Adaptive Time Synchronization for Homogeneous WSNs

Wireless sensor networks (WSNs) are being used for observing real‐world phenomenon. It is important that sensor nodes (SNs) must be synchronized to a common time in order to precisely map the data collected by SNs. Clock synchronization is very challenging in WSNs as the sensor networks are resource constrained networks. It is essential that clock synchronization protocols designed for WSNs must be light weight i.e. SNs must be synchronized with fewer synchronization message exchanges. In this paper, we propose a clock synchronization protocol for WSNs where first of all cluster heads (CHs) are synchronized with the sink and then the cluster nodes (CNs) are synchronized with their respective CHs. CNs are synchronized with the help of time synchronization node (TSN) chosen by the respective CHs. Simulation results show that proposed protocol requires considerably fewer synchronization messages as compared with the reference broadcast synchronization (RBS) protocol and minimum variance unbiased estimation (MUVE) method. Clock skew correction mechanism applied in proposed protocol guarantees long term stability and hence decreases re‐ synchronization frequency thereby conserving more energ

Physico-chemical properties based differential toxicity of graphene oxide/reduced graphene oxide in human lung cells mediated through oxidative stress

Goraphene derivatives (GD) are currently being evaluated for technological and biomedical applications owing to their unique physico-chemical properties over other carbon allotrope such as carbon nanotubes (CNTs). But, the possible association of their properties with underlying in vitro effects have not fully examined. Here, we assessed the comparative interaction of three GD - graphene oxide (GO), thermally reduced GO (TRGO) and chemically reduced GO (CRGO), which significantly differ in their lateral size and functional groups density, with phenotypically different human lung cells; bronchial epithelial cells (BEAS-2B) and alveolar epithelial cells (A549). The cellular studies demonstrate that GD significantly ineternalize and induce oxidative stress mediated cytotoxicity in both cells. The toxicity intensity was in line with the reduced lateral size and increased functional groups revealed more toxicity potential of TRGO and GO respectively. Further, A549 cells showed more susceptibility than BEAS-2B which reflected cell type dependent differential cellular response. Molecular studies revealed that GD induced differential cell death mechanism which was efficiently prevented by their respective inhibitors. This is prior study to the best of our knowledge involving TRGO for its safety evaluation which provided invaluable information and new opportunities for GD based biomedical applications

Synthesis and in vitro evaluation of novel isatinincorporated thiadiazole hybrids as potential anti-breast cancer agents

Purpose: To synthesis and characterize some novel isatin-incorporated thiadiazoles and screen them for anti-breast cancer activity in human breast adenocarcinoma cells (MCF-7).Method: A series of isatin incorporated Schiff bases of thiadiazoles (3a-3l) was synthesized by reaction of substituted thiadiazoles (1a-1d) with isatin (2a) and N-alkyl substituted isatin (2b-2c) and characterized by elemental analysis, IR, 1H NMR, 13C NMR and LCMS. The newly synthesized compounds were screened for their in-vitro cytotoxicity against MCF-7 cell lines by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) colorimetric and Sulforhodamine B (SRB) methods.Results: Compounds 3a, 3c, 3d, 3g and 3j showed anticancer activity in both MTT and SRB assay. Compound 3-(5-(4-chlorophenyl)-1,3,4-thiadiazol-2-ylimino)-1-ethylindolin-2-one (3g) showed most potent cytotoxic activity against MCF-7 cell lines.Conclusion: The novel isatin incorporated thiadiazoles synthesized and characterized in this study possess anti-cancer activities in human breast adenocarcinoma cells (MCF-7). This can possibly lead to emergence of new anti-breast cancer agents.Keywords: Thiadiazoles, Isatin, In-vitro cytotoxicity, Human breast adenocarcinoma cells (MCF-7), SRB assa

Development of transgenic cucumber mosaic virus (CMV) resistant gerbera plants expressing CMV coat protein gene

121-130Gerbera (Gerbera jamesonii L.) has its immense importance to the floriculture industry worldwide. The gerbera flower production has been hampered by various viruses, among them cucumber mosaic virus (CMV) has shown considerable damage.As natural resistance to CMV is absent in gerbera, here, we have made an attempt to develop transgenic gerbera plants expressing coat protein (CP) gene of CMV via Agrobacterium mediated transformation of base petiole explants for genetic resistance to CMV infection. Among the 44 putative transgenic gerbera plant acclimatized, 39 were found positive for integration of CP gene by polymerase chain reaction and southern hybridization assay using their specific primer and probe respectively. Northern hybridization assay using CP gene specific probe confirmed the transcription of transgene in all 39 transgenic plants. These plants showed translation of CP during DAS-ELISA when tested with antiserum specific to CP of CMV. These 39 plants when challenged by mechanical inoculations with CMV gerbera isolate showed virus resistance in 53% (21 out of 39) plants, virus tolerance (delayed mild symptom) in 33% (13/39) plants, while rest 12.8% (5/39) plants showed severe disease symptoms. The CP mediated resistance of CMV in transgenic gerbera is being reported for the first time from India

Ageratum enation virus Infection Induces Programmed Cell Death and Alters Metabolite Biosynthesis in Papaver somniferum

A previously unknown disease which causes severe vein thickening and inward leaf curl was observed in a number of opium poppy (Papaver somniferum L.) plants. The sequence analysis of full-length viral genome and associated betasatellite reveals the occurrence of Ageratum enation virus (AEV) and Ageratum leaf curl betasatellite (ALCB), respectively. Co-infiltration of cloned agroinfectious DNAs of AEV and ALCB induces the leaf curl and vein thickening symptoms as were observed naturally. Infectivity assay confirmed this complex as the cause of disease and also satisfied the Koch’s postulates. Comprehensive microscopic analysis of infiltrated plants reveals severe structural anomalies in leaf and stem tissues represented by unorganized cell architecture and vascular bundles. Moreover, the characteristic blebs and membranous vesicles formed due to the virus-induced disintegration of the plasma membrane and intracellular organelles were also present. An accelerated nuclear DNA fragmentation was observed by Comet assay and confirmed by TUNEL and Hoechst dye staining assays suggesting virus-induced programmed cell death. Virus-infection altered the biosynthesis of several important metabolites. The biosynthesis potential of morphine, thebaine, codeine, and papaverine alkaloids reduced significantly in infected plants except for noscapine whose biosynthesis was comparatively enhanced. The expression analysis of corresponding alkaloid pathway genes by real time-PCR corroborated well with the results of HPLC analysis for alkaloid perturbations. The changes in the metabolite and alkaloid contents affect the commercial value of the poppy plants

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM<inf>2·5</inf> air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation: Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Funding: Bill & Melinda Gates Foundation

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : an analysis of data from the Global Burden of Disease Study 2019

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2.5 originating from ambient and household air pollution.Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2.5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure-response curve from the extracted relative risk estimates using the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2.5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2.5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals.Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2.5 exposure, with an estimated 3.78 (95% uncertainty interval 2.68-4.83) deaths per 100 000 population and 167 (117-223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13.4% (9.49-17.5) of deaths and 13.6% (9.73-17.9) of DALYs due to type 2 diabetes were contributed by ambient PM2.5, and 6.50% (4.22-9.53) of deaths and 5.92% (3.81-8.64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2.5.Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2.5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.Peer reviewe

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : An analysis of data from the Global Burden of Disease Study 2019

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis