On the interaction between Autonomous Mobility-on-Demand systems and the power network: models and coordination algorithms

We study the interaction between a fleet of electric, self-driving vehicles servicing on-demand transportation requests (referred to as Autonomous Mobility-on-Demand, or AMoD, system) and the electric power network. We propose a model that captures the coupling between the two systems stemming from the vehicles' charging requirements and captures time-varying customer demand and power generation costs, road congestion, battery depreciation, and power transmission and distribution constraints. We then leverage the model to jointly optimize the operation of both systems. We devise an algorithmic procedure to losslessly reduce the problem size by bundling customer requests, allowing it to be efficiently solved by off-the-shelf linear programming solvers. Next, we show that the socially optimal solution to the joint problem can be enforced as a general equilibrium, and we provide a dual decomposition algorithm that allows self-interested agents to compute the market clearing prices without sharing private information. We assess the performance of the mode by studying a hypothetical AMoD system in Dallas-Fort Worth and its impact on the Texas power network. Lack of coordination between the AMoD system and the power network can cause a 4.4% increase in the price of electricity in Dallas-Fort Worth; conversely, coordination between the AMoD system and the power network could reduce electricity expenditure compared to the case where no cars are present (despite the increased demand for electricity) and yield savings of up $147M/year. Finally, we provide a receding-horizon implementation and assess its performance with agent-based simulations. Collectively, the results of this paper provide a first-of-a-kind characterization of the interaction between electric-powered AMoD systems and the power network, and shed additional light on the economic and societal value of AMoD.Comment: Extended version of the paper presented at Robotics: Science and Systems XIV, in prep. for journal submission. In V3, we add a proof that the socially-optimal solution can be enforced as a general equilibrium, a privacy-preserving distributed optimization algorithm, a description of the receding-horizon implementation and additional numerical results, and proofs of all theorem

Tropical river suspended sediment and solute dynamics in storms during an extreme drought

Droughts, which can strongly affect both hydrologic and biogeochemical systems, are projected to become more prevalent in the tropics in the future. We assessed the effects of an extreme drought during 2015 on stream water composition in the Luquillo Mountains of Puerto Rico. We demonstrated that drought base flow in the months leading up to the study was sourced from trade-wind orographic rainfall, suggesting a resistance to the effects of an otherwise extreme drought. In two catchments (Mameyes and Icacos), we sampled a series of four rewetting events that partially alleviated the drought. We collected and analyzed dissolved constituents (major cations and anions, organic carbon, and nitrogen) and suspended sediment (inorganic and organic matter (particulate organic carbon and particulate nitrogen)). The rivers appeared to be resistant to extreme drought, recovering quickly upon rewetting, as (1) the concentration-discharge (C-Q) relationships deviated little from the long-term patterns; (2) “new water” dominated streamflow during the latter events; (3) suspended sediment sources had accumulated in the channel during the drought flushed out during the initial events; and (4) the severity of the drought, as measured by the US drought monitor, was reduced dramatically after the rewetting events. Through this interdisciplinary study, we were able to investigate the impact of extreme drought through rewetting events on the river biogeochemistry

Effect of high parity on occurrence of anemia in pregnancy: a cohort study

<p>Abstract</p> <p>Background</p> <p>Studies that explore the controversial association between parity and anaemia-in-pregnancy (AIP) were often hampered by not distinguishing incident cases caused by pregnancy from prevalent cases complicated by pregnancy. The authors' aim in conducting this study was to overcome this methodological concern.</p> <p>Methods</p> <p>A retrospective cohort study was conducted in Oman on 1939 pregnancies among 479 parous female participants with available pregnancy records in a community trial. We collected information from participants, the community trial, and health records of each pregnancy. Throughout the follow-up period, we enumerated 684 AIP cases of which 289 (42.2%) were incident cases. High parity (HP, ≥ 5 pregnancies) accounted for 48.7% of total pregnancies. Two sets of regression analyses were conducted: the first restricted to incident cases only, and the second inclusive of all cases. The relation with parity as a dichotomy and as multiple categories was examined for each set; multi-level logistic regression (MLLR) was employed to produce adjusted models.</p> <p>Results</p> <p>In the fully adjusted MLLR models that were restricted to incident cases, women with HP pregnancies had a higher risk of AIP compared to those who had had fewer pregnancies (Risk Ratio, RR = 2.92; 95% CI 2.02, 4.59); the AIP risk increased in a dose-response fashion over multiple categories of parity. In the fully adjusted MLLR models that included all cases, the association disappeared (RR = 1.11; 95% CI 0.91, 1.18) and the dose-response pattern flattened.</p> <p>Conclusions</p> <p>This study shows the importance of specifying which cases of AIP are incident and provides supportive evidence for a causal relation between parity and occurrence of incidental AIP.</p

Distinct DNA Methylation Patterns of Subependymal Giant Cell Astrocytomas in Tuberous Sclerosis Complex

Tuberous sclerosis complex (TSC) is a monogenic disorder caused by mutations in either the TSC1 or TSC2 gene, two key regulators of the mechanistic target of the rapamycin complex pathway. Phenotypically, this leads to growth and formation of hamartomas in several organs, including the brain. Subependymal giant cell astrocytomas (SEGAs) are low-grade brain tumors commonly associated with TSC. Recently, gene expression studies provided evidence that the immune system, the MAPK pathway and extracellular matrix organization play an important role in SEGA development. However, the precise mechanisms behind the gene expression changes in SEGA are still largely unknown, providing a potential role for DNA methylation. We investigated the methylation profile of SEGAs using the Illumina Infinium HumanMethylation450 BeadChip (SEGAs n = 42, periventricular control n = 8). The SEGA methylation profile was enriched for the adaptive immune system, T cell activation, leukocyte mediated immunity, extracellular structure organization and the ERK1 & ERK2 cascade. More interestingly, we identified two subgroups in the SEGA methylation data and show that the differentially expressed genes between the two subgroups are related to the MAPK cascade and adaptive immune response. Overall, this study shows that the immune system, the MAPK pathway and extracellular matrix organization are also affected on DNA methylation level, suggesting that therapeutic intervention on DNA level could be useful for these specific pathways in SEGA. Moreover, we identified two subgroups in SEGA that seem to be driven by changes in the adaptive immune response and MAPK pathway and could potentially hold predictive information on target treatment response

The coding and non-coding transcriptional landscape of subependymal giant cell astrocytomas

Tuberous sclerosis complex (TSC) is an autosomal dominantly inherited neurocutaneous disorder caused by inactivating mutations in TSC1 or TSC2, key regulators of the mechanistic target of rapamycin complex 1 (mTORC1) pathway. In the CNS, TSC is characterized by cortical tubers, subependymal nodules and subependymal giant cell astrocytomas (SEGAs). SEGAs may lead to impaired circulation of CSF resulting in hydrocephalus and raised intracranial pressure in patients with TSC. Currently, surgical resection and mTORC1 inhibitors are the recommended treatment options for patients with SEGA. In the present study, high-throughput RNA-sequencing (SEGAs n = 19, periventricular control n = 8) was used in combination with computational approaches to unravel the complexity of SEGA development. We identified 9400 mRNAs and 94 microRNAs differentially expressed in SEGAs compared to control tissue. The SEGA transcriptome profile was enriched for the mitogen-activated protein kinase (MAPK) pathway, a major regulator of cell proliferation and survival. Analysis at the protein level confirmed that extracellular signal-regulated kinase (ERK) is activated in SEGAs. Subsequently, the inhibition of ERK independently of mTORC1 blockade decreased efficiently the proliferation of primary patient-derived SEGA cultures. Furthermore, we found that LAMTOR1, LAMTOR2, LAMTOR3, LAMTOR4 and LAMTOR5 were overexpressed at both gene and protein levels in SEGA compared to control tissue. Taken together LAMTOR1-5 can form a complex, known as the 'Ragulator' complex, which is known to activate both mTORC1 and MAPK/ERK pathways. Overall, this study shows that the MAPK/ERK pathway could be used as a target for treatment independent of, or in combination with mTORC1 inhibitors for TSC patients. Moreover, our study provides initial evidence of a possible link between the constitutive activated mTORC1 pathway and a secondary driver pathway of tumour growth

Outcome of Epilepsy Surgery in MRI-Negative Patients Without Histopathologic Abnormalities in the Resected Tissue

BACKGROUND AND OBJECTIVE: Patients with presumed nonlesional focal epilepsy-based on either MRI or histopathologic findings-have a lower success rate of epilepsy surgery compared with lesional patients. In this study, we aimed to characterize a large group of patients with focal epilepsy who underwent epilepsy surgery despite a normal MRI and had no lesion on histopathology. Determinants of their postoperative seizure outcomes were further studied. METHODS: We designed an observational multicenter cohort study of MRI-negative and histopathology-negative patients who were derived from the European Epilepsy Brain Bank and underwent epilepsy surgery between 2000 and 2012 in 34 epilepsy surgery centers within Europe. We collected data on clinical characteristics, presurgical assessment, including genetic testing, surgery characteristics, postoperative outcome, and treatment regimen. RESULTS: Of the 217 included patients, 40% were seizure-free (Engel I) 2 years after surgery and one-third of patients remained seizure-free after 5 years. Temporal lobe surgery (adjusted odds ratio [AOR]: 2.62; 95% CI 1.19-5.76), shorter epilepsy duration (AOR for duration: 0.94; 95% CI 0.89-0.99), and completely normal histopathologic findings-versus nonspecific reactive gliosis-(AOR: 4.69; 95% CI 1.79-11.27) were significantly associated with favorable seizure outcome at 2 years after surgery. Of patients who underwent invasive monitoring, only 35% reached seizure freedom at 2 years. Patients with parietal lobe resections had lowest seizure freedom rates (12.5%). Among temporal lobe surgery patients, there was a trend toward favorable outcome if hippocampectomy was part of the resection strategy (OR: 2.94; 95% CI 0.98-8.80). Genetic testing was only sporadically performed. DISCUSSION: This study shows that seizure freedom can be reached in 40% of nonlesional patients with both normal MRI and histopathology findings. In particular, nonlesional temporal lobe epilepsy should be regarded as a relatively favorable group, with almost half of patients achieving seizure freedom at 2 years after surgery-even more if the hippocampus is resected-compared with only 1 in 5 nonlesional patients who underwent extratemporal surgery. Patients with an electroclinically identified focus, who are nonlesional, will be a promising group for advanced molecular-genetic analysis of brain tissue specimens to identify new brain somatic epilepsy genes or epilepsy-associated molecular pathways

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570