Determination of uranium isotopes in ground water by alpha spectrometry and associated age-dependent ingestion dose.

Determination of uranium isotopes in ground water plays a key role in assessment of geochemical condition of ground water and for estimating ingestion dose received by the general public because of uranium intake through drinking water. An attempt has been made in the present study to estimate isotopic composition and activity ratios (AR) of uranium isotopes by analysing the ground water samples using alpha spectrometry. Associated age-dependent ingestion dose was also calculated for the public of different age groups. 238U, 235U and 234U activity concentration was found to vary in the ranges of 5.85 ± 1.19 to 76.67 ± 4.16, < 0.90 to 3.15 ± 0.84 and 6.52 ± 1.25 to 107.02 ± 4.92 mBq/L, respectively. 235U/238U AR varies from 0.038 to 0.068 with an average of 0.047 which is close to 0.046 implies that uranium in the ground water is from natural origin. Uranium concentration was found to vary in the range of 0.47 ± 0.10 µg/L to 6.20 ± 0.34 µg/L with a mean value of 3.01 ± 0.23 µg/L, which is much lower than national as well as international recommendation value. Annual ingestion dose to the public of all age groups for uranium intake through drinking water ranges from 0.60 ± 0.11 to 19.50 ± 1.03 µSv/y.

Neutron spectrum measurements near KAMINI reactor south beam vault door using nested neutron spectrometer.

KAlpakkam MINI reactor (KAMINI) is a 233U fuelled research reactor has various neutron irradiation locations for experimental purposes. The pit at the south beam end of KAMINI reactor is being extensively utilised for neutron attenuation experiments in prospective shielding materials as well as for neutron radiography. During reactor operation, it will be closed by a movable shield. A vault door is located above the shield and the movable shield is used to attenuate streaming neutrons and gamma-rays during reactor operation. Even with the shield, there exists significant dose because of streaming neutrons and gamma rays. Its variation depends on the power of the reactor. The neutron and gamma dose rates close to the south beam vault door have recently been found to be 275-300 µSv/h and 175-200 µSv/h, respectively, when the reactor is operating at 10 kW. In order to characterise the streaming neutron spectra of vault door place for the first time, measurements are done using the Nested Neutron Spectrometer. Along with the neutron flux, neutron mean energy and ambient dose-equivalent rate are also measured and compared with earlier measurements carried out inside the south beam pit. It is observed that the presence of paraffin shield reduces the neutron average energy from 370 to 178 keV. Apart from energy reduction, 10 kW normalised neutron flux of south beam pit is also attenuated by the shield by 25 000 times and it is found that the neutron spectrum of the measured location is also more thermalized. Neutron reference data of the location are generated.

One-to-Nine Single Spectroscopic Intelligent Probe for Risk Assessment of Multiple Metals in Drinking Water.

26% of the world's population lacks access to clean drinking water; clean water and sanitation are major global challenges highlighted by the UN Sustainable Development Goals, indicating water security in public water systems is at stake today. Water monitoring using precise instruments by skilled operators is one of the most promising solutions. Despite decades of research, the professionalism-convenience trade-off when monitoring ubiquitous metal ions remains the major challenge for public water safety. Thus, to overcome these disadvantages, an easy-to-use and highly sensitive visual method is desirable. Herein, an innovative strategy for one-to-nine metal detection is proposed, in which a novel thiourea spectroscopic probe with high 9-metal affinity is synthesized, acting as "one", and is detected based on the 9 metal-thiourea complexes within portable spectrometers in the public water field; this is accomplished by nonspecialized personnel as is also required. During the processing of multimetal analysis, issues arise due to signal overlap and reproducibility problems, leading to constrained sensitivity. In this innovative endeavor, machine learning (ML) algorithms were employed to extract key features from the composite spectral signature, addressing multipeak overlap, and completing the detection within 30-300 s, thus achieving a detection limit of 0.01 mg/L and meeting established conventional water quality standards. This method provides a convenient approach for public drinking water safety testing.

Direct Spectroscopic Ferrochelatase Assay.

