Two methods for geometric morphometric analysis of trichodinids from killifishes.

In this study, we compared the efficacy of geometric morphometric techniques, including outlines and landmark-based approaches, to support the differentiation of Trichodina bellottii from three co-occurring killifish species. Both methods were able to differentiate trichodinids from different host species. However, discriminat analyses and MANOVA results based on landmarks had greater accuracy possibly because these analyses only provide information on certain points defined by the researcher, while the analyses based on outlines take into account points with less taxonomic information.

Enhanced forecasting of chlorophyll-a concentration in coastal waters through integration of Fourier analysis and Transformer networks.

The accurate prediction of chlorophyll-a (chl-a) concentration in coastal waters is essential to coastal economies and ecosystems as it serves as the key indicator of harmful algal blooms. Although powerful machine learning methods have made strides in forecasting chl-a concentrations, there remains a gap in effectively modeling the dynamic temporal patterns and dealing with data noise and unreliability. To wiggle out of quagmires, we introduce an innovative deep learning prediction model (termed ChloroFormer) by integrating Transformer networks with Fourier analysis within a decomposition architecture, utilizing coastal in-situ data from two distinct study areas. Our proposed model exhibits superior capabilities in capturing both short-term and middle-term dependency patterns in chl-a concentrations, surpassing the performance of six other deep learning models in multistep-ahead predictive accuracy. Particularly in scenarios involving extreme and frequent blooms, our proposed model shows exceptional predictive performance, especially in accurately forecasting peak chl-a concentrations. Further validation through Kolmogorov-Smirnov tests attests that our model not only replicates the actual dynamics of chl-a concentrations but also preserves the distribution of observation data, showcasing its robustness and reliability. The presented deep learning model addresses the critical need for accurate prediction on chl-a concentrations, facilitating the exploration of marine observations with complex dynamic temporal patterns, thereby supporting marine conservation and policy-making in coastal areas.

Patients with amnestic mild cognitive impairment have higher cerebrovascular impedance than cognitively normal older adults.

Brain hypoperfusion is associated with cognitive impairment. Higher cerebrovascular impedance modulus (Z) may contribute to brain hypoperfusion. We tested hypotheses that patients with amnestic mild cognitive impairment (aMCI) (i.e., those who have a high risk of developing Alzheimer's disease) have higher Z than age-matched cognitively normal individuals, and that high Z is correlated with brain hypoperfusion. Fifty-eight patients with aMCI (67 ± 7 yr) and 25 cognitively normal subjects (CN, 65 ± 6 yr) underwent simultaneous measurements of carotid artery pressure (CAP, via applanation tonometry) and middle cerebral arterial blood velocity (CBV, via transcranial Doppler). Z was quantified using cross-spectral and transfer function analyses between dynamic changes in CBV and CAP. Patients with aMCI exhibited higher Z than NC (1.18 ± 0.34 vs. 1.01 ± 0.35 mmHg/cm/s, P = 0.044) in the frequency range from 0.78 to 4.29 Hz. The averaged Z in the frequency range (0.78-3.13 Hz) of high coherence (>0.9) was inversely correlated with total cerebral blood flow measured with 2-D Doppler ultrasonography normalized by the brain tissue mass (via structural MRI) across both patients with aMCI and NC (r = -0.311, P = 0.007), and in patients with aMCI alone (r = -0.306, P = 0.007). Our findings suggest that patients with aMCI have higher cerebrovascular impedance than cognitively normal older adults and that increased cerebrovascular impedance is associated with brain hypoperfusion.NEW & NOTEWORTHY This is the first study to compare cerebrovascular impedance between patients with amnestic mild cognitive impairment (aMCI) and age-matched cognitively normal individuals. Patients with aMCI had higher cerebrovascular impedance modulus than age-matched cognitively normal individuals, which was correlated with brain hypoperfusion. These results suggest the presence of cerebrovascular dysfunction in the dynamic regulation of cerebral blood flow in older adults who have high risks of Alzheimer's disease.

Biological Basis and Computer Vision Applications of Image Phase Congruency: A Comprehensive Survey.

The concept of Image Phase Congruency (IPC) is deeply rooted in the way the human visual system interprets and processes spatial frequency information. It plays an important role in visual perception, influencing our capacity to identify objects, recognize textures, and decipher spatial relationships in our environments. IPC is robust to changes in lighting, contrast, and other variables that might modify the amplitude of light waves yet leave their relative phase unchanged. This characteristic is vital for perceptual tasks as it ensures the consistent detection of features regardless of fluctuations in illumination or other environmental factors. It can also impact cognitive and emotional responses; cohesive phase information across elements fosters a perception of unity or harmony, while inconsistencies can engender a sense of discord or tension. In this survey, we begin by examining the evidence from biological vision studies suggesting that IPC is employed by the human perceptual system. We proceed to outline the typical mathematical representation and different computational approaches to IPC. We then summarize the extensive applications of IPC in computer vision, including denoise, image quality assessment, feature detection and description, image segmentation, image registration, image fusion, and object detection, among other uses, and illustrate its advantages with a number of examples. Finally, we discuss the current challenges associated with the practical applications of IPC and potential avenues for enhancement.

Geometric morphometric anatomy of the lacrimal punctum in normal population: Punctum update (PUP) study - Paper 5.

BACKGROUND: To investigate the geometric morphological differences of the lacrimal punctum by analyzing its shape in relation to age and sex in a normal population. METHODS: 960 high-magnification slit-lamp images were obtained from 320 puncta of normal asymptomatic Indian individuals across eight decades of life. Using advanced geometric morphometric techniques, including Elliptic Fourier Analysis and Principal Component Analysis, the intricate details of the lacrimal punctum's shape in a diverse population sample were categorized by age and sex. High-resolution images of the lacrimal punctum underwent standardization for scale and orientation, followed by precise landmark identification and coordinate data extraction. RESULTS: The geometric morphometry of the lacrimal punctum shows significant changes as one ages. However, the gender differences, in isolation, without consideration of age, remain subtle and are not pronounced. Interestingly, detailed Principal Component scores analysis revealed potential sex- and age-related variations specifically for the left and right lower puncta, which warrant further investigation. These changes could reflect unique aging changes in the proximal lacrimal drainage system. CONCLUSION: The study is a starting point for geometric morphometric analysis of the lacrimal punctum and provides valuable insights into the punctal changes in size, orientation, and overall morphology across different age groups and between sexes. These findings highlight the significance of considering individual age-wise anatomical variations to better understand the lacrimal punctum.

Nanometric determination of the thickness of aqueous samples for accurate molar absorption coefficients of water-soluble molecules in the mid-infrared region.

Absorption spectra of aqueous samples measured by transmission need to be acquired using very thin cells (5-50 µm) when targeting the mid-infrared (mid-IR) region due to the strong background absorbance of liquid water. The thickness of the cell used controls the pathlength of the light through the sample, a value needed to transform absorption spectra into molar absorption coefficient spectra, or to determine solute concentrations from absorption spectra. The most accurate way to determine the thickness of an empty cell (i.e., filled with air) is from the period of an interference pattern, known as interference fringes, that arises when the cell is placed perpendicular to the path of light in the spectrometer. However, this same approach is not directly applicable to determine the thickness of a cell filled with an aqueous solution, due partially to the smaller amplitude of the interference fringes but fundamentally caused by its complex waveform, with a wavenumber-dependent oscillation period. Here, using Fresnel equations, we derived analytical expressions to model interference fringes in absorption spectra obtained by transmission, which are also valid for aqueous samples. We also present a novel Fourier-based analysis of the interference fringes that, in combination with the derived analytical expressions, allowed us to determine the pathlength of aqueous samples with an error below âˆ¼ 50 nm. We implemented this novel approach to analyze interference fringes as a Live Script running in the software Matlab. As an application, we measured the absorption spectra of a 97 mM solution of MES buffer at pH 3.4 and pH 8.4 using cells of various nominal thicknesses (6, 25 and 50 µm), whose actual thicknesses were determined using the present approach. The derived molar absorption coefficient spectrum for both the acidic and basic forms of MES were virtually identical regardless of the cell, indicating that the determined thicknesses were likely very accurate. These results illustrate the utility of the present methodology in obtaining accurate molar absorption coefficient spectra of water-soluble molecules in the mid-IR region.

