Discrimination of Bedform Scales Using Robust Spline Filters and Wavelet Transforms: Methods and Application to Synthetic Signals and the Rio Parana, Argentina

Currently, there is no standard nomenclature and procedure to systematically identify the scale and magnitude of bedforms such as bars, dunes and ripples that are commonly present in many sedimentary environments. This thesis proposes a standardization of the nomenclature and symbolic representation of bedforms, and details the combined application of robust spline filters and continuous wavelet transforms to discriminate these morphodynamic features, namely bedform hierarchies (BHs). The proposed methodology for bedform discrimination is applied to synthetic bedform signals, which are sampled at a Nyquist ratio interval of 5 to 100 and a signal-to-noise ratio interval of 1 to 20, and to a detailed 3D bed survey of the Rio Parana, Argentina, which exhibits large-scale dune bedforms with superimposed, smaller bedforms. After discriminating the synthetic bedform signals into 3 BHs that represent bars, dunes and ripples, the accuracy of the methodology is quantified by estimating the reproducibility, the cross correlation and the standard deviation ratio of the actual and retrieved signals. For the case of the field measurements, the proposed method is used to discriminate small and large dunes; and subsequently, obtain and statistically analyze the common morphological descriptors such as wavelength, slope, and amplitude for both stoss and lee sides of these different size bedforms. The analysis of the synthetic signals demonstrates that the Morlet wavelet function is the most efficient in retrieving smaller periodicities such as ripples and that the proposed methodology effectively discriminate the waves of different periodicities scales for Nyquist ratios higher than 50 and signal-to-noise ratios. The analysis of the bedforms of the Parana River reveals that in most cases, a Gamma probability distribution (with a positive skewness) best describes the dimensionless wavelength and amplitude for both the lee and stoss sides of large dunes. For the case of the smaller superimposed dunes, the dimensionless wavelength shows a discrete behavior governed by the sampling frequency of the data, and the dimensionless amplitude better fits the Gamma probability distribution, again with a positive skewness

Statistical Characterization of Morphodynamic Signals Using Wavelet Analysis

Morphodynamic and hydrodynamic properties are concomitantly part of the entire dynamic of river systems and commonly present both temporal and spatial persistent variability. Therefore, the study of both river morphodynamic signals (e.g. bed forms and meandering and anabranching river morphometrics) and hydrodynamic signals (e.g. velocity fields, sediment concentrations) requires both temporal and spatial multi-scale signal representations. The present research is focused on the former type of signals and it is a first attempt to discriminate such signals and, subsequently, develop the theoretical background to link these processes at different spatial and temporal scales and determine the scales that have more influence on river evolution. The main contribution of this study are: [1] to design a methodology to discriminate bed form features (e.g. bars, dunes and ripples) via the combined application of robust spline filters and one-dimensional continuous wavelet transforms, allowing the quantitative recognition of bed form hierarchies. The methodology was tested by using synthetic bed form signals and subsequently applied to the analysis of bed form features from the Parana River, Argentina. [2] To develop a methodology for the statistical analysis of the spatial distribution of meandering rivers morphometrics by coupling the capabilities of one-dimensional wavelet transforms, principal component analysis and Frechet distance. A universal river classification method is also proposed. [3] To perform a novel study of the planimetric configuration of confluences in tropical free meandering rivers located in the upper Amazon catchment. River confluences in tropical environments represent areas where biota is concentrated; therefore, a better understanding and characterization of these features has a particular importance for the Amazonian ecosystem. [4] To evaluate the potential of two-dimensional wavelet transforms in the analysis of bed form features. The broader impact will be an improved understanding of river morphodynamics of the upper Amazon River for practical applications such as navigability. Furthermore, the project will provide an updated statistical analysis of the meandering rivers dynamics for practical applications, including erosion control, river ecology, and habitat restoration. The developed statistical tool will be included as an application of the RVR Meander platform (www.rvrmeander.org), which is a broadly used software for river restoration

