Air pollution from fine particulate matter (PM2.5) is increasingly driving the global burden of disease ([ 1 ][1]), and diesel-powered vehicles are substantial contributors. Recognizing the public health impacts of diesel PM2.5 (DPM) ([ 2 ][2]), many countries have reduced emissions of DPM from both on- and off-road mobile sources over the past three decades. The previous US federal administration, however, changed course by eliminating or weakening policies and standards that govern these emissions. In contrast, the State of California has continued to reduce mobile-source DPM emissions using the state's long-standing authority under the Clean Air Act (CAA) to regulate air pollution more stringently than the federal government. Our analysis of mobile-source DPM emissions suggests that many California sector-based policies have been highly effective relative to the rest of the US. To improve health in communities disproportionately affected by these emissions, we point to opportunities to further reduce DPM emissions in California, in the US more broadly, and in parts of the world where countries have less aggressive vehicle emissions policies than the US ([ 3 ][3]). The US has targeted emissions of nitrogen oxides (NO x ) and DPM from diesel trucks and buses, railway locomotives, marine vessels, and off-road engines used in construction and agriculture through successively tighter emissions standards phased in since 1994 (table S1). These standards require low- and ultralow-sulfur diesel fuels (LSDF and ULSDF), establish emissions limits, and institute systems for portable emissions measurement and onboard diagnostics (table S1). The US Environmental Protection Agency (EPA) estimated that full implementation of Obama-era US emissions standards by 2030 would prevent some 12,000 premature deaths annually ([ 4 ][4]). Despite this, EPA leadership disbanded the PM review panel ahead of the scheduled 2020 update of federal PM standards; it also rolled back, or attempted to roll back, 85 federal air pollution policies ([ 5 ][5]) and moved to restrict the ability of states to set more stringent emissions standards ([ 6 ][6]). California, whose economy would rank fifth largest in the world if it were a sovereign nation, hosts the country's two largest ports and moves 60% of its container cargo (see supplementary materials). With the associated truck and rail traffic, California stands out as the largest emitter of DPM in the country. At the same time, California has also led the nation with the largest overall reduction in metric tons of DPM emissions from mobile sources. Over the past three decades, California's policies have systematically targeted high-emitting sectors, reducing mobile-source DPM emissions by, for example, substituting electric for diesel power where feasible, tightening emissions limits for new and existing diesel engines, and requiring ULSDF, which emits substantially less PM2.5 than higher-sulfur fuels upon combustion and can be combined with particle filters to further reduce emissions. To understand the impact of California's portfolio of policies, we used DPM emissions data from the EPA National Emissions Inventory (NEI), which assembles a comprehensive estimate of air pollution emissions using data reported by states, combined with modeled and measured inputs. We compared mobile-source DPM emissions in California versus the rest of the US for the period 1990 to 2014, the earliest and most recent year for which consistent NEI data are available ([ 7 ][7]). During that time, California reduced overall mobile-source DPM emissions by 78% while the rest of the US saw only a 51% reduction. These reductions came despite a concurrent steady rise in diesel fuel consumption: 20% in California and 28% in the rest of the US (data S1). Emissions reductions from heavy-duty diesel vehicles (HDDVs)—commercial trucks and buses—caused most of this decline, accounting for 67% of DPM emissions reductions in California and 57% in the rest of the US. Although the federal phase-in of ULSDF, off-road emissions standards, and the Heavy-Duty Engine and Vehicle Rule has reduced HDDV emissions across the US, California's reductions from HDDVs have been steeper and contribute even more to the overall reductions than would be predicted from the sector's size. Analyses of DPM emissions over time and the relative contributions made by each sector point to the effectiveness of California's policies that require diesel engine retrofits (adding emissions controls to existing HDDVs) and early replacement of older engines with newer, cleaner engines. Our analysis identifies three distinct phases in mobile-source DPM emissions between 1990 and 2014. Emissions fell overall from 1990 to 2001 in California and from 1990 to 2005 in the rest of the country. Reduced emissions from HDDVs contributed the largest share of the overall drop (see the figure and data S1). These changes are attributable to the introduction of LSDF nationwide, and to California's new requirements for vehicle inspections (table S2). Then, from 2001 to 2005 in California and from 2005 to 2008 in the rest of the country, emissions rose during an economic boom, driven primarily by increasing emissions from HDDVs and marine sources. Finally, overall DPM emissions once again fell, beginning in California in 2005 and in the rest of the US in 2008. The recession played a role in the early part of this drop ([ 8 ][8]), but emissions reductions continued through 2014 despite the economic recovery and the corresponding upturn in diesel use. During this final phase, California's 67% drop in DPM emissions outpaced the 40% reduction seen in the rest of the country (see the figure and data S1). Our analysis of individual sectors and each state's HDDV emissions suggests that California policies specifically targeting emissions from HDDVs and marine sources drove this decline. The later phases of California's emissions reductions correspond to the implementation of two overarching plans by the California Air Resources Board (CARB): the Diesel Risk Reduction Plan and the Emission Reduction Plan for Ports and Goods Movement (Goods Movement Plan), both of which encompassed multiple policies governing emissions from trucks and buses, ports, and off-road engines (table S2). Key policies targeting on-road HDDVs took effect in 2006 and 2007, further lowering the sulfur content of diesel fuel to 15 ppm (table S2) and tightening DPM emissions standards by 90% for new HDDVs (table S2). Beginning in 2010, with a rolling compliance period starting in 2015, all on-road HDDVs that operate in California were required to either retrofit existing engines with particle filters or replace engines older than the 2007 model year (table S2). By comparison, federal policies do not require retrofit or replacement of old diesel engines to meet emission standards, and HDDV engines typically operate for almost two decades, or about a million miles, before retirement. Our state-level analysis shows that by 2014 California HDDVs were emitting 139 metric tons of DPM for every billion vehicle-miles traveled (VMT), far less than the next-closest state (Oklahoma, 250 metric tons DPM per billion VMT) and the average in the rest of the country (345 metric tons DPM per billion VMT) (data S1). Although HDDVs remain California's largest source of DPM emissions, regulatory actions by CARB (over and above federal standards) have reduced HDDV emissions by 85% since 1990. If California's HDDV sector had followed the trajectory of other US states and DC, HDDV emissions in the state would have dropped only 58% (95% confidence interval, 52 to 64%) in that period (data S1). Also notable is the impact of two key CARB policies targeting marine sources. The 2007 At-Berth rule requires that oceangoing vessels switch to electric shore power while in port or use alternative control technologies to reduce emissions by an equivalent amount (table S2). The Cleaner Ocean Vessel fuel policy, finalized in 2008, requires that ships within 24 nautical miles of California's shoreline replace heavy fuel oil in their main engines with lower-sulfur fuels (table S2). Between 2008 and 2014, marine DPM emissions in the state dropped 51% overall (see the figure and data S1), and by 2018 emissions measured at the Port of Los Angeles had declined by 37% (fig. S3, A and B, and data S1). ![Figure][9] California versus the rest of the United States: Mobile-source DPM emissions declined differently Mobile-source diesel PM2.5 (DPM) emissions by sector in California versus the rest of the US from 1990 to 2014. HDDV, heavy-duty diesel vehicle; LDDV, light-duty diesel vehicle. All percentage changes reflect values relative to 1990 values. GRAPHIC: N. CARY/ SCIENCE By contrast, California has struggled to target diesel emissions from agriculture (table S2). The sector is responsible for up to 18% of the state's total DPM emissions from mobile sources, but it accounted for less than 1% of the total emissions reductions in California between 1990 and 2014. Although these figures do not reflect gains from voluntary tractor engine replacements that are reported differently, opportunities remain to reduce off-road farm emissions in the nation's leading agricultural state. Voluntary programs have further reduced DPM emissions beyond California's regulatory requirements. Incentives to bring engines and equipment to a standard cleaner than required by law are estimated to have reduced DPM emissions by more than 6000 metric tons since 2001 (table S2). A program established in 2006 has provided $1 billion in grants to update trucks, locomotives, and ships at berth, eliminating an estimated 2200 metric tons of DPM emissions (table S2). Like other policies targeting emissions along goods-movement corridors, this program particularly benefits neighboring communities, which tend to be lower-income communities of color (table S4). Taken together, CARB's policies reduced emissions to the extent that by 2014 California was emitting less than half the DPM that would be expected had the state followed the same trajectory as the rest of the US (fig. S2 and data S1). Correspondingly, we estimate that more than twice as many Californians would have died from DPM-attributable cardiopulmonary disease in 2014 alone if the state had not so markedly reduced emissions (data S1). The impact of targeted emissions regulation is also evident nationally, but it has come later and never as meaningfully as in California. Farming and construction emissions fell following the 2007 EPA Heavy Duty Engine and Vehicle Rule and the 2008–2015 phase-in of Tier 4 standards targeting off-road emissions from farm and construction equipment (table S1). Federal requirements for LSDF in the 1990s and ULSDF beginning in 2006 reduced HDDV emissions from both nonroad and on-road sources (table S1). In the marine sector, US coastal areas caught up to California's fuel standards in 2012 when ULSDF was required for smaller marine engines (table S1) and in 2015 for the largest vessels when requirements for lower-sulfur marine diesel came into effect in the North American Emissions Control Area established by the International Maritime Organization (table S1). By contrast, California has taken not only earlier action on marine emissions but also aggressive steps to target emissions from the many engines that pollute the air near ports, including marine auxiliary engines, short-haul trucks, cargo-handling cranes, and yard trucks (table S2). Individual states that have reduced HDDV emissions more than the national average are more likely to have adopted California's standards, as permitted under the CAA (table S5 and data S1), and the rest of the US could do the same. Coordination across states and between state and federal agencies means that methodological differences in data collection are unlikely to account for the observed differences in DPM emissions between California and the rest of the US (see supplementary materials). But how do we know that emission inventories are accurate and, furthermore, that CARB policies are responsible for the observed reductions? Field studies measuring changes in concentrations of DPM serve to ground-truth emissions inventories and substantiate the link between policy interventions and observed outcomes (table S4). For example, following the suite of interventions under the 2006 Goods Movement Plan, California communities in close proximity to goods-movement corridors saw significantly greater air quality improvements relative to non–goods-movement corridors and control areas monitored during the same time period (table S4). These findings show specific, local impacts of regulations targeting high-emitting sectors, distinguishing those changes from secular trends in air pollution and demonstrating their potential to advance environmental justice. The 2007 CARB regulation requiring retrofit or replacement of older HDDV engines for short-haul “drayage trucks” that operate at ports and railyards corresponded to a 70% reduction in black carbon emissions (a DPM proxy) and a 75% reduction in PM mass specific to drayage trucks measured in and around the ports of Oakland and Los Angeles between 2009 and 2011 (table S4). These changes mirror the emissions reductions measured in laboratory testing of the low-sulfur fuels and retrofit technologies used to meet the drayage truck standards (table S3). Likewise, the 2009 CARB requirement for low-sulfur fuels in oceangoing vessel engines operating within 24 nautical miles of the California coastline was associated with a measured 64% drop in San Francisco Bay Area concentrations of vanadium, a marker for combustion of heavy fuel oil (table S4). Sampling conducted by aircraft flying in the exhaust plume of a container ship approaching the coast showed that the fuel switch, combined with a required speed reduction, dropped DPM emissions by 90% (table S4). That these changes all occurred in the setting of continued growth in California's population, gross state product, and diesel consumption (figs. S4 and S5) further supports the assertion that the observed reductions track to the policies targeting DPM emissions. Observed emissions reductions are further corroborated by epidemiological data that link specific CARB policies to regional reductions in children's exposure to particle pollution and show corresponding improvements in both lung function and development in children with and without asthma ([ 9 ][10]). Finally, comparing HDDV sector emissions in California to the rest of the country likely underestimates the actual impact of CARB policies, which apply not only to the nearly half-million trucks and buses registered in California but also to the same number of out-of-state HDDVs estimated to drive California's highways each year ([ 10 ][11]). This requirement reduces emissions outside of California as well, although those reductions are attributed to federal policy. In California, cleaner air has not come at the expense of the state's economy, which in recent years has grown at double the average national rate ([ 11 ][12]). CARB estimates that every dollar the state has spent controlling air pollution has generated $38 in benefits attributable to reduced air pollution–related illness, premature death, and lost productivity. California's overall economic gain from health benefits linked to air pollution reduction, including CARB rules and programs, is estimated to have exceeded $250 billion between 1973 and 2014 ([ 12 ][13]). The link between PM2.5 exposure and increased risk of hospitalization and death from COVID-19 ([ 13 ][14]) further underscores the public health importance of cleaner air, particularly for communities of color that are disproportionately affected by both. California could benefit from additional measures to reduce emissions from off-road sectors, such as construction and agriculture, which CARB has not tackled as aggressively ([ 14 ][15]). Indeed, the nation as a whole could reduce mobile-source DPM emissions by requiring ships at berth to use shore power, and by requiring replacement or retrofit of existing on-road and off-road HDDVs in advance of fleet turnover. Given the long service life of older, dirty diesel engines, the current federal policy of mandating engine upgrades only with vehicle turnover is simply too slow. As the US initiates new federal rule-making on the proposed Cleaner Trucks Initiative to reduce NO x emissions from HDDVs, industry and environmental groups are calling on EPA to address NO x and DPM emissions in tandem and to create consistent “50-state” standards ([ 15 ][16]). In doing so, the EPA should align with CARB rules. EPA should also remove federal preemption of state emissions limits for off-road engines used in construction and agriculture. Even absent more aggressive federal policy, states' authority to set and implement their own stricter emissions standards must be protected. [science.sciencemag.org/content/371/6536/1314/suppl/DC1][17] 1. [↵][18]GBD 2017 Risk Factor Collaborators, Lancet 392, 1923 (2018). [OpenUrl][19][CrossRef][20][PubMed][21] 2. [↵][22]California Air Resources Board, “Overview: Diesel Exhaust & Health”; [ww2.arb.ca.gov/resources/overview-diesel-exhaust-and-health][23]. 