage and the faster the release rate of elastic energy. Full article

Shape Memory Alloy (SMA) actuators offer strong potential for compact, lightweight, silent, and compliant robotic grippers; however, their practical deployment is limited by the challenge of controlling nonlinear and hysteretic thermal dynamics. This paper presents a complete Sim-to-Real control framework for precise temperature regulation of a tendon-driven SMA gripper using Deep Reinforcement Learning (DRL). A novel 12-action discrete control space is introduced, comprising 11 heating levels (0–100% PWM) and one active cooling action, enabling effective management of thermal inertia and environmental disturbances. The DRL agent is trained entirely in a calibrated thermo-mechanical simulation and deployed directly on physical hardware without real-world fine-tuning. Experimental results demonstrate accurate temperature tracking over a wide operating range (35–70 °C), achieving a mean steady-state error of approximately 0.26 °C below 50 °C and 0.41 °C at higher temperatures. Non-contact thermal imaging further confirms spatial temperature uniformity and the reliability of thermistor-based feedback. Finally, grasping experiments validate the practical effectiveness of the proposed controller, enabling reliable manipulation of delicate objects without crushing or slippage. These results demonstrate that the proposed DRL-based Sim-to-Real framework provides a robust and practical solution for high-precision SMA temperature control in soft robotic systems. Full article