Spectral Changes Research Articles

Repetitive active and passive cognitive stimulations induce EEG changes in patients with Rett syndrome.

Despite being considered a rare disease, Rett syndrome is a leading cause of profound cognitive impairment in females. This study explores game-based cognitive stimulation to enhance attention during learning tasks, offering an alternative treatment perspective. Fifteen diagnosed Rett syndrome girls participated in four 24-minute sessions, including a 5-minute initial resting state recording. Primary indicators for analysis included relative power and spectral entropy. Significant findings indicated variations among conditions (resting state, active task, passive task) in response to stimulation. Notably, over four days, evolution occurred, characterized by decreasing delta power and increasing theta and beta power. Topographic maps confirmed these shifts, highlighting affected brain areas. Linear regression emphasized the most significant impact on the first day, with subsequent shifts towards higher frequencies, particularly during the resting state. By the fourth day, resting-state patterns resembled those during cognitive activities. Findings suggest cognitive stimulation induces substantial EEG spectral changes, potentially linked to cognitive enhancements in Rett syndrome. The shift towards higher frequency bands and increased spectral entropy align with enhanced brain activation during cognitive sessions, underscoring the potential of cognitive stimulation therapies and calling for further research to optimize abilities in individuals with Rett syndrome. Game-based cognitive stimulation induces substantial EEG changes in individuals with Rett syndrome, enhancing cognitive functions, notably attention during learning. This study conducts a distinctive examination, assessing the habituation paradigm through the combination of game-based cognitive stimulation and learning, providing valuable insights into enhancing attention in Rett syndrome. Impacting understanding of cognitive processes in Rett syndrome, this research reveals significant EEG variations during tasks, emphasizing the potential of cognitive stimulation for attention enhancement and the need for further research in tailored interventions.

A novel dual channel six-membered spirorhodamine for Cu2+ and ClO- depending on solvent and application in real samples and bioimaging

To reveal the solvent dependence of six-membered rhodamine spirocycles (SMRS), a new probe SM-RB has been synthesized and investigated the spectral properties in different solvents upon the addition of various metal ions and anions. SM-RB exhibited high selectivity for Cu2+ in CH3CN/HEPES and ClO- in C2H5OH/HEPES solutions, respectively. The spectral changes of SM-RB in the presence of ClO- in C2H5OH/HEPES solution were much less than that of Cu2+ in CH3CN/HEPES. The detection limit of Cu2+ was as low as 36 nM (fl) in CH3CN/HEPES. The kinetic equilibration time (8 s) indicated that the two solvent systems did not delay the spectral response speed to Cu2+ and ClO-. Solvent systems influenced the pKa value of SM-RB in CH3CN/HEPES and C2H5OH/HEPES. The pKa value of SM-RB was 4.34 (±0.7) (Abs) and 4.75 (±0.14) (Fl) in CH3CN/H2O, but can’t be exactly calculated by pH titration in C2H5OH/H2O. The reversibility and Job plot of SM-RB were investigated to propose the response mechanism of SM-RB with Cu2+ and ClO- in the two solvent systems. Finally, SM-RB not only can be used for the quantitative detection of copper ions in grape peel, but also can real-time monitor the fluctuation of Cu2+ in lysosomal pools.

Mechanistic Insights into UV Spectral Changes of Pyruvic Acid and Pyruvate Part 1: Interaction with Water Molecules

We investigate how the UV spectra of pyruvic acid (PA) and pyruvate are impacted by interactions with water molecules. In particular, we would like to understand the mechanistic origin of the blue shift in the n →− π∗ transition. Pyruvic acid is the simplest α-keto organic acid and is common in the environment. We use density functional theory to optimize geometries to determine excitation energies and find that the excitation energies of the two main pyruvic acid conformers and pyruvate blue shift when interacting with 1 to 4 water molecules, both in vacuo and in a solvent. The excitation wavelength is blue-shifted by 0.9-9.2 nm when adding water molecules to the lowest energy conformer of PA. Calculations of the UV spectra of pyruvic acid (PA) and pyruvate are crucial for understanding the impact of the interactions with water molecules.

Comparisons of aerosol types and optical characters over Shouxian Area China observed from ground- and space-based systems.

This study evaluates the performance of moderate-resolution Imaging spectroradiometer (MODIS) in aerosol optical depth(AOD) and Ångström exponent(AE) retrievals under high aerosol loading conditions across various aerosol types, utilizing ground-based and space-borne aerosol measurements in Shouxian, China. The intercomparison reveals cloud-aerosol LiDAR with orthogonal polarization's (CALIOP) efficacy in detecting significant aerosol layers and the refinement of sunphotometer-based aerosol type classification through CALIPSO, achieving approximately 80% accuracy. Analysis of 2016-2017 data indicates substantial aerosol presence in Shouxian, with monthly mean AODs ranging from 0.35 to 0.72 at 550 nm, significantly above the global average. The predominant aerosol types were mixed-type (54.8%), desert dust (21.2%), urban/industrial(15.5%), biomass-burning aerosol (6.4%), and continental aerosol (12.1%), with frequent observations of elevated long-range transported aerosol layers. MODIS AOD retrievals generally align with sunphotometer measurements but exhibit higher biases, especially with increasing AOD magnitudes. However, there is a notable difference between MODIS and sunphotometer aerosol AE measurements, with MODIS accurately assessing BBA but showing varied performance across other aerosol types. The combination of AOD and AE of the DD aerosol type is the most accurate. Further analysis showed that MODIS AOD biases and AE biases are negatively correlated, these negative bias correlations show strong aerosol type sensitivities. Monthly analysis of MODIS and sunphotometer comparisons highlights varying performance, particularly during normalized difference vegetation index (NDVI) transitions, suggesting that local vegetation cycles and associated surface spectral reflectance changes significantly impact MODIS aerosol retrieval accuracy under high aerosol loading conditions.

Spectral changes in electroencephalography linked to neuroactive medications: A computational pipeline for data mining and analysis

Background and objectivesThe increasing amount of open-access medical data provides new opportunities to gain clinically relevant information without recruiting new patients. We developed an open-source computational pipeline, that utilizes the publicly available electroencephalographic (EEG) data of the Temple University Hospital to identify EEG profiles associated with the usage of neuroactive medications. It facilitates access to the data and ensures consistency in data processing and analysis, thus reducing the risk of errors and creating comparable and reproducible results. Using this pipeline, we analyze the influence of common neuroactive medications on brain activity. MethodsThe pipeline is constructed using easily controlled modules. The user defines the medications of interest and comparison groups. The data is downloaded and preprocessed, spectral features are extracted, and statistical group comparison with visualization through a topographic EEG map is performed. The pipeline is adjustable to answer a variety of research questions. Here, the effects of carbamazepine and risperidone were statistically compared with control data and with other medications from the same classes (anticonvulsants and antipsychotics). ResultsThe comparison between carbamazepine and the control group showed an increase in absolute and relative power for delta and theta, and a decrease in relative power for alpha, beta, and gamma. Compared to antiseizure medications, carbamazepine showed an increase in alpha and theta for absolute powers, and for relative powers an increase in alpha and theta, and a decrease in gamma and delta. Risperidone compared with the control group showed a decrease in absolute and relative power for alpha and beta and an increase in theta for relative power. Compared to antipsychotic medications, risperidone showed a decrease in delta for absolute powers. These results show good agreement with state-of-the-art research. The database allows to create large groups for many different medications. Additionally, it provides a collection of records labeled as “normal” after expert assessment, which is convenient for the creation of control groups. ConclusionsThe pipeline allows fast testing of different hypotheses regarding links between medications and EEG spectrum through ecological usage of readily available data. It can be utilized to make informed decisions about the design of new clinical studies.

Detection of Coral Reef Bleaching by Multitemporal Sentinel-2 Data Using the PU-Bagging Algorithm: A Feasibility Study at Lizard Island

Coral reef bleaching events have become more frequent all over the world and pose a serious threat to coral reef ecosystems. Therefore, there is an urgent need for better detection of coral reef bleaching in a time- and cost-saving manner. In recent years, remote sensing technology has often been utilized and gained recognition for coral reef bleaching detection. However, bleaching corals in the water always have weak spectral change signals, causing difficulties in using remote sensing data. Additionally, uneven change samples make it challenging to adequately capture the details of coral reef bleaching detection and produce thematic maps. To resolve these problems, a novel method named coral reef bleaching detection by positive-unlabeled bagging (CBD-PUB) is proposed in this paper. To test the capacity of the method, a series of multi-temporal Sentinel-2 remote sensing images are utilized, and Lizard Island in Australia is taken as a case study area. The pseudo-invariant feature atmospheric correction (PIF) algorithm is adopted to improve coral reef bleaching spectral signals. After that, CBD-PUB is employed to effectively explore coral reef bleaching variation and its corresponding influence relations. The experimental results show that the overall accuracy of bleaching detection by the proposed algorithm reaches 92.1% and outperforms the traditional method. It fully demonstrates the feasibility of the model for the field of coral reef bleaching detection and provides assistance in the monitoring and protection of coral environments.

Human Cervical Epidural Spinal Electrogram Topographically Maps Distinct Volitional Movements.

Little is known about the electrophysiologic activity of the intact human spinal cord during volitional movement. We analyzed epidural spinal recordings from a total of five human subjects of both sexes during a variety of upper extremity movements and found that these spinal epidural electrograms contain spectral information distinguishing periods of movement, rest, and sensation. Cervical epidural electrograms also contained spectral changes time-locked with movement. We found that these changes were primarily associated with increased power in the theta (4-8 Hz) band and feature increased theta phase to gamma amplitude coupling, and this increase in theta power can be used to topographically map distinct upper extremity movements onto the cervical spinal cord in accordance with established myotome maps of the upper extremity. Our findings have implications for the development of neurostimulation protocols and devices focused on motor rehabilitation for the upper extremity, and the approach presented here may facilitate spatiotemporal mapping of naturalistic movements.

Estimating forest aboveground biomass in tropical forests with Landsat time-series data and recurrent neural network

ABSTRACT The insensitivity and saturation of sensor signals significantly limit the application of Landsat data on estimating biomass in tropical forests with a high level of biomass. The previous studies with single-date Landsat data have lower accuracies in tropical forests compared to boreal and temperate forests. Landsat time-series data provide a promising opportunity to improve the accuracy by enhancing the relationship between Landsat spectral reflectance and forest aboveground biomass with disturbance and recovery dynamics. Compared to the single-date image, Landsat time-series data can capture abrupt spectral changes (e.g. harvesting and fire) and show the regrowth process in forested pixels. However, very limited studies take advantage of Landsat time-series data to estimate aboveground biomass in tropical forests. Recurrent neural networks (RNNs) are powerful deep learning techniques to capture time dependencies in sequence data. However, the application of RNNs in estimating forest biomass has not been explored yet. Therefore, we integrate the long short-term memory network (LSTM) and the fully connected neuron network (FNN) to establish an RNN-FNN model for estimating forest biomass with Landsat time-series imagery and airborne LiDAR data. We compared the proposed model with the commonly used Random Forest model and linear regression model which are implemented with single-date data. The results show that the RNN-FNN model can deal with Landsat time-series sequence data to enhance the relationship between Landsat spectral reflectance and forest aboveground biomass. The proposed model achieves the R2 of 0.63 and RMSE of 25.5 Mg/ha, which significantly outperformed the Random Forest model and linear regression model with Landsat single-date data. This study demonstrates the value of RNN and Landsat time-series imagery in estimating forest biomass for tropical forests.