Ferrochelatases (E.C. 4.99.1.1) catalyze the insertion of ferrous iron into either protoporphyrin IX to make protoheme IX or coproporphyrin III to make coproheme III. Ferrochelatase activity in extracts or purified protein can be measured via several assays. Here, we describe a rapid real-time direct spectroscopic ferrochelatase assay for both protoporphyrin and coproporphyrin ferrochelatases.

Spectroscopic detection of bioaerosols with the wibs-4+: Anthropogenic and meteorological impacts.

This research builds upon a previous study that explored the potential of the modified WIBS-4+ to selectively differentiate and detect different bioaerosol classes. The current work evaluates the influence of meteorological and air quality parameters on bioaerosol concentrations, specifically pollen and fungal spore dynamics. Temperature was found to be the most influential parameter in terms of pollen production and release, showing a strong positive correlation. Wind data analysis provided insights into the potential geographic origins of pollen and fungal spore concentrations. Fungal spores were primarily shown to originate from a westerly direction, corresponding to agricultural land use, whereas pollen largely originated from a North-easterly direction, corresponding to several forests. The influence of air quality was also analysed to understand its potential impact on the WIBS fluorescent parameters investigated. Most parameters had a negative association with fungal spore concentrations, whereas several anthropogenic influences showed notable positive correlations with daily pollen concentrations. This is attributed to similar driving forces (meteorological parameters) and geographical origins. In addition, the WIBS showed a significant correlation with anthropogenic pollutants originating from combustion sources, suggesting the potential for such modified spectroscopic instruments to be utilized as air quality monitors. By combining all meteorological and pollution data along with WIBS-4+ channel data, a set of Multiple Linear Regression (MLR) analyses were completed. Successful results with R2 values ranging from 0.6 to 0.8 were recorded. The inclusion of meteorological parameters was dependent on the spore or pollen type being examined.

Exploring and analyzing the role of hybrid spectrum sensing methods in 6G-based smart health care applications.

Background: Researchers are focusing their emphasis on quick and real-time healthcare and monitoring systems because of the contemporary modern world's rapid technological improvements. One of the best options is smart healthcare, which uses a variety of on-body and off-body sensors and gadgets to monitor patients' health and exchange data with hospitals and healthcare professionals in real time. Utilizing the primary user (PU) spectrum, cognitive radio (CR) can be highly useful for efficient and intelligent healthcare systems to send and receive patient health data. Methods: In this work, we propose a method that combines energy detection (ED) and cyclostationary (CS) spectrum sensing (SS) algorithms. This method was used to test spectrum sensing in CR-based smart healthcare systems. The proposed ED-CS in cognitive radio systems improves the precision of the spectrum sensing. Owing to its straightforward implementation, ED is initially used to identify the idle spectrum. If the ED cannot find the idle spectrum, the signals are found using CS-SS, which uses the cyclic statistical properties of the signals to separate the main users from the interference. Results: In the simulation analysis, the probability of detection (Pd), probability of a false alarm (Pfa), power spectral density (PSD), and bit error rate (BER) of the proposed ED-CS is compared to those of the traditional Matched Filter (MF), ED, and CS. Conclusions: The results indicate that the suggested strategy improves the performance of the framework, making it more appropriate for smart healthcare applications.

Detecting sorghum aphid infestation in grain sorghum using leaf spectral response.

Sorghum aphid, Melanaphis sorghi (Theobald) have become a major economic pest in sorghum causing 70% yield loss without timely insecticide applications. The overarching goal is to develop a monitoring system for sorghum aphids using remote sensing technologies to detect changes in plant-aphid density interactions, thereby reducing scouting time. We studied the effect of aphid density on sorghum spectral responses near the feeding site and on distal leaves from infestation and quantified potential systemic effects to determine if aphid feeding can be detected. A leaf spectrometer at 400-1000 nm range was used to measure reflectance changes by varying levels of sorghum aphid density on lower leaves and those distant to the caged infestation. Our study results demonstrate that sorghum aphid infestation can be determined by changes in reflected light, especially between the green-red range (550-650 nm), and sorghum plants respond systemically. This study serves as an essential first step in developing more effective pest monitoring systems for sorghum aphids, as leaf reflection sensors can be used to identify aphid feeding regardless of infestation location on the plant. Future research should address whether such reflectance signatures can be detected autonomously using small unmanned aircraft systems or sUAS equipped with comparable sensor technologies.