3. [↵][24]European Union Directorate-General for Internal Policies, Comparative Study on the Differences Between the EU and US Legislation on Emissions in the Automotive Sector (2016); [www.europarl.europa.eu/RegData/etudes/STUD/2016/587331/IPOL\_STU(2016)587331\_EN.pdf][25]. 4. [↵][26]DieselNet, “Emission Standards, United States”; [www.dieselnet.com/standards/us/index.php][27]. 5. [↵][28]1. J. M. Samet, 2. T. A. Burke , Annu. Rev. Public Health 41, 347 (2020). [OpenUrl][29] 6. [↵][30]1. C. Davenport , “Trump to Revoke California's Authority to Set Stricter Auto Emissions Rules.” New York Times, 17 September 2019; [www.nytimes.com/2019/09/17/climate/trump-california-emissions-waiver.html][31]. 7. [↵][32]US Environmental Protection Agency, “National Emissions Inventory (NEI)”; [www.epa.gov/air-emissions-inventories/national-emissions-inventory-nei][33]. 8. [↵][34]1. D. Q. Tong et al ., Atmos. Environ. 107, 70 (2015). [OpenUrl][35] 9. [↵][36]1. F. Gilliland et al ., “The Effects of Policy-Driven Air Quality Improvements on Children's Respiratory Health” (2017); [www.healtheffects.org/system/files/GillilandRR190.pdf][37]. 10. [↵][38]California Air Resources Board, “Staff Report: Initial Statement of Reasons for Proposed Rulemaking: Proposed Regulation for In-Use On-Road Diesel Vehicles” (2008); . 11. [↵][39]Next10, 2017 California Green Innovation Index (2017); [www.next10.org/publications/2017-gii][40]. 12. [↵][41]California Air Resources Board, Fifty Year Air Quality Trends and Health Benefits; [ww3.arb.ca.gov/board/books/2018/020818/18-1-2pres.pdf][42]. 13. [↵][43]1. X. Wu, 2. R. C. Nethery, 3. M. B. Sabath, 4. D. Braun, 5. F. Dominici , Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. Sci. Adv. 6, eabd4049 (2020). 10.1126/sciadv.abd4049pmid:33148655 [OpenUrl][44][FREE Full Text][45] 14. [↵][46]California's construction emissions declined markedly from 2008 to 2011. Although industry likely lowered emissions in anticipation of deadlines in the 2008 In-Use Off-Road Diesel-Fueled Fleet Regulation (table S2), the majority of the decline is likely attributable to CARB's 2011 construction inventory revision prompted by the regulated industry. In that year, the regulation was also amended to delay implementation by 4 years and to lower required emission reductions. 15. [↵][47]US Environmental Protection Agency, “Control of Air Pollution From New Motor Vehicles: Heavy-Duty Engine Standards” [proposed rule]; [www.federalregister.gov/documents/2020/01/21/2020-00542/control-of-air-pollution-from-new-motor-vehicles-heavy-duty-engine-standards#citation-4-p3307][48]. Acknowledgments: We thank K. Peterson (University of California, Berkeley) for data visualization; K. Karparos, C. Parmer, and B. Holmes-Gen (CARB) for manuscript review; M. Houyoux, J. Godfrey, and M. Aldrich (EPA) for assistance with NEI data; and J. Austin, R. Boyd, T. Brasil, J. Cao, M. Diaz, R. Furey, J. Herner, S. Huber, M. Komlenic, R. Krieger, T. Kuwayama, N. Lowery, N. Motallebi, S. Pournazeri, S. Yoon, S. Zelinka, and L. Zhou (CARB) for assistance with CARB regulations and data. This research was supported in part by California Breast Cancer Research Program grant 23QB-1881. J.B. serves as the Physician Member of CARB. A.A. is a former employee of CARB. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #ref-8 [9]: pending:yes [10]: #ref-9 [11]: #ref-10 [12]: #ref-11 [13]: #ref-12 [14]: #ref-13 [15]: #ref-14 [16]: #ref-15 [17]: http://science.sciencemag.org/content/371/6536/1314/suppl/DC1 [18]: #xref-ref-1-1 "View reference 1 in text" [19]: {openurl}?query=rft.jtitle%253DLancet%26rft.volume%253D392%26rft.spage%253D1923%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0140-6736%252818%252932225-6%26rft_id%253Dinfo%253Apmid%252F30496105%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [20]: /lookup/external-ref?access_num=10.1016/S0140-6736(18)32225-6&link_type=DOI [21]: /lookup/external-ref?access_num=30496105&link_type=MED&atom=%2Fsci%2F371%2F6536%2F1314.atom [22]: #xref-ref-2-1 "View reference 2 in text" [23]: http://ww2.arb.ca.gov/resources/overview-diesel-exhaust-and-health [24]: #xref-ref-3-1 "View reference 3 in text" [25]: http://www.europarl.europa.eu/RegData/etudes/STUD/2016/587331/IPOL_STU(2016)587331_EN.pdf [26]: #xref-ref-4-1 "View reference 4 in text" [27]: http://www.dieselnet.com/standards/us/index.php [28]: #xref-ref-5-1 "View reference 5 in text" [29]: {openurl}?query=rft.jtitle%253DAnnu.%2BRev.%2BPublic%2BHealth%26rft.volume%253D41%26rft.spage%253D347%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [30]: #xref-ref-6-1 "View reference 6 in text" [31]: http://www.nytimes.com/2019/09/17/climate/trump-california-emissions-waiver.html [32]: #xref-ref-7-1 "View reference 7 in text" [33]: http://www.epa.gov/air-emissions-inventories/national-emissions-inventory-nei [34]: #xref-ref-8-1 "View reference 8 in text" [35]: {openurl}?query=rft.jtitle%253DAtmos.%2BEnviron.