Spectral features related to the auditory perception of twang-like voices.

BACKGROUND: To the best of our knowledge, studies on the relationship between spectral energy distribution and the degree of perceived twang-like voices are still sparse. Through an auditory-perceptual test we aimed to explore the spectral features that may relate with the auditory-perception of twang-like voices. METHODS: Ten judges who were blind to the test's tasks and stimuli rated the amount of twang perceived on seventy-six audio samples. The stimuli consisted of twenty voices recorded from eight CCM singers who sustained the vowel [a:] in different pitches, with and without a twang-like voice. Also, forty filtered and sixteen synthesized-manipulated stimuli were included. RESULTS AND CONCLUSIONS: Based on the intra-rater reliability scores, four judges were identified as suitable to be included in the analyses. Results showed that the frequency of F1 and F2 correlated strongly with the auditory-perception of twang-like voices (0.90 and 0.74, respectively), whereas F3 showed a moderate negative correlation (-0.52). The frequency difference between F1 and F3 showed a strong negative correlation (-0.82). The mean energy between 1-2 kHz and 2-3 kHz correlated moderately (0.51 and 0.42, respectively). The frequency of F4 and F5, and the energy above 3 kHz showed weak correlations. Since the spectral changes under 2 kHz have been associated with the jaw, lips, and tongue adjustments (i.e. vowel articulation) and a higher vertical laryngeal position might affect the frequency of all formants (including F1 and F2), our results suggest that vowel articulation and the laryngeal height may be relevant when performing twang-like voices.

Theoretical and experimental study on the effect of scanning speed on FAIMS peaks.

High-Field Asymmetric Ion Mobility Spectrometry (FAIMS) is a technique for ion separation and detection based on ion mobility variation under high electronic field. While compensation voltage scanning speed is a fundamental parameter in FAIMS, its impact on spectra remains unclear. In this work, a function referred to as F-EMG is introduced to describe the impact of compensation voltage scanning speed on FAIMS spectra, and the properties of the function are studied. Theoretical analysis emphasizes the impact of the scanning speed on peak height, position, and symmetry, as well as the capability of the F-EMG function to progressively approach Gaussian function at lower scanning speeds. Furthermore, the function indicates that spectra obtained in positive and negative scanning modes exhibits symmetry. An experimental validation, conducted with a custom FAIMS setup and analyzing hydrogen sulfide, ethylbenzene, toluene, styrene, benzene and ammonia, confirms the model's influence on peak features, fitting accuracy, and exhibits a closer alignment with the Gaussian function at lower scanning speeds. Additionally, the experimental data indicate that the spectra show symmetry in positive and negative scanning models. This work not only improves understanding of FAIMS spectral analysis but also introduces a robust method for enhancing data accuracy across varying scanning speeds.

The contribution of EEG to assess and treat motor disorders in multiple sclerosis.

OBJECTIVE: Electroencephalography (EEG) can highlight significant changes in spontaneous electrical activity of the brain produced by altered brain network connectivity linked to inflammatory demyelinating lesions and neuronal loss occurring in multiple sclerosis (MS). In this review, we describe the main EEG findings reported in the literature to characterize motor network alteration in term of local activity or functional connectivity changes in patients with MS (pwMS). METHODS: A comprehensive literature search was conducted to include articles with quantitative analyses of resting-state EEG recordings (spectrograms or advanced methods for assessing spatial and temporal dynamics, such as coherence, theory of graphs, recurrent quantification, microstates) or dynamic EEG recordings during a motor task, with or without connectivity analyses. RESULTS: In this systematic review, we identified 26 original articles using EEG in the evaluation of MS-related motor disorders. Various resting or dynamic EEG parameters could serve as diagnostic biomarkers of motor control impairment to differentiate pwMS from healthy subjects or be related to a specific clinical condition (fatigue) or neuroradiological aspects (lesion load). CONCLUSIONS: We highlight some key EEG patterns in pwMS at rest and during movement, both suggesting an alteration or disruption of brain connectivity, more specifically involving sensorimotor networks. SIGNIFICANCE: Some of these EEG biomarkers of motor disturbance could be used to design future therapeutic strategies in MS based on neuromodulation approaches, or to predict the effects of motor training and rehabilitation in pwMS.

