Future Decades Research Articles

Projecting the excess mortality due to heatwave and its characteristics under climate change, population and adaptation scenarios.

Heatwaves have significant adverse effects on human health. The frequency, duration, and intensity of heatwaves are projected to increase dramatically, in the context of global warming. However, there are few comprehensive assessments of the health impact of heatwaves considering different definitions, and their characteristics under climate change scenarios. We aimed to compare future excess mortality related to heatwaves among different definitions under climate change, population, and adaptation scenarios in China and further explore the mortality burden associated with heatwave characteristics. Daily data during 2010-2019 were collected in Guangzhou, China. We adopted nine common heatwave definitions and applied quasi-Poisson models to estimate the effects of heatwaves and their characteristics' impact on mortality. We then projected the excess mortality associated with heatwaves and their characteristics concerning climate change, population, and adaptation scenarios. The relative risks of the nine common heatwave definitions ranged from 1.05 (95% CI: 1.01, 1.10) to 1.24 (95% CI: 1.13, 1.35). Heatwave-related excess mortality will consistently increase in the future decades considering multiple heatwave definitions, with more rapidly increasing rates under the Shared Socioeconomic Path5-8.5 and non-adaptability scenarios. Regarding heatwave characteristics, the intensity is the main factor involved in the threat of heatwaves. The increasing trend of characteristic-related mortality burden is similar to that of heatwaves, and the mortality burden caused by the duration of the heatwaves was the largest among all characteristics. This study provides a comprehensive picture of the impact of heatwaves and their characteristics on public health under various climate change scenarios, population changes, and adaptive assumptions. The results may provide important public health implications for policymakers in planning climate change adaptation and mitigation policies, and implementing specific plans.

Retrofitting passive cooling strategies to combat heat stress in the face of climate change: A case study of a ready-made garment factory in Dhaka, Bangladesh.

The ready-made garment industry is critical to the Bangladesh economy. There is an urgent need to improve current working conditions and build capacity for heat mitigation as conditions worsen due to climate change. We modelled a typical, mid-sized, non-air-conditioned factory in Bangladesh and simulated how the indoor thermal environment is altered by four rooftop retrofits (1. extensive green roof, 2. rooftop shading, 3. white cool roof, 4. insulated white cool roof) on present-day and future decades under different climate scenarios. Simulations showed that all strategies reduce indoor air temperatures by around 2 °C on average and reduce the number of present-day annual work-hours during which wetbulb globe temperature exceeds the standardised limits for moderate work rates by up to 603 h - the equivalent of 75 (8 h) working days per year. By 2050 under a high-emissions scenario, indoor conditions with a rooftop intervention are comparable to present-day conditions. To reduce the growing need for carbon-intensive air-conditioning, sustainable heat mitigation strategies need to be incorporated into a wider range of solutions at the individual, building, and urban level. The results presented here have implications for factory planning and retrofit design, and may inform policies targeting worker health, well-being, and productivity.

Future transition in climate extremes over Western Ghats of India based on CMIP6 models.

The effect of climate change on the tropical river catchments in the Western Ghats of India is studied using the Coupled Model Intercomparison Project-6 data (CMIP-6). Multi-model ensembles of rainfall and temperature are constructed using the Random Forest ensemble technique for bias-corrected GCMs in the near future (2014-2050) and far future (2051-2100) horizons. For the two catchments each in the southern, central, and northern Ghats, the trend in minimum and maximum temperatures, precipitation, and other indices are calculated. By 2100, dry sub-humid and humid catchments will see a higher increase in mean annual temperature than per-humid central catchments. In future decades, the warm days and nights increase by 45-50% and 40-70%, respectively, with twofold warming in the winter season. Under a climate change scenario, annual rainfall increases in Vamanapuram, Ulhas, and Purna, while Chaliyar, Netravati, and Aghanashini catchments experience a decrease in rainfall in the far future with an increase in pre-monsoon rainfall. The southern catchments are anticipated to have contrasting variations in the rainfall extremes; northern catchments face a substantial increase in very wet to extremely wet days and medium to heavy rainfall. In all catchments (excluding Vamanapuram), cumulative wet days increase with a decrease in cumulative dry days. After the mid-twenty-first century, humid to per-humid catchments encompass an increase in cool nights, whereas it disappears in dry sub-humid catchments of the Ghat. Interestingly, warming tendencies begin to slow down after 2050. This investigation can assist in comprehending the regional climate extremes in the Western Ghats to formulate better climate risk planning and adaptation strategies.

Data mining and analysis for predicting electrical energy consumption

In this study paper, the feasibility of constructing a complete smart system for anticipating electrical power consumption is created, as electricity's market share is expected to expand over the future decades. Smart grids and smart meters will help utility companies and their customers soon. New services and businesses in energy management need software development and data analytics skills. New services and enterprises are competitive. The project's electricity consumers are categorized by their hourly power usage percentage. This classification was done using data mining (five algorithms in specific) and data analysis theory. This division aims to help each group minimize energy use and expenditures, encourage energy-saving activities, and promote consumer involvement by giving tailored guidance. The intended segmentation is done through an iterative process using a computer classification computation, post-analysis, and data mining with visualization and statistical methodologies.

Effect of Diet on Depression: A Review of Nutritional Solutions

Depression is a mental illness with several categories that have common symptoms such as chronic sorrow, lack of interest, lack of pleasure, mood swings between guilt and poor self-esteem, sleep disturbances, and a loss of appetite. Over 300 million individuals globally suffer from depression, and the socioeconomic cost of this debilitating disorder is expected to rise dramatically in the future decades.
 Behavioral health illnesses can be prevented and treated to some extent with dietary and nutritional means. Nutritional psychiatry has produced observational and effectiveness evidence regarding the role of healthy dietary patterns in the onset and treatment of depressive symptoms. Diet is associated with depressive symptoms or depression, meaning that an increase in depressive disorders coincide with a deterioration in healthy living choices, including poor quality diets.
 Healthy eating habits and adequate intake of essential nutrients via the diet can help prevent and treat depression by reducing symptoms of mental illness. In addition, because nutrition is a modifiable risk factor for depression, it is practical for the public to consider dietary changes to reduce the prevalence of depressive disorders.
 This paper reviews the potential value of diet-based actions to manage depression, and ways in which dietary changes could be made to improve mental and cognitive health. Furthermore, some practical solutions for preventing and controlling depression are proposed based on health-related effects of improving dietary habits and life style.

Multi‐decadal stability of fish productivity despite increasing coral reef degradation

Abstract Under current trajectories, it is unlikely that the coral reefs of the future will resemble those of the past. As multiple stressors, such as climate change and coastal development, continue to impact coral reefs, understanding the changes in ecosystem functioning is imperative to protect key ecosystem services. We used a 26‐year dataset of benthic reef fishes (including cryptobenthic fishes) to identify multi‐decadal trends in fish biomass production on a degraded coral reef. We converted fish abundances into estimates of community productivity to track the long‐term trend of fish biomass production through time. Following the first mass coral bleaching event in 1998, the abundance, standing biomass and productivity of fish communities remained remarkably constant through time, despite the occurrence of multiple stressors, including extreme sedimentation, cyclones and mass coral bleaching events. Species richness declined following the 1998 bleaching event, but rebounded to prebleaching levels and also remained relatively stable. Although the species composition of the communities changed over time, these new community configurations still maintain a steady level of fish biomass production. While these highly dynamic and increasingly degraded systems can still provide some critical ecosystem functions, it is unclear whether these patterns will remain stable over future decades. Read the free Plain Language Summary for this article on the Journal blog.

