Project description:Many everyday life decisions require allocating finite resources, such as attention or time, to examine multiple available options, like choosing a food supplier online. In cases like these, resources can be spread across many options (breadth) or focused on a few of them (depth). Whilst theoretical work has described how finite resources should be allocated to maximize utility in these problems, evidence about how humans balance breadth and depth is currently lacking. We introduce a novel experimental paradigm where humans make a many-alternative decision under finite resources. In an imaginary scenario, participants allocate a finite budget to sample amongst multiple apricot suppliers in order to estimate the quality of their fruits, and ultimately choose the best one. We found that at low budget capacity participants sample as many suppliers as possible, and thus prefer breadth, whereas at high capacities participants sample just a few chosen alternatives in depth, and intentionally ignore the rest. The number of alternatives sampled increases with capacity following a power law with an exponent close to 3/4. In richer environments, where good outcomes are more likely, humans further favour depth. Participants deviate from optimality and tend to allocate capacity amongst the selected alternatives more homogeneously than it would be optimal, but the impact on the outcome is small. Overall, our results undercover a rich phenomenology of close-to-optimal behaviour and biases in complex choices.
Project description:The AMP-activated protein kinase (AMPK) is a sensor of cellular energy status that regulates cellular and whole-body energy balance. A recently reported crystal structure has illuminated the complex regulatory mechanisms by which AMP and ADP cause activation of AMPK, involving phosphorylation by the upstream kinase LKB1. Once activated by falling cellular energy status, AMPK activates catabolic pathways that generate ATP whilst inhibiting anabolic pathways and other cellular processes that consume ATP. A role of AMPK is implicated in many human diseases. Mutations in the γ2 subunit cause heart disease due to excessive glycogen storage in cardiac myocytes, leading to ventricular pre-excitation. AMPK-activating drugs reverse many of the metabolic defects associated with insulin resistance, and recent findings suggest that the insulin-sensitizing effects of the widely used antidiabetic drug metformin are mediated by AMPK. The upstream kinase LKB1 is a tumour suppressor, and AMPK may exert many of its antitumour effects. AMPK activation promotes the oxidative metabolism typical of quiescent cells, rather than the aerobic glycolysis observed in tumour cells and cells involved in inflammation, explaining in part why AMPK activators have both antitumour and anti-inflammatory effects. Salicylate (the major in vivo metabolite of aspirin) activates AMPK, and this could be responsible for at least some of the anticancer and anti-inflammatory effects of aspirin. In addition to metformin and salicylates, novel drugs that modulate AMPK are likely to enter clinical trials soon. Finally, AMPK may be involved in viral infection: downregulation of AMPK during hepatitis C virus infection appears to be essential for efficient viral replication.
Project description:When a fluid-immersed array of supported plates or pillars is dried, evaporation leads to the formation of menisci on the tips of the plates or pillars that bring them together to form complex patterns. Building on prior experimental observations, we use a combination of theory and computation to understand the nature of this instability and its evolution in both the two- and three-dimensional setting of the problem. For the case of plates, we explicitly derive the interaction torques based on the relevant physical parameters associated with pillar deformation, contact-line pinning/depinning and fluid volume changes. A Bloch-wave analysis for our periodic mechanical system captures the window of volumes where the two-plate eigenvalue characterizes the onset of the coalescence instability. We then study the evolution of these binary clusters and their eventual elastic arrest using numerical simulations that account for evaporative dynamics coupled to capillary coalescence. This explains both the formation of hierarchical clusters and the sensitive dependence of the final structures on initial perturbations, as seen in our experiments. We then generalize our analysis to treat the problem of pillar collapse in three dimensions, where the fluid domain is completely connected and the interface is a minimal surface with the uniform mean curvature. Our theory and simulations capture the salient features of experimental observations in a range of different situations and may thus be useful in controlling the ensuing patterns.
Project description:Sustainability of global fisheries is a growing concern. The United Nations has identified three pillars of sustainability: economic development, social development, and environmental protection. The fisheries literature suggests that there are two key trade-offs among these pillars of sustainability. First, poor ecological health of a fishery reduces economic profits for fishers, and second, economic profitability of individual fishers undermines the social objectives of fishing communities. Although recent research has shown that management can reconcile ecological and economic objectives, there are lingering concerns about achieving positive social outcomes. We examined trade-offs among the three pillars of sustainability by analyzing the Fishery Performance Indicators, a unique dataset that scores 121 distinct fishery systems worldwide on 68 metrics categorized by social, economic, or ecological outcomes. For each of the 121 fishery systems, we averaged the outcome measures to create overall scores for economic, ecological, and social performance. We analyzed the scores and found that they were positively associated in the full sample. We divided the data into subsamples that correspond to fisheries management systems with three categories of access-open access, access rights, and harvest rights-and performed a similar analysis. Our results show that economic, social, and ecological objectives are at worst independent and are mutually reinforcing in both types of managed fisheries. The implication is that rights-based management systems should not be rejected on the basis of potentially negative social outcomes; instead, social considerations should be addressed in the design of these systems.
