The capture and separation of carbon dioxide (CO2) has been the focus of a plethora of research in order to mitigate its emissions and contribute to global development. Given that CO2 is commonly found in natural gas streams, there have been efforts to seek more efficient materials to separate gaseous mixtures such as CO2/CH4. However, there are only a few reports regarding adsorption processes within pressurized systems. In the offshore scenario, natural gas streams still exhibit high moisture content, necessitating a greater understanding of processes in moist systems. In this article, a metal-organic framework synthesis based on zirconium (MOF-808) was carried out through a conventional solvothermal method and autoclave for the adsorption of CO2 and CH4 under different temperatures (45–65 °C) and pressures up to 100 bar. Furthermore, the adsorption of humid CO2 was evaluated using thermal analyses. The MOF-808 synthesized in autoclave showed a high surface area (1502 m2/g), a high capacity for CO2 adsorption at 50 bar and 45 °C and had a low selectivity to capture CH4 molecules. It also exhibited a fine stability after five cycles of CO2 adsorption and desorption at 50 bar and 45 °C − as confirmed by structural post-adsorption analyses while maintaining its adsorption capacity and crystallinity. Furthermore, it can be observed that the adsorption capacity increased in a humid environment, and that the adsorbent remained stable after adsorption cycles in the presence of moisture. Finally, it was possible to confirm the occurrence of physisorption processes through nuclear magnetic resonance (NMR) analyses, thus validating the choice of mild temperatures for regeneration and contributing to the reduction of energy consumption in processing plants.
Caregivers who interact with children at home can provide a critical, complementary perspective on a childs behaviour functioning. This research used a parent-administered measure of problem behaviours to study perceptions of child behaviours across home situations. We applied latent profile analysis to identify subgroups of children with common behavioural tendencies in a nationally representative sample (N = 709) of 4- to 13-year-old children in Trinidad and Tobago. This study (a) identified latent profiles of childrens over- and underactive behaviour problems in varied home settings and (b) examined how profile membership predicted academic skills and teacher-observed problem behaviours. The best-fitting four-profile model included one profile of adjusted behaviours (56%), one of the elevated attention-seeking behaviours (21%), a profile featuring withdrawn and disengaged behaviours (15%) and a relatively rare profile emphasising aggressive behaviours (8%). Children classified in the last profile displayed the poorest academic outcomes and the highest levels of teacher-observed behaviour problems.
We introduce five novel types of Monte Carlo (MC) moves that brings the number of moves of ensemble MC calculations from three to eight. So far such calculations have relied on affine invariant stretch moves that were originally introduced by Christen (2007) [8], walk moves by Goodman and Weare (2010) [16] and quadratic moves by Militzer (2023) [31,32]. Ensemble MC methods have been very popular because they harness information about the fitness landscape from a population of walkers rather than relying on expert knowledge. Here we modified the affine method and employed a simplex of points to set the stretch direction. We adopt the simplex concept to quadratic moves. We also generalize quadratic moves to arbitrary order. Finally, we introduce directed moves that employ the values of the probability density while all other types of moves rely solely on the location of the walkers. We apply all algorithms to the Rosenbrock density in 2 and 20 dimensions and to the ring potential in 12 and 24 dimensions. We evaluate their efficiency by comparing error bars, autocorrelation time, travel time, and the level of cohesion that measures whether any walkers were left behind. Our code is open source.
