Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

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

Epidemiology of allergic rhinitis and associated risk factors in Asia

10.1186/s40413-018-0198-zWorld Allergy Organization Journal1111

Epidemiology of allergic rhinitis and associated risk factors in Asia

World Allergy Organization Journal11117

Ionic liquid design for enhanced carbon dioxide capture by computer-aided molecular design approach

Carbon capture and storage is an emerging technology to mitigate carbon dioxide (CO2) emissions from industrial sources such as power plants. Post-combustion capture based on aqueous amine scrubbing is one of the most promising technologies for CO2 capture currently. This technology, however, possesses a number of shortcomings, including high regeneration energy requirement, high solvent loss, degradation of solvent, etc. To overcome these limitations, researchers suggested different solvents and alternative technologies to replace the current amine scrubbing technique. Ionic liquids (ILs) are the most potential substitute among all. This is mainly because they have negligible vapour pressure and high thermal stability, which reduce solvent loss. However, there are up to a million possible combinations of cation and anion that may make up the ILs, which makes experimental works very time consuming and costly. In this work, optimal IL solvents specifically for carbon capture purpose are designed using computer-aided molecular design approach. This approach utilises group contribution method to estimate the thermophysical properties of ILs, and UNIFAC model to predict CO2 solubility in the ILs. Structural constraints are included to ensure that the synthesised ILs structure will satisfy the bonding requirement. This work focuses on design of ILs based on a physical absorption mechanism, and hence no chemical reaction is involved. The results show that the designed ILs are capable of capturing CO2 and their predicted properties are in good agreement with properties as determined through experimental works. Springer-Verlag Berlin Heidelberg 2015.The financial support from Faculty of Engineering Dean's Ph.D. scholarship and NPRP Grant No 6-678-2-280 from the Qatar National Research Fund (a member of Qatar Foundation) are both gratefully acknowledged.Scopu

Ionic liquid design for enhanced carbon dioxide capture - A computer aided molecular design approach

Greenhouse gases emission is known as the main factor of climate change, and carbon dioxide (CO2) makes up vast majority of them. Carbon capture and storage (CCS) is a vital technology to mitigate industrial CO2 emissions, which is mainly generated in power plants. Currently, post-combustion capture based on aqueous amine scrubbing is considered as the most suitable technology for CO2 capture. However, the use of amine for CO2 capture has some disadvantages, such as high energy required for solvent regeneration, high solvent loss, and degradation of solvent. Recently, ionic liquids (ILs) are considered as potential alternative, because they have negligible vapour pressure, and high thermal stability. In addition, through matching of cations and anions, ILs provide a flexibility to tune their properties. However, due to vast number of potential ILs, time and expense required to obtain the optimal ILs for CO2 absorption through experimentation is unaffordable. This work presents a Computer-Aided Molecular Design (CAMD) approach for the design and selection of optimal ILs specifically for the purpose of CO2 capture. The approach utilises group contribution method to estimate the thermophyscial properties of ILs, by considering the structural constraints and allowed combination of cations and anions. Predicted properties of the potential candidates are in good agreement of experimentally measured properties. Copyright 2014 AIDIC Servizi S.r.l.Scopu

3D printing of surface characterisation and finite element analysis improvement of PEEK-HAP-GO in bone implant

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Research and development of polyetheretherketone (PEEK) composites with high thermal conductivities and ideal thermal stabilities have become one of the hot topics in composites. However, not all PEEK composites have the necessary characteristics adequate fracture toughness to resist forces and crack propagation, with an improved mechanical and structural properties. This research evaluates a novel computational surface characterisation and finite element analysis (FEA) of polyetheretherketone and hydroxyapatite graphene oxide (PEEK-HAP-GO) in the process of 3D printing to improve fracture toughness to resist forces and crack propagation. It also focuses on increasing the hydrophilicity, surface roughness, and coating osteoconductive of PEEK-HAP-GO for the bone implant. Compression and tensile tests were performed to investigate the mechanical properties of the PEEK-HAP-GO structure. The addition of calcium phosphate and the incorporation of porosity in PEEK-HAP-GO has been identified as an effective way to improve the osseointegration of bone-implant interfaces of PEEK-HAP-GO. The further analytical structure of the particle was performed, evaluating the surface luminance structure and the profile structure of composite material in 3D printing, analysing the profile curve of the nanostructure from the scanning electron microscope (SEM). The results of the uniaxial compression tests in new PEEK-HAP-GO biodegradable materials show good compressive strength suitable for loading applications. It shows melt-blending with bioactive nanoparticles can be used to produce bioactive nanocomposites like HAP-GO and is used to modify the surface structure of PEEK implants in order to make it more bioactive

A comparison of bioreactors for culture of fetal mesenchymal stem cells for bone tissue engineering

10.1016/j.biomaterials.2010.07.097Biomaterials31338684-8695BIMA

Food for thought: endocannabinoid modulation of lipogenesis

An emerging body of evidence implicates peripheral and central endocannabinoid pathways in the regulation of feeding behavior and body weight. A report in this issue of the JCI demonstrates the presence of a common endocannabinoid-regulated molecular pathway for peripheral lipogenic and central appetitive regulation. This pathway involves the activation of the transcription factor SREBP-1c and its associated enzymes, acetyl-CoA carboxylase-1 and fatty acid synthase, in the liver and hypothalamus. Activation of cannabinoid receptor 1 (CB(1)) in liver plays a key role in increased serum lipid production, fatty liver, and possibly diet-induced obesity. Conversely, stimulation of these receptors in the hypothalamus may lead to an increase in food consumption. Thus, targeting both of these pathways with CB(1) antagonists could promote sustained weight loss and favorable serum lipid profiles in obese patients