The recyclable paper based on photochromic materials not only reduces the pollution in the paper manufacture process, but also reduces the pollution caused by the use of ink, which receives wide attention. In this paper, a serial of PMoA-PWA/ZnO/PVP hybrid films which had different ratio of PMoA/PWA was prepared by the ultrasonic composite method. The results indicated that the hybrid film prepared when the ratio of PMoA to PWA was 3 had the best photochromic performance. In this system, ZnO was the photosensitizer while PMoA/PWA was the chromophore. The photochromic mechanism of PMoA-PWA/ZnO/PVP hybrid film was based on the photogenerated electron transfer mechanism. ZnO generated photoelectron under the excitation of visible light, then PMoA and PWA obtained the photoelectron and produced photoreduction reaction to generate heteropolyblue. The visible light photochromic paper was prepared by loaded PMoA-PWA/ZnO/PVP hybrid film (A3) on A4 paper. Application test showed that the prepared paper had extremely stable, excellent and reversible visible light photochromic properties, whether it was printing patterns or words and could replace the ordinary paper to realize the reuse of paper.

The retinal pigment epithelium (RPE) is a monolayer of epithelial cells lying between the neural retina and the choroid and is essential for photoreceptor function and viability. Quail Coturnix japonica is a convenient experimental animal model for the study of age and pathological retina processes to an accelerated time regime. The three main types of pigment granules present in the RPE are melanin-containing melanosomes, lipofuscin-containing lipofuscin granules, and mixed melanolipofuscin granules containing both melanin and lipofuscin. It’s known that with aging and pathology in RPE cells the content of melanosomes decreases but lipofuscin and melanolipofuscin granules accumulate. We examined melanolipofuscin granules in macular areas of the quail retina by transmission electron microscopy in young, middle-aged, and old birds, and in middle-aged birds irradiated with blue LED light (450 nm, 4 J/cm2). It has been shown that during photooxidative stress caused by the action of blue light on the quail eye, active fusion of melanosomes and lipofuscin granules occurs with formation of various types, including giant, mixed melanolipofuscin-like granules. Irradiation result in almost twofold decrease in the number of lipofuscin granules and synchronous increase in the number of melanolipofuscin-like granules. Increased accumulation of melanolipofuscin-like granules was also observed in non-irradiated old birds. It is assumed that the decrease in the number of melanosomes in the RPE during aging and photo-oxidative stress is associated with their fusion with lipofuscin granules and subsequent degradation of melanin by reactive oxygen species formed in melanolipofuscin-like granules. The disappearance of melanin deprives the RPE cells of light-filtering and antioxidant protection, and significantly increases the risk of their oxidative stress.

Today, there are commercially available high-performance electric wheelchairs, capa-ble of responding to strong limitations. However, despite these advancements, there is a significant portion of the population with severe disabilities who cannot access this mobility solution due to safety reasons. Indeed, either due to motor issues preventing reliable control of the wheelchair's commands, or associated visual or cognitive pathologies, the use of an electric wheelchair by these individuals would put them at risk and could also constitute a danger to those around them. This is why our research team is working on the development of augmented wheelchairs that allow a greater autonomy. We are mainly developing a system compatible with all electric wheel-chairs on the market, capable of making them anti-collision and anti-fall on uneven ground (sidewalks, stairs, etc.). In this article, we present our solution regarding the anti-collision function, in particular the sensors used to do this, as well as the strategy. We will focus on the shortcomings and weaknesses of various types of sensors and demonstrate how, by combining them in a certain way, we can develop a collision avoidance device capable of managing the diversity of everyday life situations. The two types of sensors that will be combined here are an in-house developed special near infrared sensor from the laboratory and a commercially available ultrasonic sensor. We will present the internal operation of the sensors, their limitations, experimental tests involving integration with the wheelchair, and the structure of the complete device.

We report a novel dual-band barrier infrared detector (DBIRD) design using type-II superlattices (T2SLs). The DBIRD structure consists of back-to-back barrier diodes: a "blue channel" (BC) diode which has an nBp architecture, an n-type layer of larger bandgap for absorbing blue band infrared/barrier/p-type layer, and a "red channel" (RC) diode which has an pBn architecture, a p-type layer of smaller bandgap for absorbing red band infrared/barrier/n-type layer. Each has a unipolar barrier using a T2SL lattice matched to a GaSb substrate to impede the flow of majority carriers from the absorbing layer. Each channel in the DBIRD can be independently accessed with a low bias voltage, as is preferable for high-speed thermal imaging. Device modeling of DBIRDs and simulation results of the current-voltage characteristics under dark and illuminated conditions are also presented. They predict that dual-band operation of the DBIRD will produce low dark currents and 27-33% quantum efficiencies for the in-band photons in the BC with λc=5.58 μm, and a nearly-constant 33% in the RC with λc=8.05 μm. The spectral quantum efficiency of the BC for 500 K blackbody radiation is approximately 20% over the range of λ=3 − 4.2 μm, while that of the RC has a peak of 42% at 5.7 μm. The DBIRD may provide improved high-speed dual-band imaging in comparison with NBn dual-band detectors.

The SBA-15 loaded with methylene blue was successfully prepared by sample adsorption of methylene blue in SBA-15 and is characterized by an XRD, SEM, FTIR, and BET. The photocatalytic activity for methyl orange (MO) degradation was investigated under visible light irradiation under LEDs. Experimental results demonstrate that the SBA-15-MB exhibited higher photocatalytic activity than SBA-15 under visible light irradiation. The degradation efficiency of MO (50 ppm) by SBA-15-MB could reach 80% within 180 min under 25W LED visible light. The photocatalytic activity of SBA-15 could be attributed to the excitation of methylene blue by visible light, the transfer of electrons from methylene blue to SBA-15, and the production of radicals at the surface of SBA-15.

Hyperspectral imaging data holds great potential for the different stages of the mining life cycle in active and post-mining environments. However, the technology has yet to reach the stage of large-scale industrial implementation and acceptance. While hyperspectral satellite imagery can achieve high spectral resolution, signal-to-noise ratio (SNR) and global availability with break-through satellite systems like EnMAP, EMIT and PRISMA, limited spatial resolution poses chal-lenges for sectors like mining, which require decimetre to centimetre scale resolution for applica-tions such as reconciliation, ore/waste estimates, geotechnical assessments and environmental monitoring. Hyperspectral imaging from drones (referred to herein as Uncrewed Aerial Systems; UASs) offers high spatial resolution data relevant to the camp/ mine scale, with the capability for frequent, user-defined re-visit times. This has been made possible by the miniaturization of hy-perspectral imaging systems. Collection of data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions enables the detection of different minerals and surface altera-tion patterns potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. In this paper, we provide a review of relevant studies de-ploying hyperspectral imaging in or applicable to the mining sector, especially for the use of hy-perspectral VNIR-SWIR Uncrewed Aerial Systems. Where required, we draw on previous in-sights derived from satellite or ground-based systems. We also discuss UAS survey planning, and sampling considerations for validation and interpretation.

Nepal, primarily an agricultural country, heavily relies on agricultural residue and fuelwood for daily energy requirements. In 2022, total energy consumption was 640 PJ, with traditional sources accounting for 64.17%, and fuelwood comprising 58.53% of total fuel consumption. The estimated potential supply of agricultural residue is 26 million tonnes, yielding about 442 million GJ of energy in 2021. Biomass trading often emphasizes volume or weight, necessitating a rapid and non-destructive assessment of energy properties for mutual benefit, aiding in the identification, management, and utilization of biomass sources. In this study, 200 biomass samples were collected in two batches (126 and 74 samples) from various locations in Nepal. Using Partial Least Squares Regression (PLSR), a model was developed correlating higher heating value (HHV) from a bomb calorimeter and spectral data from Fourier Transform near-infrared spectroscopy (FT-NIRS) (3595 – 12,489 cm-1) sensor. PLSR models incorporated raw spectra, eight preprocessing techniques, the multi-preprocessing five-range method, and a genetic algorithm. Outliers in the first batch were identified, and the first batch divided into an 80% calibration set and a 20% validation set, while the second batch was designated as an unknown sample set. The optimum PLSR model, utilizing first derivative preprocessing, improved accuracy by 6.77%, with coefficients of determination in the calibration set, validation set, and unknown set as 0.9694, 0.9578, and 0.8089, respectively. Root mean square errors were 132.4790 J/g, 189.4800 J/g, and 360.8845 J/g for the calibration set (RMSEC), validation set (RMSEP), and unknown set (RMSEUN), respectively. The prediction to deviation ratio (RPD) for the validation set and unknown set was 4.9 and 2.4, respectively. The cross validation model of combined sample data of every sets showed the R2CV of 0.95 and RPDCV of 4.6 indicating the model could serve as a reliable and swift non-destructive alternative for evaluating biomass HHV using NIRS and ready for updating for industrial use. However, incorporating a larger number of representative samples is crucial to enhance accuracy and develop a more comprehensive global model for predicting biomass HHV.

Background. Escalating global plastic production, expected to reach 34,000 million tons by 2050, poses a significant threat to human and environmental well-being, particularly in aquatic ecosystems. Microplastics (MP) and nanoplastics (NP), which originate from the degradation of plastics, are of concern due to their potential bioaccumulation and uptake of pollutants. This study addresses identification methods and focuses on insect meal, a raw material for aquaculture feed. Methods. By using different techniques, the study was able to detect MP and NP in insect meal samples. Chemical digestion with KOH at 60°C efficiently removed organic matter without affecting the synthetic polymer polyethylene (PE). Filtration, confocal Raman microscopy, SEM and TEM were used for comprehensive analysis and integrity tests on PE films were performed using Raman and FTIR spectroscopy. The results showed the presence of PE microplastic particles in the insect meal, which was confirmed by correlative Raman and SEM mapping on a positively charged surface. In addition, the increased resolution of the Raman microscope identified submicrometric PE NP (800 nm). Transmission electron microscopy (TEM) with energy dispersive X-ray spectroscopy (EDX) confirmed plastic-like structures in the insect meal, highlighting the presence of PE plastics characterized by irregular shapes and some agglomeration. The higher carbon concentration in the EDX analysis supported the plastic nature, which was also confirmed by Raman spectroscopy. Conclusions. The study provides a robust method for the detection of MP and NP in insect meal and provides valuable insight into the possible presence of plastics in insect-based aquafeeds. The combination of different analytical methods increases the reliability of the results and sets the stage for future investigations that could focus on the quantification of NP and the assessment of their potential environmental impact.

Water pollution is the main problem in the current scenario which is being faced by mankind due to the industrial and commercial effects. Industrial effluents contain heavy metals and inorganic ions like nitrates and phosphate ions. These ions are being included in waterways through industrial runoff. When the concentration of these hazardous pollutants increases in aquatic flora and fauna causes severe health problems. So remediation of these toxicants from water reserves is of chief importance. Conventional processes along with modern processes are being used for the treatment of industrial wastes. Photo-degradation is a modern method used for the degradation of inorganic ions due to its environmentally friendly nature and cost-effectiveness. In a recent study Aluminum oxide (Al2O3) nanoparticles were synthesized via a green approach at different pH by using Cymbopogan citratus (lemongrass) plant extract and these nanoparticles were used for the removal of inorganic ions from wastewater. The nanoparticles of different pH showed different % degradation of the inorganic ions in acidic medium removal of inorganic waste was less, in basic media % degradation was more as compared to acidic media but maximum % degradation was observed in neutral media like that average % degradation 91% and 81% was observed for nitrate and phosphate ions. The maximum absorbance occurred at 212nm and Al2O3 nanoparticles showed absorbance from 210nm-217nm. The R2 values of pseudo1st, 2nd, and BMG models were 0.956, 0.837, 0.7007 0.95, 0.896, and 0.756 for the nitrate and phosphate ions. Characterizations of synthesized particles were investigated by using UV-visible spectroscopy and other analytical methods like X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). The statistical analyses were done using Simple Linear regression (SLR).

Introduction The monitoring of cerebral perfusion in patients with brain damage is a major clinical challenge. Monitoring cerebral oxygenation (rSO2) by NIRS was introduced at the turn of the 1980s, and many clinicians believed it was a valuable method for assessing cerebral perfusion and subsequent measures to optimize cerebral flow. The main problem of NIRS usage is the presence of the intermediate structures-skin, skull, meninges, cerebrospinal fluid-and their influence on the outcome of the test. Therefore, it seems that NIRS assessment performed on a patient during brain death attempts, can give an idea of the magnitude of the influence of these intermediate structures on the monitoring result. Case We present a retrospective analysis of cerebral oxygenation measurements of a patient undergoing a brain death diagnostic procedure. A clinical situation where the cerebral blood flow is stopped can give an idea of the specificity of the method, particularly the impact of the influence of intermediate structures on the monitoring outcome. In this case, the NIRS result is increased by the oxygenation of the patient before the apnoea test. The influence of chromophores in the tissues surrounding the CNS, reflections and scattering of the light wave spectrum have a very significant effect on the final result of cerebral saturation measurement. Discussion The majority of research observations describing changes in cerebral perfusion or its optimisation may be burdened by the problem described, i.e. the significant influence of measured oxygenation from intermediate structures. The specificity of NIRS to assess cerebral perfusion requires careful analysis. The therapeutic implications of monitoring cerebral oxygenation with NIRS are of great importance and, from the example presented and the literature provided, the method should be used with caution. It has been shown that in a patient with brain death, the result of NIRS oxygenation measurements depends on the surrounding structures of the brain.

Axial resolution is one of the most important characteristics of a microscope. In all microscopes, a high axial resolution is desired in order to discriminate information efficiently along the longitudinal direction. However, when studying thick samples that do not contain laterally overlapping information, a low axial resolution is desirable as information from multiple planes can be recorded simultaneously from a single camera shot instead of plane-by-plane mechanical refocusing. In this study, we increased the focal depth of an infrared microscope non-invasively by introducing a binary axicon fabricated on barium fluoride substrate close to the sample. Preliminary results of imaging thick and sparse silk fibers showed an improved focal depth with a slight decrease in lateral resolution and increase in background noise.

Reactive oxygen species (ROS) play a pivotal role in cellular function, and their overproduction contributes to oxidative stress, fatigue, aging, and diseases. To counteract these effects, incorpo-rating antioxidant-rich nutrients is recommended. Functional waters, including electrolyzed hydrogen water (EHW), are gaining attention for potential antioxidant effects through daily in-take. This study employs aquaphotomics and near-infrared spectroscopy (NIRS) to elucidate the molecular mechanisms behind the antioxidant activity of EHW. Previous investigation reported a 100% loss in antioxidant functionality through autoclaving, and a 40% decrease with hydrogen gas removal, prompting the current investigation into the mechanisms of antioxidant effects and especially the role of water molecular structure in it. Aquaphotomics analysis of near infrared (NIR) spectral data revealed that the primary characteristic of EHW associated with anti-radical function is presence of water solvation shells. Autoclaving and degassing led to loss of these water molecular species and a significant increase in free water molecules. The study suggests that water shells (solvation shells) in EHW play a crucial role in neutralizing ROS, although the specific ions or nanoparticles responsible for creating these shells remain unidentified. This concept aligns well with existing proposals of the crucial role of water solvation shells in ROS neutralization.

This study investigates the long-term stability of the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) moderate-resolution Thermal Emissive Bands (M TEBs; M12 – M16) covering a period from February 2012 to August 2020. It also assesses inter-sensor consistency of the VIIRS M TEBs among three satellites-S-NPP, NOAA-20, and NOAA-21 over eight months spanning from March 18 to November 30, 2023. The field of interesting is limited to the ocean surface between 60°S and 60°N, specifically under clear-sky conditions. Taking radiative transfer modeling (RTM) as the transfer reference, we employed the Community Radiative Transfer Model (CRTM) to simulate VIIRS TEB brightness temperature (BTs), incorporating European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data as inputs. Our results reveal two key findings. Firstly, the reprocessed S-NPP VIIRS TEBs exhibit a robust long-term stability, as demonstrated through analyses of the observation minus background BT differences (O-B ∆BTs) between VIIRS measurements (O) and CRTM simulations (B). The drifts of the O-B BT differences are consistently less than 0.105 K/Decade across all S-NPP VIIRS M TEB bands. Notably, observations from VIIRS M14 and M16 stand out with drifts well within 0.04 K/Decade, reinforcing their exceptional reliability for climate change studies. Secondly, excellent inter-sensor consistency among these three VIIRS instruments is confirmed through the double-difference analysis method (O-O). This method relies on the O-B BT differences obtained from daily data. The mean inter-VIIRS O-O BT differences remain within 0.08 K for all M TEBs, except for M13. Even in the case of M13, the O-O BT differences between NOAA-21 and NOAA-20/S-NPP have values of 0.312 K and 0.234 K, respectively, which are comparable to the 0.2 K difference between some TEBs among VIIRS and MODIS. These disparities are primarily attributed to the significant differences in the Spectral Response Function (SRF) of NOAA-21 compared to NOAA-20 and S-NPP. Our study confirms the RTM-based TEB quality evaluation method’s versatility and effectiveness in assessing long-term sensor stability and inter-sensor consistency. The double-difference approach effectively mitigates uncertainties and biases inherent to CRTM simulations, establishing itself a robust mechanism for assessing inter-sensor consistency. In addition, we’ve observed that, except for M13, M12 always exhibits larger spatial variations of O-O BT differences with greater uncertainties compared to the other M TEBs. The influence of solar contribution through sea surface reflection on the Top of Atmosphere (TOA) radiance measurements during daytime in M12 should not be underestimated.

We explores the hydrodynamical limit of a homogeneous electron gas, considering the interplay between the infrared limit and phenomenological hydrodynamics. Our study involves interactions generated by non-linear coordinate transformations. The focus begins with an analysis of non-linear coordinate transformations and their impact on normal modes in a harmonic system. The Lagrangian for a harmonic oscillator is used as an illustrative example, highlighting the role of position-dependent effective mass in preventing certain coordinate values. Moving beyond single degrees of freedom, we extend the discussion to a system with several harmonic degrees of freedom, introducing a collective variable. The effective dynamics of this collective variable are defined through a Lagrange multiplier term, emphasizing linearity in the description. Our study extends to the Current Two-Point function (CTP) formalism, introducing matrices and their inverses, such as $\hD$ and $\hD^{-1}$. Further, we delve into the dynamics of current in a homogeneous electron gas at finite density and zero temperature. Green's functions are generated using a functional integral approach, and the effective action is constructed via functional Legendre transformation. The quadratic part of the generator functional is expanded to derive the effective action, leading to the Maxwell equation and the subsequent elimination of the photon field. The resulting effective action for current dynamics is expressed in terms of the Current Two-Point function, paving the way for further exploration of the hydrodynamical aspects of the electron gas. Our study combines theoretical developments and mathematical formalism to provide insights into the hydrodynamical behavior of homogeneous electron gases.

We investigate the shear quasinormal modes (QNMs) in the context of electron stars, focusing on the Lifshitz geometry and exploring the behavior in the small star limit. The study begins by analyzing the shear sector modes in the infrared (IR) Lifshitz limit, where the geometry approaches that of a pure Lifshitz space. We derive and solve the differential equations governing the shear modes, revealing the asymptotic behavior in terms of the Lifshitz exponent. In the special case of integer values of the exponent, we obtain analytic corrections to the solutions to extract hydrodynamical QNMs. We then explore the cases with a Lifshitz exponent equal to or greater than three, providing analytical corrections to the Lifshitz IR solutions. A special case with an exponent of two is also considered, leading to modified solutions. The study extends to finding hydrodynamical QNMs, emphasizing the role of the Lifshitz geometry. Further investigations involve the flux with real and complex frequencies, considering the off-shell Lagrangian and deriving conserved flux expressions. Our analysis focuses on the exterior of the star, modeled by the Reissner-Nordström-AdS geometry. The small star limit is examined, revealing interesting features in the behavior of fermionic excitations. In summary, we provide a detailed exploration of shear quasinormal modes in electron stars, shedding light on their behavior in Lifshitz geometry, small star limits, and the interplay between real and complex frequencies. Our findings contribute to our understanding of the dynamics of electron stars and their gravitational properties.

In the dynamic landscape of 6G and smart cities, Visible Light Communication (VLC) assumes critical significance for IoT (Internet of Things) applications spanning diverse sectors. The escalating demand for bandwidth and data underscores the need for innovative solutions, positioning VLC as a complementary technology within the electromagnetic spectrum. This paper focuses on the relevance of VLC in the 6G paradigm, shedding light on its applicability across smart cities and industries. The paper highlights the growing efficiency of lighting LEDs in infrastructure, facilitating the seamless integration of VLC. The study then emphasizes VLC’s robustness in outdoor settings, demonstrating effective communication up to 10 meters. This resilience positions VLC as a key player in addressing the very last meter of wireless communication, offering a seamless solution for IoT connectivity. By introducing an a freely available open-source simulator combined to an alternative waveform, UFMC, the study empowers researchers to dimension applications effectively, showcasing VLC’s potential to improve wireless communication in the evolving landscape of 6G and smart cities.

This paper explores the Wilsonian renormalization group of probe-D-branes, focusing on the Dirac-Born-Infeld (DBI) action. The analysis involves deriving the constant of motion and formulating the Wilsonian renormalization group equation. The study extends to the infrared regime, considering both zero and non-zero temperatures. Additionally, thermodynamic aspects related to the functional form of the grand potential are discussed. The investigation provides insights into the renormalization of probe-D-branes and their thermodynamic properties.

Chitosan (CS) nanoparticles are under investigation for a wide range of applications in nanomedicine. The structural, molecular and physicochemical properties of chitosan nanoparticles have a direct bearing on their efficacy in drug conjugation and delivery, gene delivery, and tissue engineering. Herein we report on the structural, morphological and molecular properties of chitosan nanoparticles synthesized using the ionic gelation method with the intended purpose of being used for drug delivery. The chitosan nanoparticles (CS-NPs) were prepared in the 0.25 to 1.0% w/v concentration range, whereas separate samples of the 1.0% w/v CS-NPs were also functionalized with polyethylene oxide (PEO) alone and with a diblock copolymer of PEO and polypropylene glycol (PPG). The average size of the CS-NPs was determined from TEM imaging to be in the range of 11.3 to 14.8 nm. The XRD and TEM analyses show that the CS-NPs have semi-crystalline structure with the degree of crystallinity depending upon the nature of synthesis. Our results show that functionalizing the 1.0% w/v CS-NPs with PEO increases the degree of crystallinity whereas functionalizing with the diblock copolymer PEO - PPG results in a significant increase in their degree crystallinity. The CS/TPP concentration (CS:TPP fixed at 1:1 ratio) had no apparent effect on the degree of crystallinity of the CS-NPs. The results from the FTIR analysis confirm incorporation of TPP with CS in the CS-NPs. Additionally, FTIR analysis shows an enhancement of hydrogen bonding that is consistent with the increase in the degree of crystallinity of the CS-NPs.

Keywords: Evanescent field; photonic sensor; optical waveguide; light-matter interaction; absorption; mid-infrared.

Yield calculation is an important link in modern precision agriculture, which is an effective means to improve breeding efficiency, and adjust planting and marketing plans. With the continuous progress of artificial intelligence and sensing technology, yield calculation schemes based on image processing technology have many advantages such as high accuracy, low cost, and non-destructive calculation, and have been favored by a large number of researchers. This article reviews the research progress of crop yield calculation based on remote sensing images and visible light images, describes the technical characteristics and applicable objects of different schemes, and focuses on detailed explanations of data acquisition, independent variable screening, algorithm selection and optimization. Common issues are also discussed and summarized. Finally, solutions are proposed for the main problems that have arisen so far, and future research directions are predicted, with the aim of achieving more progress and wider popularization of yield calculation solutions based on image technology.

Infrared small target detection (ISTD) plays a crucial role in both civilian and military applications. The detection of small targets against dense cluttered backgrounds remains a challenging task, requiring the collaboration of false alarm source elimination and target detection. Existing approaches primarily focus on modeling targets while often neglecting false alarm sources. To address this limitation, we propose a Target and False Alarm Collaborative Detection Network to leverage the information provided by false alarm sources and the background. Firstly, we introduce a False Alarm Source Estimation Block (FEB) that estimates potential interferences present in the background by extracting features on multiple scales and employing stepwise upsampling for feature fusion. Subsequently, we propose a framework that employs multiple FEBs to eliminate false alarm sources across multiple scales. Finally, a Target Segmentation Block (TSB) is introduced to accurately segment the targets to produce the final detection result. Experiments on public datasets demonstrate that, compared to other methods, our model achieves high accuracy in segmenting targets while being able to extract false alarm sources which can be used for further studies.

To investigate the associated mechanisms concerning collagen and the expression of apoptosis-related proteins in porcine skin injuries induced by laser exposure, pig skin was treated with a 1064 nm laser. The healing process of the laser-treated areas, alterations in collagen structure, and changes in apoptosis were continuously observed and analyzed from 6 hours to 28 days post-irradiation. On the 28th day following exposure, wound contraction and recovery were notably sluggish in the medium-high dose groups, displaying more premature and delicate type III collagen within the newly regenerated tissues. The collagen density in these groups was roughly 37-58% of that in the normal group. Between days 14 and 28 after irradiation, there was a substantial rise in apoptotic cell count in the forming epidermis and granulation tissue of the medium-high dose group, in contrast to the normal group. Notably, the expression of proapoptotic proteins bax, caspase-3, and caspase-9 surged significantly 14 days after irradiation in the medium-high dose groups and persisted at elevated levels on the 28th day. During the later stage of wound healing, the augmented apoptotic cell population and insufficient collagen generation in the newborn skin tissue of the medium-high dose groups were closely associated with delayed wound recovery.

Buildings are rapidly becoming more digitized, to a large extent due to developments in IoT. This will provide many opportunities but also a number of challenges. One of the central challenges in the process of digitizing buildings is the ability to monitor the building’s status effectively. This monitoring is essential for various services that rely on information about the presence and activities of individuals within different areas of the building. Occupancy information, including people counting, occupancy detection, location tracking, and activity detection, plays a vital role in the management of smart buildings. In this article, our primary focus is on the use of Passive Infrared (PIR) sensors for gathering occupancy information. PIR sensors are among the most widely used sensors for this purpose due to their consideration of privacy concerns, cost-effectiveness, and low processing complexity compared to many others. Despite numerous literature review articles in the field of occupancy information, there currently isn’t a specialized literature review dedicated to occupancy information derived specifically from PIR sensors.Therefore, this study analyzes articles that specifically explore the application of PIR sensors for occupancy information. This article provides a comprehensive literature review of PIR sensor technology from 2015 to 2023, with a focus on applications in people counting, activity detection, and localization (traking and location). It consolidates findings from a number of articles that have explored and enhanced the capabilities of PIR sensors in these interconnected domains. This review thoroughly examines the application of various techniques, machine learning algorithms, and configurations for PIR sensors in indoor building environments, emphasizing not only the data processing aspects but also their advantages, limitations, and efficacy in producing accurate occupancy information.These developments are crucial for improving building management systems in terms of energy efficiency, security, and user comfort, among other operational aspects.These developments are crucial for improving building management systems in terms of energy efficiency, security, and user comfort, among other operational aspects. The paper seeks to offer a thorough analysis of the present state and potential future advancements of PIR sensor technology in efficiently monitoring and understanding occupancy information by classifying and analyzing improvements in these domains.

Ground-based infrared cameras can be used effectively and safely to provide quantitative information about small to moderate-sized volcanic eruptions. This study describes an infrared camera that has been used to measure emissions from Mt Etna and Stromboli (Sicily, Italy) volcanoes. The camera provides calibrated brightness temperature images in a broadband (8--14 µm) channel that is used to determine height, plume ascent rate and volcanic cloud/plume temperature and emissivity at temporal sampling rates of up to 1 Hz. The camera can be operated in the field using a portable battery and includes a microprocessor, data-storage and WiFi. The processing and analyses of the data are described with examples from the field experiments. The updraft speeds of the small eruptions at Stromboli are found to decay with a timescale of $\sim$10 min and the volcanic plumes reach thermal equilibrium within $\sim$2 min. A strong eruption of Mt Etna on 1 April 2021 was found to reach $\sim$9 km, with ascent speeds of 10--20 ms$^{-1}$. The plume, mostly composed of water vapour and SO$_2$ gas became bent over by the prevailing winds at high levels.

The roots, leaves, and other parts of American ginseng contain ginsenosides and polyphenols, among other bioactive components. So far, reports on exploring the changes in bioactive components within its leaves after heat treatment have been limited. In the present study, we investigated the effects of far-infrared irradiation (FIR) heat treatment from 160 to 200 ℃ on the deglycosylation and dehydration rates of the bioactive components in American ginseng leaves. As the temperature was increased, the amounts of constant ginsenosides decreased while those of rare ginsenosides increased. After FIR heat treatment of the American ginseng leaves at an optimal 190 ℃, the highest total polyphenolic content and kaempferol content were detected, the antioxidant activity was significantly enhanced, and the amounts of rare ginsenosides F4, Rg6, Rh4, Rk3, Rk1, Rg3, and Rg5 were 41, 5, 37, 64, 222, 17, and 266 times higher than those in the untreated leaves, respectively. Moreover, the radical scavenging rates for 2,2-diphenyl-1-picrylhydrazyl and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), and the reducing power of the treated leaf extract, were 2.17, 1.86, and 1.77 times higher, respectively. Hence, optimal FIR heat treatment at 190 ℃ is an efficient method for producing beneficial bioactive components from American ginseng leaves.

