Quasi-Static Cyclic Response of Unidirectional Thin-Ply Hybrid Composites

Quasi-static cyclic loading of unidirectional (UD) thin-ply hybrid composites was conducted to assess the extent of stiffness loss with increasing applied strain. For this study, three types of hybrid configuration were examined: SG1/MR401/SG1, SG1/TR301/SG1, SG1/TR302/SG1, where SG is a high strength glass fibre and MR40 is an intermediate modulus carbon fibre while TR30 is a standard modulus carbon fibre. The strain at first carbon ply failure and the knee point strain (εk) for the SG1/TR301/SG1 hybrid is higher than for the SG1/TR302/SG1 hybrid. This is due to the ‘hybrid effect’ which provides a delay in damage initiation due to a constraint on broken carbon cluster development. For SG1/MR401/SG1 and SG1/TR302/SG1 configurations, the stiffness reduction over the course of loading was governed by fragmentation of the carbon plies and delamination between the carbon and glass plies. A smaller stiffness reduction for the SG1/TR301/SG1 configuration compared to the other hybrid configurations was observed with the fragmentation of the carbon ply as the main damage mechanism responsible for the reduction. With each loading cycle, there was a small amount of hysteresis and residual strain. The response of the UD thin-ply hybrid laminates are considered pseudo-ductile because the damage in the form of ply fragmentation and stable delamination, leads to gradual loss of stiffness. The stable delamination of this hybrid material is due to the low energy release rate of the thin carbon ply

A database and tool, IM Browser, for exploring and integrating emerging gene and protein interaction data for Drosophila

BACKGROUND: Biological processes are mediated by networks of interacting genes and proteins. Efforts to map and understand these networks are resulting in the proliferation of interaction data derived from both experimental and computational techniques for a number of organisms. The volume of this data combined with the variety of specific forms it can take has created a need for comprehensive databases that include all of the available data sets, and for exploration tools to facilitate data integration and analysis. One powerful paradigm for the navigation and analysis of interaction data is an interaction graph or map that represents proteins or genes as nodes linked by interactions. Several programs have been developed for graphical representation and analysis of interaction data, yet there remains a need for alternative programs that can provide casual users with rapid easy access to many existing and emerging data sets. DESCRIPTION: Here we describe a comprehensive database of Drosophila gene and protein interactions collected from a variety of sources, including low and high throughput screens, genetic interactions, and computational predictions. We also present a program for exploring multiple interaction data sets and for combining data from different sources. The program, referred to as the Interaction Map (IM) Browser, is a web-based application for searching and visualizing interaction data stored in a relational database system. Use of the application requires no downloads and minimal user configuration or training, thereby enabling rapid initial access to interaction data. IM Browser was designed to readily accommodate and integrate new types of interaction data as it becomes available. Moreover, all information associated with interaction measurements or predictions and the genes or proteins involved are accessible to the user. This allows combined searches and analyses based on either common or technique-specific attributes. The data can be visualized as an editable graph and all or part of the data can be downloaded for further analysis with other tools for specific applications. The database is available at CONCLUSION: The Drosophila Interactions Database described here places a variety of disparate data into one easily accessible location. The database has a simple structure that maintains all relevant information about how each interaction was determined. The IM Browser provides easy, complete access to this database and could readily be used to publish other sets of interaction data. By providing access to all of the available information from a variety of data types, the program will also facilitate advanced computational analyses

Pseudo-ductility and reduced notch sensitivity in multi-directional all-carbon/epoxy thin-ply hybrid composites

© 2017 The Author(s) Un-notched and notched tensile response and damage accumulation of quasi-isotropic carbon/epoxy hybrid laminates made of ultra-high modulus and intermediate modulus carbon fibre/epoxy thin-ply prepregs were studied. It was confirmed that the ply fragmentation demonstrated previously in unidirectional hybrids as a successful pseudo-ductility mechanism can be transferred to multi-directional laminates. Furthermore, reduced notch sensitivity was demonstrated in quasi-isotropic specimens for both open holes and sharp notches as a result of local ply fragmentation around the notch

Downregulation of Mcl-1 has anti-inflammatory pro-resolution effects and enhances bacterial clearance from the lung

