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The fundamental argument in this contribution is that quality teaching is inseparable from the quality of curriculum thought, and this includes a crucial focus on the role of geography teachers as curriculum makers and knowledge workers. This thinking is explored from a Future 3 curriculum thinking perspective - to unlock the potential of the school subject - and a GeoCapabilities approach and practice. 'Knowledge working' with powerful disciplinary knowledge in relation to other ways of knowing, is seen as a bridge between the level of epistemological principle and classroom content selection. This opens the possibility for developing a practical theory of content for teachers to engage with.

In this paper, we investigate the impact of latency aging on exchangeable (invariant under permutation of indices) inter-arrival times arising from mixed renewal point processes (statistical mixtures of point processes with renewal inter-arrival times) and explore the implications for reliability and survival analysis. We prove that aging preserves the exchangeability of inter-arrival times. Our data analysis, which includes both surrogate data and a Bayesian approach to high-frequency currency exchange-rate data, shows how aging impacts key survival analysis metrics such as failure survival, renewal, and hazard rate functions.

This article introduces an analytical framework that interprets individual measures of entropy-based mobility derived from mobile phone data. We explore and analyze two widely recognized entropy metrics: random entropy and uncorrelated Shannon entropy. These metrics are estimated through collective variables of human mobility, including movement trends and population density. By employing a collisional model, we establish statistical relationships between entropy measures and mobility variables. Furthermore, our research addresses three primary objectives: firstly, validating the model; secondly, exploring correlations between aggregated mobility and entropy measures in comparison to five economic indicators; and finally, demonstrating the utility of entropy measures. Specifically, we provide an effective population density estimate that offers a more realistic understanding of social interactions. This estimation takes into account both movement regularities and intensity, utilizing real-time data analysis conducted during the peak period of the COVID-19 pandemic.

Abstract The reproduction number of an infectious disease, such as CoViD-19, can be described through a modified version of the susceptible-infected-recovered (SIR) model with time-dependent contact rate, where mobility data are used as proxy of average movement trends and interpersonal distances. We introduce a theoretical framework to explain and predict changes in the reproduction number of SARS-CoV-2 in terms of aggregated individual mobility and interpersonal proximity (alongside other epidemiological and environmental variables) during and after the lockdown period. We use an infection-age structured model described by a renewal equation. The model predicts the evolution of the reproduction number up to a week ahead of well-established estimates used in the literature. We show how lockdown policies, via reduction of proximity and mobility, reduce the impact of CoViD-19 and mitigate the risk of disease resurgence. We validate our theoretical framework using data from Google, Voxel51, Unacast, The CoViD-19 Mobility Data Network, and Analisi Distribuzione Aiuti.

This paper combines perspectives from evolutionary biology and linguistics to discuss the early evolution of laughter and the possible role of laughter-like vocalisation as a bonding mechanism in hominins and early human species. From the perspective of evolutionary biology, we here emphasise several things: the role of exaptation, the typically very slow pace of evolutionary change, and the danger of projecting backwards from the current utilities of laughter to infer its earlier function, hundreds of thousands, or even millions, of years ago. From the perspective of linguistics, we examine both the semantics of the word ‘laugh’ and the vocal mechanics of human laughter production, arguing that greater terminological care is needed in talking about the precursors of laughter in the ancient evolutionary past. Finally, we turn to hypotheses about how laughter-like vocalisations may have arisen, long before articulate language as we know it today. We focus in particular on Robin Dunbar’s hypothesis that laughter-like vocalisation, which stimulated endorphin production, might have functioned as a bonding mechanism (a kind of “vocal grooming”) among hominins and early human species. The paper contributes to the special issue theme (Humour and Belonging) by casting a long look backwards in time to laughter-like vocalisation as a distant evolutionary precursor of humour, and to bonding as an evolutionary precursor to cognitively and socially modern forms of “belonging”. At the same time, it cautions against casual theorising about the evolutionary origins of laughter.

