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Comparison of polynomial and rational function cornea models for effective dimensionality reduction.Computers in Biology and Medicine Dec 2023This study aims to examine geometric models of the corneal surface that can be used to reduce in reasonable time the dimensionality of datasets of normal anterior...
This study aims to examine geometric models of the corneal surface that can be used to reduce in reasonable time the dimensionality of datasets of normal anterior corneas. Polynomial models (P) like Zernike polynomials (ZP) and spherical harmonic polynomials (SHP) were obvious candidates along with their rational function (R) counterparts, namely Zernike rational functions (ZR) and spherical harmonic rational functions (SHR, new model). Knowing that both SHP and ZR were more accurate than ZP for the modeling of normal and keratoconus corneas, it was expected that both spherical harmonic (SH) models (SHP and SHR) would be more accurate than their Zernike (Z) counterparts (ZP and ZR, respectively), and both rational (R) models (SHR and ZR) more accurate than their polynomial counterparts (SHP and ZP, respectively) for a low dimensional space (coefficient number J < 30). This was the case. The SH factor contributed more to accuracy than the R factor. Considering the corneal processing time as a function of J, P models were processed in quasi-linear time with a quasi-null slope and rational models in polynomial time. Z models were faster than SH models, and increasingly so in their R version. In sum, for corneal dimensionality reduction, SHR is the most accurate model, but its processing time is increasingly prohibitive unless the best coefficient combination is identified beforehand. ZP is the fastest model and is reasonably accurate with normal corneas for exploratory tasks. SHP is the best compromise between accuracy and speed.
Topics: Humans; Corneal Topography; Cornea; Keratoconus; Algorithms; Models, Statistical
PubMed: 37952306
DOI: 10.1016/j.compbiomed.2023.107635 -
American Journal of Physiology.... Mar 2016Our growing understanding of the role of the endothelin (ET) system in renal physiology and pathophysiology is from emerging studies of renal disease in animal models... (Review)
Review
Our growing understanding of the role of the endothelin (ET) system in renal physiology and pathophysiology is from emerging studies of renal disease in animal models and humans. ET receptor antagonists reduce blood pressure and proteinuria in chronic kidney disease and cause regression of renal injury in animals. However, the therapeutic potential of ET receptor antagonism has not been fully explored and clinical studies have been largely limited to patients with diabetic nephropathy. There remains a need for more work in nondiabetic chronic kidney disease, end-stage renal disease (patients requiring maintenance dialysis and those with a functioning kidney transplant), ischemia reperfusion injury, and sickle cell disease. The current review summarizes the most recent advances in both preclinical and clinical studies of ET receptor antagonists in the field of kidney disease.
Topics: Animals; Endothelin Receptor Antagonists; Endothelins; Humans; Kidney; Kidney Diseases; Ligands; Receptors, Endothelin; Signal Transduction
PubMed: 26702154
DOI: 10.1152/ajpregu.00478.2015 -
The Science of the Total Environment Apr 2015Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and...
Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods.
PubMed: 25622150
DOI: 10.1016/j.scitotenv.2015.01.008 -
Frontiers in Neuroimaging 2022Previous work in incarcerated men suggests that individuals scoring high on psychopathy exhibit aberrant resting-state paralimbic functional network connectivity (FNC)....
Previous work in incarcerated men suggests that individuals scoring high on psychopathy exhibit aberrant resting-state paralimbic functional network connectivity (FNC). However, it is unclear whether similar results extend to women scoring high on psychopathy. This study examined whether psychopathic traits [assessed the Hare Psychopathy Checklist - Revised (PCL-R)] were associated with aberrant inter-network connectivity, intra-network connectivity (i.e., functional coherence within a network), and amplitude of fluctuations across limbic and surrounding paralimbic regions among incarcerated women ( = 297). Resting-state networks were identified by applying group Independent Component Analysis to resting-state fMRI scans. We tested the association of psychopathic traits (PCL-R Factor 1 measuring interpersonal/affective psychopathic traits and PCL-R Factor 2 assessing lifestyle/antisocial psychopathic traits) to the three FNC measures. PCL-R Factor 1 scores were associated with increased low-frequency fluctuations in executive control and attentional networks, decreased high-frequency fluctuations in executive control and visual networks, and decreased intra-network FNC in default mode network. PCL-R Factor 2 scores were associated with decreased high-frequency fluctuations and default mode networks, and both increased and decreased intra-network functional connectivity in visual networks. Similar to previous analyses in incarcerated men, our results suggest that psychopathic traits among incarcerated women are associated with aberrant intra-network amplitude fluctuations and connectivity across multiple networks including limbic and surrounding paralimbic regions.
