Unsupervised Domain Adaptation (UDA) methods for person Re-Identification (Re-ID) rely on target domain samples to model the marginal distribution of the data. To deal with the lack of target domain labels, UDA methods leverage information from labeled source samples and unlabeled target samples. A promising approach relies on the use of unsupervised learning as part of the pipeline, such as clustering methods. The quality of the clusters clearly plays a major role in methods performance, but this point has been overlooked. In this work, we propose a multi-step pseudo-label refinement method to select the best possible clusters and keep improving them so that these clusters become closer to the class divisions without knowledge of the class labels. Our refinement method includes a cluster selection strategy and a camera-based normalization method which reduces the within-domain variations caused by the use of multiple cameras in person Re-ID. This allows our method to reach state-of-the-art UDA results on DukeMTMC-Market1501 (source-target). We surpass state-of-the-art for UDA Re-ID by 3.4% on Market1501-DukeMTMC datasets, which is a more challenging adaptation setup because the target domain (DukeMTMC) has eight distinct cameras. Furthermore, the camera-based normalization method causes a significant reduction in the number of iterations required for training convergence.

The Multi-armed bandit offer the advantage to learn and exploit the already learnt knowledge at the same time. This capability allows this approach to be applied in different domains, going from clinical trials where the goal is investigating the effects of different experimental treatments while minimizing patient losses, to adaptive routing where the goal is to minimize the delays in a network. This article provides a review of the recent results on applying bandit to real-life scenario and summarize the state of the art for each of these fields. Different techniques has been proposed to solve this problem setting, like epsilon-greedy, Upper confident bound (UCB) and Thompson Sampling (TS). We are showing here how this algorithms were adapted to solve the different problems of exploration exploitation.

Computer vision is an artificially intelligent technology that is rapidly growing in popularity. As this tech deals with how computers can reap high-level understanding from digital images or videos, it is becoming a part of people's everyday life. Besides having a significant impact on business transformation and consumers' lives, computer vision is starting to disrupt the global industry. The explosion in visual data, enhanced neural networks, and low-cost chips are some of the growth factors of computer vision. As a fast-evolving technology space, computer vision has attracted a lot of exposure and a great amount of investment.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Every once in a while, it's crucial to step back from the immediate mess and gossip and all the little things we tend to focus on each day to look at our world from a 30,000-foot view, to project what we should expect moving forward. As we enter a new decade, this seems like the perfect time to think about and prepare for what may come over the next 10 years both at home and abroad. To state the obvious, this is not an exact science.

This time last year we were commemorating the end of a decade and looking ahead to the next one. Enter the year that felt like a decade all by itself: 2020. News written in January, the before-times, feels hopelessly out of touch with all that came after. Stories published in the early days of the pandemic are, for the most part, similarly naive. The year’s news cycle was swift and brutal, ping-ponging from pandemic to extreme social and political tension, whipsawing economies, and natural disasters. Hope. Despair. Loneliness. Grief. Grit. More hope. Another lockdown. It’s been a hell of a year. Though 2020 was dominated by big, hairy societal change, science and technology took significant steps forward. Researchers singularly focused on the pandemic and collaborated on solutions to a degree never before seen. New technologies converged to deliver vaccines in record time. The dark side of tech, from biased algorithms to the threat of omnipresent surveillance and corporate control of artificial intelligence, continued to rear its head. Meanwhile, AI showed uncanny command of language, joined Reddit threads, and made inroads into some of science’s grandest challenges. Mars rockets flew for the first time, and a private company delivered astronauts to the International Space Station. Deprived of night life, concerts, and festivals, millions traveled to virtual worlds instead. Anonymous jet packs flew over LA. Mysterious monoliths appeared and disappeared worldwide. It was all, you know, very 2020. For this year’s (in-no-way-all-encompassing) list of fascinating stories in tech and science, we tried to select those that weren’t totally dated by the news, but rose above it in some way. So, without further ado: This year’s picks. How Science Beat the Virus Ed Yong | The Atlantic “Much like famous initiatives such as the Manhattan Project and the Apollo program, epidemics focus the energies of large groups of scientists. …But ‘nothing in history was even close to the level of pivoting that’s happening right now,’ Madhukar Pai of McGill University told me. … No other disease has been scrutinized so intensely, by so much combined intellect, in so brief a time.” ‘It Will Change Everything’: DeepMind’s AI Makes Gigantic Leap in Solving Protein Structures Ewen Callaway | Nature “In some cases, AlphaFold’s structure predictions were indistinguishable from those determined using ‘gold standard’ experimental methods such as X-ray crystallography and, in recent years, cryo-electron microscopy (cryo-EM). AlphaFold might not obviate the need for these laborious and expensive methods—yet—say scientists, but the AI will make it possible to study living things in new ways.” OpenAI’s Latest Breakthrough Is Astonishingly Powerful, But Still Fighting Its Flaws James Vincent | The Verge “What makes GPT-3 amazing, they say, is not that it can tell you that the capital of Paraguay is Asunción (it is) or that 466 times 23.5 is 10,987 (it’s not), but that it’s capable of answering both questions and many more beside simply because it was trained on more data for longer than other programs. If there’s one thing we know that the world is creating more and more of, it’s data and computing power, which means GPT-3’s descendants are only going to get more clever.” Artificial General Intelligence: Are We Close, and Does It Even Make Sense to Try? Will Douglas Heaven | MIT Technology Review “A machine that could think like a person has been the guiding vision of AI research since the earliest days—and remains its most divisive idea. …So why is AGI controversial? Why does it matter? And is it a reckless, misleading dream—or the ultimate goal?” The Dark Side of Big Tech’s Funding for AI Research Tom Simonite | Wired “Timnit Gebru’s exit from Google is a powerful reminder of how thoroughly companies dominate the field, with the biggest computers and the most resources. …[Meredith] Whittaker of AI Now says properly probing the societal effects of AI is fundamentally incompatible with corporate labs. ‘That kind of research that looks at the power and politics of AI is and must be inherently adversarial to the firms that are profiting from this technology.’i” We’re Not Prepared for the End of Moore’s Law David Rotman | MIT Technology Review “Quantum computing, carbon nanotube transistors, even spintronics, are enticing possibilities—but none are obvious replacements for the promise that Gordon Moore first saw in a simple integrated circuit. We need the research investments now to find out, though. Because one prediction is pretty much certain to come true: we’re always going to want more computing power.” Inside the Race to Build the Best Quantum Computer on Earth Gideon Lichfield | MIT Technology Review “Regardless of whether you agree with Google’s position [on ‘quantum supremacy’] or IBM’s, the next goal is clear, Oliver says: to build a quantum computer that can do something useful. …The trouble is that it’s nearly impossible to predict what the first useful task will be, or how big a computer will be needed to perform it.” The Secretive Company That Might End Privacy as We Know It Kashmir Hill | The New York Times “Searching someone by face could become as easy as Googling a name. Strangers would be able to listen in on sensitive conversations, take photos of the participants and know personal secrets. Someone walking down the street would be immediately identifiable—and his or her home address would be only a few clicks away. It would herald the end of public anonymity.” Wrongfully Accused by an Algorithm Kashmir Hill | The New York Times “Mr. Williams knew that he had not committed the crime in question. What he could not have known, as he sat in the interrogation room, is that his case may be the first known account of an American being wrongfully arrested based on a flawed match from a facial recognition algorithm, according to experts on technology and the law.” Predictive Policing Algorithms Are Racist. They Need to Be Dismantled. Will Douglas Heaven | MIT Technology Review “A number of studies have shown that these tools perpetuate systemic racism, and yet we still know very little about how they work, who is using them, and for what purpose. All of this needs to change before a proper reckoning can take pace. Luckily, the tide may be turning.” The Panopticon Is Already Here Ross Andersen | The Atlantic “Artificial intelligence has applications in nearly every human domain, from the instant translation of spoken language to early viral-outbreak detection. But Xi [Jinping] also wants to use AI’s awesome analytical powers to push China to the cutting edge of surveillance. He wants to build an all-seeing digital system of social control, patrolled by precog algorithms that identify potential dissenters in real time.” The Case For Cities That Aren’t Dystopian Surveillance States Cory Doctorow | The Guardian “Imagine a human-centered smart city that knows everything it can about things. It knows how many seats are free on every bus, it knows how busy every road is, it knows where there are short-hire bikes available and where there are potholes. …What it doesn’t know is anything about individuals in the city.” The Modern World Has Finally Become Too Complex for Any of Us to Understand Tim Maughan | OneZero “One of the dominant themes of the last few years is that nothing makes sense. …I am here to tell you that the reason so much of the world seems incomprehensible is that it is incomprehensible. From social media to the global economy to supply chains, our lives rest precariously on systems that have become so complex, and we have yielded so much of it to technologies and autonomous actors that no one totally comprehends it all.” The Conscience of Silicon Valley Zach Baron | GQ “What I really hoped to do, I said, was to talk about the future and how to live in it. This year feels like a crossroads; I do not need to explain what I mean by this. …I want to destroy my computer, through which I now work and ‘have drinks’ and stare at blurry simulations of my parents sometimes; I want to kneel down and pray to it like a god. I want someone—I want Jaron Lanier—to tell me where we’re going, and whether it’s going to be okay when we get there. Lanier just nodded. All right, then.” Yes to Tech Optimism. And Pessimism. Shira Ovide | The New York Times “Technology is not something that exists in a bubble; it is a phenomenon that changes how we live or how our world works in ways that help and hurt. That calls for more humility and bridges across the optimism-pessimism divide from people who make technology, those of us who write about it, government officials and the public. We need to think on the bright side. And we need to consider the horribles.” How Afrofuturism Can Help the World Mend C. Brandon Ogbunu | Wired “…[W. E. B. DuBois’] ‘The Comet’ helped lay the foundation for a paradigm known as Afrofuturism. A century later, as a comet carrying disease and social unrest has upended the world, Afrofuturism may be more relevant than ever. Its vision can help guide us out of the rubble, and help us to consider universes of better alternatives.” Wikipedia Is the Last Best Place on the Internet Richard Cooke | Wired “More than an encyclopedia, Wikipedia has become a community, a library, a constitution, an experiment, a political manifesto—the closest thing there is to an online public square. It is one of the few remaining places that retains the faintly utopian glow of the early World Wide Web.” Can Genetic Engineering Bring Back the American Chestnut? Gabriel Popkin | The New York Times Magazine “The geneticists’ research forces conservationists to confront, in a new and sometimes discomfiting way, the prospect that repairing the natural world does not necessarily mean returning to an unblemished Eden. It may instead mean embracing a role that we’ve already assumed: engineers of everything, including nature.” At the Limits of Thought David C. Krakauer | Aeon “A schism is emerging in the scientific enterprise. On the one side is the human mind, the source of every story, theory, and explanation that our species holds dear. On the other stand the machines, whose algorithms possess astonishing predictive power but whose inner workings remain radically opaque to human observers.” Is the Internet Conscious? If It Were, How Would We Know? Meghan O’Gieblyn | Wired “Does the internet behave like a creature with an internal life? Does it manifest the fruits of consciousness? There are certainly moments when it seems to. Google can anticipate what you’re going to type before you fully articulate it to yourself. Facebook ads can intuit that a woman is pregnant before she tells her family and friends. It is easy, in such moments, to conclude that you’re in the presence of another mind—though given the human tendency to anthropomorphize, we should be wary of quick conclusions.” The Internet Is an Amnesia Machine Simon Pitt | OneZero “There was a time when I didn’t know what a Baby Yoda was. Then there was a time I couldn’t go online without reading about Baby Yoda. And now, Baby Yoda is a distant, shrugging memory. Soon there will be a generation of people who missed the whole thing and for whom Baby Yoda is as meaningless as it was for me a year ago.” Digital Pregnancy Tests Are Almost as Powerful as the Original IBM PC Tom Warren | The Verge “Each test, which costs less than $5, includes a processor, RAM, a button cell battery, and a tiny LCD screen to display the result. …Foone speculates that this device is ‘probably faster at number crunching and basic I/O than the CPU used in the original IBM PC.’ IBM’s original PC was based on Intel’s 8088 microprocessor, an 8-bit chip that operated at 5Mhz. The difference here is that this is a pregnancy test you pee on and then throw away.” The Party Goes on in Massive Online Worlds Cecilia D’Anastasio | Wired “We’re more stand-outside types than the types to cast a flashy glamour spell and chat up the nearest cat girl. But, hey, it’s Final Fantasy XIV online, and where my body sat in New York, the epicenter of America’s Covid-19 outbreak, there certainly weren’t any parties.” The Facebook Groups Where People Pretend the Pandemic Isn’t Happening Kaitlyn Tiffany | The Atlantic “Losing track of a friend in a packed bar or screaming to be heard over a live band is not something that’s happening much in the real world at the moment, but it happens all the time in the 2,100-person Facebook group ‘a group where we all pretend we’re in the same venue.’ So does losing shoes and Juul pods, and shouting matches over which bands are the saddest, and therefore the greatest.” Did You Fly a Jetpack Over Los Angeles This Weekend? Because the FBI Is Looking for You Tom McKay | Gizmodo “Did you fly a jetpack over Los Angeles at approximately 3,000 feet on Sunday? Some kind of tiny helicopter? Maybe a lawn chair with balloons tied to it? If the answer to any of the above questions is ‘yes,’ you should probably lay low for a while (by which I mean cool it on the single-occupant flying machine). That’s because passing airline pilots spotted you, and now it’s this whole thing with the FBI and the Federal Aviation Administration, both of which are investigating.” Image Credit: Thomas Kinto / Unsplash Continue reading →

Sensors are being extensively deployed and are expected to expand at significant rates in the coming years. They typically generate a large volume of data on the internet of things (IoT) application areas like smart cities, intelligent traffic systems, smart grid, and e-health. Cloud, edge and fog computing are potential and competitive strategies for collecting, processing, and distributing IoT data. However, cloud, edge, and fog-based solutions need to tackle the distribution of a high volume of IoT data efficiently through constrained and limited resource network infrastructures. This paper addresses the issue of conveying a massive volume of IoT data through a network with limited communications resources (bandwidth) using a cognitive communications resource allocation based on Reinforcement Learning (RL) with SARSA algorithm. The proposed network infrastructure (PSIoTRL) uses a Publish/ Subscribe architecture to access massive and highly distributed IoT data. It is demonstrated that the PSIoTRL bandwidth allocation for buffer flushing based on SARSA enhances the IoT aggregator buffer occupation and network link utilization.

In this paper we present an approach for training deep generative models solely based on solving determined systems of linear equations. A network that uses this approach, called a StarNet, has the following desirable properties: 1) training requires no gradient as solution to the system of linear equations is not stochastic, 2) is highly scalable when solving the system of linear equations w.r.t the latent codes, and similarly for the parameters of the model, and 3) it gives desirable least-square bounds for the estimation of latent codes and network parameters within each layer.

Problems in dimension three with rotations around combinations of axes in multiples of 90 degrees are of particular interest in many natural applications. Let us fix the order of six such allowable rotations in dimension three arbitrarily and define: The Container Loading Problem (CLP): Given dimensions of a large box ("container") x, y, z 0 and dimensions of n small boxes D

By the end of July 2020, Kenya h ad reported only 341 deaths and ∼20,000 cases of COVID-19. This is in marked contrast to the tens of thousands of deaths reported in many higher-income countries. The true extent of COVID-19 in the community was unknown and likely to be higher than reports indicated. Uyoga et al. found an overall seroprevalence among blood donors of 4.3%, peaking in 35- to 44-year-old individuals (see the Perspective by Maeda and Nkengasong). The low mortality can be partly explained by the steep demographics in Kenya, where less than 4% of the population is 65 or older. These circumstances combine to result in Kenyan hospitals not currently being overwhelmed by patients with respiratory distress. However, the imposition of a strict lockdown in this country has shifted the disease burden to maternal and child deaths as a result of disruption to essential medical services. Science , this issue p. [79][1]; see also p. [27][2] The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Africa is poorly described. The first case of SARS-CoV-2 in Kenya was reported on 12 March 2020, and an overwhelming number of cases and deaths were expected, but by 31 July 2020, there were only 20,636 cases and 341 deaths. However, the extent of SARS-CoV-2 exposure in the community remains unknown. We determined the prevalence of anti–SARS-CoV-2 immunoglobulin G among blood donors in Kenya in April–June 2020. Crude seroprevalence was 5.6% (174 of 3098). Population-weighted, test-performance-adjusted national seroprevalence was 4.3% (95% confidence interval, 2.9 to 5.8%) and was highest in urban counties Mombasa (8.0%), Nairobi (7.3%), and Kisumu (5.5%). SARS-CoV-2 exposure is more extensive than indicated by case-based surveillance, and these results will help guide the pandemic response in Kenya and across Africa. [1]: /lookup/doi/10.1126/science.abe1916 [2]: /lookup/doi/10.1126/science.abf8832