Right main pulmonary artery distensibility on dynamic ventilation CT and its association with respiratory function.

BACKGROUND: Heartbeat-based cross-sectional area (CSA) changes in the right main pulmonary artery (MPA), which reflects its distensibility associated with pulmonary hypertension, can be measured using dynamic ventilation computed tomography (DVCT) in patients with and without chronic obstructive pulmonary disease (COPD) during respiratory dynamics. We investigated the relationship between MPA distensibility (MPAD) and respiratory function and how heartbeat-based CSA is related to spirometry, mean lung density (MLD), and patient characteristics. METHODS: We retrospectively analyzed DVCT performed preoperatively in 37 patients (20 female and 17 males) with lung cancer aged 70.6 ± 7.9 years (mean ± standard deviation), 18 with COPD and 19 without. MPA-CSA was separated into respiratory and heartbeat waves by discrete Fourier transformation. For the cardiac pulse-derived waves, CSA change (CSAC) and CSA change ratio (CSACR) were calculated separately during inhalation and exhalation. Spearman rank correlation was computed. RESULT: In the group without COPD as well as all cases, CSACR exhalation was inversely correlated with percent residual lung volume (%RV) and RV/total lung capacity (r = -0.68, p = 0.003 and r = -0.58, p = 0.014). In contrast, in the group with COPD, CSAC inhalation was correlated with MLDmax and MLD change rate (MLDmax/MLDmin) (r = 0.54, p = 0.020 and r = 0.64, p = 0.004) as well as CSAC exhalation and CSACR exhalation. CONCLUSION: In patients with insufficient exhalation, right MPAD during exhalation was decreased. Also, in COPD patients with insufficient exhalation, right MPAD was reduced during inhalation as well as exhalation, which implied that exhalation impairment is a contributing factor to pulmonary hypertension complicated with COPD. RELEVANCE STATEMENT: Assessment of MPAD in different respiratory phases on DVCT has the potential to be utilized as a non-invasive assessment for pulmonary hypertension due to lung disease and/or hypoxia and elucidation of its pathogenesis. KEY POINTS: • There are no previous studies analyzing all respiratory phases of right main pulmonary artery distensibility (MPAD). • Patients with exhalation impairment decreased their right MPAD. • Analysis of MPAD on dynamic ventilation computed tomography contributes to understanding the pathogenesis of pulmonary hypertension due to lung disease and/or hypoxia in patients with expiratory impairment.

Seed shape and size of Silene latifolia, differences between sexes, and influence of the parental genome in hybrids with Silene dioica.

Introduction: Plants undergo various natural changes that dramatically modify their genomes. One is polyploidization and the second is hybridization. Both are regarded as key factors in plant evolution and result in phenotypic differences in different plant organs. In Silene, we can find both examples in nature, and this genus has a seed shape diversity that has long been recognized as a valuable source of information for infrageneric classification. Methods: Morphometric analysis is a statistical study of shape and size and their covariations with other variables. Traditionally, seed shape description was limited to an approximate comparison with geometric figures (rounded, globular, reniform, or heart-shaped). Seed shape quantification has been based on direct measurements, such as area, perimeter, length, and width, narrowing statistical analysis. We used seed images and processed them to obtain silhouettes. We performed geometric morphometric analyses, such as similarity to geometric models and elliptic Fourier analysis, to study the hybrid offspring of S. latifolia and S. dioica. Results: We generated synthetic tetraploids of Silene latifolia and performed controlled crosses between diploid S. latifolia and Silene dioica to analyze seed morphology. After imaging capture and post-processing, statistical analysis revealed differences in seed size, but not in shape, between S. latifolia diploids and tetraploids, as well as some differences in shape among the parentals and hybrids. A detailed inspection using fluorescence microscopy allowed for the identification of shape differences in the cells of the seed coat. In the case of hybrids, differences were found in circularity and solidity. Overal seed shape is maternally regulated for both species, whereas cell shape cannot be associated with any of the sexes. Discussion: Our results provide additional tools useful for the combination of morphology with genetics, ecology or taxonomy. Seed shape is a robust indicator that can be used as a complementary tool for the genetic and phylogenetic analyses of Silene hybrid populations.