EIDM: deep learning model for IoT intrusion detection systems

Internet of Things (IoT) is a disruptive technology for the future decades. Due to its pervasive growth, it is susceptible to cyber-attacks, and hence the significance of Intrusion Detection Systems (IDSs) for IoT is pertinent. The viability of machine learning has encouraged analysts to apply learning techniques to intelligently discover and recognize cyber attacks and unusual behavior among the IoTs. This paper proposes an enhanced anomaly-based Intrusion Detection Deep learning Multi-class classification model (EIDM) that can classify 15 traffic behaviors including 14 attack types with the accuracy of 95% contained in the CICIDS2017 dataset. Four state-of-the-art deep learning models are also customized to classify six classes of network traffic behavior. An extensive comparative study in terms of classification accuracy and efficiency metrics is conducted between EIDM and several state-of-the-art deep learning-based IDSs showing that EIDM has achieved accurate detection results.

Building the foundation for a community-generated national research blueprint for inherited bleeding disorders: research priorities for ultra-rare inherited bleeding disorders

ABSTRACT Background Ultra-rare inherited bleeding disorders (BDs) present important challenges for generating a strong evidence foundation for optimal diagnosis and management. Without disorder-appropriate treatment, affected individuals potentially face life-threatening bleeding, delayed diagnosis, suboptimal management of invasive procedures, psychosocial distress, pain, and decreased quality-of-life. Research design and methods The National Hemophilia Foundation (NHF) and the American Thrombosis and Hemostasis Network identified the priorities of people with inherited BDs and their caregivers, through extensive inclusive community consultations, to inform a blueprint for future decades of research. Multidisciplinary expert Working Group (WG) 3 distilled highly feasible transformative ultra-rare inherited BD research opportunities from the community-identified priorities. Results WG3 identified three focus areas with the potential to advance the needs of all people with ultra-rare inherited BDs and scored the feasibility, impact, and risk of priority initiatives, including 13 in systems biology and mechanistic science; 2 in clinical research, data collection, and research infrastructure; and 5 in the regulatory process for novel therapeutics and required data collection. Conclusions Centralization and expansion of expertise and resources, flexible innovative research and regulatory approaches, and inclusion of all people with ultra-rare inherited BDs and their health care professionals will be essential to capitalize on the opportunities outlined herein.

Building the foundation for a community-generated national research blueprint for inherited bleeding disorders: research to advance the health of people with inherited bleeding disorders with the potential to menstruate

ABSTRACT Background People who have or had the potential to menstruate (PPM) with inherited bleeding disorders (BD) face particular challenges receiving appropriate diagnosis and care and participating in research. As part of an initiative to create a National Research Blueprint for future decades of research, the National Hemophilia Foundation (NHF) and American Thrombosis and Hemostasis Network conducted extensive all-stakeholder consultations to identify the priorities of PPM with inherited BDs and those who care for them. Research design and methods Working group (WG) 4 of the NHF State of the Science Research Summit distilled community-identified priorities for PPM with inherited BDs into concrete research questions and scored their feasibility, impact, and risk. Results WG4 identified important gaps in the foundational knowledge upon which to base optimal diagnosis and care for PPM with inherited BDs. They defined 44 top-priority research questions concerning lifespan sex biology, pregnancy and the post-partum context, uterine physiology and bleeding, bone and joint health, health care delivery, and patient-reported outcomes and quality-of-life. Conclusions The needs of PPM will best be advanced with research designed across the spectrum of sex and gender biology, with methodologies and outcome measures tailored to this population, involving them throughout.

Flooding and the interannual variability of hydrologic quantities in the Missouri River basin

AbstractThe six mainstem reservoirs in the Missouri River basin (MRB) are managed mainly to prevent flooding from snowmelt and heavy rainfall, a goal for which the interannual variabilities of precipitation (), evapotranspiration (), and surface air temperature () are vitally important. We tested the hypothesis that under the expected higher variability owing to global climate change, the months with the highest contributions to the interannual variability of , , and in the MRB will remain unchanged and quantified likely temporal trends in these quantities. Using high‐resolution, downscaled Coupled Model Intercomparison Project Phase 5 multi‐model ensemble data sets, we compared the multi‐year ratio of monthly and annual interannual variability and temporal trends in , , and during 2011–2020 with three future decades. Results showed that the 6 months with the highest interannual variability in and (April–September) are the same in all four decades. However, for , only 4 months (December–March) retain their status as highly variable throughout the four decades; September and October variability is exceeded by the variability in other months. This implies that, compared to and , the cyclical change in the probabilities of in the MRB is less stable under future global climate change. This finding can be used to consider the need to alter existing strategies for reservoir release while minimizing the likelihood of aggravating flooding below the reservoirs.

Human influence on growing-period frosts like in early April 2021 in central France

Abstract. In early April 2021 several days of harsh frost affected central Europe. This led to very severe damage in grapevine and fruit trees in France, in regions where young leaves had already unfolded due to unusually warm temperatures in the preceding month (March 2021). We analysed with observations and 172 climate model simulations how human-induced climate change affected this event over central France, where many vineyards are located. We found that, without human-caused climate change, such temperatures in April or later in spring would have been even lower by 1.2 ∘C (0.75 to 1.7 ∘C). However, climate change also caused an earlier occurrence of bud burst that we characterized in this study by a growing degree day index value. This shift leaves young leaves exposed to more winter-like conditions with lower minimum temperatures and longer nights, an effect that overcompensates the warming effect. Extreme cold temperatures occurring after the start of the growing season such as those of April 2021 are now 2 ∘C colder (0.5 to 3.3 ∘C) than in preindustrial conditions, according to observations. This observed intensification of growing-period frosts is attributable, at least in part, to human-caused climate change with each of the five climate model ensembles used here simulating a cooling of growing-period annual temperature minima of 0.41 ∘C (0.22 to 0.60 ∘C) since preindustrial conditions. The 2021 growing-period frost event has become 50 % more likely (10 %–110 %). Models accurately simulate the observed warming in extreme lowest spring temperatures but underestimate the observed trends in growing-period frost intensities, a fact that yet remains to be explained. Model ensembles all simulate a further intensification of yearly minimum temperatures occurring in the growing period for future decades and a significant probability increase for such events of about 30 % (20 %–40 %) in a climate with global warming of 2 ∘C.

Harnessing Genomic Analysis to Explore the Role of Telomeres in the Pathogenesis and Progression of Diabetic Kidney Disease.

The prevalence of diabetes is increasing globally, and this trend is predicted to continue for future decades. Research is needed to uncover new ways to manage diabetes and its co-morbidities. A significant secondary complication of diabetes is kidney disease, which can ultimately result in the need for renal replacement therapy, via dialysis or transplantation. Diabetic kidney disease presents a substantial burden to patients, their families and global healthcare services. This review highlights studies that have harnessed genomic, epigenomic and functional prediction tools to uncover novel genes and pathways associated with DKD that are useful for the identification of therapeutic targets or novel biomarkers for risk stratification. Telomere length regulation is a specific pathway gaining attention recently because of its association with DKD. Researchers are employing both observational and genetics-based studies to identify telomere-related genes associated with kidney function decline in diabetes. Studies have also uncovered novel functions for telomere-related genes beyond the immediate regulation of telomere length, such as transcriptional regulation and inflammation. This review summarises studies that have revealed the potential to harness therapeutics that modulate telomere length, or the associated epigenetic modifications, for the treatment of DKD, to potentially slow renal function decline and reduce the global burden of this disease.