Subsidence, the lowering of Earth's land surface, is a potentially destructive hazard that can be caused by a wide range of natural or anthropogenic triggers but mainly results from solid or fluid mobilization underground. Subsidence due to groundwater depletion ([ 1 ][1]) is a slow and gradual process that develops on large time scales (months to years), producing progressive loss of land elevation (centimeters to decimeters per year) typically over very large areas (tens to thousands of square kilometers) and variably affects urban and agricultural areas worldwide. Subsidence permanently reduces aquifer-system storage capacity, causes earth fissures, damages buildings and civil infrastructure, and increases flood susceptibility and risk. During the next decades, global population and economic growth will continue to increase groundwater demand and accompanying groundwater depletion ([ 2 ][2]) and, when exacerbated by droughts ([ 3 ][3]), will probably increase land subsidence occurrence and related damages or impacts. To raise awareness and inform decision-making, we evaluate potential global subsidence due to groundwater depletion, a key first step toward formulating effective land-subsidence policies that are lacking in most countries worldwide. A large-scale systematic literature review reveals that during the past century, land subsidence due to groundwater depletion occurred at 200 locations in 34 countries [see supplementary materials (SM)]. However, subsidence extent is only known for one-third of these records, information on the impacts is scarce, and mitigation measures were implemented only in a few locations. In China, widespread subsidence affects cities developed in the main sedimentary basins. In Indonesia, coastal subsidence in Jakarta is so severe that government authorities are planning to move the capital to the island of Borneo. In Japan, subsidence affected several cities during the 20th century, including more than 4 m of subsidence in Tokyo, before groundwater management practices mitigated further subsidence. Iran currently hosts some of the fastest-sinking cities in the world (25 cm year--1) because of unregulated groundwater pumping. In Europe, the greatest impact of subsidence occurs in the Netherlands, where subsidence is primarily responsible for placing 25% of the country below the mean sea level and increasing the flooding risk. Subsidence in the Po River Plain in Italy started during the second half of the 20th century and currently threatens 30% of the Italian population, contributing to recurrent coastal flooding during extreme high tides in Venice. In North America, intense groundwater depletion triggers subsidence from California's Central Valley, with as much as 9 m of subsidence in the past century, to the Atlantic and Gulf of Mexico coastal plains in the United States, where subsidence is increasing flooding risk. In México, subsidence rates are among the highest worldwide (as much as 30 cm year-1), affecting small structurally controlled intermontane basins where the main urban centers developed, causing an important but unaccounted economic impact. Spatial analysis of subsidence locations identified in our global database (see SM) reveals that subsidence has preferentially occurred in very flat areas where unconsolidated sediments accumulated in alluvial basins or coastal plains, and where urban or agricultural areas developed in temperate or arid climates characterized by prolonged dry periods. Land subsidence has generally occurred in water-stressed basins, where the combination of groundwater withdrawal and natural groundwater discharge outpaced groundwater recharge, resulting in groundwater storage losses, groundwater depletion, and compaction of susceptible aquifer systems. In the affected basins, land subsidence mainly occurred in highly populated areas, with half of documented occurrences in areas susceptible to flooding. In coastal zones, the combined effects of absolute sea-level rise and land subsidence contribute to relative sea-level rise ([ 4 ][4]). The contribution from land subsidence may exceed the contribution from absolute sea-level rise by a factor of 10 or more and could be especially critical for 21% of the geographic locations identified in our database, where land elevation is less than 1 m above the mean sea level. On the basis of the spatial analysis findings, a global model is proposed to combine the main variables influencing subsidence to identify environmental settings favoring land subsidence and the anthropogenic