Fundamentals of sleep regulation: Model and benchmark values for fractal and oscillatory neurodynamics.

Homeostatic, circadian and ultradian mechanisms play crucial roles in the regulation of sleep. Evidence suggests that ratios of low-to-high frequency power in the electroencephalogram (EEG) spectrum indicate the instantaneous level of sleep pressure, influenced by factors such as individual sleep-wake history, current sleep stage, age-related differences and brain topography characteristics. These effects are well captured and reflected in the spectral exponent, a composite measure of the constant low-to-high frequency ratio in the periodogram, which is scale-free and exhibits lower interindividual variability compared to slow wave activity, potentially serving as a suitable standardization and reference measure. Here we propose an index of sleep homeostasis based on the spectral exponent, reflecting the level of membrane hyperpolarization and/or network bistability in the central nervous system in humans. In addition, we advance the idea that the U-shaped overnight deceleration of oscillatory slow and fast sleep spindle frequencies marks the biological night, providing somnologists with an EEG-index of circadian sleep regulation. Evidence supporting this assertion comes from studies based on sleep replacement, forced desynchrony protocols and high-resolution analyses of sleep spindles. Finally, ultradian sleep regulatory mechanisms are indicated by the recurrent, abrupt shifts in dominant oscillatory frequencies, with spindle ranges signifying non-rapid eye movement and non-spindle oscillations - rapid eye movement phases of the sleep cycles. Reconsidering the indicators of fundamental sleep regulatory processes in the framework of the new Fractal and Oscillatory Adjustment Model (FOAM) offers an appealing opportunity to bridge the gap between the two-process model of sleep regulation and clinical somnology.

Evolution of Plumage Patterns in a Pattern Morphospace: A Phylogenetic Analysis of Melanerpine Woodpeckers.

AbstractPlumage patterns of melanerpine (Melanerpes-Sphyrapicus) woodpeckers are strikingly diverse. Understanding the evolution and function of this diversity is challenging because of the difficulty of quantifying plumage patterns. We use a three-dimensional space to characterize the evolution of melanerpine achromatic plumage patterns. The axes of the space are three pattern features (spatial frequency, orientation, and contrast) quantified using two-dimensional fast Fourier transformation of museum specimen images. Mapping plumage in pattern space reveals differences in how species and subclades occupy the space. To quantify these differences, we derive two new measures of pattern: pattern diversity (diversity across plumage patches within a species) and pattern uniqueness (divergence of patterns from those of other species). We estimate that the melanerpine ancestor had mottled plumage and find that pattern traits across patches and subclades evolve at different rates. We also find that smaller species are more likely to display horizontal face patterning. We promote pattern spaces as powerful tools for investigating animal pattern evolution.

Multifractal Heart Rate Value Analysis: A Novel Approach for Diabetic Neuropathy Diagnosis.

Type 2 diabetes mellitus (T2DM) is characterized by several complications, such as retinopathy, renal failure, cardiovascular disease, and diabetic neuropathy. Among these, neuropathy is the most severe complication, due to the challenging nature of its early detection. The linear Hearth Rate Variability (HRV) analysis is the most common diagnosis technique for diabetic neuropathy, and it is characterized by the determination of the sympathetic-parasympathetic balance on the peripheral nerves through a linear analysis of the tachogram obtained using photoplethysmography. We aimed to perform a multifractal analysis to identify autonomic neuropathy, which was not yet manifest and not detectable with the linear HRV analysis. We enrolled 10 healthy controls, 10 T2DM-diagnosed patients with not-full-blown neuropathy, and 10 T2DM diagnosed patients with full-blown neuropathy. The tachograms for the HRV analysis were obtained using finger photoplethysmography and a linear and/or multifractal analysis was performed. Our preliminary results showed that the linear analysis could effectively differentiate between healthy patients and T2DM patients with full-blown neuropathy; nevertheless, no differences were revealed comparing the full-blown to not-full-blown neuropathic diabetic patients. Conversely, the multifractal HRV analysis was effective for discriminating between full-blown and not-full-blown neuropathic T2DM patients. The multifractal analysis can represent a powerful strategy to determine neuropathic onset, even without clinical diagnostic evidence.

