Review on Diffuser Augmented Wind Turbine (DAWT)

Wind energy technology is one of the fastest growing alternative energy technologies. However, conventional turbines commercially available in some countries are designed to operate at relatively high speeds to be appropriately efficient, limiting the use of wind turbines in areas with low wind speeds, such as urban areas. Therefore, a technique to enhance the possibility of wind energy use within the range of low speeds is needed. The techniques of augmenting wind by the concept of Diffuser Augmented Wind Turbine (DAWT) have been used to improve the efficiency of the wind turbines by increasing the wind speed upstream of the turbine. In this paper, a comprehensive review of previous studies on improving or augmentation power of Horizontal Axis Wind Turbines (HAWT) have been reviewed in two categories, first related with relative improvement of energy by improving the aerodynamic forces that affecting on HAWT in some different modifications for blades. Second, reviews different techniques to the augment the largest possible amount of power from HAWT focusing on DAWTs to gather information,helping researchers understand the research efforts undertaken so far and identify knowledge gaps in this area. DAWTs are studied in terms of diffuser shape design, sizing of investigation and geometry features which involved diffuser length, diffuser angle, and flange height. The conclusions in this work show that the use of DAWT achieves a quantum leap in increasing the production of wind power, especially in small turbines in urban areas if it properly designed. On the other hand, shrouding the wind turbine by the diffuser reduces the noise and protects the rotor blades from possible damage

Recombination and lineage-specific mutations linked to the emergence of SARS-CoV-2

Background The emergence of SARS-CoV-2 underscores the need to better understand the evolutionary processes that drive the emergence and adaptation of zoonotic viruses in humans. In the betacoronavirus genus, which also includes SARS-CoV and MERS-CoV, recombination frequently encompasses the receptor binding domain (RBD) of the Spike protein, which is responsible for viral binding to host cell receptors. In this work, we reconstruct the evolutionary events that have accompanied the emergence of SARS-CoV-2, with a special emphasis on the RBD and its adaptation for binding to its receptor, human ACE2. Methods By means of phylogenetic and recombination analyses, we found evidence of a recombination event in the RBD involving ancestral linages to both SARS-CoV and SARS-CoV-2. We then assessed the effect of this recombination at protein level by reconstructing the RBD of the closest ancestors to SARS-CoV-2, SARS-CoV, and other Sarbecoviruses, including the most recent common ancestor of the recombining clade. The resulting information was used to measure and compare, in silico, their ACE2-binding affinities using the physics-based trRosetta algorithm. Results We show that, through an ancestral recombination event, SARS-CoV and SARS-CoV-2 share an RBD sequence that includes two insertions (positions 432-436 and 460-472), as well as the variants 427N and 436Y. Both 427N and 436Y belong to a helix that interacts directly with the human ACE2 (hACE2) receptor. Reconstruction of ancestral states, combined with protein-binding affinity analyses, suggests that the recombination event involving ancestral strains of SARS-CoV and SARS-CoV-2 led to an increased affinity for hACE2 binding and that alleles 427N and 436Y significantly enhanced affinity as well. Conclusions We report an ancestral recombination event affecting the RBD of both SARS-CoV and SARS-CoV-2 that was associated with an increased binding affinity to hACE2. Structural modeling indicates that ancestors of SARS-CoV-2 may have acquired the ability to infect humans decades ago. The binding affinity with the human receptor would have been subsequently boosted in SARS-CoV and SARS-CoV-2 through further mutations in RBD

Novel Insights into The Role of Pyruvate Kinase M2 in Podocyte Homeostasis and Function

Background: Renal diseases are major health concerns and among the top ten leading causes of death in the US. A large number of these diseases are characterized by deterioration in glomerular structure and function, leading to reduced filtration capacity and proteinuria. Glomerulus podocytes are epithelial cells that maintain glomerular integrity and act as a defense mechanism against proteinuria. Recent advances in renal research suggested a novel role of glycolysis and its related enzymes, pyruvate kinase M2 (PKM2) in particular, in the progression of renal diseases. However, the precise role of PKM2 in podocyte homeostasis and its contribution to glomerular function under normal and pathological conditions remains to be determined. Methods: In this project, we evaluated the role of PKM2 in podocyte differentiation and homeostasis, using shRNA-mediated PKM2 knockdown in murine podocytes. Next, we examined the clinical significance of PKM2 deficiency to renal function using the Cre-LoxP technology to generate mice that specifically lack PKM2 in podocytes. Then, lipopolysaccharide (LPS), an endotoxin agent, was used to induce renal injury. We also used various genetic approaches and pharmaceutical compounds to decipher the molecular mechanisms mediating PKM2 action. Results: The genetic depletion of PKM2 increased podocyte differentiation markers and protected against LPS induced albumin permeability in vitro. These effects were concomitant with enhanced activation of autophagy, AMPK, and mTORC1 but reduced AKT phosphorylation. On the other hand, the prolonged pharmacological inhibition of AKT or activation of AMPK recapitulated the effects of PKM2 deficiency on autophagy induction, podocyte differentiation, and albumin loss. In vivo, the deletion of PKM2 preserved podocyte integrity and protected against LPS induced proteinuria and nephrin loss. Further analysis revealed that PKM2 deficiency was associated with reduced inflammatory cytokines, inflammation, ER stress, and β-catenin level but sustained Wilms’ Tumor 1 (WT1) expression after LPS challenge. Additionally, PKM2 deficiency enhanced podocyte survival and ameliorated LPS-induced podocytes cell death. Mechanistic studies revealed that PKM2 interacts with β-catenin to promote LPS induced podocytes cell death. Conclusion: Our data elucidate a novel role of PKM2 in podocyte homeostasis and propose PKM2 as a potential therapeutic target to halt renal injury progression