%26rft.volume%253D107%26rft.spage%253D70%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [36]: #xref-ref-9-1 "View reference 9 in text" [37]: http://www.healtheffects.org/system/files/GillilandRR190.pdf [38]: #xref-ref-10-1 "View reference 10 in text" [39]: #xref-ref-11-1 "View reference 11 in text" [40]: http://www.next10.org/publications/2017-gii [41]: #xref-ref-12-1 "View reference 12 in text" [42]: http://ww3.arb.ca.gov/board/books/2018/020818/18-1-2pres.pdf [43]: #xref-ref-13-1 "View reference 13 in text" [44]: {openurl}?query=rft.jtitle%253DScience%2BAdvances%26rft.stitle%253DSci%2BAdv%26rft.aulast%253DWu%26rft.auinit1%253DX.%26rft.volume%253D6%26rft.issue%253D45%26rft.spage%253Deabd4049%26rft.epage%253Deabd4049%26rft.atitle%253DAir%2Bpollution%2Band%2BCOVID-19%2Bmortality%2Bin%2Bthe%2BUnited%2BStates%253A%2BStrengths%2Band%2Blimitations%2Bof%2Ban%2Becological%2Bregression%2Banalysis%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fsciadv.abd4049%26rft_id%253Dinfo%253Apmid%252F33148655%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [45]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6MzoiUERGIjtzOjExOiJqb3VybmFsQ29kZSI7czo4OiJhZHZhbmNlcyI7czo1OiJyZXNpZCI7czoxMzoiNi80NS9lYWJkNDA0OSI7czo0OiJhdG9tIjtzOjIzOiIvc2NpLzM3MS82NTM2LzEzMTQuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9 [46]: #xref-ref-14-1 "View reference 14 in text" [47]: #xref-ref-15-1 "View reference 15 in text" [48]: http://www.federalregister.gov/documents/2020/01/21/2020-00542/control-of-air-pollution-from-new-motor-vehicles-heavy-duty-engine-standards#citation-4-p3307

SCI COMMUN### Leadership President Joe Biden last week nominated former Senator Bill Nelson (D–FL) to lead NASA, a job that would require him to balance returning humans to the Moon with sending robots to observe Earth, Mars, and beyond. Nelson, who flew as a civilian on the space shuttle in 1986, was a lead Senate sponsor of NASA's new Moon rocket, the Space Launch System, which last week had the first successful test of its engines. Some advocates have called for replacing the delayed project, which has spent $20 billion so far, with privately operated rockets; but Nelson's nomination appears likely to cement the program. He has little track record of engagement with the agency's science programs, which have enjoyed rising budgets in recent years, especially for planetary science. But many members of Congress support an ambitious project to recover rock samples drilled by the Perseverance rover on Mars. Nelson is also seen as a backer of climate research, and earth scientists hope he will help reverse a long-term drop in NASA's spending on that discipline. 50% —The increase in atmospheric carbon dioxide since preindustrial times. The gas, which contributes to global warming, crossed that threshold for the first time when its concentration reached 417 parts per million this month (U.K. Met Office). ### Biodiversity Ecologists involved in mapping life on Earth have taken the next step: predicting where to find the 85% of the planet's species waiting to be discovered. Worried that conservation efforts usually ignore these hidden species, Mario Moura, an ecologist at the Federal University of Paraèba in Brazil, created an interactive map showing biodiversity hot spots with the richest potential for hosting unknown, land-dwelling species of mammals, birds, reptiles, and amphibians. He and ecologist Walter Jetz of Yale University built it using data about known vertebrates' size, habitat, and nine other attributes that influence the likelihood of discovery at a particular location. For example, large mammals living near people are much more likely to be found than tiny frogs in a remote jungle. The map predicts that Brazil has more mystery species, 10% of all, than any other country. Colombia, Indonesia, and Madagascar account for 5% each, Moura and Jetz reported this week in Nature Ecology & Evolution . ### COVID-19 The U.S. Centers for Disease Control and Prevention (CDC) last week named as a “variant of concern” a spreading strain of the pandemic coronavirus identified in California in January. The variant, which comes in two slightly different forms called B.1.427 and B.1.429, becomes the fourth given that designation by CDC. A variant of concern may evade immunity, drugs, and diagnostic tests; make people sicker; and be more transmissible than the original virus. A recent preprint study indicated that the new variant flagged by CDC resists antibodies generated by vaccines and natural infection. In the past 30 days, the variant has accounted for some 61% of the samples sequenced in California and 65% of sequences in Nevada. Also last week, the U.S. Food and Drug Administration updated its emergency use authorization for the monoclonal antibody bamlanivimab to indicate that when used alone, it is unlikely to be effective against the new variant. ### Infectious diseases In countries that bear a heavy burden of tuberculosis (TB), diagnosis and treatment for the disease declined markedly in 2020 because health care facilities closed or diverted resources to COVID-19, a nonprofit group said last week. The Stop TB Partnership collected data from nine countries, seven of them in Asia, that account for 60% of the global TB burden. It found that TB diagnosis and treatment fell on average by 23%; at least 1 million fewer new cases were treated, the lowest level since 2008. In 2019, TB was the world's leading infectious killer, with 1.4 million deaths, more than 95% of them in developing countries. The Stop TB Partnership predicts that in 2020, TB remained the leading infectious killer in these countries even though COVID-19 surpassed it globally. The group urges health systems to simultaneously test for and tackle COVID-19 and TB, both infectious respiratory diseases. ### Climate change It's back! The U.S. Environmental Protection Agency (EPA) last week relaunched a web page focused