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.
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.
Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two.
The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.
Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5 tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of 1.5 × 10−46 cm2 at a 90% confidence level for a WIMP mass of 33 GeV/c2 for this interaction.
Infectious diseases exploit niches that are often spatially defined as urban and/or rural. Yet spatial research on infectious diseases often fails to define "urban" and "rural" and how these contexts might influence their epidemiology. We use dengue fever, thought to be mostly an urban disease with rural foci, as a device to explore local definitions of urban and rural spaces and the impact of these spaces on dengue risk in the provinfine urban and rural locales. Interviews conducted from 2019 to 2021 with 71 residents and 23 health personce of Esmeraldas, Ecuador. Ecuador, like many countries, only uses population size and administrative function to denel found that they identified the availability of basic services, extent of their control over their environment, and presence of underbrush and weeds (known in Ecuador as monte and maleza and conceptualized in this paper as natural disorder) as important links to their conceptions of space and dengue risk. This broader conceptualization of space articulated by local residents and professionals reflects a more sophisticated approach to characterizing dengue risk than using categories of urban and rural employed by the national census and government. Rather than this dichotomous category of space, dengue fever can be better framed for health interventions in terms of specific environmental features and assemblages of high-risk spaces. An understanding of how community members perceive risk enhances our ability to collaborate with them to develop optimal mitigation strategies.
The Cs2LiYCl6:Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6Li(n,α) and 35Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252Cf source, an array of EJ-309 organic liquid scintillators, and a 6Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.
