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2. Towards Measuring Goal-Directedness in AI Systems

Author

Xu, Dylan and Rivera, Juan-Pablo

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, I.2.0
Abstract

Recent advances in deep learning have brought attention to the possibility of creating advanced, general AI systems that outperform humans across many tasks. However, if these systems pursue unintended goals, there could be catastrophic consequences. A key prerequisite for AI systems pursuing unintended goals is whether they will behave in a coherent and goal-directed manner in the first place, optimizing for some unknown goal; there exists significant research trying to evaluate systems for said behaviors. However, the most rigorous definitions of goal-directedness we currently have are difficult to compute in real-world settings. Drawing upon this previous literature, we explore policy goal-directedness within reinforcement learning (RL) environments. In our findings, we propose a different family of definitions of the goal-directedness of a policy that analyze whether it is well-modeled as near-optimal for many (sparse) reward functions. We operationalize this preliminary definition of goal-directedness and test it in toy Markov decision process (MDP) environments. Furthermore, we explore how goal-directedness could be measured in frontier large-language models (LLMs). Our contribution is a definition of goal-directedness that is simpler and more easily computable in order to approach the question of whether AI systems could pursue dangerous goals. We recommend further exploration of measuring coherence and goal-directedness, based on our findings., Comment: Updated acknowledgements

Published
2024

3. Unravelling compound risks of hydrological extremes in a changing climate: Typology, methods and futures

Author

Chun, Kwok P, Octavianti, Thanti, Papacharalampous, Georgia, Tyralis, Hristos, Sutanto, Samuel J., Terskii, Pavel, Mazzoglio, Paola, Treppiedi, Dario, Rivera, Juan, Dogulu, Nilay, Olusola, Adeyemi, Dieppois, Bastien, Dembélé, Moctar, Moulds, Simon, Li, Cheng, Morales-Marin, Luis Alejandro, Macdonald, Neil, Amoussou, Toundji Olivier, Yonaba, Roland, Obahoundje, Salomon, Massei, Nicolas, Hannah, David M., Chidepudi, Sivarama Krishna Reddy, and Hamududu, Byman

Subjects
Physics - Physics and Society, Physics - Atmospheric and Oceanic Physics
Abstract

We have witnessed and experienced increasing compound extreme events resulting from simultaneous or sequential occurrence of multiple events in a changing climate. In addition to a growing demand for a clearer explanation of compound risks from a hydrological perspective, there has been a lack of attention paid to socioeconomic factors driving and impacted by these risks. Through a critical review and co-production approaches, we identified four types of compound hydrological events based on autocorrelated, multivariate, and spatiotemporal patterns. A framework to quantify compound risks based on conditional probability is offered, including an argument on the potential use of generative Artificial Intelligence (AI) algorithms for identifying emerging trends and patterns for climate change. Insights for practices are discussed, highlighting the implications for disaster risk reduction and knowledge co-production. Our argument centres on the importance of meaningfully considering the socioeconomic contexts in which compound risks may have impacts, and the need for interdisciplinary collaboration to effectively translate climate science to climate actions., Comment: 19 pages, 1 figure

Published
2024

5. Escalation Risks from Language Models in Military and Diplomatic Decision-Making

Author

Rivera, Juan-Pablo, Mukobi, Gabriel, Reuel, Anka, Lamparth, Max, Smith, Chandler, and Schneider, Jacquelyn

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computers and Society, Computer Science - Multiagent Systems
Abstract

Governments are increasingly considering integrating autonomous AI agents in high-stakes military and foreign-policy decision-making, especially with the emergence of advanced generative AI models like GPT-4. Our work aims to scrutinize the behavior of multiple AI agents in simulated wargames, specifically focusing on their predilection to take escalatory actions that may exacerbate multilateral conflicts. Drawing on political science and international relations literature about escalation dynamics, we design a novel wargame simulation and scoring framework to assess the escalation risks of actions taken by these agents in different scenarios. Contrary to prior studies, our research provides both qualitative and quantitative insights and focuses on large language models (LLMs). We find that all five studied off-the-shelf LLMs show forms of escalation and difficult-to-predict escalation patterns. We observe that models tend to develop arms-race dynamics, leading to greater conflict, and in rare cases, even to the deployment of nuclear weapons. Qualitatively, we also collect the models' reported reasonings for chosen actions and observe worrying justifications based on deterrence and first-strike tactics. Given the high stakes of military and foreign-policy contexts, we recommend further examination and cautious consideration before deploying autonomous language model agents for strategic military or diplomatic decision-making., Comment: 10 pages body, 57 pages appendix, 46 figures, 11 tables

Published
2024
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9. Hepatic steatosis induced by nicotine plus Coca-Cola™ is prevented by nicotinamide riboside (NR)

Author

Rivera, Juan Carlos, Espinoza-Derout, Jorge, Hasan, Kamrul M, Molina-Mancio, Jocelyn, Martínez, Jason, Lao, Candice J, Lee, Martin L, Lee, Desean L, Wilson, Julian, Sinha-Hikim, Amiya P, and Friedman, Theodore C

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Liver Disease, Chronic Liver Disease and Cirrhosis, Prevention, Nutrition, Digestive Diseases, 2.1 Biological and endogenous factors, Good Health and Well Being, Animals, Pyridinium Compounds, Mice, Mice, Inbred C57BL, Niacinamide, Male, Nicotine, Non-alcoholic Fatty Liver Disease, Fatty Liver, High Fructose Corn Syrup, Liver, Oxidative Stress, nicotine, high-fructose corn syrup, hepatic steatosis, nicotinamide riboside, NAD(+), NAD+, Nutrition and Dietetics, Clinical sciences
Abstract