Phagocytes not only coordinate acute inflammation and host defense at mucosal sites, but also contribute to tissue damage. Respiratory infection causes a globally significant disease burden and frequently progresses to acute respiratory distress syndrome, a devastating inflammatory condition characterized by neutrophil recruitment and accumulation of protein-rich edema fluid causing impaired lung function. We hypothesized that targeting the intracellular protein myeloid cell leukemia 1 (Mcl-1) by a cyclin-dependent kinase inhibitor (AT7519) or a flavone (wogonin) would accelerate neutrophil apoptosis and resolution of established inflammation, but without detriment to bacterial clearance. Mcl-1 loss induced human neutrophil apoptosis, but did not induce macrophage apoptosis nor impair phagocytosis of apoptotic neutrophils. Neutrophil-dominant inflammation was modelled in mice by either endotoxin or bacteria (Escherichia coli). Downregulating inflammatory cell Mcl-1 had anti-inflammatory, pro-resolution effects, shortening the resolution interval (R(i)) from 19 to 7 h and improved organ dysfunction with enhanced alveolar–capillary barrier integrity. Conversely, attenuating drug-induced Mcl-1 downregulation inhibited neutrophil apoptosis and delayed resolution of endotoxin-mediated lung inflammation. Importantly, manipulating lung inflammatory cell Mcl-1 also accelerated resolution of bacterial infection (R(i); 50 to 16 h) concurrent with enhanced bacterial clearance. Therefore, manipulating inflammatory cell Mcl-1 accelerates inflammation resolution without detriment to host defense against bacteria, and represents a target for treating infection-associated inflammation

Long-Term Smart Grid Planning Under Uncertainty Considering Reliability Indexes

The electricity sector is fast moving towards a new era of clean generation devices dispersed along the network. On one hand, this will largely contribute to achieve the multi-national environment goals agreed via political means. On the other hand, network operators face new complexities and challenges regarding network planning due to the large uncertainties associated with renewable generation and electric vehicles integration. In addition, due to new technologies such as combined heat and power (CHP), the district heat demand is considered in the long-term planning problem. The 13-bus medium voltage network is evaluated considering the possibility of CHP units but also without. Results demonstrate that CHP, together with heat-only boiler units, can supply the district heat demand and contribute to network reliability. They can also reduce the expected energy not supplied and the power losses cost, avoiding the need to invest in new power lines for the considered lifetime project.This work has received funding from the EU's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013. Bruno Canizes is supported by FCT Funds through SFRH/BD/110678/2015 PhD scholarship and M. Ali Fotouhi Ghazvini is supported by FCT Funds through SFRH/BD/94688/2013 PhD scholarship.info:eu-repo/semantics/publishedVersio

Investigation of the effect of temperature on lithium-sulfur cell cycle life performance using system identification and x-ray tomography

In this study, cycle life performance of a prototype lithium-sulfur (Li−S) pouch cell is investigated using system identification and X-ray tomography methods. Li−S cells are subjected to characterization and ageing tests while kept inside a controlled-temperature chamber. After completing the experimental tests, two analytical approaches are used: i) The parameter variations of an equivalent-circuit model due to ageing are determined using a system identification technique. ii) Physical changes of the aged Li−S cells are analyzed using X-ray tomography. The results demonstrate that Li−S cell's degradation is significantly affected by temperature. Comparing to 10 °C, Li−S cell capacity fade happens 1.4 times faster at 20 °C whereas this number increases to 3.3 at 30 °C. In addition, X-ray results show a significant swelling when temperature rises from 10 to 20 °C, correspondingly the gas volume increases from 13 to 62 mm3.Innovate UK: TS/R013780/1. European Union funding: 814471. Engineering and Physical Sciences Research Council (EPSRC): EP/S003053/1, FIRG014, FIRG027

Overlap-based undersampling method for classification of imbalanced medical datasets.

Early diagnosis of some life-threatening diseases such as cancers and heart is crucial for effective treatments. Supervised machine learning has proved to be a very useful tool to serve this purpose. Historical data of patients including clinical and demographic information is used for training learning algorithms. This builds predictive models that provide initial diagnoses. However, in the medical domain, it is common to have the positive class under-represented in a dataset. In such a scenario, a typical learning algorithm tends to be biased towards the negative class, which is the majority class, and misclassify positive cases. This is known as the class imbalance problem. In this paper, a framework for predictive diagnostics of diseases with imbalanced records is presented. To reduce the classification bias, we propose the usage of an overlap-based undersampling method to improve the visibility of minority class samples in the region where the two classes overlap. This is achieved by detecting and removing negative class instances from the overlapping region. This will improve class separability in the data space. Experimental results show achievement of high accuracy in the positive class, which is highly preferable in the medical domain, while good trade-offs between sensitivity and specificity were obtained. Results also show that the method often outperformed other state-of-the-art and well-established techniques

