On the Deformation of a Hyperelastic Tube Due to Steady Viscous Flow Within

In this chapter, we analyze the steady-state microscale fluid--structure interaction (FSI) between a generalized Newtonian fluid and a hyperelastic tube. Physiological flows, especially in hemodynamics, serve as primary examples of such FSI phenomena. The small scale of the physical system renders the flow field, under the power-law rheological model, amenable to a closed-form solution using the lubrication approximation. On the other hand, negligible shear stresses on the walls of a long vessel allow the structure to be treated as a pressure vessel. The constitutive equation for the microtube is prescribed via the strain energy functional for an incompressible, isotropic Mooney--Rivlin material. We employ both the thin- and thick-walled formulations of the pressure vessel theory, and derive the static relation between the pressure load and the deformation of the structure. We harness the latter to determine the flow rate--pressure drop relationship for non-Newtonian flow in thin- and thick-walled soft hyperelastic microtubes. Through illustrative examples, we discuss how a hyperelastic tube supports the same pressure load as a linearly elastic tube with smaller deformation, thus requiring a higher pressure drop across itself to maintain a fixed flow rate.Comment: 19 pages, 3 figures, Springer book class; v2: minor revisions, final form of invited contribution to the Springer volume entitled "Dynamical Processes in Generalized Continua and Structures" (in honour of Academician D.I. Indeitsev), eds. H. Altenbach, A. Belyaev, V. A. Eremeyev, A. Krivtsov and A. V. Porubo

An efficient ensemble VTOPES multi-criteria decision-making model for sustainable sugarcane farms

© 2019 by the authors. The role of Information Technology based decision models for sustainable agriculture has gained immense prominence in recent years. Ranking of agriculture farms based on their yield plays a vital role in sustainable agriculture. In this work, an ensemble decision-making model, namely VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje), TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), entropy, and standard deviation (VTOPES), is proposed for ranking the sustainable sugarcane farms. VTOPES system model comprises of four significant steps: (i) determination of significance scores of the sub-parameters, (ii) transformation of sub-parameter sequences into main parameter values, (iii) computation of significant scores of main parameters, and (iv) generation of assessment values and deploying it for ranking the sugarcane farms. The ranking results of the proposed VTOPES model are compared with the ranking patterns obtained from five years average yield data acquired from the selected sugarcane farms. Moreover, the outcomes of the VTOPES model are also compared with other prevalent methods. Subsequently, Spearman's rank correlation method is applied for evaluating the impact of correlation of VTOPES ranks in comparison with the average yield ranks. Thus, it can be noticed that the empirical results of the VTOPES model provide reliable and sustainable results. Therefore, it suffices to be a sustainable decision model for any problem where multiple parameters are involved

IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages

India has a rich linguistic landscape with languages from 4 major language families spoken by over a billion people. 22 of these languages are listed in the Constitution of India (referred to as scheduled languages) are the focus of this work. Given the linguistic diversity, high-quality and accessible Machine Translation (MT) systems are essential in a country like India. Prior to this work, there was (i) no parallel training data spanning all the 22 languages, (ii) no robust benchmarks covering all these languages and containing content relevant to India, and (iii) no existing translation models which support all the 22 scheduled languages of India. In this work, we aim to address this gap by focusing on the missing pieces required for enabling wide, easy, and open access to good machine translation systems for all 22 scheduled Indian languages. We identify four key areas of improvement: curating and creating larger training datasets, creating diverse and high-quality benchmarks, training multilingual models, and releasing models with open access. Our first contribution is the release of the Bharat Parallel Corpus Collection (BPCC), the largest publicly available parallel corpora for Indic languages. BPCC contains a total of 230M bitext pairs, of which a total of 126M were newly added, including 644K manually translated sentence pairs created as part of this work. Our second contribution is the release of the first n-way parallel benchmark covering all 22 Indian languages, featuring diverse domains, Indian-origin content, and source-original test sets. Next, we present IndicTrans2, the first model to support all 22 languages, surpassing existing models on multiple existing and new benchmarks created as a part of this work. Lastly, to promote accessibility and collaboration, we release our models and associated data with permissive licenses at https://github.com/ai4bharat/IndicTrans2

Variability in gene expression underlies incomplete penetrance

The phenotypic differences between individual organisms can often be ascribed to underlying genetic and environmental variation. However, even genetically identical organisms in homogeneous environments vary, indicating that randomness in developmental processes such as gene expression may also generate diversity. To examine the consequences of gene expression variability in multicellular organisms, we studied intestinal specification in the nematode Caenorhabditis elegans in which wild-type cell fate is invariant and controlled by a small transcriptional network. Mutations in elements of this network can have indeterminate effects: some mutant embryos fail to develop intestinal cells, whereas others produce intestinal precursors. By counting transcripts of the genes in this network in individual embryos, we show that the expression of an otherwise redundant gene becomes highly variable in the mutants and that this variation is subjected to a threshold, producing an ON/OFF expression pattern of the master regulatory gene of intestinal differentiation. Our results demonstrate that mutations in developmental networks can expose otherwise buffered stochastic variability in gene expression, leading to pronounced phenotypic variation.National Institutes of Health (U.S.). Pioneer AwardMathematical Sciences Postdoctoral Research Fellowships (DMS-0603392)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award (5F32GM080966

