Agricultural soils serve as crucial storage sites for soil organic carbon (SOC). Their appropriate management is pivotal for mitigating climate change. To evaluate spatial and temporal changes in SOC within agricultural fields, continuous monitoring is imperative. In-field data sets of Vis-NIR soil spectra were collected on a long-term experimental site using an on-the-go spectrophotometer. Data processing for continuous SOC prediction involves a two-steps modelling approach. In Step 1, a Partial Least Square (PLSR) regression model is trained to establish a relationship between the SOC content and the spectral information also including spectral preprocesisng. In Step 2, the predicted SOC content obtained from the PLSR models is interpolated using ordinary kriging. Among the tested spectral preprocessing techniques and semivariogram models, SG and gapDer preprocessing along with a Gaussian semivariogram model, yielded the best performance resulting in a root mean square error of of 1.24 and 1.26 g kg-1. A striping effect due to the transect-based data collection was addressed by testing the effectiveness of extending the spatial separation distance, employing data aggregation, and defining the distribution based on treatment plots using block kriging. Overall, the results highlight the immense potential of on-the-go spectral Vis-NIR data for field-scale spatial-temporal monitoring of SOC.

This work shows a correlation between light reflectance, absorption, and morphologies of series of (1-x) BM–x PT, (x = 0.0, 0.02, 0.04, 0.08, 0.12, 0.16, 0.24) ceramics composite. The (1-x) BM–x PT showed features of a black mirror with a low optical energy gap. The measured Vis-NIR diffused reflectance enabled the calculation of the energy gap using the modified Kubelka-Munk function. The estimated energy gap was lower than 1.5 eV related to low reflectance in the Vis-NIR range. Moreover, obtained histograms of grains, using scanning electron microscope, enabled the correlation between grains size and amount of lead titanate. We deduced from the ceramics surface morphology that marked porosity also induced reflectivity of low magnitude. We correlated the magnitude of the energy gap with phases of the BM-PT composite and with the electrical conductivity activation energy reported in the literature. Our results findings opened prospect studied materials for optical applications.

Recognition, decoding and tracking of vortex patterns is of increasing importance in many fields reaching from astronomical observation of distant galaxies to turbulence phenomena in liquids or gases. Currently, coherent light beams with orbital angular momentum (OAM) are of particular interest for optical communication, metrology, micro-machining or particle manipulation. One common task is to identify characteristic spiral patterns in pixelated intensity maps at real-world signal-to-noise ratios. Recently, Fast Fourier Transform (FFT) was applied to the quantitative analysis of spiral interference patterns of OAM beams. Our study considers this approach in more detail. It is demonstrated that specific information can be extracted by combining conformal mapping by polar transform with determining one- or two-dimensional angular frequency spectra either in spatially fixed or scanning mode. Results of proof-of-principle experiments are presented.

In the present work, we designed a mild strategy to make Cu₂(OH)PO₄ (CHP) nanoparticles on cotton fabrics (CFs) to achieve multi-functionalities. The phytic acid (IP6) assisted method was employed to synthesize nanoparticles (CHP-IP6). Under Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS) as well as thermogravimetric analysis (TGA), we characterized the coated cotton fabrics. The CHP-IP6 treated fabrics showed prominent photocatalytic activity, excellent photocatalytic stability and thorough discoloration of methylene blue (MB) stain under sunlight irradiation.

The application of non-uniform spiral gratings to control structure, topological parameters and propagation of orbital angular momentum (OAM) beams was studied experimentally with coherent near-infrared light. Adapted digital spiral grating structures were programmed into the phase map of a high-resolution liquid-crystal-on-silicon spatial light modulator (LCoS-SLM). It is shown that characteristic spatio-spectral anomalies related to Gouy phase shift can be used as pointers to quantify rotational beam properties. Depending on sign and gradient of spatially variable periods of chirped spiral gratings (CSG), variations of rotation angle and angular velocity as a function of propagation distance were measured. Propagation-dependent self-torque is introduced in analogy to known local self-torque phenomena of OAM beams as obtained by the superposition of temporally chirped or phase modulated wavepackets.

Visible and near-infrared reflectance (Vis–NIR) techniques are a plausible method to soil analyses. The main objective of the study was to investigate the capacity to predicting soil properties Al, Ca, K, Mg, Na, P, pH, total carbon (TC), H and N, by using different spectral (350–2500 nm) pre-treatments and machine learning algorithms such as Artificial Neural Network (ANN), Random Forest (RF), Partial Least-squares Regression (PLSR) and Cubist (CB). The 300 soil samples were sampled in the upper part of the Itatiaia National Park (INP), located in Southeastern region of Brazil. The 10 K-fold cross validation was used with the models. The best spectral pre-treatment was the Inverse of Reflectance by a Factor of 104 (IRF4) for TC with CB, giving an averaged R² among the folds of 0.85, RMSE of 1.96; and 0.67 with 0.041 respectively for H. Into the K-folds models of TC, the highest prediction had a R² of 0.95. These results are relevant for the INP management plan, and also to similar environments. The good correlation with Vis–NIR techniques can be used for remote sense monitoring, especially in areas with very restricted access such as INP.

The achievement of size uniformity and monodispersity in perovskite quantum dots (QDs) requires the implementation of precise temperature control and the establishment of optimal reaction conditions. Nevertheless, the accurate control of a range of reaction variables represents a considerable challenge. This study addresses the aforementioned challenge by employing manganese (Mn) doping to achieve size uniformity in CsPbBr₃ perovskite QDs without the necessity for precise control of the reaction conditions. By optimizing the Mn:Pb ratio, it is possible to successfully dope CsPbBr₃ QDs with appropriate concentrations of Mn²⁺ and achieve a uniform size distribution. The spectroscopic measurements on single QDs indicate that the appropriate Mn²⁺ concentrations can result in a narrower spectral linewidth, a longer photoluminescence (PL) lifetime, and a reduced biexciton Auger recombination rate, thus positively affecting the PL properties. This study not only simplifies the size control of perovskite QDs, but also demonstrates the potential of Mn-doped CsPbBr₃ QDs for narrow linewidth light-emitting diode applications.

Crystalline silver thin layers were obtained by high-energy pulsed laser ablation without heating of the deposition substrate. The fluid Plateau-Rayleigh (PRI), Rayleigh – Taylor (RTI) and Richtmyer – Meshkov (RMI) instabilities, as well as crown splash induced during pulsed laser deposition (PLD) in high energy regime, resulting in ring and pearl shaped structures, offer the benefit of increased sorption surface. These morphological structures obtained for the silver thin layers make them of interest for catalytic applications. The study presented with this work addresses both the fundamental and applied issues on the morphological structures obtained for the silver thin layer and their catalytic function in organic processes. In this sense, the catalytic action of the thin silver layer was highlighted by modifications of the Reactive Blue 21 dye (C.I.) in aqueous solution with sodium bicarbonate. Specific investigations and analyzes were carried out by electron microscopy and elemental analysis (SEM-EDX), atomic force microscopy (AFM) and profilometry, mass spectrometry, ablation plasma diagnosis, diffractograms (XRD), as well as IR spectroscopy (FTIR). In addition to the experimental investigation and analyzes, simulation of the ionization energy threshold was conducted in COMSOL for complementary evaluation on the involved processes and phenomena.

In this contribution, we present a high-speed multiplex grating spectrometer based on a spectral coding approach that is founded on principles of compressive sensing. The spectrometer employs a single-pixel InGaAs detector to measure the signals encoded by an amplitude spatial light modulator (digital micromirror device, DMD). This approach leads to a speed advantage and multiplex sensitivity advantage atypical for standard dispersive systems. Exploiting the 18.2 kHz pattern rate of the DMD, we demonstrate 4.2 ms acquisition times for full spectra with a bandwidth of 450 nm (5250 cm-1 – 4300 cm-1; 1.9 µm – 2.33 µm). Due to the programmability of the DMD, spectral regions of interest can be chosen freely, thus reducing acquisition times further, down to the sub-millisecond regime. The adjustable resolving power of the system accessed by means of computer simulations is discussed, quantified for different measurement modes, and verified by comparison with a state-of-the-art Fourier-transform infrared spectrometer. We show measurements of characteristic polymer absorption bands in different operation regimes of the spectrometer. The theoretical multiplex advantage of 8 was experimentally verified by comparison of the noise behavior of the spectral coding approach and a standard line-scan approach.

Background: Since the onset of widespread COVID-19 vaccination campaigns, there have been concerns about serious cardiovascular adverse events, including myocarditis, myocardial infarction, and venous thromboembolisms, all of which can lead to cardiopulmonary arrest. This study aimed to estimate excess cardiopulmonary arrest mortality in King County, WA, and investigate any association with COVID-19 vaccination rates. Methods: Data was obtained from the annual King County, WA, EMS reports, the U.S. Census Bureau, and The Tennessean COVID-19 Vaccine Tracker. An exploratory data analysis was performed. Excess deaths were calculated using the 2015-2020 cardiopulmonary arrest mortality trend line. The relationship between excess cardiopulmonary arrest mortality and vaccination rates was analyzed using polynomial regression analysis. A quadratic regression model was used to generate expected population growth trends. The excess mortality model for King County was used to calculate yearly estimates for excess cardiopulmonary arrest fatalities in the USA. Results: Approximately 98% of the King County population received at least one dose of a COVID-19 vaccine by 2023. Our analysis revealed a 25.7% increase in total cardiopulmonary arrests and a 25.4% increase in cardiopulmonary arrest mortality from 2020 to 2023 in King County, WA. Excess cardiopulmonary arrest deaths were estimated to have increased by 1,236% from 2020 to 2023, rising from 11 excess deaths (95% CI: -12, 34) in 2020 to 147 excess deaths (95% CI: 123, 170) in 2023. A quadratic increase in excess cardiopulmonary arrest mortality was observed with higher COVID-19 vaccination rates. The general population of King County sharply declined by 0.94% (21,300) in 2021, deviating from the expected population size. Applying our model from these data to the entire United States yielded 49,240 excess fatal cardiopulmonary arrests from 2021-2023. Conclusions: We identified a very strong ecological and temporal association between excess cardiopulmonary arrest mortality and the COVID-19 vaccination campaign, which resulted in high vaccination rates. The biological plausibility of death from acute cardiac and pulmonary causes after COVID-19 vaccination has been previously demonstrated and is concerning given these real-world observations. Urgent further research is needed to determine if similar trends are observed in other regions with attention to risk mitigation for incident events and improved survival with resuscitation.

Beans are the most widely used protein source in the world and their productivity is directly linked to nitrogen (N). The short crop cycle imposes the need for fast methodologies for N quantification. In this work, we evaluated the performance of four machine learning algorithms in nitrogen prediction using NIR spectroscopy. Increasing doses of nitrogen were applied to the plants and leaf reflectance was collected. Weka software was used to test the algorithms. The selection of the most effective spectral zones was made with the VIP. Considering predictions with the whole NIR, the best results were achieved with RF (R2 = 0,84 and RMSE = 2,69 g kg-1) and KNN (R2 = 0,77 and RMSE = 3,86 g kg-1). The intervals of 700-740 nm and 983-995 nm were considered the most important for the study of N. More efficient predictions were verified when only spectral regions screened by VIP were included, increasing the accuracy of the RF, KNN and M5 models by 6%, 4% and 8%, respectively. The efficiency of N prediction based on NIR reflectance combined with machine learning was verified. This approach can optimize the management of nitrogen fertilization, serving as an important tool in precision agriculture.

Addressing within field spatial variability for nitrogen management to avoid over and under-use of nitrogen is crucial for optimizing crop productivity and ensuring environmental sustainability. In this study we investigated the economic, environmental and agronomic benefits of variable rate nitrogen application in potato (Solanum tuberosum). An online visible and near infrared (vis-NIR) spectroscopy sensor we utilized to predict soil moisture content (MC), pH, total organic carbon (TOC), extractable phosphorus (P), potassium (K), magnesium (Mg), and cation exchange capacity (CEC) using a partial least squares regression (PLSR) models. The crop's normalized difference vegetation Index (NDVI) from Sentinel-2 satellite images was incorporated to online measured soil data to derive fertility management zones (MZs) maps, after homogenous raster and clustering analyses. The MZs maps were categorized into high fertile (VR-H), medium-high fertile (VR-MH), medium-low fertile (VR-ML), and low fertile (VR-L) zones. A parallel strip experiment compared variable rate nitrogen (VR-N) with uniform rate (UR) treatments, adjusting nitrogen levels based on fertility zones as: 50% less for VR-H, 25% less for VR-MH, 25% more for VR-ML, and 50% more for VR-L zones compared to the UR treatment. Results showed that the VR-H zone received a 50% reduction in N fertilizer input and demonstrated a significantly higher crop yield compared to the UR treatment. This implies a potential reduction in negative environmental impact by lowering fertilizer costs while maintaining robust crop yields. In total, the VR -N treatment received an additional 1.2 Kg/ha of nitrogen input, resulting in a crop yield increase of 1.89 tons/ha. The relative gross margin for the VR-N treatment compared to the UR treatment 374.83 €/ha, indicating substantial profitability for the farmer. To further optimize environmental benefits and profitability, additional research is needed to explore site-specific application of all farm resources through precision agricultural technologies.