Evidence for a Cyclotron Absorption Line and Spectral Transition in EXO 2030+375 during the 2021 Giant Outburst

Based on Insight-HXMT observations of EXO 2030+375 during its 2021 giant outburst, we report the analysis of pulse variations and the broadband X-ray spectrum, and find the presence of a potential cyclotron resonant scattering feature (CRSF) with the fundamental line at ∼47 keV from both average spectra and phase-resolved spectroscopy. During the outburst, the source reached an X-ray luminosity of ∼1038 erg s−1 from 2 to 105 keV at a distance of 7.1 kpc. The X-ray pulsar at the spin period of 41.27 ± 0.61 s exhibits complex timing and spectral variations with both energy and luminosity during the outburst. The shapes of the pulse profiles show the single main peak above ∼20 keV, while appearing to exhibit multipeak patterns in low-energy bands, and the transition of the 10–20 keV pulse profiles from multipeak to single peak is observed at ∼0.8 × 1038 erg s−1, which suggests the evolution from the subcritical luminosity (pencil-beam dominated) to the supercritical luminosity (fan-beam dominated) regime. A dip structure before the energy of the CRSFs is found in the pulse fraction–energy relation of EXO 2030+375 near the peak luminosity. A detailed analysis of spectral parameters showed that the power-law photon index exhibits three distinct trends as luminosity increases, and these spectral changes also signify a spectral transition from subcritical to supercritical regimes. The critical luminosity infers a magnetic field of ∼(4.8−6.0) × 1012 G, which supports the presence of the cyclotron line at ∼47 keV. A Comptonization model applied for the broad X-ray spectra during the outburst also suggests the surface magnetic field ranging from ∼(5−9) × 1012 G.

Advancing Hydrogen Sensing for Sustainable Aviation: A Metal Hydride Coated TFBG Optical Fibre Hydrogen Sensor

The aviation industry is undergoing a significant shift toward sustainability, with hydrogen emerging as a promising green fuel to reduce carbon emissions due to its high gravimetric energy density and clean combustion exhaust compared to traditional aviation fuels. However, realizing hydrogen's aviation potential requires advanced sensors to ensure safety and efficiency in challenging environments, particularly for monitoring hydrogen near high-temperature engines and cryogenic storage tanks. Fibre optic sensors offer an exceptional advantage in these demanding conditions due to their capacity to operate in harsh environments, their small size, immunity to electromagnetic interference, spark-free operation, and remote sensing capabilities. Metal hydrides are prominent sensing materials studied for hydrogen sensing, especially palladium (Pd). Nonetheless, existing literature pertaining to Pd-coated fiber optic sensors for hydrogen detection has brought to light concerns regarding response hysteresis, stability, and linearity of Pd hydrogen sensors, calling for innovative solutions. In response to these challenges, our research introduces an innovative fibre optic hydrogen sensor, introducing tantalum (Ta) based metal hydrides as the sensing material. The sensor's construction involved the deposition of a nanometer-thick Ta thin film onto the surface of a tilted fibre Bragg grating (TFBG) using a magnetron sputtering technique. The sensing mechanism relies on the modulation of optical constants of the Ta thin film in response to even minute hydrogen concentrations, culminating in spectral changes in the transmission spectrum of the TFBG. In this proof of concept work, changes in both amplitude and the centre wavelength of cladding resonances of the TFBG transmission spectrum were observed in the hydrogen concentration range from 0.01% to 4% at room temperature. These initial findings underscore the substantial potential of our approach in developing highly sensitive and robust fibre-optic hydrogen sensors tailored specifically for hydrogen-powered aviation.

Controller-in-the-Loop Validation for Virtual Impedance-based Fault Detection Method in Grid-Connected Inverters

Abstract The high penetration of distributed energy resources and grid-connected inverters creates operation and protection challenges in distribution networks which have led to a need for advanced fault protection methods. Therefore, a virtual impedance-based short-circuit fault detection algorithm is proposed in this paper for grid-connected inverters in distribution networks which determines a short-circuit fault through measurement of the spectral change in system impedance at each harmonic frequency. Moreover, a controller-in-the-loop platform is also developed in this paper for verifying the proposed detection algorithm without jeopardizing the operation of distribution networks. By using the developed platform, real-time simulation on both grid-connected inverter and distribution network is carried out. The results have proven the effectiveness of the proposed method and theoretical analysis.