Granular Cell Tumor Imaging Using Optical Coherence Tomography

Background: Granular cell tumor (GCT) is a relatively uncommon tumor that may affect the skin. The tumor can develop anywhere on the body, although it is predominately seen in oral cavities and in the head and neck regions. Here, we present the results of optical coherence tomography (OCT) imaging of a large GCT located on the abdomen of a patient. We also present an analytical method to differentiate between healthy tissue and GCT tissues. Materials and methods: A multibeam, Fourier domain, swept source OCT was used for imaging. The OCT had a central wavelength of 1305 ± 15 nm and lateral and axial resolutions of 7.5 and 10 µm, respectively. Qualitative and quantitative analyses of the tumor and healthy skin are reported. Results: Abrupt changes in architectures of the dermal and epidermal layers in the GCT lesion were observed. These architectural changes were not observed in healthy skin. Discussion: To quantitatively differentiate healthy skin from tumor regions, an optical attenuation coefficient analysis based on single-scattering formulation was performed. The methodology introduced here could have the capability to delineate boundaries of a tumor prior to surgical excision

Proteomics identifies neddylation as a potential therapy target in small intestinal neuroendocrine tumors.

Patients with small intestinal neuroendocrine tumors (SI-NETs) frequently develop spread disease; however, the underlying molecular mechanisms of disease progression are not known and effective preventive treatment strategies are lacking. Here, protein expression profiling was performed by HiRIEF-LC-MS in 14 primary SI-NETs from patients with and without liver metastases detected at the time of surgery and initial treatment. Among differentially expressed proteins, overexpression of the ubiquitin-like protein NEDD8 was identified in samples from patients with liver metastasis. Further, NEDD8 correlation analysis indicated co-expression with RBX1, a key component in cullin-RING ubiquitin ligases (CRLs). In vitro inhibition of neddylation with the therapeutic agent pevonedistat (MLN4924) resulted in a dramatic decrease of proliferation in SI-NET cell lines. Subsequent mass spectrometry-based proteomics analysis of pevonedistat effects and effects of the proteasome inhibitor bortezomib revealed stabilization of multiple targets of CRLs including p27, an established tumor suppressor in SI-NET. Silencing of NEDD8 and RBX1 using siRNA resulted in a stabilization of p27, suggesting that the cellular levels of NEDD8 and RBX1 affect CRL activity. Inhibition of CRL activity, by either NEDD8/RBX1 silencing or pevonedistat treatment of cells resulted in induction of apoptosis that could be partially rescued by siRNA-based silencing of p27. Differential expression of both p27 and NEDD8 was confirmed in a second cohort of SI-NET using immunohistochemistry. Collectively, these findings suggest a role for CRLs and the ubiquitin proteasome system in suppression of p27 in SI-NET, and inhibition of neddylation as a putative therapeutic strategy in SI-NET

Aqueous batteries as grid scale energy storage solutions

Energy storage technologies are required to make full use of renewable energy sources, and electrochemical cells offer a great deal flexibility in the design of energy systems. For large scale electrochemical storage to be viable, the materials employed and device production methods need to be low cost, devices should be long lasting and safety during operation is of utmost importance. Energy and power densities are of lesser concern. For these reasons, battery chemistries that make use of aqueous electrolytes are favorable candidates where large quantities of energy need to be stored. Herein we describe several different aqueous based battery chemistries and identify some of the research challenges currently hindering their wider adoption. Lead acid batteries represent a mature technology that currently dominates the battery market, however there remain challenges that may prevent their future use at the large scale. Nickel–iron batteries have received a resurgence of interest of late and are known for their long cycle lives and robust nature however improvements in efficiency are needed in order to make them competitive. Other technologies that use aqueous electrolytes and have the potential to be useful in future large-scale applications are briefly introduced. Recent investigations in to the design of nickel–iron cells are reported with it being shown that electrolyte decomposition can be virtually eliminated by employing relatively large concentrations of iron sulfide in the electrode mixture, however this is at the expense of capacity and cycle life