Structural insights into the production of 3-hydroxypropionic acid by aldehyde dehydrogenase from Azospirillum brasilense

3-Hydroxypropionic acid (3-HP) is an important platform chemical to be converted to acrylic acid and acrylamide. Aldehyde dehydrogenase (ALDH), an enzyme that catalyzes the reaction of 3-hydroxypropionaldehyde (3-HPA) to 3-HP, determines 3-HP production rate during the conversion of glycerol to 3-HP. To elucidate molecular mechanism of 3-HP production, we determined the first crystal structure of a 3-HP producing ALDH, alpha-ketoglutarate-semialdehyde dehydrogenase from Azospirillum basilensis (AbKGSADH), in its apo-form and in complex with NAD(+). Although showing an overall structure similar to other ALDHs, the AbKGSADH enzyme had an optimal substrate binding site for accepting 3-HPA as a substrate. Molecular docking simulation of 3-HPA into the AbKGSADH structure revealed that the residues Asn159, Gln160 and Arg163 stabilize the aldehyde-and the hydroxyl-groups of 3-HPA through hydrogen bonds, and several hydrophobic residues, such as Phe156, Val286, Ile288, and Phe450, provide the optimal size and shape for 3-HPA binding. We also compared AbKGSADH with other reported 3-HP producing ALDHs for the crucial amino acid residues for enzyme catalysis and substrate binding, which provides structural implications on how these enzymes utilize 3-HPA as a substrate

Baroreflex sensitivity is impaired in survivors of mild COVID-19 at 3-6 months of clinical recovery; association with carotid artery stiffness

The association between the stiffening of barosensitive regions of central arteries and the derangements in baroreflex functions remains unexplored in COVID-19 survivors. Fifty-seven survivors of mild COVID-19 (defined as presence of upper respiratory tract symptoms and/or fever without shortness of breath or hypoxia; SpO2 > 93%), with an age range of 22-66 years (27 females) participated at 3-6 months of recovering from the acute phase of RT-PCR positive COVID-19. Healthy volunteers whose baroreflex sensitivity (BRS) and arterial stiffness data were acquired prior to the onset of the pandemic constituted the control group. BRS was found to be significantly lower in the COVID survivor group for the systolic blood pressure-based sequences (BRS SBP ) [9.78 (7.16-17.74) ms/mmHg vs 16.5 (11.25-23.78) ms/mmHg; p = 0.0253]. The COVID survivor group showed significantly higher carotid β stiffness index [7.16 (5.75-8.18) vs 5.64 (4.34-6.96); (p = 0.0004)], and pulse wave velocity β (PWVβ ) [5.67 (4.96-6.32) m/s vs 5.12 (4.37-5.41) m/s; p = 0.0002]. BRS quantified by both the sequence and spectral methods showed an inverse correlation with PWVβ in the male survivors. Impairment of BRS in the male survivors of mild COVID-19 at 3-6 months of clinical recovery shows association with carotid artery stiffness

An Efficient Targeted Drug Delivery through Apotransferrin Loaded Nanoparticles

BACKGROUND: Cancerous state is a highly stimulated environment of metabolically active cells. The cells under these conditions over express selective receptors for assimilation of factors essential for growth and transformation. Such receptors would serve as potential targets for the specific ligand mediated transport of pharmaceutically active molecules. The present study demonstrates the specificity and efficacy of protein nanoparticle of apotransferrin for targeted delivery of doxorubicin. METHODOLOGY/PRINCIPAL FINDINGS: Apotransferrin nanoparticles were developed by sol-oil chemistry. A comparative analysis of efficiency of drug delivery in conjugated and non-conjugated forms of doxorubicin to apotransferrin nanoparticle is presented. The spherical shaped apotransferrin nanoparticles (nano) have diameters of 25-50 etam, which increase to 60-80 etam upon direct loading of drug (direct-nano), and showed further increase in dimension (75-95 etam) in conjugated nanoparticles (conj-nano). The competitive experiments with the transferrin receptor specific antibody showed the entry of both conj-nano and direct-nano into the cells through transferrin receptor mediated endocytosis. Results of various studies conducted clearly establish the superiority of the direct-nano over conj-nano viz. (a) localization studies showed complete release of drug very early, even as early as 30 min after treatment, with the drug localizing in the target organelle (nucleus) (b) pharmacokinetic studies showed enhanced drug concentrations, in circulation with sustainable half-life (c) the studies also demonstrated efficient drug delivery, and an enhanced inhibition of proliferation in cancer cells. Tissue distribution analysis showed intravenous administration of direct nano lead to higher drug localization in liver, and blood as compared to relatively lesser localization in heart, kidney and spleen. Experiments using rat cancer model confirmed the efficacy of the formulation in regression of hepatocellular carcinoma with negligible toxicity to kidney and liver. CONCLUSIONS: The present study thus demonstrates that the direct-nano is highly efficacious in delivery of drug in a target specific manner with lower toxicity to heart, liver and kidney

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed