U-Net enhanced real-time LED-based photoacoustic imaging.

Photoacoustic (PA) imaging is hybrid imaging modality with good optical contrast and spatial resolution. Portable, cost-effective, smaller footprint light emitting diodes (LEDs) are rapidly becoming important PA optical sources. However, the key challenge faced by the LED-based systems is the low light fluence that is generally compensated by high frame averaging, consequently reducing acquisition frame-rate. In this study, we present a simple deep learning U-Net framework that enhances the signal-to-noise ratio (SNR) and contrast of PA image obtained by averaging low number of frames. The SNR increased by approximately four-fold for both in-class in vitro phantoms (4.39 ± 2.55) and out-of-class in vivo models (4.27 ± 0.87). We also demonstrate the noise invariancy of the network and discuss the downsides (blurry outcome and failure to reduce the salt & pepper noise). Overall, the developed U-Net framework can provide a real-time image enhancement platform for clinically translatable low-cost and low-energy light source-based PA imaging systems.

Fluorescence Characteristics and Main Fluorescence Component in Burmese 'chameleon' Amber.

One special variety of Burmese amber is "chameleon" amber, named for the bluish-green colour that appears to float on its surface. This material is found in the famous Tengchong market in Yunnan Province, China's largest Burmese amber market. Its bodycolour ranges from golden brown to brownish-red or even red. When exposed to sunlight or strong white light against a black background, its surface shows a uniform green colour. This research presents the gemological properties, spectral characteristics and organic components of Burmese 'chameleon' amber. Three-dimensional (3D) fluorescence spectra showed that Burmese 'chameleon' amber had fluorescence centres near 433, 465 and 470 nm, and the excitation wavelengths of the fluorescence centres of Burmese 'chameleon' amber were shifted from the ultraviolet region (380 ± 10 nm) to the visible region (410 ± 10 nm), with the emission wavelengths concentrated at the bluish-green region. Through the colour simulation and superimposition, the phenomenon of floating bluish-green fluorescence colour of Burmese 'chameleon' amber is not only derived from bluish-green fluorescence centres, but also enhanced by the mixture of surface fluorescence and its bodycolour. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) analysis demonstrated the variety of aromatic compounds in Burmese 'chameleon' amber was related to geological process and the presence of fluorescence components. The high-performance liquid chromatography-fluorescence detector obtained some fluorescent aromatics, particularly benzo[a]anthracene with yellowish-green fluorescence, which is responsible for the fluorescence characteristics of Burmese 'chameleon' amber.

Impact of Reducing Statistically Small Population Sampling on Threshold Detection in FBG Optical Sensing.

Many techniques have been studied for recovering information from shared media such as optical fiber that carries different types of communication, sensing, and data streaming. This article focuses on a simple method for retrieving the targeted information with the least necessary number of significant samples when using statistical population sampling. Here, the focus is on the statistical denoising and detection of the fiber Bragg grating (FBG) power spectra. The impact of the two-sided and one-sided sliding window technique is investigated. The size of the window is varied up to one-half of the symmetrical FBG power spectra bandwidth. Both, two- and one-sided small population sampling techniques were experimentally investigated. We found that the shorter sliding window delivered less processing latency, which would benefit real-time applications. The calculated detection thresholds were used for in-depth analysis of the data we obtained. It was found that the normality three-sigma rule does not need to be followed when a small population sampling is used. Experimental demonstrations and analyses also showed that novel denoising and statistical threshold detection do not depend on prior knowledge of the probability distribution functions that describe the FBG power spectra peaks and background noise. We have demonstrated that the detection thresholds' adaptability strongly depends on the mean and standard deviation values of the small population sampling.

A Molecular Typing Method for Invasive Breast Cancer by Serum Raman Spectroscopy.

BACKGROUND: The incidence of breast cancer ranks highest among cancers and is exceedingly heterogeneous. Immunohistochemical staining is commonly used clinically to identify the molecular subtype for subsequent treatment and prognosis. PURPOSE: Raman spectroscopy and support vector machine (SVM) learning algorithm were utilized to identify blood samples from breast cancer patients in order to investigate a novel molecular typing approach. METHOD: Tumor tissue coarse needle aspiration biopsy samples, and peripheral venous blood samples were gathered from 459 invasive breast cancer patients admitted to the breast department of Sichuan Cancer Hospital between June 2021 and September 2022. Immunohistochemical staining and in situ hybridization were performed on the coarse needle aspiration biopsy tissues to obtain their molecular typing pathological labels, including: 70 cases of Luminal A, 167 cases of Luminal B (HER2-positive), 57 cases of Luminal B (HER2-negative), 84 cases of HER2-positive, and 81 cases of triple-negative. Blood samples were processed to obtained Raman spectra taken for SVM classification models establishment with machine algorithms (using 80% of the sample data as the training set), and then the performance of the SVM classification models was evaluated by the independent validation set (20% of the sample data). RESULTS: The AUC values of SVM classification models remained above 0.85, demonstrating outstanding model performance and excellent subtype discrimination of breast cancer molecular subtypes. CONCLUSION: Raman spectroscopy of serum samples can promptly and precisely detect the molecular subtype of invasive breast cancer, which has the potential for clinical value.

Electronic tongue, proton-transfer-reaction mass spectrometry, spectral analysis, and molecular docking characterization for determining the effect of α-amylase on flavor perception.

The effects of α-amylase on of flavor perception were investigated via spectrum analysis, electronic tongue, on-line mass spectrometry, and molecular docking. Aroma release results showed that α-amylase exhibited variable release patterns of different aroma compounds. Electronic tongue analysis showed that the perception of bitterness, sweetness, sour, and saltiness was subtly increased and that of umami was significantly increased (p < 0.01) along with the increasing enzyme activity of α-amylase. Ultraviolet absorption and fluorescence spectroscopy analyses showed that static quenching occurred between α-amylase and eight flavor compounds and their interaction effects were spontaneous. One binding pocket was confirmed between the α-amylase and flavor compounds, and molecular docking simulation results showed that the hydrogen, electrostatic, and hydrophobic bonds were the main force interactions. The TYP82, TRP83, LEU173, HIS80, HIS122, ASP297, ASP206, and ARG344 were the key α-amylase amino acid residues that interacted with the eight flavor compounds.

Efficient EEG motion artifact elimination framework for ambulatory epileptic seizure detection application.

Motion artifacts are a pervasive challenge in EEG ambulatory monitoring, often obscuring critical neurological signals and impeding accurate seizure detection. In this study, we propose a new approach of outlier based grouping of two level Singular Spectrum Analysis (SSA) decomposition combined with Relative Total Variation (RTV) filter for the effective removal of motion-induced noise from ambulatory EEG data. A two-stage SSA method was employed to decompose single-channel EEG signal, which had been interfered with, into various fre quency bands. The affected sub-band signal was then subjected to an RTV filter to estimate the artifact signal. Subtracting this estimated artifact signal from the contaminated sub-band signal yielded the filtered sub-band signal. Subse quently, the filtered sub-band signal was reintegrated with the other decomposed components from noise-free bands, culminating in the generation of the ultimate denoised EEG signal. Based on the comprehensive set of simulation results, it can be deduced that the algorithm described in the paper outperforms existing methods. It demonstrates superior metrics evaluation in terms of ΔSNR,η,MAE, andPSNRwhen compared to these alternatives. Our framework sig- nificantly enhances the quality of EEG data by successfully eliminating motion artifacts while preserving crucial brainwave information. To evaluate the prac tical impact of this noise reduction technique, we assess its performance in the context of seizure detection. The results reveal a substantial improvement in the accuracy and reliability of seizure detection algorithms when applied to EEG data preprocessed with proposed method.

A method for detecting spatiotemporal patterns of cancer biomarkers-evoked activity using radial basis function network extracted time-domain features from calcium imaging data.