FTIR spectroscopy for assessment of hair from lung cancer patients and its application in monitoring the chemotherapy treatment effect.

Lung cancer is the most common cancer and the leading cause of death in China. The current gold standard for clinical lung cancer diagnosis is based on histopathological examination of tumors, but it has the limitation for easy operation and convenient applications. Therefore, researchers are still striving to develop other tools and methods for non-invasive and rapid assessment of the health conditions of lung cancer patients. Hair, as a reflection of the metabolism of the body, is closely related to human health conditions. In principle, Fourier-transform infrared (FTIR) spectroscopy can probe the major chemical compositions in the hair. However, as indicated by previous studies, there is still the challenge to make good use of FTIR spectroscopy for achieving reliable analysis of hair from cancer patients. In this study, hair samples from 82 lung cancer patients were collected and subjected to FTIR measurements and analysis, which showed the protein content in the hair is closely related to the protein content in the blood serum of patients, and the contents of protein and lipid are statistically lower in the lung cancer patients. Furthermore, we demonstrated that FTIR spectroscopy could be employed to monitor the hair of lung cancer patients undergoing chemotherapy, and confirmed that the FTIR spectra of the hair may reflect the resultant effect of the chemotherapy. As such, this work validates the way of using FTIR spectroscopy in hair analysis for the assistance of medical diagnosis of lung cancer as well as monitoring the conditions of the patients under the medical treatment.

Integrated geophysical methods to constrain subsurface structures of Tulu Moye-Bora-Berecha axial volcanic complex, main Ethiopia rift: Implications for geothermal resources.

The Main Ethiopian Rift (MER) is a well-known continental rift whose axial sector is characterized by the occurrence of regularly spaced silicic caldera complexes and central stratovolcanoes, interspersed with large fields of fissural basalts, small mafic scoria cones and numerous young normal faults and fissures. The Tulu Moye-Bora-Berecha volcanic complex is found in the central portion of the MER and includes the Tulu Moye geothermal prospect area. A combination of gravity and magnetic methods was used to better constrain the subsurface volcanic stratigraphy and tectonic structures. Regional and residual anomaly maps were produced from the gravity data and the magnetic data were corrected to produce anomaly and enhanced maps. A complete Bouguer anomaly contour map was produced after the necessary reduction was applied to the gravity data. Due to the geomagnetic field's dipolar nature and since the study area is in the equatorial region (<15°), the reduced-to-equator (RTE) technique was used to minimize external effects and correct the data as if the body had been laid at the magnetic equator. The anomalous source's depth was calculated using a Euler depth solution and spectral analysis approach. Joint 2D forward models on three profiles were developed using GM-SYS of Oasis Montaj software. From the interpretation of the geophysical results, the following conclusions have been reached: (1) the crystalline basement is more raised around Salen ridge and west of it; (2) the main heat source of the geothermal system appears to be a central region of the studied area near Salen ridge and is estimated to be at 4-5 km depth, (3) under Gnaro obsidian dome, the basaltic and silicic volcanic horizon is thin, and the deep-seated regional fault serves as the main conduit for the passage of hot fluid to the surface and (4) the gravity and magnetic anomaly plots, regional-residual maps and enhanced data plots all indicate towards the existence of a major geological feature-a large caldera-comprising of Tulu Moye, Bora and Berecha volcanic centers.

Synthesis, characterization, and biological study of new synthetic opioid hemorphin-4 peptides containing sterically restricted nonnatural amino acids.