Multi-channel and multi-parameter near-infrared spectrometers (NIRS) have gradually become a new research direction and hot spot due to their ability to provide real-time, continuous, comprehensive indicators of multiple parameters. However, multi-channel and multi-parameter detection may lead to crosstalk between signals. There is still a lack of benchmarks on the evaluation of reliability, sensitivity, stability and response consistency of the NIRS instrument. In this study, a set of test methods (the ink drop test, multi-channel crosstalk test and multi-parameter crosstalk test) for analysis crosstalk and verifying the reliability of NIRS were conducted to test experimental verification on a multi-channel (8-channel), multi-parameter (4-parameter) NIRS instrument independently developed by our team. Results show that these tests can be used to analyze the signal crosstalk and verify the reliability, sensitivity, stability and response consistency in the NIRS instrument. This study contributes to the establishment of benchmarks for the NIRS instrument crosstalk and reliability testing. These novel tests have the potential to become the benchmark for the NIRS instrument reliability testing.

Near-infrared spectroscopy (NIRS) has become a key modality in medical imaging, finding application in both brain and breast imaging. This paper discusses the current trends in NIRS for brain and breast imaging, exploring advances in multi-modal integration with modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Challenges related to spatial resolution, depth sensitivity, and the impact of extracerebral tissues on signal specificity are examined. In addition, ongoing efforts to enhance hemodynamic measurements’ quantitative accuracy. Challenges, including limited spatial resolution and tissue heterogeneity, are discussed. The discussion extends to diffuse optical tomography and ongoing instrumentation development, clinical trials and studies validating NIRS diagnostic efficacy in breast imaging. The paper emphasizes the need for standardization, integration into routine clinical practice, and motivates for future work.

Genetic engineering and directed evolution are effective methods to address the low yield and poor industrialization level of microbial target products. The current research focus is on how to efficiently and rapidly screen beneficial mutants from constructed large-scale mutation libraries. Traditional screening methods such as plate screening and well plate screening are severely limited in their development and application due to their low efficiency and high costs. In the past decade, microfluidic technology has become an important high-throughput screening technology due to its fast speed, low cost, high automation, and high screening throughput, and it has developed rapidly. Droplet-based microfluidic high-throughput screening has been widely used in various fields such as strain/enzyme activity screening, pathogen detection, single-cell analysis, drug discovery, and chemical synthesis, and has been widely applied in industries such as materials, food, chemicals, textiles, and biomedicine. In particular, in the field of enzyme research, droplet-based microfluidic high-throughput screening has shown excellent performance in discovering enzymes with new functions, improved catalytic efficiency or stability, acid-base tolerance, etc. Currently, droplet-based microfluidic high-throughput screening technology has achieved high-throughput screening of enzymes such as glycosidase, lipase, peroxidase, protease, amylase, oxidase, and transaminase, as well as high-throughput detection of products such as riboflavin, coumarin, 3-dehydroquinate, lactic acid, and ethanol. This article reviews the application of droplet-based microfluidics in high-throughput screening, with a focus on high-throughput screening strategies based on UV, visible, and fluorescence spectroscopy, including labeled optical signal detection screening, as well as label-free electrochemical detection, mass spectrometry, Raman spectroscopy, nuclear magnetic resonance, etc. Furthermore, the research progress and development trends of droplet-based microfluidic technology in enzyme modification and strain screening are also introduced.

Aiming at the classification identification problem of aeroengines, this paper adopts telemetry Fourier Transform Infrared Spectrometer to collect aeroengine hot jet infrared spectrum data, and proposes an aeroengine classification identification method based on spectral feature vectors. First, aeroengine hot jet infrared spectrum data are acquired and measured, meanwhile, the spectral feature vectors based on CO2 are constructed. Then, the feature vectors are combined with the seven mainstream classification algorithms to complete the training and prediction of the classification model. In the experiment, two Fourier transform infrared spectrometers, EM27 developed by Bruker and a self-developed telemetry FTIR, were used to telemeter the hot jet of three aeroengines to obtain infrared spectral data. The training data set and test data set were randomly divided in a ratio of 3:1. The model training of the training data set and the label prediction of the test data set were carried out by combining spectral feature vectors and classification algorithms. The classification evaluation indicators were accuracy, precision, recall, confusion matrix, and F1-score. The classification recognition accuracy of the algorithm was approximately 98%. This paper has great significance for the fault diagnosis of aeroengines and classification recognition of aircrafts.

A non-destructive analysis of proximate parameters (moisture content, MC; volatile matter, VM; fixed carbon, FC; and ash content) for a variety of chipped and ground biomasses was investigated through a combination of thermogravimetric analysis (TGA) and near-infrared spectroscopy (NIRS) with partial least squares regression (PLSR). In this study, the thermogravimetric method was employed as a tool to determine the proximate analysis data of biomass samples through TG and DTG curves, which were generated by tracking changes in biomass mass loss over time or temperature. NIRS non−destructively scanned the chipped biomass in diffuse reflectance while ground biomass using transflectance mode, covering the wavenumber range of 3594.87 to 12,489.48 cm−1. The PLSR−based models: Full−PLSR, genetic algorithm (GA)−PLSR, successive projection algorithm (SPA)−PLSR, the spectral multi−preprocessing (MP) PLSR− 5 range method, and the MP PLSR−3 range method were developed. Model performance was assessed, compared, and selected based on the coefficient of determination in the prediction set (R2P), root mean square error in the validation set (RMSEP), and the ratio of prediction to deviation (RPD). Based on the comprehensive analysis of model performance, MC and FC models of chip biomass have demonstrated satisfactory performance which makes it applicable cautiously in any application, including research. The optimum models for MC and FC in chip biomass were constructed using GA−PLSR with 2nd derivative and Full−PLSR with a constant offset, resulting in R2P values of 0.8654 and 0.8773, RMSEP values of 0.85% and 2.12%, and RPD values of 2.9 and 3.0, respectively. Other parameters such as MC and FC in ground biomass as well as VM and ash content in both chip and ground biomass were found suitable for rough screening. The sensitivity of the selected model was assessed by calculating the limit of quantification (LOQ), and the results indicated that the calculated LOQ values for VM in both chip and ground biomass and FC in chip biomass are lower than the minimum reference values used during model development, signifying a high level of sensitivity. However, for the remaining parameters, the LOQ values surpass the established minimum reference value, suggesting the model could not predict the future samples with reference value lower than the calibration range. Nevertheless, enhancing the models by incorporation an ample number of representative biomass samples and consistently validating the models with unknown samples is imperative to ensure accurate predictions.

The Advanced Meteorological Image (AMI) onboard GEOKOMPSAT 2A (GK-2A) enables the retrieval of dust aerosol optical depth (DAOD) from geostationary satellites using infrared (IR) channels. IR observations allow the retrieval of DAOD and the dust layer altitude (24 hour) over surface properties, particularly over deserts. In this study, dust events in northeast Asia from 2020 to 2021 were investigated using five GK-2A thermal IR bands (8.7, 10.5, 11.4, 12.3, and 13.3 μm). For the dust cloud, the observed brightness temperature differences (BTDs) of 10.5 and 12.3 μm were found to be always negative, while the BTD of 8.7 and 10.5 μm varies relying on the dust intensity. Making the best use of optical properties, a physical approach for DAOD lookup tables (LUTs) was developed using IR channels to retrieve the DAOD. This study simulated the characteristics of thermal radiation transfer using the forward model and dust aerosols can explain by BTD (10.5, 12.3 μm), which is an intrinsic characteristic of dust aerosol. The DAOD and property of dust can be gained from the brightness temperature (BT) of 10.5 μm and the BTD of 10.5, 12.3 μm. Additionally, the cumulative distribution function (CDF) was employed to strengthen the continuity of 24-hour DAOD, which was applied to the algorithm by calculating the conversion value coefficient for the DAOD error correction of the IR with daytime visible aerosol optical depth (VAOD) as the true value. The results show that DAOD product can be successfully used during both daytime and nighttime to continuously monitor the flow of yellow dust from the GK-2A satellite in northeast Asia. In particular, the validation result of IR DAOD was similar to that of the active satellite product (CALIPSO/CALIOP), which showed a tendency similar to that for IR DAOD at night.

Background: Glioblastoma remains a challenging brain tumor to treat due to its infiltrative nature. Accurately identifying tumor boundaries during surgery is crucial for successful tumor resection. This study introduces an innovative intraoperative visualization method utilizing a surgical fluorescence microscope to precisely locate tumor cells. The focus of the study is on IR-Glint, a novel preparation comprising Cy7.5-labeled aptamers Gli-233nt and Gli-55_3L specific to human glioblastoma. Methods: The aptamers were modified using molecular modeling and quantum chemical techniques. The effectiveness of the preparation was assessed using flow cytometry and microscopy on primary cultures of human glioblastoma. In vivo studies were conducted on mouse and rabbit models, employing orthotopic xenotransplantation of human brain glioblastoma with various imaging techniques, including PET/CT, in vivo fluorescence visualization, confocal laser scanning, and surgical microscopy. Results: The experiments validated the potential of IR-Glint for intraoperative visualization of glioblastoma using infrared imaging. Surface application of the aptamer-based formulation on the brain allowed clear visualization of the tumor, aiding surgeons in tumor resection. This approach also reduces the dosage required and mitigates potential toxic effects on the patient. Conclusions: This study demonstrates the promising potential of using in-frared dye-labeled aptamers for intraoperative visualization of glioblastoma. By improving surgical treatment outcomes in neurosurgery, this novel approach may pave the way for future advancements in the field.

Saudi Arabia is a prominent producers of dates, with 1.6 million tons annually. There is a need to evaluate physical properties and quality of fruits non-destructively and then be modeled and predicted throughout the storage period. The aim of the current study was to generate a quality index (Qi) and Near-infrared spectra (NIR) models non-destructively to predict properties of Barhi dates fruits including objective and sensory evaluations. The engineering properties of Barhi dates were measured and modeled with quality index (Qi) based on NIR of fresh Barhi fruits (hardness, color, TSS, pH, and sensory evaluations) and during storage in cold, ambient, and controlled at-mosphere (CA) for up to four months. The prediction of Qi is non- destructively based on NIR utilizing PLSR and ANN data analysis. The results showed that the Qi generated corresponds with high precision to the characteristics of the examined fruits through the duration of the storage period with R2 of 0.96. The NIR spectrum proves to be an efficient method to evaluate the Barhi fruits' quality index. where ANN was found to be more suitable than PLSR analysis. Thus, NIR can be utilized to accurately predict the Qi of fruits quality effectively throughout the handling, processing, transporting, storage, and retail sector supply chain.

Microplastics have been detected as widespread in an aquatic environment at the microscale, also known as plastic debris. They have continuously increased due to the increase in population, production of synthetic plastics and poor waste management. They are ubiquitous and slowly degrade in soil and water. They are emerging contaminants that have received attention from research communities and public audiences over the last few years. They have high stability and can absorb several other pollutants like heavy metals, pesticides, etc. After entering the environment, they can accumulate and persist for a long time. They can create a serious threat to freshwater ecosystems and human health. These particles can cause physical damage to freshwater organisms. Raman spectroscopy, Fourier-transform infrared spectroscopy, visual identification, density separation, microscopic method, chemical method, thermos-analytical method and hyperspectral imaging method are the commonly known approaches for identification and quantification of microplastics. The noticed concentration of microplastics depends on the analysis method, sampling location and technique. The authors reviewed the sources, health impact, transport and treatment of microplastics in freshwater environments in detail. This study will provide the baseline data for the researchers to do more research on microplastic pollution in the future.

The ultimate analysis parameters including carbon (C), hydrogen (H), nitrogen (N), and oxygen (O) content in biomass was rarely found to be predicted by nondestructive tests until to date. In this research, we developed partial least squares regression (PLSR) models to predict the ultimate analysis parameters of chip biomass using near infrared (NIR) raw spectra of non-wood and wood samples from fast growing tree and agricultural residue and nine different traditional spectral preprocessing techniques. These techniques include first derivative (sd1), second derivative (sd2), constant offset, standard normal variate (SNV), multiplicative scatter correction (MSC), vector normalization, min-max normalization, mean centering, sd1 + vector normalization, and sd1 + MSC. Additionally, we employed a genetic algorithm (GA), successive projection algorithm (SPA), multi-preprocessing (MP) 5−range, and MP 3−range to develop a PLSR model for rapid prediction. A dataset consisting of 120 chip biomass samples was utilized for model development in which the samples was non-wood samples of 65-67% and wood samples was 33-35%, and the model performance were evaluated and compared. The selection of the optimum performing model was mainly based on criteria such as the coefficient of determination in the prediction set (R2P), root mean square error of the prediction set (RMSEP), and the ratio of prediction to deviation values (RPD). The optimal model for weight percentage (wt.%) of C was obtained using GA−PLSR, yielding R2P, RMSEP, and RPD values of 0.6954, 1.1252 wt.%, and 1.8, respectively. Similarly, for wt.% of O, the most effective model was obtained using the multi-preprocessing PLSR−5 range method with R2P of 0.7150, RMSEP of 1.3088 wt.%, and RPD of 1.9. For wt.% of N, the optimal model was obtained using the MP PLSR−3 range method, resulting in R2P, RMSEP, and RPD values of 0.6073, 0.1008 wt.%, and 1.6, respectively. However, wt.% of H model provided R2P, RMSEP, and RPD values of 0.5162, 0.2322 wt.%, and 1.5, respectively. Notably, the limit of quantification (LOQ) values for C, H, and O were lower than the minimum reference values used during model development, indicating a high level of sensitivity. However, the LOQ for N, exceeded the minimum reference value, implying the samples to be predicted by the model must be in the range of reference range in calibration set. By scatter plot analysis, the effect of combined non-wood and wood spectra of biomass chips on rapid prediction of ultimate analysis parameters using NIR spectroscopy was investigated. To include different species in a model, the species have to be not only in the different values of the constituents to make a wider range for robust model but also they must provide their trend line characteristics in the scatter plot i.e. correlation coefficient (R), slope and intercept (same slope and slope approached to 1 and intercept is same (no gap) and approached zero, high R approached to 1). The effect of the R, slope and intercept to obtain the better optimized model were studied. The results show that the different species affected model performance of each parameter prediction in a different manner and by scatter plot analysis which of these species were affecting the model negatively and how the model could be improved was indicated. This is the first time of the effect is studied by the principle of scatter plot.