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.

A milk drink flavored with dates syrup produced at a lab scale level was evaluated. The production process of date syrup involves a sequence of essential unit operations, commencing with the extraction, filtration, and concentration processes from two cultivars: Sukkary and Khlass. Date syrup was then mixed with cow’s and camel’s milk at four percentages to form a nutritious, natural, sweet, and energy milk drink. Sensory, physical, and chemical characteristics of the milk drinks flavored with date syrup were examined. The objective of this work was to measure physiochemical properties of dates fruits and milk drinks flavored with dates syrup, then to evaluate the physical properties of milk drinks utilizing a non-destructive NIR spectra. The study assessed the characteristics of the milk drink enhanced with date syrup by employing near-infrared spectra (NIR) spectra and analyzed utilizing partial least-square regression (PLSR) and artificial neural network (ANN) analysis. The NIR spectrum proved to be highly effective in estimating the physiochemical attributes of the flavored milk drink. The ANN model outperformed the PLSR model in this context. RMSECV is considered a more reliable indicator of a model's future predictive performance compared to RMSEC, R2 ranged between 0.946 and 0.989. Consequently, non-destructive NIR technology demonstrates significant promise for accurately predicting and contributing to the entire production process of the product's properties examined.

Solar and wind resources available for power generation are subject to variability due to meteorological factors. Here, we use a new global climate reanalysis product, Version 2 of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), to quantify interannual variability of monthly-mean solar and wind resource from 1980 to 2016 at a resolution of about 0.5 degrees. We find an average coefficient of variation (CV) of 11% for monthly-mean solar radiation and 8% for windspeed. Mean CVs were about 25% greater over ocean than over land, and, for land areas, were greatest at high latitude. The correlation between solar and wind anomalies was near zero in the global mean, but markedly positive or negative in some regions. Both wind and solar variability were correlated with values of climate modes such as the Southern Oscillation Index and Arctic Oscillation, with correlations in the Northern Hemisphere generally stronger during winter. We conclude that reanalysis solar and wind fields could be helpful in assessing variability in power generation due to interannual fluctuations in the wind and solar resource. Skillful prediction of these fluctuations seems to be possible, particularly for certain regions and seasons, given persistence or predictability of climate modes with which these fluctuations are associated.

Tissue engineering has the potential for repairing large bone defects, which impose a heavy financial burden on the public health. However, difficulties with O₂ delivery to the cells residing in the interior of tissue engineering scaffolds make it challenging to grow artificial tissues of clinically-relevant sizes. This study uses image-based simulation in order to provide insight into how to better optimize the scaffold manufacturing parameters, and the culturing conditions, in order to resolve the O₂ bottleneck. To do this, high resolution 3D X-ray images of two common scaffold types (salt leached foam and non-woven fiber mesh) are fed into a Lattice Boltzmann Method fluid dynamics and reactive Lagrangian Scalar Tracking mass transfer solvers. The obtained findings indicate that the scaffolds should have maximal surface area-to-solid volume ratios, for higher chances of the molecular collisions with the cells. Furthermore, the cell culture media should be flown through the scaffold pores as fast as practically possible (without detaching or killing the cells). Finally, we have provided a parametric sweep that maps how the molecular transport within the scaffolds is affected by variations in rates of O₂ consumption by the cells. Ultimately, the results of this study are expected to benefit the computer-assisted design of tissue engineering scaffolds and culturing experiments.

Biosolids from stabilized sludge presents a high fertilization potential due to its rich content of nutrients and organic matter. Three formulas of organo-mineral fertilizers based on biosolids were manufactured having at least 2 % N, 2 % P2O5, and 2 % K2O and characterized by classical and advanced methods. The content of N and P in the final formula was measured using specific reactants combined with VIS-nearIR spectroscopy. Additionally, all three formulas were characterized by advanced 1H NMR relaxometry, double-quantum and FT-IR spectroscopy. Structural characterization was performed using SEM, EDX and X-ray diffraction. Four dynamical components were identified in the T2-distribution showing that the rigid component is into a percentage larger than 90 %. In order to evaluate the release properties of organo-mineral fertilizers dynamic measurements of electric conductivity and pH were performed, by placing 0.25 g of formulas (V1, V2 and V3) in 200 ml of distillate water. It was found that V3 present the smallest release velocity, but release the largest amount of fertilizers. Two release mechanisms were also observed.

Global change is affecting vegetation cover and processes through multiple pathways. Long time series of surface land surface properties derived from satellite remote sensing offer a unique abilities to observe these changes, particularly in areas with complex topography and limited research infrastructure. Here, we focus on Nepal, a biodiversity hotspot where vegetation productivity is limited by moisture availability (dominated by a summer monsoon) at lower elevations and by temperature at high elevations. We analyze normalized difference vegetation index (NDVI) from 1981 to 2015 semimonthly, at 8 km spatial resolution. We use a random forest (RF) of regression trees to generate a statistical model of NDVI as a function of elevation, land use, CO2 level, temperature, and precipitation. We find that NDVI has increased over the studied period, particularly at low and middle elevations and during fall (post-monsoon). We infer from the fitted RF model that the NDVI linear trend is primarily due to CO2 level (or another environmental parameter that is changing quasi-linearly), and not primarily to temperature or precipitation trends. On the other hand, interannual fluctuation in NDVI is more correlated with temperature and precipitation. RF accurately fits the available data and shows promise for estimating trends and testing hypotheses about their causes.

Seeds can maintain their quality for a limited time; after that, they will lose their germination ability and vigor. Some physiological and physicochemical changes in the structure of the seeds during storage can decrease the quality of the seeds which is known as aging. Therefore, detection of the strong young seeds from the old ones is a vital issue in the modern agriculture. Conventional methods of detection of the seed viability and germination are destructive, time-consuming and costly. In this research, two peanut cultivars, namely North Carolina 2 (NC-2) and Florispan were selected and three artificial aging levels were induced to them. Hyperspectral images (HSI) of the samples were acquired and the seed viability was evaluated using two pre-trained convolutional neural network (CNN) image processing models, AlexNet and VGGNet. The noise of the reflection spectra of the samples was relatively resolved and modified by combining Preprocessing techniques of moving average (MA) and standard normal variate (SNV). Using principal component analysis (PCA), the dimensions were declined and three principal components (PC) were extracted. These PCs were then used as variables in the classification of support vector machine (SVM) and linear discriminant analysis (LDA). The results showed the high capability of CNN architectures such as AlexNet and VGGNet in detection of the seed viability based on the HIS with no pre-processing and feature extraction. The mentioned architectures reached the accuracy of 0.985 and 0.986, respectively. The combination of feature extraction method of PCA with LDA and SVM classifiers showed that the use of a limited number of PCs instead of all wavelengths can decrease the complexity of modeling, while enhancing the efficiency of the models such that LDA and SVM classifiers achieved the accuracy of 0.983 and 0.986 in classification of peanut sees, respectively.

Re-shaping of thermodynamics with the graph theory and Ramsey theory is suggested. Maps built of thermodynamic states are addressed. Thermodynamic states may be attainable and non-attainable by the thermodynamic process in the system of constant mass. We address the following question how large should be a graph describing connections between discrete thermodynamic states to guarantee the appearance of thermodynamic cycles? The Ramsey theory supplies the answer to this question. Direct graphs emerging from the chains of irreversible thermodynamic processes are considered. In any complete directed graph, representing the thermodynamic states of the system the Hamiltonian path is found. Transitive thermodynamic tournaments are addressed. The entire transitive thermodynamic tournament built of irreversible processes does not contain a cycle of length 3, or in other words, the transitive thermodynamic tournament is acyclic and contains no directed thermodynamic cycles.

We apply the Ramsey theory to the analysis of geometrical properties of closed contours. Consider a set of six points placed on a closed contour. The straight lines connecting these points are yikx=αikx+βik i,k=1...6, αik≠0. We color the edges connecting the points for which αik>0 holds with red, and the edges for which αik<0 with green with red. At least one monochromic triangle should necessarily appear within the curve (according to the Ramsey number R3,3=6). This result is immediately applicable for the analysis of dynamical billiards. The second theorem emerges from the combination of the Jordan curve and Ramsey theorem. The closed curve is considered. We connect the points located within the same region with green links and the points placed within the different regions with red links. In this case, transitivity/intransitivity of the relations between the points should be considered. Ramsey constructions arising from the differential geometry of closed contours are discussed.

The chiral optical Tamm state (COTS) is a special localized state at the interface of a handedness-preserving mirror and a structurally chiral medium such as a cholesteric liquid crystal or a chiral sculptured thin film. The spectral behavior of COTS, observed as reflection resonances, is described by the temporal coupled-mode theory. Mode coupling is different for two circular light polarizations because COTS has a helix structure replicating that of the cholesteric. The mode coupling for co-handed circularly polarized light exponentially attenuates with the cholesteric layer thickness since the COTS frequency falls into the stop band. Cross-handed circularly polarized light freely goes through the cholesteric layer and can excite COTS when reflected from the handedness-preserving mirror. The coupling in this case is proportional to anisotropy of the cholesteric and theoretically it is only anisotropy of magnetic permittivity that can ultimately cancel this coupling. These two couplings being equal results in a polarization crossover (the Kopp--Genack effect) for which a linear polarization is optimal to excite COTS. The corresponding cholesteric thickness and scattering matrix for COTS are generally described by simple expressions.

Parasitic diseases are among the most serious public health problems in developing countries, causing high mortality and economic burdens. The Trypanosomatidae family includes Leishmania spp. and Trypanosoma cruzi, which cause leishmaniasis and Chagas disease, respectively. Both these parasites are among the major agents of neglected tropical diseases (NTDs). Leishmaniasis is currently the second most widespread vector-borne parasitic disease after malaria. The World Health Organization (WHO) records approximately 0.7-1 million newly diagnosed leishmaniasis cases each year, resulting in approximately 20,000-30,000 deaths. Also, 25 million people worldwide are at risk of Chagas disease and an estimated 6 million people are infected with Trypanosoma cruzi. Despite the similarity of the parasites, the evolution of the disease and the clinical indexes are explicitly different in African, Asian, and American forms of infection. Clinical therapies are associated with drug resistance and side effects. As a result, the discovery of novel therapeutic agents has emerged as a top priority and a promising alternative. Peptide-based drugs are an attractive class of therapeutic agents. They are recognized for being highly selective and effective, as well as safe and well tolerated. Moreover, they are now being explored in the development of novel therapeutics for a variety of health disorders, including oncology, endocrinology, metabolic, cardiovascular, and bone diseases. In addition, they are being explored in tropical diseases such as leishmaniasis and Chagas disease. We will discuss current knowledge regarding the parasite life cycle, signs and symptoms, diagnosis, and treatment options for leishmaniasis and Chagas disease.

Declaration of smallpox eradication by the WHO on 1980 led to discontinuation of the world-wide vaccination campaign. The increasing percentage of unvaccinated individuals, the existence of its causative infectious agent variola virus (VARV) and the recent synthetic achievements, increases the threat of intentional or accidental release and reemergence of smallpox. Control of smallpox would require an emergency vaccination campaign as no other protective measure has been approved to achieve eradication and ensure world-wide protection. Experimental data in surrogate animal models support the assumption, based on anecdotal, uncontrolled historical data, that vaccination up to 4 days postexposure, confers effective protection. The long incubation period and the uncertainty of the exposure status in the surrounding population calls for the development and evaluation of safe and effective methods that would allow to extend the therapeutic window and to reduce the disease manifestations and vaccine adverse reactions. To achieve these goals, we need to evaluate the efficacy of novel and already licensed vaccines as a sole treatment or in conjunction with immune modulators and antiviral drugs. In this review, we address the available data, recent achievements and open questions.