Harnessing Cooperative Multivalency in Thioguanine for SERS Differentiation of Polyfunctional Analytes Differing by Single Functional Group

Small‐molecule receptors are increasingly employed to probe various functional groups for (bio)chemical analysis. However, differentiation of polyfunctional analogs sharing multiple functional groups remains challenging for conventional mono‐ and bidentate receptors because their insufficient number of binding sites limits interactions with the least reactive yet property‐determining functional group. Herein, we introduce 6‐thioguanine (TG) as a supramolecular receptor for unique tridentate receptor‐analyte complexation,achieving ≥ 95% identification accuracy among 16 polyfunctional analogs across three scenarios: glycerol derivatives, disubstituted propanes, and vicinal diols. Crucially, we demonstrate distinct spectral changes induced by the tridentate interaction between TG’s three anchoring points and all the analyte’s functional groups, even the least reactive ones. Notably, H‐bond networks formed in the TG‐analyte complexes demonstrate additive effect in binding strength originating from good bond linearity, cooperativity, and resonance, thus strengthens complexation events and amplifies the differences in spectral changes induced among analytes. It also enhances spectral consistency by selectively form a sole configuration that is stronger than the respective analyte‐analyte interaction. Finally, we achieve 95.4% accuracy for multiplex identification of a mixture consisting of multiple polyfunctional analogs. We envisage that extension to other multidentate non‐covalent interactions enables the development of interference‐free small molecule‐based sensors for various (bio)chemical analysis applications.

Improved greywater quality after biofiltration with a fibre-biofilter derived from plantain pseudo stem

In this study, we addressed the prevalent issue of untreated greywater discharge into waterbodies in many developing countries, despite the associated public health risks. Our approach involved utilizing fibers extracted from plantain pseudo-stems to enhance the quality of greywater through simple biofiltration setups. Greywater sourced from the GETFund Hostel of the University of Energy and Natural Resources in Sunyani, Ghana, served as the focal point of our investigation. Through the application of this biofilter, we achieved notable reductions in two crucial parameters for assessing greywater quality: biochemical oxygen demand (BOD) and chemical oxygen demand (COD), averaging at 30.4 % and 28.67 %, respectively. Furthermore, we conducted comparative analyses between the efficacy of plantain pseudo-stem fibers and carbonized coconut shell adsorbent, both individually and in composite form as biosorbents. While certain combinations of biofilters led to slight increases in conductivity, pH, and total dissolved solids (TDS) in the treated greywater, these variations were anticipated and attributed to potential organic matter leaching during the biofiltration process. Employing Fourier-transform infrared (FT-IR) spectroscopy, we detected significant spectral changes indicative of successful organic matter removal from the greywater. Specifically, we observed an intensified phenolic hydroxyl (OH) peak at 3300 cm⁻¹, which shifted marginally to 3335 cm⁻¹ post-biofiltration. Additionally, the emergence of a carboxylic hydroxyl stretch at 2850 cm⁻¹ post-biofiltration provided strong evidence supporting the efficacy of our approach in mitigating organic contaminants in greywater.

SEM/Raman spectroscopy of clathrites as analogs of authigenic carbonates in ocean worlds

AbstractThere is evidence from the near‐infrared observations of space missions of the presence of carbonates on the surface of several ocean worlds. However, their genesis remains unresolved. We investigate the hypothesis that these carbonates may be in the form of clathrites assuming that clathrate hydrates are stable phases in the crust and ocean of these ocean worlds. In order to support this, we studied a sample of a potential clathrite from the Hydrate Ridge cold seep (Cascadia Subduction Zone), the carbonate rock fossil of clathrate hydrates, as a terrestrial analogue. We characterised the mineralogy and texture of the sample by using a coupled confocal Raman microscope and scanning electron microscopy instrument with the aim of identifying possible geo‐ and biosignatures, which could be relevant for future missions of exploration to ocean worlds and Mars. Our results show that aragonite is the dominant mineral phase in the clathrite sample, but Mg‐calcite and dolomite were also identified. These three carbonates constitute a pattern related to clathrate hydrate formation and dissociation processes. Dolomite was defined as a biosignature of gas hydrate microbiomes because it was integrated within Mg‐calcite grains precipitated after clathrate hydrate dissociation. Nevertheless, no spectral changes were observed in Raman bands of carbonate minerals that would indicate the influence of clathrate hydrates in their genesis. We also observed that Raman band positions of the associated framboidal pyrites are a characteristic signature of the associated framboid‐like texture because its potential as biosignature may only be attributed by biochemical analysis.

A comprehensive analysis of royal jelly protection against cypermethrin-induced toxicity in the model organism Allium cepa L., employing spectral shift and molecular docking approaches

In this study, the toxicity of the pesticide cypermethrin and the protective properties of royal jelly against this toxicity were investigated using Allium cepa L., a model organism. Toxicity was evaluated using 6 mg/L cypermethrin, while royal jelly (250 mg/L and 500 mg/L) was used in combination with cypermethrin to test the protective effect. To comprehend toxicity and protective impact, growth, genotoxicity, biochemical, comet assay and anatomical parameters were employed. Royal jelly had no harmful effects when applied alone. On the other hand, following exposure to cypermethrin, there was a reduction in weight increase, root elongation, rooting percentage, mitotic index (MI), and chlorophyll a and b. Cypermethrin elevated the frequencies of micronucleus (MN) and chromosomal aberrations (CAs), levels of proline and malondialdehyde (MDA), and the activity rates of the enzymes catalase (CAT) and superoxide dismutase (SOD). A spectral change in the DNA spectrum indicated that the interaction of cypermethrin with DNA was one of the reasons for its genotoxicity, and molecular docking investigations suggested that tubulins, histones, and topoisomerases might also interact with this pesticide. Cypermethrin also triggered some critical meristematic cell damage in the root tissue. At the same time, DNA tail results obtained from the comet assay revealed that cypermethrin caused DNA fragmentation. When royal jelly was applied together with cypermethrin, all negatively affected parameters due to the toxicity of cypermethrin were substantially restored. However, even at the maximum studied dose of 500 mg/L of royal jelly, this restoration did not reach the levels of the control group. Thus, the toxicity of cypermethrin and the protective function of royal jelly against this toxicity in A. cepa, the model organism studied, were determined by using many different approaches. Royal jelly is a reliable, well-known and easily accessible protective functional food candidate against the harmful effects of hazardous substances such as pesticides.

Study on cellular uptake of a hydrophobic near-infrared-absorbing diradical-platinum(II) complex solubilized by albumin using hyperspectral imaging, spectrophotometry, and spectrofluorimetry.

Owing to its biopenetrability and minimal invasiveness, near-infrared (NIR) light in the region between 700-1100nm has attracted attention in cancer diagnosis and therapy. Our group previously reported that the hydrophobic diradical-platinum(II) complex PtL2 is a promising agent for cancer photothermal therapy (L = 3,5-dibromo-1,2-diiminobenzosemiquinonate radical). Because PtL2 does not fluoresce, its intercellular uptake of PtL2 cannot be observed with a fluorescence microscope. In this study, we clarified the uptake and intracellular behavior of PtL2 solubilized by bovine serum albumin (BSA) using hyperspectral imaging enabling spectrophotometric analysis of the image. The spectral changes in the obtained images indicated that the internalization of PtL2 was followed by crystallization of the complex during the long incubation period (> 4h). Additionally, the binding constant Kb = 5.91 × 104M-1 could be estimated upon fluorescence quenching analysis of BSA upon binding of PtL2; Kb is two orders of magnitude smaller than that of albumin-common drugs. Considering the small Kb and low solubility of PtL2 in water, we ultimately proposed the internalization path and fate of PtL2 in the cell: release of PtL2 from BSA near cellular membranes and subsequent cellular uptake via membrane permeation followed by saturation, resulting in crystallization.

Characterization of Near Infrared-Dye Colored Fabrics Using Hyperspectral Imaging.

Near-infrared (NIR) dyes have a unique ability to interact favorably with light in the NIR region, which is particularly interesting where stealth and camouflage are paramount, such as in military uniforms. Characterization of cotton fabric dyed with NIR-absorbing dyes using visible-NIR (Vis-NIR) and short-wave infrared (SWIR) hyperspectral imaging was done. The aim of the study was to discern spectral changes caused by variations in dye concentration and dyeing temperature as these parameters directly influence color- and crocking-fastness of fabrics impacting the camouflage effect. The fabric was dyed at three concentrations (2.5, 5, and 10%) and two dyeing temperatures (55 °C and 85 °C) and principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed on the spectra to discriminate the fabrics based on dye concentrations. The PCA models successfully segregated the fabrics based on the dye concentration and dyeing temperature, while PLS-DA models demonstrated classification accuracies between 75 and 100% in the Vis-NIR range. Spectra in the SWIR region could not be used to detect the differences in the concentrations of the NIR dyes. This finding is promising, as it aligns with the objective of creating NIR-dyed camouflage fabrics that remain indistinguishable under varying dye concentrations. These results open possibilities for further exploration in enhancing the stealth capabilities of textiles in military applications.

Development of a novel sensory material for rapid detection of mercury ions in various water sources: Solution and solid-state analysis

A xanthene propane nitrile-based sensor material was successfully prepared, and an attempt towards the preparation of polymer bead form was made for the sensitive or selective detection of mercury ions (Hg2+) in water. The sensor material in solution as well as in polymeric form showed amazing selectivity over other added metal ions with a naked eye color change, UV visible spectral and fluorescence spectral change, and a rapid and excellent color change from colorless to purple. The 1H NMR study exposed the probable binding site of the probe with the added mercury ion. In this study, the imine nitrogen and the C = O interact with the mercury ion, resulting in the ring opening of lactam with a vivid color change. The EDTA test was done to verify the reversible behavior of the probe and confirmed its reversibility by UV–visible and fluorescence spectral studies. The polymer bead made using this probe can be used as a tool for monitoring mercury ions in real time in different sources of water samples. The sensor molecule itself senses the mercury ion in its solid state by simple grinding and changes its color from pale yellow to deep purple. The sensor color change response is very rapid towards mercury detection, which is confirmed by the prepared test strip.

Network Hyperexcitability in Early-Stage Alzheimer's Disease: Evaluation of Functional Connectivity Biomarkers in a Computational Disease Model.

There is increasing evidence from animal and clinical studies that network hyperexcitability (NH) may be an important pathophysiological process and potential target for treatment in early Alzheimer's disease (AD). Measures of functional connectivity (FC) have been proposed as promising biomarkers for NH, but it is unknown which measure has the highest sensitivity for early-stage changes in the excitation/inhibition balance. We aim to test the performance of different FC measures in detecting NH at the earliest stage using a computational approach. We use a whole brain computational model of activity dependent degeneration to simulate progressive AD pathology and NH. We investigate if and at what stage four measures of FC (amplitude envelope correlation corrected [AECc], phase lag index [PLI], joint permutation entropy [JPE] and a new measure: phase lag time [PLT]) can detect early-stage AD pathophysiology. The activity dependent degeneration model replicates spectral changes in line with clinical data and demonstrates increasing NH. Compared to relative theta power as a gold standard the AECc and PLI are shown to be less sensitive in detecting early-stage NH and AD-related neurophysiological abnormalities, while the JPE and the PLT show more sensitivity with excellent test characteristics. Novel FC measures, which are better in detecting rapid fluctuations in neural activity and connectivity, may be superior to well-known measures such as the AECc and PLI in detecting early phase neurophysiological abnormalities and in particular NH in AD. These markers could improve early diagnosis and treatment target identification.

Real-time and operando observation of intermediates on TiO2 photoelectrocatalysis by soft X-ray absorption spectroscopy

The oxygen evolution reaction (OER) on the TiO2 surface at the solid–liquid interface was observed in real-time and operando using fluorescence-yield X-ray absorption spectroscopy (XAS) in the soft X-ray region. The OER was observed during a potential sweep with UV light on or off, focusing on the oxygen K-edge XAS. Although conventional XAS measurements require long measurement times, the spectra during the reaction were obtained every 3 s in the present experiment via wavelength-dispersive XAS technique. An increase in the X-ray absorption intensity at approximately 533.8 eV was observed during the potential sweep only with UV light on. The observed spectral change is discussed in relation to the reaction mechanism of the OER. The present technique can be applied to a wide range of analyses of (photo-) electrocatalysis and electrochemical reactions at solid–liquid interfaces to observe their products and intermediates during the reaction.