Fourier Phase Analysis of Dynamic Antral Contraction Scintigraphy: New Software, Reference Values, and Comparisons to Conventional Gastric Emptying.

Dynamic antral contraction scintigraphy (DACS) has been used to evaluate for gastric dysmotility by measuring antral contraction frequency and ejection fraction (EF). Fourier phase image analysis has the potential to assess gastric antral contractions for dyssynchrony as has been used for analyzing nuclear cardiology ventriculography (multigated acquisition studies) for cardiac dyssynchrony. The aims of this study were to determine whether Fourier phase analysis helps to characterize antral motility physiology, whether Fourier phase analysis correlates with conventional gastric emptying scintigraphy (GES), and which DACS parameters may aid in diagnosing gastric dysmotility, particularly delayed gastric emptying (GE). Methods: DACS and GES of healthy volunteers (n = 22) were compared with patients (n = 99) with symptoms of gastroparesis. New DACS Fourier phase analysis software was developed. Results: GE was delayed (n = 53) or normal (n = 46) in patients. There was a linear correlation between the time for the stomach to empty 50% of the meal and the percentage total proximal and distal in-phase antral pixels at 30 min (r = 0.37, P = 0.0001) and 60 min (r = 0.26, P = 0.007). In healthy volunteers, the mean proximal-to-distal ratio of in-phase antral pixels increased from 1.67 (30 min) to 2.65 (120 min) (P = 0.035), and EF increased from 23% (30 min) to 32% (120 min) (P = 0.022). Multivariable regressions of percentage total proximal and distal in-phase antral pixels (30 min) and EF (60 min) were the best predictors of abnormal GE (adjusted odds ratio, 3.30 [95% CI, 1.21-9.00] and 2.97 [95% CI, 1.08-8.21], respectively). Conclusion: This study used Fourier phase analysis to analyze DACS in healthy volunteers and patients with symptoms of gastroparesis. In addition to establishing reference values, new physiologic information on antral motility was obtained. In healthy volunteers, there was an increasing proximal-to-distal ratio of in-phase antral pixels and antral EF over time after meal ingestion. The percentage total proximal and distal in-phase antral pixels at both 30 and 60 min correlated well with GE values for the time for the stomach to empty 50% of the meal. For symptomatic patients, the percentage total proximal and distal in-phase antral pixels at 30 min and the EF at 60 min after meal ingestion correlated with delayed GE on conventional GES. Thus, Fourier phase analysis of DACS appears to have potential to further aid in diagnosing gastric dysmotility in GES.

Improved assessment sensitivity of time-varying cavitation events based on wavelet analysis.

Ultrasonic cavitation, characterized by the oscillation or abrupt collapse of cavitation nuclei in response to ultrasound stimulation, plays a significant role in various applications within both industrial and biomedical sectors. In particular, inertial cavitation (IC) has garnered considerable attention due to the resulting mechanical, chemical, and thermal effects. Passive cavitation detection (PCD) has emerged as a valuable technique for monitoring this procedure. While the fast Fourier transform (FFT) is a widely used algorithm to analyze IC-induced broadband noise detected by PCD system, it may not adequately capture the time-varying instability of cavitation due to potential nuclei collapse during ultrasound irradiation. In contrast, the continuous wavelet transform offers a more flexible approach, enabling more sensitive analysis of signals with varying frequencies over time. In this study, nanodiamond (ND) and its derivative, nitro-doped nanodiamond (N-AND), known to possess cavitation potential from previous research, were chosen as the source of cavitation nuclei. The cavitation signals detected by PCD were subjected to both FFT and wavelet analyses, with their results comprehensively compared. This research showcased the feasibility of employing wavelet analysis for effective inertial cavitation evaluation. It provided the advantage of monitoring the temporal evolution of cavitation events in real-time, enhancing sensitivity to weak and unstable cavitation signals, especially those in higher order components (3rd and 4th order). Additionally, it yielded a higher level of precision in determining IC thresholds and doses. Furthermore, the inclusion of time information through wavelet analysis offered insights into the limitations of low-cycle ultrasound in inducing IC. This study introduces a novel perspective for more sensitive and precise cavitation assessment, leveraging time and frequency data from wavelet analysis, and holds promise for effective utilization of cavitation effects while minimizing losses and damages resulting from unintended cavitation events.

