High Thermoelectric Performance of Multiwalled Carbon Nanotubes based Ionogels

Ionogels have emerged as promising thermoelectric materials with Seebeck coefficient 2–3 orders of magnitude higher than Seebeck coefficient of their inorganic counter parts. However, they suffer from the problem of low ionic conductivity, which can be improved with the addition of inorganic nanofillers to the ionogels. In the present work, thermoelectric performance of multiwall carbon nanotubes (MWCNTs) based ionogels (IGs) has been investigated. IGs were synthesized via in situ radical polymerization of polyethylene glycol 200 dimethacrylate (PEG200DMA) difunctional monomer in the presence of 1-butyl-3-methyl imidazolium tetrafluoroborate (an ionic liquid) and MWCNTs. Three composites namely MWCNTs-0.25, MWCNTs-0.5 and MWCNTs-1 were prepared having the concentration of MWCNTs by 0.25, 0.5 and 1 wt% respectively. A remarkable 75.3% enhancement in ionic conductivity was achieved for the MWCNTs-1 wt% ionogel compared to the base IG at 40 °C. This substantial improvement can be attributed to the "breathing polymer chain model," which describes the dissociation of ion aggregates due to the interaction between the ionic liquid and polymer chains. In terms of thermoelectric performance amongst the MWCNT ionogels, 0.25 wt% MWCNT-based ionogels was the optimized concentration with very high Seebeck coefficient of 1.70 mV/K and power factor of 4.1 µW/m. K along with excellent thermal stability up to 386 °C. These high-performing ionogels hold great promise for efficient utilization of low-grade thermal energy

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

WSN BASED INDUSTRY MONITORING AND CONTROL SYSTEM THROUGH IOT USING RASPBERRY PI

Intrusion plays an essential role as compared to other security systems, automation systems have were much demand as compare to other systems. Security policy of intrusion has big challenge in today's world. Not design proper security system in industry may damage and lead to cyber attack on the system; this may result in loss of important data. However, current intrusion system only works on security policy but it fails when actual implementation of the system. Work in this paper gives us correct approach of this and how to solve the thinks of instruction and Security related thinks. Security policy generally consists of Decisions and it ignores security policy implementation. In this paper Security consist of Table driven management Security and service cluster. In this project we have Genetic formula for sorting the data in proper manner . The task in system is reconfigured through associate integrated programming theme wherever system tasks and response tasks are mapped moreover, results from each simulations of numerical values and a real time application simulation showed that the projected technique will implement the Security system

Diet of Houbara bustard Chlamydotis undulata in Punjab, Pakistan

Volume: 20Start Page: 91End Page: 9

Tailoring the Scattering Response of Optical Nanocircuits Using Modular Assembly

Owing to the localized plasmon resonance of an ensemble of interacting plasmonic nanoparticles (NPs), there has been a tremendous drive to conceptualize complex optical nanocircuits with versatile functionalities. In comparison to modern research, there is still not a sufficient level of sophistication to treat the nanostructures as lumped circuits that can be adjusted into complex systems on the basis of a metatronic touchstone. Here, we present the design, assembly, and characterization of single relatively complex photonic nanocircuits by accurately positioning several metallic and dielectric nanoparticles acting as modular lumped elements. In this research, Au NPs along with silica NPs were used to compare the proficiency and precision of our lumped circuit model analytically. On increasing the size of an individual Au NP, the spectral peak resonance not only modifies but also causes more scattering efficiency which increases the fringe capacitance linearly and decreases the nanoinductance of lumped circuit element. The NPs-based assembly induced the required spectral resonance ascribed by simple circuit methods and are depicted to be actively reconfigurable by tuning the direction or polarization of input signals. Our work demonstrates a vital step toward developing the modern modular designing tools of complex electronic circuits into nanophotonic-related applications

Optimizing and Quantifying Gold Nanospheres Based on LSPR Label-Free Biosensor for Dengue Diagnosis

The localized surface plasmon resonance (LSPR) due to light–particle interaction and its dependence on the surrounding medium have been widely manipulated for sensing applications. The sensing efficiency is governed by the refractive index-based sensitivity (ηRIS) and the full width half maximum (FWHM) of the LSPR spectra. Thereby, a sensor with high precision must possess both requisites: an effective ηRIS and a narrow FWHM of plasmon spectrum. Moreover, complex nanostructures are used for molecular sensing applications due to their good ηRIS values but without considering the wide-band nature of the LSPR spectrum, which decreases the detection limit of the plasmonic sensor. In this article, a novel, facile and label-free solution-based LSPR immunosensor was elaborated based upon LSPR features such as extinction spectrum and localized field enhancement. We used a 3D full-wave field analysis to evaluate the optical properties and to optimize the appropriate size of spherical-shaped gold nanoparticles (Au NPs). We found a change in Au NPs’ radius from 5 nm to 50 nm, and an increase in spectral resonance peak depicted as a red-shift from 520 nm to 552 nm. Using this fact, important parameters that can be attributed to the LSPR sensor performance, namely the molecular sensitivity, FWHM, ηRIS, and figure of merit (FoM), were evaluated. Moreover, computational simulations were used to assess the optimized size (radius = 30 nm) of Au NPs with high FoM (2.3) and sharp FWHM (44 nm). On the evaluation of the platform as a label-free molecular sensor, Campbell’s model was performed, indicating an effective peak shift in the adsorption of the dielectric layer around the Au NP surface. For practical realization, we present an LSPR sensor platform for the identification of dengue NS1 antigens. The results present the system’s ability to identify dengue NS1 antigen concentrations with the limit of quantification measured to be 0.07 μg/mL (1.50 nM), evidence that the optimization approach used for the solution-based LSPR sensor provides a new paradigm for engineering immunosensor platforms