PubMed: 37555166
DOI: 10.3389/fnimg.2022.971201 -
Frontiers in Psychology 2021Many authors regard counseling self-efficacy (CSE) as important in therapist development and training. The purpose of this study was to examine the factor structure,...
Many authors regard counseling self-efficacy (CSE) as important in therapist development and training. The purpose of this study was to examine the factor structure, reliability, and validity of the German version of the Counselor Activity Self-Efficacy Scales-Revised (CASES-R). The sample consisted of 670 German psychotherapy trainees, who completed an online survey. We examined the factor structure by applying exploratory and confirmatory factor analysis to the instrument as a whole. A bifactor-exploratory structural equation modeling model with one general and five specific factors provided the best fit to the data. Omega hierarchical coefficients indicated optimal reliability for the general factor, acceptable reliability for the (AS-R) factor, and insufficient estimates for the remaining factors. The CASES-R scales yielded significant correlations with related measures, but also with therapeutic orientations. We found support for the reliability and validity of the German CASES-R. However, the subdomains (except AS-R) should be interpreted with caution, and we do not recommend the CASES-R for comparisons between psychotherapeutic orientations.
PubMed: 34975668
DOI: 10.3389/fpsyg.2021.780088 -
Psychiatry Investigation May 2021To investigate associations between Swedish universities Scales of Personality (SSP) and scales of the following personality instruments: Structured Clinical Interview...
OBJECTIVE
To investigate associations between Swedish universities Scales of Personality (SSP) and scales of the following personality instruments: Structured Clinical Interview for DSM-III-R axis II screening questionnaire (SCID-II screen), revised NEO personality inventory (NEO-PI-R), revised Chapman scales (Chapman) and the psychotic traits questionnaire (STQ).
METHODS
Healthy individuals (n=406) completed self-report personality questionnaires including SSP and at least one more personality inventory. Correlations were calculated between the 13 different SSP subscales as well as SSP's three factors and factors and scales/subscales in SCID-II screen, NEO-PI-R, Chapman and STQ. The main factors of the various instruments were factor analysed. ICC were calculated.
RESULTS
SSP Neuroticism factor correlated with SCID-II cluster C (r=0.71), NEO Neuroticism (r=0.80) and Chapman Social anhedonia (r=0.62). SSP Extraversion factor correlated with NEO Extraversion (r=0.63) and SSP Aggressiveness factor with NEO Agreeableness (r=-0.62). Strong correlations between SSP factors and scales and scales of the other instruments were sparse, although weaker correlations were common.
CONCLUSION
SSP is a useful investigation tool when measuring personality traits related to temperament-like features. SSP partly correlates well to especially three of the NEO-PI-R factors. The different personality inventories are not completely comparable to each other. Instead, they measure personality aspects in partly different ways.
PubMed: 33910329
DOI: 10.30773/pi.2020.0052 -
PLoS Genetics Jun 2023Transposable elements (TE) are mobile DNA sequences whose excessive proliferation endangers the host. Although animals have evolved robust TE-targeting defenses,...
Transposable elements (TE) are mobile DNA sequences whose excessive proliferation endangers the host. Although animals have evolved robust TE-targeting defenses, including Piwi-interacting (pi)RNAs, retrotransposon LINE-1 (L1) still thrives in humans and mice. To gain insights into L1 endurance, we characterized L1 Bodies (LBs) and ORF1p complexes in germ cells of piRNA-deficient Maelstrom null mice. We report that ORF1p interacts with TE RNAs, genic mRNAs, and stress granule proteins, consistent with earlier studies. We also show that ORF1p associates with the CCR4-NOT deadenylation complex and PRKRA, a Protein Kinase R factor. Despite ORF1p interactions with these negative regulators of RNA expression, the stability and translation of LB-localized mRNAs remain unchanged. To scrutinize these findings, we studied the effects of PRKRA on L1 in cultured cells and showed that it elevates ORF1p levels and L1 retrotransposition. These results suggest that ORF1p-driven condensates promote L1 propagation, without affecting the metabolism of endogenous RNAs.
Topics: Humans; Male; Mice; Animals; Retroelements; Ribonucleoproteins; Piwi-Interacting RNA; Spermatocytes; Long Interspersed Nucleotide Elements; RNA; RNA, Messenger; Cytoplasm; RNA, Small Interfering
PubMed: 37307272
DOI: 10.1371/journal.pgen.1010797 -
Environmental Science and Pollution... Jul 2023While some robust artificial intelligence (AI) techniques such as Gene-Expression Programming (GEP), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS)...