Ramsey theory influences the dynamics of mechanical systems, which may be described as abstract complete graphs. We address a mechanical system which is completely interconnected with the two kinds of ideal Hookean springs. The suggested system mechanically corresponds to the cyclic molecules, in which functional groups are interconnected with two kinds of chemical bonds, represented mechanically with two springs k1 and k2. In this paper, we consider a Cyclic system (molecule) built of six equal masses m and two kinds of springs. We pose the following question: what is the minimal number of masses in the such a system in which three masses are constrained to be connected with spring k1 or three masses to be connected with spring k2? The answer to this question is supplied by the Ramsey theory, and it is formally stated as follows: what is the minimal number R3,3? The result emerging from the Ramsey theory is R3,3=6. Thus, in the aforementioned interconnected mechanical system will be necessarily present the triangles (at least one triangle), built of masses and springs. This prediction constitutes the vibrational spectrum of the system. Thus, the Ramsey Theory supplies the selection rules for the vibrational spectra of the cyclic molecules. Symmetrical system built of six vibrating entities is addressed. The Ramsey approach works for 2D and 3D molecules, which may be described as abstract complete graphs. The extension of the proposed Ramsey approach to the systems, partially connected by ideal springs, viscoelastic systems and systems, in which elasticity is of an entropy nature is discussed. “Multi-color systems” built of three kinds of ideal springs are addressed. The notion of the inverse Ramsey network is introduced and analyzed.

Informational (Shannon) measures of symmetry are introduced and analyzed for the patterns built of 1D and 2D shapes. The informational measure of symmetry Hsym (G) characterizes the an averaged uncertainty in the presence of symmetry elements from the group G in a given pattern; whereas the Shannon-like measure of symmetry Ωsym (G) quantifies averaged uncertainty of appearance of shapes possessing in total n elements of symmetry belonging to group G in a given pattern. Hsym(G1)=Ωsym(G1)=0 for the patterns built of irregular, non-symmetric shapes. Both of informational measures of symmetry are intensive parameters of the pattern and do not depend on the number of shapes, their size and area of the pattern. They are also insensitive to the long-range order inherent for the pattern. Informational measures of symmetry of fractal patterns are addressed. The mixed patterns including curves and shapes are considered. Time evolution of the Shannon measures of symmetry is treated. The close-packed and dispersed 2D patterns are analyzed.

Fingerprints are essential for human identification and are valuable tools in criminal investigations. The pursuit of new materials for digital printing is expanding, with increasing interest in natural compounds such as bixin, sourced from annatto seeds. Despite its traditional use as a natural dye with medicinal properties, the potential of bixin in papilloscopy remains largely untapped. In this study, we meticulously extracted bixin from annatto seeds and meticulously developed composites incorporating zinc carbonate (bixin/ZnCO3) and kaolinite (bixin/kaolinite). UV-visible spectroscopy was used for characterization, and the extracted bixin showed absorption peaks at 429, 453, and 481 nm, which were very similar to standard peaks at 429, 457, and 487 nm. The two samples also had the same retention times (7.07 min) according to further liquid chromatography analysis. Sweat pores were easier to detect thanks to the effectiveness of the bixin/ZnCO3 and bixin/kaolinite composites in creating high contrast sebaceous and natural latent fingerprints. These results highlight the composites’ potential as novel and fascinating instruments for papilloscopy applications, which might also improve forensic investigations.

This study involved a comprehensive examination of sensory attributes in Bísaro dry-cured loins, including odor, androsterone, scatol, color, fat color, hardness, juiciness, chewiness, flavor intensity, and flavor persistence. Analysis of 40 samples revealed a wide variation in these attributes, ensuring a robust margin for multivariate calibration purposes. The respective near-infrared (NIR) spectra unveil distinct peaks associated with significant components such as protein, lipid, and water. Support Vector Regression (SVR) models were methodically calibrated for all sensory attributes, with optimal results using multiplicative scattering correction pre-treatment, MinMax normalization, and radial base kernel (non-linear SVR model). The predictive models exhibited acceptable results, characterized by R-squared values close to 1 (0.9616 - 0.9955) and low RMSE values (0.0400 – 0.1031). The prediction set's relative standard deviation (RSD) remained under 5%. Comparisons with prior research revealed significant improvements in prediction accuracy, particularly when considering attributes like pig aroma, hardness, fat color, and flavor intensity. This research underscores the potential of advanced analytical techniques to improve the precision of sensory evaluations in food quality assessment.

Anaerobic digestion is a biological process that transforms high-strength organic effluents into biogas with multiple benefits. However, concurrent with organics' biological transformation, a liquid phase with a high solid content is also derived from this process. Valorizing this fraction is not an easy task if an agronomic application cannot be considered as a suitable option. The thermal valorization of this fraction allows for energy extraction, but also gives rise to additional capital investment and increases the energy demand of the global process. In addition, the thermal treatment of digestate has to deal with a mineralized material. The changes in organic matter due to anaerobic stabilization were studied in the present manuscript, by evaluating the thermal behavior of samples, activation energy and organic transformation using FTIR spectroscopy. Digested samples of a mixture composed of manure and glycerin (5% v/v) were studied. The stabilization caused a dramatic decrease in aliphatic compounds, greatly increasing the mineral content of the sample. Thermal valorization of digestates must consider the lower energy content and more complex structure of these materials, with higher content of lignin and protein-type compounds.

We used the complete set of convex pentagons enabling filing the plane without any overlaps or gaps (including the Marjorie Rice tiles) as generators of Voronoi tessellations. Shannon entropy of the tessellations was calculated. Some of the basic mosaics are flexible and give rise to a diversity of Voronoi tessellations. The Shannon entropy of these tessellations varied in a broad range. Voronoi tessellation, emerging from the basic pentagonal tiling built from hexagons only, was revealed (the Shannon entropy of this tiling is zero). Decagons and hendecagon did not appear in the studied Voronoi diagrams. The most abundant Voronoi tessellations are built from three different kinds of polygons. The most widespread is the combination of pentagons, hexagons and heptagons. The most abundant polygons are pentagons and hexagons. No Voronoi tiling built only of pentagons was registered. Flexible basic pentagonal mosaics give rise to a diversity of Voronoi tessellations, which are characterized by the same symmetry group; however, the coordination number of the vertices is variable. These Voronoi tessellations may be useful for the interpretation of the iso-symmetrical phase transitions.

Biological nitrogen fixation (BNF) by symbiotic bacteria plays a vital role in sustainable agriculture. However, current quantification methods are often expensive and impractical. This study explores the potential of Raman spectroscopy, a non-invasive technique, for rapid assessment of BNF activity in soybeans. Raman spectra were obtained from soybean plants grown with and without rhizobia bacteria to identify spectral signatures associated with BNF. δN15 isotope ratio mass spectrometry (IRMS) was used to determine actual BNF percentages. Partial least squares regression (PLSR) was employed to develop a model for BNF quantification based on Raman spectra. The model explained 80% of the variation in BNF activity. To enhance the model's specificity for BNF detection regardless of nitrogen availability, a subsequent elastic net (Enet) regularization strategy was implemented. This approach provided insights into key wavenumbers and biochemicals associated with BNF in soybeans.

Diesel is consistently a very popular fuel for internal combustion engines. Its consumption in the European Union has been rising over recent years, as has the number of engines increasingly sensitive to fuel contamination. One of the most important parameters affecting diesel quality is water content. Although its exceedances of the standard’s permissible amount are not common, they carry the risk of serious damage to expensive, modern fuel injection systems. Current methods of measuring water content require both specialised personnel and equipment, as well as transporting the sample to a suitable laboratory. The research presented in this paper was aimed at verifying whether it would be possible to test the moisture content of diesel using impedance spectroscopy. Once refined, such measurement method could be used in situ. Analysing the properties of diesel is challenging, mainly because many types of the fuel are sold, the chemical composition of which is always a well-guarded manufacturer’s secret. The experimental results obtained on many types of commercially available diesel show that it is possible to use impedance spectroscopy to estimate the water content of different types of diesel fuel. The measurement accuracy achieved makes it possible to detect approaching or exceeding the permissible water content.

Application of the Ramsey graph theory to the analysis of physical systems is reported. Physical interactions may be very generally classified as attractive and repulsive. This classification creates the premises for the application of the Ramsey theory to the analysis of physical systems built of electrical charges, electric and magnetic dipoles. The notions of mathematical logic, such as transitivity and intransitivity relations, become crucial for understanding of the behavior of physical systems. The Ramsey theory explains why nature prefers cubic lattices over hexagonal ones for systems built of electric or magnetic dipoles. The Ramsey approach may be applied to the analysis of mechanical systems when actual and virtual paths between the states in the configurational space are considered. Irreversible mechanical and thermodynamic processes are seen within the reported approach as directed graphs. Chains of irreversible processes appear as transitive tournaments. These tournaments are acyclic; the transitive tournaments necessarily contain the Hamiltonian path. The set of states in the phase space of the physical system, between which irreversible processes are possible, is considered. The Hamiltonian path of the tournament emerging from the graph uniting these states is a relativistic invariant. Applications of the Ramsey theory to the general relativity become possible when the discrete changes in the metric tensor are assumed. Reconsideration of the concept of “simultaneity” within the Ramsey approach is reported.

A lead zirconate titanate [PZT;Pb(Zr_0.52Ti_0.48)O₃] layer embedded infrared (IR) detector decorated with wavelength-selective plasmonic crystals has been investigated for high-performance non-dispersive infrared (NDIR) spectroscopy. A plasmonic IR detector with an enhanced IR absorption band has been designed based on numerical simulations, fabricated by conventional microfabrication techniques, and characterized with a broadly tunable quantum cascade laser. The enhanced responsivity of the plasmonic IR detector at specific wavelength band has improved the performance of NDIR spectroscopy and pushed the limit of detection (LOD) by an order of magnitude. In this paper, a 13 fold enhancement in the LOD of a methane gas sensing using NDIR spectroscopy is demonstrated with the plasmonic IR detector.

The notion of the informational measure of symmetry is introduced according to: HsymG=-i=1kPGilnPGi, where PGi is the probability of appearance of the symmetry operation Gi within the given 2D pattern. HsymG is interpreted as an averaged uncertainty in the presence of symmetry elements from the group G in the given pattern. The informational measure of symmetry of the “ideal” pattern built of identical equilateral triangles is established as HsymD3=1.792. The informational measure of symmetry of the random, completely disordered pattern is zero, Hsym=0. Informational measure of symmetry is calculated for the patterns generated by the P3 Penrose tessellation. Informational measure of symmetry does not correlate neither with the Voronoi entropy of the studied patterns nor with the continuous measure of symmetry of the patterns.

Shape-shifting polymers are widely used in various fields such as intelligent switches, soft robots and sensors, which require both multiple stimulus response functions and qualified mechanical strength. In this study, a novel near infrared light (NIR) responsible shape-shifting hydrogel system was designed and fabricated, through embedding vinylsilane modified carbon nanotubes (CNTs) into particle-double network (P-DN) hydrogels by micellar copolymerization. The dispersed brittle Poly(sodium 2-acrylamido-2-methylpropane-1-sulfonate) (PNaAMPS) network of the microgels can serves as sacrificial bonds to toughen the hydrogels, and the CNTs endow it NIR photothermal conversion ability. The results show that the CNTs embedded P-DN hydrogels present excellent mechanical strength, i. e. fracture strength of 312 kPa and fracture strain of 357%. Moreover, an asymmetric bilayer hydrogel, where the active layer contains CNTs, can achieve 0°–110° bending deformation within 10 min under NIR irradiation and can realise complex deformation movement. This study provides a theoretical and experimental basis for the design and manufacture of photoresponsive soft actuators.