on climate change that former President Donald Trump's administration dismantled 4 years ago. The agency says it plans to add new, updated information in coming months about climate science and its actions to curb global warming. In 2017, then-EPA Administrator Scott Pruitt erased the page, which had existed for some 20 years, along with many other mentions of climate science on the agency's website. ### Agriculture The golden apple snail ( Pomacea canaliculata ), an invasive pest that costs rice farmers in Asia more than $1 billion a year, has been documented in continental Africa for the first time. Farmers in Kenya's Mwea irrigation area, a 10,000-hectare region that produces more than 70% of the country's rice, noticed the 2-centimeter snails, which were later confirmed by DNA tests, researchers report this week in CABI Agriculture and Bioscience . The snails are eating 90% of seedlings, the farmers say. The snail species is native to the Americas. To help prevent its spread in Africa, researchers say Kenya should consider restricting movement of farm machinery and host plants from the infected area. ### Biomedicine The founding director of the U.S. National Institutes of Health's (NIH's) center focusing on the translation of basic science into treatments is stepping down. Neurologist and geneticist Christopher Austin, who led the National Center for Advancing Translational Sciences (NCATS), will become a partner at the venture capital firm Flagship Pioneering. NIH Director Francis Collins persuaded Congress to create NCATS in 2011, despite skepticism from industry. Under Austin, the center's efforts included screening small molecules for drug candidates, developing treatments for rare diseases, and streamlining clinical trials at academic health centers. Some observers say NCATS never had the budget to realize its ambitions ( Science , 27 September 2019, p. [1363][1]). But the government's role in drug development may soon grow, with President Joe Biden expected to reveal details for a health agency modeled after the applications-oriented Defense Advanced Research Projects Agency. ### Drug development A late-stage drug trial that had buoyed the hopes of families afflicted by Huntington disease, a devastating, incurable neurological illness, was stopped on 22 March by the manufacturer, Roche. A data monitoring committee had recommended the move after weighing benefits and risks of the drug, tominersen (formerly called IONIS-HTTRx and RG6042). The company said no new safety issues had emerged during the trial, but provided no additional details. Tominersen is an antisense oligonucleotide, a snippet of genetic code designed to interfere with production of a protein—in this case, the mutant protein called huntingtin that causes the inherited disease. The drug was developed by Ionis Pharmaceuticals, which licensed it to Roche in 2017, shortly after an early human trial showed it caused dose-dependent reductions in huntingtin ( Science , 24 August 2018, p. [742][2]). The sudden cessation stunned trial leaders, who had finished enrolling nearly 800 people in April 2020 and expected results in 2022. ![Figure][3] In Focus The stems, air bladders, and blades of giant kelp ( Macrocystis pyrifera ), the world's largest seaweed, form a golden still life. With fronds reaching more than 30 meters, the species thrives in cold, clear water, forming dense forests that host diverse ecosystems. This prize-winning image is part of an outdoor exhibit about algae at the University of Nottingham that can be seen at . PHOTO: ERASMO EMACAYA ### Animal behavior Adult mountain gorillas, including male silverbacks, often adopt motherless or orphaned young members of their social groups—a behavior previously thought to be rare in mammals other than humans—a study reports. Chimpanzees and other social mammals that lose their mothers face a greater risk of dying, and gorillas often kill orphans from different social groups. But thanks to the in-group communal care, gorillas who were motherless or orphaned survived as well as youngsters whose mothers were still around. This week in eLife , scientists describe the analysis, which used a remarkable 53 years of data on mountain gorillas collected at the Dian Fossey Gorilla Fund's Karisoke Research Center in Rwanda, in one of the longest field studies. Scientists found that 59 motherless or orphaned gorillas also suffered no long-term decline in social rank or ability to reproduce. Older sisters and peers of orphans joined males, including dominant silverbacks, in frequent child care. Some motherless males who spent lots of time with the silverback in their social group did well: They grew up to become its dominant ape. ### Climate science The Biden administration last week appointed Jane Lubchenco, who headed the National Oceanic and Atmospheric Administration under former President Barack Obama, to serve as its top climate scientist in the White House Office of Science and Technology Policy. A marine ecologist and advocate for the ocean, Lubchenco will work as deputy director for climate and the environment, coordinating climate science across federal agencies and the U.S. Global Change Research Program. Lubchenco's focus will be to spur research and action on climate mitigation that can also benefit the U.S. economy. ### Science policy In Sweden, a national code uses 44,000 words to define research misconduct and discuss scientific values. Next door, Norway's equivalent is a brisk 900 words. An analysis of scientific integrity policies in 32 European nations has found wide differences not only in length, but in standards