A method for determining the distribution of carbon nanotubes in nanocomposites by electric conductivity

Carbon nanotube (CNT) polymer nanocomposites are one of the most promising materials due to their remarkable mechanical properties as well as the electrical conductivity, which offers the capability of monitoring the deformation and damage of composite structures by measuring the related conductivity variations. However, quantifying the distribution of CNTs inside the material remains a challenge with respects to both experimental and numerical works. In the current study, the electrical conductivity was used to determine the microstructure of CNT-reinforced polymer. By introducing a modified parameter related to the polar angle of CNTs, the mechanical properties as well as the electrical conductivity change with respect to deformation of nanocomposites can be replicated. After validation by experimental data from the multi-walled CNT/polymer nanocompo sites under tensile loading, the capability of the current method was then studied for composites with various weight fractions of nanotubes. (C) 2022 The Authors. Published by Elsevier B.V

Stimulatory Effects of Gamma Irradiation on Phytochemical Properties, Mitotic Behaviour, and Nutritional Composition of Sainfoin ( Onobrychis viciifolia

Sainfoin (Onobrychis viciifolia Scop. Syn. Onobrychis sativa L.) is a bloat-safe forage crop with high levels of tannins, which is renowned for its medicinal qualities in grazing animals. Mutagenesis technique was applied to investigate the influence of gamma irradiation at 30, 60, 90, and 120 Gy on mitotic behavior, in vitro growth factors, phytochemical and nutritional constituents of sainfoin. Although a percentage of plant necrosis and non-growing seed were enhanced by irradiation increment, the germination speed was significantly decreased. It was observed that gamma irradiated seeds had higher value of crude protein and dry matter digestibility compared to control seeds. Toxicity of copper was reduced in sainfoin irradiated seeds at different doses of gamma rays. Anthocyanin content also decreased in inverse proportion to irradiation intensity. Accumulation of phenolic and flavonoid compounds was enhanced by gamma irradiation exposure in leaf cells. HPLC profiles differed in peak areas of the two important alkaloids, Berberine and Sanguinarine, in 120 Gy irradiated seeds compared to control seeds. There were positive correlations between irradiation dose and some abnormality divisions such as laggard chromosome, micronucleus, binucleated cells, chromosome bridge, and cytomixis. In reality, radiocytological evaluation was proven to be essential in deducing the effectiveness of gamma irradiation to induce somaclonal variation in sainfoin

Using Support Vector Machine and Evolutionary Profiles to Predict Antifreeze Protein Sequences

Antifreeze proteins (AFPs) are ice-binding proteins. Accurate identification of new AFPs is important in understanding ice-protein interactions and creating novel ice-binding domains in other proteins. In this paper, an accurate method, called AFP_PSSM, has been developed for predicting antifreeze proteins using a support vector machine (SVM) and position specific scoring matrix (PSSM) profiles. This is the first study in which evolutionary information in the form of PSSM profiles has been successfully used for predicting antifreeze proteins. Tested by 10-fold cross validation and independent test, the accuracy of the proposed method reaches 82.67% for the training dataset and 93.01% for the testing dataset, respectively. These results indicate that our predictor is a useful tool for predicting antifreeze proteins. A web server (AFP_PSSM) that implements the proposed predictor is freely available

Antioxidant rich flavonoids from Oreocnide integrifolia enhance glucose uptake and insulin secretion and protects pancreatic β-cells from streptozotocin insult

<p>Abstract</p> <p>Background</p> <p>Insulin deficiency is the prime basis of all diabetic manifestations and agents that can bring about insulin secretion would be of pivotal significance for cure of diabetes. To test this hypothesis, we carried out bioactivity guided fractionation of <it>Oreocnide integrifolia </it>(Urticaceae); a folklore plant consumed for ameliorating diabetic symptoms using experimental models.</p> <p>Methods</p> <p>We carried out bioassay guided fractionation using RINmF and C2C12 cell line for glucose stimulated insulin secretion (GSIS) and glucose uptake potential of fractions. Further, the bioactive fraction was challenged for its GSIS in cultured mouse islets with basal (4.5 mM) and stimulated (16.7 mM) levels of glucose concentrations. The Flavonoid rich fraction (FRF) was exposed to 2 mM streptozotocin stress and the anti-ROS/RNS potential was evaluated. Additionally, the bioactive fraction was assessed for its antidiabetic and anti-apoptotic property <it>in-vivo </it>using multidose streptozotocin induced diabetes in BALB/c mice.</p> <p>Results</p> <p>The results suggested FRF to be the most active fraction as assessed by GSIS in RINm5F cells and its ability for glucose uptake in C2C12 cells. FRF displayed significant potential in terms of increasing intracellular calcium and cAMP levels even in presence of a phosphodiesterase inhibitor, IBMX in cultured pancreatic islets. FRF depicted a dose-dependent reversal of all the cytotoxic manifestations except peroxynitrite and NO formation when subjected <it>in-vitro </it>along with STZ. Further scrutinization of FRF for its <it>in-vivo </it>antidiabetic property demonstrated improved glycemic indices and decreased pancreatic β-cell apoptosis.</p> <p>Conclusions</p> <p>Overall, the flavonoid mixture has shown to have significant insulin secretogogue, insulinomimetic and cytoprotective effects and can be evaluated for clinical trials as a therapeutant in the management of diabetic manifestations.</p

Terpenoid biotransformations by Mucor species

Terpenoids are natural products of great interest due to their widespread use in agrochemicals, drugs, fragrances, flavouring and pigments. Biocatalysts are increasingly being used in the search for new derivatives with improved properties especially to obtain structurally novel leads for new drugs which are difficult to obtain using conventional organic chemical methods. This review, covering up to the end of 2012, reports on the application of Mucor species as catalysts in terpenoid biotransformation to obtain new drug targets, enhance pharmacological activity or decrease the unwanted effects of starting material

Imbalanced Multi-Modal Multi-Label Learning for Subcellular Localization Prediction of Human Proteins with Both Single and Multiple Sites

It is well known that an important step toward understanding the functions of a protein is to determine its subcellular location. Although numerous prediction algorithms have been developed, most of them typically focused on the proteins with only one location. In recent years, researchers have begun to pay attention to the subcellular localization prediction of the proteins with multiple sites. However, almost all the existing approaches have failed to take into account the correlations among the locations caused by the proteins with multiple sites, which may be the important information for improving the prediction accuracy of the proteins with multiple sites. In this paper, a new algorithm which can effectively exploit the correlations among the locations is proposed by using Gaussian process model. Besides, the algorithm also can realize optimal linear combination of various feature extraction technologies and could be robust to the imbalanced data set. Experimental results on a human protein data set show that the proposed algorithm is valid and can achieve better performance than the existing approaches

Economic-Environmental Analysis of Combined Heat and Power-Based Reconfigurable Microgrid Integrated with Multiple Energy Storage and Demand Response Program

Microgrids (MGs) are solutions to integrate high shares of variable renewable energy which can contribute to more economical and environmental benefits, as well as improving the energy supply efficiency. One significant potential of MGs is an expanded opportunity to use the waste heating energy from the conversion of the primary fuel (such as natural gas) to generate electricity. The use of waste heat in combined heat and power (CHP)-based MG is more efficient to meet local load and decrease the emission pollution. Hence, this paper elaborates on optimal multi-objective scheduling of CHP-based MG coupled with compressed air energy storage (CAES), renewable energy, thermal energy storage (TES), and demand response programs through shiftable loads, which considers a reconfiguration capability. The embedded CAES, in addition to the charging/discharging scheme, can operate in a simple cycling mode and serve as a generation resource to supply local load in an emergency condition. The daily reconfiguration of MG will introduce a new generation of MG named reconfigurable microgrid (RMG) that offers more flexibility and enhances system reliability. The RMG is coupled with TES to facilitate the integration of the CHP unit that enables the operator to participate in the thermal market, in addition to the power market. The main intents of the proposed multi-objective problem are to minimize the operation cost along with a reduction in carbon emission. The epsilon-constraint technique is used to solve the multi-objective problem while fuzzy decision making is implemented to select an optimal solution among all the Pareto solutions. The electricity prices and wind power generation variation are captured as random variables in the model and the scenario-based stochastic approach is used to handle them. Simulation results prove that the simultaneous integration of multiple technologies in CHP-based RMG decreases the operation cost and emission up to 3% and 10.28%, respectively

Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995–2050

© 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods: We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories—government, out-of-pocket, and prepaid private health spending—and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings: Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89–4·12) annually, although it grew slower in per capita terms (2·72% [2·61–2·84]) and increased by less than $1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5·55$8·0 trillion (7·8–8·1) in 2016 (comprising 8·6% [8·4–8·7] of the global economy and $10·3 trillion [10·1–10·6] in purchasing-power parity-adjusted dollars), with a per capita spending of US$5252 (5184–5319) in high-income countries, $491 (461–524) in upper-middle-income countries,$81 (74–89) in lower-middle-income countries, and $40 (38–43) in low-income countries. In 2016, 0·4$9·5 billion, 24·3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ($644·7 million in 2018). Globally, health spending is projected to increase to$15·0 trillion (14·0–16·0) by 2050 (reaching 9·4% [7·6–11·3] of the global economy and $21·3 trillion [19·8–23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1·84% (1·68–2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0·6% (0·6–0·7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130·2 (122·9–136·9) in 2016 and is projected to remain at similar levels in 2050 (125·9 [113·7–138·1]). The decomposition analysis identified governments’ increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Interpretation: Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets. Funding: Bill & Melinda Gates Foundation

Sustainable supply chain management towards disruption and organizational ambidexterity:A data driven analysis

Balancing sustainability and disruption of supply chains requires organizational ambidexterity. Sustainable supply chains prioritize efficiency and economies of scale and may not have sufficient redundancy to withstand disruptive events. There is a developing body of literature that attempts to reconcile these two aspects. This study gives a data-driven literature review of sustainable supply chain management trends toward ambidexterity and disruption. The critical review reveals temporal trends and geographic distribution of literature. A hybrid of data-driven analysis approach based on content and bibliometric analyses, fuzzy Delphi method, entropy weight method, and fuzzy decision-making trial and evaluation laboratory is used on 273 keywords and 22 indicators obtained based on the experts’ evaluation. The most important indicators are identified as supply chain agility, supply chain coordination, supply chain finance, supply chain flexibility, supply chain resilience, and sustainability. The regions show different tendencies compared with others. Asia and Oceania, Latin America and the Caribbean, and Africa are the regions needs improvement, while Europe and North America show distinct apprehensions on supply chain network design. The main contribution of this review is the identification of the knowledge frontier, which then leads to a discussion of prospects for future studies and practical industry implementation