factors leading to groundwater depletion (see SM). Statistical analyses of lithology, land-surface slope, land cover, and Koppen-Geiger climate classes are used to predict global subsidence susceptibility at a spatial resolution of 1 km2. The probability of groundwater depletion is estimated by identifying urban and irrigated areas suffering water stress and where groundwater demand is high. The analyses do not consider subsidence magnitude and rate, owing to the lack of this information at a global scale. Hence, the combination of subsidence susceptibility and the probability of groundwater depletion is used to predict a “proxy” of subsidence hazard, which permits identification of exposed areas where the probability of land subsidence occurrence is high or very high. Even though these results do not necessarily translate to direct impacts or damages, they are useful for identifying potential subsidence areas where further local-scale analysis is necessary. T he comparison of our model predictions with an independent validation dataset reveals a 94% capability to distinguish between subsidence and nonsubsidence areas, according to the value of the area under the receiver operating characteristic curve (see SM). The global exposure to potential subsidence is evaluated by calculating the number of inhabitants living in potential subsidence areas, i.e., subsidence hazard proxy, and the equivalent gross domestic product (GDP). T his “proxy” of exposed assets is calculated assuming that GDP per capita is homogeneous within each country. Finally, the evolution of potential global subsidence and the related exposure is predicted for 2040 for a global change scenario based on steady population growth and increasing greenhouse gas emissions (Shared Socioeconomic Pathways 2, Representative Concentration Pathway 8.5), which accounts for the greatest sea-level rise projections. ![Figure][5] Potential global subsidence The color scale indicates the probability intervals classified from very low (VL) to very high (VH), for every 30-arcsec resolution pixel (1 km by 1 km at the Equator). The white hatched polygons indicate countries where groundwater data is unavailable, and the potential subsidence only includes information on the susceptibility. See maps of other regions in supplementary materials. GRAPHIC: N. DESAI/ SCIENCE Our results suggest that potential subsidence threatens 12 million km2 (8%) of the global land surface with a probability greater than 50% (MH to VH in the figure). Potential subsidence areas are concentrated in and near densely urban and irrigated areas with high water stress and high groundwater demand, overlying some of the largest and most depleted aquifer systems ([ 5 ][6]) in Asia (e.g., North China Plain) and North America (e.g., Gulf of Mexico coastal plain); coastal and river delta areas worldwide (e.g., Vietnam, Egypt, or the Netherlands); and inland sedimentary basins of México, Iran, and the Mediterranean countries. Potential subsidence is lower in Africa, Australia, and South America, owing to the lower groundwater depletion ([ 6 ][7]). In central Africa, potential subsidence only includes information on the susceptibility, as groundwater depletion is unknown. In this region, subsidence susceptibility (see fig. S6) could be useful to prevent subsidence impacts on developing cities that during the next decades could rely more on the available groundwater resources. To evaluate the exposure to potential subsidence, we focus on areas where the potential subsidence probability is high or very high (see the figure). The cumulative potential subsidence area amounts to 2.2 million km2, or 1.6% of the land; includes 1.2 billion inhabitants, or 19% of the global population; and has an exposed GDP of US$ 8.19 trillion, or 12% of the global GDP. Hi gh-income countries account for 62% of the global exposed GDP but only 11% of the global exposed population, whereas low-income countries account for 54% of the global exposed population and 12% of the global exposed GDP. It is expected that the capability of low-income countries to implement the political, regulatory, and socioeconomic measures necessary to prevent and mitigate subsidence impact will be less than that for high-income countries. Potential subsidence threatens 484 million inhabitants living in flood-prone areas, 75% of whom live in fluvial areas and 25% of whom live near the coast. This number of threatened inhabitants corresponds to 50% of the global population exposed to flooding hazards according to previous estimates ([ 7 ][8]), demonstrating the importance of considering potential subsidence in global flooding risk analyses. Most of the global population exposed to potential subsidence live in Asia (86%), which is about 10 times the combined exposed population of North America and Europe (9%). The results indicate that 97% of the exposed global population is concentrated in 30 countries (see SM). India and China share the top two rankings of potential subsidence in terms of spatial extent and exposed population. Egypt and the Netherlands have the largest populations living in potential subsidence areas that are below the mean sea level. The greatest population densities in potential subsidence areas occur in Egypt and Indonesia, whereas the relative exposure per country, measured as the exposed population normalized by the total population, is greater than 30% for Egypt, Bangladesh, Netherlands, and Italy. The United States ranks first in terms of GDP exposed to potential subsidence, owing to its high GDP per capita. Combination of the aforementioned metrics permits derivation of a potential subsidence index ranking (see SM). Seven of the first ten ranked countries have the greatest subsidence impact, accounting for the greatest amount of reported damages (Netherlands, China, USA, Japan, Indonesia, México and Italy). During this century, climate change will cause serious impacts on the world's water resources through sea-level rise, more frequent and severe floods and droughts, changes in the mean value and mode of precipitation (rain versus snow), and increased evapotranspiration. Prolonged droughts will decrease groundwater recharge and increase groundwater depletion, intensifying subsidence. The global potential subsidence is predicted for 2040 using the same subsidence metrics and available global projections of water stress, water demand variations, climate, and population (see SM). Although predicted potential subsidence areas increase only by 7% globally, the threatened population is predicted to rise by 30%, affecting 1.6 billion inhabitants, 635 million of whom will be living in flood-prone areas. These changes will not be homogeneous. Between 2010 and 2040, the predicted population exposed to potential subsidence increases more than 80% in the Philippines, Iraq, Indonesia, México, Israel, Netherlands, Algeria, and Bangladesh. The increase will be moderate, less than 30%, for China, the United States, Italy, and Iran. Potential subsidence is forecasted to decrease in Japan and Germany, owing to effective groundwater management policies and population declines. Finally, potential subsidence is predicted to emerge in high-latitude northern countries like Canada and to increase in extent in Russia or Hungary, where climate change will favor longer dry seasons. Further advancements in the global evaluation of subsidence can be made when a global historical database on subsidence rate, magnitude, and extent has been compiled, which could be largely sourced from continental monitoring of surface displacements using satellite radar imagery ([ 8 ][9]). Widespread continuous monitoring of subsidence will permit better evaluation of the potential impact of land subsidence, especially in countries like Indonesia, México, and Iran, where local studies revealed the highest subsidence rates worldwide, but the national dimension of subsidence is still unknown. Further research also is necessary to evaluate the cost of damage caused by current and historical subsidence worldwide. The combination of damage information with hazard estimates will permit improved assessments of potential loss and design of cost-effective countermeasures. Presently, annual subsidence costs are only published for China (US$ 1.5 billion) and the Netherlands (US$ 4.8 billion) ([ 9 ][10]). The greater subsidence costs in the Netherlands owe to the exposed population below the mean sea level and the large investments made to prevent flooding. Our model, which does not yet consider mitigation measures, likely overestimates potential subsidence exposure in the Netherlands and Japan, where groundwater management has effectively controlled subsidence over the past decades ([ 10 ][11]). Our results identify 1596 major cities, or about 22% of the world's 7343 major cities that are in potential subsidence areas, with 57% of these cities also located in flood-prone areas. Moreover, subsidence threatens 15 of the 20 major coastal cities ranked with the highest flood risk worldwide ([ 11 ][12]), where potential subsidence can help delimit areas in which flooding risk could be increased and mitigation measures are necessary. Overall, potential global subsidence results can be useful to better define the spatial extent of poorly documented subsidence occurrences, discover unknown subsiding areas, prevent potential subsidence impacts wherever groundwater depletion occurs, and better identify areas where subsidence could increase the flooding risk. In any of these scenarios, an effective land-subsidence policy should include systematic monitoring and modeling of exposed areas, evaluation of potential damages, and cost-benefit analyses permitting implementation of adequate mitigation or adaptation measures. 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Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. government. The authors declare no competing interests. All data included in this study are available at figshare ([ 12 ][45]). 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