The aim of this study was to find a correlation between in vivo NIR scan patterns, oxidative status, and blood serum metabolites in rabbits fed diets protected or unprotected against oxidation. Rabbits does in groups of eight were fed for 9 weeks with diets containing linseed, rich in polyunsaturated fatty acids (LS), or linseed plus hazelnut skins, with antioxidant function (LS+HS), and palm oil, rich in saturated fatty acids (PO). The animals were examined at days 1, 31, and 63 using a smart SCÏO molecular sensor, a new miniaturized web-based wireless device, applied to the internal ear flap (NIR range 740-1070 nm). The hazelnut peels integrated diet protected the rabbits from the oxidative stress induced by the addition of unprotected polyunsaturated fats. NIR tomoscopy was variously correlated with serum parameters, lysozyme (R2=0.71), ROMs (0.47), cholesterol (0.49), triglycerides (0.40), and a multivariate Index of Oxidative Risk (0.67 [IOR]). The correlations suggested a close connection between the clustering of the diets according to the laboratory variables and the NIRS scan pattern clustering at the ending trial day, as shown by the highly significant odds ratios. Advantageous use of this simple, painless technique was evident in the planning phase, with no difference among the groups at the beginning of the study, but an effect size that evolved differently over time until the end of the study. In a practical validation of the SCÏO model in 92 commercial rabbit does, the average spread of the predicted IOR was 33% in lactating does (2.54±0.05) vs. dry does (1.91±0.07).

We present an analysis of high-resolution, near-infrared (NIR) spectra relative to the solar transit of Venus of 5-6 June 2012, as observed with the Facility Infrared Spectropolarimeter (FIRS) at the Dunn Solar Telescope in New Mexico. These observations offer the unique opportunity to probe the upper layers (between ∼84 and 150 km in altitude) of a thick, CO2-dominated atmosphere with the transmission spectroscopy technique – a proxy for future studies of highly-irradiated atmospheres of Earth-sized exoplanets. We were able to visually identify absorption lines from the two most abundant CO2 isotopologues, and from the main isotopologue of CO in the retrieved spectrum of Venus. Furthermore, we perform a cross-correlation analysis of the transmission spectrum using transmission templates generated with petitRADTRANS. With the cross-correlation technique, it was possible to confirm detections of both CO2 isotopologues and CO. Additionally, we retrieve a cross-correlation signal for O3 on Venus. We demonstrate the feasibility of high-resolution, ground-based observations to study the chemical inventory of planetary atmospheres, employing techniques commonly used in exoplanet characterization.

Voronoi mosaics inspired by the seed points placed on the Archimedes Spirals are reported. Voronoi entropy was calculated for these patterns. Equidistant and non-equidistant patterns are treated. Voronoi mosaics built from a sells of equal size which are of a primary importance for decorative arts are reported. The pronounced prevalence of hexagons is inherent for the patterns with an equidistant and non-equidistant distribution of points, when the distance between the seed points is of the same order of magnitude as the distance between the turns of the spiral. Penta- and heptagonal “defected” cells appeared in the Voronoi diagrams due to the finite nature of the pattern. The ordered Voronoi tessellations demonstrating the Voronoi entropy larger than 1.71, reported for the random 2D distribution of points, were revealed. The dependence of the Voronoi entropy on the total number of the seed points located on the Archimedes Spirals is reported. Voronoi tessellations generated by the phyllotaxis-inspired patterns are addressed. The aesthetic attraction of the Voronoi mosaics arising from seed points placed on the Archimedes Spirals is discussed.

Paraffin wax stores energy in the form of latent heat at a nearly constant temperature during melting and releases this energy during solidification. This effect is used in industrial energy storage. An unusual change in the shape of a melted droplet of paraffin wax placed on a relatively cold glass plate is studied. As the droplet solidifies, its upper surface becomes nearly flat and a dimple is formed in the center of this surface, making the droplet look like a fruit (pumpkins are more commonly shaped like this, but the authors prefer apples). A series of experiments, as well as physical and numerical modeling of the droplet's thermal state, taking into account the formation of a mushy zone between liquidus and solidus, made it possible to understand the role of gravity and gradual increase in viscosity and density of paraffin wax on changing the droplet shape and, in particular, to clarify the mechanism of formation of the dimple on its upper.

Water resources planners and policymakers often ask questions about the future projections of drought characteristics (events, intensity, severity, duration, and peak) under different climatic scenarios. This study focused on quantifying the historical (1951-2005) and future (2026-2100) drought characteristics using the Standardized precipitation index (SPI) under RCP 4.5 and RCP 8.5 climate scenarios for the Balochistan province of Pakistan, an arid and drought-vulnerable region. Precipitation data of MPI-ESM-LR_RCA4 RCM was obtained from the Coordinated Regional Climate Downscaling Experiment South Asia (CORDEX-SA). The CORDEX-SA data was interpolated at 12-gauge stations and bias-corrected by the distribution mapping method using Asian Precipitation - Highly-Resolved Observational Data Integration towards Evaluation (APHRODITE) data. The drought characteristics were calculated based on standardized precipitation index (SPI), and intercompared between northern Balochistan (NB) and southern Balochistan (SB). It was found that the northern Balochistan (NB) region has suffered more droughts in the historical period and is also projected to have more severe and intense droughts than SB region. It was also found that with the increase of drought events, the duration reduces, which means that the higher the drought events at a station, the lower the drought duration. Government officials should focus more on managing the already few freshwater resources sustainably, given the increased likelihood of droughts in Balochistan due to climate change.

Sepsis still remains one of the most difficult conditions to diagnose as it presents unspecific clinical signs and symptoms, which makes early detection crucial. Our study aimed to enhance the accuracy of sepsis diagnosis by integrating multimodal monitoring technologies with traditional diagnostic methods. The research involved 121 newborns, comprising 39 cases of late-onset sepsis, 35 cases of early-onset sepsis, and 47 control subjects. Biosignals including pulse oximetry (PO), near-infrared spectroscopy (NIRS), and skin temperature (ST) were continuously monitored and an algorithm was developed using Python for identifying early signs of sepsis. The model demonstrated the ability to detect sepsis 6 to 48 hours in advance with an accuracy rate of 87.67% ± 7.42%. Sensitivity and specificity were recorded at 76% and 90%, respectively, with NIRS and ST having the most significant impact on predictive accuracy. Despite the promising results, limitations such as sample size, data variability, and potential biases were noted. The findings highlight the critical role of non-invasive biosensing methods in conjunction with traditional biomarkers and cultures, offering a robust framework for early sepsis detection and improved neonatal care. Further studies are recommended to validate these results across diverse clinical settings.

Antimony (Sb) has gained significance as a critical raw material (CRM) within the European Union (EU) due to its strategic importance in various industrial sectors, particularly in the textile industry for flame retardants and as a component of Sb-based semiconductor materials. Moreover, Sb is emerging as a potential alternative for anodes used in lithium-ion batteries, a key element in the Energy transition. This study focused on exploring the feasibility of identifying and quantifying Sb mineralizations through the spectral signature of soils using reflectance spectroscopy, a non-invasive remote sensing technique, and by employing deep learning algorithms such as Convolutional Neural Networks (CNNs). Common signal preprocessing techniques were applied to the spectral data, and the soils were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Despite achieving high R-squared values, the study faces a significant challenge of generalization of the model to new data. Despite the limitations, this study provides valuable insights into potential strategies for future research in this field.

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.

Exploring the relationship between cereal yield and remotely sensed normalized difference vegetation index (NDVI) is of great importance to decision-makers and agricultural stakeholders. In this study, an approach based on the Pearson correlation coefficient and linear regression method is carried out to reveal the relationship between cereal yield and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data in the Fez-Meknes region of Morocco. The results obtained show strong correlations reaching 0.70 to 0.89 between NDVI and grain yield. The linear regression model explains 58 to 79% of the variability in yield in regional provinces marked by the importance of cereal cultivation, and 51 to 53% in the mountainous provinces with less agricultural land devoted to major cereals. The regression slopes indicate that a 0.1 increase in NDVI results in an expected increase in grain yield of 4.9 to 8.7 quintals (q) per ha, with an average of 6.8 q/ha throughout the Fez-Meknes region. RMSE ranges from 2.12 to 4.96 q/ha. These results are promising in terms of early yield forecasting based on MODIS NDVI data.

A Cu₂ZnSnS₄ (CZTS) film with a thickness of approximately 1.5 μm was fabricated on a Mo-coated glass substrate by annealing a CZTS precursor fabricated from nanoparticle ink. The chemical states of the elements in the CZTS thin film in the depth direction were studied to identify the presence of secondary phases, which are detrimental to the performance of solar cells containing CZTS. X-ray diffraction was unable to detect any secondary phases in CZTS because of their small relative amount. Instead, X-ray photoelectron spectroscopy (XPS), which is highly sensitive to chemical state, was conducted at different depths in the CZTS film to further check the presence of secondary phases. XPS analysis revealed peaks shift consistent with the presence of secondary phases. For the CZTS film annealed in a S atmosphere at 575 °C for 3 h, the film surface consisted of a secondary-phase layer composed of CuS, ZnS, and SnSx (x=1 or 2) originating from the decomposition of CZTS. At depths below 80 nm, the film was pure CZTS. Formation of MoS2 at the CZTS–Mo interface was confirmed by XPS analysis of Mo and S.

Recently Candida auris has emerged as a multi-resistant fungal pathogen, with a significant clinical impact, and has become a critical issue in WHO fungal priority list, due to its unique ability to persist for long time on human skin and hospital environments. It is therefore fundamental to reinforce hospital surveillance protocols to limit nosocomial outbreaks. The study purpose was the Fourier-Transform Infrared Spectroscopy (FT-IR) application to investigate the phylogenetic relationships between isolated strains within the C. auris outbreak at the university Intensive Care Unit of a Tertiary University hospital in Turin (Italy). In order to calculate a clustering cut-off, intra- and inter-isolates distance values were analysed. Data showed the presence of a major cluster Alfa and a minor cluster Beta with a defined C. auris clustering cut-off. The results were validated by an external C. auris strain and Principal Component and Linear Discriminant Analysis. The application of FT-IR technology had allowed to obtain important information about the phylogenetic relationships between the analysed strains, defining for the first time a “not WGS-based” clustering cut-off with a statistical-mathematical approach. FT-IR could represent a valid alternative to molecular methods for rapid and cost saving typing of C. auris strains with important clinical implications.

Phytochromes are biological photoswitches that translate light into a physiological function. Spec-troscopic techniques are essential tools in molecular research on these photoreceptors. This review is directed to summarize how resonance Raman and IR spectroscopy contributed to the under-standing of structure, dynamics, and reaction mechanism of phytochromes, outlining the substan-tial experimental and theoretical challenges and describing the strategies to master them. It is shown that the potential of the various vibrational spectroscopic techniques can be most efficient-ly exploited in integral approaches by combination with theoretical methods as well as other ex-perimental techniques.

The development of new cultivars is important for the profitability of the floriculture industry. There are a limited number of cultivars of Zantedeschia aethiopica, an iconic ornamental cut flower, garden plant, and potted plant, due to the incompatibility of interspecific crossings within the genus. Most present-day varieties are the result of spontaneous mutations or classical breeding within the species, followed by a long selection process. Breeders are very interested in the development of a time- and cost-effective method for producing new Z. aethiopica cultivars with novel characteristics. Here, Z. aethiopica mutants were generated by treating seeds with 100 Gy of X-ray radiation. The resulting putative mutants were selected based on particular flowering parameters and compared to non-irradiated, control plants. Over two growing seasons, characteristics such as early flowering, flower size and shape, yield and response to soft-rot disease were monitored and considerable variation was observed among the mutated lines. Out of 319 mutants, 20 lines were selected based on their phenotypes and then propagated and further analyzed. Within this group, only two phenotypes displayed at least five improved flowering properties under natural, Mediterranean conditions. The rest displayed two to four desired combinations of flowering traits, some with great commercial potential.

Properties of the Voronoi tessellations arising from the random 2D distribution points are reported. We applied the procedure of dividing the sides of Voronoi cells into equal or random parts to Voronoi diagrams generated by a set of randomly placed on the plane points. The dividing points were then used to construct the following Voronoi diagram. Repeating this procedure led to a surprising effect of positional ordering of Voronoi cells, reminiscent of the formation of lamellae and spherulites in linear semi-crystalline polymers and metallic glasses. Thus, we can conclude, that by applying even a simple set of rules to a random set of seeds we introduce order into an initially disordered system. At the same time, the Voronoi entropy showed a tendency to values typical for completely random patterns and did not distinguish the short-range ordering. The Voronoi entropy and the continuous measure of symmetry of the patterns demonstrated the distinct asymptotic behavior, while approaching the close saturation values with the increase of the number of the iteration steps. Voronoi entropy grew, with the number of iterations, whereas the continuous measure of symmetry of the same patterns demonstrated the opposite asymptotic behavior. The Voronoi entropy is not an unambiguous measure of order in the 2D patterns. The more symmetrical patterns may demonstrate the higher values of the Voronoi entropy.

