Search Results (105)

The unique vegetation in riparian zones is fundamental for various ecological and socio-economic functions in these transitional areas. Sustainable management requires detailed spatial information about the occurring flora. Here, we present a Deep Learning (DL)-based approach for processing multimodal high-resolution remote sensing data (aerial RGB and near-infrared (NIR) images and elevation maps) to generate a classification map of the tidal Elbe and a section of the Rhine River (Germany). The ground truth was based on existing mappings of vegetation and biotope types. The results showed that (I) despite a large class imbalance, for the tidal Elbe, a high mean Intersection over Union (IoU) of about 78% was reached. (II) At the Rhine River, a lower mean IoU was reached due to the limited amount of training data and labelling errors. Applying transfer learning methods and labelling error correction increased the mean IoU to about 60%. (III) Early fusion of the modalities was beneficial. (IV) The performance benefits from using elevation maps and the NIR channel in addition to RGB images. (V) Model uncertainty was successfully calibrated by using temperature scaling. The generalization ability of the trained model can be improved by adding more data from future aerial surveys. Full article

Photosensitizers with high singlet oxygen (¹O₂) generation capacity under near-infrared (NIR) irradiation are essential and challenging for photodynamic therapy (PDT). A simple yet effective molecular design strategy is realized to construct 1 + 1 > 2 photosensitizers with synergistic effects by covalently integrating iridium complexes with cyanine via ether linkages, as well as introducing aldehyde groups to suppress non-radiative decay, named CHO−Ir−Cy. It is demonstrated that CHO−Ir−Cy successfully maintains the NIR absorption and emission originated from cyanine units and high ¹O₂ generation efficiency from the iridium complex part, which gives full play to their respective advantages while compensating for shortcomings. Density functional theory (DFT) calculations reveal that CHO−Ir−Cy exhibits a stronger spin–orbit coupling constant (ξ (S1, T1) = 9.176 cm⁻¹) and a reduced energy gap (ΔE = −1.97 eV) between triplet excited states (T₁) and first singlet excited states (S₁) compared to parent Ir−Cy or Cy alone, directly correlating with its enhanced ¹O₂ production. Remarkably, CHO−Ir−Cy demonstrates superior cellular internalization in 4T1 murine breast cancer cells, generating substantially elevated ¹O₂ yields compared to individual Ir−Cy/Cy under 808 nm laser irradiation. Such enhanced reactive oxygen species production translates into effective cancer cell ablation while maintaining favorable biocompatibility, significant phototoxicity and negligible dark toxicity. This molecular engineering strategy overcomes the inherent NIR absorption limitation of traditional iridium complexes and ensures their own high ¹O₂ generation ability through dye–metal synergy, establishing a paradigm for designing metal–organic photosensitizers with tailored photophysical properties for precision oncology. Full article

Chalcogen–containing therapeutic agents (TAs), which include sulfur (S), selenium (Se), and tellurium (Te) atoms, have recently emerged as a promising class of photosensitizers (PSs) and photothermal agents (PTAs) for cancer phototherapy. The incorporation of heavier chalcogens into organic chromophores leads to visible–to–near–infrared (VIS–NIR) light absorption, efficient triplet harvesting, and adequate heat and energy transfer efficiency, all of which are paramount for photodynamic therapy (PDT) and photothermal therapy (PTT). However, chalcogen–based PSs/PTAs suffer from photostability, bioavailability, and targeted delivery issues, which minimize their PDT/PTT performances. Nevertheless, significant progress in the rational design of nanoencapsulation strategies has been achieved to overcome the challenges of chalcogen–based TAs for effective phototherapeutic cancer treatment. This review highlights the recent advances (within the last five years) in nano-drug delivery approaches adapted for chalcogen–substituted PSs/PTAs for PDT, PTT, or synergistic PDT/PTT, integrating imaging and treatment. The PSs/PTAs described in this review are classified into three classes: (i) sulfur, (ii) selenium, and (iii) tellurium–containing TAs used in phototherapy applications. This review offers a comprehensive perspective on the design of chalcogen–substituted photosensitizers (PSs) and photothermal agents (PTAs), covering spectroscopic and computational characterization, nanoformulation strategies, and their roles in enhancing reactive oxygen species (ROS) generation and photothermal conversion efficiency for improved in vitro and in vivo performance. We hope this work will encourage further research into nanotechnological strategies designed to enhance the phototherapeutic efficacy of chalcogen–containing therapeutic agents. Full article

Three new asymmetrically coordinated lanthanide derivatives based on the bicompartmental salen-type ligands N,N′-bis(3-ethoxysalicylidene)propylene-1,3-diamine (H₂EtOsalpr) and 3-ethoxysalicylaldehyde (HEtvain) have been synthesized and structurally and photophysically characterized. All the compounds show dimeric structures of the general formula [Ln(H₂EtOsalpr)(NO₃)₂(Etvain)]₂ (Ln = Nd, Eu, Dy), with each salen-type ligand bridging two lanthanide ions. The Etvain ligand comes from the H₂EtOsalpr decomposition being coordinated to the corresponding lanthanide. The Nd(III) derivative shows fluorescence emission in the NIR region, but for the Eu(III) and Dy(III) compounds, only a broad band, attributed to the ligand emission, was observed. Full article

The design, synthesis, and study of lanthanide coordination compounds with luminescent and magnetic properties attractive in modern technologies is still a pressing and challenging task. In the present work, a series of coordination compounds of tetrakis-carbacylamidophosphate PPh₄[LnL₄] (where HL = diphenyl-N-benzoylamidophosphate) with several lanthanide ions such as Nd^III, Sm^III, Dy^III, and Tm^III was prepared and studied by X-ray analysis and luminescence spectroscopy at 293 and 77 K, as well as by magnetic measurements. Coordination compounds are not isostructural, but the type of coordination is the same. All of them have intense sensitized emission. PPh₄[SmL₄], PPh₄[DyL₄], and PPh₄[TmL₄] chelates are characterized by dual visible and infrared emission and mechanoluminescence. In addition, PPh₄[DyL₄] has multifunctional properties such as Vis and NIR emissions, brilliant mechanoluminescence and single-ion molecular magnet (SIM) properties. This type of compound holds great promise in multifunctional magnetic radiation converters. Full article

Background: Many studies, for example, on taste-visual dissonance, have shown that the influence of the visual cortex on taste sensation is enormous. The presented work aims to investigate, using fNIRS, whether a taste stimulus, in this case, the taste of bitter, also causes stimulation of the visual cortex in the fNIRS study. Methods: fNIRS was used to examine 51 participants (204 examinations, 9996 records), collecting signals from the left hemisphere. Differences between the maximum and minimum changes in oxyHb concentrations (ΔoxyHb) for the areas of the brain cortex considered responsible for recording visual and gustatory signals were analyzed. Protocols I, II, III, and IV—activation with distillate water, coffee with lower concentration, reference (no stimulation), and coffee with higher concentration, respectively, were used. Results: We recorded high signals for teste activation on channels covering the gustatory cortex, which confirms the correctness of the choice of research method. As expected, a significant statistical difference was observed between protocols I, II, and IV and reference III (without stimulation). What seems important is the fact that we also received high signals for the channels 45–49, which cover the visual cortex. The statistical analysis shows no differences between protocols I, II, and IV (different taste activation—water, coffee A, and coffee B) for specific channels for analyzing regions of interest. As a result of the analysis of the correlation between the subjective bitterness assessment solutions and the signal ΔoxyHb height, it was observed that a statistically significant correlation, although weak, occurs only for 14 and gustatory channels, only for coffee with a higher concentration. Additionally, the only statistically significant difference between women and men was observed in Protocol I (water), where the ΔoxyHb signal was twice as high in women compared to men. Conclusions: In conclusion, we can clearly state that the senses of sight and taste work closely together. Moreover, this cooperation is not one-sided: while visual activation influences taste perception, interestingly, a taste stimulus can also generate a hemodynamic response, activating the visual cortex. Full article

