Hodge-Decomposition of Brain Networks

We analyze brain networks by decomposing them into three orthogonal components: gradient, curl, and harmonic flows, through the Hodge decomposition, a technique advantageous for capturing complex topological features. A Wasserstein distance based topological inference is developed to determine the statistical significance of each component. The Hodge decomposition is applied to human brain networks obtained from a resting-state fMRI study. Our results indicate statistically significant differences in the topological features between male and female brain networks.Comment: Will be published in ISBI 202

Topological Data Analysis of Human Brain Networks Through Order Statistics

Understanding the topological characteristics of the brain network across a population is central to understanding brain functions. The abstraction of human connectome as a graph has been pivotal in gaining insights on the topological features of the brain network. The development of group-level statistical inference procedures in brain graphs while accounting for the heterogeneity and randomness still remains a difficult task. In this study, we develop a robust statistical framework based on persistent homology using the order statistics for analyzing brain networks. The use of order statistics greatly simplifies the computation of the persistent barcodes. We validate the proposed methods using comprehensive simulation studies and subsequently apply to the resting-state functional magnetic resonance images. We conclude a statistically significant topological difference between the male and female brain networks

Empowering Communication: Speech Technology for Indian and Western Accents through AI-powered Speech Synthesis

Neural Text-to-speech (TTS) synthesis is a powerful technology that can generate speech using neural networks. One of the most remarkable features of TTS synthesis is its capability to produce speech in the voice of different speakers. This paper introduces voice cloning and speech synthesis https://pypi.org/project/voice-cloning/ an open-source python package for helping speech disorders to communicate more effectively as well as for professionals seeking to integrate voice cloning or speech synthesis capabilities into their projects. This package aims to generate synthetic speech that sounds like the natural voice of an individual, but it does not replace the natural human voice. The architecture of the system comprises a speaker verification system, a synthesizer, a vocoder, and noise reduction. Speaker verification system trained on a varied set of speakers to achieve optimal generalization performance without relying on transcriptions. Synthesizer is trained using both audio and transcriptions that generate Mel spectrogram from a text and vocoder which converts the generated Mel Spectrogram into corresponding audio signal. Then the audio signal is processed by a noise reduction algorithm to eliminate unwanted noise and enhance speech clarity. The performance of synthesized speech from seen and unseen speakers are then evaluated using subjective and objective evaluation such as Mean Opinion Score (MOS), Gross Pitch Error (GPE), and Spectral distortion (SD). The model can create speech in distinct voices by including speaker characteristics that are chosen randomly

Weighted persistent homology for biomolecular data analysis

In this paper, we systematically review weighted persistent homology (WPH) models and their applications in biomolecular data analysis. Essentially, the weight value, which reflects physical, chemical and biological properties, can be assigned to vertices (atom centers), edges (bonds), or higher order simplexes (cluster of atoms), depending on the biomolecular structure, function, and dynamics properties. Further, we propose the first localized weighted persistent homology (LWPH). Inspired by the great success of element specific persistent homology (ESPH), we do not treat biomolecules as an inseparable system like all previous weighted models, instead we decompose them into a series of local domains, which may be overlapped with each other. The general persistent homology or weighted persistent homology analysis is then applied on each of these local domains. In this way, functional properties, that are embedded in local structures, can be revealed. Our model has been applied to systematically studying DNA structures. It has been found that our LWPH based features can be used to successfully discriminate the A-, B-, and Z-types of DNA. More importantly, our LWPH based PCA model can identify two configurational states of DNA structure in ion liquid environment, which can be revealed only by the complicated helical coordinate system. The great consistence with the helical-coordinate model demonstrates that our model captures local structure variations so well that it is comparable with geometric models. Moreover, geometric measurements are usually defined in very local regions. For instance, the helical-coordinate system is limited to one or two basepairs. However, our LWPH can quantitatively characterize structure information in local regions or domains with arbitrary sizes and shapes, where traditional geometrical measurements fail.Comment: 27 pages; 18 figure

Strength Evaluation of Functionalized MWCNT-Reinforced Polymer Nanocomposites Synthesized Using a 3D Mixing Approach

