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Abstract Doping silicon wafers without using highly toxic or corrosive chemical substances has become a critical issue for semiconductor device manufacturing. In this work, ultra‐thin films of hydroxyapatite (Ca5(PO4)3OH) are prepared by tethering by aggregation and growth (T‐BAG), and further processed by spike annealing. Via in situ infrared (IR), the decomposition of hydroxyapatite and intermixing with the native silicon oxide is observed already at temperatures as low as 200 °C. Phosphate transport through the native silicon oxide is driven by a phase transformation into a more stable thermal oxide. At 700 °C, diffusion of phosphorus into the sub‐surface region of oxide‐free silicon is observed. In situ IR combined with electrical impedance spectroscopy (EIS), time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS), and X‐ray photoelectron spectroscopy (XPS) measurements allows to conclude that the phosphorus is: i) transported through the silicon oxide barrier, ii)) diffused inside the oxide‐free silicon, and iii) finally modified the electrical activity of the silicon wafer. To further explain the experimental findings, density‐functional theory (DFT) is used to demonstrate the extent of the effect of phosphorus doping on the electronic nature of silicon surfaces, showing that even small amounts of doping can have a measurable effect on the electrical performance of semiconductor wafers.

BackgroundHuman milk is the best option for feeding newborns, especially premature infants. In the absence of breast milk, milk from a human milk bank can be a suitable alternative. However, the nutritional content of human milk may be insufficient to meet these high requirements and milk fortification is needed. To facilitate the implementation of simpler and faster analyzers in neonatal healthcare facilities, this study focuses on the concordance analysis of two different analyzers, one based on mid-infrared and the other on ultrasound, in comparison to the Bradford method for determining protein concentration in human milk.MethodsMature milk samples from donor mothers were collected and pasteurized at the Human Milk Bank of Barcelona and protein quantification was performed using mid-infrared (MIRIS-HMA), ultrasound (MilkoScope Julie27), and the classical Bradford reference methods. The intraclass correlation coefficient (ICC) with 95% confidence interval and Bland–Altman plots were used to assess the agreement between methods.ResultsThe mean protein concentration of 142 milk samples calculated using MIRIS-HMA, MilkoScope, and the Bradford assay were 1.38, 1.15, and 1.19 g/100 ml, respectively. The ICC was 0.70 for MIRIS-HMA vs. Bradford and 0.37 for MilkoScope vs. Bradford.ConclusionMIRIS-HMA obtained a better agreement with the Bradford technique and is a promising method for developing new devices based on MIR transmission spectroscopy principles. This study confirms how MIRIS-HMA can be used to accurately calculate the protein concentration of human milk.

ABSTRACT: Roasting is the most common processing method that enhances color, and texture. In this study, infrared roasting of peanuts was done using an infrared rotary dryer. Roasting was operated at 90% infrared power (630 W) with different rotating speed (1 and 2 r/min). The effect of roasting was studied at different moisture levels (7.66%, 11.49%, and 13.72% db). From the study, the color parameter, L* value, was found to be significantly different (P < 0.05), and it decreased with the decrease in rotating speed, and the ∆E value varies from 2.32 to 10.56. Results also showed that the antioxidant activity decreased with the reduction in rotating speed as lesser revolutions took longer roasting time, and the values decreased from 84.34% to 71.74%. Minimal changes in total phenolic content were found and varied from 3.62 to 2.10 mg/g GAE, an appropriate limit for good-quality roasted peanuts. The hardness of roasted peanuts ranged from 12.25 to 39.43 N. Moisture content 13.72%, and 1 r/min is the best possible treatment for infrared peanut roasting, significantly enhancing the quality of peanuts. This study concluded that high-power short-time infrared roasting could give good-quality roasted peanuts with optimum bioactive compounds.

Pulse Detonation Engine has been a point of interest in the propulsion industry for some time and the interest has been rising due to its better output and results. But any system can perform its task efficiently based on the efficiency of its control system. In this paper we have presented a comparative study between multiple control systems- one based on Bluetooth technology, the other based on infrared sensor technology and one based on wired electrical system. For the wireless system, the signal received from either of the media is passed to the various sensors and systems connected through an Arduino board that further controls the solenoid valves and ignition system. Primarily, a control system circuit is developed using Arduino board and different sensors to connect the fuel supply and ignition system. In the next stage, Bluetooth sensors are connected using an android app and then an infrared sensor based system is integrated with the Arduino to control the engine and the performance of the two systems are compared. Whereas for wired system, every sub system is controlled through optical wires including the solenoid valves, the injection system and the sensors.

The effects of infrared baking and microwave baking on the quality of pork tenderloin was compared by using sensory evaluation, texture, malondialdehyde, peroxide value, protein, volatile flavor substances as examination factors. The results showed that, there was no significant difference in the effect of two roasting methods on the color of pork (P>0.05). Infrared roasted pork had an average sensory score of 3.67 points higher than microwave roasted pork, but had lower hardness and chewiness. The content of malondialdehyde and peroxide value of infrared roasted pork were 16.89% and 38.36% higher than those of microwave roasted pork, respectively. The active sulfhydryl content in infrared roasted pork was significantly lower than that in microwave roasted pork (P

Infrared (IR) luminosity of lightning channel in the 3–5 μm range usually persisted throughout the entire interstroke interval, which is in contrast to the simultaneously recorded visible (0.4–0.8 μm) luminosity that always decayed to an undetectable level prior to a subsequent return stroke pulse. A longer visible luminosity period at the end of flash tended to be associated with a longer IR afterglow period following the decay of visible luminosity (and by inference current) to an undetectable level. At the end of flash, the IR luminosity persisted up to about 1 s, and the median IR afterglow duration was a factor of 10 longer than the median visible luminosity duration. The IR luminosity often exhibited a hump when the visible luminosity was monotonically decaying or undetectable, with the corresponding channel temperature being likely around 3400 K. Plain Language Summary: Lightning is usually imaged in the visible (0.4–0.8 μm) range, although it also produces significant infrared (IR) emission. In this study, we compare, for the first time, the medium‐to‐far (3–5 μm) IR luminosity of lightning channels with the simultaneously recorded visible luminosity. The key findings include the persistent nature of IR luminosity throughout interstroke intervals, which is in contrast to visible luminosity that always decayed to an undetectable level before the following return‐stroke onset. After the last stroke, IR luminosity persisted much longer than visible luminosity. The IR luminosity often exhibited a hump when visible luminosity was monotonically decreasing or already undetectable. We inferred that the IR hump, occurring when the channel temperature decreases to a few thousand Kelvin, is associated with enhanced IR emission from nitric oxide molecules whose concentration is expected to be maximum around 3400 K. We also examined a number of factors influencing IR afterglow duration, such as the number of preceding strokes, return‐stroke peak current, and the occurrence of M‐components. This study contributes to the very limited literature on the IR emission from lightning and provides new insights into the dynamics of lightning channel cooling process. Key Points: In contrast to the visible, infrared (IR) channel luminosity between strokes usually persisted through the following return‐stroke onsetIR luminosity profile often exhibited an increase (hump) when the visible luminosity was monotonically decaying or undetectableAt the end of flash, IR luminosity persisted up to ∼1 s and its median duration was a factor of 10 longer than its visible counterpart [ABSTRACT FROM AUTHOR]

In the autonomous driving industry, there is a growing trend to employ long-wave infrared (LWIR)-based uncooled thermal-imaging cameras, capable of robustly collecting data even in extreme environments. Consequently, both industry and academia are actively researching contrast-enhancement techniques to improve the quality of LWIR-based thermal-imaging cameras. However, most research results only showcase experimental outcomes using mass-produced products that already incorporate contrast-enhancement techniques. Put differently, there is a lack of experimental data on contrast enhancement post-non-uniformity (NUC) and temperature compensation (TC) processes, which generate the images seen in the final products. To bridge this gap, we propose a histogram equalization (HE)-based contrast enhancement method that incorporates a region-based clipping technique. Furthermore, we present experimental results on the images obtained after applying NUC and TC processes. We simultaneously conducted visual and qualitative performance evaluations on images acquired after NUC and TC processes. In the visual evaluation, it was confirmed that the proposed method improves image clarity and contrast ratio compared to conventional HE-based methods, even in challenging driving scenarios such as tunnels. In the qualitative evaluation, the proposed method demonstrated upper-middle-class rankings in both image quality and processing speed metrics. Therefore, our proposed method proves to be effective for the essential contrast enhancement process in LWIR-based uncooled thermal-imaging cameras intended for autonomous driving platforms. [ABSTRACT FROM AUTHOR]

Rapid and minimally destructive methods for estimating the endogenous organic content of subfossil bone save time, lab consumables, and valuable ancient materials. Fourier transform infrared (FTIR) spectroscopy is an established method to estimate bone protein content, and portable spectroscopes enable field applications. We review the ability of benchtop and portable FTIR indices to predict %N and %collagen from 137 bone specimens drawn from eight taxa. We also explore associations of these indices with the endogenous DNA content estimated for 105 specimens. Bulk bone elemental abundance and crystallinity index data reflect diagenetic alteration of these specimens, which come from a variety of depositional environments in four countries (Madagascar, Greece, Monaco, and Germany). Infrared (IR) indices from benchtop and portable units perform similarly well in predicting observed sample N content and collagen yields. Samples that include little collagen (0–5 wt%) tend to have similar IR index values, and we present a Bayesian approach for the prediction of collagen yields. Bone type best explains variation in target species DNA content (endogenous DNA being particularly abundant in petrosals), but low IR index values were consistently associated with minimal DNA content. We conclude that, although portable FTIR fails to distinguish collagen preservation among poorly preserved samples, a simple approach with minimal sample preparation can effectively screen bone from a variety of taxa, elements, and environments for the extraction of organics. [ABSTRACT FROM AUTHOR]

Significance: Biomanufacturing utilizes modified microbial systems to sustainably produce commercially important biomolecules for use in agricultural, energy, food, material, and pharmaceutical industries. However, technological challenges related to non-destructive and high-throughput metabolite screening need to be addressed to fully unlock the potential of synthetic biology and sustainable biomanufacturing. Aim: This perspective outlines current analytical screening tools used in industrial cell strain development programs and introduces label-free vibrational spectromicroscopy as an alternative contrast mechanism. Approach: We provide an overview of the analytical instrumentation currently used in the “test” portion of the design, build, test, and learn cycle of synthetic biology. We then highlight recent progress in Raman scattering and infrared absorption imaging techniques, which have enabled improved molecular specificity and sensitivity. Results: Recent developments in high-resolution chemical imaging methods allow for greater throughput without compromising the image contrast. We provide a roadmap of future work needed to support integration with microfluidics for rapid screening at the single-cell level. Conclusions: Quantifying the net expression of metabolites allows for the identification of cells with metabolic pathways that result in increased biomolecule production, which is essential for improving the yield and reducing the cost of industrial biomanufacturing. Technological advancements in vibrational microscopy instrumentation will greatly benefit biofoundries as a complementary approach for non-destructive cell screening. [ABSTRACT FROM AUTHOR]

Soil acidification is an issue for agriculture that requires effective management, typically in the form of lime (calcium carbonate, CaCO3), application. Mid infrared (MIR) spectroscopy methods offer an alternative to conventional laboratory methods, that may enable cost-effective and improved measurement of soil acidity and responses to liming, including detection of small–scale heterogeneity through the profile. Properties of an acidic soil following lime application were measured using both MIR spectroscopy with Partial Least Squares Regression (MIR-PLSR) and laboratory measurements to (a) compare the ability of each method to detect lime treatment effects on acidic soil, and (b) assess effects of the different treatments on selected soil properties. Soil properties including soil pH (in H2O and CaCl2), Aluminium (Al, exchangeable and extractable), cation exchange capacity (CEC) and organic carbon (OC) were measured at a single field trial receiving lime treatments differing in rate, source and incorporation. Model performance of MIR-PLSR prediction of the soil properties ranged from R2 = 0.582, RMSE = 2.023, RPIQ = 2.921 for Al (extractable) to R2 = 0.881, RMSE = 0.192, RPIQ = 5.729 for OC. MIR-PLSR predictions for pH (in H2O and CaCl2) were R2 = 0.739, RMSE = 0.287, RPIQ = 2.230 and R2 = 0.788, RMSE = 0.311, RPIQ = 1.897 respectively, and could detect a similar treatment effect compared to laboratory measurements. Treatment effects were not detected for MIR-PLSR-predicted values of CEC and both exchangeable and extractable Al. Findings support MIR-PLSR as a method of measuring soil pH to monitor effects of liming treatments on acidic soil to help inform precision agricultural management strategies, but suggests that some nuance and important information about treatment effects of lime on CEC and Al may be lost. Improvements to prediction model performance should be made to realise the full potential of this approach. [ABSTRACT FROM AUTHOR]