In this paper, we study the spreading of epidemic in a network of individuals who may either contract a disease through contact with infected nearest neighbors or be vaccinated under the influence of neighbors who are already vaccinated. We show that both interaction between susceptible S and infected individuals I and the imitation of vaccination, a form of sociological interaction between susceptible S and vaccinated V individuals, may lead to a phase transition. If the spreading of epidemic is in the supercritical condition, corresponding to an unlimited growth of infection, the interaction between S and V must reach the supercritical condition to generate control of the spreading of infection, and bring the system to criticality. By adopting a theoretical perspective like that of multilayer complex networks, we study the case where the epidemiological network is under the influence of a sociological debate on whether to be vaccinated. We show that at criticality this debate generates clusters of individuals in favor of vaccination and clusters of individuals opposing it.3,4 We study the influence of this debate on the spread of infection. We show that because of this debate in the epidemic network, a pattern emerges mirroring the structures of the sociological network. Finally, we introduce feedback of the epidemic network on the sociological network, and we prove that because of this feedback the sociological system undergoes a process of self-organization maintaining it at criticality. This system exhibits temporal complexity and critical slowing down.1 We hope that these results may have an important effect of giving interesting suggestions to behavioral psychologists and information scientists actively involved in the analysis of the social debate on the moral issues connected to sexual activities.

Several studies have used the logistic equation to model the growth of cancer cell populations1 as seen in Eq. (1). This has included correlated multiplicative, [Formula: see text] and additive, [Formula: see text], noise terms. These noise terms can affect the growth rate, [Formula: see text], and death rate, [Formula: see text], of tumor cells and can be induced from factors such as radiotherapy or other cancer treatments. Depending on the intensity of the noise the terms, the fluctuations can induce a phase transition. Noise-induced transitions of nonlinear stochastic systems have applications in the fields of physics, chemistry and biology. (1)dxdt=ax−bx2+xϵ(x)−Γ(t). We study the logistic differential equation with a multiplicative noise term before and at phase transition. Computational methods used to investigate this cancer cell model include a Diffusion Entropy Analysis method and a waiting time distribution method.2,3,4 DEA will establish the scaling of a simulated series without altering the data through detrending. We hypothesize the treatment that causes a phase transition in the logistic model will induce tumor extinction and management. Understanding how to better evaluate and study cancer cell growth models will assist in assessing the efficacy of cancer treatments. Future work will include running simulations with a modified DEA method that includes the use of stripes.2 For better statistics, the code will be adopted to run ensembles of simulated data instead of a single series. Generating and analyzing these large datasets can be computationally expensive. Through multiprocessing and the use of a supercomputer, we believe these computational limitations can be overcome.

A common question posed to environmental scientists by nonscientists, particularly policymakers, is the following: In a world that is globally warmer, what will the new climate be like in specific geographical regions? This question has been and continues to be addressed by computer modeling, a technique that is out of reach for vast majority of students. However, an alternate approach to investigating this issue exists that is more practical for students. Past climates can be inferred for specific regions from fossils, utilizing climate tolerances of related modern organisms. When these inferred past climates correspond to periods of the Earth's history where levels of carbon dioxide were as high or higher than today, these data can be used to extrapolate possible future local climates in a globally warmer world. The last Pleistocene interglacial period (known as the Eemian), which occurred approximately 120,000 years ago, is an ideal time period for studies of this kind for the following reasons. First, carbon dioxide levels were elevated at this time to levels approximating modern global conditions, and the world was warmer as evidenced by a much higher sea level than exists today. Secondly, most Eemian-age animals (especially mollusks) still exist, have known climate tolerances, and are relatively common as fossils. Students examining fossil mollusk faunas have applied this methodology to infer the Eemian climates of South Florida and coastal Virginia and found unexpectedly that for both regions the Eemian climate did not greatly differ from the modern one. The methodology described here can be used to address other important questions and puts such authentic and potentially valuable scientific research within practical reach of student scientists.