By combining Er^III and Yb^III ions with 3,6-dithiophene-anilate (Th₂An) and scorpionate hydrotris(pyrazol-1-yl)borate (HBpz₃⁻) ligands new luminescent dinuclear complexes are obtained. The two materials formulated as [((HB(pz)₃)₂Yb)₂(μ-th₂An)]·4DCM·1.3H₂O 1Yb and [((HB(pz)₃)₂Er)₂(μ-th₂An)]·4DCM·1.8H₂O 1Er, respectively, have been structurally characterized by SC-XRD and PXRD studies. This study presents a comprehensive investigation of the photophysical properties of the Th₂An ligand for the first time. Our findings reveal the crucial role of the thiophene anilate as an effective optical antenna, which sensitizes near-infrared (NIR)-emitting lanthanide ions, specifically Er^III and Yb^III. The significant impact of vibrational quenching on the Ln^III NIR emission efficiency has been also highlighted. Full article

Hypoxia, characterized by inadequate tissue oxygenation, may result in tissue damage and organ failure if not addressed. Current detection approaches frequently prove insufficient, depending on symptoms and rudimentary metrics such as tissue oxygenation, which fail to comprehensively identify the onset of hypoxia. The European Pressure Ulcer Advisory Panel (EPUAP) has recognized sweat lactate as a possible marker for the early identification of decubitus ulcers, nevertheless, neither sweat lactate nor oxygenation independently provides an appropriate diagnosis of hypoxia. We have fabricated a wearable device that non-invasively and concurrently monitors sweat lactate and tissue oxygenation to fill this gap. The apparatus comprises three essential components: (i) a hydrogel-based colorimetric lactate biosensor, (ii) a near-infrared (NIR) sensor for assessing tissue oxygenation, and (iii) an integrated form factor for enhanced wearability. The lactate sensor alters its hue upon interaction with lactate in sweat, whereas the NIR sensor monitors tissue oxygenation levels in real-time. The device underwent testing on phantom exhibiting tissue-mimicking characteristics and on human sweat post aerobic and anaerobic activities. Moreover, the device was demonstrated to be capable of real-time “on-body” simultaneous monitoring of sweat lactate spikes and tissue oxygenation (StO₂) drops, which showed strong correlation during a hypoxia protocol. This innovative technology has a wide range of potential applications, such as post-operative care, sepsis detection, and athletic performance monitoring, and may provide economical healthcare solutions in resource-limited regions. Full article

This study aims to classify plant communities by applying discriminant analysis based on principal components (DAPC) on near-infrared spectra (FT-NIRS) starting from fresh herbage samples. Grassland samples (n~156) belonged to (i) recent alfalfa pure crops (CAA), (ii) recent grass–legume mixtures (GLM), (iii) permanent meadows derived from old alfalfa stands that were re-colonized (PMA), and iv) permanent meadows originated from old grass–legume mixtures (PLM). Samples were scanned using FT-NIRS, and a multivariate exploration of the original spectra was performed using DAPC. The following two scenarios were proposed: (i) cross-validation, where all data were used for model training, and (ii) semi-external validation, where the group assignment was performed without samples of the training set. The first two components explained 98% of the total variability. The DAPC model resulted in an overall assignment success rate of 77%, and, from cross-validation, it emerged that it was possible to assign the CAA and PMA to their group with more than of 80% of success, which were different in botanical and chemical composition. In comparison, GLM and PLM obtained lower success of assignment (~52%). External validation suggested similarity between PLM and GLM groups (93%) and between GLM and PLM (77%). However, a dataset increase could improve group differentiation. Full article