The sprouting process includes changes in nutritional, biochemical, and sensory characteristics that improve chickpea quality and increase its digestibility. Various products such as Falafel are made from ground and dried chickpea sprouts. Therefore, in this research, the use of hot air (70°C), infrared (250 W), and microwave (220 W) methods for drying ground chickpea sprouts was investigated and modeled. The drying time of the samples in the infrared dryer was shorter than the other two dryers. The average drying time of the samples in the hot air, infrared and microwave dryers was 63.3, 26.7, and 156.7 min, respectively. In this research, the effective moisture diffusivity coefficient of ground chickpea sprouts in hot air, infrared and microwave dryers was determined to be 4.99×10-9 m² s -1, 17.95×10-9 m² s -1, and 1.59×10-9 m² s -1, respectively. To study the drying kinetics of ground chickpea sprouts, Wang and Singh, Henderson and Pabis, Approximation of diffusion, Page, Newton, Midilli, and Logarithmic mathematical models were fitted to the experimental data. Finally, when modeling the drying process of this product, Midilli's mathematical model with four parameters was chosen as the best model due to its minimal error. [ABSTRACT FROM AUTHOR]

The Europa Thermal Emission Imaging System (E-THEMIS) on the Europa Clipper spacecraft will investigate the temperature and physical properties of Europa using thermal infrared (TIR) images in three wavelength bands centered from 7-14 μm, 14-28 μm and 28-80 μm. E-THEMIS will map >80% of the surface Europa at multiple times of day at a resolution of 8-km per pixel, ∼32% percent of the surface at ≤1 km/pixel resolution, and ∼6% percent at ≤100 m/pixel resolution. The specific objectives of the investigation are to 1) understand the formation of surface features, including sites of recent or current geologic activity, in order to understand regional and global processes and evolution and 2) to identify safe sites for future landed missions. E-THEMIS uses an uncooled microbolometer detector array for the IR focal plane. The E-THEMIS focal plane has 920 cross-track pixels (896 active) and 140 along-track pixels in each of the three spectral bands. The image data are collected at 14-bits per pixel at a frame rate of 60 Hz. The instrument can operate in framing mode, where full frame images are collected, and optionally co-added in time, in each band, or in time-delay-integration (TDI) mode where consecutive rows from each band are offset spatially to remove the spacecraft motion and then summed. In addition, the data in each band can be spatially aggregated from 2 × 2 to 5 × 5 pixels. These modes will be varied throughout each Europa flyby to optimize the data precision while fitting within the E-THEMIS data allocation. The expected temperature precision, measured as the noise equivalent spectral radiance, is 1.2 K at scene temperatures ≥90 K for a TDI of 16 with 4 × 4 pixel coaggregation in Band 2. The absolute accuracy at 90 K is 2−3 K in Band 2. E-THEMIS is an all-reflective, three-mirror anastigmat telescope with a 6.45-cm effective aperture and a speed of f/1.34 cross-track and 1.92 along-track. The mass of instrument Sensor Assembly, mounted on the spacecraft nadir deck, is 11.4 kg, the vault electronics are 1.8 kg, and the two are connected through a 3.1 kg harness. The Sensor volume is 23.7 cm x 31.8 cm x 29.8 cm. E-THEMIS consumes an average operation power of 34.8 W at 28 V. E-THEMIS was developed by Arizona State University with Raytheon Vision Systems developing the microbolometer focal plane assembly and Ball Aerospace developing the electronics. E-THEMIS was integrated, tested, and radiometrically calibrated on the Arizona State University campus in Tempe, AZ. [ABSTRACT FROM AUTHOR]

Background: This study used infrared thermography (IRT) for mapping the facial and ocular temperatures of howler monkeys, to determine parameters for the diagnosis of febrile processes. There are no published IRT study in this species. Methods: Were evaluated images of a group of monkeys kept under human care at Sorocaba Zoo (São Paulo, Brazil). The images were recorded during 1 year, in all seasons. Face and eye temperatures were evaluated. Results: There are statistically significant differences in face and eye temperatures. Mean values and standard deviations for facial and ocular temperature were respectively: 33.0°C (2.1) and 36.5°C (1.9) in the summer; 31.5°C (4.5) and 35.3°C (3.6) in the autumn; 30.0°C (4.3) and 35.6°C (3.9) in the winter; 30.8°C (2.9) and 35.5°C (2.1) in the spring. Conclusions: The IRT was effective to establish a parameter for facial and ocular temperatures of black‐and‐gold howler monkeys kept under human care. [ABSTRACT FROM AUTHOR]

In this study, we innovatively propose salience-combined map and gradientlet filter for infrared and visible image fusion. It can enhance the infrared image of the target and also retain more detailed textures. First, our method is based on a multi-scale decomposition framework and gradientlet filter to decompose the source graph into approximate layers and residual layers. The approximate layers preserve smooth areas of the source images without edge blurring. The residual layers reflect the small gradients and noise of the source image. Since the texture part of the residual layer is weak, we introduce a Gamma-enhanced gradient map to complement the texture. The initial fusion image can be obtained by fusing the approximate layers and the residual layers. The salience-combined map directly extracts salient objects from infrared images according to pixel threshold segmentation, and extracts background information other than objects from visible images. Then the salience-combined map is used to guide the initial fusion image to get the final image. In our qualitative analysis, we compared our method against 5 traditional methods and deep learning-based methods. In the quantitative assessment, utilizing 29 pairs of randomly selected source images, our algorithm distinctly showcased absolute superiority across various metrics, including EN, SF, AG, and FD. The aforementioned results affirm that our method ensures the generation of fused images with clear targets and rich details. [ABSTRACT FROM AUTHOR]

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Unmanned Aerial Vehicle (UAV) infrared detection has problems such as weak and small targets, complex backgrounds, and poor real-time detection performance. It is difficult for general target detection algorithms to achieve the requirements of a high detection rate, low missed detection rate, and high real-time performance. In order to solve these problems, this paper proposes an improved small target detection method based on Picodet. First, to address the problem of poor real-time performance, an improved lightweight LCNet network was introduced as the backbone network for feature extraction. Secondly, in order to solve the problems of high false detection rate and missed detection rate due to weak targets, the Squeeze-and-Excitation module was added and the feature pyramid structure was improved. Experimental results obtained on the HIT-UAV public dataset show that the improved detection model's real-time frame rate increased by 31 fps and the average accuracy (MAP) increased by 7%, which proves the effectiveness of this method for UAV infrared small target detection. [ABSTRACT FROM AUTHOR]

Simple Summary: The poultry industry is advancing through a focus on nutrition, management practices, and technology to enhance productivity by improving feed conversion ratios, disease control, lighting management, and exploring antibiotic; alternatives. Infrared (IR) radiation, with wavelengths ranging from 760 to 10,000 nm, is being used to improve the well-being of humans, animals, and poultry. IR applications like heating, spectroscopy, beak trimming, and other therapies offer health benefits such as improved skin health, wound healing, and enhanced immune responses. In poultry production, IR radiation positively impacts growth performance, gut health, blood profiles, and food safety. Despite its benefits, applications of IR in poultry are limited but show promise for wider adoption. This innovative approach has the potential to revolutionize traditional practices in the industry by optimizing productivity and efficiency while improving animal welfare. The poultry industry is dynamically advancing production by focusing on nutrition, management practices, and technology to enhance productivity by improving feed conversion ratios, disease control, lighting management, and exploring antibiotic alternatives. Infrared (IR) radiation is utilized to improve the well-being of humans, animals, and poultry through various operations. IR radiation occurs via electromagnetic waves with wavelengths ranging from 760 to 10,000 nm. The biological applications of IR radiation are gaining significant attention and its utilization is expanding rapidly across multiple sectors. Various IR applications, such as IR heating, IR spectroscopy, IR thermography, IR beak trimming, and IR in computer vision, have proven to be beneficial in enhancing the well-being of humans, animals, and birds within mechanical systems. IR radiation offers a wide array of health benefits, including improved skin health, therapeutic effects, anticancer properties, wound healing capabilities, enhanced digestive and endothelial function, and improved mitochondrial function and gene expression. In the realm of poultry production, IR radiation has demonstrated numerous positive impacts, including enhanced growth performance, gut health, blood profiles, immunological response, food safety measures, economic advantages, the mitigation of hazardous gases, and improved heating systems. Despite the exceptional benefits of IR radiation, its applications in poultry production are still limited. This comprehensive review provides compelling evidence supporting the advantages of IR radiation and advocates for its wider adoption in poultry production practices. [ABSTRACT FROM AUTHOR]

Many rocks, minerals, and soil types reflect short-wave infrared (SWIR) imagery (900–2500 nm) in distinct ways, and geologists have long relied on this property to aid in the mapping of differing surface lithologies. Although surface archaeological features including artifacts, anthrosols, or structural remains also likely reflect SWIR wavelengths of light in unique ways, archaeological applications of SWIR imagery are rare, largely due to the low spatial resolution and high acquisition costs of these data. Fortunately, a new generation of compact, drone-deployable sensors now enables the collection of ultra-high-resolution (<10 cm), hyperspectral (>100 bands) SWIR imagery using a consumer-grade drone, while the analysis of these complex datasets is now facilitated by powerful imagery-processing software packages. This paper presents an experimental effort to develop a methodology that would allow archaeologists to collect SWIR imagery using a drone, locate surface artifacts in the resultant data, and identify different artifact types in the imagery based on their reflectance values across the 900–1700 nm spectrum. Our results illustrate both the potential of this novel approach to exploring the archaeological record, as we successfully locate and characterize many surface artifacts in our experimental study, while also highlighting challenges in successful data collection and analysis, largely related to current limitations in sensor and drone technology. These findings show that as underlying hardware sees continued improvements in the coming years, drone-acquired SWIR imagery can become a powerful tool for the discovery, documentation, and analysis of archaeological landscapes. [ABSTRACT FROM AUTHOR]

A device that can dynamically control the reflection, transmission, and absorption of infrared thermal radiation is essential for the development of a broad range of infrared (IR) technologies. However, realizing efficient thermal emission regulation is challenging due to the inherent complexity or limitation in traditional radiative materials or structures. Here, we design a memristor-type, tunable IR emissivity device composed of an indium tin oxide/tungsten trioxide/gold (ITO/WO3/Au) nanoscale multilayer structure. The device exhibits resonant characteristics in optics and memristive behavior in electronics, as evidenced by the results of both optical and electrical analyses. The emissivity variation of the proposed device is 0.32 in the range of 2.5–25 μm. Moreover, a transparent memristor-type device was fabricated and combined with a V2O5–WO3-based electrochromic device to decouple the IR emissivity and visible color, enabling tunable visible-infrared compatible applications. This investigation will provide a novel nanoscale design approach for dynamic thermal emission control in fundamental science and can significantly benefit a number of applications, including energy-efficient thermoregulation, information encryption, thermal signature masking, and radiative cooling. [ABSTRACT FROM AUTHOR]

Face recognition has been well studied under visible light and infrared (IR) in both intra-spectral and cross-spectral cases. However, how to fuse different light bands for face recognition, i.e., hyperspectral face recognition, is still an open research problem, which has the advantages of richer information retention and all-weather functionality over single-band face recognition. Thus, in this research, we revisit the hyperspectral recognition problem and provide a deep learning-based approach. A new fusion model (named HyperFace) is proposed to address this problem. The proposed model features a pre-fusion scheme, a Siamese encoder with bi-scope residual dense learning, a feedback-style decoder, and a recognition-oriented composite loss function. Experiments demonstrate that our method yields a much higher recognition rate than face recognition using only visible light or IR data. Moreover, our fusion model is shown to be superior to other general-purpose image fusion methods that are either traditional or deep learning-based, including state-of-the-art methods, in terms of both image quality and recognition performance. [ABSTRACT FROM AUTHOR]

Due to a legacy originating in the limited capability of early computers, the spectroscopic resolution used in Fourier transform infrared spectroscopy and other systems has largely been implemented using only powers of two for more than 50 years. In this study, we investigate debunking the spectroscopic lore of, e.g., using only 2, 4, 8, or 16 cm−1 resolution and determine the optimal resolution in terms of both (i) a desired signal-to-noise ratio and (ii) efficient use of acquisition time. The study is facilitated by the availability of solids and liquids reference spectral data recorded at 2.0 cm−1 resolution and is based on an examination in the 4000–400 cm−1 range of 61 liquids and 70 solids spectra, with a total analysis of 4237 peaks, each of which was also examined for being singlet/multiplet in nature. Of the 1765 liquid bands examined, only 27 had widths <5 cm−1. Of the 2472 solid bands examined, only 39 peaks have widths <5 cm−1. For both the liquid and solid bands, a skewed distribution of peak widths was observed: For liquids, the mean peak width was 24.7 cm−1 but the median peak width was 13.7 cm−1, and, similarly, for solids, the mean peak width was 22.2 cm−1 but the median peak width was 11.2 cm−1. While recognizing other studies may differ in scope and limiting the analysis to only room temperature data, we have found that a resolution to resolve 95% of all bands is 5.7 cm−1 for liquids and 5.3 cm−1 for solids; such a resolution would capture the native linewidth (not accounting for instrumental broadening) for 95% of all the solids and liquid bands, respectively. After decades of measuring liquids and solids at 4, 8, or 16 cm−1 resolution, we suggest that, when accounting only for intrinsic linewidths, an optimized resolution of 6.0 cm−1 will capture 91% of all condensed-phase bands, i.e., broadening of only 9% of the narrowest of bands, but yielding a large gain in signal-to-noise with minimal loss of specificity. [ABSTRACT FROM AUTHOR]

Infrared analysis reveals the presence of interwoven inclusions, primarily comprised of silicon nitride and silicon carbide, in the casting process of monocrystalline silicon ingots. This study investigates how the longitudinal temperature gradient affects the removal of inclusions during the casting of monocrystalline silicon ingots through simulations and comparative experiments. Two monocrystalline silicon ingots were cast, each using different longitudinal temperature gradients: one employing smaller gradients and the other conventional gradients. CGSim (Version Basic CGSim 23.1) simulation software was utilized to analyze the melt flow and temperature distribution during the growth process of quasi–monocrystalline silicon ingots. The findings indicate that smaller longitudinal temperature gradients lead to a more robust upward flow of molten silicon at the solid–liquid interface, effectively carrying impurities away from this interface and preventing their inclusion formation. Analysis of experimental photoluminescence and IR results reveals that although inclusions may not be observed, impurities persist but are gradually displaced to the top of the silicon melt through a stable growth process. [ABSTRACT FROM AUTHOR]

Retro-reflective materials are gradually increasing in popularity and use due to their safety properties, and aesthetic advantages. This study details an experimental procedure of the functional performance of silver (Ag), stainless steel (SS), and titanium (Ti) coatings of 150 nm in thickness on retro-reflective fabrics (with plain, twill and diamond weave structures) via magnetron sputtering. The deposited thin films were characterised using CIE L* a* b* values, SEM, contact angle, air permeability, thermal conductivity, anti-static, IR and UV protection. The results reveal that Ag coated fabric can transfer away body heat, hence ensuring a feeling of coolness. The Ag coated fabric samples have an overall good infrared (IR) protective property followed by SS, with Ti having a poor IR protective performance. All of the coated fabrics show excellent ultraviolet protection with 50+ UPF ratings. Furthermore, the coated fabrics have good anti-static properties which prevent the build-up of static charge that can cause discomfort to the wearer, especially in dry weather conditions. The deposition of Ag, SS or Ti nanoparticles on the surface of the fabric increases the hydrophobicity of the material or results in a fabric with low wettability as evident from the measured contact angles. [ABSTRACT FROM AUTHOR]

Solution‐processed low‐bandgap semiconductors are crucial to next‐generation infrared (IR) detection for various applications, such as autonomous driving, virtual reality, recognitions, and quantum communications. In particular, III–V group colloidal quantum dots (CQDs) are interesting as nontoxic bandgap‐tunable materials and suitable for IR absorbers; however, the device performance is still lower than that of Pb‐based devices. Herein, a universal surface‐passivation method of InAs CQDs enabled by intermediate phase transfer (IPT), a preliminary process that exchanges native ligands with aromatic ligands on the CQD surface is presented. IPT yields highly stable CQD ink. In particular, desirable surface ligands with various reactivities can be obtained by dispersing them in green solvents. Furthermore, CQD near‐infrared (NIR) photodetectors are demonstrated using solution processes. Careful surface ligand control via IPT is revealed that enables the modulation of surface‐mediated photomultiplication, resulting in a notable gain control up to ≈10 with a fast rise/fall response time (≈12/36 ns). Considering the figure of merit (FOM), EQE versus response time (or −3 dB bandwidth), the optimal CQD photodiode yields one of the highest FOMs among all previously reported solution‐processed nontoxic semiconductors comprising organics, perovskites, and CQDs in the NIR wavelength range. [ABSTRACT FROM AUTHOR]

Occupational exposure to airborne dust is responsible for numerous respiratory and cardiovascular diseases. Because of these hazards, air samples are regularly collected on filters and sent for laboratory analysis to ensure compliance with regulations. Unfortunately, this approach often takes weeks to provide a result, which makes it impossible to identify dust sources or protect workers in real time. To address these challenges, we developed a system that characterizes airborne dust by its spectro-chemical profile. In this device, a micro-cyclone concentrates particles from the air and introduces them into a hollow waveguide where an infrared signature is obtained. An algorithm is then used to quantitate the composition of respirable particles by incorporating the infrared features of the most relevant chemical groups and compensating for Mie scattering. With this approach, the system can successfully differentiate mixtures of inorganic materials associated with construction sites in near-real time. The use of a free-space optic assembly improves the light throughput significantly, which enables detection limits of approximately 10 µg/m3 with a 10 minute sampling time. While respirable crystalline silica was the focus of this work, it is hoped that the flexibility of the platform will enable different aerosols to be detected in other occupational settings. [ABSTRACT FROM AUTHOR]

Simple Summary: Osteoarthritis is a leading cause of lameness and joint disease in horses. A simple, economical, and accurate diagnostic test is required to routinely screen horses for OA. The study assessed the accuracy of infrared (IR) spectroscopy in analyzing synovial fluid (SF) to identify horses with early inflammatory changes related to equine carpal osteoarthritis (OA). OA was surgically induced in one group of horses while the others were allocated as controls. SF samples were collected before OA induction and weekly until 63 days. IR spectroscopy was used to analyze the SF samples, and predictive models were created to classify the samples. Overall, the accuracy for distinguishing between joints with OA and any other joint was 80%. Results show that IR spectroscopy could classify samples based on the day they were collected with 87% accuracy. Distinguishing between OA vs. OA Control and OA vs. Sham joints had lower accuracies of 75% and 70%, respectively. The authors conclude that IR spectroscopy accurately discriminates between SF in joints with induced OA and controls. Osteoarthritis is a leading cause of lameness and joint disease in horses. A simple, economical, and accurate diagnostic test is required for routine screening for OA. This study aimed to evaluate infrared (IR)-based synovial fluid biomarker profiling to detect early changes associated with a traumatically induced model of equine carpal osteoarthritis (OA). Unilateral carpal OA was induced arthroscopically in 9 of 17 healthy thoroughbred fillies; the remainder served as Sham-operated controls. The median age of both groups was 2 years. Synovial fluid (SF) was obtained before surgical induction of OA (Day 0) and weekly until Day 63. IR absorbance spectra were acquired from dried SF films. Following spectral pre-processing, predictive models using random forests were used to differentiate OA, Sham, and Control samples. The accuracy for distinguishing between OA and any other joint group was 80%. The classification accuracy by sampling day was 87%. For paired classification tasks, the accuracies by joint were 75% for OA vs. OA Control and 70% for OA vs. Sham. The accuracy for separating horses by group (OA vs. Sham) was 68%. In conclusion, SF IR spectroscopy accurately discriminates traumatically induced OA joints from controls. [ABSTRACT FROM AUTHOR]