Background: The currently advised follow-up scheme of PSA-testing after robot-assisted radical prostatectomy (RARP) is strict and might pose a burden to our healthcare system. We aimed to optimize the 1-year follow-up scheme for patients who undergo RARP. Methods: All patients with histologically-proven prostate cancer (PCa) who underwent RARP between 2018 and August 2022 in the Prostate Cancer Network the Netherlands were retrospectively evaluated. We excluded patients who underwent salvage RARP and patients who had <1 year of PSA follow-up. Postoperative PSA-values were collected. Biochemical persistence (BCP) was defined as PSA-level >0.10 ng/mL at 0-4 months after RARP, whereas biochemical recurrence (BCR) was defined as PSA-level >0.2 ng/mL at any time point after RARP. We aimed to identify a group of patients who had a very low risk of BCR at different time-points after surgery. Results: Of all 1155 patients, BCP was observed in 151 (13%), of whom 79 (6.8%) had PSA ≥0.2 ng/mL. BCR further developed in 51 (4.7%), and 37 (3.4%) patients at 5-8 and 9-12 months after RARP, respectively. In 12 patients, BCR was found at 5-8 months after RARP in absence of BCP. These patients represented 1.2% (12/1004) of the entire group. In other words, 98.8% (992/1004) of patients who had an unmeasurable PSA-level at 0-4 months after RARP also had unmeasurable PSA-level 5-8 months after surgery. Limitations are the retrospective design and incomplete follow-up. Conclusions: Patients with an unmeasurable PSA-level at 3-4 months after RARP may not need to be retested until 12 months of follow-up as almost 100% of patients will not have biochemically recurrent disease at 5-8 months of follow-up. This will reduce PSA-testing substantially at the costs of hardly any missed patients with recurrent disease.

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10-20% of individuals following COVID-19 infection. FM and LC shares similarities with regards to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCA) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n= 48 FM and n= 46 LC) and volumetric absorptive micro sampling tips (VAMS, n= 39 FM and n= 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra was acquired using SERS with gold nanoparticles (AuNPs). Soft Independent Modelling of Class Analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNPs SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

Within the spectra of lanthanide atoms quite often overlapping spectral lines (blends) are observed. On the example of complicated blend situations within Pr I and La I it is shown that in such cases a combination of optogalvanic and laser-induced fluorescence detection is necessary to find all transitions contributing to the observed spectral signature.

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.

This article reports new measurements of laser-induced plasma hypersonic expansion measurements of diatomic molecular cyanide (CN). Focused, high-peak power 1064-nm Q-switched radiation of the order of 1 TW/cm² generates optical breakdown plasma in a cell containing a 1:1 molar gas mixture of N₂ and CO₂ at a fixed pressure of 1.1 × 10⁵ Pascal and in a 100 ml/min flow of the mixture. Line-of-sight (LOS) analysis of recorded molecular spectra indicate the outgoing shockwave at expansion speeds well in excess of Mach number 5. Spectra of atomic carbon confirm an increased electron density near the shock wave, and equally, molecular CN spectra reveal higher excitation temperature near the shockwave. The results are consistent with corresponding high-speed shadow graphs obtained by visualization with an effective shutter speed of five n anosecond. In addition, LOS analysis and application of integral inversion techniques allow inferences about the spatio-temporal distribution of the plasma.

To follow the growth and development of each tree (N = 1200) Pinus sylvestris L., var. Negorelskaya starting from the seed and continuing at the juvenile (or even generative) stage is the goal of an ambitious project to create a plant passport if possible. Five datasets of replenished empirical (tab-ular and file) and systematic data reflect the early results of a unique ongoing experiment conducted with families moved along a climatic gradient from the collection area (1731 degree days, 722 mm) to the experimental area (2326 degree days; 786 mm). Datasets of morphometric, VIS-spectrometric, and germination seed data, combined with the first results of biometric data (including the Dickson quality index) of seedlings produced from these seeds, will allow scientists in the future to conduct correlation and other statistical analysis, or train a neural network to determine the presence of connections between a seed and a plant. These data contribute to the early non-destructive diag-nosis and grading of seeds according to VIS-spectrometric properties. This dataset structure can complement the FLR-Library. In the future, by tracing seedlings in their early growth (for example, over three growing seasons at the site being restored), it will be possible to determine the degree of intensification of FRM production depending on the initial properties of the seed.

The pharmaceutical industry is making significant strides in enhancing process comprehension through the development of concepts like Quality by Design (QbD) and Process Analytical Technology (PAT). This shift has moved from traditional offline testing methods to real-time estimation of product quality. The dissolution characteristics of pharmaceutical tablets play a crucial role in maximizing the release of medications and their bioavailability. One factor that can affect dissolution is the blending procedure. Inadequate mixing can lead to patches of concentrated active components or excipients within the tablet, resulting in inconsistent dissolution behavior. A study investigated the impact of blending time and speed on the dissolution behavior of Amlodipine tablets using near-infrared (NIR) spectroscopy and multivariate modeling. NIR spectra were collected for Amlodipine tablets produced under various blending conditions using a 2-level central composite design. Dissolving profiles were analyzed using a USP dissolution device. Multivariate analysis techniques, including principal component analysis (PCA), partial least squares (PLS), Support Vector Machine (SVM), and Artificial Neural Networks (ANN), were applied to the collected NIR spectra. The findings demonstrated that blending speed and time had a significant influence on the dissolving properties of Amlodipine tablets. Blending at faster speeds and for shorter durations resulted in excessive shear and insufficient mixing, ultimately reduced drug release. The multivariate models constructed using ANN outperformed SVM and PLS in predicting dissolution profiles based on NIR spectra. This research highlights the effectiveness of NIR spectroscopy and multivariate modeling in optimizing tablet dissolution. These advancements enable continuous manufacturing of high-quality pharmaceutical products.

Lanthanide-doped upconversion nanoparticles (UCNPs) are promising bioimaging nanoprobes due to their excellent photostability. As one of the most commonly-used lanthanide activators, Tm3+ ions have perfect ladder-type electron configuration and can be directly excited by bio-friendly near-infrared-II (NIR-II) wavelengths. Here, the emission characteristics of Tm3+-doped nanoparticles under laser excitations of different near-infrared-II wavelengths were systematically investigated. The 1064 nm, 1150 nm and 1208 nm lasers are proposed to be three excitation strategies with different response spectra of Tm3+ ions. Particularly we found that 1150 nm laser excitation enables intense three-photon 475 nm emission, which is nearly 100 times stronger than that excited by 1064 nm excitation. We further optimized the luminescence brightness after investigating the luminescence quenching mechanism of bare NaYF4:Tm (1.75%) core. After growing inert shell, ten-fold increase of emission intensity was achieved. Combining the advantages of NIR-II wavelength and the higher-order nonlinear excitation, a promising facile excitation strategy was developed for the application of thulium-doped upconversion nanoparticles in single nanoparticle imaging and cancer cell microscopic imaging.

The color and NIR spectrum are key to build an oil estimation model, thus it requires individual olives clustering before the Sohlext oil extraction method can be applied. The objective was to analyze an OC estimation model of individual olives, based on cluster of similar color and NIR spectrum in different combination of the first and/or the second season. This study was performed with Chilean Arbequina olives in 2016 and 2017. The descriptor of the cluster consisted of the 3 color channels of c1, c2, c3 color model plus 11 reflectance points between 1710 and 1735 nm of each olive, normalized with the Z-score index. Clusters of similar color and NIR spectrum were formed with the k-means++ algorithm, leaving a sufficient amount of olives to be able to perform the Sohlext analysis of OC, as reference value. The estimation models were based on the Support Vector Machine. The test was carried out with the Leave One-Out Cross Validation in different training-testing combinations. The best model predicted the OC with 6% and 13%deviation respect to the real value in one season by itself and when one season tested with another season, respectively. The use of clustering in estimation model is discussed.

The interpretation of optical spectra requires thorough comprehension of quantum mechanics, especially understanding the concept of angular momentum operators. Suppose now that a transformation from laboratory-fixed to molecule-attached coordinates, by invoking the correspondence principle, induces reversed angular momentum operator identities. However, the foundations of quantum mechanics and the mathematical implementation of specific symmetries assert that reversal of motion or time reversal includes complex conjugation as part of anti-unitary operation. Quantum theory contraindicates sign changes of the fundamental angular momentum algebra. Reversed angular momentum sign changes are of heuristic nature and are actually not needed in analysis of diatomic spectra. This work addresses sustenance of usual angular momentum theory, including presentation of straightforward proofs leading to falsification of the occurrence of reversed angular momentum identities. This review also summarises aspects of a consistent implementation of quantum mechanics for spectroscopy with selected diatomic molecules of interest in astrophysics and in engineering applications.

Franklinite-Zincochromite-Gahnite solid solutions have been prepared by ceramic or coprecipitation method and its pigmenting capacity as cool ceramic pigments in different glazes (double and single firing frits and porcelain frit) was studied. XRD, UV-Vis-NIR diffuse reflectance, CIEL*a*b* colour analysis, bandgap measurement and the photocatalytic activity over the Orange II azoic dye were carried out for the characterization of samples. Following criteria of high red colouring capacity and high NIR reflectance at minimum Cr amount, Zn(Fe1.8Cr0.2), Zn(Al1.5Cr0.5) and Zn(Al1.3Cr0.5Fe0.2)O4 turn out to be the optimal compositions for an intense reddish cool pigment. All powders show a direct semiconductor behaviour with bandgap around 2 eV, falling in the visible range (620 nm), and according to literature, the associated photocatalytic activity over Orange II with visible light irradiation is moderate in all cases, but the Franklinite-Zincochromite Zn(Fe1.8Cr0.2) stands out.

As one of GEO-constellation for environmental monitoring in the next decade, Geostationary Environment Monitoring Spectrometer (GEMS) is designed to observe the Asia Pacific region to provide the information on the atmospheric chemicals, aerosol and cloud properties. For the continuous monitoring of the sensor performance after its launch in early 2020, here we suggest deep convective clouds (DCCs) as a possible target for the vicarious calibration of GEMS, the first UV/VIS hyperspectral sensor onboard a geostationary satellite. Tropospheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) are used as a proxy of GEMS, and a conventional DCC detection approach applying the thermal threshold test is used for the DCC detection based on the collocations with Advance Himawari-8 Imager (AHI) onboard Himawari-8 geostationary satellite. DCCs are frequently detected over the GEMS observation area on average over 200 pixels in a single observation scene. Considering the spatial resolution of GEMS, 3.5 km×7 km which is similar to TROPOMI, and its temporal resolution (8 times a day), availability of DCCs for vicarious calibration of GEMS is expected to be sufficient. Inspection of the DCC reflectivity spectra estimated from the OMI and TROPOMI data also shows a promising result. Even though, their observation geometry and sensor characteristics are quite a different, the estimated DCC spectra agree quite a well within a known uncertainty range with comparable spectral features. When the DCC detection is further improved by applying both visible and infrared tests, the variability of DCC reflectivity from the TROPOMI data is reduced by half, from 10% to 5%. This is mainly due to the efficient screening of cold thin cirrus with the visible test and of bright warm clouds with the infrared test. The precise DCC detection is also expected to contribute to the accurate characterization of the cloud reflectivity, which will be further investigated.

We have investigated the influence of the relative proportions of glass formers in a series of lithium alumino-borosilicate glasses with respect to electrical conductivity () and glass transition temperature (Tg) as functions of glass structure, as determined by Raman spectroscopy. The ternary lithium alumino-borate glass exhibits the highest  and lowest Tg among all the compositions of the glass series, 30Li2O•3Al2O3• (67-x) B2O3•xSiO2. However, as B2O3 is replaced by SiO2, a shallow minimum in  as well as a shallow maximum in Tg are observed near x = 27, where the Raman spectra indicate isolated diborate/tetraborate/orthoborate groups are being progressively replaced by danburite/reedmergnerite-like borosilicate network units. Overall, as the glasses become silica-rich,  is minimized, while Tg is maximized. In general, these findings show correlations among Tg, (sensitive to network polymerization),  (proportional to ionic mobility), and the different borate and silicate glass structural units as determined by Raman spectroscopy. X-ray diffraction analyses demonstrate the absence of appreciable crystallinity in the glasses investigated. However, scanning electron microscopy (SEM) images of HF-etched samples showed that glasses, and especially the borate-rich compositions comprise two distinct glassy phases. The isolated phase is 25-100 nm in diameter, dispersed evenly in a glassy matrix.

