Spectroscopy Signals Research Articles

Spatio-temporal scale information fusion of Functional Near-Infrared Spectroscopy signal for depression detection

Depression, a prevalent and debilitating mental health disorder, necessitates early detection to enable effective intervention. Functional Near-Infrared Spectroscopy (fNIRS) has proven to be a promising technique for studying depressive symptoms due to its affordability, portability, high spatial resolution and non-invasiveness. However, existing fNIRS-based depression detection approaches often overlook signal intrinsic properties and intrinsic correlations among different feature types, as well as local spatial geometric structures of data. To overcome these limitations, we suggest a spatio-temporal scale information fusion framework that involves supervised local low-rank correlation (IFLRC) to detect depression. IFLRC incorporates a low-rank constraint, a sparse ℓ2,1-norm term, multiple Laplacian regularizations, and a sparse penalty projection matrix to capture global spatial functional information, handle errors to enhance robustness to noise, preserve local spatial geometric structures, exploit correlations among multiple information sets, and enhance discriminative ability. An iterative algorithm, based on the alternating direction method of multipliers (ADMM), has been developed to solve the suggested objective function. The experimental findings validate the efficacy of IFLRC, yielding favorable detection rates of 95.8%, 87.3%, and 97.2% in response to positive, neutral, and negative emotional stimuli, respectively. These findings exceed existing methods, demonstrating the potential of fNIRS and the effectiveness of IFLRC for detecting depression. IFLRC presents notable advancements in feature extraction and fusion techniques for depression detection. Its capacity to capture spatio-temporal scale information, leverage intrinsic correlations, and preserve local geometric structures translates into improved performance. This framework holds promise for early detection and intervention in depressive disorders, offering valuable insights for clinical applications.

Differences in peripheral microcirculatory blood flow regulation in chronic kidney disease based on wavelet analysis of resting near-infrared spectroscopy

Vascular impairment is closely related to increased mortality in chronic kidney disease (CKD). The objective of this study was to assess impairments in the regulation of peripheral microvascular perfusion in patients with CKD based on time-frequency spectral analysis of resting near-infrared spectroscopy (NIRS) signals. Total hemoglobin (tHb) concentration and tissue saturation index (TSI) signals were collected using NIRS for a continuous 5 mins at 10 Hz from the forearm of 55 participants (34 CKD including 5 with end-stage renal disease, and 21 age-matched control). Continuous wavelet transform-based spectral analysis was used to quantify the spectral amplitude within five pre-defined frequency intervals (I, 0.0095–0.021 Hz; II, 0.021–0.052 Hz; III, 0.052–0.145 Hz; IV, 0.145–0.6 Hz and V, 0.6–2.0 Hz), representing endothelial, neurogenic, myogenic, respiratory and heartbeat activity, respectively. CKD patients showed lower tHb average spectral amplitude within the neurogenic frequency interval compared with controls (p = 0.014), consistent with an increased sympathetic outflow observed in CKD. CKD patients also showed lower TSI average spectral amplitude within the endothelial frequency interval compared with controls (p = 0.046), consistent with a reduced endothelial function in CKD. These findings demonstrate the potential of wavelet analysis of NIRS to provide complementary information on peripheral microvascular regulation in CKD.

Multimodal Assessment of Cognitive Workload Using Neural, Subjective and Behavioural Measures in Smart Factory Settings.

Collaborative robots (cobots) have largely replaced conventional industrial robots in today's workplaces, particularly in manufacturing setups, due to their improved performance and intelligent design. In the framework of Industry 5.0, humans are working alongside cobots to accomplish the required level of automation. However, human-robot interaction has brought up concerns regarding human factors (HF) and ergonomics. A human worker may experience cognitive stress as a result of cobots' irresponsive nature in unpredictably occurring situations, which adversely affects productivity. Therefore, there is a necessity to measure stress to enhance a human worker's performance in a human-robot collaborative environment. In this study, factory workers' mental workload was assessed using physiological, behavioural, and subjective measures. Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) signals were collected to acquire brain signals and track hemodynamic activity, respectively. The effect of task complexity, cobot movement speed, and cobot payload capacity on the mental stress of a human worker were observed for a task designed in the context of a smart factory. Task complexity and cobot speed proved to be more impactful. As physiological measures are unbiased and more authentic means to estimate stress, eventually they may replace the other conventional measures if they prove to correlate with the results of traditional ones. Here, regression and artificial neural networks (ANN) were utilised to determine the correlation between physiological data and subjective and behavioural measures. Regression performed better for most of the targets and the best correlation (rsq-adj = 0.654146) was achieved for predicting missed beeps, a behavioural measure, using a combination of multiple EEG and fNIRS predictors. The k-nearest neighbours (KNN) algorithm was used to evaluate the accuracy of correlation between traditional measures and physiological variables, with the highest accuracy of 77.8% achieved for missed beeps as the target. Results show that physiological measures can be more insightful and have the tendency to replace other biased parameters.

On the design of low phase noise and flat spectrum optical parametric frequency comb

Optical frequency combs (OFCs) have become increasingly pervasive in recent years, with their advantageous frequency coherence properties enabling significant developments in numerous fields, such as optical communications, spectroscopy, and microwave signal processing. Recent interest in OFC development emphasizes minimizing and mitigating phase noise of individual comb lines for high-quality signal generation, processing, and detection. Cavity-less electro-optic combs and parametric combs are attractive sources for these applications in that they permit flat spectra, tunable tone spacing, and robustness to temperature variations. Although previous research has demonstrated broadband parametric OFC generation, the scaling of the phase noise has not been systematically investigated. Here, we demonstrate a 25 GHz-spacing cavity-less parametric OFC generator and investigate the interaction between electronic and optical noise sources that affect its phase noise and linewidth. In addition, we study the optimal design of a nonlinear amplified loop mirror based pulse shaper with a focus on the impact of pump power on the signal-to-pedestal power ratio, which ultimately influences the spectral flatness and the optical signal-to-noise ratio (OSNR) after the parametric expansion. Notably, we design the OFC using all polarization-maintaining (PM) components, demonstrating the performance of PM highly nonlinear fibers in parametric comb generation. This results in a PM cavity-less comb with <9 dB power variation over 110 nm, >0 dBm power per tone, <10 kHz linewidth, and >23 dB OSNR. These characteristics make it highly desirable for application in communication and signal processing.

Observations of very fast electron traps at SiC/high-κ dielectric interfaces

Very fast interface traps have recently been suggested to be the main cause behind poor channel-carrier mobility in SiC metal–oxide–semiconductor field effect transistors. It has been hypothesized that the NI traps are defects located inside the SiO2 dielectric with energy levels close to the SiC conduction band edge and the observed conductance spectroscopy signal is a result of electron tunneling to and from these defects. Using aluminum nitride and aluminum oxide as gate dielectrics instead of SiO2, we detect NI traps at these SiC/dielectric interfaces as well. A detailed investigation of the NI trap density and behavior as a function of temperature is presented and discussed. Advanced scanning transmission electron microscopy in combination with electron energy loss spectroscopy reveals no SiO2 at the interfaces. This strongly suggests that the NI traps are related to the surface region of the SiC rather than being a property of the gate dielectric.

Compressibility Analysis of Functional Near-Infrared Spectroscopy Signals in Children With Attention-Deficit/Hyperactivity Disorder.

Functional near- infrared spectroscopy (fNIRS) as an emerging optical neuroimaging technique has attracted the interest and attention of many investigators. With the growth of fNIRS data volume, effective data compression methods are urgent. Compressive sensing (CS) has been demonstrated a promising tool to deal with biomedical data. However, whether the compressibility of fNIRS data can discriminate different brain states is unclear. In this study, the fNIRS signals from fifteen attention-deficit/hyperactivity disorder (ADHD) children and fifteen typically developing (TD) children were recorded during an N-back task and a Go/NoGo task respectively. A block sparse Bayesian learning-based CS method was used to reconstruct the compressed fNIRS data. To assess the performance of the CS method, we adopted two metrics, structural similarity index (SSIM) and mean squared error (MSE), both of them effective in evaluating the compressibility of fNIRS data. Then, the two metrics were analyzed to discriminate the brain states of ADHD children and TD children during the two tasks using the multivariate pattern analysis (MVPA) method. As indicated by the results, the CS method could reconstruct the compressed fNIRS data with a high reconstruction quality at different compression ratio ([Formula: see text] and [Formula: see text]). Furthermore, the MVPA method could distinguish different brain states with high accuracy, and identify that the prefrontal cortex is a key brain region for distinguishing ADHD vs. TD or N-back vs. Go/NoGo. These findings indicated that CS is very promising for the storage and transmission of massive fNIRS data, and the compressibility of fNIRS data is a potential biomarker for the diagnosis of ADHD.

Construction of SERS chip based on silver nanoparticles and detection of sports doping β-agonists

Sports doping is a persistent challenge in competitive sports, undermining the integrity of athletic competitions and posing health risks to athletes. This study focuses on the development of a surface-enhanced Raman spectroscopy (SERS) chip for the detection of β-agonists, such as clenbuterol, ractopamine, and salbutamol, which are commonly abused as performance-enhancing drugs. The SERS chip was constructed by depositing silver nanoparticles (AgNPs) onto activated carbon (AC) as a substrate, utilizing their plasmonic properties and ease of synthesis. The successful loading of AgNPs onto AC was confirmed by SEM imaging, demonstrating a uniform distribution of AgNPs on the surface of AC. The SERS chip exhibited enhanced sensitivity in detecting β-agonists compared to conventional methods. The SERS signals of the analytes decreased with decreasing concentrations, indicating the chip's ability to detect low-concentration analytes. Notably, the AC/AgNPs composite demonstrated stronger SERS signals compared to AgNPs alone, attributed to the improved loading efficiency and electromagnetic field enhancement provided by the AC substrate. The detection limit of the AC/AgNPs SERS chip for clenbuterol, ractopamine, and salbutamol was found to be 0.003 mg/L, 0.001 mg/L, and 0.007 mg/L, respectively. The developed SERS chip offers rapid and sensitive detection of β-agonists in sports doping control. It overcomes the limitations of conventional methods, such as immunoassays and chromatographic techniques, in terms of sensitivity, selectivity, and sample preparation time. The application of SERS in anti-doping efforts holds great promise for maintaining fair and clean sports competitions.

Hybridization of ellipsometry and XPS energy loss: Robust band gap and broadband optical constants determination of SiGe, HfON and MoOx thin films

In this study, we compare the robustness of optical constants and optical band gap determination of three different materials: SiGe, N-doped HfO2 and MoOx, using the combination of two techniques: spectroscopic ellipsometry, and energy loss signal (ELS) of X-ray photoelectron spectroscopy (XPS). The determination of such physical properties is achieved through the hybridization of the two techniques based on multiple Tauc-Lorentz model, applied on the whole energy range of measurement.Such use of hybridized data demonstrates a new robust method to determine the band gap of the studied materials, together with the optical indices (refractive index and extinction coefficient) on a wide energy range (up to 40 eV). This method provides an extension of determination of the relevant physical quantities compared to each technique on their own.Moreover, this algorithm is tested on limit conditions, where the energy ranges of measurement of the two respective techniques presented no overlap. Yet the use of a unique physical model still allows us to calculate the different physical quantities even on the energy range where no measurement is performed, validating the semi-predictive nature of the hybrid technique. Additional measurements under different experimental configurations validate the extended scope of such hybrid technique.

Engineered vertically-aligned carbon nanotube microarray for self-concentrated SERS detection

Surface-enhanced Raman spectroscopy (SERS) is a high-sensitivity, label-free detection method that shows promise for various analytical applications. Hydrophobic low-adhesion surfaces make excellent SERS substrates since they allow the usage of trace analytes at low concentrations by efficiently enriching them into the SERS-active region. Herein, we introduce a hydrophobic surface-enhanced Raman scattering substrate based on engineered carbon nanotube arrays (CNT-SERS) and study the role of structural design in both micro- and nanoscales. This substrate has predetermined microstructures with a high aspect ratio, providing controlled self-enrichment capability. Likewise, the vertically aligned 3D surface porosity enables enhanced sensitivity, exhibiting an amplification in the SERS signal of ∼507.6%. The applicability of CNT-SERS to environmental science is shown by analyzing 5 nM of industrial dye (crystal violet) with 121 consecutive SERS measurements that exhibit distinct peaks from the molecules. We explore the underlying mechanics governing the enrichment behavior during analyte deposition on microarrays and discuss the effective strategies for designing hydrophobic SERS substrates. A theoretical model predicting the extent of concentration is developed and compared with the experimental results. In addition, we suggest a robust analyte concentration strategy inspired by plants in the Bromeliaceae family. The proposed method utilizes a hydrophobic yet flexible CNT SERS substrate that prevents roll-off failures during droplet loading.

A core-satellite self-assembled SERS aptasensor containing a “biological-silent region” Raman tag for the accurate and ultrasensitive detection of histamine

Herein, a novel interference-free surface-enhanced Raman spectroscopy (SERS) strategy based on magnetic nanoparticles (MNPs) and aptamer-driven assemblies was proposed for the ultrasensitive detection of histamine. A core-satellite SERS aptasensor was constructed by combining aptamer-decorated Fe3O4@Au MNPs (as the recognize probe for histamine) and complementary DNA-modified silver nanoparticles carrying 4-mercaptobenzonitrile (4-MBN) (Ag@4-MBN@Ag-c-DNA) as the SERS signal probe for the indirect detection of histamine. Under an applied magnetic field in the absence of histamine, the assembly gave an intense Raman signal at “Raman biological-silent” region due to 4-MBN. In the presence of histamine, the Ag@4-MBN@Ag-c-DNA SERS-tag was released from the Fe3O4@Au MNPs, thus decreasing the SERS signal. Under optimal conditions, an ultra-low limit of detection of 0.65 × 10-3 ng/mL and a linear range 10-2–105 ng/mL on the SERS aptasensor were obtained. The histamine content in four food samples were analyzed using the SERS aptasensor, with the results consistent with those determined by high performance liquid chromatography. The present work highlights the merits of indirect strategies for the ultrasensitive and highly selective SERS detection of small biological molecules in complex matrices.

Rapid Detection of SARS-CoV-2 in Clinical and Environmental Samples via a Resonant Cavity SERS Platform within 20 min.

The coronavirus disease 2019 (COVID-19) epidemic has given a warning that it is important to explore the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in clinical specimens or environmental samples for public health strategies and future variants. The surface-enhanced Raman spectroscopy (SERS) technique was demonstrated to achieve this goal. However, the consistency of signals originating from the poor compatibility of virions with SERS hotspots remains a key scientific challenge for the practical applications of SERS. Herein, we develop a SERS platform for the ultrasensitive and rapid detection of SARS-CoV-2 antigen within 20 min by the combination of a highly consistent SERS substrate and a supervised deep learning algorithm. A V-shaped resonant cavity array (VRC) substrate was fabricated to trap SARS-CoV-2 virions in the periodic V cavity array and stimulate the integral SERS signal of the virus via a resonance coupling effect. Benefiting from the unique architecture of the VRC substrate, we were able to directly detect the SARS-CoV-2 virus with high sensitivity and high consistency. These excellent performances enabled us to identify five different kinds of SARS-CoV-2 variants and detect SARS-CoV-2 from clinical and environmental samples with high accuracies.

Modified PSYCHE NMR - The possibility for the direct semi-quantitation of components in mixtures

A series of commonly occurring biologically relevant compounds were analysed using internally referenced PSYCHE NMR and the accuracy/precision compared with that achieved using conventional qNMR. The effect of chemical shift, coupling constants, swept frequency pulse angle, excitation sculpting and the impact of signal overlap in mixtures was evaluated in terms of statistically significant variation between the two techniques. It is shown that suitably optimised PSYCHE NMR represents a potentially reliable method for the semi-quantitation of mixtures of compounds, whose spectroscopic signals overlap in conventional qNMR analysis and hence cannot be accurately quantified with that technique. This is of particular relevance for complex mixtures of natural products. Of particular note is the effect of the excitation sculpting block introduced to supress baseline artefacts.

Molecular tracking of interactions between progenitor and endothelial cells via Raman and FTIR spectroscopy imaging: a proof of concept of a new analytical strategy for in vitro research

Circulating endothelial cell progenitors originating from the bone marrow are considered to be a powerful tool in the repair of endothelium damage. Due to their unique properties, endothelial progenitors are now broadly investigated to assess their clinical significance in diseases e.g., associated with brain endothelial dysfunction. However, their distinction in terms of the expression of specific markers remains ambiguous. Additionally, endothelial progenitor cells may change their repertoire of markers depending on the microenvironment of the tissue in which they are currently located. Here, we applied the label-free Raman and FTIR imaging to discriminate mice brain endothelium and endothelial progenitors. Cells cultured separately showed distinctly different spectral signatures extracted from the whole cellular interior as well as the detected intracellular compartments (nucleus, cytoplasm, perinuclear area, and lipid droplets). Then, we used these spectroscopic signals to examine the cells co-cultured for 24 h. Principal cluster analysis showed their grouping with the progenitor cells and segregation from brain endothelium at a level of the entire cell machinery (in FTIR images) which resulted from biochemical alternations in the cytoplasm and lipid droplets (in Raman images). The models included in partial least square regression indicated that lipid droplets are the key element for the classification of endothelial progenitor-brain endothelial cells interactions.

3D SERS and Raman imaging of protective microcapsules containing bio‐active terpenoids

AbstractTerpenoids play a major role in agriculture, given their fungicidal and herbicidal actions, as well as their favorable toxicological, ecotoxicological, and environmental profiles. Despite all these advantages, terpenoids are reported to be unstable in direct sunlight and atmospheric conditions, so both commercial suppliers and scientific literature foresee their protection by encapsulation. The so‐called microcapsules (μCaps) are therefore of high relevance as drug‐delivery vectors, but very few techniques focus on their surface as well as on their morphological characterization. Indeed, these aspects are of great importance, given that their surface chemistry governs both their colloidal stability and mechanism of action. Common analysis techniques, such as chromatographic and mass‐spectrometric ones, are destructive, require sample preparation, and do not result in the complete morphological characterization of the microcapsules. Micro‐Raman spectroscopy, in conjunction with the surface‐enhanced Raman spectroscopy (SERS) effect, offers a valuable alternative method of investigation capable of achieving a complete and non‐destructive morphological characterization of the terpenoid‐encapsulating systems, the dimensions of which fall within the micrometric range. In addition, the SERS effect can be exploited by fabricating the microcapsules with gold nanostars (AuNSs) modified with chitosan and a SERS reporter (Nile Blue A). Thanks to the high contrast provided by the SERS signals of this tag, it was possible to localize and confirm the chitosan in the morphology of the microcapsules. The results of this study shed new light on the possibility of analyzing terpenoid‐encapsulating microcapsules and possibly other kinds of encapsulates brought by using Raman spectroscopy and by exploiting the SERS effect.

Normothermic Ex Situ Machine Perfusion of Vascularized Composite Allografts with Oxygen Microcarriers for 12 Hours Using Real-Time Mitochondrial Redox Quantification.

Normothermic ex situ perfusion of vascularized composite allografts (VCAs) necessitates high oxygen demand and, thus, increased metabolic activity, which, in turn, requires the use of blood-based perfusion solutions. However, blood-derived perfusates, in turn, constitute an antigenic load. To circumvent this immunogenic problem, we used a perfusate enriched with acellular dextrane oxygen microcarriers to perfuse rat hindlimbs. Rat hindlimbs (n = 11) were perfused with either (non-), oxygenated dextrane-enriched Phoxilium, or Phoxilium enriched with dextrane oxygen microcarriers (MO2) for 12 h at 37 °C or stored on ice. Oxygenation of the skeletal muscle was assessed with Raman spectroscopy, tissue pO2-probes, and analysis of the perfusate. Transmission electronic microscopy was utilized to assess the ultrastructure of mitochondria of the skeletal muscle. For all evaluated conditions, ischemia time until perfusion was comparable (22.91 ± 1.64 min; p = 0.1559). After 12 h, limb weight increased significantly by at least 81%, up to 124% in the perfusion groups, and by 27% in the static cold storage (SCS) group. Raman spectroscopy signals of skeletal muscle did not differ substantially among the groups during either perfusion or static cold storage across the duration of the experiment. While the total number of skeletal muscle mitochondria decreased significantly compared to baseline, mitochondrial diameter increased in the perfusion groups and the static cold storage group. The use of oxygen microcarriers in ex situ perfusion of VCA with acellular perfusates under normothermic conditions for 12 h facilitates the maintenance of mitochondrial structure, as well as a subsequent recovery of mitochondrial redox status over time, while markers of muscle injury were lower compared to conventional oxygenated acellular perfusates.

Detection of micro-plasma-induced exosomes secretion in a fibroblast-melanoma co-culture model

BackgroundMelanoma is a highly aggressive tumor and a significant cause of skin cancer-related death. Timely diagnosis and treatment require identification of specific biomarkers in exosomes secreted by melanoma cells. In this study, label-free surface-enhanced Raman spectroscopy (SERS) method with size-matched selectivity was used to detect membrane proteins in exosomes released from a stimulated environment of fibroblasts (L929) co-cultured with melanoma cells (B16–F10). To promote normal secretion of exosomes, micro-plasma treatment was used to gently induce the co-cultured cells and slightly increase the stress level around the cells for subsequent detection using the SERS method. Results and discussionFirstly, changes in reactive oxygen species/reactive nitrogen species (ROS/RNS) concentrations in the cellular microenvironment and the viability and proliferation of healthy cells are assessed. Results showed that micro-plasma treatment increased extracellular ROS/RNS levels while modestly reducing cell proliferation without significantly affecting cell survival. Secondly, the particle size of secreted exosomes isolated from the culture medium of L929, B16–F10, and co-cultured cells with different micro-plasma treatment time did not increase significantly under single-cell conditions at short treatment time but might be changed under co-culture condition or longer treatment time. Third, for SERS signals related to membrane protein biomarkers, exosome markers CD9, CD63, and CD81 can be assigned to significant Raman shifts in the range of 943–1030 and 1304-1561 cm-1, while the characteristics SERS peaks of L929 and B16–F10 cells are most likely located at 1394/1404, 1271 and 1592 cm-1 respectively. Significance and noveltyTherefore, this micro-plasma-induced co-culture model provides a promising preclinical approach to understand the diagnostic potential of exosomes secreted by cutaneous melanoma/fibroblasts. Furthermore, the label-free SERS method with size-matched selectivity provides a novel approach to screen biomarkers in exosomes secreted by melanoma cells, aiming to reduce the use of labeling reagents and the processing time traditionally required.

Instability and fault analysis of arc plasma using advanced signal processing methods.

This study focuses on the instability and fault analysis of transferred arc plasma, utilizing advanced signal processing methods. Transferred arc plasma systems find significant applications in various industries, including material processing, metallurgy, and waste management. However, the occurrence of instabilities and fault events can severely impact system performance and reliability. To address instabilities in arc plasma, various conditions were experimented. The operating parameters, such as arc voltage, arc current, acoustic, optical, and spectroscopic signals, were simultaneously recorded at a higher sampling rate. The proposed approach employs advanced signal processing methods, such as the Lyapunov exponent, fast-Fourier transform, short-time-Fourier transform, and power spectral density, to analyze the characteristics and instabilities of the transferred arc plasma process. By capturing and analyzing signals from multiple sensors, it becomes possible to identify deviations, irregularities, and fault patterns that arise during plasma operation. The outcomes of this research will have significant implications for the optimization and control of transferred arc plasma processes. By identifying and characterizing instabilities due to fault events at an early stage, system operators can take timely corrective actions, preventing potential damage and improving the overall system efficiency.

Determination of Layer-By-Layer Profiles of Hydrogen Isotopes in Carbon and Beryllium Based on Electron Spectroscopy Methods

A quantitative method for interpreting the spectroscopy signal of elastically reflected electron peaks is constructed taking into account the layer-by-layer analysis of the content of hydrogen isotopes in structural materials used in the international experimental thermonuclear reactor ITER under construction. The relative protium and deuterium concentrations in hydrocarbon samples are determined. The relative deuterium concentrations in a beryllium sample are determined.

Mending cracks atom-by-atom in rutile TiO2 with electron beam radiolysis

Rich electron-matter interactions fundamentally enable electron probe studies of materials such as scanning transmission electron microscopy (STEM). Inelastic interactions often result in structural modifications of the material, ultimately limiting the quality of electron probe measurements. However, atomistic mechanisms of inelastic-scattering-driven transformations are difficult to characterize. Here, we report direct visualization of radiolysis-driven restructuring of rutile TiO2 under electron beam irradiation. Using annular dark field imaging and electron energy-loss spectroscopy signals, STEM probes revealed the progressive filling of atomically sharp nanometer-wide cracks with striking atomic resolution detail. STEM probes of varying beam energy and precisely controlled electron dose were found to constructively restructure rutile TiO2 according to a quantified radiolytic mechanism. Based on direct experimental observation, a “two-step rolling” model of mobile octahedral building blocks enabling radiolysis-driven atomic migration is introduced. Such controlled electron beam-induced radiolytic restructuring can be used to engineer novel nanostructures atom-by-atom.

Motivation-related influences on fNIRS signals during walking exercise: a permutation entropy approach.

Cortical activity is typically indexed by analyzing functional near-infrared spectroscopy (fNIRS) signals in terms of the mean (e.g., mean oxygenated hemoglobin; HbO). Entropy approaches have been proposed as useful complementary methods for analyzing fNIRS signals. Entropy methods consider the regularity of a time series, and in doing so, may provide additional insights into the underlying dynamics of brain activity. Recent research using fNIRS found that non-disabled adults exhibit widespread increases in cortical activity and walk faster when under "extra motivation" conditions (e.g., verbal encouragement, lap timer) compared to trials without such motivators ("standard motivation"). This ancillary analysis of that study aimed to assess the extent to which fNIRS permutation entropy (PE) was affected by motivational conditions and explained variance in self-reported motivation. No regional PE differences were found between different motivational conditions. However, a greater difference in PE between motivational conditions (higher in standard, lower in extra motivation) in the anterior prefrontal cortex (aPFC) was associated with greater self-determined motivation. PE was also higher (less regular) in the primary sensorimotor cortex lower limb area compared to all other cortical areas analyzed, except the dorsal premotor cortex, regardless of motivational condition. This study provides early evidence to suggest that while different motivational environments during walking activity influence the magnitude of fNIRS signals, they may not influence the regularity of cortical signals. However, the magnitude of PE difference between motivational conditions was related to self-determined motivation in the aPFC, and this is an area warranting further investigation.