Temperature and water vapor play crucial roles in the Earth's climate system, and it is important to understand and monitor the variation in the thermodynamic profile within the lower troposphere. Among various observation platforms for understanding the vertical structure of temperature and humidity, ground-based Fourier-transform infrared (FTIR) can provide detailed information about the lower troposphere by complementing the limitations of radiosonde or satellite methods. However, these ground-based systems have limitations in terms of cost, operation, and mobility. Herein, we introduce a cost-effective and easily deployable FTIR observation system designed to enhance monitoring capabilities for atmospheric conditions. The atmospheric downwelling radiance spectrum of sky is measured by applying a real-time radiative calibration using a blackbody. From the observed radiance spectrum, the thermodynamic profile (temperature and the water vapor mixing ratio) of the lower troposphere was retrieved using an algorithm based on the optimal estimation method (OEM). The retrieved vertical structure results in the lower troposphere were similar to the fifth-generation reanalysis database (ERA-5) of the European Center for Medium-range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction final analysis (NCEP FNL). This provides a potential possibility for monitoring atmospheric conditions by a compact FTIR system. [ABSTRACT FROM AUTHOR]

Scrotal surface thermography is a non-invasive method for assessing testicular thermoregulation in stallions; however, few studies have explored the application of this technique concerning the thermal physiology of equine reproductive systems. This study aimed to evaluate the consistency of testicular thermoregulation in stallions over a year using thermography to measure the scrotal surface temperature (SST). Moreover, we assessed the best region for measuring the surface body temperature compared with the SST. Ten light-breed stallions were used in the experiment. Thermographic images of the scrotal and body surfaces (neck and abdomen) were captured. Fresh, cooled and frozen-thawed semen samples were evaluated to verify the impact of thermoregulation on semen quality. Testicular thermoregulation was maintained throughout the year in stallions amidst changes in the external temperature, as evidenced by the weak correlation between the SST and ambient temperature. A lower correlation was observed between the environmental temperature and body surface temperature (BTS) obtained from the abdomen (BTS-A; R = .4772; p < .0001) than with that obtained from the neck (BTS-N; R = .7259; p < .0001). Moreover, both BTS-A and SST were simultaneously captured in a single image. The consistent quality of the fresh, cooled and frozen semen suggests efficient thermoregulation in stallions throughout the year. [ABSTRACT FROM AUTHOR]

The MAJIS (Moons And Jupiter Imaging Spectrometer) instrument on board the ESA JUICE (JUpiter ICy moon Explorer) mission is an imaging spectrometer operating in the visible and near-infrared spectral range from 0.50 to 5.55 μm in two spectral channels with a boundary at 2.3 μm and spectral samplings for the VISNIR and IR channels better than 4 nm/band and 7 nm/band, respectively. The IFOV is 150 μrad over a total of 400 pixels. As already amply demonstrated by the past and present operative planetary space missions, an imaging spectrometer of this type can span a wide range of scientific objectives, from the surface through the atmosphere and exosphere. MAJIS is then perfectly suitable for a comprehensive study of the icy satellites, with particular emphasis on Ganymede, the Jupiter atmosphere, including its aurorae and the spectral characterization of the whole Jupiter system, including the ring system, small inner moons, and targets of opportunity whenever feasible. The accurate measurement of radiance from the different targets, in some case particularly faint due to strong absorption features, requires a very sensitive cryogenic instrument operating in a severe radiation environment. In this respect MAJIS is the state-of-the-art imaging spectrometer devoted to these objectives in the outer Solar System and its passive cooling system without cryocoolers makes it potentially robust for a long-life mission as JUICE is. In this paper we report the scientific objectives, discuss the design of the instrument including its complex on-board pipeline, highlight the achieved performance, and address the observation plan with the relevant instrument modes. [ABSTRACT FROM AUTHOR]

The growing need for the multiband photodetection of a single scene has promoted the development of both multispectral coupling and broadband detection technologies. Photodetectors operating across the infrared (IR) to terahertz (THz) regions have many applications such as in optical communications, sensing imaging, material identification, and biomedical detection. In this review, we present a comprehensive overview of the latest advances in broadband photodetectors operating in the infrared to terahertz range, highlighting their classification, operating principles, and performance characteristics. We discuss the challenges faced in achieving broadband detection and summarize various strategies employed to extend the spectral response of photodetectors. Lastly, we conclude by outlining future research directions in the field of broadband photodetection, including the utilization of novel materials, artificial microstructure, and integration schemes to overcome current limitations. These innovative methodologies have the potential to achieve high-performance, ultra-broadband photodetectors. [ABSTRACT FROM AUTHOR]

Crowds can lead up to severe disasterous consequences resulting in fatalities. Videos obtained through public cameras or captured by drones flying overhead can be processed with artificial intelligence-based crowd analysis systems. Being a hot area of research over the past few years, the goal is not only to identify the presence of crowds but also to predict the probability of crowd-formation in order to issue timely warnings and preventive measures. Such systems will significantly reduce the probablity of the potential disasters. Developing effective systems is a challenging task, especially due to factors such as naturally occuring diverse conditions, variations in people or background pixel areas, noise, behaviors of individuals, relative amounts/distributions/directions of crowd movements, and crowd building reasons. This paper proposes an infrared video processing system based on U-Net convolutional neural network for crowd monitoring in infrared video frames to help estimate the people crowd with normal or abnormal trends. The proposed U-Net architecture aims to efficiently extract crowd features, achieve sufficient people marking-up accuracy, competitively with optimal network configurations in terms of the depth and number of filters to consequently minimise the number of coefficients. For further faster processing, hardware resources/implementation area savings, and lower power, the optimized network coefficients measured are represented in Canonic-Signed Digit with minimal number of nonzero (± 1) digits, minimizing the number of underlying shift-add/subtract operations of all multipliers. The achieved significantly reduced computational cost makes the proposed U-Net effectively suitable for resource-constrained and low power applications. [ABSTRACT FROM AUTHOR]

