Reducing Anhedonia in Major Depressive Disorder with Future Event Specificity Training (FEST): A Randomized Controlled Trial

Objective: Improving future thinking may be one means to reduce anhedonia, particularly in Major Depressive Disorder (MDD) in which future thinking is impaired. The current study therefore examined whether enhancing future thinking is a viable method of reducing anhedonia in MDD. Methods: Participants (N=177; 80.8% women; M age=43.7, SD=11.8) with a current depressive episode including anhedonia and high symptom severity were randomized to a Future Event Specificity Training (FEST) program or wait-list control. Future thinking characteristics, anhedonia-related variables, and other clinical outcomes were assessed at baseline, one- and three-month follow-up. Results: The FEST group showed significantly improved future thinking characteristics compared to the control group, as expected. Relative to the control group, FEST was also associated with a reduced likelihood of anhedonia (35.1% vs 61.1%, p = .015), improvements on other anhedonia-related variables such as anticipatory (d = 0.63, p = .004) and anticipated pleasure (d = 0.77, p < .001), and desirable clinical outcomes such as less people meeting criteria for MDD (37.8% vs 64.8%, p = .011), lower symptom severity (d = 0.41, p = .048), higher behavioural activation (d = 0.71, p = .001) and improved global functioning (d = 0.52, p = .017). Changes in future thinking characteristics were found to mediate the effect of FEST on anhedonia.Conclusions: Future thinking can be enhanced in MDD, and this leads to a substantially reduced likelihood of anhedonia, other significant clinical effects and functional gains. Future research might examine FEST’s effects on other diagnostic groups with anhedonia and the utility of FEST as an adjunct to other treatments.

How Good is a Paleoseismic Record of Megathrust Earthquakes for Probabilistic Forecasting?

Time-dependent earthquake forecast depends on the frequency and number of past events and time since the last event. Unfortunately, only a few past events are historically documented along subduction zones where forecasting relies mostly on paleoseismic catalogs. We address the role of dating uncertainty and completeness of paleoseismic catalogs on probabilistic estimates of forthcoming earthquakes using a 3.6-ka-long catalog including 11 paleoseismic and 1 historic (Mw≥8.6) earthquakes that preceded the great 1960 Chile earthquake. We set the clock to 1940 and estimate the conditional probability of a future event using five different recurrence models. We find that the Weibull model predicts the highest forecasting probabilities of 44% and 72% in the next 50 and 100 yr, respectively. Uncertainties in earthquake chronologies due to missing events and dating uncertainties may produce changes in forecast probabilities of up to 50%. Our study provides a framework to use paleoseismic records in seismic hazard assessments including epistemic uncertainties.

Do I stay or do I go? Shifts in perch use by lizards during morning twilight suggest anticipatory behaviour

Anticipatory behaviour is the expectation of a near-future event based on information processed in the past and influences an animal's tactical decisions, particularly when there are significant fitness consequences. The grass lizard ( Takydromus viridipunctatus ) perches on blades of grass at night which likely reduces the probability of predation by terrestrial predators such as snakes, rodents and shrews. During twilight (starting 30 min before sunrise), they move from above the grass to within grass clumps and this is thought to afford the lizard protection while reducing detection by avian predators. Here, we examined how lizards shift their behaviour as a function of visual detectability to their primary predator, the cattle egret ( Bubulcus ibis ). We show that the lizards shift from their perch site during twilight at the earliest time at which egrets depart communal roosts. At the same time, visual modelling shows a dramatic increase in the detectability of the lizards to the visual system of egrets. Therefore, anticipatory behaviour in response to environmental cues acts to reduce predation risk as lizards become more conspicuous and predators become more active. Grass lizard anticipatory behaviour appears to be finely tuned by natural selection to adjust to temporal changes in predation risk.

A varying dark energy effective speed of sound parameter in the phantom Universe

We analyse the phenomenological effects of a varying Dark Energy (DE) effective speed of sound parameter, $$c^{2}_{\text {sd}}$$ c sd 2 , on the cosmological perturbations of three phantom DE models. Each of these models induce a particular abrupt future event known as Big Rip (BR), Little Rip (LR), and Little Sibling of the Big Rip (LSBR). In this class of abrupt events, all the bound structures in the Universe would be ripped apart at a finite cosmic time. We compute the evolution of the perturbations, $$f\sigma _{8}$$ f σ 8 growth rate and forecast the current matter power spectrum. We vary the $$c^{2}_{\text {sd}}$$ c sd 2 parameter in the interval [0, 1] and compute the relative deviation with respect $$c^{2}_{\text {sd}}=1$$ c sd 2 = 1 . In addition, we analyse the effect of gravitational potential sign flip that occurs at very large scale factors as compared with the current one.

Cosmological consequences of Rényi, Sharma–Mittal holographic and new agegraphic dark energy models in generalized Rastall gravity

The main motivation of our study is to explore Rényi holographic dark energy, Sharma–Mittal holographic dark energy, Rényi new agegraphic dark energy, and Sharma–Mittal new agegraphic dark energy in the context of generalized Rastall gravity with the two-fluid system, dark energy, and dark matter. In this regard, we have considered the scale factors into two distinct categories, one of which corresponds to the future singularity, whereas the other represents initial singularity. By employing future event horizon as infrared (IR)-cutoff, different cosmological quantities like deceleration parameter, equation of state (EoS) parameter are evaluated, and their ramifications have been described graphically. Analyzing the squared speed of sound, we have seen classically stable and unstable behavior for each of the considered models. Finally, we study [Formula: see text]–[Formula: see text] plane and find the thawing/freezing regions.

Towards an Intelligent Personalized Persuasive Conversational System for Human Interaction on Divining the Future Event and Assisting by Using Artificial Intelligence

In the next wave of insurgence, humans may endeavour self-reflection which can lead to an effortless talk and to find out if an event will fructify. Training the system on how to make accurate prognostication with the help of machine learning and statistical models can lead to an intelligent personalized conversational system. The Chatbot industry is ever-growing and after the COVID-19 pandemic and rigorous lockdowns all around the world, people have realized the importance of human interaction in their lives. We are developing this model to create a more intimate relationship between the system and humans. For this purpose, many open-source platforms are available. Artificial Intelligence Markup Language (AIML) is derived from Extensible Markup Language (XML) which is used to build up a conversational agent artificially. The success of this project will help the model in observing and understanding human emotions which will ultimately help it to form a more personalized relationship to delineate the future course of events.

Towards an Intelligent Personalized Persuasive Conversational System for Human Interaction on Divining the Future Event and Assisting by Using Artificial Intelligence

In the next wave of insurgence, humans may endeavour self-reflection which can lead to an effortless talk and to find out if an event will fructify. Training the system on how to make accurate prognostication with the help of machine learning and statistical models can lead to an intelligent personalized conversational system. The Chatbot industry is ever-growing and after the COVID-19 pandemic and rigorous lockdowns all around the world, people have realized the importance of human interaction in their lives. We are developing this model to create a more intimate relationship between the system and humans. For this purpose, many open-source platforms are available. Artificial Intelligence Markup Language (AIML) is derived from Extensible Markup Language (XML) which is used to build up a conversational agent artificially. The success of this project will help the model in observing and understanding human emotions which will ultimately help it to form a more personalized relationship to delineate the future course of events.

Towards an Intelligent Personalized Persuasive Conversational System for Human Interaction on Divining the Future Event and Assisting by Using Artificial Intelligence

In the next wave of insurgence, humans may endeavour self-reflection which can lead to an effortless talk and to find out if an event will fructify. Training the system on how to make accurate prognostication with the help of machine learning and statistical models can lead to an intelligent personalized conversational system. The Chatbot industry is ever-growing and after the COVID-19 pandemic and rigorous lockdowns all around the world, people have realized the importance of human interaction in their lives. We are developing this model to create a more intimate relationship between the system and humans. For this purpose, many open-source platforms are available. Artificial Intelligence Markup Language (AIML) is derived from Extensible Markup Language (XML) which is used to build up a conversational agent artificially. The success of this project will help the model in observing and understanding human emotions which will ultimately help it to form a more personalized relationship to delineate the future course of events.