This paper presents an actuator fault-tolerant control (FTC) strategy for a hexacopter unmanned aerial vehicle (UAV) designed specifically for precision agriculture applications. The proposed approach integrates advanced sensing techniques, including the estimation of Near-Infrared (NIR) reflectance from RGB imagery using the Pix2Pix deep learning network based on conditional Generative Adversarial Networks (cGANs), to enable the calculation of the Normalized Difference Vegetation Index (NDVI) for health assessment. Additionally, trajectory flight planning is developed to ensure the efficient coverage of the targeted agricultural area while considering the vehicle’s dynamics and fault-tolerant capabilities, even in the case of total actuator failures. The effectiveness of the proposed system is validated through simulations and real-world experiments, demonstrating its potential for reliable and accurate data collection in precision agriculture. An NDVI test was conducted on a sugarcane crop using the estimated NIR to assess the crop’s condition during its tillering stage. Therefore, the main contributions this paper include (i) the development of an actuator FTC strategy for a hexacopter UAV in precision agriculture applications, integrating advanced sensing techniques such as NIR reflectance estimation using deep learning network; (ii) the design of a flight trajectory planning method ensuring the efficient coverage of the targeted agricultural area, considering the vehicle’s dynamics and fault-tolerant capabilities; (iii) the validation of the proposed system through simulations and real-world experiments; and (iv) the successful integration of FTC scheme, advanced sensing, and flight trajectory planning for reliable and accurate data collection in precision agriculture. Full article

As a commonly used metal ion, iron(II) (Fe²⁺) ions pose a potential threat to ecosystems and human health. Therefore, it is particularly important to develop analytical techniques for the rapid and accurate detection of Fe²⁺ ions. However, the development of near-infrared (NIR) luminescence probes with good photostability for Fe²⁺ ions remain challenging. In this work, we report a novel iridium(III) complex-based luminescence probe for the sensitive and rapid detection of Fe²⁺ ions in a solution based on an Fe²⁺-mediated reduction reaction. This probe is capable of sensitively detecting Fe²⁺ ions with a limit of detection (LOD) of 0.26 μM. Furthermore, this probe shows high photostability, and its luminescence remains stable under 365 nm irradiation over a time period of 30 min. To our knowledge, this is first iridium(III) complex-based NIR probe for the detection of Fe²⁺ ions. We believe that this work provides a new method for the detection of Fe²⁺ ions and has great potential for future applications in water quality testing and human monitoring. Full article

Second near-infrared (NIR-II) fluorescence imaging is the most advanced imaging fidelity method with extraordinary penetration depth, signal-to-background ratio, biocompatibility, and targeting ability. It is currently booming in the medical realm to diagnose tumors and is being widely applied for fluorescence-imaging-guided tumor surgery. To efficiently execute this modern imaging modality, scientists have designed various probes capable of showing fluorescence in the NIR-II window. Here, we update the state-of-the-art NIR-II fluorescent probes in the most recent literature, including indocyanine green, NIR-II emissive cyanine dyes, BODIPY probes, aggregation-induced emission fluorophores, conjugated polymers, donor–acceptor–donor dyes, carbon nanotubes, and quantum dots for imaging-guided tumor surgery. Furthermore, we point out that the new materials with fluorescence in NIR-III and higher wavelength range to further optimize the imaging results in the medical realm are a new challenge for the scientific world. In general, we hope this review will serve as a handbook for researchers and students who have an interest in developing and applying fluorescent probes for NIR-II fluorescence-imaging-guided surgery and that it will expedite the clinical translation of the probes from bench to bedside. Full article

Plants respond to biotic and abiotic pressures by changing their biophysical and biochemical aspects, such as reducing their biomass and developing chlorosis, which can be readily identified using remote-sensing techniques applied to the VIS/NIR/SWIR spectrum range. In the current scenario of agriculture, production efficiency is fundamental for farmers, but diseases such as target spot continue to harm soybean yield. Remote sensing, especially hyperspectral sensing, can detect these diseases, but has disadvantages such as cost and complexity, thus favoring the use of UAVs in these activities, as they are more economical. The objectives of this study were: (i) to identify the most appropriate input variable (bands, vegetation indices and all reflectance ranges) for the metrics assessed in machine learning models; (ii) to verify whether there is a statistical difference in the response of NDVI (normalized difference vegetation index), grain weight and yield when subjected to different levels of severity; and (iii) to identify whether there is a relationship between the spectral bands and vegetation indices with the levels of target spot severity, grain weight and yield. The field experiment was carried out in the 2022/23 crop season and involved different fungicide treatments to obtain different levels of disease severity. A spectroradiometer and UAV (unmanned aerial vehicle) imagery were used to collect spectral data from the leaves. Data were subjected to machine learning analysis using different algorithms. LR (logistic regression) and SVM (support vector machine) algorithms performed better in classifying target spot severity levels when spectral data were used. Multivariate canonical analysis showed that healthy leaves stood out at specific wavelengths, while diseased leaves showed different spectral patterns. Disease detection using hyperspectral sensors enabled detailed information acquisition. Our findings reveal that remote sensing, especially using hyperspectral sensors and machine learning techniques, can be effective in the early detection and monitoring of target spot in the soybean crop, enabling fast decision-making for the control and prevention of yield losses. Full article