The consequences of Cosmos 1408 breakup: The optimization of the breakup model and the influence of debris clouds

The Cosmos 1408 man-made breakup event generated a large number of fragments. These fragments pose a threat to the operating spacecrafts in the Low Earth Orbit (LEO). The lifetimes of cataloged Cosmos 1408 fragments are shorter than those of fragments simulated by NASA's breakup model. Therefore, the particle swarm optimization (PSO) was used to modify the parameters in the breakup model, and the modified debris cloud highly matches the SSN cataloged fragments. The Cosmos debris cloud was simulated by the optimized breakup model, and the impact of this event on the space debris environment, the International Space Station (ISS) and the Chinese Space Station (CSS) was analyzed by applying Space Debris Environment Engineering Model 2019 (SDEEM 2019) and Survivability of Spacecraft in Space Debris Environment (S3DE). The results show that most (90%) dangerous debris was estimated to reenter within one year due to atmospheric drag. The sensitivity analysis for the ISS and the CSS shows that the sensitivity of the threatening debris of the ISS and the CSS increases about 40% and 50% over a future decade compared to that without this event, respectively.

Towards policies to eradicate ethnic discrimination in amateur sports

Field experiments in the last decade documented discrimination in several social domains: labour, housing, education, transportation, and sports. Previous research shows that when asking to join a training with an amateur soccer club, people with foreign-sounding names are significantly less likely to receive a positive response than those with native-sounding names. This result differs in magnitude but is traceable across 23 European countries, including Switzerland (Gomez-Gonzalez et al., 2021; Nesseler et al., 2019). The findings redirect attention from self-segregation to collective exclusion mechanisms when analyzing the ethnic participation gap in amateur sports. The negative implications are magnified as research identifies sport participation as key in promoting social integration among minority group members.
 Experimental economics also show that field experiments can play a crucial role in developing effective policies to combat discrimination in the future decade. Previous research demonstrates the importance of intervention studies to test the effectiveness of the policies, as not all have the intended results. Dur et al. (2022) analyze the effectiveness of a low-cost intervention to reduce discrimination among amateur soccer clubs in Norway. A correspondence test is preceded by an anti-discrimination intervention in collaboration with the Norwegian Football Federation (NFF). The intervention is based on an information campaign sent via email to a random selection of amateur soccer clubs, which do not modify their behavior as expected.
 The experimental design of an intervention makes it possible to estimate the causal effect of a low-cost policy against discrimination in the field. In this research, I design an intervention to reduce the ethnic response gap among amateur soccer clubs in Switzerland, where more than 1,000 amateur clubs would be subject to an intervention. I explore the features of the information campaign: message, sender, and channel, and potential collaborations with sports governing bodies to increase the impact of such policy.
 References
 Dur, R., Gomez-Gonzalez, C., & Nesseler, C. (2022). How to reduce discrimination? Evidence from a field experiment in amateur soccer. Journal of Ethnic and Migration Studies, 49(1), 175-191. https://doi.org/10.1080/1369183X.2022.2071688
 Gomez-Gonzalez, C., Nesseler, C., & Dietl, H. M. (2021). Mapping discrimination in Europe through a field experiment in amateur sport. Humanities and Social Sciences Communications, 8, Article 95. https://doi.org/10.1057/s41599-021-00773-2
 Nesseler, C., Gomez-Gonzalez, C., & Dietl, H. (2019). What’s in a name? Measuring access to social activities with a field experiment. Palgrave Communications, 5, Article 160. https://doi.org/10.1057/s41599-019-0372-0

Mortality of Alzheimer's Disease and Other Dementias in China: Past and Future Decades.

Objectives: This study aimed to explore the distribution features and trends of dementia mortality in China from 2011 to 2020 and make a prediction for the next decade. Methods: Mortality-relevant data were gathered from the Chinese Center for Disease Control and Prevention's Disease Surveillance Points system. Joinpoint regression was applied to evaluate the trends. Results: Crude Mortality Rate (CMR) of AD and other dementias increased from 3.7 per 100,000 to 6.2 per 100,000 in 2011-2020, with an Average Annual Percent Change (AAPC) of 5.3% (95% CI 4.4%-6.3%). Age-Standardized Mortality Rate (ASMR) slightly decreased from 5.0 per 100,000 to 4.1 per 100,000 in 2011-2020, with AAPC of -0.4% (95% CI -2.5%-1.8%). CMR will increase to 9.66 per 100,000 while ASMR will decline to 3.42 per 100,000 in the following decade. Conclusion: The upward trend in CMR and downward trend in ASMR suggested the further development of population aging and dementia mortality in the past and future decades. In China, there were gender, urban-rural, regional and age differences.

The last glaciers in Africa and their environmental implications

Climate models and ongoing monitoring studies predict the remaining glaciers in Africa are predicted to disappear by the middle of the 21st Century. These will likely be the only glaciers present on the continent for some tens of thousands of years, until the next global ice age. This paper considers the implications of the shrinking cryosphere in Africa for the surrounding environment and local communities. Glacier retreat will give rise to significant and irreversible downstream effects on East African mountain landscapes in future decades, including impacts on water resources; slope stability and geohazards; ecosystems and ecosystem services; and human socioeconomic and cultural activities and heritage. This foresight study is the first to discuss future environmental impacts of deglacierization in East Africa, and this is framed around understanding the interconnections that exist between physical and human landscape elements in mountainous regions. A key outcome is the identification of elements of mountain systems that are most sensitive to environmental disturbance as a result of global warming, such as long-term water availability and processes that give rise to geohazards, and highlighting the need for management and mitigation of these varied impacts.

Fluvial Flood Losses in the Contiguous United States Under Climate Change

AbstractFlooding is one of the most devastating natural disasters causing significant economic losses. One of the dominant drivers of flood losses is heavy precipitation, with other contributing factors such as built environments and socio‐economic conditions superimposed to it. To better understand the risk profile associated with this hazard, we develop probabilistic models to quantify the future likelihood of fluvial flood‐related property damage exceeding a critical threshold (i.e., high property damage) at the state level across the conterminous United States. The model is conditioned on indicators representing heavy precipitation amount and frequency derived from observed and downscaled precipitation. The likelihood of high property damage is estimated from the conditional probability distribution of annual total property damage, which is derived from the joint probability of the property damage and heavy precipitation indicators. Our results indicate an increase in the probability of high property damage (i.e., exceedance of 70th percentile of observed annual property damage for each state) in the future. Higher probability of high property damage is projected to be clustered in the states across the western and south‐western United States, and parts of the U.S. Northwest and the northern Rockies and Plains. Depending on the state, the mean annual probability of high property damage in these regions could range from 38% to 80% and from 46% to 95% at the end of the century (2090s) under RCP4.5 and RCP8.5 scenarios, respectively. This is equivalent to 20%–40% increase in the probability compared to the historical period 1996–2005. Results show that uncertainty in the projected probability of high property damage ranges from 14% to 35% across the states. The spatio‐temporal variability of the uncertainty across the states and three future decades (i.e., 2050s, 2070s, and 2090s) exhibits nonstationarity, which is driven by the uncertainty associated with the probabilistic prediction models and climate change scenarios.

High Resolution SnowModel Simulations Reveal Future Elevation‐Dependent Snow Loss and Earlier, Flashier Surface Water Input for the Upper Colorado River Basin

AbstractContinued climate warming is reducing seasonal snowpacks in the western United States, where >50% of historical water supplies were snowmelt‐derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effectively to future conditions, we need to understand current spatiotemporal distributions of SWE and SWI and how they may change in future decades. We developed 100‐m SnowModel simulations for water years 2001–2013 and two scenarios: control (CTL) and pseudo‐global‐warming (PGW). The PGW fraction of precipitation falling as snow was lower relative to CTL, except for November–April at high elevations. PGW peak SWE was lower for low (−45%) and mid elevations (−14%), while the date of peak SWE was uniformly earlier in the year for all elevations (17–23 days). Currently unmonitored high elevation snow represented a greater fraction of total PGW SWE. PGW peak daily SWI was higher for all elevations (30%–42%), while the dates of SWI peaks and centroids were earlier in the year for all elevations under PGW. PGW displayed elevated winter SWI, lower summer SWI, and changes in spring SWI timing were elevation‐dependent. Although PGW peak SWI was elevated and earlier compared to CTL, SWI was more evenly distributed throughout the year for PGW. These simulated shifts in the timing and magnitude of SWE and SWI have broad implications for water management in dry, snow‐dominated regions.

Late Health Outcomes Among Survivors of Wilms Tumor Diagnosed Over Three Decades: A Report From the Childhood Cancer Survivor Study.

To evaluate long-term morbidity and mortality among unilateral, nonsyndromic Wilms tumor (WT) survivors according to conventional treatment regimens. Cumulative incidence of late mortality (≥ 5 years from diagnosis) and chronic health conditions (CHCs) were evaluated in WT survivors from the Childhood Cancer Survivor Study. Outcomes were evaluated by treatment, including nephrectomy combined with vincristine and actinomycin D (VA), VA + doxorubicin + abdominal radiotherapy (VAD + ART), VAD + ART + whole lung radiotherapy, or receipt of ≥ 4 chemotherapy agents. Among 2,008 unilateral WT survivors, 142 deaths occurred (standardized mortality ratio, 2.9, 95% CI, 2.5 to 3.5; 35-year cumulative incidence of death, 7.8%, 95% CI, 6.3 to 9.2). The 35-year cumulative incidence of any grade 3-5 CHC was 34.1% (95% CI, 30.7 to 37.5; rate ratio [RR] compared with siblings 3.0, 95% CI, 2.6 to 3.5). Survivors treated with VA alone had comparable risk for all-cause late mortality relative to the general population (standardized mortality ratio, 1.0; 95% CI, 0.5 to 1.7) and modestly increased risk for grade 3-5 CHCs compared with siblings (RR, 1.5; 95% CI, 1.1 to 2.0), but remained at increased risk for intestinal obstruction (RR, 9.4; 95% CI, 3.9 to 22.2) and kidney failure (RR, 11.9; 95% CI, 4.2 to 33.6). Magnitudes of risk for grade 3-5 CHCs, including intestinal obstruction, kidney failure, premature ovarian insufficiency, and heart failure, increased by treatment group intensity. With approximately 40% of patients with newly diagnosed WT currently treated with VA alone, the burden of late mortality/morbidity in future decades is projected to be lower than that for survivors from earlier eras. Nevertheless, the risk of late effects such as intestinal obstruction and kidney failure was elevated across all treatment groups, and there was a dose-dependent increase in risk for all grade 3-5 CHCs by treatment group intensity.

The necessary optimization of the data lifecycle: Marine geosciences in the big data era

In the marine geosciences, observations are typically acquired using research vessels to understand a given phenomenon or area of interest. Despite the plateauing of ship time and active research vessels in the last decade, the rate of marine geoscience data production has continued to increase. Simultaneously, there exists large quantities of legacy data aggregated within data repositories; however, these data are rarely curated to be both discoverable and machine-readable (i.e., accessible). This results in inefficient use, or even omission, of high-quality data, that is, both increasingly important to utilize and impractical to recollect. The proliferation of newly acquired data, and increasing importance of legacy data, has only been met with incremental evolution in the methods of data integration. This paper describes some improvements at each stage of the data lifecycle (acquisition, curation, and integration) that could align the marine geosciences better with the “big data” paradigm. We have encountered several major issues coordinating these efforts which we outline here: 1) geologic anomalies are the primary focus of data acquisition and pose difficulty in understanding the dominant (i.e., baseline) marine geology, 2) marine geoscience data are rarely curated to be accessible, and 3) aforementioned issues preclude the use of efficient integration tools that can make optimal use of data. In this paper, we discuss challenges and solutions associated with these issues to overcome these concerns in future decades of marine geoscience. The successful execution of these interconnected steps will optimize the lifecycle of marine geoscience data in the “big data” era.