Ultrafast pump-probe spectroscopic studies allow for deep insights into the mechanisms and timescales of photophysical and photochemical processes. Extracting valuable information from these studies, such as reactive intermediates' lifetimes and coherent oscillation frequencies, is an example of the inverse problems of chemical kinetics. This article describes a consistent approach for solving this inverse problem that avoids the common obstacles of simple least-squares fitting that can lead to unreliable results. The presented approach is based on the regularized Markov Chain Monte Carlo sampling for the strongly nonlinear parameters, allowing for a straightforward solution of the ill-posed nonlinear inverse problem. The software to implement the described fitting routine is introduced and the numerical examples of its application are given. We will also touch on critical experimental parameters, such as the temporal overlap of pulses and cross-correlation time and their connection to the minimal reachable time resolution.

Solving the problem of searching for new scintillators based on available materials, we were the first to obtain and study a single crystal of CsI doped with divalent ytterbium ions. This work was directed to study of luminescence mechanism of Yb2+ ions and excitation transfer from crystalline matrix of CsI to dopant ions under VUV excitation. Using time-resolved spectroscopy, spin-allowed and spin-forbidden radiative transitions of ytterbium ions at room temperature were discovered. At 10 degrees, the emission of self-trapped excitons was detected. UV and VUV excitation spectra were obtained in the emission bands of ytterbium and self-trapped excitons. It was found that Yb2+ luminescence is excited in the excitonic region in the range of 10-45 eV. The mechanism of charge compensation of Yb2+ ions in a CsI crystal was also studied, the spectrum of the thermally stimulated depolarization current was measured, and the activation energies of the two observed peaks were calculated. These peaks belong to impurity-vacancy complexes in two different positions.It is concluded that Yb2+ ions are promising dopants for CsI scintillators and X-ray phosphors in combination with SiPM photodetectors.

Laser-induced breakdown spectroscopy (LIBS) of pharmaceutical drugs that contain paracetamol is investigated in air and argon atmospheres. Characteristic neutral and ionic spectral lines of various elements and molecular signatures of CN violet and C₂ Swan band systems are observed. The relative hardness of all drug samples is measured as well. Principal component analysis, a multivariate method, is applied in data analysis for demarcation purposes of the drug samples. The CN violet and C₂ Swan spectral radiances are investigated for evaluation of possible correlation of the chemical and molecular structures of the pharmaceuticals. Complementary Raman and Fourier-transform-infra-red spectroscopies are used record molecular spectra of the drug samples. The applicationof the above techniques for the drug screening are important for identification and mitigation of drugs that reveal additives that may cause adverse side-effects.

Propolis is a bee product widely used as a dietary supplement and included in sweets or baby foods due to its well-known antioxidant and nutritional properties that are directly correlated with its phenolic composition. For this reason, this study analysed the total contents of flavones and flavonols, flavanones and dihydroflavonols, and the antioxidant capacity by using the methods of ABTS and linoleic acid/β-carotene in 99 samples of propolis from Spain and Chile. A rapid method was developed for quantifying these parameters in raw propolis using near infrared (NIR) spectroscopy with an optical fibre probe of remote reflectance applied directly to the ground up sample. The models developed allow the determination of the total of flavones and flavonols (0-183 mg rutin/ g propolis), of the total of flavanones and dihydroflavonols (9-109 mg pinocembrin/ g propolis extract), and the antioxidant capacity by the ABTS method (0-3212 nmolesTrolox/ mg of propolis) and of linoleic acid/β-carotene (22-86% inhibition). The NIR spectroscopy models were applied in external validation to different samples of the calibration group, which led to the conclusion that the methods developed provide significantly identical data to the initial chemical data of reference.

Dairy products are an important source of protein and other nutrients in the Mediterranean diet. In these countries the most common source of milk for producing dairies are cow, goat, sheep and buffalo. Andalusia is traditionally the largest producer of goat milk in Spain. Kefir is a fermented product made from bacteria and yeasts which has health benefits beyond its nutritional properties. There is a lack of knowledge about the molecular mechanisms and metabolites that bring about these benefits. In this work, the combination of analytical techniques (GC-FID, UHPLC-MS-QToF, GC-QqQ-MS, and GC-ToF-MS) resulted in the detection of 105 metabolites in kefir produced with goat milk from two different thermal treatments (raw and pasteurized) fermented at four times (12, 24, 36, and 48 h, using 0 h as control). Of these, 27 metabolites differed between kefir produced with raw and pasteurized milk. These changes could be possibly caused by the effect of pasteurization on the microbial population in the starting milk. Some interesting molecules were identified, as shikimic acid, dehydroabietic acid, GABA and tyramine that could be related to antibacterial properties, enhance of immune system and arterial pressure. Moreover, a viability assay of the NIRS technique was performed to evaluate its use on monitoring the fermentation and classification of samples, which had resulted in a 90 % of correct classified samples according to their fermentation time. This study represents the most comprehensive metabolomic analysis of goat milk kefir so far, revealing the intricate changes in metabolites during fermentation and the impact of milk treatment.

In human body, carboxylesterases (CEs) play the crucial roles in xenobiotic metabolism and lipid homeostasis. But the abnormal CEs expression is highly associated with some diseases, such as hyperlipidemia, diabetes and liver cancer. Therefore, it is of great significance to develop an efficient tool for the accurate detection of CEs in living organisms. Herein, an innovative near-infrared (NIR) fluorescent probe TTAP−AB has been designed for CEs detection based on aggregation-induced emission (AIE) mechanism. This probe exhibits rapid response (2 min), excellent sensitivity (limit of detection = 8.14×10−6 U/mL), and high selectivity towards CEs. Additionally, owing to the good biocompatibility, probe TTAP−AB enables to monitor the dynamic changes of CEs level under drug-induced modulation in living cells and zebrafish. More importantly, probe TTAP−AB is successfully employed to image the liver tumor and assist tumor resection by the real-time monitoring of CEs, indicating that TTAP−AB is promising to guide liver cancer surgery. Therefore, probe TTAP−AB can not only enrich the strategies for CEs detection in biological systems, but also has great potential for some clinical imaging applications, including medical diagnosis, preclinical research, and imaging-guided surgery.

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.

This work investigates spatial and temporal distributions of hydroxyl, OH, in laser-plasma in laboratory air at standard ambient temperature and pressure. Of interest are determination of temperature and density of OH and establishment of a correlation of molecular OH emission spectra with shadow graphs for time delays of 50 to 100 microsecond, analogous to previous work on shadow graph and emission spectroscopy correlation for cynaide, CN, in gas mixtures and for time delays of the order of 1 microsecond. Wavelength- and sensitivity- corrected spatiotemporal data analysis focuses on temperature inferences using molecular OH emission spectroscopy. Near-ir radiation from a Q-switched laser device initiates optical breakdown in laboratory air. The laser device provides 6 nanosecond, up to 850 milli Joule pulses at a wavelength of 1064 nanometer, and focal irradiance in the range of 1 to 10 Tera Watt per centimeter-squared. Frequency doubled beams are utilized for capturing shadow graphs for visualization of the breakdown kernel at time delays in the range of 0.1 to 100 microsecond. OH emission spectra of the laser plasma, spatially resolved along the slit dimension, are recorded in the wavelength range of 298 nm to 321 nm, and with gate widths adjusted to 10 microsecond for the intensified charge-coupled device that is mounted at the exit plane of a 0.64 m Czerny-Turner configuration spectrometer. Diatomic OH signals occur due to recombination of the plasma and are clearly distinguishable for time delays larger than 50 microsecond, but are masked by spectra of N2 early in the plasma decay.

Current sources play an essential role in tissue excitation used in bioelectrical impedance spectroscopy. Most investigations use Howland current sources that, despite their practicality and simplified implementation, have operating frequency limitations and dependence on the load impedance due to theirs narrow output impedance, specially at higher frequencies. The objective of this work is to propose model for a robust current-controlled sinusoidal oscillator. The oscillator is based on fully analog electronics, which enables controlling oscillation phase and amplitude by using a voltage reference. The mathematical model is based on Pyragas control application to the classical harmonic oscillator. From the modelling process, it was build an oscillator topology based on second-generation current carriers and on transconductance amplifiers. The reference signal (Fsync) was a sinusoidal voltage source having a frequency of 1MHz and an amplitude of 1Vpp. The oscillator output current synchronized the oscillations’ phase and amplitude with Fsync, regardless of their magnitude before the control signal acted in the circuit at t≈13.5μs. SPICE simulations using ideal components have confirmed the successful operation of the proposed oscillator. This type of oscillator can be implemented in SOIC, then allowing oscillation control interface with logic circuits.

Observation of parity-violating effects in chiral molecules is a long-standing challenge of the molecular spectroscopy community. In the microwave regime, the difference in transition frequencies between enantiomers is predicted to be below the mHz level, which is considerably beyond current experimental capabilities. The most promising future efforts combine vibrational spectroscopy, buffer gas cooling, and carefully chosen molecular candidates with large predicted parity-violating shifts. Here, we demonstrate for the first time high-precision differential microwave spectroscopy, achieving sub-Hz precision by coupling a cryogenic buffer gas cell with a tunable microwave Fabry-Perot cavity. We report statistically limited sub-Hz precision of (0.08±0.72) Hz, observed between enantiopure samples of (R)-1,2-propanediol and (S)-1,2-propanediol at frequencies near 15 GHz. We confirm highly repeatable spectroscopic measurements compared to traditional pulsed-jet methods, opening up new capabilities in probing subtle molecular structural effects at the 10−10 level and providing a platform for exploring sources of systematic error in parity-violation searches. We discuss dominant systematic effects at this level and propose possible extensions of the technique for higher precision.

This article discusses laser-induced laboratory-air plasma measurements and analysis of hydroxyl (OH) ultraviolet spectra. New experiments with Q-switched laser pulses illustrate occurrence of molecular recombination spectra for time delays of the order of several dozen of microseconds after plasma initiation. The computation of the emission spectra utilizes line strength data that are communicated as a supplementary file. Applications of detailed OH computations include laser-induced plasma and combustion analyses, to name but two applications.

Orientational dependence of the IR absorbing amide bands of silk is demonstrated from two orthogonal longitudinal and transverse microtome slices only $\sim 100$~nm thick. A scanning near-field optical microscopy (SNOM) which preferentially probes orientation perpendicular to the sample's surface was used. Spatial resolution of silk-epoxy boundary was defined with a $\sim 100$~nm resolution while the spectra were collected by a $\sim 10$~nm tip. Ratio of the absorbance of the amide-II C-N at 1512~cm$^{-1}$ and amide-I C=O $\beta$-sheets at 1628~cm$^{-1}$ showed sensitivity of SNOM to the molecular orientation. SNOM characterisation is complimentary to the far-field absorbance which is sensitive to the in-plane polarisation. Volumes with cross sections smaller than 100~nm can be characterised for molecular orientation. A method of absorbance measurements at four angles of slice cut orientation, which is equivalent to the four polarisation angles absorbance measurement is proposed.

Solar neutrinos have played a central role in the discovery of the neutrino oscillation mechanism. They still are proving to be a unique tool to help investigate the fusion reactions that power stars and further probe basic neutrino properties. The Borexino neutrino observatory has been operationally acquiring data at Laboratori Nazionali del Gran Sasso in Italy since 2007. Its main goal is the real-time study of low energy neutrinos (solar or originated elsewhere, such as geo-neutrinos). The latest analysis of experimental data, taken during the so-called Borexino Phase-II (2011-present), will be showcased in this talk - yielding new high-precision, simultaneous wide band flux measurements of the four main solar neutrino components belonging to the "pp" fusion chain (pp, pep, ⁷Be, ⁸B), as well as upper limits on the remaining two solar neutrino fluxes (CNO and hep).