Some new hemorphin-4 analogs with structures of Xxx-Pro-Trp-Thr-NH2 and Tyr-Yyy-Trp-Thr-NH2, where Xxx is 2-amino-3-(4-hydroxy-2,6-dimethylphenyl)propanoic acid or 2-amino-3-(4-dibenzylamino-2,6-dimethylphenyl)propanoic acid, and Yyy is (2S,4S)-4-amino-pyrrolidine-2-carboxylic acid, were synthesized and characterized by electrochemical and spectral analyses. In vivo anticonvulsant and antinociceptive activities of peptide derivatives were studied after intracerebroventricular injection in mice. The therapeutic effects of the modified peptides on seizures and pain in mice were evaluated to provide valuable insights into the potential applications of the novel compounds. Electrochemical characterization showed that the compounds behave as weak protolytes and that they are in a soluble, stable molecular form at physiological pH values. The antioxidant activity of the peptides was evaluated with voltammetric analyses, which were confirmed by applying the 2,2-Diphenyl-1-picrylhydrazyl method. The compounds showed satisfactory results regarding their structural stability, reaching the desired centers for the manifestation of biological activity without hydrolysis processes at 37°C and physiological pH. Dm-H4 and H4-P1 exhibited 100% and 83% potency to suppress the psychomotor seizures in the 6-Hz test compared to 67% activity of H4. Notably, only the H4-P1 had efficacy in blocking the tonic component in the maximal electroshock test with a potency comparable to H4. All investigated peptides containing unnatural conformationally restricted amino acids showed antinociceptive effects. The analogs Db-H4 and H4-P1 showed the most pronounced and long-lasting effect in both experimental models of pain induced by thermal and chemical stimuli. Dm-H4 produced a dose-dependent thermal antinociception and H4-P2 inhibited only formalin-induced pain behavior.

Detection of quadratic phase coupling by cross-bicoherence and spectral Granger causality in bifrequencies interactions.

Quadratic Phase Coupling (QPC) serves as an essential statistical instrument for evaluating nonlinear synchronization within multivariate time series data, especially in signal processing and neuroscience fields. This study explores the precision of QPC detection using numerical estimates derived from cross-bicoherence and bivariate Granger causality within a straightforward, yet noisy, instantaneous multiplier model. It further assesses the impact of accidental statistically significant bifrequency interactions, introducing new metrics such as the ratio of bispectral quadratic phase coupling and the ratio of bivariate Granger causality quadratic phase coupling. Ratios nearing 1 signify a high degree of accuracy in detecting QPC. The coupling strength between interacting channels is identified as a key element that introduces nonlinearities, influencing the signal-to-noise ratio in the output channel. The model is tested across 59 experimental conditions of simulated recordings, with each condition evaluated against six coupling strength values, covering a wide range of carrier frequencies to examine a broad spectrum of scenarios. The findings demonstrate that the bispectral method outperforms bivariate Granger causality, particularly in identifying specific QPC under conditions of very weak couplings and in the presence of noise. The detection of specific QPC is crucial for neuroscience applications aimed at better understanding the temporal and spatial coordination between different brain regions.

Modelling of Musical Perception using Spectral Knowledge Representation.

We present a novel approach to representing perceptual and cognitive knowledge, spectral knowledge representation, that is focused on the oscillatory behaviour of the brain. The model is presented in the context of a larger hypothetical cognitive architecture. The model uses literal representations of waves to describe the dynamics of neural assemblies as they process perceived input. We show how the model can be applied to representations of sound, and usefully model music perception, specifically harmonic distance. We demonstrate that the model naturally captures both pitch and chord/key distance as empirically measured by Krumhansl and Kessler, thereby providing an underlying mechanism from which their toroidal model might arise. We evaluate our model with respect to those of Milne and others.

Supramolecular architecture of sodium heterocyclic dithiocarbamate salt: Insights from spectral analysis and bond valence sum characterization.