It is well known that people will exert effort on a task if sufficiently motivated, but how they distribute these efforts across different strategies (e.g., efficiency vs. caution) remains uncertain. Past work has shown that people invest effort differently for potential positive outcomes (rewards) versus potential negative outcomes (penalties). However, this research failed to account for differences in the context in which negative outcomes motivate someone - either as punishment or reinforcement. It is therefore unclear whether effort profiles differ as a function of outcome valence, motivational context, or both. Using computational modeling and our novel Multi-Incentive Control Task, we show that the influence of aversive outcomes on one's effort profile is entirely determined by their motivational context. Participants (N:91) favored increased caution in response to larger penalties for incorrect responses, and favored increased efficiency in response to larger reinforcement for correct responses, whether positively or negatively incentivized. STATEMENT OF RELEVANCE: People have to constantly decide how to allocate their mental effort, and in doing so can be motivated by both the positive outcomes that effort accrues and the negative outcomes that effort avoids. For example, someone might persist on a project for work in the hopes of being promoted or to avoid being reprimanded or even fired. Understanding how people weigh these different types of incentives is critical for understanding variability in human achievement as well as sources of motivational impairments (e.g., in major depression). We show that people not only consider both potential positive and negative outcomes when allocating mental effort, but that the profile of effort they engage under negative incentives differs depending on whether that outcome is contingent on sustaining good performance (negative reinforcement) or avoiding bad performance (punishment). Clarifying the motivational factors that determine effort exertion is an important step for understanding motivational impairments in psychopathology.
Spirulina is the common name for the edible, nonheterocystous, filamentous cyanobacterium Arthrospira platensis that is grown industrially as a food supplement, animal feedstock, and pigment source. Although there are many applications for engineering this organism, until recently no genetic tools or reproducible transformation methods have been published. While recent work showed the production of a diversity of proteins in A. platensis, including single-domain antibodies for oral delivery, there remains a need for a modular, characterized genetic toolkit. Here, we independently establish a reproducible method for the transformation of A. platensis and engineer this bacterium to produce acetaminophen as proof-of-concept for small molecule production in an edible host. This work opens A. platensis to the wider scientific community for future engineering as a functional food for nutritional enhancement, modification of organoleptic traits, and production of pharmaceuticals for oral delivery.
Gender norms have been posited to impact intimate partner violence (IPV), but there is scant evidence of the longitudinal association between community-level gender norms and IPV. Using longitudinal data on 3,965 married girls surveyed in India, we fitted mixed-effects ordinal and binary logistic regression models for physical IPV intensity and occurrence of sexual IPV. We found a 26% increase in the odds that women experience frequent physical IPV per one unit increase in greater community-level equitable gender norms. We did not find an association between community-level equitable gender norms and sexual IPV. Findings suggest that the relationship between gender norms and physical and sexual IPV differs, indicating the need for tailored interventions for different types of IPV.
Learning structures that effectively abstract decision policies is key to the flexibility of human intelligence. Previous work has shown that humans use hierarchically structured policies to efficiently navigate complex and dynamic environments. However, the computational processes that support the learning and construction of such policies remain insufficiently understood. To address this question, we tested 1026 human participants, who made over 1 million choices combined, in a decision-making task where they could learn, transfer, and recompose multiple sets of hierarchical policies. We propose a novel algorithmic account for the learning processes underlying observed human behavior. We show that humans rely on compressed policies over states in early learning, which gradually unfold into hierarchical representations via meta-learning and Bayesian inference. Our modeling evidence suggests that these hierarchical policies are structured in a temporally backward, rather than forward, fashion. Taken together, these algorithmic architectures characterize how the interplay between reinforcement learning, policy compression, meta-learning, and working memory supports structured decision-making and compositionality in a resource-rational way.
Insulin is an important regulator of whole-body glucose homeostasis. In insulin sensitive tissues such as muscle and adipose, insulin induces the translocation of glucose transporter 4 (GLUT4) to the cell membrane, thereby increasing glucose uptake. However, insulin also signals in tissues that are not generally associated with glucose homeostasis. In the human reproductive endocrine axis, hyperinsulinemia suppresses the secretion of gonadotropins from gonadotrope cells of the anterior pituitary, thereby linking insulin dysregulation to suboptimal reproductive health. In the mouse, gonadotropes express the insulin receptor which has the canonical signaling response of IRS, AKT, and mTOR activation. However, the functional outcomes of insulin action on gonadotropes are unclear. Here, we demonstrate through use of an optimized cell fractionation protocol that insulin stimulation of the LβT2 gonadotropic cell line results in the unexpected translocation of GLUT1 to the plasma membrane. Using our high purity fractionation protocol, we further demonstrate that though Akt signaling in response to insulin is intact, insulin-induced translocation of GLUT1 occurs independently of Akt activation in LβT2 cells.