This study aimed to synthesize magnesium oxide (MgO) using a colloidal starch method for two primary purposes: the removal of chromium (III) ions from synthetic wastewater and the subsequent use of the chromium-containing material as synthetic inorganic pigments (SIPs) in commercial paints. The synthesis used to obtain the oxide (St-MgO) is a promising method for using plants, such as cassava, as green fuels due to their abundance, low cost, and non-toxicity. With this, the oxide showed greater porosity and alkalinity, compared to commercial magnesium oxide (Cm-MgO). The MgO samples were subjected to structural characterization using XRD and FTIR, surface area and pore volume study by B.E.T. and SEM, and chemical composition by ICP-OES and thermogravimetric analysis (TGA). The crystalline periclase phase was identified for both samples, but the brucite phase was shown to be a secondary phase for the commercial sample. After the removal of chromium ions, the brucite crystalline phase became the majority phase for the samples, regardless of the concentration of ions removed. The pigments were characterized by color measurements and discussed in terms of colorimetric parameters using the CIELab method and electron spectroscopy (VIS-NIR). This study also evaluated the colorimetric stability of green pigments in aggressive environments (acidic and alkaline) over a 240 h exposure period, demonstrating minimal color difference. This study aims to develop materials for the decontamination of wastewater containing chromium and its reuse as a synthetic inorganic pigment, using an innovative and sustainable synthesis method. Full article

Visible-near infrared (Vis-NIR) and mid-infrared (MIR) spectroscopy are increasingly being used for the fast determination of soil properties. The aim of this study was (i) to test the use of MIR spectra (Agilent 4300 FTIR Handheld spectrometer) for the prediction of soil properties and (ii) to compare the prediction performances of MIR spectra and Vis-NIR (ASD FieldSpecPro) spectra; the Vis-NIR data were adopted from a previous study. Both the MIR and Vis-NIR spectra were coupled with partial least squares regression, different pre-processing techniques, and the same 114 soil samples, collected from the agricultural land located between boreal forests and semi-arid steppe belts (Kastanozems). The prediction accuracy (R² = 0.70–0.99) of both techniques was similar for most of the soil properties assessed. However, (i) the MIR spectra were superior for estimating CaCO₃, pH, SOC, sand, Ca, Mg, Cd, Fe, Mn, and Pb. (ii) The Vis-NIR spectra provided better results for silt, clay, and K, and (iii) the hygroscopic water content, Cu, P, and Zn were poorly predicted by both methods. The importance of the applied pre-processing techniques was evident, and among others, the first derivative spectra produced more reliable predictions for 11 of the 17 soil properties analyzed. The spectrally active CaCO₃ had a dominant contribution in the MIR predictions of spectrally inactive soil properties, followed by SOC and Fe, whereas particle sizes and hygroscopic water content appeared as confounding factors. The estimation of spectrally inactive soil properties was carried out by considering their secondary correlation with carbonates, clay minerals, and organic matter. The soil information covered by the MIR spectra was more meaningful than that covered by the Vis-NIR spectra, while both displayed similar capturing mechanisms. Both the MIR and Vis-NIR spectra seized the same soil information, which may appear as a limiting factor for combining both spectral ranges. The interpretation of MIR spectra allowed us to differentiate non-carbonated and carbonated samples corresponding to carbonate leaching and accumulation zones associated with topography and land use. The prediction capability of the MIR spectra and the content of nutrient elements was highly related to soil-forming factors in the study area, which highlights the importance of local (site-specific) prediction models. Full article