Vibrational spectroscopies (FTIR, Raman) are exceptionally valuable tools for the identification and crystal-chemical study of fibrous minerals, and asbestos amphiboles in particular. Raman spectroscopy has been widely applied in toxicological studies and thus a large corpus of reference data on regulated species is found in the literature. However, FTIR spectroscopy has been mostly used in crystal-chemical studies and very few data are found on asbestos amphiboles. This paper is intended to fill this gap; we report new FTIR data collected on a suite of well-characterized samples of the five regulated amphibole species: anthophyllite, amosite and crocidolite, provided by the Union for International Cancer Control (UICC) Organization, and tremolite and actinolite, from two well-known occurrences. The data from these reference samples have been augmented by results from additional specimens to clarify some aspects of their spectroscopic features. We show that the FTIR spectra in both the OH-stretching region and in the lattice modes region can be effective for rapid identification of the asbestos type.

This work reports measurements of calcified gallstone elemental compositions using laser-induced optical emission spectroscopy. The experimental results support the importance of the magnesium concentration in gallstone growth. Granular stones reveal an increased magnesium concentration at the periphery of the granules, suggesting the inhibition of further growth. Non-granular gallstones reveal lower overall magnesium concentrations but with higher values near the center.

Friction and wear take place on two solid surfaces in sliding contact as a result of the mechanical, thermal and chemical interactions with the participation of environmental species. Electron microscopy and the associated spectroscopic analyses are powerful in probing these mechanisms in spatial resolutions from micro to atomic scale. This article provides a review of the author’s work in the wear and friction mechanisms of PVD hard coatings in which various SEM- and TEM-based microscopic and spectroscopic techniques were employed. Understanding on the failure mechanisms and the origin of self-adaptive friction has been improved to nano-scale. Other related issues are also discussed, such as sample preparation techniques for cross-sectional electron microscopy, energy dispersive X-ray spectroscopy and electron energy loss spectroscopy.

In this work we theoretically investigate the responsivity/noise equivalent power (NEP) trade-off in graphene/semiconductor Schottky photodetectors (PDs) operating in the near-infrared regime and working at room temperature. Our analysis shows as the responsivity/NEP ratio is strongly dependent on the Schottky barrier height (SBH) of the junction and we derive a closed analytical formula for maximizing it. In addition, we theoretically discuss as the SBH is linked to the bias applied to the junction in order to show how these devices could be optimized in practice for different semiconductors. We discover that graphene/n-silicon (Si) Schottky PDs could be optimized at 1550nm showing a responsivity and NEP of 133mA/W and 500fW/Hz, respectively, by a low reverse bias of only 0.66V. Moreover, we show that graphene/n-germanium (Ge) Schottky PDs optimized in term of responsivity/NEP ratio could be employed at 2000nm with a responsivity and NEP of 233mA/W and 31pW/Hz, respectively. We believe that our insights are of great importance in the field of silicon photonics for the realization of Si-based PDs to be employed in power monitoring, lab-on-chip and environment monitoring applications.

A hypothesis that the generally accepted value of the LiPON conductivity should be attributed to the absorption and displacement currents is substantiated. The reason is a small contribution of the drift current due to field screening by the electric double layer. The basis for this assumption is the measurement of the LiPON absorption capacitance, according to which its dielectric constant is about 106. An alternative equivalent circuit containing a non-ideal absorption element is proposed and its impedance is calculated. It is shown that the Bode diagrams of the alternative circuit well approximate the experimental curves. Parameters and the magnitude of electric field screening are calculated basing on proposed model of a double electric layer. Considering the screening effect, the drift conductivity of LiPON is obtained, which value is in good agreement with the data on lithium concentration and mobility.

Abstract: The high entropy alloy (HEA) of equiatomic composition CrNiFeCoMn and with FCC 11 crystal structure was prepared by either induction melting and additive manufacturing with a se- 12 lective laser melting (SLM) process, starting from mechanically alloyed powders. Unlike induction 13 melting, the as-produced SLM alloy showed fine nitride and Cr-rich s phase precipitates. Mechan- 14 ical spectroscopy measurements were performed on specimens cold worked and/or recrystallized. 15 Young’s modulus values of (140±10) GPa and (90±10) GPa were measured at 300 K for induction 16 melted and SLM samples, respectively. The values increased to (160±10) GPa and (170±10) GPa for 17 recrystallized samples. Damping measurements as a function of temperature showed two peaks 18 which were attributed to dislocations bending and grain boundaries sliding. The peaks were super- 19 posed on a temperature increasing background.

Micro- and nanoflowers are a class of materials composed of particles with high surface-to-volume ratio. They are being extensively studied in the last decade due to simple preparation protocols and promising applications in biosensing, as drug delivery agents, for water purification and so on. Flowerlike objects, due to their highly irregular surface, may act also as plasmonic materials, providing resonant coupling between optical waves and surface plasmon excitations. This fact infers for the possibility to use micro- and nanoflowers as effective surface-enhanced Raman scattering (SERS) substrate materials. Here, we report on the design and Raman enhancement properties of silver flowerlike structures, deposited on aluminum surface. A simple and cost-effective fabrication method is described, which leads to SERS substrates of high developed surface area. The morphology of the silver flowers on a nanoscale is characterized by self-organized quasiperiodic stacks of nanosheets, which act as plasmonic cavity-resonators. The substrates were tested against rhodamine-6G (R6G) water solutions of concentration varying between 10^–3 M and 10^–7 M. Optimal SERS enhancement factors of up to 10⁵ were established at R6G concentrations in the range 10^–6 – 10^–7 M.

Biocomposite membranes based on polylactic acid (PLA) and cellulose nanocrystals (CNCs) were developed using a scientific approach. Dicumyl peroxide (DCP) was used as a polymerization ini-tiator, while tin octoate (Sn(Oct)2) and triphenylphosphane (P(C6H5)3) were used as catalysts. A torque rheometer was used to mix the components of the biocomposite, and thin films was prepared by solvent casting. Fourier transform infrared (FTIR) spectroscopy confirmed the coupling between the PLA and CNCs. Field emission scanning electron microscopy (FESEM) showed that the CNCs were well-dispersed in the PLA matrix with an unimodal particle size distribution and a maximum particle size of around 200 nm. Thermogravimetric analysis (TGA) and differential scanning calo-rimetry (DSC) analysis demonstrated good thermal stability and improved biodegradability of the biocomposite membrane compared to pure PLA. Mechanical characterization showed a Young's modulus of 1.65 GPa, which is comparable to that of other composite materials, and a maximum tensile strength of 20.31 MPa, which is higher than that of pure PLA. These results suggest that the developed biocomposite membrane has potential applications in water filtration, food packaging, and biomedical devices.

Two-dimensional (2D) semiconductors like Transitional Metal Dichalcogenides (TMDCs) have attracted strong research interest in the last decade. Unlike the more celebrated 2D material graphene, TMDCs like molybdenum disulfide(MoS₂) possess bandgap. The number of layers critically depends on the band structure of MoS₂. For example, it is indirect for bulk MoS₂. However, it becomes direct bandgap material for a monolayer MoS₂. Monolayer MoS₂, therefore, becomes an important material for photoelectronic devices. An essential aspect of such devices is the metal-semiconductor junction. Metal-TMDC junction is, therefore, a well-studied interface due to its importance for 2D materials-based photoelectronic devices. Most importantly, it can be flexible, stretchable to it’s length, and bent to a large angle. We used metals like Au and Al to interface with TMDs like MoS₂. We used silicon and PDMS as substrates. So, we have to focus on investigating the relative properties of various TMDCs. We see change in band energy and vibrational modes via Photoluminiscence and Raman spectroscopy as shown in the article. However, certain aspects are yet to be explored, for example, how this interface behaves in the presence of strain.

Gold nanoparticles have been indicated for use in a diagnostic and/or therapeutic role in several cancer types. The use of gold nanorods (AuNRs) with a surface plasmon resonance (SPR) in the second Near-Infrared II (NIR-II) optical window promises deeper anatomical penetration through increased maximum permissible exposure and lower optical attenuation. In this study, the targeting efficiency of anti-epidermal growth factor receptor (EGFR) antibody functionalised AuNRs with an SPR at 1064 nm was evaluated in vitro. Four cell lines, KYSE-30, CAL-27, Hep-G2 and MCF-7 that either over or under expressed EGFR were used. This expression was confirmed by flow cytometry and immunofluorescence. Cytotoxicity assays showed no AuNRs toxicity to both EGFR positive and EGFR negative cell lines up to a concentrations of 19 µg/ml. Optical microscopy demonstrated a significant difference (p<0.0001) between targeted AuNRs (tAuNRs) and untargeted AuNRs (uAuNRs) in all four cancer cell lines. This study demonstrates that anti-EGFR functionalisation significantly increased the number of tAuNRs associated with each EGFR positive cancer cell. This successful targeting highlights the use of tAuNRs for molecular photoacoustic imaging or tumour treatment through plasmonic photothermal therapy.

Micro-Raman spectroscopy was carried out to evaluate the localized residual stresses in commercial Gallium Nitride-based devices, specifically AlGaN/GaN High Electron Mobility Transistors (HEMTs) in a novel packaging design provided by STMicroelectronics S.r.l. The packaging plays a key role in protecting the device core against the external environment, thus minimizing damages caused by mechanical shocks, exposure to light, and contact with chemicals, conjointly achieving an efficient heat dissipation rate. Even though the packaging is a required step for the proper functioning of ready-to-use electronic devices, its application typically may introduce mechanical stress to AlGaN/GaN HEMTs, which can result in various reliability issues. In this paper, we investigate the impact of packaging on residual stress by analyzing the frequency shift of the E2 Raman peak along GaN layers and at the GaN/Si interface. An extensive evaluation was conducted using both a packaged device and a wafer-level device. The correlation between Raman frequency shifts of the E2 mode was accurately quantified, revealing a stress mitigation of approximately 0.1 GPa. This reduction is ascribed to the compressive stress introduced by the packaging, which partially offsets the intrinsic tensile stress of the wafer-level device. The proposed methodology could, in principle, be implemented to improve the development of a packaging.

In this paper, a relatively new hyper convolution spectra for characterization liquid, viscoelastic and solid samples is presented. Special attention is paid to the biophysical characterization of epithelial tissues and early detection of cancer of the skin, cervix, colon, and oral cavity. The method is based on the use of two types of white light, diffuse and polarized, from the same LED light sources. Based on the subtraction of the intensity values of these two lights and using the hyper convolution algorithm, the ratio of paired and unpaired electrons of tissue is obtained. This ratio correlates well with the state of the tissue: normal, irritating, precancerous, and cancerous. First, a proof-of-concept studies were performed, and later clinical studies on samples from one thousand two hundred fifteen people were performed. It showed that hyper Opto-Magnetic Imaging Spectroscopy (OMIS) can detect epithelial tissue cancers with an accuracy of 85-96%. Bearing in mind that the OMIS method also acquires the biophysical characteristics of the deeper skin layers (epidermis, basement membrane, dermis) by analysing convolution spectra of RGB channels of both diffuse and polarized white light, it is possible to apply this method in cosmetics (skin hydration, collagen, and elastin states, etc.). During OMIS applications, we noticed places where improvements could be made to increase method’s accuracy using advanced machine learning methodologies.

Functional osseoconductive coatings based on hydroxylapatite (HAp) and applied preferentially by atmospheric plasma spraying to medical implant surfaces are a mainstay of modern implantology. During contact with the hot plasma jet, HAp particles melt incongruently and undergo complex dehydration and decomposition reactions that alter their phase composition and crystallographic symmetry, and thus, the physical and biological properties of the coatings. Surface analytical methods such as laser-Raman and nuclear magnetic resonance (NMR) spectroscopies are useful tools to assess the structural changes of HAp imposed by heat treatment during their flight along the hot plasma jet. In this contribution, the controversial information on the existence or non-existence of oxyapatite, i.e. fully dehydrated HAp as a thermodynamically stable compound is highlighted.

Principle of memristor presented by Leon Chua and time reversal based non-linear elastic wave spectroscopy (TR-NEWS) which can be applied to acoustic tomography are reviewed. Correlation of acoustic or electromagnetic nonlinear waves and its time reversed wave can produce strong signal. Materials like transducer or biological skin can be assumed to be composed of a large number of small elastic unit: hysteretic elementary unit (HEU), and one can take a HEU as a memristor whose operation depends on time. Relation between TR-NEWS and solitonic wave in fluid, and relation between decomposition of time reversal operator (DORT) and chaotic oscillation are discussed.

