Study of the magnetostructural transition in critical-element free Mn1−xNi1−xFe2xSi0.95Al0.05

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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

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Magnetically Functional Materials:Design and 3D Printing

3D printing has revolutionized the manufacturing landscape by offering unparalleled design flexibility, rapid prototyping, and the ability to produce small batches of customized components. In the same vein, development of magnetic bonded materials has opened new possibilities for the customization and fabrication of magnetic structures with potential applications in various industries, including automotive, aerospace, and medical devices. However, challenges remain in the field of 3D printing of magnetic materials, such as producing small quantities, customized designs and developing reliable fabrication methods for hard magnetic materials.Fused filament fabrication (FFF) 3D printing presents a promising solution to these challenges, as it enables the creation of intricate structures with tailored magnetic properties. Despite its potential, there is currently no commercial hard magnetic filament available. To address this gap, we developed a custom filament with various filling factors by using ABS as an effective binder for the hard magnetic particles. This approach allowed us to achieve precise control over the magnetic properties and optimize the performance of the printed components.As a proof of concept showing the versatility and utility of our custom hard magnetic filaments, we designed, and 3D printed a passive shimming system in a Halbach array configuration to improve the magnetic field homogeneity. This application showcases the potential of our filament for producing complex magnetic structures with tailored properties, which could lead to advancements in a wide range of industries that rely on magnetic materials.Additionally, a near-room-temperature magneto-responsive elastomer within the context of soft robotics was developed. The elastomer exhibits unique actuation properties, combining the advantages of magnetically and thermally responsive actuators, with potential applications in a wide range of industries. By employing specific types of soft magnetic materials, and mixing them with silicone rubber, a thermo-magneto actuator with a low responsive temperature was created. The study incorporated finite element modeling and experimental data to understand the elastomer's behavior, providing a foundation for future research in soft robotics applications.In summary, our work highlights the great potential of 3D printing for the development of hard magnetic materials and demonstrates the potential of FFF 3D printing to create customized magnetic components and addresses fabrication challenges in various applications

Interpretable clustering of epigenetic marks by incorporating their relationships to genes and their functions

Recent advances in high-throughput technologies have allowed researchers to measure epigenetic information, such as the methylation levels of CpG sites or the accessibility levels of chromatin, for hundreds of thousands of genomic regions. Many statistical methods have been developed to cluster these epigenetic measurements into contiguous, functional regions involved in biological processes or disease. In this project, I proposed a new approach for clustering the epigenetic marks into regions. The proposed model defines each region as the set of epigenetic marks located within a predefined window around the transcript start site of a gene. Therefore, the one-to-one mapping between the regions and genes helps elucidate the epigenetic functions of regions by looking at the functions of genes mapped to the regions. The proposed statistical model uses a weighted linear model that combines the values of marks in each region to construct a gene-level representation for that region. The weights of marks in each region are estimated using a scalable, coordinate descent optimization algorithm. I evaluated the quality of the inferred gene-level representations on two types of epigenetic data: chromatin accessibility and DNA methylation. When applied to the chromatin accessibility data, the results showed that the gene-level representations inferred by the proposed model could represent the variations in the expression levels of genes across samples with higher accuracy compared to the baseline methods. The model performance declined when applied to the DNA methylation data. To address this observation, I investigated the role of the type and quality of the epigenetic data on the model performance and offered a set of recommendations for using the proposed model effectively.Science, Faculty ofGraduat

Recurrent spatio-temporal modeling of check-ins in location-based social networks.

Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users' movements, and finding the latent influence network. It is observed that users have periodic patterns in their movements. Also, they are influenced by the locations that their close friends recently visited. Leveraging these two observations, we propose a probabilistic model based on a doubly stochastic point process with a periodic-decaying kernel for the time of check-ins and a time-varying multinomial distribution for the location of check-ins of users in the location-based social networks. We learn the model parameters by using an efficient EM algorithm, which distributes over the users, and has a linear time complexity. Experiments on synthetic and real data gathered from Foursquare show that the proposed inference algorithm learns the parameters efficiently and our method models the real data better than other alternatives

Additive Manufacturing of Hard Magnetic Passive Shims to Increase Field Homogeneity of a Halbach Magnet

Obtaining a highly homogeneous magnetic field is desired for field-controlled applications. For example, the resolution of magnetic analysis methods can be improved by generating a stronger and more homogeneous field over the region of interest (ROI). A set of 3D-printed passive shims is fabricated using additive manufacturing to improve the magnetic field homogeneity of a Halbach magnet assembly. The feedstock is a custom acrylonitrile butadiene styrene (ABS)-hard magnet composite filament filled with 60% wt. isotropic NdFeB. Additionally, a method for investigating the remanence is developed and validated. The result reveals a good agreement between the new method and existing measurement techniques for the remanence of permanent magnets. It is also shown that the additive manufacturing procedure has negligible effects on the magnetic properties. Performing a parametric study over a rectangular ROI, an optimized shim configuration is achieved. In the optimized and 3D-printed configuration, the average norm of the magnetic flux density, Bnorm, is increased by 13% and, more importantly, a 43% increase in the magnetic uniformity is obtained. These results highlight the great potential of freeform manufacturing, namely, additive manufacturing, to tailor the properties of magnet structures

Periodic point process.

<p>An event at time <i>t</i> = 0 triggers a poisson process. The solid curve shows the intensity of the proposed periodic point process with a Gaussian kernel and period <i>τ</i>, and the dashed curve shows a Hawkes process with an exponential decaying kernel.</p

Scalability comparision.

<p>The time complexity of different temporal models and our spatial model (the other baseline spatial models also have approximately the same time complexity, so only one of them is depicted), for different network sizes (<i>left</i>), and for different sizes of events history (<i>right</i>).</p