IntroductionCigarettes containing nicotine (Nic) are a risk factor for the development of cardiovascular and metabolic diseases. We reported that Nic delivered via injections or e-cigarette vapor led to hepatic steatosis in mice fed with a high-fat diet. High-fructose corn syrup (HFCS) is the main sweetener in sugar-sweetened beverages (SSBs) in the US. Increased consumption of SSBs with HFCS is associated with increased risks of non-alcoholic fatty liver disease (NAFLD). Nicotinamide riboside (NR) increases mitochondrial nicotinamide adenine dinucleotide (NAD+) and protects mice against hepatic steatosis. This study evaluated if Nic plus Coca-Cola™ (Coke) with HFCS can cause hepatic steatosis and that can be protected by NR.MethodsC57BL/6J mice received twice daily intraperitoneal (IP) injections of Nic or saline and were given Coke (HFCS), or Coke with sugar, and NR supplementation for 10 weeks.ResultsOur results show that Nic+Coke caused increased caloric intake and induced hepatic steatosis, and the addition of NR prevented these changes. Western blot analysis showed lipogenesis markers were activated (increased cleavage of the sterol regulatory element-binding protein 1 [SREBP1c] and reduction of phospho-Acetyl-CoA Carboxylase [p-ACC]) in the Nic+Coke compared to the Sal+Water group. The hepatic detrimental effects of Nic+Coke were mediated by decreased NAD+ signaling, increased oxidative stress, and mitochondrial damage. NR reduced oxidative stress and prevented mitochondrial damage by restoring protein levels of Sirtuin1 (Sirt1) and peroxisome proliferator-activated receptor coactivator 1-alpha (PGC1) signaling.ConclusionWe conclude that Nic+Coke has an additive effect on producing hepatic steatosis, and NR is protective. This study suggests concern for the development of NAFLD in subjects who consume nicotine and drink SSBs with HFCS.

Published
2024

14. An Exploration of Genetic Algorithms Operators for the Detection of Multiple Change-Points of Exceedances Using Non-homogeneous Poisson Processes and Bayesian Methods

Author

Taimal, Carlos A., Suárez-Sierra, Biviana Marcela, Rivera, Juan Carlos, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Tabares, Marta, editor, Vallejo, Paola, editor, Suarez, Biviana, editor, Suarez, Marco, editor, Ruiz, Oscar, editor, and Aguilar, Jose, editor

Published
2024
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17. The lipolysis inhibitor acipimox reverses the cardiac phenotype induced by electronic cigarettes

Author

Espinoza-Derout, Jorge, Arambulo, Jose Mari Luis, Ramirez-Trillo, William, Rivera, Juan Carlos, Hasan, Kamrul M, Lao, Candice J, Jordan, Maria C, Shao, Xuesi M, Roos, Kenneth P, Sinha-Hikim, Amiya P, and Friedman, Theodore C

Subjects
Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Genetics, Cardiovascular, Tobacco, Heart Disease, Tobacco Smoke and Health, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Humans, Mice, Animals, Electronic Nicotine Delivery Systems, Nicotine, Lipolysis, Mice, Inbred C57BL, Phenotype, Cytokines
Abstract

Electronic cigarettes (e-cigarettes) are a prevalent alternative to conventional nicotine cigarettes among smokers and people who have never smoked. Increased concentrations of serum free fatty acids (FFAs) are crucial in generating lipotoxicity. We studied the effects of acipimox, an antilipolytic drug, on e-cigarette-induced cardiac dysfunction. C57BL/6J wild-type mice on high fat diet were treated with saline, e-cigarette with 2.4% nicotine [e-cigarette (2.4%)], and e-cigarette (2.4%) plus acipimox for 12 weeks. Fractional shortening and ejection fraction were diminished in mice exposed to e-cigarettes (2.4%) compared with saline and acipimox-treated mice. Mice exposed to e-cigarette (2.4%) had increased circulating levels of inflammatory cytokines and FFAs, which were diminished by acipimox. Gene Set Enrichment Analysis revealed that e-cigarette (2.4%)-treated mice had gene expression changes in the G2/M DNA damage checkpoint pathway that was normalized by acipimox. Accordingly, we showed that acipimox suppressed the nuclear localization of phospho-p53 induced by e-cigarette (2.4%). Additionally, e-cigarette (2.4%) increased the apurinic/apyrimidinic sites, a marker of oxidative DNA damage which was normalized by acipimox. Mice exposed to e-cigarette (2.4%) had increased cardiac Heme oxygenase 1 protein levels and 4-hydroxynonenal (4-HNE). These markers of oxidative stress were decreased by acipimox. Therefore, inhibiting lipolysis with acipimox normalizes the physiological changes induced by e-cigarettes and the associated increase in inflammatory cytokines, oxidative stress, and DNA damage.

Published
2023

18. Fatty Acid Excess Dysregulates CARF to Initiate the Development of Hepatic Steatosis

Author

Hasan, Kamrul M, Parveen, Meher, Pena, Alondra, Bautista, Francisco, Rivera, Juan Carlos, Huerta, Roxana Ramirez, Martinez, Erica, Espinoza-Derout, Jorge, Sinha-Hikim, Amiya P, and Friedman, Theodore C

Subjects
Biochemistry and Cell Biology, Biomedical and Clinical Sciences, Biological Sciences, Liver Disease, Nutrition, Chronic Liver Disease and Cirrhosis, Digestive Diseases, 2.1 Biological and endogenous factors, Aetiology, Animals, Mice, Endoribonucleases, Fatty Acids, Non-alcoholic Fatty Liver Disease, Palmitates, Protein Serine-Threonine Kinases, Humans, Hep G2 Cells, Apoptosis Regulatory Proteins, RNA-Binding Proteins, CARF, lipo-toxicity, hepatic steatosis, ER-stress, oxidative stress, metabolic stress, NAFLD, Biological sciences, Biomedical and clinical sciences
Abstract

CARF (CDKN2AIP) regulates cellular fate in response to various stresses. However, its role in metabolic stress is unknown. We found that fatty livers from mice exhibit low CARF expression. Similarly, overloaded palmitate inhibited CARF expression in HepG2 cells, suggesting that excess fat-induced stress downregulates hepatic CARF. In agreement with this, silencing and overexpressing CARF resulted in higher and lower fat accumulation in HepG2 cells, respectively. Furthermore, CARF overexpression lowered the ectopic palmitate accumulation in HepG2 cells. We were interested in understanding the role of hepatic CARF and underlying mechanisms in the development of NAFLD. Mechanistically, transcriptome analysis revealed that endoplasmic reticulum (ER) stress and oxidative stress pathway genes significantly altered in the absence of CARF. IRE1α, GRP78, and CHOP, markers of ER stress, were increased, and the treatment with TUDCA, an ER stress inhibitor, attenuated fat accumulation in CARF-deficient cells. Moreover, silencing CARF caused a reduction of GPX3 and TRXND3, leading to oxidative stress and apoptotic cell death. Intriguingly, CARF overexpression in HFD-fed mice significantly decreased hepatic steatosis. Furthermore, overexpression of CARF ameliorated the aberrant ER function and oxidative stress caused by fat accumulation. Our results further demonstrated that overexpression of CARF alleviates HFD-induced insulin resistance assessed with ITT and GTT assay. Altogether, we conclude that excess fat-induced reduction of CARF dysregulates ER functions and lipid metabolism leading to hepatic steatosis.