A novel chemically cross-linked hydrogel was prepared through the utilization of the nor-bornene (Nb)-methyl tetrazine (mTz) click reaction, derived from carboxymethyl cellulose (CMC) and alginate (Alg). The hydrogel was designed to generate reactive oxygen species (ROS) from NIR-dye, indocyanine green (ICG) for a combined photothermal and photodynamic ther-apy (PTT/PDT). The cross-linking of Nb and mTz moieties occurred via an inverse elec-tron-demand Diels-Alder reaction under physiological conditions avoiding the need for a cata-lyst. The resulting hydrogels exhibited viscoelastic properties (G′ ~ 492-270 Pa) and high porosi-ty. The hydrogels were found to be injectable with tunable mechanical characteristics. The ICG encapsulated hydrogels demonstrated ROS generation ability under NIR exposure. The ROS production was investigated through DPBF assays to access photodynamic effect (with NIR irra-diation at 1-2W for 5-15 min). The temperature of the ICG-loaded hydrogels was also raised up-on the NIR irradiation to eradicate tumor cells photothermally. In vitro cytocompatibility as-sessments revealed the non-toxic nature of CMC-Nb and Alg-mTz towards HEK-293 cells. Fur-thermore, the ICG-loaded hydrogels effectively inhibited the metabolic activity of Hela cells following NIR exposure. This innovative hydrogel system holds promise for applications in combined PTT and PDT.

This work communicates the connection of measured shadowgraphs from optically induced air breakdown with emission spectroscopy in selected gas mixtures. Laser-induced optical breakdown is generated using 850 mJ and 170 mJ, 6-ns pulses at a wavelength of 1064 nm, the shadowgraphs are recorded using time-delayed 5-ns pulses at a wavelength of 532 nm and a digital camera, and emission spectra are recorded for typically a dozen of discrete time-delays from optical breakdown by employing an intensified charge-coupled device. The symmetry of the breakdown event can be viewed as close-to spherical symmetry for time-delays of several 100 ns. Spectroscopic analysis explores well-above hypersonic expansion dynamics using primarily the diatomic molecule cyanide and atomic hydrogen emission spectroscopy. Analysis of the air breakdown and selected gas breakdown events permits the use of Abel inversion for inference of the expanding species distribution. Typically, species are prevalent at higher density near the hypersonically expanding shockwave, measured by tracing cyanide and a specific carbon atomic line. Overall, recorded air breakdown shadowgraphs are indicative of laser-plasma expansion in selected gas mixtures, and optical spectroscopy delivers analytical insight into plasma expansion phenomena.

A recent study showed the potential of DA Perten 7200 NIR Spectrometer in detecting chlorpyrifos-methyl pesticide residue in rough, brown, and milled rice. However, this instrument is still lab-based and generally suited for point-of-sale testing in many countries. To provide a field deployable version of this technique, an existing light emitting diode (LED)-based instrument which provide discrete NIR wavelength illumination and reflectance spectra over the range of 850-1550 nm was tested. Spectra were collected from rough, brown, and milled rice at different pesticide concentrations and analysed for quantitative and qualitative measurement using partial least squares regression (PLS) and discriminant analysis (DA). Simulations for LED-based instruments were also evaluated using segments of spectra from the DA7200 to represent LED illumination. For the simulation of the existing LED-based instrument (LEDPrototype1) using their wavelengths range yielded 70.4% to 100% correct classification. Simulation of a second LED instrument, LEDPrototype2, with spectral segments selected based on significant wavelength regions from PLS regressions coefficients obtained from the DA7200 showed improved performance with R2 of 0.59 to 0.82 and correct classifications of 71.3 to 100%. An actual LED based instrument with this capability could provide a quick screening tool to determine if MRLs are exceeded.

Hyperspectral imaging data holds great potential for various stages of the mining life cycle in active and abandoned mines. The technology, however, has yet to achieve large-scale industrial implementation and acceptance. While hyperspectral satellite im-agery yields high spectral resolution, high signal-to-noise ratio (SNR), and global availability with breakthrough satellite sys-tems like EnMAP, EMIT, and PRISMA, limited spatial resolution poses challenges for mining sectors, which require decimeter- to centimeter-scale spatial resolution for applications such as reconciliation, ore/waste estimates, geotechnical assessments, and en-vironmental monitoring. Hyperspectral imaging from drones (Uncrewed Aerial Systems; UASs) offers high spatial resolution data relevant to the pit/ mine scale, with the capability for frequent, user-defined re-visit times. Collecting data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions offers to detect different minerals and surface alteration patterns, potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. In this paper, we review of applicable instrumentation, software components, and relevant studies deploying hyperspectral imaging in or appropriate to the mining sector, especially for hyperspectral VNIR-SWIR UASs. If directly applicable, draw on previous insights derived from airborne, satellite, and ground-based imaging systems. We also discuss common practices for UAS survey planning and sampling considerations for interpretation.

The fine structure of Apricot pectin polysaccharides is discussed from both literature and recent work we have performed. Structural characterization utilized 1D and 2D homo- and hetero-nuclear NMR spectroscopy including results from High Performance Size Exclusion Chromatography (HP-SEC), HP Anion-Exchange Chromatography with Pulsed Amperometric Detection (HPAEC-PAD) and FTIR spectroscopy. The purified pectin fraction (F1AP) was found to be composed of D-galacturonic acid, L-rhamnose, D-arabinose and D-galactose in a 1.0 : 0.1 : 0.36 : 0.12 molar ratio, respectively, which is consistent with a pectin RG-1 branched with arabinogalactan side chain polysaccharides, and has a weight-average molecular weight of approximately 1588.2 kDa. The slope of the hydrodynamic radius versus the molar mass was 0.57, indicating the presence of coil conformations. The results from HPAEC-PAD, HPSEC and NMR spectroscopy (1H, 13C, zTOCSY, HSQC, HSQCTOXY and HMBC) demonstrated that F1AP fine fraction F1AP1, derived from original F1AP, has a backbone of (1→4)-linked -D-galacturonic acid and -L-rhamnopyranosyl residues branched with arabinogalactan of multiply glycosidic linkages of T- α-Araf, 3-α-Araf, 5-α-Araf, T- α -Arap, 2- α-Arap side chains, having methyl and acetylated groups, and has high molecular weights (1945 kDa). While the other F1A6 fraction consists predominately of an HG region of pectin polysaccharides with low molecular weights (117.5 kDa), less aggregated. The F1AP1 polysaccharide was highly viscous and its hydrodynamic radius was 64,3 nm. The exponent b of Rh-Mw (conformation plot) was determined to be 0.48, indicating a compact flexible coil conformation of the macromolecule in solution. However, the F1AP6 fraction of apricot fruits belong to backbone of repeats units of [-(1→4)-α-D-GalpA-1]n – both HG and partly contents RG-II polysaccharides, bearing heterosugar sidechains, including α-Ara, α -Rha and β-Gal residues and adopt more stiffness rod like conformation.

Fourier Transform Infrared Spectroscopy (FTIR), provides valuable biochemical information for biomedical analysis. It aids in identifying cancerous tissues, diagnosing diseases like acute pancreatitis or Alzheimer's, and has applications in genomics, proteomics, and metabolomics. A combination of FTIR and chemometrics constitute an approach that shows promise in fields like biology, forensics, food quality control, and plant variety identification. The study aims to explore the feasibility of ATR-FTIR spectroscopy for identifying ABO-blood types using spectroscopic tools. We employ various classifying algorithms, including Linear Discriminant Analysis (LDA), Naïve Bayes Classifier (NBC), Principal Component Analysis (PCA), and combinations of these methods, to detect A and B antigens and determine the ABO blood type. The results show that these algorithms predict the blood type to a greater extent than random selection, although they do not match the precision of biochemical blood typing tools. Additionally, our findings suggest a higher sensitivity of the methodology in identifying B antigens compared to A antigens.

This work discusses diatomic molecular spectroscopy of laser-induced plasma and analysis of data records, specifically signatures of cyanide, CN. Line strength data from various databases are compared for simulation of the CN, B2Σ+⟶X2Σ+, Δv=0 sequence. Of interest are recent predictions using an astrophysical database, i.e., ExoMol, a laser-induced fluorescence database, i.e., LIFBASE, and a program for simulating rotational, vibrational and electronic spectra, i.e., PGOPHER. Cyanide spectra that are predicted from these databases are compared with line strength data that are in use by the author for the last three decades in the analysis of laser-plasma emission spectra. Comparisons with experimental laser-plasma records are communicated as well, and for spectral resolutions of 33 and 110 picometer. The accuracy of the CN line strength data is better than one picometer. Laboratory experiments utilize 308-nm, 35-picosecond bursts within an overall 1-nanosecond pulse-width, and 1064-nm, 6-ns pulse-width radiation. Experimental results are compared with predictions. Differences of the databases are elaborated for equilibrium of rotational and vibrational modes and at an internal, molecular temperature of the order of 8,000 Kelvin. Applications of accurate CN data include for example combustion diagnosis, chemistry, and supersonic and hypersonic expansion diagnosis. The cyanide molecule is also of interest in the study of astrophysical phenomena.

Water plays a crucial role in maintaining plant functionality and drives many ecophysiological processes. The distribution of water resources is in a continuous change due to global warming affecting the productivity of ecosystems around the globe, but there is a lack of non-destructive methods capable of continuous monitoring of plant and leaf water content that would help us in understanding the consequences of the redistribution of water. We studied the utilization of novel small hyperspectral sensors in the 1350-2450 nm spectral range in non-destructive estimation of leaf water content in laboratory and field conditions. We found that the sensors captured up to 96% of the variation in equivalent water thickness (EWT, g/m²) and up to 90% of the variation in relative water content (RWC). These laboratory findings were supported by field measurements, where repeated leaf spectra measurements were in good agreement (R²=0.79) with a time-lagged change of tree xylem diameter. Further tests were done with an indoor plant (Dracaena marginate Lem.) by continuously measuring leaf spectra while drought conditions developed, which revealed detailed diurnal dynamics of leaf water content. We conclude that close-range hyperspectral spectroscopy can provide a novel tool for continuous measurement of leaf water content at the single leaf level and help us to better understand plant responses to varying environmental conditions.

A laser-based hydrogen (H₂) sensor using wavelength modulation spectroscopy (WMS) was developed for contactless measurements of molecular hydrogen. The sensor uses a distributed feedback (DFB) laser to target the H₂ quadrupole absorption line at 2121.8 nm. The H₂ absorption line exhibits weak collisional broadening and strong collisional narrowing effects. Both effects were investigated by comparing measurements of the absorption linewidth with detailed models using different line profiles that include collisional narrowing effects. The collisional broadening and narrowing parameters were determined for pure hydrogen as well as for hydrogen in nitrogen and air. Performance of the sensor was evaluated and the sensor applicability for H₂ measurements in a range of 0- 10 %v of H₂ was demonstrated. A precision of 0.02 %v was achieved with 1 meter of absorption pathlength (0.02 %v∙m) and 1 s of integration time. For the optimum averaging time of 20 s a precision of 0.005 %v∙m was achieved. A good linear relationship between H₂ concentration and the sensor response was observed. A simple and robust transmitter-receiver configuration of the sensor allows in-situ installations in harsh industrial environments.

Free volume is an extremely important intrinsic defect in polymers. Structurally, the free volume is the randomly distributed holes in the polymer molecular chain segments. From the perspective of molecular movement, it is also the space needed for the movement of molecular segments. In proton exchange membrane fuel cells, the free volume is also the space needed for the directional conduction of protons. Irradiation grafting sulfonated polyvinylidene fluoride (PVDF) is one of the methods to produce proton exchange membrane with good proton channel rate. Using the LYS-1 program, based on the linear absorption coefficient and backscatter coefficient models, the percentage of annihilated positrons in PVDF in the two-layer model and the three-layer model was studied, and comparing the two fitting results it is determined that the model closest to the positron annihilation percentage required by the PALS experiment is the two-layer model, which allows the percentage of positrons that are annihilated in PVDF films with a thickness of 100 μm to reach 46% using the high energy positron source ⁴⁴Ti without using the positron moderator. Using positron annihilation lifetime spectrum (PALS) analysis methods, based on Eldrup's classical model of free volume, the influence of absorbed doses of α particles on the free volume and crystallinity of PVDF was investigated, respectively. Based on the two test results the model of cross-linking and degradation of polyvinylidene fluoride irradiated by α particles was determined. Afterwards, X-ray diffraction (XRD) methods was used to study the change of PVDF crystal area before and after irradiation. The XRD results are consistent with the results measured by PALS.