Machine-learned molecular models for protein structure, networks, and design

The advent of a new modeling paradigm known as â differentiable programmingâ makes possible bespoke machine-learned models of biological phenomena that are partly learned from data and partly informed by human-derived biophysical knowledge. In this talk I will describe three instantiations of this new approach for (i) de novo protein structure prediction, (ii) elucidation of the combinatorial grammar underlying metazoan signaling networks, and (iii) design of new protein function. In all cases qualitative improvements in model accuracy or speed, or both, are achieved using differentiable programming, enabling new scientific insights into biological macromolecules and the networks they comprise.Non UBCUnreviewedAuthor affiliation: Harvard Medical SchoolPostdoctora

Lexical bundles in an advanced INTOCSU writing class and engineering texts: a functional analysis

2014 Summer.The purpose of this study is to investigate the functions of lexical bundles in two corpora: a corpus of engineering academic texts and a corpus of IEP advanced writing class texts. This study is concerned with the nature of formulaic language in Pathway IEPs and engineering texts, and whether those types of texts show similar or distinctive formulaic functions. Moreover, the study looked into lexical bundles found in an engineering 1.26 million-word corpus and an ESL 65000-word corpus using a concordancing program. The study then analyzed the functions of those lexical bundles and compared them statistically using chi-square tests. Additionally, the results of this investigation showed 236 unique frequent lexical bundles in the engineering corpus and 37 bundles in the pathway corpus. Also, the study identified several differences between the density and functions of lexical bundles in the two corpora. These differences were evident in the distribution of functions of lexical bundles and the minimal overlap of lexical bundles found in the two corpora. The results of this study call for more attention to formulaic language at ESP and EAP programs

An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system

Background: Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. Description We have developed an integrated affinity-structure database in which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. Conclusions: This database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu

Investigating the Avocado (Persea americana) fruit's anti-anxiety potentials in rat models

Background and aim: Anxiety has an effect on the common regular living of a human as it causes fatigue and restlessness. In the current study, an effort was undertaken to investigate the anti-anxiety behavior of male albino by the treatment of Avocado Powder and Juice in vivo. Methods: Avocado Powder 10 % (AP1) and 15 % (AP2) substituted from the diet and Avocado Juice 100 mL/kg (AJ1) and150ml/kg body weight (AJ2) rat over control rats. Results: The oral intake of Avocado powder and Juice caused a significant decrease in the body weight gain, daily feed intake, and feed efficiency ratio (FER) in all experimental groups tested as compared to control. Also, the activity of the antioxidant enzymes like SOD, GST, GPX, and Catalase is not much influenced by the intake of avocado fruit. This significant result has confirmed the effectiveness of this fruit for the treatment of anxiety. The anti-anxiety effect of the avocado fruit was tested by exploring the behavioral changes tests in experimental rats. All the experiments conducted showed that the intake of dose AP2 and AJ2 has significantly decreased the number of head dips and cage crossing and increased the time spent in light side in light–dark transition box test, and increased time spent in open arm in elevated plus maze test. Conclusions: This result proved that the avocado fruit as powder then as juice have an anxiolytic effects and will be a better alternative for people with an anxiety disorder

High-throughput deep learning variant effect prediction with Sequence UNET

Abstract Understanding coding mutations is important for many applications in biology and medicine but the vast mutation space makes comprehensive experimental characterisation impossible. Current predictors are often computationally intensive and difficult to scale, including recent deep learning models. We introduce Sequence UNET, a highly scalable deep learning architecture that classifies and predicts variant frequency from sequence alone using multi-scale representations from a fully convolutional compression/expansion architecture. It achieves comparable pathogenicity prediction to recent methods. We demonstrate scalability by analysing 8.3B variants in 904,134 proteins detected through large-scale proteomics. Sequence UNET runs on modest hardware with a simple Python package