The top three carbon emitters, the European Union (EU), China, and the United States (US), account for up to 50% of the global total, and actions of them are deterministic for the ambitious target of ...the Paris Agreement. Towards carbon neutrality, while the EU has been consistently leading and the US has been swinging, China features a drastic but firm change of stance from a passive responder to a proactive leader in the past decade. Drawing the literature comparing their policies and plans, this paper analyzes the behaviors of the three actors within a theoretical framework of rational choice and applies game theory to find the Nash equilibria of their strategy combinations. Considering the complex variations in socioeconomic and international relations criteria, our ternary game model shows that the Nash equilibria evolve with time and are different from that of the prevalent Prisoner's Dilemma. Importantly, we found the collective cooperation strategy combination forms the only Nash equilibrium in the 2010s and after. Our model provides an explanation for the historic behaviors of the three players and allows for the prediction of their future environmental policy directions.
•We construct a ternary climate game model to analyze the interaction between the top 3 greenhouse gas emitters of the world.•With a multidimensional rating system, the game evolves with time and settles at a cooperative strategy equilibrium.•We explain the swinging US strategies, the persistent EU leadership, and the drastic change of China towards carbon neutrality.
Bilinguals are known to switch language spontaneously in everyday conversations, even if there are no external requirements to do so. However, in the laboratory setting, language control is often ...investigated using forced switching tasks, which result in significant performance costs. The present study assessed whether switching would be less costly when performed in a more natural fashion, and what factors might account for this. Mandarin-English bilinguals engaged in language switching under three different contexts with varied task demands. We examined two factors which may be characteristic of natural switching: (i) freedom of language selection; (ii) consistency of language used to name each item. Participants’ brain activities were recorded using magnetoencephalography (MEG), along with behavioural measures of reaction speed and accuracy. The natural context (with both free selection and consistent language use for each item) produced better performance overall, showing reduced mixing cost and no significant switch cost. The neural effect of language mixing was also reversed in this context, suggesting that freely mixing two languages was easier than staying in a single language. Further, while switching in the forced context elicited increased brain activity in the right inferior frontal gyrus, this switch effect disappeared when the language used to name each item was consistent. Together, these findings demonstrate that the two factors above conjointly contribute to eliminating significant performance costs and cognitive demands associated with language switching and mixing. Such evidence aligns with lexical selection models which do not assume bilingual production to be inherently effortful.
Interplay between DNA repair of the oxidatively modified base 8-oxo-7,8-dihydroguanine (OG) and transcriptional activation has been documented in mammalian genes. Previously, we synthesized OG into ...the VEGF potential G-quadruplex sequence (PQS) in the coding strand of a luciferase promoter to identify that base excision repair (BER) unmasked the G-quadruplex (G4) fold for gene activation. In the present work, OG was site-specifically synthesized into a luciferase reporter plasmid to follow the time-dependent expression in mammalian cells when OG in the VEGF PQS context was located in the coding vs template strands of the luciferase promoter. Removal of OG from the coding strand by OG glycosylase-1 (OGG1)-mediated BER upregulated transcription. When OG was in the template strand in the VEGF PQS context, transcription was downregulated by a BER-independent process. The time course changes in transcription show that repair in the template strand was more efficient than repair in the coding strand. Promoters were synthesized with an OG:A base pair that requires repair on both strands to yield a canonical G:C base pair. By monitoring the up/down luciferase expression, we followed the timing of repair of an OG:A base pair occurring on both strands in mammalian cells in which one lesion resides in a G-quadruplex loop and one in a potential i-motif. Depending on the strand in which OG resides, coding vs template, this modification is an up/downregulator of transcription that couples DNA repair with transcriptional regulation.
Bilinguals have a remarkable ability to juggle two languages. A central question in the field is concerned with the control mechanisms that enable bilinguals to switch language with ease. Theoretical ...models and neuroimaging evidence suggest that a range of control processes are at play during language switching, and their underlying neural mechanisms are closely related to executive function. What remains unclear is when these control processes are engaged in language switching. In this study, we used magnetoencephalography (MEG) to examine the brain activity while unbalanced Mandarin-English bilinguals performed a digit-naming task with cued language switching. Following presentation of the language cue, an asymmetrical switch effect was observed in the left inferior frontal gyrus (IFG), where switch-related increase in evoked brain activity was larger for switching into the non-dominant language. Following presentation of the naming target, evoked brain activity in the right IFG was larger when naming was required in the non-dominant language compared to the dominant language. We conclude that control processes take place in two stages during language switching, with the left IFG resolving interference following cue presentation and the right IFG inhibiting competing labels following target presentation.
Despite the classical hormonal effect, estrogen possesses a neuroprotective effect in the brain, which has led many to search for novel treatments for neurodegenerative diseases. Flavonoids, a group ...of compounds mainly derived from vegetables, share a resemblance, chemically, to estrogen, and indeed, some have been used as estrogen substitutes. To search for potential therapeutic agents against neurodegenerative diseases, different subclasses of flavonoids were analyzed and compared with estrogen. First, the estrogenic activities of these flavonoids were determined by activating the estrogen-responsive elements in cultured MCF-7 breast cancer cells. Second, the neuroprotective effects of flavonoids were revealed by measuring its inhibition effects on the formation of reactive oxygen species, the aggregation of β-amyloid, and the induction of cell death by β-amyloid in cultured neuronal PC12 cells. Among these flavonoids, baicalein, scutellarin, hibifolin, and quercetin-3‘-glucoside possessed the strongest effect in neuroprotection; however, the neuroprotective activity did not directly correlate with the estrogenic activity of the flavonoids. Identification of these flavonoids could be very useful in finding potential drugs, or food supplements, for treating Alzheimer's disease. Keywords: Alzheimer's disease; β-amyloid; flavonoids; estrogen; neuroprotection
To use a recurrent neural network (RNN) to reconstruct neural activity responsible for generating noninvasively measured electromagnetic signals. Approach: Output weights of an RNN were fixed as the ...lead field matrix from volumetric source space computed using the boundary element method with co-registered structural magnetic resonance images and magnetoencephalography (MEG). Initially, the network was trained to minimize mean-squared-error loss between its outputs and MEG signals, causing activations in the penultimate layer to converge towards putative neural source activations. Subsequently, L1 regularization was applied to the final hidden layer, and the model was fine-tuned, causing it to favour more focused activations. Estimated source signals were then obtained from the outputs of the last hidden layer. We developed and validated this approach with simulations before applying it to real MEG data, comparing performance with beamformers, minimum-norm estimate, and mixed-norm estimate source reconstruction methods. Main results: The proposed RNN method had higher output signal-to-noise ratios and comparable correlation and error between estimated and simulated sources. Reconstructed MEG signals were also equal or superior to the other methods regarding their similarity to ground-truth. When applied to MEG data recorded during an auditory roving oddball experiment, source signals estimated with the RNN were generally biophysically plausible and consistent with expectations from the literature. Significance: This work builds on recent developments of RNNs for modelling event-related neural responses by incorporating biophysical constraints from the forward model, thus taking a significant step towards greater biological realism and introducing the possibility of exploring how input manipulations may influence localized neural activity.
In the current study we aimed to determine which cognitive skills play a role when learning to program. We examined five cognitive skills (pattern recognition, algebra, logical reasoning, grammar ...learning and vocabulary learning) as predictors of course-related programming performance and their generalised programming performance in 282 students in an undergraduate introductory programming course. Initial skills in algebra, logical reasoning, and vocabulary learning predicted performance for generalised programming skill, while only logical reasoning skills predicted course-related programming performance. Structural equation modelling showed support for a model where the cognitive skills were grouped into a language factor and an algorithmic/mathematics factor. Of these two factors, only the algorithmic/mathematics factor was found to predict generalised and course-related programming skills. Our results suggested that algorithmic/mathematical skills are most relevant when predicting generalised programming success, but also showed a role for memory-related language skills.
A prominent theory of bilingual speech production holds that appropriate language selection is achieved via inhibitory control. Such inhibition may operate on the whole-language and/or item-specific ...level. In this study, we examined these two levels of control in parallel, by introducing a novel element into the traditional cued language switching paradigm: half of the stimuli were univalent (each required naming in the same language every time it appeared), and the other half were bivalent (each required naming in different languages on different trials). Contrasting switch and stay trials provided an index for whole-language inhibition, while contrasting bivalent and univalent stimuli provided an index for item-specific inhibition. We then investigated the involvement of domain-general brain mechanisms in these two levels of language control. Neuroimaging studies report activation of the pre-supplementary motor area (pre-SMA), a key region in the executive control brain network, during language switching tasks. However, it is unclear whether or not the pre-SMA plays a causal role in language control, and at which level it exerts control. Using repetitive transcranial magnetic stimulation (TMS) to transiently disrupt the pre-SMA, we observed an essential role of this brain region in general speech execution, while evidence for its specific involvement in each level of inhibition remains inconclusive.
We utilize a unique setting associated with the mandatory closure of the government‐to‐business revolving door to examine whether and how an exogenous rise in firm‐level political uncertainty affects ...the mispricing of earnings. The tension that underlies our study stems from two opposing effects. To the extent that such uncertainty can trigger opinion divergence (rational attention) among investors, it is expected to delay (accelerate) price discovery and increase (decrease) security mispricing. Our identification strategy draws on the difference‐in‐differences analysis associated with the Chinese regulation in 2013 that mandated the resignation of corporate independent directors with a government background. Consistent with the dominance of the opinion divergence effect, we observe that these involuntary resignations unintentionally increase delays in share price responses following earnings announcements. These findings are more evident among firms that enjoy more benefits from independent directors with a government background. Further analyses confirm that these involuntary resignations trigger more opinion divergence rather than rational attention among investors by showing significant increases in analyst forecast diversity but no changes in analyst coverage following such resignations. We provide novel evidence that market information efficiency could deteriorate as an unintended consequence of the escalation of firm‐level political uncertainty.
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