BACKGROUND: Two-photon calcium imaging is widely used to study the odor-evoked glomerular activity in the dorsal olfactory bulb of macrosmatic animals. The nonstationary character of activated patterns sets a limit on the use of a traditional image processing approaches. NEW METHOD: The developed method makes it possible to automatically map cancer biomarkers-activated glomeruli in the rat dorsal olfactory bulb. We interpolated fluorescence intensity of calcium dynamics based on the Gaussian RBF network and synthesized the physiological fluorescence model of the receptive glomerular field. RESULTS: The experiments on 5 rats confirmed the correctness of the developed approach. Patterns evoked by the 6-methyl-5-hepten-2-one (stomach cancer biomarker) and benzene (lung cancer biomarker) were correctly identified. COMPARISON WITH EXISTING METHODS: The proposed method was compared with the nonnegative matrix factorization method and with the method based on computer vision algorithms. The developed approach showed better accuracy in experiments and provided the mathematical models of the odor-evoked patterns synthesis. These models can be used to generate synthetic images of odor-evoked glomerular activity and thus to overcome the problem of small experimental data collected in calcium imaging. CONCLUSIONS: The proposed method should be considered part of the toolkit for fully automatic analysis of calcium imaging-based studies. Currently available methodology is not able to use breath biomarkers to reliably discriminate between cancer patients and healthy controls. Nevertheless, the effective identification of the spatial patterns of cancer biomarkers-evoked glomerular activity can serve as the foundation for highly sensitive biohybrid systems for cancer screening.

High-skilled first-person shooting game players have specific frontal lobe activity: Power spectrum analysis in an electroencephalogram study.

First-person shooting (FPS) games are among the most famous video games worldwide. However, cortical activities in environments related to real FPS games have not been studied. This study aimed to determine differences in cortical activity between low- and high-skilled FPS game players using 160-channel electroencephalography. Nine high-skilled FPS game players (official ranks: above the top 10%) and eight low-skilled FPS game players (official ranks: lower than the top 20%) were recruited for the experiment. The task was set for five different conditions using the AimLab program, which was used for the FPS game players' training. Additionally, we recorded the brain activity in the resting condition before and after the task, in which the participants closed their eyes and relaxed. The reaction time and accuracy (the number of hit-and-miss targets) were calculated to evaluate the task performance. The results showed that high-skilled FPS game players have fast reaction times and high accuracy during tasks. High-skilled FPS game players had higher cortical activity in the frontal cortex than low-skilled FPS game players during each task. In low-skilled players, cortical activity level and performance level were associated. These results suggest that high cortical activity levels were critical to achieving high performance in FPS games.

Methods for the Design and Analysis of Analytical Ultracentrifugation Experiments.

Analytical ultracentrifugation experiments play an integral role in the solution-phase characterization of biological macromolecules and their interactions. This unit discusses the design of sedimentation velocity and sedimentation equilibrium experiments performed with a Beckman Proteomelab XL-A or XL-I analytical ultracentrifuge and with a Beckman Optima AUC. Instrument settings and experimental design considerations are explained, and strategies for the analysis of experimental data with the UltraScan data analysis software package are presented. Special attention is paid to the strengths and weaknesses of the available detectors, and guidance is provided on how to extract maximum information from analytical ultracentrifugation experiments. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC.

Visually evoked local field potential changes in the caudate nucleus are remarkably more frequent in awake, behaving cats than in anaesthetized animals.

Previous results show that halothane gas anaesthesia has a suppressive effect on the visually evoked single-cell activities in the feline caudate nucleus (CN). In this study, we asked whether the low-frequency neuronal signals, the local field potentials (LFP) are also suppressed in the CN of anaesthetized animals.To answer this question, we compared the LFPs recorded from the CN of two halothane-anaesthetized (1.0%), paralyzed, and two awake, behaving cats during static and dynamic visual stimulation. The behaving animals were trained to perform a visual fixation task.Our results denoted a lower proportion of significant power changes to visual stimulation in the CN of the anesthetized cats in each frequency range (from delta to beta) of the LFPs, except gamma. These differences in power changes were more obvious in static visual stimulation, but still, remarkable differences were found in dynamic stimulation, too. The largest differences were found in the alpha and beta frequency bands for static stimulation. Concerning dynamic stimulation, the differences were the biggest in the theta, alpha and beta bands.Similar to the single-cell activities, remarkable differences were found between the visually evoked LFP changes in the CN of the anaesthetized, paralyzed and awake, behaving cats. The halothane gas anaesthesia and the immobilization suppressed the significant LFP power alterations in the CN to both static and dynamic stimulation. These results suggest the priority of the application of behaving animals even in the analysis of the visually evoked low-frequency electric signals, the LFPs recorded from the CN.