The utilization of titanium dioxide (TiO2) as a photocatalyst for the treatment of wastewater has attracted significant attention in the environmental field. Herein, we have prepared a NH2-MIL-125-derived TiO2@N-doped C Visible Light Catalyst through an in-situ calcination method. The nitrogen element in the organic connector is released through calcination, simul-taneously doping into the sample, thereby enhancing its spectral response to cover the visible region. The as-prepared TiO2@N-doped C catalyst exhibited preserved cage structure even after calcination, thereby alleviating the optical shielding effect and further augmenting its photo-catalytic performance by increasing the reaction sites between the catalyst and pollutants. The calcination time of the TiO2@N-doped C-450 °C catalyst was optimized to achieve a balance be-tween the TiO2 content and nitrogen doping level, ensuring efficient degradation rates for basic fuchsin (99.7%), Rhodamine B (89.9%), and tetracycline hydrochloride (93%) within 90 minutes.

Ensuring safe, high-quality food is an ongoing priority, yet consumers face heightened risk from foodborne pathogens due to extended supply chains and climate change in food industry. Nanomaterial-based assays are popular and have recently been developed to ensure food safety and high quality. This review discusses strategies for using nanomaterials in colorimetric biosensors. Localized surface plasmon resonance (LSPR) biosensors are commonly utilized for colorimetric biosensing. Several emerging technologies aimed at simple and rapid immunoassays for onsite applications have been introduced in the food industry. In the foreseeable future, field-friendly colorimetric biosensors could be adopted in food monitoring systems. The onsite and real-time detection of possible contaminants and biological substances in food and water is essential to ensure human health safety.

The purpose of this study was to explore and develop high-resolution infrared thermal (HRIT) imaging for screening toddler’s fracture. A Toddler’s fracture is a common tibial fracture of children younger than 6 years old. Initial x-ray radiographs may not show the fracture and another x-ray during a follow-on visit is usually required. The study included 39 participants admitted to an emergency department with a suspected toddler’s fracture. X-ray confirmed 8 cases with a toddler’s fracture (20.5%). Infrared images of participants were recorded on their index visit, focusing on region-of-interests on the injured and the contralateral (uninjured) legs. The uninjured leg acted as a thermal reference. Nine statistical measures were extracted from the images: maximum, mini-mum, mean, standard deviation, median, mode, interquartile range, skewness, and kurtosis. Wilcoxon rank sum test indicated that maximum, mean, standard deviation, median, and inter quartile range temperature measures were significantly different (p<0.05) when comparing fractured and non-fractured legs. Principal component analysis of these measures highlighted distinct separation of toddler’s fracture and non-fracture cases. Similarly, plots of the statistical measures further confirmed clustering of toddler’s fracture cases. The study demonstrated that HRIT imaging can be a valuable tool for screening for toddler’s fracture.

The structural evolution and phase composition of multi-block thermoplastic polyurethanes, with different nature of the soft segments based on poly(butylene adipate) (PBA), were analyzed during in-situ thermal treatments. A combination of synchrotron small- and wide-angle X-ray scattering, differential scanning calorimetry, thermogravimetric analysis, and FTIR spectroscopy was used to determine the influence of macrodiol nature and crystallization conditions on the polymorphic behavior of PBA. Using a new synthesis scheme, a relatively high degree of crystallinity for urethane blocks was achieved, which depends on the diisocyanate type in the structure of the soft segment. The hard segment domains impose geometrical constraints on PBA, thereby altering its crystallization process compared to the neat oligomer. Thus, crystallization after annealing at a low temperature (80 °C) is fast, predominantly yielding a metastable β-phase. When heated to 180 °C, which is higher than the hard-segment melting temperature, a phase-separated structure is observed. Subsequent crystallization is slower, favoring the formation of the stable α-PBA modification. The phase separation can be observed even after the hard block melting. A notably slow crystallization from an isotropic melt was documented after the disruption of phase separation at 230 °C.

The novel ternary composites, BiOBr-TiO2-attapulgite (BTA), were synthesized using a simple hydrothermal and water-bath method, exhibiting excellent photocatalytic performance to mul-tiple xanthates. For BTA photocatalyst, TiO2 and BiOBr were uniformly loaded on the surface of acid-activated attapulgite. As a widely used collector in mining processes, sodium ethyl-xanthate (SEX) was selected as the target pollutant due to its high toxicity. The BTA ternary photocatalyst demonstrated significantly higher adsorption and photocatalytic degradation performance compared to TiO2 nanoparticles, BiOBr nanosheets, and BiOBr-TiO2 heterojunction. Structural characterization and experimental results indicated that the exceptional photocatalytic degrada-tion efficiency of BTA was mainly attributed to the formation of heterojunction between BiOBr and TiO2, as well as the presence of additional active adsorption sites provided by attapulgite. Free radical scavenging experiments and EPR results confirmed that the photogenerated holes were the predominant active species to photodegrade SEX throughout the entire experiment. The LC-MS results provided insight into potential degradation pathways of SEX. This research demonstrates that BTA, as a novel triple composite material, achieves rapid and complete degradation to 20 mg/L SEX within 20 min. This work presents a novel approach to synthesize mineral-based photo-catalysts, which have broad prospects for application in flotation wastewater treatment.

The rising severity and frequency of wildfires in recent years in the United States have raised numerous concerns regarding the improvement in wildfire emergency response management and decision-making systems, which require operational high temporal and spatial resolution monitoring capabilities. Satellites are one of the tools that can be used for wildfire monitoring. However, none of the currently available satellite systems provide both high temporal and spatial resolution. For example, GOES-17 geostationary satellite fire products have high temporal (1-5 min) but low spatial resolution (2 km), and VIIRS polar orbiter satellite fire products have low temporal (~12 h) but high spatial resolution (375 m). This work aims to leverage currently available satellite data sources, such as GOES and VIIRS, along with Deep Learning (DL) advances to achieve an operational high-resolution, both spatially and temporarily, wildfire monitoring tool. Specifically, this study considers the problem of increasing the spatial resolution of high temporal but low spatial resolution GOES-17 data products using low temporal but high spatial resolution VIIRS data products. The main idea is using an Autoencoder DL model to learn how to map GOES-17 geostationary low spatial resolution satellite images to VIIRS polar orbiter high spatial resolution satellite images. In this context, several loss functions and DL architectures are implemented and tested to predict both the fire area and the corresponding brightness temperature. These models are trained and tested on wildfire sites from 2019 to 2021 in the western U.S. The results indicate that DL models can improve the spatial resolution of GOES-17 images, leading to images that mimic the spatial resolution of VIIRS images. Combined with GOES-17 higher temporal resolution, the DL model can provide high-resolution near-real-time wildfire monitoring capability as well as semi-continuous wildfire progression maps.

The models of partial least squares (PLS) regression and artificial neural network (ANN) for evaluation of texture properties of cooked germinated brown rice (GBR) using the Fourier transform near infrared (NIR) spectra of uncooked whole grain combined with data separation methods, spectral pretreatment methods were investigated in this study. The ANN was outperformed in evaluation of hardness by back extrusion test of cooked GBR using the smoothing combined with standard normal variate pretreated NIR spectra in the range of 12,500-4,000 cm−1 of 188 whole grain samples where the calibration sample set was separated from prediction set by Kennard-Stone method where the best ANN model for hardness from hidden layers of 25 and 8 iteration time provided R2, r2, RMSEC, RMSEP, Bias and RPD of 0.9987, 0.9447, 0.1021 N, 0.7699 N, 0.0216 N and 4.3 respectively. The PLS regression of 64 sample KDML GBR group and 64 sample various variety GBR group, provided models for the hardness of the former and the toughness of the latter which developed by using 7506−5446.3, 4605.4−4242.9 cm−1 which included the amylose vibration band of 6834 cm−1 while toughness model was from 9403.8-6094.3 cm−1 where included 6834 and 8316 cm−1 vibration bands of amylose which influenced the texture of cooked rice. The PLS regression models for hardness and toughness were with the r2 of 0.85 and 0.82, and the RPD of 2.9 and 2.4, respectively. The ANN model for hardness of cooked GBR should be implemented to the practical use in GBR production factories for the quality assurance and further updating using more samples and several brands to obtain the robust models.

The LED light source is an important light source for indoor visible light communication. It has the characteristics of a large divergence angle and a high transmission rate. Therefore, using LED as the light source for visible light full-duplex communication can not only satisfy the lighting requirements but also transmit information at high speed. To analyze the factors that affect the optical power of the indoor single-light source visible light communication uplink receiving end, an indoor visible light communication model was established, and mathematical calculation formulas were derived based on the model establishment, and the maximum movable range formula of the retroreflective end under specific conditions was derived; The reliability of the formula was verified with the help of Zemax simulation software. Theoretical analysis and experimental results show that increasing the movement range of the retroreflective end can be achieved by increasing the lens diameter, reducing the focal length, and increasing the link distance.

Polyvinyl Alcohol (PVA)/ Graphene Quantum Dots (GQDs) polymer nanocomposite films have been prepared, and the relationship between their structural, thermal and nanoscale morphologi-cal properties, and their photoluminescent response, has been investigated. Although according to X-ray Diffraction (XRD), Fourier-Transform Infrared Spectroscopy (FT-IR) and Differential Thermal Analysis (DTA) the incorporation of GQDs does not significantly affect the percentage crystallinity of the PVA matrix, for a range of added GQD concentrations, Atomic Force Micros-copy (AFM) showed the formation of islands with apparent crystalline morphology on the surface of the PVA/GQD films, with GQD presumably acting as a nucleating agent for island growth. The incorporation of GQD also led to the formation of characteristic surface pores with increased stiffness and frictional contrast, according to Ultrasonic Force Microscopy (UFM) and Frictional Force Microscopy (FFM) data. The photoluminescence (PL) spectra of the films were found to de-pend both on the amount of GQD incorporated and on the film morphology. For GQD loads > 1,2wt%, a GQD-related band was observed at ~ 1650 cm-1 in FT-IR, along with an increase in the PL band at lower energy. For a load of ~2wt% GQD, the surface morphology was characterized by extended cluster aggregates with lower stiffness and friction than the surrounding matrix, and the PL signal decreased.

High-performance insulation and airtight building envelopes are the two most important factors to optimize the building energy efficiency and thermal performance. However, thermal performance of building envelopes can be significantly affected by thermal bridging. Thermal bridges can take place at different locations of the building envelope, causing added transmission losses, increasing heat flow, lower inner surface temperatures. Thermal bridges are regarded in all national regulations for new buildings of all states of European Union (EU) but there are no specifications assessing balconies to wall junctions and the impact on the building thermal performance is not well regulated. In this paper, balcony to wall thermal bridge assessment using infrared thermography is highlighted. The originality is that, infrared thermography, has been applied to a real living latest building in the north east of France showing that there is noncompliance in the national regulations as some exigencies are not met. Thermography of thermal break windows and window doors has also revealed air leakage. The goal, is to illustrate that thermal imaging is a means of quality assurance to new building specifications and should include a clause specifying quality assurance procedure for balconies junction in national building regulations for all states if the EU.

Since the photocatalytic reaction is a surface reaction, enhancing the gas movement around photocatalyst would promote photocatalytic CO₂ reduction performance. A new approach to enhance the gas movement around the photocatalyst by the natural thermosiphon movement of gasses around photocatalyst using black body material was proposed and confirmed experimentally, but the heat transfer mechanism on the phenomena was not clarified yet. The purpose of this study is to clarify the heat transfer mechanism of it. This study calculated the temperature of mixed gases of CO₂ and NH₃ around P₄O₁₀/TiO₂ photocatalyst by the heat transfer formula. It is revealed that there was no difference between the increase temperature (T_g) from the temperature at the beginning of the CO₂ reduction experiment (T_ini) and the temperature of mixed gases of CO₂ and NH₃ measured by thermocouple in the experiment (T_e) under the illumination condition with a visible light (VIS) + an infrared light (IR) and IR only. The heat transfer model proposed by this study has predicted T_g well under the illumination condition with VIS + IR and IR only well. On the other hand, it is revealed that the difference between T_g and T_e was as large as 10 ℃ under the illumination condition with an ultra violet light (UV) + VIS + IR.

N-maleimide-derivatized phospholipids are often used to facilitate protein anchoring to membranes. In autophagy studies, this is applied to the covalent binding of Atg8, an autophagy protein, to a phosphatidylethanolamine (PE) in the nascent autophagosome. However, the question remains on how closely the N-maleimide PE derivative (PE-mal) mimicks the native PE in the bilayer. In the present paper, spectroscopic and calorimetric techniques have been applied to vesicles containing either PE or PE-mal (together with other phospholipids) to compare the properties of the native and derivatized forms of PE. According to differential scanning calorimetry, and to infrared spectroscopy, the presence of PE-mal did not perturb the fatty acyl chains in the bilayer. Fluorescence spectroscopy and microscopy showed that PE-mal did not alter bilayer permeability either. However, fluorescence emission polarization of Laurdan and DPH probes indicated an increased order, or decreased fluidity, in the bilayers containing PE-mal. In addition, infrared spectral data from the phospholipid phosphate region revealed a PE-mal-induced conformational change of the polar heads, accompanied by an increased hydration. Globally considered, the results suggest that PE-mal would be a reasonable substitute for PE in model membranes containing reconstituted proteins.

Milk MIR spectra have been shown to provide valuable information on a wide range of traits to be used in dairy cattle breeding programs. Selecting the most informative variables from complex data can improve prediction accuracy and model robustness and, consequently, the interpretability of MIR spectra. Thus, we aimed to investigate the prediction performance of feature selection methods based on MIR spectra data, using the milk fatty acid (FA) profile as an example to illustrate the evaluated procedure. Data of MIR spectra, milk test-day records, and reference FA concentrations of 155 first-parity Holstein cows were used in the analyses. Four models comprising different explanatory variables and five feature selection methods were evaluated. The results indicated that the Competitive Adaptive Reweighted Sampling (CARS) method can effectively select the most informative variables from the MIR spectra, resulting in higher prediction accuracies than other variable selection approaches. The model including selected MIR spectra and cow information variables [days in milk at the test day, age at the test day, pregnancy stage (in days), number of days open, number of inseminations, and somatic cell count] yielded the best FA profile predictions based on Partial Least Square regression. In particular, ten FAs (C8:0, C10:0, C14:1, C17:0 isomers, C18:1, C18:1 isomer, medium-chain FA, unsaturation FA, monounsaturated FA, and polyunsaturated FA) presented accuracies based on the determination coefficient (R2cv) ranging from 0.66 to 0.85 in internal validation and from 0.65 to 0.84 in external validation. By running CARS 1,000 times in internal validations, we obtained the frequency of selected milk MIR wavenumber for 35 FAs. The most related wavenumbers to FAs were found within 1,003 to 1,145 cm-1, while other discrete areas were between 1,651 to 1,797 and 2,834 to 2,954 cm-1. These biomarkers may give insights into the relationship between MIR spectra and FA phenotypes. In conclusion, using CARS and cow information improved predictions of FAs based on MIR spectra in Chinese Holstein dairy cows. Additional validation studies should be conducted as larger datasets become available.

