Breakdown of 1D water wires inside Charged Carbon Nanotubes

Using Molecular Dynamics approach we investigated the structure, dynamics of water confined inside pristine and charged 6,6 carbon nanotubes (CNTs). This study reports the breakdown of 1D water wires and the emergence of triangular faced water on incorporating charges in 6,6 CNTs. Incorporation of charges results in high potential barriers to the flipping of water molecules due to the formation of a large number of hydrogen bonds. The PMF analyses show the presence of ~2 kcal/mol barrier for the movement of water inside pristine CNT and almost negligible barrier in charged CNTs.Comment: 12 Pages, 21 figure

Charged Carbon Nanotubes

As the degree of functionalization on CNTs greatly affects its properties, the structure and dynamics of water confined inside pristine and functionalized/charged carbon nanotubes (CNTs) is of prime importance. The presence of charges on the surface of CNTs results in hydrophobic to hydrophilic transitions which increase its occupancy of the water molecules thereby breaking down 1D water wires, as seen in pristine CNTs

Monitoring tasks in aerospace.

Approximately up to one-fifth of the direct operating cost of a commercial civilian fixed-wing aircraft is projected to be due to inspection and maintenance alone. Managing aircraft health with minimal human intervention and technologies that can perform continuous or on-demand monitoring/evaluation of aircraft components without having to take the aircraft out of service can have a significant impact on increasing availability while reducing maintenance cost. The ambition of these monitoring technologies is to shift aircraft maintenance practice from planned maintenance (PM), where the aircraft is taken out of service for scheduled inspection/maintenance, to condition-based maintenance (CBM), where aircraft is taken out of service only when maintenance is required, while maintaining the required levels of safety. Structural health monitoring (SHM) techniques can play a vital role in progressing towards CBM practice. Therefore, this chapter aims to provide the reader with a brief overview of the different SHM techniques and their use, as well as, challenges in implementing them for aircraft applications

Defect types.

This chapter provides an overview of the common types of defects found in various structural materials and joints in aircraft. Materials manufacturing methods (including large-scale production) have been established in the aircraft industry. However, as will be seen in this chapter, manufacturing defects and defects during in-service conditions are very common across all material types. The structural material types include metals, composites, coatings, adhesively bonded and stir-welded joints. This chapter describes the defect types as a baseline for the description of their detection with the methods of Chap. 5 to 8. Based on the understanding of the defect types, there is great expectation for a technical breakthrough for the application of structural health monitoring (SHM) damage detection systems, where continuous monitoring and assessment with high throughput and yield will produce the desired structural integrity

Drone-based non-destructive inspection of industrial sites: a review and case studies

Using aerial platforms for Non-Destructive Inspection (NDI) of large and complex structures is a growing field of interest in various industries. Infrastructures such as: buildings, bridges, oil and gas, etc. refineries require regular and extensive inspections. The inspection reports are used to plan and perform required maintenance, ensuring their structural health and the safety of the workers. However, performing these inspections can be challenging due to the size of the facility, the lack of easy access, the health risks for the inspectors, or several other reasons, which has convinced companies to invest more in drones as an alternative solution to overcome these challenges. The autonomous nature of drones can assist companies in reducing inspection time and cost. Moreover, the employment of drones can lower the number of required personnel for inspection and can increase personnel safety. Finally, drones can provide a safe and reliable solution for inspecting hard-to-reach or hazardous areas. Despite the recent developments in drone-based NDI to reliably detect defects, several limitations and challenges still need to be addressed. In this paper, a brief review of the history of unmanned aerial vehicles, along with a comprehensive review of studies focused on UAV-based NDI of industrial and commercial facilities, are provided. Moreover, the benefits of using drones in inspections as an alternative to conventional methods are discussed, along with the challenges and open problems of employing drones in industrial inspections, are explored. Finally, some of our case studies conducted in different industrial fields in the field of Non-Destructive Inspection are presented