Quantitative EEG Spectral and Connectivity Analysis for Cognitive Decline in Amnestic Mild Cognitive Impairment.

BACKGROUND: Mild cognitive impairment (MCI) is considered to be the borderline of cognitive changes associated with aging and very early dementia. Cognitive functions in MCI can improve, remain stable or progress to clinically probable AD. Quantitative electroencephalography (qEEG) can become a useful tool for using the analytical techniques to quantify EEG patterns indicating cognitive impairment. OBJECTIVE: The aim of our study was to assess spectral and connectivity analysis of the EEG resting state activity in amnestic MCI (aMCI) patients in comparison with healthy control group (CogN). METHODS: 30 aMCI patients and 23 CogN group, matched by age and education, underwent equal neuropsychological assessment and EEG recording, according to the same protocol. RESULTS: qEEG spectral analysis revealed decrease of global relative beta band power and increase of global relative theta and delta power in aMCI patients. Whereas, decreased coherence in centroparietal right area considered to be an early qEEG biomarker of functional disconnection of the brain network in aMCI patients. In conclusion, the demonstrated changes in qEEG, especially, the coherence patterns are specific biomarkers of cognitive impairment in aMCI. CONCLUSIONS: Therefore, qEEG measurements appears to be a useful tool that complements neuropsychological diagnostics, assessing the risk of progression and provides a basis for possible interventions designed to improve cognitive functions or even inhibit the progression of the disease.

The Influence of Manganese Slag on the Properties of Ultra-High-Performance Concrete.

Manganese slag (MS) is a kind of chemical waste, which may pollute the environment if conventional handling methods (stacking and landfill) are applied. Ultra-high-performance concrete (UHPC)-with considerably high compactness and strength-can be used not only as a special concrete material, but also to solidify the toxic substances in solid waste. This study proposes the addition of MS to UHPC, where the mass ratio of MS varies from 0% to 40% in the total mass of MS and silica fume. The effects of MS on the fluidity, plastic viscosity, and yield shear stress are investigated, and the flexural strength, compressive strength, and dry shrinkage rate of UHPC with MS are measured. X-ray diffraction (XRD) spectrum and energy spectrum analysis (EDS) diagrams are obtained to analyze the performance mechanism of the UHPC. A rheological study confirms that the slump flow increases with the increasing rate of 0-14.3%, while the yield shear stress and plastic viscosity decrease with the rates of 0-29.6% and 0-22.2%, respectively. The initial setting time increases with the mass ratio of MS by 0-14.3%, and MS has a positive effect on the flexural and compressive strengths of UHPC. In the early curing stage (less than 14 days), the increasing rate in the specimens increases with the curing age; meanwhile, when the curing age reaches 14 days or higher, the increasing rate decreases with increasing curing age. The compactness of UHPC is increased by adding MS. Furthermore, MS can increase the elements of Al and decrease crystals of Ca(OH)2 and calcium silicate hydrate in UHPC.

Classification of First-Episode Psychosis with EEG Signals: ciSSA and Machine Learning Approach.

