Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

This work introduces a number of algebraic topology approaches, such as multicomponent persistent homology, multi-level persistent homology and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. Multicomponent persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for chemical and biological problems. Extensive numerical experiments involving more than 4,000 protein-ligand complexes from the PDBBind database and near 100,000 ligands and decoys in the DUD database are performed to test respectively the scoring power and the virtual screening power of the proposed topological approaches. It is demonstrated that the present approaches outperform the modern machine learning based methods in protein-ligand binding affinity predictions and ligand-decoy discrimination

Factories of the Future

Engineering; Industrial engineering; Production engineerin

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Automation and Control

Advances in automation and control today cover many areas of technology where human input is minimized. This book discusses numerous types and applications of automation and control. Chapters address topics such as building information modeling (BIM)–based automated code compliance checking (ACCC), control algorithms useful for military operations and video games, rescue competitions using unmanned aerial-ground robots, and stochastic control systems

New advances in vehicular technology and automotive engineering

An automobile was seen as a simple accessory of luxury in the early years of the past century. Therefore, it was an expensive asset which none of the common citizen could afford. It was necessary to pass a long period and waiting for Henry Ford to establish the first plants with the series fabrication. This new industrial paradigm makes easy to the common American to acquire an automobile, either for running away or for working purposes. Since that date, the automotive research grown exponentially to the levels observed in the actuality. Now, the automobiles are indispensable goods; saying with other words, the automobile is a first necessity article in a wide number of aspects of living: for workers to allow them to move from their homes into their workplaces, for transportation of students, for allowing the domestic women in their home tasks, for ambulances to carry people with decease to the hospitals, for transportation of materials, and so on, the list don’t ends. The new goal pursued by the automotive industry is to provide electric vehicles at low cost and with high reliability. This commitment is justified by the oil’s peak extraction on 50s of this century and also by the necessity to reduce the emissions of CO2 to the atmosphere, as well as to reduce the needs of this even more valuable natural resource. In order to achieve this task and to improve the regular cars based on oil, the automotive industry is even more concerned on doing applied research on technology and on fundamental research of new materials. The most important idea to retain from the previous introduction is to clarify the minds of the potential readers for the direct and indirect penetration of the vehicles and the vehicular industry in the today’s life. In this sequence of ideas, this book tries not only to fill a gap by presenting fresh subjects related to the vehicular technology and to the automotive engineering but to provide guidelines for future research. This book account with valuable contributions from worldwide experts of automotive’s field. The amount and type of contributions were judiciously selected to cover a broad range of research. The reader can found the most recent and cutting-edge sources of information divided in four major groups: electronics (power, communications, optics, batteries, alternators and sensors), mechanics (suspension control, torque converters, deformation analysis, structural monitoring), materials (nanotechnology, nanocomposites, lubrificants, biodegradable, composites, structural monitoring) and manufacturing (supply chains). We are sure that you will enjoy this book and will profit with the technical and scientific contents. To finish, we are thankful to all of those who contributed to this book and who made it possible.info:eu-repo/semantics/publishedVersio

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways.publishedVersio

Investigation and ranking antiscalants and biocides in a new monitoring system for reverse osmosis desalination and benchmarking results to the conventional system