The adsorption of surfaces exposed to sunlight results in increased temperature that can cause physical damage and increase in energy consumption. The infrared reflective coatings that keep objects cooler have significant benefits in a wide variety of application by reflecting the infrared lights, reducing the operating costs, improving energy efficiency of buildings and vehicles (roofs, walls and windows), extend the objects’ lifespan. Our research focused on the elaboration of coatings with minimum adsorption in the infrared wavelength range. This was achieved by production of coatings that have infrared transparent and infrared reflective ability. The infrared reflection and surface warm up was investigated in the function of concentration and composition of pigments in the coatings. With investigation of different coating compositions the pigments and the binding systems were optimized. The coatings with different compositions were characterized by total solar reflection in the UV, visible and infrared wavelength range as well as by infrared reflection. Different coatings were produced in RAL7016 anthracite green color but with much better infrared reflectance, transparency as well as with heat reflectance.

Antarctica and its surrounding environment are considered untouched and thought that it is free from microplastics (MPs) pollution. However, recent studies and science projects have reported MPs in both water and sediment in the South Polar Regions. The reports state that the MP’s pollution occurs in this region due to fishing, tourism, and research activities by the nearby countries and nature's circulation is also part of it. The Antarctic Treaty System (ATS) has received attention on MP’s pollution and initiated research on it. MPs are tiny plastic particles with a size of less than 5 mm. It has two types, 1. Primary MPs have been manufactured directly for various applications like cosmetics and scrubbing etc 2. The secondary MPs are generated by photochemical degradation of large plastics.Although several studies have been done there is a quite gap in our understanding of the concentration, characteristics, and impact of plastics on the ecosystem of the Antarctic Region. The impact of MP’s pollution in this region may be very high. The presence of MP is a serious issue that is affecting not only the aquatic environment but also humans. It is an alarming situation that causes environmental damage. The main objective of this paper is to review MP's introduction, occurrence, sources, harmful effects, and detection methods. This review highlighted the various methodologies and analyses like density separation, microscope observation of MP’s properties Fourier-transform infrared spectroscopy (FTIR), and Raman spectrometer respectively, and urged for more research in the future and gave several recommendations to maintain the pristine region near Antarctica.

We report a diode pumped solid state (DPSS) laser used for intracavity pump-enhanced difference frequency generation (DFG) to create a 3.5 micron laser. Using a 50 mm-long periodically poled lithium niobate (PPLN) crystal inside the cavity of an Nd:YVO4 solid state laser at 1064 nm with 4.5 W pump power at 808 nm, and a 310 mW C-band signal at 1529 nm, up to 31 mW of mid-infrared output power at 3499 nm is obtained. The cavity requires no active stabilization and/or locking, and the entire cavity is &lt;8 cm in length. The obtained output power corresponds to a black box efficiency of 2.20 %W-1, which is the highest value reported to date for continuous wave DFG based on a bulk nonlinear optical crystal with no active stabilization. Potential future applications in free space optical communication are discussed as well.

porous silicon-based photodetectors have attracted more researches due to their high luminous efficiency, good stability and low cost. In this paper, a PbS quantum dots/porous silicon hybrid structure has been fabricated. The PbS quantum dots (QDs) partly infiltrated into the porous silicon (PSi) layer and partly deposited on its surface, which could increase the absorption of near-infrared wavelength range and extend the light absorption in silicon for wavelengths longer than 1100 nm. After that, A metal-semiconductor-metal (MSM) device is fabricated and its response spectrum could extend to the 1200 nm at -3 V. As a silicon-based photodetector (PD), one can envision its role for operation from visible light to short-wavelength infrared range.

The flour milling industry, a vital component of global food production, is undergoing a transformative phase driven by the integration of smart devices and advanced technologies. This transition promises improved efficiency, quality, and sustainability in flour production. Accurate estimation of protein, moisture and ash content in wheat grains and flour is of paramount importance due to their direct impact on product quality and compliance with industry standards. This paper explores the application of Near-Infrared (NIR) spectroscopy as a non-destructive, efficient, and cost-effective method for measuring the aforementioned essential parameters in wheat and flour, by investigating the effectiveness of a low-cost handle NIR spectrometer. Furthermore, a novel approach using Fuzzy Cognitive Maps (FCMs) is proposed to estimate protein, moisture and ash content in grain seeds and flour, marking the first known application of FCMs in this context. Our study includes an experimental setup that assesses different types of wheat seeds and flour samples and evaluates three NIR pre-processing techniques to enhance parameter estimation accuracy. The results indicate that low-cost NIR equipment can contribute to the estimation of the under-study parameters.

Amorphous germanium films on non-refractory glass substrates were annealed by ultrashort near-infrared (1030 nm, 1.4 ps) and mid-infrared (1500 nm, 70 fs) laser pulses. Crystallization of germanium irradiated at a laser energy density (fluence) range from 25 to 400 mJ/cm2 under single-shot and multi-shot conditions was investigated using Raman spectroscopy. The dependence of the fraction of the crystalline phase on the fluence was obtained for picosecond and femtosecond laser annealings. The regimes of almost complete crystallization of germanium films over the entire thickness are obtained (from the analysis of Raman spectra with excitation of 785 nm laser). The possibility of scanning laser processing is shown, which can be used to create films of micro and nanocrystalline germanium on flexible substrates.

Definitions of bronchopulmonary dysplasia (BPD) or post-prematurity respiratory disease (PPRD) aim to stratify the risk of mortality and morbidity, with an emphasis on long-term respiratory outcomes. There is no univocal classification of BPD, due to its complex multifactorial nature and the substantial heterogeneity of clinical presentation. Currently, there is no definitive cure available for extremely premature very-low-birth-weight infants with BPD, and challenges in finding targeted preventive therapies persist. However, innovative stem cells-based postnatal therapies targeting BPD-free survival are emerging, which are likely to be offered in the first few days of life to higher-risk subpopulations of premature infants. Hence the need for easy-to-use noninvasive tools for a standardized, precise and reliable BPD assessment at a very early stage, to support clinical decision-making and to predict the response to treatment. In this non-systematic review, we present an overview of strategies for monitoring preterm infants with early and evolving BPD-PPRD, and make some remarks on future prospects, with a focus on near-infrared spectroscopy (NIRS).

Addressing global environmental problem, water splitting to produce hydrogen fuel by solar energy is getting so much attention. In the water splitting, the essential problem to solve is the development of efficient　catalysts for oxygen production. In this paper, having the prospect for a practical application of photocatalysts to artificial photosynthesis, molecular mechanisms in the current literature are briefly reviewed. At first, recent progress in the function of Mn cluster at the natural photosystem II is briefly described. The kinds of devices in which oxygen evolution reaction (OER) catalysts are used were designated; water electrolyzers, photoelectrodes, and photocatalysts. Some methods for analyzing molecular mechanism in OER catalysis, emphasized by FTIR method, are shown briefly. After describing common OER mechanisms, the molecular mechanisms are discussed for TiO2 and BiVO4 photoelectrodes with our novel data, followed by presenting of co-catalysts IrO2, RuO2, NiO2, and other metal oxides for OER catalysts. Recent reports describing OER catalysts of perovskites, layered double hydroxides (LDH), metal-organic frameworks (MOF), single atom catalysts, as well as metal complexes are reviewed. Finally, by comparing with natural photosystem, the requiring factors to improve the activity of the catalysts for artificial photosynthesis will be discussed.

A recent study demonstrated that noninvasive measurements of cortical hemodynamics and metabolism in the resting human prefrontal cortex can facilitate quantitative metrics of unilateral mitochondrial-hemodynamic coupling and bilateral connectivity in infraslow oscillation (ISO) frequencies in young adults (YA). The ISO includes three distinct vasomotions with endogenic (E), neurogenic (N), and myogenic (M) frequency bands. The goal of this study was to prove the hypothesis that there are significant differences between young and older adults (OA) in the unilateral coupling (uCOP) and bilateral connectivity (bCON) in the prefrontal cortex. Accordingly, we performed measurements from 24 OA (67.2 ± 5.9 years of age) using the same 2-channel broadband near-infrared spectroscopy (bbNIRS) setup and resting-state experimental protocol as those in the recent study (Shahdadian et al, Cerebral Cortex Communications, 2022). After quantification of uCOP and bCON in three E/N/M frequencies and statistical analysis, we demonstrated that OA had significantly weaker bilateral hemodynamic connectivity but significantly stronger bilateral metabolic connectivity than YA in the M band. Furthermore, OA exhibited significantly stronger unilateral coupling on both prefrontal sides in all E/N/M bands, particularly with a very large effect size in the M band (&gt; 1.9). These age-related results clearly support our hypothesis and were well interpreted following neurophysiological principles. The key finding of this paper is that the neurophysiological metrics of uCOP and bCON are highly associated with age and may have the potential to become meaningful features for human brain health and be translatable for future clinical applications, such as early detection of Alzheimer’s disease.

The present study investigates the relationship between the local structure, photocatalytic ability, and cathode performances in sodium-ion batteries (SIBs) and lithium-ion batteries (LIBs) using Ni-substituted goethite nanoparticles (Ni_xFe_1-xOOH NPs) with a range of 'x' values from 0 to 0.5. The structural characterization was performed applying various techniques, including X-ray diffractometry (XRD), Thermogravimetry differential thermal analysis (TG-DTA), Fourier Transform Infrared Spectroscopy (FT-IR), X-ray absorption spectroscopy (XANES/EXAFS), both measured at room temperature (RT), and ⁵⁷Fe Mössbauer spectroscopy recorded at RT and at low temperatures (LT) from 20 K to 300 K, Brunauer-Emmett-Teller surface area measurement (BET), and diffuse reflectance spectroscopy (DRS). In addition, the electrical properties of Ni_xFe_1-xOOH NPs were evaluated by impedance spectroscopy. XRD showed the presence of goethite as the only crystalline phase in prepared samples with x ≤ 0.20, and goethite and α-Ni(OH)₂ in the samples with x > 0.20. Sample with x = 0.10 (Ni10) showed the highest photo-Fenton ability with a first-order rate constant value (k) of 15.8×10^-3 min^-1. The ⁵⁷Fe Mössbauer spectrum of Ni0, measured at RT, displayed a sextet corresponding to goethite, with an isomer shift (δ) of 0.36 mm s^-1 and a hyperfine magnetic distribution (B_hf) of 32.95 T. Moreover, the DC conductivity decreased from 5.52×10^-10 to 5.30×10^-12 (Ω.cm)^–1 with 'x' increasing from 0.10 to 0.50. Ni20 showed the highest initial discharge capacity of 223 mAh g^-1, attributed to its largest specific surface area of 174.0 m² g^-1. In conclusion, Ni_xFe_1-xOOH NPs can be effectively utilized as visible-light-activated catalysts and active cathode materials in secondary batteries.

Leakages in the water distribution networks (WDNs) are real problems for utilities and other governmental agencies. Timely leak detection and location identification has been a challenge. In this paper, an integrated approach to geospatial and infrared image processing method was used for robust leak detection. The method combines drops in flow, pressure, and chlorine residuals to determine potential water leakage locations in the WDN using Geographic Information System (GIS) techniques. GIS layers were created from the hourly values of these three parameters for the city of Sharjah provided by Sharjah Electricity, Water and Gas Authority (SEWA). These layers are then analyzed for locations with dropped values of each of the parameters and are overlaid with each other. In the case where there were no overlaying locations between flow and pressure, further water quality analysis was avoided, assuming no potential leak. In the case where there are locations with drops in flow and pressure layers, these overlaying locations are then examined for drops in chlorine values. If overlaying locations are found, then these regions are considered potential leak locations. Once potential leak locations are identified, a specialized remote sensing technique can be used for precise leak location. This study also demonstrated the suitability of using an infrared camera for leak detection in a laboratory-based setup. This paper concludes that the following methodology can help water utility companies in the timely detection of leaks, saving money, time, and effort.

As an important organelle in eukaryotic cells, Golgi apparatus is responsible for processing and transporting proteins and lipids in cells. Precise monitoring the status of Golgi apparatus by targeting fluorescence imaging technology is of enormous importance but remains an attractive yet dramatically challenging task. In this study, we report the construction of the first Golgi apparatus targeted sensor with bright near-infrared fluorescence, termed as Golgi-Pdots. As a start point of our investigation, hydrophobic CDs with bright NIR fluorescence at 674 nm (fluorescence quantum yield : 12.18%), narrow emission band of 23 nm, and excellent stability were facilely prepared from Magnolia Denudata flowers through an ultrasonic method. Incorporating the CDs into a polymer matrix modified with Golgi-targeting molecules can produce the water-soluble Golgi-Pdots, which showed high colloidal stability and similar optical properties as compared to CDs. Further studies revealed that the Golgi-Pdots showed good biocompatibility and Golgi-targeting ability. Based on these fascinating properties, Golgi-Pdots have been successfully used for long term bioimaging of Golgi apparatus inside live cells.

This study aimed to investigate the atherogenicity (quality) of LDL particles in patients with acute and recovered from COVID-19 infection. The participants were adults, aged 18 years or older of both sexes. Those with positive RT-PCR results at baseline were included in the Acute COVID-19 group (n=33), and those with negative RT-PCR six months after acute infection, were included in the Recovered COVID-19 group (n=30). The LDL quality was evaluated using three validated methods: Z-scan, UV-visible spectroscopy, and Lipoprint. The Recovered COVID-19 group showed significantly higher numbers of large LDL particles (less atherogenic) than the Acute COVID-19 group (P&lt;0.05). We also found that COVID-19 infection was associated with the oxidative modification of LDL particles. D-dimer and CRP levels were correlated with Z-scan results and antioxidant-amount estimate. Moreover, we noticed that the infection left a sequel in LDL quality, even after six months of recovery. These findings highlight the importance of monitoring lipids during and after recovery from COVID-19 infection, and their potential deleterious effect on the LDL profile might correlate with the progression of atherosclerosis and poor clinical outcomes.