First-episode psychosis (FEP) typically marks the onset of severe psychiatric disorders and represents a critical period in the field of mental health. The early diagnosis of this condition is essential for timely intervention and improved clinical outcomes. In this study, the classification of FEP was investigated using the analysis of electroencephalography (EEG) signals and circulant spectrum analysis (ciSSA) sub-band signals. FEP poses a significant diagnostic challenge in the realm of mental health, and it is aimed at introducing a novel and effective approach for early diagnosis. To achieve this, the LASSO method was utilized to select the most significant features derived from entropy, frequency, and statistical-based characteristics obtained from ciSSA sub-band signals, as well as their hybrid combinations. Subsequently, a high-performance classification model has been developed using machine learning techniques, including ensemble, support vector machine (SVM), and artificial neural network (ANN) methods. The results of this study demonstrated that the hybrid features extracted from EEG signals' ciSSA sub-bands, in combination with the SVM method, achieved a high level of performance, with an area under curve (AUC) of 0.9893, an accuracy of 96.23%, a sensitivity of 0.966, a specificity of 0.956, a precision of 0.9667, and an F1 score of 0.9666. This has revealed the effectiveness of the ciSSA-based method for classifying FEP from EEG signals.

Effect of Lactobacillus plantarum PS128 on neuromuscular efficiency after a half-marathon.

Introduction: Lactobacillus plantarum PS128 (PS128) could be considered an antioxidant supplement to reduce muscle fatigue and improve exercise capacity recovery after vigorous exercise. Purpose: The purpose of this study is to investigate the effect of PS128 on muscle fatigue and electromyography (EMG) activity after a half-marathon (HM). Methods: The experimental design used a repeated-measures design with a double-blind approach. The participants either took two capsules of PS128 for 4 weeks as the PS128 group (PSG, n = 8) or took two capsules of a placebo for 4 weeks as the placebo group (PLG, n = 8) to ensure counterbalancing. The time points of the maximal voluntary isometric contraction (MVIC) and EMG activity test were set before probiotics were taken (baseline), 48 h before HM (Pre), and immediately at 0 h, 3 h, 24 h, 48 h, 72 h, and 96 h after HM. Results: EMG activity included median power frequency (MDF), integrated EMG (iEMG), and neuromuscular efficiency (peak torque/iEMG). The MVICs of knee extensors, analyzed by using an isokinetic dynamometer, showed a decrease from the Pre to 0 h (p = 0.0001), 3 h (p < 0.0001), 24 h (p < 0.0001), 48 h (p < 0.0001), 72 h (p = 0.0002), and 96 h (p = 0.0408) time points in the PLG. Sidak's multiple comparisons tests showed that the PLG was significantly lower than the PSG at 0 h (p = 0.0173), 3 h (p < 0.0001), 24 h (p < 0.0001), 48 h (p < 0.0001), 72 h (p < 0.0001), and 96 h (p = 0.0004) time points. The MDF of vastus medialis oblique (VMO) in the PLG was significantly decreased 24 h after HM and significantly lower than that in the PSG at all times points after HM. The iEMG of VMO in the PLG was significantly decreased 48 h after HM and significantly lower than that in the PSG at 0 h, 3 h, 24 h, 48 h, and 72 h after HM. Conclusion: The PS128 supplementation may prevent the decrease in MDF, iEMG, and peak torque after vigorous exercise. Recreational runners may consider implementing a probiotic supplementation regimen as a potential strategy to mitigate muscle fatigue following HM.

Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis.

It is of great significance to study the thermal radiation anomalies of earthquake swarms in the same area in terms of selecting abnormal characteristic determination parameters, optimizing and determining the processing model, and understanding the abnormal machine. In this paper, we investigated short-term and long-term thermal radiation anomalies induced by earthquake swarms in Iran and Pakistan between 2007 and 2016. The anomalies were extracted from infrared remote sensing black body temperature data from the China Geostationary Meteorological Satellites (FY-2C/2E/2F/2G) using the multiscale time-frequency relative power spectrum (MS T-FRPS) method. By analyzing and summarizing the thermal radiation anomalies of series earthquake groups with consistency law through a stable and reliable MS T-FRPS method, we first obtained the relationship between anomalies and ShakeMaps from USGS and proposed the anomaly regional indicator (ARI) to determine seismic anomalies and the magnitude decision factor (MDF) to determine seismic magnitude. In addition, we explored the following discussions: earthquake impact on regional thermal radiation background and the relationship between thermal anomalies and earthquake magnitude and the like. Future research directions using the MS T-FRPS method to characterize regional thermal radiation anomalies induced by strong earthquakes could help improve the accuracy of earthquake magnitude determination.

Online spectral unmixing in gamma-ray spectrometry.

We introduced in a previous paper a time-dependent full-spectrum analysis algorithm speeding up the estimation of the activity of the radionuclides present in a sample. In this paper, we present a new version of the algorithm allowing online estimation. It uses only on a buffer of few segments while keeping the time information by using a time dependent regularization, thus reducing the size of the data matrices and the length of the processing of each iteration. The algorithm is optimized and tested on both simulated and measured spectra of aerosol samples.

Brain-Computer Interface: The HOL-SSA Decomposition and Two-Phase Classification on the HGD EEG Data.

An efficient processing approach is essential for increasing identification accuracy since the electroencephalogram (EEG) signals produced by the Brain-Computer Interface (BCI) apparatus are nonlinear, nonstationary, and time-varying. The interpretation of scalp EEG recordings can be hampered by nonbrain contributions to electroencephalographic (EEG) signals, referred to as artifacts. Common disturbances in the capture of EEG signals include electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG) and other artifacts, which have a significant impact on the extraction of meaningful information. This study suggests integrating the Singular Spectrum Analysis (SSA) and Independent Component Analysis (ICA) methods to preprocess the EEG data. The key objective of our research was to employ Higher-Order Linear-Moment-based SSA (HOL-SSA) to decompose EEG signals into multivariate components, followed by extracting source signals using Online Recursive ICA (ORICA). This approach effectively improves artifact rejection. Experimental results using the motor imagery High-Gamma Dataset validate our method's ability to identify and remove artifacts such as EOG, ECG, and EMG from EEG data, while preserving essential brain activity.

Analysis of the distribution of microhardness, mineral, and organic content of human, bovine, and ovine teeth / Análisis de la distribución de microdureza, contenido mineral y orgánico de dientes humanos, bovinos y ovinos

Objetive. Human teeth have been commonly used for in vitro and in situ studies. Cu­rrently, other animals' teeth have been purposed for dental research to overcome human teeth' problematic availability. This study aimed to investigate the enamel and dentin from human, bovine, and ovine teeth concerning the microhardness, organic, and in­ organic contents via micro­Raman spectroscopy. Methods. Human, bovine, and ovine teeth were divided according to their type and age into seven groups: Ovine; Bovine­12 months; Bovine­24 months; Bovine­36 months; Bovine­48 months; Bovine­+60 months; Human (control). The enamel's microhardness (superficial and deep) and den­tin (superficial, middle, and deep) were analyzed. The calcium/phosphate ratio and am­ide contents were determined by micro­Raman spectroscopy. Results. Overall, the mi­crohardness of human enamel was superior to the other species. Dentin's microhardness was similar among groups. Ovine group showed lower values of calcium/phosphate ratio than human. Amide content was similar between bovine and human. The microhardness and calcium/phosphate ratio of enamel and dentin, respectively, decreased as the age of bovine teeth increased. Conclusions. Researchers must be aware and take into consider­ation the differences of ovine and bovine enamel compared to human enamel. Other al­ternatives that are more similar to the microhardness of human enamel should be sought. Bovine teeth of 12 and 24 months are suitable substitutes for dentin of human teeth. Researchers must also be aware of the age of the animals and specify it in the studies.