Single-Particle Spectroscopic Chromatography Reveals Heterogeneous RNA Loading and Size Correlations in Lipid Nanoparticles.

Lipid nanoparticles (LNP) have emerged as pivotal delivery vehicles for RNA therapeutics. Previous research and development usually assumed that LNPs are homogeneous in population, loading density, and composition. Such perspectives are difficult to examine due to the lack of suitable tools to characterize these physicochemical properties at the single-nanoparticle level. Here, we report an integrated spectroscopy-chromatography approach as a generalizable strategy to dissect the complexities of multicomponent LNP assembly. Our platform couples cylindrical illumination confocal spectroscopy (CICS) with single-nanoparticle free solution hydrodynamic separation (SN-FSHS) to simultaneously profile population identity, hydrodynamic size, RNA loading levels, and distributions of helper lipid and PEGylated lipid of LNPs at the single-particle level and in a high-throughput manner. Using a benchmark siRNA LNP formulation, we demonstrate the capability of this platform by distinguishing seven distinct LNP populations, quantitatively characterizing size distribution and RNA loading level in wide ranges, and more importantly, resolving composition-size correlations. This SN-FSHS-CICS analysis provides critical insights into a substantial degree of heterogeneity in the packing density of RNA in LNPs and size-dependent loading-size correlations, explained by kinetics-driven assembly mechanisms of RNA LNPs.

Probing chromatin condensation dynamics in live cells using interferometric scattering correlation spectroscopy.

Chromatin organization and dynamics play important roles in governing the regulation of nuclear processes of biological cells. However, due to the constant diffusive motion of chromatin, examining chromatin nanostructures in living cells has been challenging. In this study, we introduce interferometric scattering correlation spectroscopy (iSCORS) to spatially map nanoscopic chromatin configurations within unlabeled live cell nuclei. This label-free technique captures time-varying linear scattering signals generated by the motion of native chromatin on a millisecond timescale, allowing us to deduce chromatin condensation states. Using iSCORS imaging, we quantitatively examine chromatin dynamics over extended periods, revealing spontaneous fluctuations in chromatin condensation and heterogeneous compaction levels in interphase cells, independent of cell phases. Moreover, we observe changes in iSCORS signals of chromatin upon transcription inhibition, indicating that iSCORS can probe nanoscopic chromatin structures and dynamics associated with transcriptional activities. Our scattering-based optical microscopy, which does not require labeling, serves as a powerful tool for visualizing dynamic chromatin nano-arrangements in live cells. This advancement holds promise for studying chromatin remodeling in various crucial cellular processes, such as stem cell differentiation, mechanotransduction, and DNA repair.

Investigating the Free Volumes as Nanospaces in Human Stratum Corneum Lipid Bilayers Using Positron Annihilation Lifetime Spectroscopy (PALS).

This work is the first one that provides not only evidence for the existence of free volumes in the human stratum corneum but also focuses on comparing these experimental data, obtained through the unique positron annihilation lifetime spectroscopy (PALS) method, with theoretical values published in earlier works. The mean free volume of 0.269 nm was slightly lower than the theoretical value of 0.4 nm. The lifetime τ3 (1.83 ns with a coefficient of variation CV of 3.21%) is dependent on the size of open sites in the skin. This information was used to calculate the free volume radius R (0.269 nm with CV 2.14%), free volume size Vf (0.081 nm3 with CV 4.69%), and the intensity I3 (9.01% with CV 10.94%) to estimate the relative fractional free volume fv (1.32 a.u. with CV 13.68%) in human skin ex vivo. The relation between the lifetime of o-Ps (τ3) and the radius of free volume (R) was formulated using the Tao-Eldrup model, which assumes spherical voids and applies to sites with radii smaller than 1 nm. The results indicate that PALS is a powerful tool for confirming the existence of free volumes and determining their size. The studies also focused on describing the probable locations of these nanospaces in SC lipid bilayers. According to the theory, these play an essential role in dynamic processes in biological systems, including the diffusion of low-molecular-weight hydrophobic and moderately hydrophilic molecules. The mechanism of their formation has been determined by the molecular dynamics of the lipid chains.

High sensitive detection of Cd, Hg, Pb and Cr in rice based on LA-MPT-OES with optimized excitation regions by two-dimensional characterization of plasma plume.

Direct, rapid and highly sensitive detection of heavy metals in rice is essential to ensure food safety. In this research, a combination of laser ablation and microwave plasma torch optical emission spectrometry (LA-MPT-OES) was proposed. Based on the optimal observation positions, a high sensitivity and direct determination of Cd, Hg, Pb and Cr in rice were realized. The limits of detection (LOD) were 0.97, 0.12, 0.61 and 0.15 µg/kg, respectively, which were reduced by one order of magnitude compared to the optimal observation height. In addition, the LOD was reduced by one to two orders of magnitude compared with the techniques that require sample pre-treatment. Moreover, the results of the Certified Reference Materials and real samples were in agreement with the reference values with a relative error in the range of 0.28% âˆ¼ 14.16%. The results demonstrated that LA-MPT-OES could be a promising tool to detect heavy metals in rice.

Prediction of in-vitro dissolution and tablet hardness from optical porosity measurements.

Advanced manufacturing technologies such as continuous processing require fast information on the quality of intermediates and products. Process analytical technologies (PAT) to monitor many critical quality attributes (CQAs) have been developed and successfully implemented in pharmaceutical industry. However, there are some CQAs, which still have to be measured off-line with significant effort due to the lack of suitable PAT sensors. Two prominent examples are the in-vitro dissolution and the tablet hardness. Both are obtained via destructive measurement, and the dissolution is tedious and time-consuming to determine. In this study, these two CQAs were predicted via correlation with the optical porosity of tablets. The optical porosity was measured via a novel combination of gas in scattering media absorption spectroscopy (GASMAS) and photon time of flight spectroscopy (pTOFS) with a SpectraPore instrument. The approach was tested in a continuous tableting line and showed promising results in predicting the amount of drug released after specific dissolution times as well as the tablet hardness. This indicates that the measurement of optical porosity can support control strategies within the real-time release testing (RTRT) concept.

Intraoperative characterization of cardiac tissue: the potential of light scattering spectroscopy.

Significance: Damage to the cardiac conduction system remains one of the most significant risks associated with surgical interventions to correct congenital heart disease. This work demonstrates how light-scattering spectroscopy (LSS) can be used to non-destructively characterize cardiac tissue regions. Aim: To present an approach for associating tissue composition information with location-specific LSS data and further evaluate an LSS and machine learning system as a method for non-destructive tissue characterization. Approach: A custom LSS probe was used to gather spectral data from locations across 14 excised human pediatric nodal tissue samples (8 sinus nodes, 6 atrioventricular nodes). The LSS spectra were used to train linear and neural-network-based regressor models to predict tissue composition characteristics derived from the 3D models. Results: Nodal tissue region nuclear densities were reported. A linear model trained to regress nuclear density from spectra achieved a prediction r-squared of 0.64 and a concordance correlation coefficient of 0.78. Conclusions: These methods build on previous studies suggesting that LSS measurements combined with machine learning signal processing can provide clinically relevant cardiac tissue composition.

Theory of 2D electronic spectroscopy of water soluble chlorophyll-binding protein (WSCP): Signatures of Chl b derivate.

We investigate how electronic excitations and subsequent dissipative dynamics in the water soluble chlorophyll-binding protein (WSCP) are connected to features in two-dimensional (2D) electronic spectra, thereby comparing results from our theoretical approach with experimental data from the literature. Our calculations rely on third-order response functions, which we derived from a second-order cumulant expansion of the dissipative dynamics involving the partial ordering prescription, assuming a fast vibrational relaxation in the potential energy surfaces of excitons. Depending on whether the WSCP complex containing a tetrameric arrangement of pigments composed of two dimers with weak excitonic coupling between them binds the chlorophyll variant Chl a or Chl b, the resulting linear absorption and circular dichroism spectra and particularly the 2D spectra exhibit substantial differences in line shapes. These differences between Chl a WSCP and Chl b WSCP cannot be explained by the slightly modified excitonic couplings within the two variants. In the case of Chl a WSCP, the assumption of equivalent dimer subunits facilitates a reproduction of substantial features from the experiment by the calculations. In contrast, for Chl b WSCP, we have to assume that the sample, in addition to Chl b dimers, contains a small but distinct fraction of chemically modified Chl b pigments. The existence of such Chl b derivates has been proposed by Pieper et al. [J. Phys. Chem. B 115, 4042 (2011)] based on low-temperature absorption and hole-burning spectroscopy. Here, we provide independent evidence.