In order to further reduce the emissivity of the hydrophobic low infrared emissivity composite coating and improve the mechanical properties of the coating, the dispersant, adhesion enhancer, and defoamer were used to improve the dispersion state of the fillers, the interface structure, and the surface state of the hydrogen silicone oil modified polyurethane/Al composite coating. The effects of dispersant, adhesion enhancer, and defoamer on the micro-structure, emissivity, glossiness, hydrophobic property, and mechanical properties of the coating were systematically studied. The results show that the polycarboxylate anionic dispersant can obviously improve the dispersion state of flake Al powder and nano-SiO2 in the coating, so that the infrared emissivity of the coating can be reduced, and the coating can have higher hydrophobic and mechanical properties. The bonding strength between the resin matrix and the metal substrate of the coating can be significantly improved by the adhesion enhancer through the bridging action, so that the adhesion strength and impact strength of the coating can be significantly improved. The defoamer can significantly reduce the pores in the coating, so that the surface state of the coating can be significantly improved, and the mechanical properties of the coating can be significantly improved. The coating has the best emissivity (0.527), glossiness (4.3), adhesion strength (grade 1), impact strength (40 kg.cm), and hydrophobic property (water contact angle (WCA) is 140o) when the amount of dispersant, adhesion enhancer, and defoamer is 5 wt%, 4 wt%, and 1 wt%, respectively.

The particulars of stimulus-response experiments done on dynamic biosystems clearly limit what one can learn and validate about their structural interconnectivity (topology), even when collected kinetic output data are perfect (noise-free). As always, available access ports and other data limitations rule. For linear systems, exponential modes, visible and hidden, play an important role in understanding data limitations, embodied in what we call dynamical signatures in the data. We show here how to circumscribe and analyze modal response data in compartmentalizing model structures – so that modal analysis can be used constructively in systems biology model building – for nonlinear (NL) as well as linear biosystems. We do this by developing and exploiting the modal basis for dynamical signatures in hypothetical (perfect) input-output data associated with a structural model – one that includes inputs and outputs explicitly – and for NL as well as linear biosystems. The methodology establishes model dimensionality (size, complexity) from particular data sets; helps select among multiple candidate models (model distinguishability); helps in designing new experiments to extract “hidden” structure; and helps to simplify (reduce) models to their essentials. For NL biosystems, results are not as comprehensive, similarly informative about their dominant dynamical properties, and unified with linear models on invariant 2-dimensional manifolds in phase space. Some automation of these highly technical aspects of biomodeling is also introduced.

It is known that during the process of aging there is a significant decrease in the number of melanosomes in the retinal pigment epithelium (RPE) cells of the human eye. We have previously shown that the interaction of melanin melanosomes with superoxide radicals results in its oxidative degradation with the formation of water-soluble fluorescent products. In the present study, we show using fluorescence analysis, HPLC, and mass spectrometry, that visible light irradiation of melanolipofuscin granules isolated from RPE cells of the human eye results in the formation of water-soluble fluorescent products of oxidative degradation of melanin, in contrast to lipofuscin granules and melanosomes irradiation. The formation of these products occurs as a result of oxidative degradation of melanin by superoxide radicals, which are generated by the lipofuscin part of the melanolipofuscin granule. We identified these products both in the composition of melanolipofuscin granules irradiated with visible light, and in composition of non-irradiated but oxidized by superoxide radicals, melanosomes. In melanolipofuscin granules irradiated with visible light, ions that could be associated to melanin oxidative degradation products were identified by applying principal component analysis of time-of-flight secondary ion mass spectrometry (ToF-SIMS) data. Degradation of the intact melanosomes by visible light is also possible; however, this requires significantly higher irradiation intensities than for melanolipofuscin granules. It is concluded that the decrease in the concentration of melanin in RPE cells of the human eye with age is due to its oxidative degradation by reactive oxygen species generated by lipofuscin as part of melanolipofuscin granules under the action of light.

The mechanism of anionic/cationic combination collector ST-8 for the efficient separation of spodumene and feldspar was investigated by flotation tests, surface tension measurements, zeta potential measurements and infrared spectroscopy analysis. The flotation results indicated that when the optimum molar combination of sodium oleate and dodecylamine was 6:1-10:1 and pH=8.5 or so, the recovery of spodumene reached a maximum of 80% and that of feldspar reached about 24.5%. Zeta potential measurements showed that the negative shift of the kinetic potential on the surface of spodumene was much stronger than that on the surface of feldspar, indicating that the adsorption capacity of the combined collector on spodumene surface and feldspar surface was greatly different. From the surface tension as well as the synergistic parameters, there was a strong mutual attraction between dodecylamine and sodium oleate, and there was a significant synergistic effect between them. Infrared spectroscopy indicated that the combined collector chemisorbed on the mineral surface, and the intensity of the absorption peak after the action of spodumene was much stronger than that after the action of feldspar. The solution chemistry of the combined collector revealed that at pH 8.5, the positively charged ions RNH3+ and (RNH3+)22+ in dodecylamine and the negatively charged RCOO- and (RCOO-)22- ions in oleic acid form highly reactive complexes to interact with the mineral surface by electrostatic gravitation, thus achieving efficient separation of spodumene and feldspar. Finally, from the closed circuit test results, a flotation index of 6.34% Li2O grade and 88.51% Li2O recovery was obtained.

In order to apply visible light communication systems in different scenarios, this article utilizes an excellent temperature adjustable light source mixed with RGB LEDs, and applies it in a visible light communication system. It utilizes color division multiplexing technology to achieve three-channel communication, thereby improving the communication bandwidth of the system. The communication system adopts three constant current driving circuits to control the duty cycle of Pulse Width Modulation (PWM) of each channel, thereby changing the proportion of RGB LEDs, and obtaining different color temperatures to achieve the purpose of color control for mixed color LEDs. The experimental results show that when adjusting the color temperature, the change in luminous flux is very small, with fluctuations of less than 2.24%; When adjusting the brightness, the color temperature fluctuation is within 40K, which is less than the 50K color temperature limit that the human eye can distinguish, and the average color temperature error is 0.609%; Color tolerance less than 5.5×10-3 indicates good dimming effect, and the communication performance of the system is better in the high color temperature range, which is significantly superior to the low color temperature range. When the error rate is below 3.8×10-3, the total modulation bandwidth of the three channels reaches 11.7 MHz.

Group-IV GeSn photodetectors (PDs) compatible with standard complementary metal-oxide-semiconductor (CMOS) processing have emerged as a new and non-toxic infrared detection technology to enable a wide range of infrared applications. The performance of GeSn PDs is highly dependent on the Sn composition and operation temperature. Here, we develop theoretical models to establish a simple rule of thumb, namely “GeSn-rule 23”, to describe GeSn PDs’ dark current density in terms of operation temperature, cutoff wavelength, and Sn composition. In addition, analysis of GeSn PDs’ performance shows that the responsivity, detectivity, and bandwidth are highly dependent on operation temperature. This rule provides a simple and convenient indicator for device developers to estimate the device performance at various conditions for practical applications.

Infrared sensors incorporating suspended zinc oxide (ZnO) pyroelectric films and thermally-insulated silicon substrates are fabricated using conventional MEMS-based thin-film deposition, photolithography, and etching techniques. The responsivity of the pyroelectric film is improved through annealing at 500℃ for 4 h. The voltage response of the fabricated sensors is evaluated experimentally for a substrate thickness of 1 µm over a sensing range of 30 cm. The results show that the voltage signal varies as an inverse exponential function of the distance. A positioning system based on three infrared sensors is implemented in LabVIEW. It is shown that the position estimates obtained using the proposed system are in excellent agreement with the actual locations. In general, the results presented in this study provide a useful source of reference for the further development of MEMS-based pyroelectric infrared sensors.

Food safety and quality are the first steps in the food chain. This work reports a low-cost and easy-to-use optoelectronic measurement system for improving feed chain quality and safety, based on near-infrared spectrometry (NIRS) technology. This is a significant challenge for dairy farm technicians and producers who need rapid and reliable knowledge of forage quality on their farms. In most cases, instrumentation suitable for these specifications is expensive and difficult to operate. The core of the measurement system is Texas Instruments´ NIRscan Nano Evaluation Module (EVM) spectrometer. This module has a large sensing area and high resolution suitable for forage samples. To evaluate the feasibility of the prototype to analyze agrifood samples, different ways of presenting the sample, intact or ground, were tested. The final objective of the research is not just to check the efficiency of the proposed system. It is also to determine the measurement system characteristics and how to improve them.

Near-infrared (NIR) photodetectors (PDs) have attracted much attention in noninvasive medical diagnosis and treatment. Especially, the self-filtered NIR PDs are highly demandable for tremendous biomedical application due to their strong ability in wavelength discrimination. In this work, we designed and then fabricated a Si micro-holes array/Graphene (Si MHA/Gr) van der Waals (vdW) Schottky NIR photodiode by using PbS quantum dots (QDs) coating. The device exhibits a unique self-filtered NIR response with a responsivity of 0.7 A/W at -1 V and a response time of 61 μs, which are higher than that without PbS QDs coating and even most of previous Si/Gr Schottky photodiodes. The light trapping of the Si MHA and the PbS QDs coating can be attributed to the high responsivity of the vdW photodiode. Furthermore, the presented NIR photodiode can also be integrated in photoplethysmography (PPG) for real-time heart-rate (HR) monitoring. The extracted HR is in great accord with the value measured with the patient monitor by analyzing the Fourier transform of the stable and reliable fingertip PPG waveform, suggesting its potential for practical applications.

Background: In recent years, the assessment and guidance of cardiopulmonary resuscitation (CPR) quality using noninvasive and invasive monitoring techniques have been increasingly recommended. In this study, we introduce a new physiological monitoring system that simultaneously measures arterial pressure (AP), venous pressure (VP), and cerebral tissue oxygen saturation (SctO2) during CPR. Methods: This prospective observational study was conducted at a single center (Kagoshima City Hospital). Adult out-of-hospital patients aged ≥18 years with an intravenous femoral arterial line, venous line, and SctO2 monitor were included. We measured femoral arterial pressure (FAP) and femoral venous pressure (FVP) invasively if catheters were immediately inserted into the femoral artery and vein for potential candidates who require interventions such as extracorporeal cardiopulmonary resuscitation but did not receive such interventions as a result. Results: We observed several representative cases that provided the following insights: We presented several cases, including two patients with significant increases in FVP and low SctO2 values, and in both cases, return of spontaneous circulation (ROSC) was not achieved. In contrast, we also presented two cases in which CPR resulted in higher FAP compared to FVP and an upward trend in SctO2 values was observed, and both instances achieved ROSC. Conclusion: We presented a simultaneous physiological monitoring system that can monitor AP, VP, and SctO2 during CPR. Further case accumulations will be necessary to assess the variations in hemodynamic status during CPR and the association between each hemodynamic status and outcomes after cardiac arrest.

Silicon-based photodetectors, as low-cost and environmentally friendly optical sensors, are attractive. Also, their compatibility with complementary metal-oxide-semiconductor (CMOS) technology is advantageous for the development of silicon photonics systems. However, extending optical responsivity of silicon-based photodetectors to the mid-infrared (mid-IR) wavelength range remains challenging. In developing mid-IR infrared Schottky detectors, nanoscale metals are critical. Nonetheless, one key factor is the Fermi level pinning effect at the metal/silicon interface and the presence of metal-induced gap states (MIGS). Here, we demonstrate the utilization of the passivated surface layer on semiconductor materials as an insulating material in metal-insulator-semiconductor (MIS) contacts to mitigate the Fermi level pinning effect. The removal of Fermi level pinning effectively reduces the Schottky barrier height by 12.5% to 16%. The demonstrated devices exhibit a high responsivity of up to 234 μA/W at a wavelength of 2 μm, 48.2 μA/W at 3 μm, and 1.75 μA/W at 6 μm. The corresponding detectivities at 2 and 3 μm are 1.17×10^8 cm Hz^1/2 W^-1 and 2.41×10^7 cm Hz^1/2 W^-1, respectively. The expanded sensing wavelength range contributes to the application development of future silicon photonics integration platforms.

Infrared and visible image fusion technologies are used to characterize the same scene by diverse modalities. However, most existing deep learning-based fusion methods are designed as symmetric networks, which ignore the differences between modal images and lead to the source image information loss during feature extraction. In this paper, we propose a new fusion framework for the different characteristics of infrared and visible images. Specifically, we design a dual-stream asymmetric network with two different feature extraction networks to extract infrared and visible feature maps respectively. The transformer architecture is introduced in the infrared feature extraction branch, which can force the network to focus on the local features of infrared images while still obtaining their contextual information. And the visible feature extraction branch uses residual dense blocks to fully extract the rich background and texture detail information of visible images. In this way, it can provide better infrared targets and visible details for the fused image. Experimental results on multiple datasets indicate that DSA-Net outperforms state-of-the-art methods in both qualitative and quantitative evaluations. In addition, we also apply the fusion results to the target detection task, which indirectly demonstrates the fusion performances of our method.

'Huangguan' pear has significant social and economic value, and phosphorus, as one of the three main mineral elements of plants, has an irreplaceable effect on the normal growth of 'Huangguan' pear trees. The objective of this study was to predict the content of phosphorus in the pulp and peel of ‘Huangguan’ pears nondestructively and conveniently by using near-infrared spectroscopy (900–1700 nm) technology. First, twelve algorithms are used to preprocess the original spectral data, and the partial least squares regression algorithm and the gradient boosting regression tree algorithm are used to build a full-band prediction model based on the original spectral data and the processed spectral data. The characteristic wavelengths were extracted using genetic algorithms, followed by establishing a characteristic wavelength prediction model. The prediction accuracy of the models was evaluated according to the coefficient of determination R² and the relative analysis error RPD. The study found that the best prediction model for predicting phosphorus content in the pulp of 'Huangguan' pear was MSC-GA-PLSR, which had R²=0.843 and RPD=1.857 in the modelling set and R²=0.989 and RPD=7.041 in the prediction set. The best prediction model for predicting phosphorus content in the peel of ‘Huangguan’ pear was SG+SNV+FD-GA-PLSR, which had R²=0.991 and RPD=7.470 in the modelling set and R²=0.974 and RPD=4.414 in the prediction set, and the effect was good and met expectations. The results demonstrated that near-infrared spectroscopy could successfully achieve nondestructive detection of phosphorus content in the pulp and peel of 'Huangguan' pears.

The aim of this work was to investigate a new, simple one-pot combustion synthesis technique for creating sulphur-based CuS/ZnS p-n heterojunction nanocomposite photocatalysts. The study examined the photocatalytic activity and reusability of these nanocomposites in removing rhodamine B (RhB) dye under visible light irradiation. Various methods of characterisation were employed to determine the properties of the materials, including particle morphology, crystalline phases and bandgap energy. The intrinsic reaction parameters, such as catalyst loading, pH level of the solution, and initial pollutant concentration, were varied to establish the optimal photo-degradation conditions. The results showed that a binary CuS/ZnS catalyst with a 10 gL-1 loading, at pH 5, degraded 97% of 5 ppm RhB dye after 270 minutes of visible light irradiation. Addition-ally, this composite catalyst exhibited excellent chemical stability and reusability, achieving 83% RhB dye removal after five recycling runs. Scavenger tests identified the photogenerated holes (h+) and superoxide free radicals (•O2) as the primary reactive species responsible for degradation. This study provides valuable insight into the design of highly efficient nanomaterials for removing organopollutants in wastewater, and a possible reaction mechanism is proposed.

Zeolite Y with microporous and hierarchical structure containing Ti–Ni and Ti–Co oxides were obtained as active photocatalysts. Different Ti amounts (5, 10% TiO2) were supported, followed by loading of Ni or Co oxides (5 %). The X-ray diffraction evidenced the presence of TiO2 as anatase. N2 adsorption-desorption results showed type IV isotherms, for hierarchical zeolite Y samples, and a combination of type IV and I isotherms, for zeolite Y samples. UV–Vis diffuse reflectance spectra showed shift of absorption band to visible with increasing of Ti loading and especially after Co and Ni addition. A significant effect of the support was evidenced for Ti and interaction with Co/Ni species. The zeolite Y support stabilizes Ti in the 4+ oxidation state while hierarchical zeolite Y support favored the formation of Ti 3+ species and oxidation of Co and especially of Ni to 3+. Photocatalytic activity, under UV and visible light, was evaluated in degradation of amoxicillin, used as a model test. The photocatalytic mechanism was investigated using ethanol, p-benzoquinone and KI as ·OH, ·O2- radicals and hole (h+) scavengers. The best results were obtained for the immobilized Ni-Ti species on hierarchical zeolite Y support.

Olive tree vegetal materials are considered a powerful source for isolation of bioactive compounds, mainly, phenols and triterpenic acids. However, the high humidity content of them reduces their preservation and extractability to a liquid solvent. Accordingly, a drying step is crucial to homogenize the material and to obtain an efficiency extraction. We studied the influence of the drying process on the extraction efficiency of bioactive compounds from olive vegetal material. For this purpose, we evaluated the effects of four drying processes on the solid–liquid extraction of bioactive compounds from two by-products, olive leaves and pomace, and olive fruits harvested from two cultivars, Alfafara and Koroneiki. Infrared-assisted drying (IAD) was the most suited approach to obtain extracts enriched in oleuropein from leaves. In the case of pomace, lyophilization and microwaves-assisted drying led to extracts concentrated in oleacein and oleuropein aglycone, whereas IAD and oven-drying led to extracts with enhanced content in hydroxytyrosol glucoside and hydroxytyrosol, respectively. The drying process affected considerably to the chemical composition of extracts obtained from fruits. Changes in the composition of extracts were explained essentially by the drying process conditions using auxiliary energies, temperature and time, which promoted chemical alterations and increased the extractability of compounds.

The integration of spray drying and agglomeration offers significant advantages, such us continuous production with lower energy consumption. However, it is a knife-edge process with a narrow operating window and limited degrees of freedom that decide between successful agglomeration and fluidized bed blockage due to excessive moisture. In this contribution, factors influencing the spray-through agglomeration process of skim milk powder as a model system were investigated via a design of experiments. Three in-line monitoring methods were applied and tested to observe the most important parameters in the agglomeration process: product moisture and particle size distribution. Regarding the moisture content, a capacitive moisture sensor was calibrated with linear regression and a near-infrared sensor with partial least squares regression. Near-infrared spectroscopy was found to be the suitable method for determining moisture content, while the capacitive moisture sensor mainly provides information on the bulk density, the filling level or fluidization state in the fluidized bed. Additionally, particle size distribution data was extracted from the spectral data using in-line data of a spatial filter velocimetry probe in the fluidized bed. This opens the potential to monitor both parameters in real-time with a single non-invasive sensor.

In this study, the partial least squares regression (PLSR) models were developed using no pre-processing, traditional preprocessing, multi-preprocessing 5 range, multi-preprocessing 3 range, genetic algorithm (GA), and successive projection algorithm (SPA) to assess the higher heating value (HHV) and ultimate analysis of grounded biomass for energy usage employing near-infrared (NIR) spectroscopy. A novel approach was utilized based on the assumption that using multiple pretreatment methods across different sections in the entire NIR wavenumber range would enhance the performance of the model. The performance of the model obtained from 200 biomass samples for HHV and 120 samples for ultimate analysis was compared, and the best model was selected based on the coefficient of determination of validation set, root mean square error of prediction, and the ratio of prediction to deviation values. Based on model performance results, the proposed HHV model from GA-PLSR, and the N and O models from the mul-ti-preprocessing PLSR 5 range method could be used for most applications, including research, whereas the C and H models from GA-PLSR performance is fair and applicable only for rough screening. The overall findings highlight that the multi-preprocessing 5-range method, which was attempted as a novel approach in this study to develop the PLSR model, demonstrated better accuracy for HHV, C, N, and O, improving by 4.1839%, 8.1842%, 3.7587%, and 35.9404%, respec-tively. Therefore, it can be considered a reliable and non-destructive alternative method for rap-idly assessing biomass properties for energy usage and can also be used effectively in biomass trading. However, due to the smaller number of samples used in the model development, more samples are needed to update the model for a robust application.

The Global Burden of Disease Study (GBD 2019 Diseases and Injuries Collaborators) found that diabetes significantly increases the overall burden of disease, leading to a 24.4% increase in disability-adjusted life years. Persistently high glucose levels in diabetes can cause structural and functional changes in proteins throughout the body, and the accumulation of protein aggregates in the brain is associated with the progression of Alzheimer's Disease (AD).To address this burden of type 2 diabetes mellitus (T2DM), a combined aerobic and resistance exercise program was developed based on the recommendations of the American College of Sports Medicine. The prospectively registered clinical trials (https://www.clinicaltrials.gov/ct2/show/NCT04626453, https://www.clinicaltrials.gov/ct2/show/NCT04812288) involved two groups: an Intervention group of older sedentary adults with T2DM and a Control group of healthy older adults who could be either active or sedentary. The completion rate for the 2-month exercise program was high, with participants completing on an average of 89.14% of the exercise sessions. This indicated that the program was practical, feasible, and well-tolerated, even during the COVID pandemic. It was also safe, requiring minimal equipment and no supervision. The exercise instructions were easy to understand, making them suitable for older adults with cognitive decline.The near-infrared spectroscopy (NIRS) based brain and muscle oxygenation study provided evidence on brain overactivation among older adults with T2DM, supporting the compensatory theory. It also demonstrated that the 2-month combined exercise intervention effectively reduced brain overactivation and contributed to improved cognitive function. Operational modal analysis showed an exercise-related effect on the very low-frequency hemodynamic oscillations cluster, which may be associated with better vascular muscle and/or perivascular neurogenic regulation. Furthermore, we personalized the exercise duration and interval based on muscle oxygenation during physical tasks, leading to improvements in muscle oxidative capacity within just two months. This finding has practical implications for physical therapists, as they can target muscle oxygenation changes during physical tests to prescribe appropriate exercise doses for enhancing physical performance.

Infrared detection plays an important role in the military, aerospace, and other fields, which has the advantages of all-weather, high stealth, and strong anti-interference. However, infrared dim small target detection suffers from complex backgrounds, low signal-to-noise ratio, blurred targets with small area percentages, and other challenges. In this paper, we proposed a multiscale YOLOv5-AFAM algorithm to realize high-accuracy and real-time detection. Aiming at the problem of target intra-class feature difference and inter-class feature similarity, the Adaptive Fusion Attention Module - AFAM was proposed to generate feature maps that are calculated to weigh the features in the network and make the network focus on small targets. This paper proposed a multiscale fusion structure to solve the problem of small and variable detection scales in infrared vehicle targets. In addition, the downsampling layer is improved by combining Maxpool and convolutional downsampling to reduce the number of model parameters and retain the texture information. For multiple scenarios, we constructed an infrared dim and small vehicle target detection dataset, ISVD. The multiscale YOLOv5-AFAM was conducted on the ISVD dataset, compared to YOLOv7, mAP@0.5 achieves a small improvement while the parameters are only 17.98% of it. By contrast with the YOLOv5s model, mAP@0.5 was improved by 4.3% with a 6.6% reduction in the parameters. Experiments results demonstrate that the multiscale YOLOv5-AFAM has a higher detection accuracy and detection speed on infrared dim and small vehicles.

For the agricultural sector to develop sustainably in the future, progress toward more environmentally friendly technologies and methods is crucial. It is necessary to increase output while reducing the demand for energy, agrochemicals, and water resources. Although greenhouses can be utilized successfully for this purpose, significant technical advancements are required, especially when it comes to heating, to lower the use of fossil fuels and boost energy efficiency. Infrared waves and microwaves, for instance, can warm plants without having to heat the entire greenhouse volume, which takes a significant amount of energy to compensate for heat loss to the outdoor environment. In this paper, through a thorough examination of the state of the art, a general overview of novel greenhouse heating systems based on radiation is reported. First, infrared heating of greenhouses is analyzed, then the strengths and weaknesses of microwave and dielectric heating are discussed, and finally the use of microwaves for soil sterilization is examined. All outcomes suggest these irradiation-based technologies can contribute significantly to an agriculture that is energetically sustainable.

Hypoxic-ischemic encephalopathy (HIE) secondary to perinatal asphyxia occurs when the brain does not receive enough oxygen and blood. A surrogate marker for ‘intact survival’ is necessary for the successful management of HIE. The severity of HIE can be classified based on clinical presentation, including presence of seizures, using a clinical classification scale called Sarnat staging; however, Sarnat staging is subjective and the score changes over time. Furthermore, seizures are difficult to detect clinically and are associated with a poor prognosis. Therefore, a tool for continuous monitoring on the cot side is necessary, for example, electroencephalogram (EEG) that non-invasively measures the electrical activity of the brain from the scalp. Then, multimodal brain imaging, when combined with functional near-infrared spectroscopy (fNIRS), can capture the neurovascular coupling (NVC) status. In this study, we first tested the feasibility of a low-cost EEG-fNIRS imaging system to differentiate between normal, hypoxic, and ictal states in a perinatal ovine hypoxia model. Here, the objective was to evaluate a portable cot side device and autoregressive (ARX) modelling to capture the perinatal ovine brain states during a simulated HIE injury. So, ARX parameters were tested with a linear classifier using a single differential channel EEG, with varying states of tissue oxygenation detected using fNIRS, to label simulated HIE states in a perinatal ovine hypoxia model. Then, we showed the technical feasibility of the low-cost EEG-fNIRS device and ARX modeling with support vector machine classification for a human HIE case series with and without sepsis. The classifier trained with the ovine hypoxia data labelled ten severe HIE human cases (with and without sepsis) as “hypoxia” group and the four moderate HIE human cases as the “control” group. Furthermore, we showed the feasibility of experimental modal analysis (EMA) based on the ARX model to investigate the NVC dynamics using EEG-fNIRS joint-imaging data that differentiated six severe HIE human cases without sepsis from four severe HIE human cases with sepsis. In conclusion, our study showed the technical feasibility of EEG-fNIRS imaging, ARX modeling of NVC for HIE classification, and EMA that may provide a biomarker to detect sepsis effects on the NVC in HIE.

For the traditional indoor visible light communication heterogeneous network switching algorithm is only concerned with the research of vertical switching algorithm, however, the research of horizontal vertical collaborative switching combined with multi-carrier modulation technology is seldom mentioned, based on the above, this paper proposes a horizontal-vertical collaborative switching strategy based on the residency time of the communication blind area. Firstly, we use asymmetrically clipped optical OFDM (ACO-OFDM) for signal processing to reduce the bit error rate (BER) of the system by reducing the multipath interference generated during signal transmission.Secondly, the BER is used to determine the communication blind area and to calculate its dwell time. Finally, the threshold time is set as the channel interruption time in the communication blind zone, and the horizontal-vertical cooperative switching is performed by comparing with the dwell time. The simulation results show that the average network throughput is 195.28Mbps, and the average number of handovers is 1.35. Compared with instant vertical handover (IVHO) scheme and dwell vertical handover (DVHO) scheme, the average network throughput is improved by 37.21% and 28.45%, respectively, and the average switching times are reduced by 28.05% and 5.27%, respectively.

Gold nanoparticles (AuNPs) are promising candidates in various biomedical applications such as sensors, imaging, and cancer therapy. Understanding the influence of AuNPs on lipid membranes is important to assure their safety in the biological environment and to improve their scope in nanomedicine. In this regard, the present study aims to analyze the effects of different concentrations (0.5, 1, and 2 w %) of dodecanethiol functionalized hydrophobic AuNPs on the structure and fluidity of zwitterionic 1-stearoyl-2-oleoyl-sn-glycerol-3-phosphocholine (SOPC) lipid bilayer membranes using Fourier transform infrared (FTIR) spectroscopy and fluorescent spectroscopy. The size of AuNPs was found to be 2.2 ± 1.1 nm using transmission electron microscopy. FTIR results have shown that the AuNPs induced a slight shift in methylene stretching bands, while the band positions of carbonyl and phosphate group stretching were unaffected. Temperature-dependent fluorescent anisotropy measurements have shown that the incorporation of AuNPs up to 2 w % did not affect the lipid order in membranes. Overall, these results indicate that the hydrophobic AuNPs in the studied concentration did not cause any significant alterations in the structure and membrane fluidity, which suggests the suitability of these particles to form liposome-AuNP hybrids for diverse biomedical applications including drug delivery and therapy.

The administration of regional neuraxial analgesia for pain relief during labor is widely recognized as a safe and effective method involving medication delivery into the epidural or subarachnoid space in the lower back. This study proposes an innovative semantic image segmentation methodology emphasizing enhanced interpretability using convolutional Random Fourier Features and layer-wise weighted class-activation maps tailored explicitly for foot segmentation in regional analgesia monitoring. Namely, our contribution is twofold: i) a novel Random Fourier Features layer is introduced to deal with image data to enhance three well-known architectures (FCN, UNet, and ResUNet); ii) three novel quantitive measures are presented to evaluate the interpretability of a given deep learning model devoted to segmentation tasks. Our approach is rigorously evaluated on a demanding dataset of foot thermal images from pregnant women who received epidural anesthesia. Its small size and considerable variability characterize the dataset. Our validation results demonstrate that the proposed methodology not only achieves competitive foot segmentation performance but also significantly enhances the explainability of the process, rendering it well-suited for applications such as epidural insertion during labor.

Virgin coconut oil (VCO) is a functional food with important health benefits. Its economic interest encourages fraudsters to deliberately adulterate VCO with cheap and low-quality vegetable oils for financial gain, causing health and safety problems for consumers. In this context, there is an urgent need for rapid, accurate and precise analytical techniques to detect VCO adulteration. In this study, the use of Fourier Transform Infrared (FTIR) spectroscopy combined with Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS) methodology was evaluated to verify purity or adulteration of VCO with reference to several low-cost commercial oils such as sun-flower, maize and peanut oils. Control charts were developed to assess the purity of oil samples using MCR-ALS scores values calculated from a data set of pure and adulterated oils. In addition, quantification models were developed using MCR-ALS with correlation constraint for adulterated coconut oil to assess the blend composition. Different data pre-treatment strategies were tested in order to best extract the information contained in the sample fingerprints, and the calibration models were optimised using a genetic algorithm (GA) to select the most important variables. The models gave satisfactory results in external validation procedure, with absolute errors of less than 4.6 % for samples adulterated with sunflower, maize and peanut oils.

The communication link between the base station and the mobile sensor networks, such as multi-agent systems for collaborative tasks which include ground mobile robots and drones, is crucial for localization and success of tasks in indoor environments. The Power-domain Non-Orthogonal Multiple Access (P-NOMA) is an emerging multiplexing technique that enables the base station to accumulate signals for different agents using the same time-frequency channel. The environment information such as distance from the base station is required at the base station to calculate communication channel gains and allocate suitable signal power to each agent. The accurate estimate of the position for power allocation of P-NOMA in a dynamic environment is challenging due to changing location of the end-agent and shadowing. In this paper, we take advantage of the two-way Visible Light Communication (VLC) link to: (1) estimate the position of the end-agent in a real-time indoor environment based on the signal power received at the base station and (2) allocate resources using the Simplified Gain Ratio Power Allocation (S-GRPA) scheme with the look-up table method. In addition, we use the Euclidean Distance Matrix (EDM) to estimate the location of the end-agent whose signal was lost due to shadowing.

The rampant misuse of drones poses a serious threat to national security and human life. Currently, the CNN method has been widely used in drone detection. However, there is a challenge that traditional CNN cannot cope with, which is small drone targets often have reduced amplitude or even lost features in infrared images. This paper proposes a Progressive Feature Fusion Network (PFFNet) that gradually increases the response amplitude of the target in the deep network. The Feature Selection Model (FSM) is designed to improve the utilisation of the output coding graph and enhance the feature representation of the target in the network. A lightweight segmentation head is also designed to achieve progressive feature fusion with multi-layer outputs. Experimental results show that the proposed algorithm can achieve low duration and high accuracy in drone target detection. On the public dataset, the IoU is improved by 2.53% and the detection time is reduced by 81.03%.

The compilation summarizes results so far gathered in a project that investigates the atom with classical (Newtonian) physics. It posits that the atom’s wave-particle dual nature is real, objective and intrinsic; the wave gives rise to the cosmic vacuum field while the particle, of course, manifests condensed matter. Light’s π radians oscillation manifests, on molar scale, significant radial tension in the vacuum field, the effect, amongst others, causes molecular matter to precipitate out of the vacuum – so-called ‘molecular outflow’. Cosmic vacuum field radial tension relates to molecular mass, in other words, a mass-radius (M-R) relationship is uncovered. It is argued that using the M-R relation it is possible to perform a valid simulation of the cosmic physical reality. The three states of matter are meaningfully accounted for using the atom’s e-m radiation wavelength. It is explained that force, be it of any kind whatsoever, originates in the atomic waveform, i.e., the cosmic vacuum field.

Visible light communication (VLC) can offer the advantages of license and electromagnetic interference (EMI) free wireless transmission. As optical signal does not interference with the radio-frequency (RF) signal, VLC can be used to augment RF wireless communication to provide extra communication capacity while without degrading the performance of both signals. In order to achieve high performance VLC transmission, optical alignment between the optical transmit (Tx) and receiver (Rx) is very critical to enhance the received signal-to-noise ratio (SNR). Optical beam-steering at the Tx can be utilized to ensure narrow optical beam can reach the Rx; however, complicated and active tracking are required. Lenses or compound parabolic concentrators (CPCs) can be install in front of the Rx for focusing to enhance the SNR. However, these will limit the Rx field-of-view (FOV) and making the VLC transmission more subjected to misalignment issue. Hence, many creative optical antennas have been proposed and demonstrated using special optical materials as well as special Rx to enhance the FOV of VLC systems. However, they have their limitations, such as data rates and FOVs. In this work, we put forward and demonstrate a bi-direction free-space VLC system supporting multiple moveable Rxs using a light-diffusing optical fiber (LDOF). The downlink (DL) signal is launched from an head-end or central office (CO) far away to the LDOF at the client side via a free-space transmission. When the DL signal is launched to the LDOF, which acts as an optical antenna to re-transmit the DL signal to different moveable Rxs. The uplink (UL) signal is sent via the LDOF towards the CO. In a proof-of-concept demonstration, the LDOF is 100 cm long and the free space VLC transmission between the CO and the LDOF is 100 cm. 210 Mbit/s DL and 850 Mbit/s UL transmissions, meeting the pre-forward-error-correction bit error rate (pre-FEC BER = 3.8 × 10−3) threshold are achieved.

The near-infrared (NIR) organic dyes with strong ultrafast nonlinear optical (NLO) activities are of importance for various applications. However, such kinds of dyes are still scarce. In this work, we have compared the NLO properties of two NIR Aza-BODIPY derivatives, in which the strong electron-donating groups, namely 4-(N, N-dimethylamino) phenyl and 1-ethyl-1,2,3,4-tetrahydroquinoline groups, are connected with the cores of Aza-BODIPY. Z-Scan experimental results show that two Aza-BODIPY derivatives exhibit strong saturation absorption and large modulation depth under the excitation of femtosecond pulses at 800 nm. Under 1300 nm excitation, two derivatives exhibit strong nonlinear refraction. In addition, the Aza-BODIPY derivatives also display effective two-photon excited fluorescence emission in the wavelength range of 1200-1600 nm. Based on the experimental results, it is found that 1-ethyl-1,2,3,4-tetrahydroquinoline group can more effectively enhance the NLO properties of Aza-BODIPY derivatives compared with the 4-(N, N-dimethylamino) phenyl group, thus providing new possibilities for the design and development of NIR NLO materials.

The shortwave infrared Ge-Si photodetector will become the core device of the LiDAR optical receiver. In order to meet the urgent demand for photodetectors in the LiDAR field, we have designed and produced a 32×32 pixel Ge-Si photodetector array proposed and developed to meet the performance requirements of the detector array. A dark current detection system for fast scanning and detecting large-scale Ge-Si detector arrays is proposed and developed to achieve rapid detection of dark current in each pixel of the detector. The system was used to validate the main performance indicators of the detector array we designed, achieving rapid discrimination of array performance and rapid localization of damaged pixels. The scanning test results show that the average dark current of the detector array chip we designed is at the nano ampere level, and the proportion of bad points is less than 1%. The consistency of the array chip is high, which can meet the requirements of light detection at the receiving end of the LiDAR. This work laid the foundation for our subsequent development of a LiDAR prototype system.

Introduction: Successful R0 resection is crucial for the survival of patients with primary liver cancer (PLC) or liver metastases. Up to date, surgical resection lacks a sensitive, real-time intraoperative imaging modality to determine R0 resection. Real-time intraoperative visualization with near-infrared light fluorescence (NIRF) using indocyanine green (ICG) may have the potential to meet this demand. This study evaluates the value of ICG visualization in PLC and liver metastases surgery regarding R0 resection rates. Materials and Methods Patients with PLC or liver metastases were included in this prospective cohort study. ICG 10mg was administered intravenously 24 hours before surgery. Real-time intraoperative NIRF visualization was made with the SpectrumTM Fluorescence Imaging Camera System. First, all liver segments were inspected with the fluorescence imaging system and intraoperative ultrasound for identification of the known tumor as well as additional lesions, compared to preoperative MRI. PLC, liver metastases, and additional lesions were then resected according to oncological principles. Of all resected specimens the resection margins were analyzed with the fluorescence imaging system for ICG positive spots right after resection. Histology of additional detected lesions as well as ICG fluorescence compared to histological resection margins were assessed. Results Of the 66 included patients median age was 65.5 years (IQR 58.7 - 73.9), 27 (40.9%) were female and 18 (27.3%) were operated laparoscopically. Additional ICG positive lesions were detected in 23 (35.4%) patients of which nine (29%) were malignant. In patients with no fluorescent signal at the resection margin, R0 rate was 93.9%, R1 rate was 6.1%, and R2 rate was 0% compared to a ICG positive resection margin with a R0 rate of 64.3%, R1 rate of 21.4%, and R2 rate of 14.3% (p=0.005). One and two year overall survival were 95.2% and 88.4%, respectively. Conclusion The here presented study provides significant evidence that ICG NIRF guidance helps to identify R0 resection intraoperatively. This offers a true potential to verify radical resection and improve patients´ outcome. Furthermore, implementation of NIRF guided imaging in liver tumor surgery allows to detect a considerable amount of additional malignant lesions.

Knowing, with reasonable accuracy, the dry matter (DM) content of Hass avocado fruit will help determine when the fruit must be harvested. The reliability of predictive models based on near infrared spectra for DM quantification depends on the ability of the spectra to be representative of the DM gradient within a whole fruit. The aim of this work was to develop a methodology to determine the optimum number of spectra to develop a robust model for DM content quantification. Three spectra were recorded for each zone of the intact fruit: peduncle, equator, and base. Each scanning point was sampled, and the DM content was determined using oven drying. Two-way ANOVA confirmed the DM gradient within the whole fruit. This gradient was observed within spectra using the RMS (root mean square) criterion and PCA. The PLS models showed that at least one spectrum per zone could be enough to construct an efficient and robust model for dry matter quantification.

Diffuse optical tomography (DOT) is an optical medical imaging method that can assess the structural properties of tissues and their functional characteristics, such as hemoglobin concentration, water content, as well as lipid concentration, via three-dimensional image reconstruction. This paper presents the theoretical basis and working principle of diffuse optical tomography. The paper explains how the optical properties of tissue can be imaged by photon migration techniques based on diffusion theory. The author presents the reasoning for near-infrared (NIR) imaging as the most effective technique in terms of quantitative recovery of spectroscopic optical parameters. This work also listed various advantages, applications, and challenges of DOT. The paper also briefly discusses current progress in near-infrared medical imaging and its future direction.

Recently, the interest in silicon-based detectors capable of detecting single photons in the near-infrared is growing mainly due to LiDAR applications, autonomous driving in particular. Silicon single-photon avalanche diodes are one of the most interesting single-photon NIR technology available on the market, nevertheless, their efficiency is hindered by the low absorption coefficient of Si in the NIR. The idea is the integration of CMOS-compatible nanostructures, specifically, silver grating array supporting Surface Plasmons Polaritons (SPPs), to confine superficially the incoming NIR photons and therefore increase photons probability to generate an electron-hole pair. The plasmonic silver array is geometrically fine-tuned using time domain simulation software to achieve maximum detector performance at 950 nm. Then, the plasmonic silver array is integrated by means of the focused ion beam technique on the detector. Finally, the integrated detector is electro-optically characterized, demonstrating a quantum efficiency of 13 at 950 nm, 2,2 times more than the reference detector. This result suggests the production of a device capable of detecting single NIR photons, at a very low cost and compatible with CMOS, thus integrable on existing technology platforms.

The optical properties and physiology of biological tissue, as well as how near-infrared (NIR) light interacts with the tissue, both play a significant role in interpreting the tissue probing optical measurements, and in solving the inverse problem of near-infrared spectroscopy (NIRS)-based medical imaging modalities such as diffuse optical tomography and functional near-infrared spectroscopy. This paper discusses the optical properties of tissue, specifically in the NIR wavelength range, which influence NIRS measurements in NIRS-based medical imaging. There is an easy-to-understand explanation given in this paper of the NIR light-tissue interaction phenomenon. The mathematical explanation, the processes involved in the interaction, and the rationale for a few approximations are described. Various types of chromophores present in the tissue, their composition in the tissue, and how these chromophores overall affect the scattering and absorption of NIR light are presented. The absorption spectra of these chromophores are shown. Finally, the paper concludes with the author’s perspective on two NIRS-based medical imaging modalities, diffuse optical tomography, and functional near-infrared spectroscopy.

The increasing regulatory pressure to monitor and reduce GHG emissions and air pollutants requires cost-effective methods for their surveillance. The most common technique used for scientific investigations on gas concentration monitoring in barns are accurate but expensive and with a complex maintenance. This research study analysed the potential use of a low-cost portable measurement devices for the measurement of ammonia (NH3) and carbon dioxide (CO2) concentrations in an open dairy barn. A comparison between gas concentrations acquired at different heights from the floor by using portable devices and those acquired by a photoacoustic infrared multigas spectroscope (i.e., reference measurement) in the same sampling locations was carried out to determine the precision of the low-cost portable devices. The performance of low-cost portable devices was statistically analysed by the application of the one-way analysis of variance, correlation analysis and regression analysis. The results showed a significant difference between gas concentration values at various heights from the floor for both NH3 and CO2. The correlations between concentrations acquired by the low-cost portable device and the INNOVA were statistically significant (r=0.83; P&lt;0.001) for gas concentrations monitored at 0.4 m from the floor. Compared with the reference measurement device, the low-cost devices were effective in the monitoring of NH3 concentrations at 0.40 m from the floor though it underestimated them in the barn at increasing of the height from the floor, whereas the device was not adequate for CO2 concentrations. In detail, the relative measurement error of the low-cost devices compared to INNOVA was reduced close to the floor during NH3 concentration measurements. Within these limitations, this device could be useful for monitoring NH3 concentration in the barn and to assess variation in NH3 concentrations mainly related to the animal occupied zone. Further efforts are needed in this field of research to identify low-cost device that could simplify emission estimation from open dairy barns.

Socks with the same three-dimensional plantar design, but with different compositions in the separation of their weaves could have different thermoregulatory effects. The objective of this study was therefore to evaluate the temperatures on the sole of the foot after a 10-km run, using two models of socks with different weave separations. In a sample of 20 individuals (14 men and 6 women), plantar temperatures were analysed using a Flir E60bx® (Flir Systems) thermographic camera before and after a run of 10 km wearing two models of socks that had different separations between the fabric weaves (5 mm versus 3 mm). After the post-exercise thermographic analysis, the participants responded to a Likert type survey to evaluate the physiological characteristics of the two models of socks. There was a significant increase in temperature in the areas of interest (p&lt;0.001) after the 10-km run with both models of sock. The temperature under the 1st metatarsal head was higher with the AWC 2.1 model than with the AWC 1 (33.6±2.0°C vs 33.2±2.1°C) (p = 0.014). No significant differences were found in the scores on the physiological characteristics comfort survey (p&gt;0.05 in all cases. The two models presented similar thermoregulatory effects on the soles of the feet, although the model with the narrowest weave separation generated greater temperatures (+0.4°C) under the first metatarsal head.