Project description:While CCSD(T) is often considered the "gold standard" of computational chemistry, the scaling of its computational cost as N7 limits its applicability for large and complex molecular systems. In this work, we apply the density-based many-body expansion [ Int. J. Quantum Chem. 2020, 120, e26228] in combination with CCSD(T). The accuracy of this approach is assessed for neutral, protonated, and deprotonated water hexamers, as well as (H2O)16 and (H2O)17 clusters. For the neutral water clusters, we find that already with a density-based two-body expansion, we are able to approximate the supermolecular CCSD(T) energies within chemical accuracy (4 kJ/mol). This surpasses the accuracy that is achieved with a conventional, energy-based three-body expansion. We show that this accuracy can be maintained even when approximating the electron densities using Hartree-Fock instead of using coupled-cluster densities. The density-based many-body expansion thus offers a simple, resource-efficient, and highly parallelizable approach that makes CCSD(T)-quality calculations feasible where they would otherwise be prohibitively expensive.
Project description:Programming language identification (PLI) is a common need in automatic program comprehension as well as a prerequisite for deeper forms of code understanding. Image-based approaches to PLI have recently emerged and are appealing due to their applicability to code screenshots and programming video tutorials. However, they remain limited to the recognition of a small amount of programming languages (up to 10 languages in the literature). We show that it is possible to perform image-based PLI on a large number of programming languages (up to 149 in our experiments) with high (92%) precision and recall, using convolutional neural networks (CNNs) and transfer learning, starting from readily-available pretrained CNNs. Results were obtained on a large real-world dataset of 300,000 code snippets extracted from popular GitHub repositories. By scrambling specific character classes and comparing identification performances we also show that the characters that contribute the most to the visual recognizability of programming languages are symbols (e.g., punctuation, mathematical operators and parentheses), followed by alphabetic characters, with digits and indentation having a negligible impact.
Project description:In recent years, researchers have taken the many-objective optimization algorithm, which can optimize 5, 8, 10, 15, 20 objective functions simultaneously, as a new research topic. However, the current research on many-objective optimization technology also encounters some challenges. For example: Pareto resistance phenomenon, difficult diversity maintenance. Based on the above problems, this paper proposes a many-objective evolutionary algorithm based on three states (MOEA/TS). Firstly, a feature extraction operator is proposed. It can extract the features of the high-quality solution set, and then assist the evolution of the current individual. Secondly, based on Pareto front layer, the concept of "individual importance degree" is proposed. The importance degree of an individual can reflect the importance of the individual in the same Pareto front layer, so as to further distinguish the advantages and disadvantages of different individuals in the same front layer. Then, a repulsion field method is proposed. The diversity of the population in the objective space is maintained by the repulsion field, so that the population can be evenly distributed on the real Pareto front. Finally, a new concurrent algorithm framework is designed. In the algorithm framework, the algorithm is divided into three states, and each state focuses on a specific task. The population can switch freely among these three states according to its own evolution. The MOEA/TS algorithm is compared with 7 advanced many-objective optimization algorithms. The experimental results show that the MOEA/TS algorithm is more competitive in many-objective optimization problems.
Project description:Classical antiviral therapy inhibit viral proteins and are subject to resistance. To counteract this emergence, alternative strategy has been developed that target cellular factors. We hypothesized that such approach could also be useful to identify broad antivirals. Influenza A virus was used as a model for viral diversity and need for therapy against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection with different influenza A virus subtypes which could help to identify potential antiviral drugs with broad spectrum. Cellular gene expression response to infection with five different human and avian influenza viruses strains was analyzed and 300 genes were determined as differentially expressed between infected and non-infected samples. Strikingly, only a few genes were induced by infection and related to immune response. A more concise list was used to screen connectivity map, a database of drug-associated gene expression profiles, for molecules with inverse profiles than the signature of infection. We hypothesized that such compounds would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified, and six inhibited influenza viral growth in vitro. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five of the eight identified molecules, demonstrating that this strategy could help to identify broad spectrum antivirals. This is the first study showing that a gene expression based-screening can be used to identify antivirals. Such approaches could accelerate the drug discovery progress and could be extended to other pathogens. A549 (human lung epithelial cells) were infected with 5 different influenza A strains (A/New Caledonia/20/99 (H1N1), A/Moscow/10/99 (H3N2), A/Lyon/969/09 (H1N1 SOI-V), A/Turkey/582/2006 (H5N1), A/Finch/England/2051/94 (H5N2), and A/Chicken/Italy/2076/99 (H7N1)) or mock infected. Five independant replicates were done and hybridized on a different microarray. The overall design is thus composed of 5 mock samples, and 5x5 infected samples.
Project description:We demonstrate the importance of addressing the Γ vertex and thus going beyond the GW approximation for achieving the energy levels of liquid water in many-body perturbation theory. In particular, we consider an effective vertex function in both the polarizability and the self-energy, which does not produce any computational overhead compared with the GW approximation. We yield the band gap, the ionization potential, and the electron affinity in good agreement with experiment and with a hybrid functional description. The achieved electronic structure and dielectric screening further lead to a good description of the optical absorption spectrum, as obtained through the solution of the Bethe-Salpeter equation. In particular, the experimental peak position of the exciton is accurately reproduced.