Elucidating the structural and conformational preferences of bioactive chromone and its monohydrate through advanced rotational spectroscopy.

Chromones are a class of naturally occurring compounds, renowned for their diverse biological activities with significant relevance in medicine and biochemistry. This study marks the first analysis of rotational spectra of both the chromone monomer and its monohydrate through Fourier transform microwave spectroscopy. The observation of nine mono-substituted 13C isotopologues facilitated a semi-experimental determination of the equilibrium structure of the chromone monomer. In the case of chromone monohydrate, two distinct isomers were identified, each characterized by a combination of O-H⋯O and C-H⋯O hydrogen bonds involving the chromone's carbonyl group. This study further delved into intermolecular non-covalent interactions, employing different theoretical approaches. The relative population ratio of the two identified isomers was estimated to be about 2:1 within the supersonic jet.

Imaging the elemental distribution within human malignant melanomas using Laser-Induced Breakdown Spectroscopy.

The diagnosis of malignant melanoma, often an inconspicuous but highly aggressive tumor, is most commonly done by histological examination, while additional diagnostic methods on the level of elements and molecules are constantly being developed. Several studies confirmed differences in the chemical composition of healthy and tumor tissue. Our study presents the potential of the LIBS (Laser-Induced-Breakdown Spectroscopy) technique as a diagnostic tool in malignant melanoma (MM) based on the quantitative changes in elemental composition in cancerous tissue. Our patient group included 17 samples of various types of malignant melanoma and one sample of healthy skin tissue as a control. To achieve a clear perception of results, we have selected two biogenic elements (calcium and magnesium), which showed a dissimilar distribution in cancerous tissue from its healthy surroundings. Moreover, we observed indications of different concentrations of these elements in different subtypes of malignant melanoma, a hypothesis that requires confirmation in a more extensive sample set. The information provided by the LIBS Imaging method could potentially be helpful not only in the diagnostics of tumor tissue but also be beneficial in broadening the knowledge about the tumor itself.

Association between atherosclerotic cardiovascular disease score and skin carotenoid levels estimated via refraction spectroscopy in the Japanese population: a cross-sectional study.

Carotenoids play a role in preventing and impeding the progression of atherosclerotic cardiovascular diseases (ASCVDs) through their anti-oxidative effects. This study evaluated associations between ASCVD risk and skin carotenoid (SC) levels, reflecting dietary carotenoid intake. Participants' ASCVD risk was assessed using the Hisayama ASCVD risk prediction model, and SC levels were measured through a reflection spectroscope (Veggie Meter). The associations between high ASCVD risk and SC levels were analyzed using logistic regression analysis and a restricted cubic spline (RCS) model. A total of 1130 men and women (mean age: 56 years) from participants who underwent a health examination in Seirei Center for Health Promotion and Prevention Medicine in 2019 and 2022 were analyzed. Of these, 4.6% had moderate or high ASCVD risk. Mean SC values were 236, 315, 376, 447, and 606 in quintile Q1 to Q5, respectively. The adjusted odds ratios (95% confidence intervals) of SC quintile for moderate- or high-risk ASCVD was 0.24 (0.12-0.51) in Q5 (495 ≤), 0.42 (0.23-0.77) in Q4, 0.50 (0.29-0.88) in Q3, and 0.68 (0.41-1.12) in Q2 compared to Q1 (< 281). High SC values continuously showed non-linear inverse association with moderate- or high-risk for ASCVD in Japanese adults. Non-invasive SC measurements may be a good indicator for recommending carotenoids to prevent cardiovascular disease.

Cotton seed cultivar identification based on the fusion of spectral and textural features.