Reverse osmosis (RO) membranes are growing to be the dominant technology for water purification applications. However, fouling is the primary obstacle affecting the RO technologies, and it forces the operator to apply higher operating pressure and use more cleaning chemicals. Therefore, the membrane research major objective is to develop complementary approaches to control fouling based on the development of effective antiscalants and biocides to control fouling and biofouling. Moreover, useful tools for quantitative online monitoring of fouling at early stages and evaluation of cleaning steps. The three experimental research chapters in this thesis are covering the two approaches. Three antiscalants were assessed in Chapter 7 to investigate the promotion of the RO recovery percentage despite the high saturation indices of feed water. The study was carried out on a model reject brine solution. Two cross-flow RO membrane units were utilised in the test. The scaling experiments were carried by circulating the feed solution through membrane modules for 90 hours in a total recycle mode at a flow rate of 48 L/h, the temperature was kept between 20 to 25 oC, and the operating pressure was controlled at 10 bars. The assessment was based on the normalised permeate flux decline and the normalised pressure drop in the absence of antiscalant dose and (2, 10 and 20 mg/L antiscalant doses). Additionally, at the end of each scaling run, membrane autopsies were carried out on a fouled membrane to provide a quantitative and quantified analysis. Two biocides were evaluated in chapter 8. The study was focusing on simulating biofouling accumulation in the cross-flow RO filtration units by utilising fresh bacterial inoculum and nutrients and exposing the system to biocide dose for cleaning. The feed water was recirculated through the system at flow rate 18 L/h in a total recycle mode for two weeks. The tank temperature was kept at 40 oC to keep the bacteria growing. The operating pressure was controlled at 10 bars. The biocide was added stepwise when the permeate flux dropped by 10-15 % of initial values. The permeate flux and normalised pressure drop were continuously monitored to verify the ability of biocide to control biofouling on RO membrane. At the end of the test, the membrane coupons were examined to determine the effect of biocide on the biofilm accumulation. The research objective of chapter 9 was to develop a prototype for real-time monitoring membrane fouling. The primary aims were to verify the device accuracy for detecting fouling of the spacer grids and membrane surface in the early phase, the device response to chemical addition (Biocide and Antiscalants), and its capability to classify and distinguish between biofouling and fouling

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

Hydrophobicity Classification of RTV Silicone Rubber-Coated Insulators Using Deep Learning Algorithms

Silicone rubber-based outdoor polymeric insulators are widely employed in electric power transmission and distribution networks to replace conventional ceramic insulators, owing to their superior performance in contaminated and wet environments. Silicone rubber (SIR) insulators offer several advantages like high hydrophobicity, low cost, vandalism resistance, and lightweight. However, when exposed to electrical (dry band arcing and partial discharge) and environmental stresses (humidity, ultraviolet radiation, acid rain and pollution) they suffer from different forms of aging. The first form of aging is the temporal loss of hydrophobicity. However, SIR insulators can recover the hydrophobicity property due to the diffusion of the low molecular weight (LMW) from the bulk of the insulating material to the insulators’ surface. Hence, it is important to classify the hydrophobicity status of SIR insulators as an indication of the aging degree. Different methods have been implemented to classify the hydrophobicity of the insulator surface including static contact angle measurement, dynamic contact angle measurement, and hydrophobicity class (HC). The later technique is the most practical method that can be used in the field and can assess a wide surface area. The surface wetting tendency is manually classified using one of six classes, i.e. HC1-HC6, where HC1 refers to a completely hydrophobic surface and HC6 is a completely hydrophilic surface. The main objective of this thesis is to automatically assess the hydrophobicity classes of non-ceramic insulators under a variety of conditions using deep learning techniques. A dataset of hydrophobicity classes (HC1-HC6) was created and prepared including 4197 images each having 2242×24 pixels size to train the proposed model. Several deep learning techniques, including Convolutional Neural Networks (CNN), Transfer Learning (TL), and Object Detection (OD), were used in this thesis to categorize and assess the hydrophobicity classes of ceramic insulators coated with room temperature vulcanized silicone rubber (RTV-SIR). MobileNet model was found to have the highest accuracy and less training time after comparing with other CNN pre-trained models. This model was then trained and tested under several conditions, including indoor, bright, and dark lighting conditions, and achieved accuracy of 97.77%, 89.44%, and 95%, respectively. Moreover, the proposed model achieved a recognition rate of 96.11% when tested on a full-scale silicone rubber insulator. The developed model was then deployed as a web application for convenience in the assessment of hydrophobicity classes. The proposed model could be utilized to evaluate SIR insulators surface conditions in an effective and automatic way under different conditions

Factories of the Future

Engineering; Industrial engineering; Production engineerin