The hydrated sodium salt of 1,2,3,4-tetrahydroquinolinedithiocarbamate (1) has been successfully synthesized and characterized using IR, NMR, and X-ray single crystal analysis. The υC-S and thioureide υC-N bands appeared at 1484 cm-1 and 968 cm-1, respectively, in Na(H2O)3+(thqdtc)- • H2O. The notable NCS2 carbon signal emerged at 212 ppm, credited to unique nitrogen and sulfur-induced deshielding effects. Compound 1 crystallizes in the monoclinic system, P21/c space group, with dimensions a = 14.4297(4) Å, b = 6.1534(2) Å, c = 17.6701(4) Å, ß = 108.7340(10)°, V = 1485.83(7) Å3, and Z = 4. The structure of 1 exhibits a supramolecular architecture through secondary interactions, such as weak intermolecular interactions that link the molecules into a linear polymeric chain. The incorporation of heterocyclic rings in the dithiocarbamate ligands leads to the formation of an intriguing supramolecular architecture, as confirmed by BVS analysis results. The BVS value of sodium does not agree well with the formal oxidation state due to the interactions of anions, cations, coordinated and uncoordinated water molecules.

Altered neural oscillations in classical galactosaemia during sentence production.

Classical galactosaemia (CG) is a hereditary disease in galactose metabolism that despite dietary treatment is characterized by a wide range of cognitive deficits, among which is language production. CG brain functioning has been studied with several neuroimaging techniques, which revealed both structural and functional atypicalities. In the present study, for the first time, we compared the oscillatory dynamics, especially the power spectrum and time-frequency representations (TFR), in the electroencephalography (EEG) of CG patients and healthy controls while they were performing a language production task. Twenty-one CG patients and 19 healthy controls described animated scenes, either in full sentences or in words, indicating two levels of complexity in syntactic planning. Based on previous work on the P300 event related potential (ERP) and its relation with theta frequency, we hypothesized that the oscillatory activity of patients and controls would differ in theta power and TFR. With regard to behavior, reaction times showed that patients are slower, reflecting the language deficit. In the power spectrum, we observed significant higher power in patients in delta (1-3 Hz), theta (4-7 Hz), beta (15-30 Hz) and gamma (30-70 Hz) frequencies, but not in alpha (8-12 Hz), suggesting an atypical oscillatory profile. The time-frequency analysis revealed significantly weaker event-related theta synchronization (ERS) and alpha desynchronization (ERD) in patients in the sentence condition. The data support the hypothesis that CG language difficulties relate to theta-alpha brain oscillations.

Are there effects of light exposure on daytime sleep for rotating shift nurses after night shift?: an EEG power analysis.

Introduction: Night-shift workers often face various health issues stemming from circadian rhythm shift and the consequent poor sleep quality. We aimed to study nurses working night shifts, evaluate the electroencephalogram (EEG) pattern of daytime sleep, and explore possible pattern changes due to ambient light exposure (30 lux) compared to dim conditions (<5 lux) during daytime sleep. Moethods: The study involved 31 participants who worked night shifts and 24 healthy adults who had never worked night shifts. The sleep macro and microstructures were analyzed, and electrophysiological activity was compared (1) between nighttime sleep and daytime sleep with dim light and (2) between daytime sleep with dim and 30 lux light conditions. Results: The daytime sleep group showed lower slow or delta wave power during non-rapid eye movement (NREM) sleep than the nighttime sleep group. During daytime sleep, lower sigma wave power in N2 sleep was observed under light exposure compared to no light exposure. Moreover, during daytime sleep, lower slow wave power in N3 sleep in the last cycle was observed under light exposure compared to no light exposure. Discussion: Our study demonstrated that night shift work and subsequent circadian misalignment strongly affect sleep quality and decrease slow and delta wave activities in NREM sleep. We also observed that light exposure during daytime sleep could additionally decrease N2 sleep spindle activity and N3 waves in the last sleep cycle.

Online Detection of Laser Welding Penetration Depth Based on Multi-Sensor Features.

The accurate online detection of laser welding penetration depth has been a critical problem to which the industry has paid the most attention. Aiming at the laser welding process of TC4 titanium alloy, a multi-sensor monitoring system that obtained the keyhole/molten pool images and laser-induced plasma spectrum was built. The influences of laser power on the keyhole/molten pool morphologies and plasma thermo-mechanical characteristics were investigated. The results showed that there were significant correlations among the variations of the keyhole-molten pool, plasma spectrum, and penetration depth. The image features and spectral features were extracted by image processing and dimension-reduction methods, respectively. Moreover, several penetration depth prediction models based on single-sensor features and multi-sensor features were established. The mean square error of the neural network model built by multi-sensor features was 0.0162, which was smaller than that of the model built by single-sensor features. The established high-precision model provided a theoretical basis for real-time feedback control of the penetration depth in the laser welding process.

Spectral changes in skin blood flow during pressure manipulations or sympathetic stimulation.

Skin blood flow is commonly determined by laser Doppler flowmetry (LDF). It has been suggested that pathophysiological conditions can be assessed by analysis of specific frequency domains of the LDF signals. We tested whether physiological stimuli that activate myogenic and neurogenic mechanisms would affect relevant portions of the laser Doppler spectrum. LDF sensors were placed on the right forearm of 14 healthy volunteers for myogenic (six females) and 13 for neurogenic challenge (five females). Myogenic responses were tested by positioning the arm ∼50° above/below heart level. Neurogenic responses were tested by immersing the left hand into an ice slurry with and without topical application of local anaesthetic. Short-time Fourier analyses were computed over the range of 0.06 to 0.15 Hz for myogenic and 0.02 to 0.06 Hz for neurogenic. No significant differences in spectral density were observed (P = 0.40) in the myogenic range with arm above (7 ± 54 × 10-4 dB) and below heart (7 ± 14 × 10-4 dB). Neurogenic spectral density showed no significant increase from baseline to cold pressor test (0.0017 ± 0.0013 and 0.0038 ± 0.0039 dB; P = 0.087, effect size 0.47). After application of anaesthetic, neurogenic spectral density was unchanged between the baseline and cold pressor test (0.0014 ± 0.0025 and 0.0006 ± 0.0005 dB; P = 0.173). These results suggest that changes in the myogenic and neurogenic spectral density of LDF signals did not fully reflect the skin vascular function activated by pressure manipulation and sympathetic stimulation. Therefore, LDF myogenic and neurogenic spectral density data should be interpreted with caution.

Tilt-evoked, breathing-driven blood pressure oscillations: Independence from baroreflex-sympathoneural function.

PURPOSE: Orthostasis increases the variability of continuously recorded blood pressure (BP). Low-frequency (LF) BP oscillations (Mayer waves) in this setting are related to the vascular-sympathetic baroreflex. Mechanisms of increased high-frequency (HF) BP oscillations at the periodicity of respiration during orthostasis have received less research attention. A previously reported patient with post-neurosurgical orthostatic hypotension (OH) and vascular-sympathetic baroreflex failure had large tilt-evoked, breathing-driven BP oscillations, suggesting that such oscillations can occur independently of vascular-sympathetic baroreflex modulation. In the present study we assessed effects of orthostasis on BP variability in the frequency domain in patient cohorts with or without OH. METHODS: Power spectral analysis of systolic BP variability was conducted on recordings from 73 research participants, 42 with neurogenic OH [13 pure autonomic failure, 14 Parkinson's disease (PD) with OH, 12 parkinsonian multiple system atrophy, and 3 status post-brainstem neurosurgery] and 31 without OH (control group of 16 healthy volunteers and 15 patients with PD lacking OH), before, during, and after 5' of head-up tilt at 90 degrees from horizontal. The data were log transformed for statistical testing. RESULTS: Across all subjects, head-up tilting increased HF power of systolic BP variability (p = 0.001), without a difference between the neurogenic OH and control groups. LF power during orthostasis was higher in the control than in the OH groups (p = 0.009). CONCLUSIONS: The results of this observational cohort study confirm those based on our case report and lead us to propose that even in the setting of vascular-sympathetic baroreflex failure orthostasis increases HF power of BP variability.

Characterization of Vagus Nerve Stimulation (VNS) Dose-Dependent Effects on EEG Power Spectrum and Synchronization.

This study investigates the dose-dependent EEG effects of Vagus Nerve Stimulation (VNS) in patients with drug-resistant epilepsy. This research examines how varying VNS intensities impacts EEG power spectrum and synchronization in a cohort of 28 patients. Patients were categorized into responders, partial-responders, and non-responders based on seizure frequency reduction. The methods involved EEG recordings at incremental VNS intensities, followed by spectral and synchronization analysis. The results reveal significant changes in EEG power, particularly in the delta and beta bands across different intensities. Notably, responders exhibited distinct EEG changes compared to non-responders. Our study has found that VNS intensity significantly influences EEG power topographic allocation and brain desynchronization, suggesting the potential use of acute dose-dependent effects to personalized VNS therapy in the treatment of epilepsy. The findings underscore the importance of individualized VNS dosing for optimizing therapeutic outcomes and highlight the use of EEG metrics as an effective tool for monitoring and adjusting VNS parameters. These insights offer a new avenue for developing individualized VNS therapy strategies, enhancing treatment efficacy in epilepsy.

Condition Monitoring of Pneumatic Drive Systems Based on the AI Method Feed-Forward Backpropagation Neural Network.

Machine condition monitoring is used in a variety of industries as a very efficient strategy for equipment maintenance. This paper presents a study on monitoring a pneumatic system using a feed-forward backpropagation neural network as a classifier and compares the results obtained with different sensor signals and associated extracted features as input for classification. The vibrations of the body of a pneumatic cylinder are acquired using both common industrial sensors and low-cost sensors integrated into an Arduino board. Pressure sensors for both chambers and a position sensor are also used. Power spectral density (PSD) is used to extract features from the acceleration signals, as well as statistical indices. Statistical indices are considered for pressure and position sensors. The results, which are based on experimental data obtained on a test bench, show that a feed-forward neural network makes it possible to identify the operating states with a good degree of reliability. Even with low-cost instrumentation, it is possible to realize reliable condition monitoring based on vibrations. This last result is particularly important as it can help to further increase the uptake of this maintenance approach in the industrial environment.

Spectral analysis of environmental microplastic polyethylene (PE) using average spectra.

In this study, microplastic samples from surface seawater of Tokyo Bay were collected, polyethylene (PE) microplastics were used to calculate carbonyl index (CI), and average spectra of PE were analyzed and compared with a previous study applying agitation during chemical treatment. It was found that PE and polypropylene (PP) were the predominant polymer type in the samples. Among PE samples, fragments were the most commonly observed shape, with white being the dominant color. Deviations were found in the average spectra among different shapes and colors when compared to the standard PE spectrum. A comparison of the average spectra between the two datasets suggests that pronounced peaks related to oxidation are most likely resulted from agitation during the chemical treatment. Additionally, it was found a closer spectral resemblance between the sample spectra and the spectrum of standard sample of oxidized PE (PEOx) than with the standard PE spectrum, suggesting that using the oxidized PE as a reference spectrum might be more effective for identification. These findings highlight the complex factors affecting the spectral properties of microplastics and highlight the importance of understanding these variations to enhance the accuracy of microplastic identification workflows and understanding of environmental fate of microplastics.

Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia.