The mixing of cotton seeds of different cultivars and qualities can lead to differences in growth conditions and make field management difficult. In particular, except for yield loss, it can also lead to inconsistent cotton quality and poor textile product quality, causing huge economic losses to farmers and the cotton processing industry. However, traditional cultivar identification methods for cotton seeds are time-consuming, labor-intensive, and cumbersome, which cannot meet the needs of modern agriculture and modern cotton processing industry. Therefore, there is an urgent need for a fast, accurate, and non-destructive method for identifying cotton seed cultivars. In this study, hyperspectral images (397.32 nm-1003.58 nm) of five cotton cultivars, namely Jinke 20, Jinke 21, Xinluzao 64, Xinluzao 74, and Zhongmiansuo 5, were captured using a Specim IQ camera, and then the average spectral information of seeds of each cultivar was used for spectral analysis, aiming to estab-lish a cotton seed cultivar identification model. Due to the presence of many obvious noises in the < 400 nm and > 1000 nm regions of the collected spectral data, spectra from 400 nm to 1000 nm were selected as the representative spectra of the seed samples. Then, various denoising techniques, including Savitzky-Golay (SG), Standard Normal Variate (SNV), and First Derivative (FD), were applied individually and in combination to improve the quality of the spectra. Additionally, a successive projections algorithm (SPA) was employed for spectral feature selection. Based on the full-band spectra, a Partial Least Squares-Discriminant Analysis (PLS-DA) model was established. Furthermore, spectral features and textural features were fused to create Random Forest (RF), Convolutional Neural Network (CNN), and Extreme Learning Machine (ELM) identification models. The results showed that: (1) The SNV-FD preprocessing method showed the optimal denoising performance. (2) SPA highlighted the near-infrared region (800-1000 nm), red region (620-700 nm), and blue-green region (420-570 nm) for identifying cotton cultivar. (3) The fusion of spectral features and textural features did not consistently improve the accuracy of all modeling strategies, suggesting the need for further research on appropriate modeling strategies. (4) The ELM model had the highest cotton cultivar identification accuracy, with an accuracy of 100% for the training set and 98.89% for the test set. In conclusion, this study successfully developed a highly accurate cotton seed cultivar identification model (ELM model). This study provides a new method for the rapid and non-destructive identification of cotton seed cultivars, which will help ensure the cultivar consistency of seeds used in cotton planting, and improve the overall quality and yield of cotton.

Development of an atmospheric pressure plasma-based OES device for in-situ mapping of Cd and related elements in plants.

We have developed an innovative optical emission spectrometry imaging device integrating a diode laser for sample introduction and an atmospheric pressure plasma based on dielectric barrier discharge for atomization and excitation. By optimizing the device parameters and ensuring appropriate leaf moisture, we achieved effective imaging with a lateral resolution as low as 50 µm. This device allows for tracking the accumulation of Cd and related species such as K, Zn, and O2+∙, in plant leaves exposed to different Cd levels and culture times. The results obtained are comparable to established in-lab imaging and quantitative methods. With its features of compact construction, minimal sample preparation, ease of operation, and low limit of detection (0.04 µg/g for Cd), this novel methodology shows promise as an in-situ elemental imaging tool for interdisciplinary applications.

Reassociation of Skeletal Remains Using Laser-Induced Breakdown Spectroscopy.

A major challenge in forensic anthropology and bioarcheology is the development of fast and effective methods for sorting commingled remains. This study assesses how portable laser-induced breakdown spectroscopy (LIBS) can be used to group skeletal remains based on their elemental profiles. LIBS spectra were acquired from the remains of 45 modern skeletons, with a total data set of 8388 profiles from 1284 bones. Spectral feature selection was conducted to reduce the spectral profiles to the peaks exhibiting the highest variation among individuals. Emission lines corresponding to 9 elements (Ca, P, C, K, Mg, Na, Al, Ba, and Sr) were found important for classification. Linear discriminant analysis (LDA) was concurrently used to classify each spectral profile. From the 45 individuals, each LIBS spectrum was successfully sorted to its corresponding skeleton with an average accuracy of 87%. These findings indicate that variation exists among the LIBS profiles of individuals' skeletal remains, highlighting the potential for portable LIBS technology to aid in the sorting of commingled remains.