The incorporation of carboxyl functionalized multi-walled carbon nanotube (MWCNT- COOH) into a polymethyl methacrylate (PMMA) has been investigated. The resultant tensile and flexural mechanical properties have been determined. In this paper, a novel synthesis process for a MWCNT-reinforced polymer nanocomposite is proposed. The proposed method significantly eliminates the most challenging issues of the nano-dispersed phase, including agglomeration and non-homogeneous mixing within a given matrix material, and also resolves the issues occurring in conventional mixing processes. The results of scanning electron microscopy support these claims. This 3D-mixing process is followed by an extrusion process, using a twin-screw extruder for pristine MWCNT, and a compression molding process for COOH-MWCNT, to prepare test specimens for experimentally determining the mechanical properties. The test specimens are fabricated using 0.1, 0.5, and 1.0 wt.% MWCNT, with a remaining PMMA phase. The testing is conducted according to ASTM D3039 and ASTM D7264 standards. Significant improvements of 25.41%, 35.85%, and 31.75% in tensile properties and 18.27%, 48%, and 33.33% in flexural properties for 0.1, 0.5, and 1.0 wt.% COOH-MWCNT in PMMA, respectively, compared to non-functionalized MWCNTs, were demonstrated. The highest strength was recorded for the nanocomposite with 0.5 wt.% f-MWCNT content, indicating the best doping effect at a lower concentration of f-MWCNT. The proposed CNT-PMMA nanocomposite may be found suitable for use as a scaffold material in the domain of bone tissue engineering research. This type of research possesses a high strength requirement, which may be fulfilled using MWCNT. Furthermore, this analysis also shows a significant amount of enhancement in flexural strength, which is clinically required for fabricating denture bases.This research was funded by a grant from the Romanian Ministry of Research, Innovation, and Digitalization, project number PFE 26/30.12.2021, PERFORM-CDI@UPT100—The increasing of the performance of the Polytechnic University of Timis, oara by strengthening the research, development, and technology transfer capacity in the field of “Energy, Environment and Climate Change” at the beginning of the second century of its existence, within Program 1—Development of the national system of Research and Development, Subprogram 1.2—Institutional Performance-Institutional Development Projects—Excellence Funding Projects in RDI, PNCDI III.info:eu-repo/semantics/publishedVersio

Interrater agreement of nasal endoscopy in patients with a prior history of endoscopic sinus surgery

Nasal endoscopy is an important part of the clinical evaluation of patients with chronic rhinosinusitis. However, its objectivity and inter-rater agreement have not been well studied, especially in patients who have previously had sinus surgery

An overview of vaccine development for COVID-19

The COVID-19 pandemic continues to endanger world health and the economy. The causative SARS-CoV-2 coronavirus has a unique replication system. The end point of the COVID-19 pandemic is either herd immunity or widespread availability of an effective vaccine. Multiple candidate vaccines - peptide, virus-like particle, viral vectors (replicating and nonreplicating), nucleic acids (DNA or RNA), live attenuated virus, recombinant designed proteins and inactivated virus - are presently under various stages of expansion, and a small number of vaccine candidates have progressed into clinical phases. At the time of writing, three major pharmaceutical companies, namely Pfizer and Moderna, have their vaccines under mass production and administered to the public. This review aims to investigate the most critical vaccines developed for COVID-19 to date

Effects of sacubitril/valsartan on N-terminal pro-B-type natriuretic peptide in heart failure with preserved ejection fraction

Objectives: The authors sought to evaluate the prognostic significance of baseline N-terminal pro–B-type natriuretic peptide (NT-proBNP), whether NT-proBNP modified the treatment response to sacubitril/valsartan, and the treatment effect of sacubitril/valsartan on NT-proBNP overall and in key subgroups. Background: Sacubitril/valsartan reduces NT-proBNP in heart failure (HF) with both reduced and preserved ejection fraction (EF), but did not significantly reduce total HF hospitalizations and cardiovascular death compared with valsartan in patients with HF with preserved EF (HFpEF). Methods: In the PARAGON-HF (Efficacy and Safety of LCZ696 Compared to Valsartan, on Morbidity and Mortality in Heart Failure Patients With Preserved Ejection Fraction) trial, 4,796 patients with HFpEF and elevated NT-proBNP were randomized to sacubitril/valsartan or valsartan. NT-proBNP was measured at screening in all patients and at 5 subsequent times in >2,700 patients: before, between, and after sequential valsartan and sacubitril/valsartan run-in periods, and 16 and 48 weeks post-randomization. Results: Median NT-proBNP was 911 pg/ml (interquartile range: 464 to 1,613 pg/ml) at screening. Screening NT-proBNP was strongly associated with the primary endpoint, total HF hospitalizations and cardiovascular death (rate ratio [RR]: 1.68 per log increase in NT-proBNP, 95% confidence interval [CI]: 1.53 to 1.85; p < 0.001). This relationship was stronger in patients with atrial fibrillation (adjusted RR: 2.33 [95% CI: 1.89 to 2.87] vs. 1.58 [95% CI: 1.42 to 1.75] in patients without atrial fibrillation; p interaction <0.001) and weaker in obese patients (adjusted RR: 1.50 [95% CI: 1.31 to 1.71] vs. 1.92 [95% CI: 1.70 to 2.17] in nonobese patients; p interaction <0.001). Screening NT-proBNP did not modify the treatment effect of sacubitril/valsartan compared with valsartan (p interaction = 0.96). Sacubitril/valsartan reduced NT-proBNP by 19% (95% CI: 14% to 23%; p < 0.001) compared with valsartan 16 weeks post-randomization, with similar reductions in men (20%) and women (18%), and in patients with left ventricular EF ≤57% (20%) and >57% (18%). Decreases in NT-proBNP predicted lower subsequent risk of the primary endpoint. Conclusions: Baseline NT-proBNP predicted HF events but did not modify the sacubitril/valsartan treatment effect in patients with HFpEF. Sacubitril/valsartan reduced NT-proBNP consistently in men and women, and in patients with lower or higher EF. (Efficacy and Safety of LCZ696 Compared to Valsartan, on Morbidity and Mortality in Heart Failure Patients With Preserved Ejection Fraction [PARAGON-HF]; NCT01920711