Analysis and Prediction of Electromobility and Energy Supply by the Example of Stuttgart

This paper seeks to identify bottlenecks in the energy grid supply regarding different market penetration of battery electric vehicles in Stuttgart, Germany. First, medium-term forecasts of electric and hybrid vehicles and the corresponding charging infrastructure are issued from 2017 to 2030, resulting in a share of 27% electric vehicles by 2030 in the Stuttgart region. Next, interactions between electric vehicles and the local energy system in Stuttgart were examined, comparing dif-ferent development scenarios in the mobility sector. Further, a travel demand model was used to generate charging profiles of electric vehicles under consideration of mobility patterns. The charg-ing demand was combined with standard household load profiles and a load flow analysis of the peak hour was carried out for a quarter comprising 349 households. The simulation shows that a higher charging capacity can lead to a lower transformer utilization, as charging and household peak load may fall temporally apart. Finally, it was examined whether the existing infrastructure is suitable to meet future demand focusing on the transformer reserve capacity. Overall, the need for action is limited; only 10% of the approximately 560 sub-grids were identified as potential weak points

Characterization of pulmonary vascular remodeling and MicroRNA-126-targets in COPD-pulmonary hypertension

BACKGROUND: Despite causing increased morbidity and mortality, pulmonary hypertension (PH) in chronic obstructive pulmonary disease (COPD) patients (COPD-PH) lacks treatment, due to incomplete understanding of its pathogenesis. Hypertrophy of pulmonary arterial walls and pruning of the microvasculature with loss of capillary beds are known features of pulmonary vascular remodeling in COPD. The remodeling features of pulmonary medium- and smaller vessels in COPD-PH lungs are less well described and may be linked to maladaptation of endothelial cells to chronic cigarette smoking (CS). MicroRNA-126 (miR126), a master regulator of endothelial cell fate, has divergent functions that are vessel-size specific, supporting the survival of large vessel endothelial cells and inhibiting the proliferation of microvascular endothelial cells. Since CS decreases miR126 in microvascular lung endothelial cells, we set out to characterize the remodeling by pulmonary vascular size in COPD-PH and its relationship with miR126 in COPD and COPD-PH lungs. METHODS: Deidentified lung tissue was obtained from individuals with COPD with and without PH and from non-diseased non-smokers and smokers. Pulmonary artery remodeling was assessed by ⍺-smooth muscle actin (SMA) abundance via immunohistochemistry and analyzed by pulmonary artery size. miR126 and miR126-target abundance were quantified by qPCR. The expression levels of ceramide, ADAM9, and endothelial cell marker CD31 were assessed by immunofluorescence. RESULTS: Pulmonary arteries from COPD and COPD-PH lungs had significantly increased SMA abundance compared to non-COPD lungs, especially in small pulmonary arteries and the lung microvasculature. This was accompanied by significantly fewer endothelial cell markers and increased pro-apoptotic ceramide abundance. miR126 expression was significantly decreased in lungs of COPD individuals. Of the targets tested (SPRED1, VEGF, LAT1, ADAM9), lung miR126 most significantly inversely correlated with ADAM9 expression. Compared to controls, ADAM9 was significantly increased in COPD and COPD-PH lungs, predominantly in small pulmonary arteries and lung microvasculature. CONCLUSION: Both COPD and COPD-PH lungs exhibited significant remodeling of the pulmonary vascular bed of small and microvascular size, suggesting these changes may occur before or independent of the clinical development of PH. Decreased miR126 expression with reciprocal increase in ADAM9 may regulate endothelial cell survival and vascular remodeling in small pulmonary arteries and lung microvasculature in COPD and COPD-PH

Sphingosine 1 Phosphate (S1P) Receptor 1 Is Decreased in Human Lung Microvascular Endothelial Cells of Smokers and Mediates S1P Effect on Autophagy

Destruction of alveoli by apoptosis induced by cigarette smoke (CS) is a major driver of emphysema pathogenesis. However, when compared to cells isolated from non-smokers, primary human lung microvascular endothelial cells (HLMVECs) isolated from chronic smokers are more resilient when exposed to apoptosis-inducing ceramide. Whether this adaptation restores homeostasis is unknown. To better understand the phenotype of HLMVEC in smokers, we interrogated a major pro-survival pathway supported by sphingosine-1-phosphate (S1P) signaling via S1P receptor 1 (S1P1). Primary HLMVECs from lungs of non-smoker or smoker donors were isolated and studied in culture for up to five passages. S1P1 mRNA and protein abundance were significantly decreased in HLMVECs from smokers compared to non-smokers. S1P1 was also decreased in situ in lungs of mice chronically exposed to CS. Levels of S1P1 expression tended to correlate with those of autophagy markers, and increasing S1P (via S1P lyase knockdown with siRNA) stimulated baseline macroautophagy with lysosomal degradation. In turn, loss of S1P1 (siRNA) inhibited these effects of S1P on HLMVECs autophagy. These findings suggest that the anti-apoptotic phenotype of HLMVECs from smokers may be maladaptive, since it is associated with decreased S1P1 expression that may impair their autophagic response to S1P

Structural and functional characterization of endothelial microparticles released by cigarette smoke

Circulating endothelial microparticles (EMPs) are emerging as biomarkers of chronic obstructive pulmonary disease (COPD) in individuals exposed to cigarette smoke (CS), but their mechanism of release and function remain unknown. We assessed biochemical and functional characteristics of EMPs and circulating microparticles (cMPs) released by CS. CS exposure was sufficient to increase microparticle levels in plasma of humans and mice, and in supernatants of primary human lung microvascular endothelial cells. CS-released EMPs contained predominantly exosomes that were significantly enriched in let-7d, miR-191; miR-126; and miR125a, microRNAs that reciprocally decreased intracellular in CS-exposed endothelium. CS-released EMPs and cMPs were ceramide-rich and required the ceramide-synthesis enzyme acid sphingomyelinase (aSMase) for their release, an enzyme which was found to exhibit significantly higher activity in plasma of COPD patients or of CS-exposed mice. The ex vivo or in vivo engulfment of EMPs or cMPs by peripheral blood monocytes-derived macrophages was associated with significant inhibition of efferocytosis. Our results indicate that CS, via aSMase, releases circulating EMPs with distinct microRNA cargo and that EMPs affect the clearance of apoptotic cells by specialized macrophages. These targetable effects may be important in the pathogenesis of diseases linked to endothelial injury and inflammation in smokers

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

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

Application and machine learning methods for dynamic load point controls of electric vehicles (xEVs)

From the customer's perspective, the appeal of electric vehicles depends on the simplicity and ease of their use, such as flexible access to electric power from the grid to recharge the batteries of their vehicles. Therefore, the expansion of charging infrastructure will be an important part of electric mobility. The related charging infrastructure is a big challenge for the load capacity of the grid connection without additional intelligent charge management: if the control of the charging process is not implemented, it is necessary to ensure the total of the maximum output of all xEVs at the grid connection point, which requires huge costs. This paper proposes to build a prediction module for forecasting dynamic charging load using machine learning (ML) techniques. The module will be integrated into a real charge management concept with optimization procedures for controlling the dynamic load point. The value of load forecasting through practical load data of a car park were taken to illustrate the proposed methods. The prediction performance of different ML methods under the same data condition (e.g., holiday data) are compared and evaluated

Hydrolysis hydrogen generation behavior of mechanico-chemical reaction Mg-M (M = Ni, Ce, and La) binary alloys—A feasible strategy for activating and improving environmental stability

Mg-based alloys are regard to be suitable hydrolysis materials for hydrogen generation. The mechanico-chemical reaction (MCR) strategy was employed to effectively activate Mg-based binary alloys as well as elevate their environmental stability. MCR is proved to be an effective way to activate Mg-based binary alloys and enhance the ability to resist environmental toxicity. The hydrolysis H2 generation process of MCR Mg25Ni, Mg30Ce and Mg30La samples after environmental exposure are elevated and the final H2 capacities can increase to 186.1, 204.8 and 341.4 mL·g−1 with the fastest H2 generation rates of 26.0, 24.2 and 41.5 mL·g−1·min−1, respectively. The generation capacities of the above-mentioned samples are 297, 370 and 629 mL·g−1 at 318 K within 10 min, respectively. Mg-based binary alloys can be effectively activated by MCR and Maintain high reactivity at the same time. The hydrogen generation activation energies of MCR Mg25Ni, Mg30Ce and Mg30La after environmental exposure are 26.6, 30.8 and 23.3 kJ·mol−1, respectively. The above-mentioned work may provide a feasible strategy to activate the as-cast Mg-based alloys and elevate the Resistance to environmental toxicity, which may pave the way for applying the portable hydrogen generators

Silver Doped Mesoporous Silica Nanoparticles Based Electrochemical Enzyme-Less Sensor for Determination of H₂O₂ Released from Live Cells

In this study, a silver doped mesoporous silica nanoparticles-based enzyme-less electrochemical sensor for the determination of hydrogen peroxide (H2O2) released from live cells was constructed for the first time. The presented electrochemical sensor exhibited fast response (2 s) towards the reduction of H2O2 concentration variation at an optimized potential of −0.5 V with high selectivity over biological interferents such as uric acid, ascorbic acid, and glucose. In addition, a wide linear range (4 μM to 10 mM) with a low detection limit (LOD) of 3 μM was obtained. Furthermore, the Ag-mSiO2 nanoparticles/glass carbon electrode (Ag-mSiO2 NPs/GCE) based enzyme-less sensor showed good electrocatalytic performance, as well as good reproducibility, and long-term stability, which provided a successful way to in situ determine H2O2 released from live cells. It may also be promising to monitor the effect of reactive oxygen species (ROS) production in bacteria against oxidants and antibiotics