and definitions of research misconduct. The nonbinding European Code of Conduct for Research Integrity, issued by the European Federation of Academies of Sciences and Humanities in 2017, was intended to promote consistency; it also allows countries to add language to fit their circumstances. But only two of 32 countries examined—Bulgaria and Luxembourg—have adopted the code wholesale, according to a study last month in Bioethics . And there's just one principle that all countries have agreed on: that fabrication, falsification, and plagiarism of data and findings constitute research misconduct. Research ethicists say the differences threaten to create confusion and disputes for multinational scientific collaborations as they decide which country's rules apply. ### Microbiology Soil bacteria called Streptomyces are guardian angels of the microbial world: They produce antibiotics that humans depend on and protect plants from harmful microbes. But because they lack self-propulsion, researchers have long puzzled over how they find the plants they defend. Now, scientists have discovered that the microbe's dormant spores typically hitch rides on the whiplike flagella of other, mobile soil microbes heading for plant roots, researchers reported last week in The ISME Journal: Multidisciplinary Journal of Microbial Ecology . A few other species of bacteria and a fungus are known to catch rides on other microbes. But the observed piggybacking on microbes by spores—previously known to latch on to insects and other small animals for travel—is a first, says co-author Alise Muok of Leiden University. With this mystery solved, researchers may one day modify the hitchhiking to improve plant protection, she adds. [1]: http://www.sciencemag.org/content/365/6460/1363 [2]: http://www.sciencemag.org/content/361/6404/742 [3]: pending:yes

We introduce the problem of robust subgroup discovery, i.e., finding a set of interpretable descriptions of subsets that 1) stand out with respect to one or more target attributes, 2) are statistically robust, and 3) non-redundant. Many attempts have been made to mine either locally robust subgroups or to tackle the pattern explosion, but we are the first to address both challenges at the same time from a global perspective. First, we formulate a broad model class of subgroup lists, i.e., ordered sets of subgroups, for univariate and multivariate targets that can consist of nominal or numeric variables. This novel model class allows us to formalize the problem of optimal robust subgroup discovery using the Minimum Description Length (MDL) principle, where we resort to optimal Normalized Maximum Likelihood and Bayesian encodings for nominal and numeric targets, respectively. Notably, we show that our problem definition is equal to mining the top-1 subgroup with an information-theoretic quality measure plus a penalty for complexity. Second, as finding optimal subgroup lists is NP-hard, we propose RSD, a greedy heuristic that finds good subgroup lists and guarantees that the most significant subgroup found according to the MDL criterion is added in each iteration, which is shown to be equivalent to a Bayesian one-sample proportions, multinomial, or t-test between the subgroup and dataset marginal target distributions plus a multiple hypothesis testing penalty. We empirically show on 54 datasets that RSD outperforms previous subgroup set discovery methods in terms of quality and subgroup list size.

The unification of statistical (data-driven) and symbolic (knowledge-driven) methods is widely recognised as one of the key challenges of modern AI. Recent years have seen large number of publications on such hybrid neuro-symbolic AI systems. That rapidly growing literature is highly diverse and mostly empirical, and is lacking a unifying view of the large variety of these hybrid systems. In this paper we analyse a large body of recent literature and we propose a set of modular design patterns for such hybrid, neuro-symbolic systems. We are able to describe the architecture of a very large number of hybrid systems by composing only a small set of elementary patterns as building blocks. The main contributions of this paper are: 1) a taxonomically organised vocabulary to describe both processes and data structures used in hybrid systems; 2) a set of 15+ design patterns for hybrid AI systems, organised in a set of elementary patterns and a set of compositional patterns; 3) an application of these design patterns in two realistic use-cases for hybrid AI systems. Our patterns reveal similarities between systems that were not recognised until now. Finally, our design patterns extend and refine Kautz' earlier attempt at categorising neuro-symbolic architectures.

But these scenarios depend upon an unanswered question: are machines intelligent to begin with? Computers are essentially logic machines that process digital information. But in a recent paper entitled "The Emperor of Strong AI Has No Clothes," physicist Robert K. Logan in Toronto and Adriana Braga in Rio de Janeiro argue that the dream of a super intelligence has limits that its adherents choose to ignore. The things the Singularity will never get right amount to a long list, to quote the two researchers: "… curiosity, imagination, intuition, emotions, passion, desires, pleasure, aesthetics, joy, purpose, objectives, goals, telos, values, morality, experience, wisdom, judgment, and even humor." A clever programmer can figure out how to get a computer to answer human questions like "How is your mother feeling?", "What does chocolate taste like?", and "Don't you just love fresh snow?"

Transformer architectures have become the model of choice in natural language processing and are now being introduced into computer vision tasks such as image classification, object detection, and semantic segmentation. However, in the field of human pose estimation, convolutional architectures still remain dominant. In this work, we present PoseFormer, a purely transformer-based approach for 3D human pose estimation in videos without convolutional architectures involved. Inspired by recent developments in vision transformers, we design a spatial-temporal transformer structure to comprehensively model the human joint relations within each frame as well as the temporal correlations across frames, then output an accurate 3D human pose of the center frame. We quantitatively and qualitatively evaluate our method on two popular and standard benchmark datasets: Human3.6M and MPI-INF-3DHP. Extensive experiments show that PoseFormer achieves state-of-the-art performance on both datasets. Code is available at \url{https://github.com/zczcwh/PoseFormer}

Label noise in multiclass classification is a major obstacle to the deployment of learning systems. However, unlike the widely used class-conditional noise (CCN) assumption that the noisy label is independent of the input feature given the true label, label noise in real-world datasets can be aleatory and heavily dependent on individual instances. In this work, we investigate the instance-dependent noise (IDN) model and propose an efficient approximation of IDN to capture the instance-specific label corruption. Concretely, noting the fact that most columns of the IDN transition matrix have only limited influence on the class-posterior estimation, we propose a variational approximation that uses a single-scalar confidence parameter. To cope with the situation where the mapping from the instance to its confidence value could vary significantly for two adjacent instances, we suggest using instance embedding that assigns a trainable parameter to each instance. The resulting instance-confidence embedding (ICE) method not only performs well under label noise but also can effectively detect ambiguous or mislabeled instances. We validate its utility on various image and text classification tasks.

In this work we address the problem of solving ill-posed inverse problems in imaging where the prior is a variational autoencoder (VAE). Specifically we consider the decoupled case where the prior is trained once and can be reused for many different log-concave degradation models without retraining. Whereas previous MAP-based approaches to this problem lead to highly non-convex optimization algorithms, our approach computes the joint (space-latent) MAP that naturally leads to alternate optimization algorithms and to the use of a stochastic encoder to accelerate computations. The resulting technique (JPMAP) performs Joint Posterior Maximization using an Autoencoding Prior. We show theoretical and experimental evidence that the proposed objective function is quite close to bi-convex. Indeed it satisfies a weak bi-convexity property which is sufficient to guarantee that our optimization scheme converges to a stationary point. We also highlight the importance of correctly training the VAE using a denoising criterion, in order to ensure that the encoder generalizes well to out-of-distribution images, without affecting the quality of the generative model. This simple modification is key to providing robustness to the whole procedure. Finally we show how our joint MAP methodology relates to more common MAP approaches, and we propose a continuation scheme that makes use of our JPMAP algorithm to provide more robust MAP estimates. Experimental results also show the higher quality of the solutions obtained by our JPMAP approach with respect to other non-convex MAP approaches which more often get stuck in spurious local optima.

Prediction tasks about students have practical significance for both student and college. Making multiple predictions about students is an important part of a smart campus. For instance, predicting whether a student will fail to graduate can alert the student affairs office to take predictive measures to help the student improve his/her academic performance. With the development of information technology in colleges, we can collect digital footprints which encode heterogeneous behaviors continuously. In this paper, we focus on modeling heterogeneous behaviors and making multiple predictions together, since some prediction tasks are related and learning the model for a specific task may have the data sparsity problem. To this end, we propose a variant of LSTM and a soft-attention mechanism. The proposed LSTM is able to learn the student profile-aware representation from heterogeneous behavior sequences. The proposed soft-attention mechanism can dynamically learn different importance degrees of different days for every student. In this way, heterogeneous behaviors can be well modeled. In order to model interactions among multiple prediction tasks, we propose a co-attention mechanism based unit. With the help of the stacked units, we can explicitly control the knowledge transfer among multiple tasks. We design three motivating behavior prediction tasks based on a real-world dataset collected from a college. Qualitative and quantitative experiments on the three prediction tasks have demonstrated the effectiveness of our model.

Identifying the research topics that best describe the scope of a scientific publication is a crucial task for editors, in particular because the quality of these annotations determine how effectively users are able to discover the right content in online libraries. For this reason, Springer Nature, the world's largest academic book publisher, has traditionally entrusted this task to their most expert editors. These editors manually analyse all new books, possibly including hundreds of chapters, and produce a list of the most relevant topics. Hence, this process has traditionally been very expensive, time-consuming, and confined to a few senior editors. For these reasons, back in 2016 we developed Smart Topic Miner (STM), an ontology-driven application that assists the Springer Nature editorial team in annotating the volumes of all books covering conference proceedings in Computer Science. Since then STM has been regularly used by editors in Germany, China, Brazil, India, and Japan, for a total of about 800 volumes per year. Over the past three years the initial prototype has iteratively evolved in response to feedback from the users and evolving requirements. In this paper we present the most recent version of the tool and describe the evolution of the system over the years, the key lessons learnt, and the impact on the Springer Nature workflow. In particular, our solution has drastically reduced the time needed to annotate proceedings and significantly improved their discoverability, resulting in 9.3 million additional downloads. We also present a user study involving 9 editors, which yielded excellent results in term of usability, and report an evaluation of the new topic classifier used by STM, which outperforms previous versions in recall and F-measure.