Evaluation and selection of video stabilization techniques for UAV-based active infrared thermography application

nmanned Aerial Vehicles (UAVs) that can fly around an aircraft carrying several sensors, e.g., thermal and optical cameras, to inspect the parts of interest without removing them can have significant impact in reducing inspection time and cost. One of the main challenges in the UAV based active InfraRed Thermography (IRT) inspection is the UAV’s unexpected motions. Since active thermography is mainly concerned with the analysis of thermal sequences, unexpected motions can disturb the thermal profiling and cause data misinterpretation especially for providing an automated process pipeline of such inspections. Additionally, in the scenarios where post-analysis is intended to be applied by an inspector, the UAV’s unexpected motions can increase the risk of human error, data misinterpretation, and incorrect characterization of possible defects. Therefore, post-processing is required to minimize/eliminate such undesired motions using digital video stabilization techniques. There are number of video stabilization algorithms that are readily available; however, selecting the best suited one is also challenging. Therefore, this paper evaluates video stabilization algorithms to minimize/mitigate undesired UAV motion and proposes a simple method to find the best suited stabilization algorithm as a fundamental first step towards a fully operational UAV-IRT inspection system

Diagnosis of composite materials in aircraft applications: towards a UAV active thermography inspection approach

Diagnosis and prognosis of failures for aircrafts’ integrity are some of the most important regular functionalities in complex and safety-critical aircraft structures. Further, development of failure diagnostic tools such as Non-Destructive Testing (NDT) techniques, in particular, for aircraft composite materials, has been seen as a subject of intensive research over the last decades. The need for diagnostic and prognostic tools for composite materials in aircraft applications rises and draws increasing attention. Yet, there is still an ongoing need for developing new failure diagnostic tools to respond to the rapid industrial development and complex machine design. Such tools will ease the early detection and isolation of developing defects and the prediction of damages propagation; thus allowing for early implementation of preventive maintenance and serve as a countermeasure to the potential of catastrophic failure. This paper provides a brief literature review of recent research on failure diagnosis of composite materials with an emphasis on the use of active thermography techniques in the aerospace industry. Furthermore, as the use of unmanned aerial vehicles (UAVs) for the remote inspection of large and/or difficult access areas has significantly grown in the last few years thanks to their flexibility of flight and to the possibility to carry one or several measuring sensors, the aim to use a UAV active thermography system for the inspection of large composite aeronautical structures in a continuous dynamic mode is proposed

Development of a thermal excitation source used in an active thermographic UAV platform

This work aims to address the effectiveness and challenges of using active infrared thermography (IRT) onboard an unmanned aerial vehicle (UAV) platform. The work seeks to assess the performance of small low-powered forms of excitation which are suitable for active thermography and the ability to locate subsurface defects on composites. An excitation source in multiple 250 W lamps is mounted onto a UAV and is solely battery powered with a remote trigger to power cycle them. Multiple experiments address the interference from the UAV whilst performing an active IRT inspection. The optimal distances and time required for a UAV inspection using IRT are calculated. Multiple signal processing techniques are used to analyse the composites which help locate the sub-surface defects. It was observed that a UAV can successfully carry the required sensors and equipment for an Active thermographic NDT inspection which can provide access to difficult areas. Most active thermographic inspection equipment is large, heavy, and expensive. Furthermore, using such equipment for the inspection of complex structures is time-consuming. For example, a cherry picker would be required to inspect the tail of an aircraft. This solution looks to assist engineers in inspecting complex composite structures and could potentially significantly reduce the time and cost of a routine inspection.Engineering and Physical Sciences Research Council (EPSRC): EP/N509450/1 and Innovate UK: 105625

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Investigation of structural dynamics and the function of membrane proteins with computational techniques

With the development of more accurate force fields and powerful computers, molecular dynamics (MD) has become a ubiquitous tool to study complex structural, thermodynamic and kinetic processes of real world systems across disciplines. MD has a long history of being employed to enhance our understanding and guide experiments by unravelling fine details at high spatial and temporal resolution. This unique feature of MD offers insights to the highly specific interactions that dictate various biological processes. This dissertation entails the use and development of advanced simulation techniques by employing synergies between statistical mechanics, computer simulations and artificial intelligence (AI) to study the complex biological processes at the interface of the biological membranes.Through the use of accelerated membrane models, which enhanced phospholipid diffusion and reorganization in the membrane using an atomistic representation, we captured repeated and spontaneous insertion of human signalling proteins, in a lipid-dependent manner. More specifically, simulations of GRP1-PH domain allowed us to capture differential binding and conformational dynamics of the PH domain in the presence of membranes containing PC,PS, and PIP3lipids in varying compositions. Interestingly, the use of Highly Mobile Membrane Mimetic (HMMM) allowed us to capture, for the first time, two distinct PIP3 binding modes,suggesting the possibility of simultaneous binding of multiple anionic lipids might dictate the recruitment and stabilization of the domain. In a separate study, membrane-binding simulations of ASAP1-PH domain shows that the overall electrostatic environment of the membrane drives the membrane recruitment of the protein and specific binding to the rare PIP2lipids, leads to its allosteric modulation. We believe that this allosteric modulation plays a very important role in the downstream signalling events.Integral membrane proteins in their native environment are also presented. As a major class of integral membrane proteins, secondary active neurotransmitter transporters strictly couple the uphill transport of the substrate, with Na+and/or H+ ions. To achieve their functional role, these transporters undergo large-scale transition between outward-facing (OF) and inward-facing (IF) states, following the so-called “alternating-access model”. To address the key role of alternating access model and elucidate the molecular mechanism of the transport cycle, we performed MD simulations combined with advanced simulation techniques on human and bacterial glutamate transporters, involved in the neurotransmission of the brain. As the human glutamate transporter is proton coupled, we first employed constant pH MD simulations to capture the proton binding site and its binding sequence. The results obtained from these simulations were further verified by our experimental collaborators. Also, we were able to uncover how the strict coupling between the substrate, Na+and H+dictates the transition cycle of the human transporter. Next, we combined the power of concerted structural biology and computational biophysics to unravel the alter-ego of a transporter.We were able to uncover, for the first time, how a transporter develops an ion channel property right in the middle of its transport cycle. Finally, the section on neurotransmitter transporters concludes with the lipid-dependent energetic characterization of conformational transitions in human glutamate transporters. These extensive free energy calculations allowed us to capture, in atomic details, the forward transition cycle and specific intermediates which might play an important role in designing novel therapeutics against various neurological disorders. We applied our protocol to capture large-scale conformational transitions in P-glycoprotein, with the aim to uncover novel binding sites for the third-generation inhibitor. Based on this study, we were able to propose a novel inhibitory mechanism for third-generation Pgp inhibitors, where lipids are seen to enhance the inhibitory role in the catalytic cycle of membrane transporters. Lastly, in this section we employed MD simulations in combination with electrophysiology experiments to capture lipid-mediated conformational regulation of an epilepsy-causing voltage-gated potassium channel, Kv7.2.In the last section, we have developed an AI-based approach which can be combined with MD simulations to mitigate the problem of sampling. Typically, MD simulations, per construction, suffer from limited sampling and thus limited data. As such, the use of AI in molecular simulations can suffer from a dangerous situation where the AI optimization could get stuck in spurious regimes, leading to incorrect characterization of the reaction coordinate (RC) for the problem at hand. To deal with this problem of spurious AI solutions,we developed an automated approach which combines the idea from statistical physics, including the concept of maximum caliber to differentiate between the fast and the slow processes. We show the applicability of this protocol for three classic benchmark problems, namely, the conformational dynamics of a model peptide, ligand unbinding from a protein, and folding/unfolding energy landscape of a peptide.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste