Preferences and Beliefs in a Sequential Social Dilemma: A Within-Subjects Analysis

Within-subject data from sequential social dilemma experiments reveal a correlation of first-and second-mover decisions for which two channels may be responsible, that our experiment allows to separate: i) a direct, preference-based channel that influences both first- and second-mover decisions; ii) an indirect channel, where second-mover decisions influence beliefs via a consensus effect, and the first-mover decision is a best response to these beliefs. We find strong evidence for the indirect channel: beliefs about second-mover cooperation are biased toward own second-mover behavior, and most subjects best respond to stated beliefs. But when first movers know the true probability of second-mover cooperation, subjects' own second moves still have predictive power regarding their first moves, suggesting that the direct channel also plays a role.experimental economics, consensus effect, social dilemmas

Capture of CO2 from Steam Reformer Flue Gases Using Monoethanolamine: Pilot Plant Validation and Process Design for Partial Capture

Carbon dioxide (CO2) capture from a slipstream of steam reformer flue gas (18–20 vol %wet CO2) using 30 wt % aqueous monoethanolamine was performed for ∼500 h in a mobile test unit (∼120 kg CO2/h). Specific reboiler duties (SRDs) of 3.6–3.8 MJ/kg CO2 were achieved at 90% capture. The pilot data validate the modeling of off-design partial capture, that is, operation at lower CO2 capture rates (at constant gas flow) than the absorption column was designed to achieve. This paper demonstrates that off-design partial capture enables significant energy savings (SRD, cooling) relative to on-design capture. The accrued savings depend on the column design (packing height, flooding approach) and the feed CO2 concentration. Finally, a concept for stepwise deployment of carbon capture and storage in industries with high-CO2 concentration sources (e.g., steel and cement manufacturing and refining) is introduced. Thanks to its inherent full-capture-ready design, the initial energy-efficient, off-design partial capture operation can be extended to full capture over time

Dynamic-ADAPT-QAOA: An algorithm with shallow and noise-resilient circuits

The quantum approximate optimization algorithm (QAOA) is an appealing proposal to solve NP problems on noisy intermediate-scale quantum (NISQ) hardware. Making NISQ implementations of the QAOA resilient to noise requires short ansatz circuits with as few CNOT gates as possible. Here, we present Dynamic-ADAPT-QAOA. Our algorithm significantly reduces the circuit depth and the CNOT count of standard ADAPT-QAOA, a leading proposal for near-term implementations of the QAOA. Throughout our algorithm, the decision to apply CNOT-intensive operations is made dynamically, based on algorithmic benefits. Using density-matrix simulations, we benchmark the noise resilience of ADAPT-QAOA and Dynamic-ADAPT-QAOA. We compute the gate-error probability $p_\text{gate}^\star$ below which these algorithms provide, on average, more accurate solutions than the classical, polynomial-time approximation algorithm by Goemans and Williamson. For small systems with $6-10$ qubits, we show that $p_{\text{gate}}^\star>10^{-3}$ for Dynamic-ADAPT-QAOA. Compared to standard ADAPT-QAOA, this constitutes an order-of-magnitude improvement in noise resilience. This improvement should make Dynamic-ADAPT-QAOA viable for implementations on superconducting NISQ hardware, even in the absence of error mitigation.Comment: 15 pages, 9 figure

Measuring Metacognition in Cancer: Validation of the Metacognitions Questionnaire 30 (MCQ-30)

Objective The Metacognitions Questionnaire 30 assesses metacognitive beliefs and processes which are central to the metacognitive model of emotional disorder. As recent studies have begun to explore the utility of this model for understanding emotional distress after cancer diagnosis, it is important also to assess the validity of the Metacognitions Questionnaire 30 for use in cancer populations. Methods 229 patients with primary breast or prostate cancer completed the Metacognitions Questionnaire 30 and the Hospital Anxiety and Depression Scale pre-treatment and again 12 months later. The structure and validity of the Metacognitions Questionnaire 30 were assessed using factor analyses and structural equation modelling. Results Confirmatory and exploratory factor analyses provided evidence supporting the validity of the previously published 5-factor structure of the Metacognitions Questionnaire 30. Specifically, both pre-treatment and 12 months later, this solution provided the best fit to the data and all items loaded on their expected factors. Structural equation modelling indicated that two dimensions of metacognition (positive and negative beliefs about worry) were significantly associated with anxiety and depression as predicted, providing further evidence of validity. Conclusions These findings provide initial evidence that the Metacognitions Questionnaire 30 is a valid measure for use in cancer populations

Charting service quality gaps

Some of the most influential models in the service management literature (Parasuraman et al., 1985; Grönroos, 1990) focus on the concept of service quality gap (SQG). Parasuraman et al. (1985) define a pioneering model with five SQGs, the concepts of which are amplified in Brogowicz et al.’s (1990) model. The latter has five types of encompassing gaps: information and feedback-related gaps; design-related gaps; implementation-related gaps; communication-related gaps; and customers’ perceptions and expectations related gaps. Additionally to this model amplification, other authors (e.g., Brown & Swartz, 1989) have pointed to relevant SQGs that have not been considered previously. This paper integrates current models and a group of SQGs dispersed through the literature in a new comprehensive model. It draws a link between the model and the stages of a strategy process, emphasising the SQGs’ impact on the process and raising relevant research questions.FCT, FEUALG, UALG

Variational quantum chemistry requires gate-error probabilities below the fault-tolerance threshold

The variational quantum eigensolver (VQE) is a leading contender for useful quantum advantage in the NISQ era. The interplay between quantum processors and classical optimisers is believed to make the VQE noise resilient. Here, we probe this hypothesis. We use full density-matrix simulations to rank the noise resilience of leading gate-based VQE algorithms in ground-state computations on a range of molecules. We find that, in the presence of noise: (i) ADAPT-VQEs that construct ansatz circuits iteratively outperform VQEs that use "fixed" ansatz circuits; and (ii) ADAPT-VQEs perform better when circuits are constructed from gate-efficient elements rather than physically-motivated ones. Our results show that, for a wide range of molecules, even the best-performing VQE algorithms require gate-error probabilities on the order of $10^{-6}$ to $10^{-4}$ to reach chemical accuracy. This is significantly below the fault-tolerance thresholds of most error-correction protocols. Further, we estimate that the maximum allowed gate-error probability scales inversely with the number of noisy (two-qubit) gates. Our results indicate that useful chemistry calculations with current gate-based VQEs are unlikely to be successful on near-term hardware without error correction.Comment: 17 pages, 8 figure

Enhanced adenosine A(1) receptor and Homer1a expression in hippocampus modulates the resilience to stress-induced depression-like behavior

Resilience to stress is critical for the development of depression. Enhanced adenosine A1 receptor (A1R) signaling mediates the antidepressant effects of acute sleep deprivation (SD). However, chronic SD causes long-lasting upregulation of brain A1R and increases the risk of depression. To investigate the effects of A1R on mood, we utilized two transgenic mouse lines with inducible A1R overexpression in forebrain neurons. These two lines have identical levels of A1R increase in the cortex, but differ in the transgenic A1R expression in the hippocampus. Switching on the transgene promotes robust antidepressant and anxiolytic effects in both lines. The mice of the line without transgenic A1R overexpression in the hippocampus (A1Hipp-) show very strong resistance towards development of stress-induced chronic depression-like behavior. In contrast, the mice of the line in which A1R upregulation extends to the hippocampus (A1Hipp+), exhibit decreased resilience to depression as compared to A1Hipp-. Similarly, automatic analysis of reward behavior of the two lines reveals that depression resistant A1Hipp-transgenic mice exhibit high sucrose preference, while mice of the vulnerable A1Hipp + line developed stress-induced anhedonic phenotype. The A1Hipp + mice have increased Homer1a expression in hippocampus, correlating with impaired long-term potentiation in the CA1 region, mimicking the stressed mice. Furthermore, virus-mediated overexpression of Homer1a in the hippocampus decreases stress resilience. Taken together our data indicate for first time that increased expression of A1R and Homer1a in the hippocampus modulates the resilience to stress-induced depression and thus might potentially mediate the detrimental effects of chronic sleep restriction on mood

Computational interpretations of analysis via products of selection functions

We show that the computational interpretation of full comprehension via two wellknown functional interpretations (dialectica and modified realizability) corresponds to two closely related infinite products of selection functions