A Review on Overcoming Dual Challenges for Maize Cropping under High Plant Density: Stalk Lodging and Kernel Abortion

Increased optimal plant density is necessary in ensuring future food security by increasing crop productivity. However, maintaining relatively high plant density has to overcome two challenges i.e. kernel abortion and stalk lodging. The response of maize to increased plant density and the effects of increased plant density on maize productivity were discussed in this research. Increased plant density induces increased plant height, causes low photosynthetic capacity, limits the carbohydrate supply and increases kernel abortion. Also, increased plant density incurs a high risk of stalk lodging due to increased ear height and diminished stem diameter associated with reduced vascular bundles that provide, mechanical force. This review proposes a potential capacity of sucrose storage in stalk for tackling kernel abortion and stalk lodging. The mechanisms of boosting stem sugar storage with more efficient unloading, transporting, and storage in internodes are discussed

Mechanical Properties and Failure Mechanisms of Novel Resin-infused Thermoplastic and Conventional Thermoset 3D Fabric Composites

This paper presents an extensive comparison of the mechanical properties and failure mechanisms of a recently developed thermoplastic (Elium ®) 3D fabric-reinforced composite (3D-FRC) with the conventional thermoset (epoxy) 3D-FRC. Experiments involved tensile tests, compression tests, V-notch shear tests, and short beam shear tests for specimens produced through the vacuum-assisted resin infusion process in each case. These tests were used for the determination of in-plane elastic constants, failure strengths and for investigating the failure mechanisms. A micro-mechanical model validated against these experiments was used to predict the remaining orthotropic elastic constants. This work enhances our understanding of the mechanics of infusible thermoplastic 3D-FRC as a new class of emerging materials and provides useful data which substantiates that this unconventional thermoplastic resin is also easier to recycle, uses similar manufacturing processes and can be a suitable replacement for conventional thermoset resins.Universiti Teknologi PETRONAS, Malaysia, financial support under Yayasan Universiti Teknologi PETRONAS, grant number 015LC0-19

Synthesis and characterization of novel p-type chemically cross-linked ionogels with high ionic seebeck coefficient for low-grade heat harvesting

The low value of the Seebeck coefficient of the order of few μV/K in inorganic conductors, semiconductors and conducting polymers has inspired the researchers to explore alternative thermoelectric materials. In this work, a novel class of ionogels (IGs) has been synthesized with the aim of developing high-performance thermoelectric materials. Chemically cross-linked ionogels were prepared by the immobilization of ionic liquid, 1-butyl-3-methyl imidazolium tetrafluoroborate (BMIMBF4) in polyethylene glycol dimethacrylate (PEGDMA) matrix using azobisisobutyronitrile (AIBN) as the free radical initiator. The concentration of BMIMBF4 in IGs was varied from 60 to 90 wt (wt. %). The impact of variation of ionic liquid content on the thermoelectric properties of ionogels was analyzed by measuring their thermoelectric properties. Thermal stability, glass transition temperature (Tg), Surface morphology, microstructure, the crystallinity of IGs and nature of chemical interaction between the ionic liquid and polymer matrix were observed by performing TGA, DSC, FESEM, FETEM, XRD, and FTIR respectively. The ionic conductivities of neat BMIMBF4 and IGs were determined by electrochemical spectroscopy using SI 1260 Impedance/Gain-Phase Analyzer. It is worth noting that ionic conductivity (49.41 mS/cm) of IG with 90 wt % of BMIMBF4 is 10 times higher than the ionic conductivity of neat BMIMBF4 (4.5 mS/cm). The origin of this promising achievement (very high conductivity) lies in the “breathing polymer chain model”. The breathing in and out of polymer chains dissociates the ion aggregates resulting in a significant increase in ionic conductivity of IGs. A remarkably higher value of the Seebeck coefficient (2.35 mV/K) was achieved for IG with 60 wt % of BMIMBF4 and defined as ionic Seebeck coefficient because of its origin from the diffusion of ions of the ionic liquid. Due to the positive value of ionic Seebeck coefficient (in an analogy to positive Seebeck coefficient of p-type semiconductors) we termed the ionogels as p-type chemically crosslinked ionogels. A decrease in glass transition temperature of IGs with an increase in ionic liquid content was observed from DSC curves corresponding to an increase in mobility of cations and anions. TGA analysis showed that the synthesized IGs were highly thermally stable up to 390 °C. FESEM and FETEM images revealed that ionic liquid is well confined in the PEGDMA scaffold. The results indicate that ionogels may serve as promising candidates for future thermoelectric applications and also opens the perspective of engineering ionogels with high Seebeck coefficients and electrical conductivities. © 2019 Elsevier Lt