Objetivo. Los dientes humanos se han utilizado comúnmente para estudios in vitro e in situ. Actualmente, los dientes de otros animales se han destinado a la investiga­ción dental para superar la disponibilidad problemática de los dientes humanos. Este estudio tuvo como objetivo investigar el esmalte y la dentina de los dientes humanos, bovinos y ovinos en relación con la microdureza y los contenidos orgánicos e inor­gánicos a través de la espectroscopia micro­Raman. Métodos. Los dientes humanos, bovinos y ovinos se dividieron según su tipo y edad en siete grupos: Ovinos; Bovino­12 meses; Bovino­24 meses; Bovino­36 meses; Bovino­48 meses; Bovino­+60 meses; Hu­mano (control). Se analizó la microdureza del esmalte (superficial y profunda) y de la dentina (superficial, media y profunda). La relación calcio/fosfato y los contenidos de amida se determinaron mediante espectroscopía micro­Raman. Resultados. En general, la microdureza del esmalte humano fue superior a la de otras especies. La microdureza de la dentina fue similar entre los grupos. El grupo ovino mostró valores más bajos de la relación calcio/fosfato que el humano. El contenido de amida fue similar entre bovinos y humanos. La microdureza y la relación calcio/fosfato del esmalte y la dentina, respectiva­mente, disminuyeron a medida que aumentaba la edad de los dientes bovinos. Conclusiones. El esmalte de los dientes ovinos y bovinos no es un sustituto adecuado del de los dientes humanos. Se deben buscar otras alternativas que sean similares a la microdureza del esmalte humano. Sin embargo, los dientes bovinos de 12 y 24 meses son sustitutos adecuados de la dentina de los dientes humanos. Los investigadores deben conocer la edad de los animales y especificarla en los estudios.

Quantitative and Qualitative Representation of Introductory and Advanced EEG Concepts: An Exploration of Different EEG Setups.

Electroencephalograms (EEGs) are the gold standard test used in the medical field to diagnose epilepsy and aid in the diagnosis of many other neurological and mental disorders. Growing in popularity in terms of nonmedical applications, the EEG is also used in research, neurofeedback, and brain-computer interface, making it increasingly relevant to student learning. Recent innovations have made EEG setups more accessible and affordable, thus allowing their integration into neuroscience educational settings. Introducing students to EEGs, however, can be daunting due to intricate setup protocols, individual variation, and potentially expensive equipment. This paper aims to provide guidance for introducing students and educators to fundamental beginning and advanced level EEG concepts. Specifically, this paper tested the potential of three different setups, with varying channel number and wired or wireless connectivity, for introducing students to qualitative and quantitative exploration of alpha enhancement when eyes are closed, and observation of the alpha/beta anterior to posterior gradient. The setups were compared to determine their relative advantages and their robustness in detecting these well-established parameters. The basic 1- or 2-channel setups are sufficient for observing alpha and beta waves, while more advanced systems containing 8 or 16 channels are required for consistent observation of an anterior-posterior gradient. In terms of localization, the 16-channel setup, in principle, was more adept. The 8-channel setup, however, was more effective than the 16-channel setup with regards to displaying the anterior to posterior gradient. Thus, an 8-channel setup is sufficient in an education setting to display these known trends. Modification of the 16-channel setup may provide a better observation of the anterior to posterior gradient.

Photoacoustic spectrum analysis for spherical target size and optical property determination: A feasibility study.

The photoacoustic signal generated by an optically absorbing target is determined by the spatial profile of absorbed optical energy within the target. The analysis of the time profile and frequency content of the signal enables the recovery of the geometry of the object, as well as information about the optical properties. The photoacoustic response of spheres with a homogeneous absorbed optical energy profile is well described, and it is known that the width of the photoacoustic pulse is determined by the diameter of the sphere and its sound speed. In practice, the optical attenuation coefficients within the sphere will result in an inwardly decaying fluence profile leading to a similarly decaying absorbed optical energy profile. Further, the optical attenuation coefficients may be inhomogeneously distributed in the sphere. The implication for both cases is that the existing model for spheres does not fully apply. In this work, we developed analytical expressions for the photoacoustic time traces and amplitude spectra generated by a sphere with absorbed optical energy only in a spherical shell, and by a sphere with an inwardly decaying optical energy profile. Numerical simulations and experiments were conducted on these two imperfect sphere types. Fitting our model to the simulated or measured spectra allowed us to test our model's ability to extract the sphere size and optical properties. We found that the radii can be recovered with high accuracy, even when the frequency response of the detector recording the photoacoustic pulse is not precisely known. The model was found to be less sensitive in recovering the optical attenuation coefficient, but it is feasible when the detector's frequency response is well known.