Elastic and electrical properties of graphite and talc filler reinforced polypropylene (PP) composites

Graphite filler reinforced polypropylene (PP) composites and talc filler reinforced (PP) composites were prepared by compression molding at 160 ºC. Mechanical and electrical properties were studied. The tensile strength of the composites decreases with the increase of filler addition and also with the increase of wt.% of filler. But, a slight improvement of the Young's modulus of the filaments reinforced with different wt.% of filler is observed. It was found that the Bulk density of test materials increased with the fillers content. Capacitance decreases with the increase of both frequency and voltage which suggest good electrical properties of PP-graphite composites and PP-talc composites. All of these results indicated that PP-graphite composites are better than the PP-talc composites

Eight-Chain and Full-Network Models and Their Modified Versions for Rubber Hyperelasticity: A Comparative Study

The eight-chain model, also known as Arruda-Boyce model, is widely used to capture the rate-independent hyperelastic response of rubber-like materials. The parameters of this model are physically based and explained from micromechanics of chain molecules. Despite its excellent performance with only two material parameters to capture bench measurements in uniaxial and pure shear regime, the model is known to be significantly deficient in predicting the equibiaxial data. To ameliorate such drawback, over the years, several modified versions of this successful model have been proposed in the literature. The so-called full-network model is another micromechanically motivated chain model, which has also few modified versions in the literature. For this study, two modified versions of the full-network model have been selected. In this contribution, five modified versions of the Arruda-Boyce model and two modified versions of full-network model are critically compared with the classical eight-chain model for their adequacy in representing equibiaxial data. To do a comparison of all selected models in reproducing the well-known Treloar data, the analytical expressions for the three homogeneous deformation modes, that is, uniaxial tension, equibiaxial tension, and pure shear have been derived and the performances of the selected models are analysed. The comparative study demonstrates that modified Flory-Erman model, Gornet-Desmorat (GD) model, Meissner-Matějka model, and bootstrapped eight-chain model predict well the three deformation modes compare to the classical eight-chain model

Identification of novel transcripts and peptides in developing murine lens.

We previously investigated the transcriptome and proteome profiles of the murine ocular lens at six developmental time points including two embryonic (E15 and E18) and four postnatal time points (P0, P3, P6, and P9). Here, we extend our analyses to identify novel transcripts and peptides in developing  mouse lens. We identified a total of 9,707 novel transcripts and 325 novel fusion genes in developing mouse lens. Additionally, we identified 13,281 novel alternative splicing (AS) events in mouse lens including 6,990 exon skipping (ES), 2,447 alternative 3' splice site (A3SS), 1,900 alternative 5' splice site (A5SS), 1,771 mutually exclusive exons (MXE), and 173 intron retention (IR). Finally, we integrated our OMIC (Transcriptome and Proteome) datasets identifying 20 novel peptides in mouse lens. All 20 peptides were validated through matching MS/MS spectra of synthetic peptides. To the best of our knowledge, this is the first report integrating OMIC datasets to identify novel peptides in developing murine lens

Ionization Potential of the Helium Atom

Ground state ionization potential of the He^4 atom is evaluated to be 5 945 204 221 (42) MHz. Along with lower order contributions, this result includes all effects of the relative orders alpha^4, alpha^3*m_e/m_alpha and alpha^5*ln^2(alpha).Comment: 4 page

Modelling Future Coronary Heart Disease Mortality to 2030 in the British Isles.

OBJECTIVE: Despite rapid declines over the last two decades, coronary heart disease (CHD) mortality rates in the British Isles are still amongst the highest in Europe. This study uses a modelling approach to compare the potential impact of future risk factor scenarios relating to smoking and physical activity levels, dietary salt and saturated fat intakes on future CHD mortality in three countries: Northern Ireland (NI), Republic of Ireland (RoI) and Scotland. METHODS: CHD mortality models previously developed and validated in each country were extended to predict potential reductions in CHD mortality from 2010 (baseline year) to 2030. Risk factor trends data from recent surveys at baseline were used to model alternative future risk factor scenarios: Absolute decreases in (i) smoking prevalence and (ii) physical inactivity rates of up to 15% by 2030; relative decreases in (iii) dietary salt intake of up to 30% by 2030 and (iv) dietary saturated fat of up to 6% by 2030. Probabilistic sensitivity analyses were then conducted. RESULTS: Projected populations in 2030 were 1.3, 3.4 and 3.9 million in NI, RoI and Scotland respectively (adults aged 25-84). In 2030: assuming recent declining mortality trends continue: 15% absolute reductions in smoking could decrease CHD deaths by 5.8-7.2%. 15% absolute reductions in physical inactivity levels could decrease CHD deaths by 3.1-3.6%. Relative reductions in salt intake of 30% could decrease CHD deaths by 5.2-5.6% and a 6% reduction in saturated fat intake might decrease CHD deaths by some 7.8-9.0%. These projections remained stable under a wide range of sensitivity analyses. CONCLUSIONS: Feasible reductions in four cardiovascular risk factors (already achieved elsewhere) could substantially reduce future coronary deaths. More aggressive polices are therefore needed in the British Isles to control tobacco, promote healthy food and increase physical activity

The incidence and prevalence of delirium across palliative care settings: A systematic review

© The Author(s) 2019. Background: Delirium is a common and distressing neurocognitive condition that frequently affects patients in palliative care settings and is often underdiagnosed. Aim: Expanding on a 2013 review, this systematic review examines the incidence and prevalence of delirium across all palliative care settings. Design: This systematic review and meta-analyses were prospectively registered with PROSPERO and included a risk of bias assessment. Data sources: Five electronic databases were examined for primary research studies published between 1980 and 2018. Studies on adult, non-intensive care and non-postoperative populations, either receiving or eligible to receive palliative care, underwent dual reviewer screening and data extraction. Studies using standardized delirium diagnostic criteria or valid assessment tools were included. Results: Following initial screening of 2596 records, and full-text screening of 153 papers, 42 studies were included. Patient populations diagnosed with predominantly cancer (n = 34) and mixed diagnoses (n = 8) were represented. Delirium point prevalence estimates were 4%–12% in the community, 9%–57% across hospital palliative care consultative services, and 6%–74% in inpatient palliative care units. The prevalence of delirium prior to death across all palliative care settings (n = 8) was 42%–88%. Pooled point prevalence on admission to inpatient palliative care units was 35% (confidence interval = 0.29–0.40, n = 14). Only one study had an overall low risk of bias. Varying delirium screening and diagnostic practices were used. Conclusion: Delirium is prevalent across all palliative care settings, with one-third of patients delirious at the time of admission to inpatient palliative care. Study heterogeneity limits meta-analyses and highlights the future need for rigorous studies

Distributed energy resources and the application of AI, IoT, and blockchain in smart grids

Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic, knowledge-based systems, and neural networks. They have brought advances in controlling DER-based SG. The IoT and BC have also enabled various services like data sensing, data storage, secured, transparent, and traceable digital transactions among ESN peers and its clusters. These promising technologies have gone through fast technological evolution in the past decade, and their applications have increased rapidly in ESN. Hence, this study discusses the SG and applications of AI, IoT, and BC. First, a comprehensive survey of the DER, power electronics components and their control, electric vehicles (EVs) as load components, and communication and cybersecurity issues are carried out. Second, the role played by AI-based analytics, IoT components along with energy internet architecture, and the BC assistance in improving SG services are thoroughly discussed. This study revealed that AI, IoT, and BC provide automated services to peers by monitoring real-time information about the ESN, thereby enhancing reliability, availability, resilience, stability, security, and sustainability

Simulation of High Conversion Efficiency and Open-circuit Voltages Of {\alpha}-si/poly-silicon Solar Cell

The P+ {\alpha}-Si /N+ polycrystalline solar cell is molded using the AMPS-1D device simulator to explore the new high efficiency thin film poly-silicon solar cell. In order to analyze the characteristics of this device and the thickness of N+ poly-silicon, we consider the impurity concentration in the N+ poly-silicon layer and the work function of transparent conductive oxide (TCO) in front contact in the calculation. The thickness of N+ poly-silicon has little impact on the device when the thickness varies from 20 {\mu}m to 300 {\mu}m. The effects of impurity concentration in polycrystalline are analyzed. The conclusion is drawn that the open-circuit voltage (Voc) of P+ {\alpha}-Si /N+ polycrystalline solar cell is very high, reaching 752 mV, and the conversion efficiency reaches 9.44%. Therefore, based on the above optimum parameters the study on the device formed by P+ {\alpha}-Si/N+ poly-silicon is significant in exploring the high efficiency poly-silicon solar cell.Comment: 8 pages 6figures, 1 table

Numerical study of crack path by MMCG specimen using M integral

The mixed mode loading configuration occurs in many civil engineering and mechanical applications. In wood material, the study of this problem is very important due to the orthotropic character and the heterogeneity of the material. In order to study the mixed mode loading in wood material, Moutou Pitti et al [1] have proposed a new specimen called Mixed Mode Crack Growth (MMCG). The main goal of this geometry is to propose a decrease of the energy release rate during the crack growth process. In this case, the fracture parameters can be decoupled into Mode I and Mode II in order to determine the impact of time during creep crack test. The present work proposes to study the crack path stability in MMCG specimen for different sizes and thicknesses. The M? integral, combining real and virtual mechanical displacement fields is used in order to separate numerically mode I and mode II in the mixed mode ratio. The stability is shown for the opening mode (Mode I), the shear mode (Mode II), and the mixed mode of 15°, 30°, 45°, 60°, 75° by computing the energy release rate versus the crack length. Finally, it is shown that the MMCG specimen can be reduced in various shape and used for example in small climate chamber in order to perform creep test at different temperature and moisture content levels