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Forecasts of long-run economic growth are critical inputs into policy decisions being made today on the economy and the environment. Despite its importance, there is a sparse literature on long-run forecasts of economic growth and the uncertainty in such forecasts. This study presents comprehensive probabilistic long-run projections of global and regional per-capita economic growth rates, comparing estimates from an expert survey and a low-frequency econometric approach. Our primary results suggest a median 2010–2100 global growth rate in per-capita gross domestic product of 2.1% per year, with a standard deviation (SD) of 1.1 percentage points, indicating substantially higher uncertainty than is implied in existing forecasts. The larger range of growth rates implies a greater likelihood of extreme climate change outcomes than is currently assumed and has important implications for social insurance programs in the United States.

Network approaches to psychopathology have become increasingly common in mental health research, with many theoretical and methodological developments quickly gaining traction. This article illustrates contemporary practices in applying network analytical tools, bridging the gap between network concepts and their empirical applications. We explain how we can use graphs to construct networks representing complex associations among observable psychological variables. We then discuss key network models, including dynamic networks, time‐varying networks, network models derived from panel data, network intervention analysis, latent networks, and moderated models. In addition, we discuss Bayesian networks and their role in causal inference with a focus on cross‐sectional data. After presenting the different methods, we discuss how network models and psychopathology theories can meaningfully inform each other. We conclude with a discussion that summarizes the insights each technique can provide in mental health research.

People’s ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis—connectome-based predictive modeling—to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems—intrinsic functional networks that tend to work in opposition—suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Functional neuroimaging research has recently revealed brain network interactions during performance on creative thinking tasks—particularly among regions of the default and executive control networks—but the cognitive mechanisms related to these interactions remain poorly understood. Here we test the hypothesis that the executive control network can interact with the default network to inhibit salient conceptual knowledge (i.e., pre-potent responses) elicited from memory during creative idea production. Participants studied common noun-verb pairs and were given a cued-recall test with corrective feedback to strengthen the paired association in memory. They then completed a verb generation task that presented either a previously studied noun (high-constraint) or an unstudied noun (low-constraint), and were asked to “think creatively” while searching for a novel verb to relate to the presented noun. Latent Semantic Analysis of verbal responses showed decreased semantic distance values in the high-constraint (i.e., interference) condition, which corresponded to increased neural activity within regions of the default (posterior cingulate cortex and bilateral angular gyri), salience (right anterior insula), and executive control (left dorsolateral prefrontal cortex) networks. Independent component analysis of intrinsic functional connectivity networks extended this finding by revealing differential interactions among these large-scale networks across the task conditions. The results suggest that interactions between the default and executive control networks underlie response inhibition during constrained idea production, providing insight into specific neurocognitive mechanisms supporting creative cognition.

Chlorides commonly precipitate during the evaporation of surface water or groundwater and during volcanic outgassing. Spectrally distinct surface deposits consistent with chloride-bearing materials have been identified and mapped using data from the 2001 Mars Odyssey Thermal Emission Imaging System. These deposits are found throughout regions of low albedo in the southern highlands of Mars. Geomorphologic evidence from orbiting imagery reveals these deposits to be light-toned relative to their surroundings and to be polygonally fractured. The deposits are small (< ~25 km²) but globally widespread, occurring in middle to late Noachian terrains with a few occurrences in early Hesperian terrains. The identification of chlorides in the ancient southern highlands suggests that near-surface water was available and widespread in early Martian history.

The presence of a scattering medium in the imaging path between an object and an observer is known to severely limit the visual acuity of the imaging system. We present an approach to circumvent the deleterious effects of scattering, by exploiting spectral correlations in scattered wavefronts. Our Synthetic Wavelength Holography (SWH) method is able to recover a holographic representation of hidden targets with sub-mm resolution over a nearly hemispheric angular field of view. The complete object field is recorded within 46 ms, by monitoring the scattered light return in a probe area smaller than 6 cm × 6 cm. This unique combination of attributes opens up a plethora of new Non-Line-of-Sight imaging applications ranging from medical imaging and forensics, to early-warning navigation systems and reconnaissance. Adapting the findings of this work to other wave phenomena will help unlock a wider gamut of applications beyond those envisioned in this paper. Here, the authors present Synthetic Wavelength Holography, an approach for Non-Line-of-Sight imaging. By exploiting spectral correlations in scattered light, the authors transform real world surfaces such as walls or scatterers into High-Resolution, Wide-Field-of-View imaging portals that provide holograms of objects obscured from view.

Cognitive and neuroimaging evidence suggests that episodic and semantic memory—memory for autobiographical events and conceptual knowledge, respectively—support different aspects of creative thinking, with a growing number of studies reporting activation of brain regions within the default network during performance on creative thinking tasks. The present research sought to dissociate neural contributions of these memory processes by inducing episodic or semantic retrieval orientations prior to performance on a divergent thinking task during fMRI. We conducted a representational similarity analysis (RSA) to identify multivoxel patterns of neural activity that were similar across induction (episodic and semantic) and idea generation. At the behavioral level, we found that semantic induction was associated with increased idea originality, assessed via computational estimates of semantic distance between concepts. RSA revealed that multivoxel patterns during semantic induction and subsequent idea generation were more similar (compared to episodic induction) within the left angular gyrus (AG), posterior cingulate cortex (PCC), and left anterior inferior parietal lobe (IPL). Conversely, activity patterns during episodic induction and subsequent generation were more similar within left parahippocampal gyrus and right anterior IPL. Together, the findings point to dissociable contributions of episodic and semantic memory processes to creative cognition and suggest that distinct regions within the default network support specific memory-related processes during divergent thinking. •Creative thinking involves semantic and episodic memory retrieval.•Memory inductions were given prior to creative thinking during fMRI.•Representational similarity analysis assessed induction and idea generation activity.•Semantic induction boosted semantic distance of generated ideas.•Default network regions support specific memory processes for creative thinking.

TRPA1 (transient-receptor-potential-related ion channel with ankyrin domains) is a direct receptor or indirect effector for a wide variety of nociceptive signals, and thus is a compelling target for development of analgesic pharmaceuticals such as channel blockers. Recently, the structure of TRPA1 was reported, providing insights into channel assembly and pore architecture. Here we report whole-cell and single-channel current recordings of wild-type human TRPA1 as well as TRPA1 bearing point mutations of key charged residues in the outer pore. These measurements demonstrate that the glutamate at position 920 plays an important role in collecting cations into the mouth of the pore, by changing the effective surface potential by ~16 mV, while acidic residues further out have little effect on permeation. Electrophysiology experiments also confirm that the aspartate residue at position 915 represents a constriction site of the TRPA1 pore and is critical in controlling ion permeation.

Despite increased focus on well-being in the psychological sciences in recent years, cross-sectional and group-level methods fall short of capturing the dynamics of individual people’s well-being in daily life. Such an investigation is especially important for young adults who are in a developmental phase in which they are more likely to experience fluctuations in their daily lives. We used ecological momentary assessment over one week in two samples of first-year college students (Sample 1, N  = 103, assessments = 2,535; Sample 2, N  = 76, assessments = 1,796) and a dynamic network approach (Dynamic Exploratory Graph Analysis). This approach estimates, within each person, how well-being elements fluctuate across days and co-vary with one another, recovering both their differentiation (exclusivity) and their interdependence (connectivity). In this approach, elements of well-being—measured via the PERMA framework—are modeled as a dynamic network to address the following research questions: (1) How do elements of well-being in young adults’ daily life form a dynamic network? (2) Does the structure of well-being hold across all young adults, or is there heterogeneity? (3) Is there synchrony among well-being elements, and do they drive a person’s well-being network? Findings suggest that whereas group-level dynamic well-being networks align with theoretical models, each person’s individual experiences vary significantly, with each person demonstrating unique well-being network structures and synchronous elements. These findings underscore the importance of considering individual variability in well-being, highlighting the necessity for personalized approaches to understand and promote well-being among young adults.

A numerical model of heat conduction through particulate media made of spherical grains cemented by various bonding agents is presented. The pore‐filling gas conductivity, volume fraction, and thermal conductivity of the cementing phase are tunable parameters. Cement fractions <0.001–0.01% in volume have small effects on the soil bulk thermal conductivity. A significant conductivity increase (factor 3–8) is observed for bond fractions of 0.01 to 1% in volume. In the 1 to 15% bond fraction domain, the conductivity increases continuously but less intensely (25–100% conductivity increase compared to a 1% bond system). Beyond 15% of cements, the conductivity increases vigorously and the bulk conductivity rapidly approaches that of bedrock. The composition of the cements (i.e. conductivity) has little influence on the bulk thermal inertia of the soil, especially if the volume of bond <10%. These results indicate that temperature measurements are sufficient to detect cemented soils and quantify the amount of cementing phase, but the mineralogical nature of the bonds and the typical grain size are unlikely to be determined from orbit. On Mars, a widespread surface unit characterized by a medium albedo (0.19–0.26) and medium/high thermal inertia (200–600 J s−0.5 m−2 K−1) has long been hypothesized to be associated with a duricrust. The fraction of cement required to fit the thermal data is less than ∼1–5% by volume. This small amount of material is consistent with orbital observations, confirming that soil cementation is an important factor controlling the thermal inertia of the Martian surface.