Removal of Color and Turbidity in Runoff Water using Coconut (Cocos Nucifera) Endocarp Activated Carbon

The aim of this research was to determine the efficiency of activated carbon obtained from coconut (Cocos nucifera) endocarp in the reduction of color in runoff water to improve its quality. For this purpose, activated carbon was produced at a carbonization temperature of 700 °C in a time of 30 minutes and phosphoric acid at a concentration of 85% was used as an activating agent. A completely randomized design was used, consisting of 3 treatments (100, 50 and 25 g of activated carbon) and a control (without treatment), with three replicates of each treatment, where 1 L of water from the uptake was filtered. It was determined that the best percentage removal was obtained with treatment 3 (T3) in the reduction of color and turbidity with average values of 97.56% and 97.11%, respectively. An activated carbon filter was installed in the San Lorenzo - Moyobamba sector in a similar way to the laboratory tests, in which the efficiency of this product in reducing the color and turbidity of the water was demonstrated, achieving values suitable for human consumption

A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression among University Students:A Secondary Analysis of a Randomized Clinical Trial

Importance: Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT. Objective: To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors. Design, Setting, and Participants: This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022. Interventions: Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435). Main Outcomes and Measures: Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline. Results: The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P =.003) or treatment as usual (40.0% [2.7%]; P =.001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P =.007; self-guided i-CBT: 25.4% [8.8%]; P =.004; treatment as usual: 31.0% [9.4%]; P =.001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P =.14; treatment as usual: 53.0% [6.0%]; P =.25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P =.001; treatment as usual: 41.8% [3.2%]; P &lt;.001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P =.07). Conclusions and Relevance: Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings. Trial Registration: ClinicalTrials.gov Identifier: NCT04780542.</p

A randomized trial of multivitamin supplementation in children with tuberculosis in Tanzania

Children with tuberculosis often have underlying nutritional deficiencies. Multivitamin supplementation has been proposed as a means to enhance the health of these children; however, the efficacy of such an intervention has not been examined adequately. 255 children, aged six weeks to five years, with tuberculosis were randomized to receive either a daily multivitamin supplement or a placebo in the first eight weeks of anti-tuberculous therapy in Tanzania. This was only 64% of the proposed sample size as the trial had to be terminated prematurely due to funding constraints. They were followed up for the duration of supplementation through clinic and home visits to assess anthropometric indices and laboratory parameters, including hemoglobin and albumin. There was no significant effect of multivitamin supplementation on the primary endpoint of the trial: weight gain after eight weeks. However, significant differences in weight gain were observed among children aged six weeks to six months in subgroup analyses (n=22; 1.08 kg, compared to 0.46 kg in the placebo group; 95% CI=0.12, 1.10; p=0.01). Supplementation resulted in significant improvement in hemoglobin levels at the end of follow-up in children of all age groups; the median increase in children receiving multivitamins was 1.0 g/dL, compared to 0.4 g/dL in children receiving placebo (p<0.01). HIV-infected children between six months and three years of age had a significantly higher gain in height if they received multivitamins (n=48; 2 cm, compared to 1 cm in the placebo group; 95% CI=0.20, 1.70; p=0.01; p for interaction by age group=0.01). Multivitamin supplementation for a short duration of eight weeks improved the hematological profile of children with tuberculosis, though it didn't have any effect on weight gain, the primary outcome of the trial. Larger studies with a longer period of supplementation are needed to confirm these findings and assess the effect of multivitamins on clinical outcomes including treatment success and growth failure. CLINICALTRIALS.GOV IDENTIFIER: NCT00145184

A new synaptic player leading to autism risk: Met receptor tyrosine kinase

The validity for assigning disorder risk to an autism spectrum disorder (ASD) candidate gene comes from convergent genetic, clinical, and developmental neurobiology data. Here, we review these lines of evidence from multiple human genetic studies, and non-human primate and mouse experiments that support the conclusion that the MET receptor tyrosine kinase (RTK) functions to influence synapse development in circuits relevant to certain core behavioral domains of ASD. There is association of both common functional alleles and rare copy number variants that impact levels of MET expression in the human cortex. The timing of Met expression is linked to axon terminal outgrowth and synaptogenesis in the developing rodent and primate forebrain, and both in vitro and in vivo studies implicate this RTK in dendritic branching, spine maturation, and excitatory connectivity in the neocortex. This impact can occur in a cell-nonautonomous fashion, emphasizing the unique role that Met plays in specific circuits relevant to ASD

Expansion of Signal Transduction Pathways in Fungi by Extensive Genome Duplication

International audienceno abstrac

Identification and Functional Analysis of Light-Responsive Unique Genes and Gene Family Members in Rice

Functional redundancy limits detailed analysis of genes in many organisms. Here, we report a method to efficiently overcome this obstacle by combining gene expression data with analysis of gene-indexed mutants. Using a rice NSF45K oligo-microarray to compare 2-week-old light- and dark-grown rice leaf tissue, we identified 365 genes that showed significant 8-fold or greater induction in the light relative to dark conditions. We then screened collections of rice T-DNA insertional mutants to identify rice lines with mutations in the strongly light-induced genes. From this analysis, we identified 74 different lines comprising two independent mutant lines for each of 37 light-induced genes. This list was further refined by mining gene expression data to exclude genes that had potential functional redundancy due to co-expressed family members (12 genes) and genes that had inconsistent light responses across other publicly available microarray datasets (five genes). We next characterized the phenotypes of rice lines carrying mutations in ten of the remaining candidate genes and then carried out co-expression analysis associated with these genes. This analysis effectively provided candidate functions for two genes of previously unknown function and for one gene not directly linked to the tested biochemical pathways. These data demonstrate the efficiency of combining gene family-based expression profiles with analyses of insertional mutants to identify novel genes and their functions, even among members of multi-gene families

Common Limitations of Image Processing Metrics:A Picture Story

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide.Comment: This is a dynamic paper on limitations of commonly used metrics. The current version discusses metrics for image-level classification, semantic segmentation, object detection and instance segmentation. For missing use cases, comments or questions, please contact [email protected] or [email protected]. Substantial contributions to this document will be acknowledged with a co-authorshi

The predictive validity of a Brain Care Score for dementia and stroke: data from the UK Biobank cohort

IntroductionThe 21-point Brain Care Score (BCS) was developed through a modified Delphi process in partnership with practitioners and patients to promote behavior changes and lifestyle choices in order to sustainably reduce the risk of dementia and stroke. We aimed to assess the associations of the BCS with risk of incident dementia and stroke.MethodsThe BCS was derived from the United Kingdom Biobank (UKB) baseline evaluation for participants aged 40–69 years, recruited between 2006–2010. Associations of BCS and risk of subsequent incident dementia and stroke were estimated using Cox proportional hazard regressions, adjusted for sex assigned at birth and stratified by age groups at baseline.ResultsThe BCS (median: 12; IQR:11–14) was derived for 398,990 UKB participants (mean age: 57; females: 54%). There were 5,354 incident cases of dementia and 7,259 incident cases of stroke recorded during a median follow-up of 12.5 years. A five-point higher BCS at baseline was associated with a 59% (95%CI: 40-72%) lower risk of dementia among participants aged &lt;50. Among those aged 50–59, the figure was 32% (95%CI: 20-42%) and 8% (95%CI: 2-14%) for those aged &gt;59 years. A five-point higher BCS was associated with a 48% (95%CI: 39-56%) lower risk of stroke among participants aged &lt;50, 52% (95%CI, 47-56%) among those aged 50–59, and 33% (95%CI, 29-37%) among those aged &gt;59.DiscussionThe BCS has clinically relevant and statistically significant associations with risk of dementia and stroke in approximately 0.4 million UK people. Future research includes investigating the feasibility, adaptability and implementation of the BCS for patients and providers worldwide