Published
2023

26. The Impact of Excluding Adverse Neonatal Outcomes on the Creation of Gestational Weight Gain Charts Among Women from Low- and Middle-income Countries with Normal and Overweight BMI

Author

Accrombessi, Manfred, Adu-Afarwuah, Seth, Alves, João Guilherme, Leal de Araújo, Carla Adriane, Arifeen, Shams, Artes, Rinaldo, Ashorn, Per, Ashorn, Ulla, Assefa, Nega, Ayoola, Omolola Olukemi, Azizi, Fereidoun, Bawah, Ahmed Tijani, Behboudi-Gandevani, Samira, Berhane, Yemane, Bernstein, Robin, Bhutta, Zulfiqar, Briand, Valérie, Calvo, Elvira Beatriz, Cardoso, Marly Augusto, Cheng, Yue, Chico-Barba, Gabriela, Clayton, Peter Ellis, Collins, Shalean M, Costello, Anthony M, Cruickshank, John Kennedy, Devakumar, Delanjathan, Dewey, Kathryn G, Dwarkanath, Pratibha, Estrada-Gutierrez, Guadalupe, Fair, Frankie J, Farias, Dayana Rodrigues, Friis, Henrik, Ghosh, Shibani, Girard, Amy Webb, Gomo, Exnevia, Gondwe, Austrida, Hallamaa, Lotta, Hambidge, K Michael, Hussein, Hawawu, Huybregts, Lieven, Iqbal, Romaina, Katz, Joanne, Khatry, Subarna K, Kolsteren, Patrick, Krebs, Nancy F, Kulmala, Teija, Kumar, Pratap, Kurpad, Anura V, Lachat, Carl, Lartey, Anna, Lauer, Jacqueline M, Li, Qian, Lipoeto, Nur Indrawaty, López, Laura Beatriz, Loy, See Ling, Maiya, G Arun, Maleta, Kenneth, Malta, Maíra Barreto, Manandhar, Dharma S, Mangani, Charles, Martínez-Rojano, Hugo, Martin-Prevel, Yves, Martorell, Reynaldo, Matias, Susana L, McClure, Elizabeth M, Melse-Boonstra, Alida, Miller, Joshua D, Mohamad, Marhazlina, Jan Mohamed, Hamid Jan, Moore, Sophie, Mosquera, Paola Soledad, Mridha, Malay Kanti, Munim, Shama, Muñoz-Manrique, Cinthya, Natamba, Barnabas K, Ome-Kaius, Maria, Osrin, David, Perichart-Perera, Otilia, Prentice, Andrew M, Ramachandra, Preetha, Ramakrishnan, Usha, Rivera, Juan, Roberfroid, Dominique, Rodrigues, Patricia Lima, Rodríguez-Cano, Ameyalli, Rogerson, Stephen J, Rondó, Patricia HC, Sámano, Reyna, Saville, Naomi M, Shivalli, Siddharudha, Shrestha, Bhim P, Shrestha, Robin, Roberto da Silva Júnior, José, Soltani, Hora, Soofi, Sajid, Tehrani, Fahimeh Ramezani, Thomas, Tinku, Tielsch, James M, Unger, Holger W, Vaz, Juliana dos Santos, Worku, Alemayehu, Yang, Nianhong, Young, Sera L, Yussif, Adam Bawa, Zeng, Lingxia, Zhong, Chunrong, Zhu, Zhonghai, Rangel Bousquet Carrilho, Thais, Wang, Dongqing, Hutcheon, Jennifer A, Wang, Molin, Fawzi, Wafaie W, and Kac, Gilberto

Published
2024
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37. Predicted impact of banning nonessential, energy-dense food and beverages in schools in Mexico: A microsimulation study

Author

Basto-Abreu, Ana, Carnalla, Martha, Reyes-Sánchez, Francisco, Reyes-García, Alan, Haby, Michelle M., Junquera-Badilla, Isabel, Sartoris-Ayala, Lianca, Rivera, Juan A., Popkin, Barry M., and Barrientos-Gutiérrez, Tonatiuh

Subjects
Mexico -- Health aspects -- Social aspects -- Economic aspects, Medical research, Medicine, Experimental, Beverages -- Social aspects -- Health aspects -- Economic aspects, School lunches -- Social aspects -- Health aspects -- Economic aspects, Junk food -- Social aspects -- Health aspects -- Economic aspects, School lunchrooms, cafeterias, etc. -- Social aspects -- Health aspects -- Economic aspects, Biological sciences
Abstract

Background Childhood obesity is a growing concern worldwide. School-based interventions have been proposed as effective means to improve nutritional knowledge and prevent obesity. In 2023, Mexico approved a reform to the General Education Law to strengthen the ban of sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools and surroundings. We aimed to predict the expected one-year change in total caloric intake and obesity prevalence by introducing the ban of NEDFBs sales in schools, among school-aged children and adolescents (6 to 17 years old) in Mexico. Methods and findings We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and then estimated total energy intake (TEI) per day. The TEI after the intervention was estimated under 4 scenarios: (1) using national data to inform the intervention effect; (2) varying law compliance; (3) using meta-analytic data to inform the intervention effect size on calories; and (4) using national data to inform the intervention effect by sex and socioeconomic status (SES). We used Hall's microsimulation model to estimate the potential impact on body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools. We found that children could reduce their daily energy intake by 33 kcal/day/person (uncertainty interval, UI, [25, 42] kcal/day/person), reducing on average 0.8 kg/person (UI [0.6, 1.0] kg/person) and 1.5 percentage points (pp) in obesity (UI [1.1, 1.9] pp) 1 year after implementing the law. We showed that compliance will be key to the success of this intervention: considering a 50% compliance the intervention effect could reduce 0.4 kg/person (UI [0.3, 0.5] kg/person). Our sensitivity analysis showed that the ban could reduce body weight by 1.3 kg/person (UI [0.8, 1.8] kg/person) and up to 5.4 kg/person (UI [3.4, 7.5] kg/person) in the best-case scenario. Study limitations include assuming that obesity and the contribution of NEDFBs consumed at school remain constant over time, assuming full compliance, and not considering the potential effect of banning NEDFBs in stores near schools. Conclusions Even in the most conservative scenario, banning sales of NEDFBs in schools is expected to significantly reduce obesity, but achieving high compliance will be key to its success. Why was this study done? - School-based interventions have been recognized as effective means to improve nutritional knowledge and prevent obesity-related diseases. - In December 2023, the Chamber of Representatives of Mexico approved an amendment that strengthens and updates the General Education Law (Article 75) and nutritional guidelines to ban the sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools. What did the researchers do and find? - We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and total energy intake (TEI) per day. - We used microsimulation modeling to predict body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools. - Our modeling study suggests that an important impact on obesity prevalence can be expected if the law is implemented and enforced as intended. What do these findings mean? - If successful, this law could serve as an example beyond Mexico on how to achieve changes in body weight through school food regulation. - An important limitation of our main scenario is that we assumed full compliance of schools with the law, yet lower compliance will reduce its impact. We also did not consider historical trends on obesity or NEDFBs consumed in schools during our 1 year simulation, and we considered only the ban impact inside schools, excluding effects near and outside schools., Author(s): Ana Basto-Abreu 1, Martha Carnalla 1, Francisco Reyes-Sánchez 1, Alan Reyes-García 1, Michelle M. Haby 2, Isabel Junquera-Badilla 1, Lianca Sartoris-Ayala 1, Juan A. Rivera 1, Barry M. Popkin [...]

Published
2024
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39. Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