Sensory processing and sensorimotor integration are abnormal in dystonia, including impaired modulation of beta-corticomuscular coherence. However, cortex-muscle interactions in either direction are rarely described, with reports limited predominantly to investigation of linear coupling, using corticomuscular coherence or Granger causality. Information-theoretic tools such as transfer entropy detect both linear and non-linear interactions between processes. This observational case-control study applies transfer entropy to determine intra- and cross-frequency cortex-muscle coupling in young people with dystonia/dystonic cerebral palsy. Fifteen children with dystonia/dystonic cerebral palsy and 13 controls, aged 12-18 years, performed a grasp task with their dominant hand. Mechanical perturbations were provided by an electromechanical tapper. Bipolar scalp EEG over contralateral sensorimotor cortex and surface EMG over first dorsal interosseous were recorded. Multi-scale wavelet transfer entropy was applied to decompose signals into functional frequency bands of oscillatory activity and to quantify intra- and cross-frequency coupling between brain and muscle. Statistical significance against the null hypothesis of zero transfer entropy was established, setting individual 95% confidence thresholds. The proportion of individuals in each group showing significant transfer entropy for each frequency combination/direction was compared using Fisher's exact test, correcting for multiple comparisons. Intra-frequency transfer entropy was detected in all participants bidirectionally in the beta (16-32 Hz) range and in most participants from EEG to EMG in the alpha (8-16 Hz) range. Cross-frequency transfer entropy across multiple frequency bands was largely similar between groups, but a specific coupling from low-frequency EMG to beta EEG was significantly reduced in dystonia [P = 0.0061 (corrected)]. The demonstration of bidirectional cortex-muscle communication in dystonia emphasizes the value of transfer entropy for exploring neural communications in neurological disorders. The novel finding of diminished coupling from low-frequency EMG to beta EEG in dystonia suggests impaired cortical feedback of proprioceptive information with a specific frequency signature that could be relevant to the origin of the excessive low-frequency drive to muscle.

ANOPOW FOR REPLICATED NONSTATIONARY TIME SERIES IN EXPERIMENTS.

We propose a novel analysis of power (ANOPOW) model for analyzing replicated nonstationary time series commonly encountered in experimental studies. Based on a locally stationary ANOPOW Cramér spectral representation, the proposed model can be used to compare the second-order time-varying frequency patterns among different groups of time series and to estimate group effects as functions of both time and frequency. Formulated in a Bayesian framework, independent two-dimensional second-order random walk (RW2D) priors are assumed on each of the time-varying functional effects for flexible and adaptive smoothing. A piecewise stationary approximation of the nonstationary time series is used to obtain localized estimates of time-varying spectra. Posterior distributions of the time-varying functional group effects are then obtained via integrated nested Laplace approximations (INLA) at a low computational cost. The large-sample distribution of local periodograms can be appropriately utilized to improve estimation accuracy since INLA allows modeling of data with various types of distributions. The usefulness of the proposed model is illustrated through two real data applications: analyses of seismic signals and pupil diameter time series in children with attention deficit hyperactivity disorder. Simulation studies, Supplementary Materials (Li, Yue and Bruce, 2023a), and R code (Li, Yue and Bruce, 2023b) for this article are also available.

Fluorescence spectral analysis and logistic regression modeling for diagnosing basal cell carcinoma on head and neck.

The optical fluorescence method is distinguished by key features such as non-invasiveness, high sensitivity, and resolution, which are superior to traditional diagnostic approaches. Unlike histopathological examinations and biochemical analyses, optical diagnostic methods obviate the need for tissue sampling, enabling the analysis of virtually unlimited material. The research aims to examine the effectiveness of emission spectra analysis in the diagnosis of basal cell carcinoma (BCC) of the scalp and neck. The analysis was based on data provided by Specialized Hospital No. 2 in Bytom comprising a study sample of 10 patients. For each patient, fluorescence emission spectra were recorded from each of 512 points along a 5 mm line. The results obtained from the histopathological examination, the analysis and morphological evaluation of the tissue, and the diagnosis through microscopic observation were used to define a dichotomous variable (presence or absence of a cancerous lesion), adopted in the study as the modeled variable. The next step of the presented study involved constructing a logistic regression model for identifying cancerous lesions depending on the biochemical indicator's relative fluorescence value (RFV) and emission wavelength (ELW) within the 620 nm to 730 nm range. This wavelength range is often used in fluorescence diagnostics to detect various pathologies, including cancerous lesions. The resulting binary logistic regression model, logit(p)=-33.17+0.04ELW+0.01RFV, indicates a statistically significant relationship between wavelength and relative fluorescence values with the probability of detecting cancer. The estimated model exhibits a good fit and high predictive accuracy. The overall model accuracy is 84.8 %, with the correct classification rates at approximately 96 % for healthy individuals and 74 % for individuals with cancer. These findings underscore the potential of photodynamic diagnostics in cancer detection and monitoring.