Autonomous driving does not imply self-driving vehicles; self-driving vehicles are the final evolution level of autonomous driving. Autonomous driving aims to add more benefits and features to the vehicle, including driver assistance technologies and automated driving systems. Object detection is a fundamental pillar in the autonomous vehicle industry. Recently, thermal imaging is increasingly gaining an essential role in autonomous driving. The use of a thermal camera in the sensor suite of an automotive vehicle has become more and more popular to increase reliability for robust and safe operation. Thermal imaging can detect the infrared radiation heat emitted by objects. Therefore, a thermal camera can outperform other sensors, such as LiDAR, radar, and RGB, in adverse lighting conditions. In this work, we study object detection in thermal imaging. We propose the Multi-Domain Feature Fusion Thermal Detector (MDFFTDet) framework that fuses the thermal weights with the RGB weights using only thermal images from the FLIR ADAS dataset. The proposed framework inherits the architecture of EfficientDet and further proposes a technique for the feature fusion of two different modalities: thermal and RGB. We use UNIT GAN for the image-to-image translation task to generate pseudo-RGB images from the input thermal images. The proposed framework could tackle the problem of the lack of large datasets in the thermal domain and improve detection accuracy. The experimental results on the FLIR ADAS dataset demonstrate that the proposed framework outperforms the detection accuracy of other state-of-the-art object detectors in thermal imagery, achieving this using much fewer parameters and FLOPS. Two variants of the framework, MDFFTDet-D0 and MDFFTDet-D2, are proposed, achieving mAP of 63.15% and 77.81%, respectively. On the other hand, EfficientDet-D0 and EfficientDet-D2, which are used as a baseline for the proposed frameworks, achieved mAP of 59.4% and 69.12%, respectively. [ABSTRACT FROM AUTHOR]

Pulse Detonation Engine has been a point of interest in the propulsion industry for some time and the interest has been rising due to its better output and results. But any system can perform its task efficiently based on the efficiency of its control system. In this paper we have presented a comparative study between multiple control systems- one based on Bluetooth technology, the other based on infrared sensor technology and one based on wired electrical system. For the wireless system, the signal received from either of the media is passed to the various sensors and systems connected through an Arduino board that further controls the solenoid valves and ignition system. Primarily, a control system circuit is developed using Arduino board and different sensors to connect the fuel supply and ignition system. In the next stage, Bluetooth sensors are connected using an android app and then an infrared sensor based system is integrated with the Arduino to control the engine and the performance of the two systems are compared. Whereas for wired system, every sub system is controlled through optical wires including the solenoid valves, the injection system and the sensors. [ABSTRACT FROM AUTHOR]

PurposeTo describe the construction and diagnostic accuracy of a modularized, virtual reality (VR)-based, pupillometer for detecting relative afferent pupillary defect (RAPD) in unilateral optic neuropathies, vis-à-vis, clinical grading by experienced neuro-ophthalmologists.MethodsProtocols for the swinging flashlight test and pupillary light response analysis used in a previous stand-alone pupillometer was integrated into the hardware of a Pico Neo 2 Eye® VR headset with built-in eye tracker. Each eye of 77 cases (mean ± 1SD age: 39.1 ± 14.9yrs) and 77 age-similar controls were stimulated independently thrice for 1sec at 125lux light intensity, followed by 3sec of darkness. RAPD was quantified as the ratio of the direct reflex of the stronger to the weaker eye. Device performance was evaluated using standard ROC analysis.ResultsThe median (25th – 75th quartiles) pupil constriction of the affected eye of cases was 38% (17 – 23%) smaller than their fellow eye (p

Abstract A straightforward analytical approach is proposed for the design of minimally thin metal absorbers. Unlike traditional resonant design principles, where shape, size, and periodicity of a nanostructured film determine the absorption properties, this study uses only the thickness and permittivity (i.e., sheet conductivity) of the material at hand to demonstrate maximal absorption in the minimal possible thickness at any given wavelength in planar layers – guided by only the derived material‐agnostic equations. An alternative mechanism is further proposed and experimentally demonstrated to obtain precise control over the sheet conductivity of metal films necessary for such designs using metal dilution, enabling the tuning of both the amplitude and the phase of reflected waves. Finally, the concept of “phase doping” is proposed and experimentally demonstrated, wherein an ultrathin metal layer is placed within the spacer of the absorber cavity, which spectrally tunes the absorption feature without changing the spacer thickness or participating in the absorption. By judiciously combining the dilution of the absorbing and phase layers, a multifunctional ultrathin absorber architecture is demonstrated with customizable amplitude, spectral position, and selectivity, all leveraging the same vertical stack. These findings are promising for the design of ultrasensitive detectors, thermal emitters, and nonlinear optical components.

The nanoscale structure and dynamics of proteins on surfaces has been extensively studied using various imaging techniques, such as transmission electron microscopy and atomic force microscopy (AFM) in liquid environments. These powerful imaging techniques, however, can potentially damage or perturb delicate biological material and do not provide chemical information, which prevents a fundamental understanding of the dynamic processes underlying their evolution under physiological conditions. Here, we use a platform developed in our laboratory that enables acquisition of infrared (IR) spectroscopy and AFM images of biological material in physiological liquids with nanometer resolution in a cell closed by atomically thin graphene membranes transparent to IR photons. In this work, we studied the self-assembly process of S-layer proteins at the graphene-aqueous solution interface. The graphene acts also as the membrane separating the solution containing the proteins and Ca2+ ions from the AFM tip, thus eliminating sample damage and contamination effects. The formation of S-layer protein lattices and their structural evolution was monitored by AFM and by recording the amide I and II IR absorption bands, which reveal the noncovalent interaction between proteins and their response to the environment, including ionic strength and solvation. Our measurement platform opens unique opportunities to study biological material and soft materials in general.

Context. One of the long-term goals of exoplanet science is the atmospheric characterization of dozens of small exoplanets in order to understand their diversity and search for habitable worlds and potential biosignatures. Achieving this goal requires a space mission of sufficient scale that can spatially separate the signals from exoplanets and their host stars and thus directly scrutinize the exoplanets and their atmospheres.Aims. We seek to quantify the exoplanet detection performance of a space-based mid-infrared (MIR) nulling interferometer that measures the thermal emission of exoplanets. We study the impact of various parameters and compare the performance with that of large single-aperture mission concepts that detect exoplanets in reflected light.Methods. We have developed an instrument simulator that considers all major astrophysical noise sources and coupled it with Monte Carlo simulations of a synthetic exoplanet population around main-sequence stars within 20 pc of the Sun. This allows us to quantify the number (and types) of exoplanets that our mission concept could detect. Considering single visits only, we discuss two different scenarios for distributing 2.5 yr of an initial search phase among the stellar targets. Different apertures sizes and wavelength ranges are investigated.Results. An interferometer consisting of four 2 m apertures working in the 4–18.5 μ.m wavelength range with a total instrument throughput of 5% could detect up to ≈550 exoplanets with radii between 0.5 and 6 R⊕ with an integrated S/N ≥ 7. At least ≈160 of the detected exoplanets have radii ≤1.5 R⊕. Depending on the observing scenario, ≈25–45 rocky exoplanets (objects with radii between 0.5 and 1.5 R⊕) orbiting within the empirical habitable zone (eHZ) of their host stars are among the detections. With four 3.5 m apertures, the total number of detections can increase to up to ≈770, including ≈60–80 rocky eHZ planets. With four times 1 m apertures, the maximum detection yield is ≈315 exoplanets, including ≤20 rocky eHZ planets. The vast majority of small, temperate exoplanets are detected around M dwarfs. The impact of changing the wavelength range to 3–20 μm or 6–17 μm on the detection yield is negligible.Conclusions. A large space-based MIR nulling interferometer will be able to directly detect hundreds of small, nearby exoplanets, tens of which would be habitable world candidates. This shows that such a mission can compete with large single-aperture reflected light missions. Further increasing the number of habitable world candidates, in particular around solar-type stars, appears possible via the implementation of a multi-visit strategy during the search phase. The high median S/N of most of the detected planets will allow for first estimates of their radii and effective temperatures and will help prioritize the targets for a second mission phase to obtain high-S/N thermal emission spectra, leveraging the superior diagnostic power of the MIR regime compared to shorter wavelengths.

Abstract Background Thermography is an industrial method for surface temperature measurements, and although it is medically safe and non-invasive, its place in daily practice has been limited. With the development of technology, thermal cameras have become more accessible and practical via adaptation to mobile phones. Among patients evaluated with bilateral nerve conduction studies (NCS) for suspected carpal tunnel syndrome (CTS), those with electrophysiological findings consistent with mild-to-moderate unilateral CTS were accepted for this prospective study. The hands with positive NCS findings were the study group, and the unaffected hands were the control group. The images were evaluated with the thermal analysis software (FLIR Tools ver. 6.4, Windows 10) and compared with NCS for statistical significance. In addition, thermal images were examined by three orthopaedic surgeons, and interobserver correlation was analyzed. Our study aims to evaluate the mobile phone-assisted thermal camera (FLIR One Pro, FLIR Systems, Wilsonville, OR, USA) as a suitable tool to diagnose CTS. Results 48 patients, 35 women and 13 men were included in the study. Bilaterally, a total of 96 hands were evaluated. 18 patients had mild, and 30 patients had moderate NCS stages unilaterally. The mean temperature difference at the region of interest in the palm, first and third fingers were statistically significant between the study and control groups (p

The next generation of infrared (IR) sensors may enable unprecedented applications in fields like spectroscopy, health monitoring, and communication systems. For instance, metasurface-enhanced micro-electromechanical system (MEMS)-based IR sensors have demonstrated excellent performance in terms of responsivity and spectral-selectivity. However, it is burdensome to experimentally determine the performance limits of this and other IR sensing technologies as it requires time-consuming and expensive systematic testing not always feasible in research settings. To address this challenge, an automated solution for characterizing miniaturized sensing devices is presented in this paper and applied to experimentally determine the performance limits of MEMS-based IR sensors. The system offers low-cost, rapid, and automated characterization of on-chip IR sensors, determining key performance metrics such as noise, responsivity, and noise-equivalent power. The platform is flexible, easily adapted to different types of devices, chip layouts, and light sources, and is designed to test a large number of sensors within the same wafer −spending ~20 seconds per device− using a combination of optical and radiofrequency interrogation techniques. The system has been applied to test over 1500 MEMS-based IR sensors. Collected data revealed hidden trade-offs between responsivity and noise with respect to the device thickness and allowed a statistical analysis of sensing response versus device geometrical dimensions. The best-performing devices exhibit a quality factor, responsivity, fluctuation induced noise, and noise-equivalent power of 2391, 164 Hz/nW, 0.257 Hz/ $\sqrt {\mathbf {Hz}}$ , and 5.01 pW/ $\sqrt {\mathbf {Hz}}$ respectively. The proposed automated platform provides an efficient and cost-effective solution for characterizing the next generation of IR sensing devices.

Facial expression recognition (FER) is one of the best non-intrusive methods for understanding and tracking mood and mental states. In this study, we propose early and late fusion methods to recognize five facial expressions (angry, happy, neutral, sad, and surprised) using different combinations from a publicly available database (VIRI) with visible, infrared, and multispectral dynamic imaging (MSX) images and the (NVIE) database. A distinctive feature is the use of concatenation and combining techniques to combine ResNet-18 with transfer learning (TL) to create a model that is significantly more accurate than individual models. In the early fusion, we concatenated features from the modalities and classified facial expressions (FEs). In the late fusion, we combined the outputs of the modalities using weighted sums. For this purpose, we used different weighting factors depending on the accuracy of the individual models. The experimental results demonstrated that the proposed model outperformed the previous works by providing an accuracy of 83.33% when we trained the model (1-step training). Through further fine-tuning (3-step training), we obtained an improved performance of 84.44%. We conducted additional experiments by combining them with another modality (MSX) available in the database. By performing experiments with an additional modality (MSX), we obtained improved performance, which confirms that the additional modality combined with existing modalities can help improve the performance of fusion models for facial expression recognition. We also experimented by changing the backbones (Vgg-16, ShuffleNetv2, MobileNetv2, and GhostNet) in addition to ResNet-18 for visible and MSX data. ResNet-18 outperformed the other backbones in facial expression recognition for visible and MSX data.

Abstract Metamaterials and metasurfaces of artificial micro-/nano- structures functioning from microwave, terahertz, to infrared regime have enabled numerous applications from bioimaging, cancer detection and immunoassay to on-body health monitoring systems in the past few decades. Recently, the trend of turning metasurface devices flexible and stretchable has arisen in that the flexibility and stretchability not only makes the device more biocompatible and wearable, but also provides unique control and manipulation of the structural and geometrical reconfiguration of the metasurface in a creative manner, resulting in an extraordinary tunability for biomedical sensing and detection purposes. In this Review, we summarize recent advances in the design and fabrication techniques of stretchable reconfigurable metasurfaces and their applications to date thereof, and put forward a perspective for future development of stretchable reconfigurable metamaterials and metasurfaces.