While some robust artificial intelligence (AI) techniques such as Gene-Expression Programming (GEP), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS) have been frequently employed in the field of water resources, documents aimed to explore their uncertainty levels are few and far between. Meanwhile, uncertainty determination of these AI models in practical applications is highly important especially when we aimed to use the AI models for streamflow forecast due to the repercussions of poorly managed water resources. With the aid of a global daily streamflow dataset, understanding the uncertainty of GEP, MT, and MARS for forecasting streamflow of natural rivers was studied. The efficiency of uncertainty analysis was quantified by two statistical indicators: 95% Percent Prediction Uncertainty (95%PPU) and R-factor. The results demonstrated that MT had lower uncertainty (95%PPU=0.59 and R-factor=1.67) in comparison with MARS (95%PPU=0.61 and R-factor=1.92) and GEP (95%PPU=0.64 and R-factor=2.03). Overall, although the confidence interval bands of uncertainty for the AI models almost captured the mean streamflow measurements, wide bands of uncertainty were obtained and consequently remarkable uncertainty in the calculation of monthly streamflow values was met.
Topics: Artificial Intelligence; Uncertainty; Lead; Water Resources; Trees; Rivers; Forecasting
PubMed: 37369900
DOI: 10.1007/s11356-023-28236-y -
Personality Disorders Jul 2023Recidivism places a significant burden on society and efforts aimed at reducing cyclical criminal justice involvement are needed. This prospective study tested the...
Recidivism places a significant burden on society and efforts aimed at reducing cyclical criminal justice involvement are needed. This prospective study tested the utility of psychopathic traits in predicting general, felony, and substance-related rearrest in women following release from a correctional facility. The extent to which psychopathic traits offered incremental utility in predicting outcomes, above and beyond other established risk factors, including substance use disorder, was examined. Participants included 327 incarcerated adult women who completed comprehensive clinical and psychiatric assessments prior to release from correctional facilities. Psychopathic traits and lifetime substance use disorder were measured using the Hare Psychopathy Checklist-Revised (PCL-R) and Structured Clinical Interview for DSM-IV-TR Axis I Disorders, respectively. Results showed that general, felony, and substance-related rearrest following institutional release were associated with higher PCL-R Factor 2 scores, assessing lifestyle/behavioral and antisocial/developmental psychopathic traits. Additionally, when controlling for other risk factors associated with recidivism, including age at release, number of prior adult prison terms, and substance use disorder, higher PCL-R Factor 2 scores remained significantly associated with rearrest outcomes in women. Findings inform risk prediction and treatment efforts aimed at reducing recidivism in justice-involved women. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Topics: Adult; Humans; Female; Recidivism; Prospective Studies; Antisocial Personality Disorder; Substance-Related Disorders; Checklist
PubMed: 36595436
DOI: 10.1037/per0000615 -
Journal of Environmental Management Nov 2022One of the greatest threats to maintaining sustainable agro-ecosystems is mitigating the episodic soil loss from farm operations, further exacerbated by meteorological...
One of the greatest threats to maintaining sustainable agro-ecosystems is mitigating the episodic soil loss from farm operations, further exacerbated by meteorological extremes. The Revised Universal Soil Loss Equation (RUSLE) is a model that combines the effects of rain, soil erodibility, topography, land cover, and conservation practices for estimating the annual average soil losses. This study aims to quantify soil water erosion to continental South America (S.A.) through RUSLE using available datasets and characterizing the average sediment delivery rate (SDR) to the major S.A. basins. Soil erodibility was estimated from the Global Gridded Soil Information soil database. LS-factor's topographical parameter was derived from Digital Elevation Models using the "Shuttle Radar Topography Mission" dataset. The R-factor was estimated from a previous study developed for S.A. and the C-factor from the Global Land Cover (Copernicus Global Land Services) database. We used a modeling study for SDR that simulated the annual average sediment transport in 27 basins in S.A. RUSLE set up presented a satisfactory performance compared to other applications on a continental scale with an estimated averaged soil loss for S.A. of 3.8 t ha year. Chile (>20.0 t ha year) and Colombia (8.1 t ha year) showed the highest soil loss. Regarding SDR, Suriname, French Guyana, and Guyana presented the lowest values (<1.0 t ha year). The highest soil losses were found in the Andes Cordillera of Colombia and the Center-South Region of Chile. In the former, the combination of "high" K-factor, "very high" C-factor, and "very high" LS-factor were the leading causes. In the latter, agriculture, livestock, deforestation, and aggressive R-factor explained the high soil loss. Basins with the highest SDR were located in the North Argentina - South Atlantic basin (27.73%), Mar Chiquitita (2.66%), Amazon River basin (2.32%), Magdalena (2.14%) (in Andes Cordillera), and Orinoco (1.83%).
Topics: Chile; Conservation of Natural Resources; Ecosystem; Environmental Monitoring; Geographic Information Systems; Soil; Sustainable Development
PubMed: 35973288
DOI: 10.1016/j.jenvman.2022.115933