Author

Phelps, Nowell H, Singleton, Rosie K, Zhou, Bin, Heap, Rachel A, Mishra, Anu, Bennett, James E, Paciorek, Christopher J, Lhoste, Victor PF, Carrillo-Larco, Rodrigo M, Stevens, Gretchen A, Rodriguez-Martinez, Andrea, Bixby, Honor, Bentham, James, Di Cesare, Mariachiara, Danaei, Goodarz, Rayner, Archie W, Barradas-Pires, Ana, Cowan, Melanie J, Savin, Stefan, Riley, Leanne M, Aguilar-Salinas, Carlos A, Baker, Jennifer L, Barkat, Amina, Bhutta, Zulfiqar A, Branca, Francesco, Caixeta, Roberta B, Cuschieri, Sarah, Farzadfar, Farshad, Ganapathy, Shubash, Ikeda, Nayu, Iotova, Violeta, Kengne, Andre P, Khang, Young-Ho, Laxmaiah, Avula, Lin, Hsien-Ho, Ma, Jun, Mbanya, Jean Claude N, Miranda, J Jaime, Pradeepa, Rajendra, Rodríguez-Artalejo, Fernando, Sorić, Maroje, Turley, Maria, Wang, Limin, Webster-Kerr, Karen, Aarestrup, Julie, Abarca-Gómez, Leandra, Abbasi-Kangevari, Mohsen, Abdeen, Ziad A, Abdrakhmanova, Shynar, Abdul Ghaffar, Suhaila, Abdul Rahim, Hanan F, Abdurrahmonova, Zulfiya, Abu-Rmeileh, Niveen M, Abubakar Garba, Jamila, Acosta-Cazares, Benjamin, Adam, Ishag, Adamczyk, Marzena, Adams, Robert J, Adu-Afarwuah, Seth, Aekplakorn, Wichai, Afsana, Kaosar, Afzal, Shoaib, Agbor, Valirie N, Agdeppa, Imelda A, Aghazadeh-Attari, Javad, Ågren, Åsa, Aguenaou, Hassan, Agyemang, Charles, Ahmad, Mohamad Hasnan, Ahmad, Noor Ani, Ahmadi, Ali, Ahmadi, Naser, Ahmadi, Nastaran, Ahmed, Imran, Ahmed, Soheir H, Ahrens, Wolfgang, Aitmurzaeva, Gulmira, Ajlouni, Kamel, Al-Hazzaa, Hazzaa M, Al-Hinai, Halima, Al-Lahou, Badreya, Al-Lawati, Jawad A, Al-Raddadi, Rajaa, Al Asfoor, Deena, Al Hourani, Huda M, Al Qaoud, Nawal M, Alarouj, Monira, AlBuhairan, Fadia, AlDhukair, Shahla, Aldwairji, Maryam A, Alexius, Sylvia, Ali, Mohamed M, Alieva, Anna V, Alkandari, Abdullah, Alkerwi, Ala'a, Alkhatib, Buthaina M, Allin, Kristine, Alomary, Shaker A, Alomirah, Husam F, Alshangiti, Arwa M, Alvarez-Pedrerol, Mar, Aly, Eman, Amarapurkar, Deepak N, Amiano Etxezarreta, Pilar, Amoah, John, Amougou, Norbert, Amouyel, Philippe, Andersen, Lars Bo, Anderssen, Sigmund A, Androutsos, Odysseas, Ängquist, Lars, Anjana, Ranjit Mohan, Ansari-Moghaddam, Alireza, Anufrieva, Elena, Aounallah-Skhiri, Hajer, Araújo, Joana, Ariansen, Inger, Aris, Tahir, Arku, Raphael E, Arlappa, Nimmathota, Aryal, Krishna K, Assefa, Nega, Aspelund, Thor, Assah, Felix K, Assembekov, Batyrbek, Assunção, Maria Cecília F, Aung, May Soe, Aurélio de Valois, Correia Júnior Marco, Auvinen, Juha, Avdičová, Mária, Avi, Shina, Azad, Kishwar, Azevedo, Ana, Azimi-Nezhad, Mohsen, Azizi, Fereidoun, Babu, Bontha V, Bacopoulou, Flora, Bæksgaard Jørgensen, Maja, Baharudin, Azli, Bahijri, Suhad, Bajramovic, Izet, Bakacs, Marta, Balakrishna, Nagalla, Balanova, Yulia, Bamoshmoosh, Mohamed, Banach, Maciej, Banegas, José R, Baran, Joanna, Baran, Rafał, Barbagallo, Carlo M, Barbosa Filho, Valter, Barceló, Alberto, Baretić, Maja, Barnoya, Joaquin, Barrera, Lena, Barreto, Marta, Barros, Aluisio JD, Barros, Mauro Virgílio Gomes, Bartosiewicz, Anna, Basit, Abdul, Bastos, Joao Luiz, Bata, Iqbal, Batieha, Anwar M, Batista, Aline P, Batista, Rosangela L, Battakova, Zhamilya, Baur, Louise A, Bayauli, Pascal M, Beaglehole, Robert, Bel-Serrat, Silvia, Belavendra, Antonisamy, Ben Romdhane, Habiba, Benedek, Theodora, Benedics, Judith, Benet, Mikhail, Benitez Rolandi, Gilda Estela, Benzeval, Michaela, Bere, Elling, Berger, Nicolas, Bergh, Ingunn Holden, Berhane, Yemane, Berkinbayev, Salim, Bernabe-Ortiz, Antonio, Bernotiene, Gailute, Berrios Carrasola, Ximena, Bettiol, Heloísa, Beutel, Manfred E, Beybey, Augustin F, Bezerra, Jorge, Bhagyalaxmi, Aroor, Bharadwaj, Sumit, Bhargava, Santosh K, Bi, Hongsheng, Bi, Yufang, Bia, Daniel, Biasch, Katia, Bika Lele, Elysée Claude, Bikbov, Mukharram M, Bista, Bihungum, Bjelica, Dusko J, Bjerregaard, Anne A, Bjerregaard, Peter, Bjertness, Espen, Bjertness, Marius B, Björkelund, Cecilia, Bloch, Katia V, Blokstra, Anneke, Blychfeld Magnazu, Moran, Bo, Simona, Bobak, Martin, Boddy, Lynne M, Boehm, Bernhard O, Boer, Jolanda MA, Boggia, Jose G, Bogova, Elena, Boissonnet, Carlos P, Bojesen, Stig E, Bonaccio, Marialaura, Bongard, Vanina, Bonilla-Vargas, Alice, Bopp, Matthias, Borghs, Herman, Botomba, Steve, Bourne, Rupert RA, Bovet, Pascal, Boymatova, Khadichamo, Braeckevelt, Lien, Braeckman, Lutgart, Bragt, Marjolijn CE, Braithwaite, Tasanee, Brajkovich, Imperia, Breckenkamp, Juergen, Breda, João, Brenner, Hermann, Brewster, Lizzy M, Brian, Garry R, Briceño, Yajaira, Brinduse, Lacramioara, Bringolf-Isler, Bettina, Brito, Miguel, Brophy, Sinead, Brug, Johannes, Bruno, Graziella, Bugge, Anna, Buoncristiano, Marta, Burazeri, Genc, Burns, Con, Cabrera de León, Antonio, Cacciottolo, Joseph, Cai, Hui, Cama, Tilema, Cameron, Christine, Camolas, José, Can, Günay, Cândido, Ana Paula c, Cañete, Felicia, Capanzana, Mario V, Čapková, Naděžda, Capuano, Eduardo, Capuano, Rocco, Capuano, Vincenzo, Cardol, Marloes, Cardoso, Viviane C, Carlsson, Axel C, Carmuega, Esteban, Carvalho, Joana, Casajús, José A, Casanueva, Felipe F, Casas, Maribel, Celikcan, Ertugrul, Censi, Laura, Cervantes-Loaiza, Marvin, Cesar, Juraci A, Chamnan, Parinya, Chamukuttan, Snehalatha, Chan, Angelique, Chan, Queenie, Charchar, Fadi J, Charles, Marie-Aline, Chaturvedi, Himanshu K, Chaturvedi, Nish, Che Abdul Rahim, Norsyamlina, Chee, Miao Li, Chen, Chien-Jen, Chen, Fangfang, Chen, Huashuai, Chen, Long-Sheng, Chen, Shuohua, Chen, Zhengming, Cheng, Ching-Yu, Cheng, Yiling J, Cheraghian, Bahman, Chetrit, Angela, Chikova-Iscener, Ekaterina, Chinapaw, Mai JM, Chinnock, Anne, Chiolero, Arnaud, Chiou, Shu-Ti, Chirita-Emandi, Adela, Chirlaque, María-Dolores, Cho, Belong, Christensen, Kaare, Christofaro, Diego G, Chudek, Jerzy, Cifkova, Renata, Cilia, Michelle, Cinteza, Eliza, Cirillo, Massimo, Claessens, Frank, Clare, Philip, Clarke, Janine, Clays, Els, Cohen, Emmanuel, Cojocaru, Cosmin R, Colorado-Yohar, Sandra, Compañ-Gabucio, Laura-María, Concin, Hans, Confortin, Susana C, Cooper, Cyrus, Coppinger, Tara C, Corpeleijn, Eva, Cortés, Lilia Yadira, Costanzo, Simona, Cottel, Dominique, Cowell, Chris, Craig, Cora L, Crampin, Amelia C, Cross, Amanda J, Crujeiras, Ana B, Cruz, Juan J, Csányi, Tamás, Csilla, Semánová, Cucu, Alexandra M, Cui, Liufu, Cureau, Felipe V, Czenczek-Lewandowska, Ewelina, D'Arrigo, Graziella, d'Orsi, Eleonora, da Silva, Alanna G, Dacica, Liliana, Dahm, Christina C, Dallongeville, Jean, Damasceno, Albertino, Damsgaard, Camilla T, Dankner, Rachel, Dantoft, Thomas M, Dasgupta, Parasmani, Dastgiri, Saeed, Dauchet, Luc, Davletov, Kairat, de Assis Guedes de Vasconcelos, Francisco, de Assis, Maria Alice Altenburg, De Backer, Guy, De Bacquer, Dirk, De Bacquer, Jaco, de Bont, Jeroen, De Curtis, Amalia, de Fragas Hinnig, Patrícia, de Gaetano, Giovanni, De Henauw, Stefaan, De Miguel-Etayo, Pilar, De Neve, Jan-Walter, Duarte de Oliveira, Paula, De Ridder, David, De Ridder, Karin, de Rooij, Susanne R, de Sá, Ana Carolina MGN, De Smedt, Delphine, Deepa, Mohan, Deev, 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Alireza, Safarpour, Ali Reza, Safi, Sare, Safiri, Saeid, Saghi, Mohammad Hossien, Saidi, Olfa, Saieva, Calogero, Sakata, Satoko, Saki, Nader, Šalaj, Sanja, Salanave, Benoit, Salazar Martinez, Eduardo, Salhanova, Akkumis, Salmerón, Diego, Salomaa, Veikko, Salonen, Jukka T, Salvetti, Massimo, Samoutian, Margarita, Sánchez-Abanto, Jose, Sánchez Rodríguez, Inés, Sandjaja, Sans, Susana, Santa-Marina, Loreto, Santacruz, Ethel, Santos, Diana A, Santos, Ina S, Santos, Lèlita C, Santos, Maria Paula, Santos, Osvaldo, Santos, Rute, Santos, Tamara R, Saramies, Jouko L, Sardinha, Luis B, Sarrafzadegan, Nizal, Sathish, Thirunavukkarasu, Saum, Kai-Uwe, Savva, Savvas, Savy, Mathilde, Sawada, Norie, Sbaraini, Mariana, Scazufca, Marcia, Schaan, Beatriz D, Schaffrath Rosario, Angelika, Schargrodsky, Herman, Schienkiewitz, Anja, Schindler, Karin, Schipf, Sabine, Schmidt, Börge, Schmidt, Carsten O, Schmidt, Ida Maria, Schneider, Andrea, Schnohr, Peter, Schöttker, Ben, Schramm, Sara, Schramm, Stine, Schröder, Helmut, Schultsz, Constance, Schultz, Gry, Schulze, Matthias B, Schutte, Aletta E, Sebert, Sylvain, Sedaghattalab, Moslem, Selamat, Rusidah, Sember, Vedrana, Sen, Abhijit, Senbanjo, Idowu O, Sepanlou, Sadaf G, Sequera, Guillermo, Serra-Majem, Luis, Servais, Jennifer, Ševčíková, Ľudmila, Sewpaul, Ronel, Shalnova, Svetlana, Shamah-Levy, Teresa, Shamshirgaran, Seyed Morteza, Shanthirani, Coimbatore Subramaniam, Sharafkhah, Maryam, Sharma, Sanjib K, Sharman, Almaz, Shaw, Jonathan E, Shayanrad, Amaneh, Shayesteh, Ali Akbar, Shengelia, Lela, Shi, Zumin, Shibuya, Kenji, Shimizu-Furusawa, Hana, Shimony, Tal, Shiri, Rahman, Shrestha, Namuna, Si-Ramlee, Khairil, Siani, Alfonso, Siantar, Rosalynn, Sibai, Abla M, Sidossis, Labros S, Silitrari, Natalia, Silva, Antonio M, Silva, Caroline Ramos de Moura, Silva, Diego Augusto Santos, Silva, Kelly Samara, Sim, Xueling, Simon, Mary, Simons, Judith, Simons, Leon A, Sjöberg, Agneta, Sjöström, Michael, Skoblina, Elena V, Skoblina, Natalia A, Slazhnyova, Tatyana, Slowikowska-Hilczer, Jolanta, Slusarczyk, Przemysław, Smeeth, Liam, So, Hung-Kwan, Soares, Fernanda Cunha, Sobek, Grzegorz, Sobngwi, Eugène, Sodemann, Morten, Söderberg, Stefan, Soekatri, Moesijanti YE, Soemantri, Agustinus, Sofat, Reecha, Solfrizzi, Vincenzo, Solovieva, Yuliya V, Somi, Mohammad Hossein, Sonestedt, Emily, Song, Yi, Soofi, Sajid, Sørensen, Thorkild IA, Sørgjerd, Elin P, Sossa Jérome, Charles, Soto-Rojas, Victoria E, Soumaré, Aïcha, Sousa-Poza, Alfonso, Sovic, Slavica, Sparboe-Nilsen, Bente, Sparrenberger, Karen, Spencer, Phoebe R, Spinelli, Angela, Spiroski, Igor, Staessen, Jan A, Stamm, Hanspeter, Stang, Andreas, Starc, Gregor, Staub, Kaspar, Stavreski, Bill, Steene-Johannessen, Jostein, Stehle, Peter, Stein, Aryeh D, Steinsbekk, Silje, Stergiou, George S, Stessman, Jochanan, Stevanović, Ranko, Stieber, Jutta, Stöckl, Doris, Stokwiszewski, Jakub, Stoyanova, Ekaterina, Stratton, Gareth, Stronks, Karien, Strufaldi, Maria Wany, Sturua, Lela, Suárez-Medina, Ramón, Suarez-Ortegón, Milton F, Suebsamran, Phalakorn, Sugiyama, Mindy, Suka, Machi, Sulo, Gerhard, Sun, Chien-An, Sun, Liang, Sund, Malin, Sundström, Johan, Sung, Yn-Tz, Sunyer, Jordi, Suriyawongpaisal, Paibul, Sweis, Nabil William G, Swinburn, Boyd A, Sy, Rody G, Sylva, René Charles, Szponar, Lucjan, Tabone, Lorraine, Tai, E Shyong, Takuro, Furusawa, Tambalis, Konstantinos D, Tammesoo, Mari-Liis, Tamosiunas, Abdonas, Tan, Eng Joo, Tang, Xun, Tanrygulyyeva, Maya, Tanser, Frank, Tao, Yong, Tarawneh, Mohammed Rasoul, Tarp, Jakob, Tarqui-Mamani, Carolina B, Taxová Braunerová, Radka, Taylor, Anne, Taylor, Julie, Tchibindat, Félicité, Te Velde, Saskia, Tebar, William R, Tell, Grethe S, Tello, Tania, Tessema, Masresha, Tham, Yih Chung, Thankappan, KR, Theobald, Holger, Theodoridis, Xenophon, Thomas, Nihal, Thorand, Barbara, Thrift, Amanda G, Tichá, Ľubica, Timmermans, Erik J, Tjandrarini, Dwi Hapsari, Tjonneland, Anne, Tolonen, Hanna K, Tolstrup, Janne S, Tomaszewski, Maciej, Topbas, Murat, Topór-Mądry, Roman, Torheim, Liv Elin, Tornaritis, Michael J, Torrent, Maties, Torres-Collado, Laura, Toselli, Stefania, Touloumi, Giota, Traissac, Pierre, Tran, Thi Tuyet-Hanh, Tremblay, Mark S, Triantafyllou, Areti, Trichopoulos, Dimitrios, Trichopoulou, Antonia, Trinh, Oanh TH, Trivedi, Atul, Tshepo, Lechaba, Tsigga, Maria, Tsintavis, Panagiotis, Tsugane, Shoichiro, Tuitele, John, Tuliakova, Azaliia M, Tulloch-Reid, Marshall K, Tullu, Fikru, Tuomainen, Tomi-Pekka, Tuomilehto, Jaakko, Twig, Gilad, Tynelius, Per, Tzala, Evangelia, Tzotzas, Themistoklis, Tzourio, Christophe, Udoji, Nwannedimma, Ueda, Peter, Ugel, Eunice, Ukoli, Flora AM, Ulmer, Hanno, Unal, Belgin, Usupova, Zhamyila, Uusitalo, Hannu MT, Uysal, Nalan, Vaitkeviciute, Justina, Valdivia, Gonzalo, Vale, Susana, Valvi, Damaskini, van Dam, Rob M, van den Born, Bert-Jan, Van der Heyden, Johan, van der Schouw, Yvonne T, Van Herck, Koen, Van Lippevelde, Wendy, Van Minh, Hoang, Van Schoor, Natasja M, van Valkengoed, Irene GM, Vanderschueren, Dirk, Vanuzzo, Diego, Varbo, Anette, Varela-Moreiras, Gregorio, Vargas, Luz Nayibe, Varona-Pérez, Patricia, Vasan, Senthil K, Vasques, Daniel G, Vatasescu, Radu, Vega, Tomas, Veidebaum, Toomas, Velasquez-Melendez, Gustavo, Velika, Biruta, Verloigne, Maïté, Veronesi, Giovanni, Verschuren, WM Monique, Victora, Cesar G, Viegi, Giovanni, Viet, Lucie, Vik, Frøydis N, Vilar, Monica, Villalpando, Salvador, Vioque, Jesus, Viriyautsahakul, Napaphan, Virtanen, Jyrki K, Visser, Marjolein, Visvikis-Siest, Sophie, Viswanathan, Bharathi, Vladulescu, Mihaela, Vlasoff, Tiina, Vocanec, Dorja, Vollenweider, Peter, Völzke, Henry, Vourli, Georgia, Voutilainen, Ari, Vrijheid, Martine, Vrijkotte, Tanja GM, Vuletić, Silvije, Wade, Alisha N, Waldhör, Thomas, Walton, Janette, Wambiya, Elvis OA, Wan Bebakar, Wan Mohamad, Wan Mohamud, Wan Nazaimoon, Wanderley Júnior, Rildo de Souza, Wang, Chongjian, Wang, Huijun, Wang, Ming-Dong, Wang, Ningli, Wang, Qian, Wang, Xiangjun, Wang, Ya Xing, Wang, Ying-Wei, Wannamethee, S Goya, Wareham, Nicholas, Wartha, Olivia, Weber, Adelheid, Wedderkopp, Niels, Weghuber, Daniel, Wei, Wenbin, Weres, Aneta, Werner, Bo, Westbury, Leo D, Whincup, Peter H, Wichstrøm, Lars, Wickramasinghe, Kremlin, Widhalm, Kurt, Widyahening, Indah S, Więcek, Andrzej, Wild, Philipp S, Wilks, Rainford J, Willeit, Johann, Willeit, Peter, Williams, Julianne, Wilsgaard, Tom, Wirth, James P, Wojtyniak, Bogdan, Woldeyohannes, Meseret, Wolf, Kathrin, Wong-McClure, Roy A, Wong, Andrew, Wong, Emily B, Wong, Jyh Eiin, Wong, Tien Yin, Woo, Jean, Woodward, Mark, Wu, Frederick C, Wu, Hon-Yen, Wu, Jianfeng, Wu, Li Juan, Wu, Shouling, Wyszyńska, Justyna, Xu, Haiquan, Xu, Liang, Yaacob, Nor Azwany, Yamborisut, Uruwan, Yan, Li, Yan, Weili, Yang, Ling, Yang, Xiaoguang, Yang, Yang, Yardim, Nazan, Yasuharu, Tabara, Yépez García, Martha, Yiallouros, Panayiotis K, Yngve, Agneta, Yoosefi, Moein, Yoshihara, Akihiro, Yotov, Yoto, You, Qi Sheng, You, San-Lin, Younger-Coleman, Novie O, Yu, Yu-Ling, Yu, Yunjiang, Yusof, Safiah Md, Yusoff, Ahmad Faudzi, Zaccagni, Luciana, Zafiropulos, Vassilis, Zainuddin, Ahmad A, Zakavi, Seyed Rasoul, Zamani, Farhad, Zambon, Sabina, Zampelas, Antonis, Zamrazilová, Hana, Zapata, Maria Elisa, Zargar, Abdul Hamid, Zaw, Ko Ko, Zayed, Ayman A, Zdrojewski, Tomasz, Żegleń, Magdalena, Zejglicova, Kristyna, Zeljkovic Vrkic, Tajana, Zeng, Yi, Zentai, Andrea, Zhang, Bing, Zhang, Luxia, Zhang, Zhen-Yu, Zhao, Dong, Zhao, Ming-Hui, Zhao, Wenhua, Zhecheva, Yanitsa V, Zhen, Shiqi, Zheng, Wei, Zheng, Yingfeng, Zholdin, Bekbolat, Zhou, Maigeng, Zhu, Dan, Zimmet, Paul, Zins, Marie, Zitt, Emanuel, Zocalo, Yanina, Zoghlami, Nada, Zuñiga Cisneros, Julio, Zuziak, Monika, and Ezzati, Majid

Published
2024
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41. Electronic Cigarette Use and the Risk of Cardiovascular Diseases

Author

Espinoza-Derout, Jorge, Shao, Xuesi M, Lao, Candice J, Hasan, Kamrul M, Rivera, Juan Carlos, Jordan, Maria C, Echeverria, Valentina, Roos, Kenneth P, Sinha-Hikim, Amiya P, and Friedman, Theodore C

Subjects
Paediatrics, Biomedical and Clinical Sciences, Cardiovascular, Tobacco, Electronic Nicotine Delivery Systems, Prevention, Tobacco Smoke and Health, Heart Disease, 2.1 Biological and endogenous factors, 2.2 Factors relating to the physical environment, Cancer, Good Health and Well Being, electronic cigarettes, nicotine, heart failure, cardiovascular disease, atherosclerosis, Cardiovascular medicine and haematology
Abstract

Electronic cigarettes or e-cigarettes are the most frequently used tobacco product among adolescents. Despite the widespread use of e-cigarettes and the known detrimental cardiac consequences of nicotine, the effects of e-cigarettes on the cardiovascular system are not well-known. Several in vitro and in vivo studies delineating the mechanisms of the impact of e-cigarettes on the cardiovascular system have been published. These include mechanisms associated with nicotine or other components of the aerosol or thermal degradation products of e-cigarettes. The increased hyperlipidemia, sympathetic dominance, endothelial dysfunction, DNA damage, and macrophage activation are prominent effects of e-cigarettes. Additionally, oxidative stress and inflammation are unifying mechanisms at many levels of the cardiovascular impairment induced by e-cigarette exposure. This review outlines the contribution of e-cigarettes in the development of cardiovascular diseases and their molecular underpinnings.

Published
2022

42. Spectral band selection for vegetation properties retrieval using Gaussian processes regression

Author

Verrelst, Jochem, Rivera, Juan Pablo, Gitelson, Anatoly, Delegido, Jesus, Moreno, José, and Camps-Valls, Gustau

Subjects
Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Applications
Abstract

With current and upcoming imaging spectrometers, automated band analysis techniques are needed to enable efficient identification of most informative bands to facilitate optimized processing of spectral data into estimates of biophysical variables. This paper introduces an automated spectral band analysis tool (BAT) based on Gaussian processes regression (GPR) for the spectral analysis of vegetation properties. The GPR-BAT procedure sequentially backwards removes the least contributing band in the regression model for a given variable until only one band is kept. GPR-BAT is implemented within the framework of the free ARTMO's MLRA (machine learning regression algorithms) toolbox, which is dedicated to the transforming of optical remote sensing images into biophysical products. GPR-BAT allows (1) to identify the most informative bands in relating spectral data to a biophysical variable, and (2) to find the least number of bands that preserve optimized accurate predictions. This study concludes that a wise band selection of hyperspectral data is strictly required for optimal vegetation properties mapping.

Published
2020
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43. Active Learning Methods for Efficient Hybrid Biophysical Variable Retrieval

Author

Verrelst, ochem, Dethier, Sara, Rivera, Juan Pablo, Muñoz-Marí, Jordi, Camps-Valls, Gustau, and Moreno, José

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Kernel-based machine learning regression algorithms (MLRAs) are potentially powerful methods for being implemented into operational biophysical variable retrieval schemes. However, they face difficulties in coping with large training datasets. With the increasing amount of optical remote sensing data made available for analysis and the possibility of using a large amount of simulated data from radiative transfer models (RTMs) to train kernel MLRAs, efficient data reduction techniques will need to be implemented. Active learning (AL) methods enable to select the most informative samples in a dataset. This letter introduces six AL methods for achieving optimized biophysical variable estimation with a manageable training dataset, and their implementation into a Matlab-based MLRA toolbox for semi-automatic use. The AL methods were analyzed on their efficiency of improving the estimation accuracy of leaf area index and chlorophyll content based on PROSAIL simulations. Each of the implemented methods outperformed random sampling, improving retrieval accuracy with lower sampling rates. Practically, AL methods open opportunities to feed advanced MLRAs with RTM-generated training data for development of operational retrieval models.

Published
2020
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44. Pickup and Delivery Vehicle Routing Problems in Bike Sharing Systems: A Review

Author

Palacio, Juan D., Rivera, Juan Carlos, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Figueroa-García, Juan Carlos, editor, Hernández, German, editor, Villa Ramirez, Jose Luis, editor, and Gaona García, Elvis Eduardo, editor

Published
2023
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50. Optimal Design of Multi-Layer Fog Collectors

Author

Azeem, Musaddaq, Guèrin, Adrien, Dumais, Thomas, Caminos, Luis, Goldstein, Raymond E., Pesci, Adriana I., Rivera, Juan de Dios, Torres, María Josefina, Wiener, Jakub, Campos, José Luis, and Dumais, Jacques

Subjects
Physics - Fluid Dynamics, Condensed Matter - Soft Condensed Matter, Physics - Applied Physics
Abstract

The growing concerns over desertification have spurred research into technologies aimed at acquiring water from non-traditional sources such as dew, fog, and water vapor. Some of the most promising developments have focused on improving designs to collect water from fog. However, the absence of a shared framework to predict, measure and compare the water collection efficiencies of new prototypes is becoming a major obstacle to progress in the field. We address this problem by providing a general theory to design efficient fog collectors as well as a concrete experimental protocol to furnish our theory with all the necessary parameters to quantify the effective water collection efficiency. We show in particular that multi-layer collectors are required for high fog collection efficiency and that all efficient designs are found within a narrow range of mesh porosity. We support our conclusions with measurements on simple multi-layer harp collectors., Comment: 33 pages, 8 figures (including supplemental material); in press at ACS Applied Materials & Interfaces

Published
2020

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