Plasma Volume Oscillations during Fluid Therapy in Humans.

INTRODUCTION: Oscillations are frequently observed on plasma dilution curves during intravenous fluid therapy. This study aimed to examine how common these oscillations are and what they represent. METHODS: Fourier transforms were used to analyze the residuals obtained during fitting of a volume kinetic model to 269 plasma dilution curves. Oscillating patterns were identified in two-thirds of the fluid infusion experiments. RESULTS: The wave frequency usually had a dominating frequency of 1 h or multiples thereof. The wave amplitudes varied between 1% and 4% of the plasma volume. The "peak-to-peak" amplitudes were then twice as large, which corresponded to blood volume changes of 60-240 mL. A population kinetic analysis of the distribution of infused fluid between body fluid compartments was then applied to search for clues that could explain the oscillations. This analysis showed that amplitudes >1.5% were associated with doubled turnover of fluid in a fast-exchange interstitial fluid compartment and, together with data on plasma albumin, suggested that oscillations might represent bursts of efferent lymph. CONCLUSIONS: Oscillations with very low frequency were often observed on plasma dilution-time curves obtained during fluid therapy. They were associated with fast turnover of interstitial fluid and can possibly have resulted from accelerated lymphatic flow.

Bulk-fill composite in challenging cavities: conversion rate, solubility, and water absorption analysis.

In a deep, curved cavity, polymerization of a bulk fill composite can be challenging. The aim of this study was to investigate the solubility, water absorption, and conversion rate of bulk-fill composite samples prepared using molds with various slope angles. Bulk-fill composite resin (Filtek One Bulk Fill) was placed into cylindrical Teflon molds with a depth of 4 mm, angled at varying degrees (90°, 75°, 60°, 45°). Two different LED light-curing units (VALO Cordless, iLed Curing Light) were used to cure the samples. Polymerizations were performed at three different distances (0 mm, 2 mm, and 4 mm). Five samples per group were used, resulting in a total of 24 groups. The Fourier Transform Infrared Spectrometer was utilized to evaluate the conversion levels of the samples. Water sorption and solubility values were determined by storing the composites in distilled water at 37 °C for 21 days. The VALO light-curing unit applied closest to samples inserted in a 90° angulation mold had the highest mean degree of conversion (41.55%), while iLED light-curing unit group that applied from 4 mm to the samples inserted in a 45° angulation mold had the lowest mean conversion (8.97%). The angle of the cavity and the distance at which the light-curing unit is applied significantly affected bulk-fill composite resin conversion. In addition, the choice of light-curing unit impacted the conversion levels. However, with the tested conditions, the water sorption and solubility values of polymerized composite resin samples remain unaffected by these factors.

Improved cerebrovascular reactivity mapping using coherence weighted general linear model in the frequency domain.

Cerebrovascular reactivity (CVR) is a prognostic indicator of cerebrovascular health. Estimating CVR from endogenous end-tidal carbon dioxide (CO2) fluctuation and MRI signal recorded under resting state can be difficult due to the poor signal-to-noise ratio (SNR) of signals. Thus, we aimed to improve the method of estimating CVR from end-tidal CO2 and MRI signals. We proposed a coherence weighted general linear model (CW-GLM) to estimate CVR from the Fourier coefficients weighted by the signal coherence in frequency domain, which confers two advantages. First, it requires no signal alignment in time domain, which simplifies experimental methods. Second, it limits the GLM analysis within the frequency band where CO2 and MRI signals are highly correlated, which automatically suppresses noise and nuisance signals. We compared the performance of our method with time-domain GLM (TD-GLM) and frequency-domain GLM (FD-GLM) in both synthetic and in-vivo data; wherein we calculated CVR from signals recorded under both resting state and sinusoidal stimulus. In synthetic data, CW-GLM has a remarkable performance on CVR estimation from narrow band signals with a mean-absolute error of 0.7 % (gray matter) and 1.2 % (white matter), which was lower than all the other methods. Meanwhile, CW-GLM maintains a comparable performance on CVR estimation from resting signals, with a mean-absolute error of 4.1 % (gray matter) and 8 % (white matter). The superior performance was maintained across the 36 in-vivo measurements, with CW-GLM exhibiting limits of agreement of -16.7 % - 9.5 % between CVR calculated from the resting and sinusoidal CO2 paradigms which was 12 % - 209 % better than current time-domain methods. Evaluating of the cross-coherence spectrum revealed highest signal coherence within the frequency band from 0.01 Hz to 0.05 Hz, which overlaps with previously recommended frequency band (0.02 Hz to 0.04 Hz) for CVR analysis. Our data demonstrates that CW-GLM can work as a self-adaptive band-pass filter to improve CVR robustness, while also avoiding the need for signal temporal alignment.

Dataset of quality assurance measurements of rhythmic movements.

A low-cost quantitative structured office measurement of movements in the extremities of people with Parkinson's disease [1,2] was performed on participants with Parkinson's disease and multiple system atrophy as well as age- and sex-matched healthy participants with typical development. Participants underwent twelve videotaped procedures rated by a trained examiner while connected to four accelerometers [1,2] generating a trace of the three location dimensions expressed as spreadsheets [3,4]. The signals of the five repetitive motion items (3.4 Finger tapping, 3.5 Hand movements, 3.6 Pronation-supination movements of hands, 3.7 Toe tapping, and 3.8 Leg agility) [1] underwent processing to fast Fourier [5] and amor and bump continuous wavelet transforms [6], [7], [8], [9], [10], [11], [12], [13]. Images of the signals and their transforms [4], [5], [6] of the five repetitive tasks of each participant were randomly expressed as panels on an electronic framework for rating by 35 trained examiners who did not know the source of the original output [14]. The team of international raters completed ratings of the signals and their transforms independently using criteria like the scoring systems for live assessments of movements in human participants [1,2]. The raters scored signals and transforms for deficits in the sustained performance of rhythmic movements (interruptions, slowing, and amplitude decrements) often observed in people with Parkinson's disease [15], [16], [17], [18], [19], [20]. Raters were first presented the images of the signals and transforms of a man with multiple system atrophy as a test and a retest in a different random order. After the raters completed the assessments of the man with multiple system atrophy, they were presented random test and retest panels of the images of signals and transforms of ten participants with Parkinson's disease who completed a single rating session. After the raters completed the assessments of the participants with Parkinson's disease who completed one set of ratings, they were presented random test and retest panels of the images of signals and transforms of (A) ten participants with Parkinson's disease and (B) eight age- and sex-match healthy participants with typical development who completed two rating session separated by a month or more [15], [16], [17], [18], [19], [20]. The data provide a framework for further analysis of the acquired information. Additionally, the data provide a template for the construction of electronic frameworks for the remote analysis by trained raters of signals and transforms of rhythmic processes to verify that the systems are operating smoothly without interruptions or changes in frequency and amplitude. Thus, the data provide the foundations to construct electronic frameworks for the virtual quality assurance of a vast spectrum of rhythmic processes. The dataset is a suitable template for solving unsupervised and supervised machine learning algorithms. Readers may utilize this procedure to assure the quality of rhythmic processes by confirming the absence of deviations in rate and rhythm. Thus, this procedure provides the means to confirm the quality of the vast spectrum of rhythmic processes.

Oblique Vibratory Surface Grinding-Experimental Study.

The article reports the results of experimental study of vibratory surface grinding in the range of low excitation frequencies and variable directions of excited vibrations in the plane of the table, and investigates the effect of these directions on the roughness and waviness of the ground surface. The tests were conducted on a production surface grinder with a vibrating table on which the samples were mounted. The table made it possible to change the direction for the introduction of vibrations to the workpiece (longitudinally, transversely, and obliquely to the longitudinal feed of the table) and the parameters of the introduced vibrations, frequency and amplitude. In the course of the study, selected parameters of surface roughness and waviness of samples ground conventionally and with vibrations introduced on the workpiece were compared. The results show an improvement in the roughness and waviness parameters of the vibration-ground surfaces compared to surfaces ground without vibration (conventionally). The profile of the ground surface was subjected to Fourier analysis and the harmonic components of the surface shape of the ground samples were determined to characterize the effect of the introduced vibrations on the surface roughness. It was determined that the direction of vibration introduction, which is most favorable in terms of the parameters of the geometric structure of the ground surface, is the direction perpendicular to the longitudinal feed of the grinding table. In other directions of vibration introduction, the simultaneous effect of improving both parameters of the geometric structure of the ground surface profile was not obtained.

Hierarchical network structure as the source of hierarchical dynamics (power-law frequency spectra) in living and non-living systems: How state-trait continua (body plans, personalities) emerge from first principles in biophysics.

Living systems are hierarchical control systems that display a small world network structure. In such structures, many smaller clusters are nested within fewer larger ones, producing a fractal-like structure with a 'power-law' cluster size distribution (a mereology). Just like their structure, the dynamics of living systems shows fractal-like qualities: the timeseries of inner message passing and overt behavior contain high frequencies or 'states' (treble) that are nested within lower frequencies or 'traits' (bass), producing a power-law frequency spectrum that is known as a 'state-trait continuum' in the behavioral sciences. Here, we argue that the power-law dynamics of living systems results from their power-law network structure: organisms 'vertically encode' the deep spatiotemporal structure of their (anticipated) environments, to the effect that many small clusters near the base of the hierarchy produce high frequency signal changes and fewer larger clusters at its top produce ultra-low frequencies. Such ultra-low frequencies exert a tonic regulatory pressure that produces morphological as well as behavioral traits (i.e., body plans and personalities). Nested-modular structure causes higher frequencies to be embedded within lower frequencies, producing a power-law state-trait continuum. At the heart of such dynamics lies the need for efficient energy dissipation through networks of coupled oscillators, which also governs the dynamics of non-living systems (e.q., earthquakes, stock market fluctuations). Since hierarchical structure produces hierarchical dynamics, the development and collapse of hierarchical structure (e.g., during maturation and disease) should leave specific traces in system dynamics (shifts in lower frequencies, i.e. morphological and behavioral traits) that may serve as early warning signs to system failure. The applications of this idea range from (bio)physics and phylogenesis to ontogenesis and clinical medicine.

Deciphering the mandibular shape variation in a group of Malagasy primates using Fourier outline analysis.

OBJECTIVES: Among living Malagasy primates, the family Lemuridae has previously been recognized as presenting a higher mandibular morphological variation than other families. We conducted a quantitative analysis of mandibular size and shape within the five genera (Lemur, Eulemur, Hapalemur, Prolemur, and Varecia) associated with a set of covariables that could explain this variation. MATERIALS AND METHODS: We used Fourier outline analysis on the left hemimandible of 182 specimens covering the Lemuridae family. The influence of the phylogeny but also seven covariables (genus, diet, sex, sexual behavior, mating system, ecoregion, and forest type) on mandibular variation was examined using multivariate statistics and model selection. RESULTS: Our results indicate that the high level of morphological variation within the family, associated with a phylogenetic effect and differences in diet, is due to a strong distinction between the genera Prolemur and Hapalemur and the other genera of the family. A second analysis, correcting this strong effect, indicates that mandibular shape variation is influenced not only by the phylogeny and the diet but by a combination of all the covariables. DISCUSSION: The analysis of morphological variation is a powerful tool with major applications, both for the estimation of biological diversity and for the understanding of the fundamental parameters of species' ecology. Our work indicates that, if mandibular shape variation is mainly driven by dietary adaptation, other variables describing ecology and habitat should be considered and taken into account for an integrative understanding of species resources and the establishment of conservation measures.