Hasil untuk "Geography (General)"

D. Massey

P. Krugman

A. Baker, R. Brooks

K. Frenken, R. Boschma

Olha Ivashchenko, Oleg Khudolii, Mykola Khudolii

Objectives. To synthesize contemporary scientific approaches to interpreting physical education of schoolchildren within the logic of a managed learning process and to clarify the role of pedagogical control, modelling, and age-related developmental regularities in shaping learning outcomes. Materials and Methods. The study was conducted as a narrative review of publications addressing physical education theory, pedagogical control, modelling of the learning process, age-related developmental regularities, and the teaching of physical exercises in general secondary education. The analysis was carried out from systems-based and learning-oriented perspectives on the organisation of physical education. Results. The review supports interpreting physical education of schoolchildren as a managed learning process in which learning outcomes emerge through the interaction of pedagogical control, modelling, and learners’ age-related developmental characteristics. Age-related regularities are best treated as parameters of learning models that define the boundaries for valid interpretation of pedagogical-control results. Pedagogical control acquires a regulatory function only when embedded within a model of the learning process. The synthesis also allows the learning of physical exercises to be interpreted as the formation and dynamics of learning states that can serve as objects of pedagogical control and regulation. Conclusions. The proposed synthesis enables interpreting outcomes of physical education as consequences of the organisation of the learning process rather than as autonomous normative indicators. This narrative review delineates theoretical and methodological frames for further research aimed at empirically testing models of managed physical education and refining tools of pedagogical control in general secondary education practice.

Balkar Yildirim, Alan Albert Coley, Diego Fernando López

We investigate whether black holes can persist through the bounce with a minimal scale factor in a non-singular cosmology, whereby black holes from a previous contracting phase survive into the current expanding one. We do so by studying a generalized McVittie spacetime which embeds a spherically symmetric black hole in a positive spatial curvature bouncing FLRW cosmological background within the modified theory of teleparallel new general relativity. There are no further assumptions on the spacetime (e.g., on the form of the scale factor) initially, and the local evolution is derived from the field equations of the theory, utilizing a perturbative scheme which is valid ``near the bounce". To leading order we obtain a simple bounce solution similar to that in general relativity for a closed FLRW model with a positive cosmological constant, but in which the curvature term in the Friedmann equation is re-normalized within new general relativity. Qualitatively the minimum of the bounce at $t=0$ changes, but near the bounce the evolution remains symmetric. The central inhomogeneity evolves at higher perturbative orders, where the details depend on the arbitrary constants of the perturbative solution. Hence the evolution of the local horizon during the bounce changes qualitatively, where the effects depend on the signs of the perturbation, and the symmetry across the bounce is disrupted due to a linear term.

Krzysztof Janowicz, Gengchen Mai, Rui Zhu et al.

Understanding how AI will represent and reason about geography should be a key concern for all of us, as the broader public increasingly interacts with spaces and places through these systems. Similarly, in line with the nature of foundation models, our own research often relies on pre-trained models. Hence, understanding what world AI systems construct is as important as evaluating their accuracy, including factual recall. To motivate the need for such studies, we provide three illustrative vignettes, i.e., exploratory probes, in the hope that they will spark lively discussions and follow-up work: (1) Do models form strong defaults, and how brittle are model outputs to minute syntactic variations? (2) Can distributional shifts resurface from the composition of individually benign tasks, e.g., when using AI systems to create personas? (3) Do we overlook deeper questions of understanding when solely focusing on the ability of systems to recall facts such as geographic principles?

Piotr J. Wróbel

General Lucjan Żeligowski’s dilemmas regarding his national identity reflect the difficult choices faced by millions of people living in the borderlands between Russia and various East-Central European nations over the past several centuries. Born and raised in a Polish-patriotic family in 1865 in the heart of the former Grand Duchy of Lithuania, which was controlled by Tsarist Russia, he joined the Russian Army out of poverty and became almost entirely Russified. Seeking a compromise between his Polish and Russian identities, he became interested in Slavophile ideology. By the end of World War I, his Polish identity had prevailed over his Lithuanian and Russian sentiments, and he contributed to the rebirth of Poland. However, he noticed a distinction between Poles from central Poland and himself, a “Polish” or “Slavic Lithuanian”. He was very critical of Warsaw’s policies towards the regions of the former Grand Duchy of Lithuania and endeavoured to preserve their separate character. In 1939, he escaped from Poland and joined the Polish émigré authorities. In the West, he returned to Pan-Slavic ideology, hoping it would help bridge the Polish-Soviet chasm. Also, his political views shifted. In interwar Poland, he became an agrarian, but he was moving to the left, dreaming of a “People’s Poland”. This allowed him to stay connected with the Soviets during World War II and later to decide on his return to communist-controlled Poland. He had never found peace of mind and paid a steep price for his numerous identity crises. He was not alone; millions traversed similar mental paths, impacting the entire history of Eastern and East Central Europe.

Louis Boucherie

Complex systems are made up of many interacting components. Network science provides the tools to analyze and understand these interactions. Community detection is a key technique in network science for uncovering the structures that shape the behavior of these networks. This thesis introduces the Adaptive Cut, a novel method that improves clustering methods by employing multi-level cuts in hierarchical dendrograms. Overcoming the limitations of traditional single-level cuts-especially in unbalanced dendrograms-the Adaptive Cut provides a multi-level cut by optimizing a Markov chain Monte Carlo with simulated annealing. In addition, we propose the Balanceness score, an information-theoretic metric that quantifies dendrogram balance and predicts the benefits of multilevel cuts. Evaluations on over 200 real and synthetic networks show significant improvements in partition density and modularity. In the second part, our analysis shows that incorporating network geometry allows redefining administrative boundaries into non-contiguous regions that better reflect social and spatial dynamics. We also discuss the representation of hierarchical data in hyperbolic space through Poincare maps, which can represent tree-like structures in low dimension. In addition, we examine how geography constrains human mobility, an aspect often overlooked in scale-free characterizations of mobility. By incorporating geography via the pair distribution function from condensed matter physics, we separate geographic constraints from mobility choices. Analyzing datasets containing millions of individual movements, we identify a universal power law that spans five orders of magnitude, thereby bridging the divide between distance-based and opportunity-driven models of human mobility.

Haicang Zhou, Weiming Huang, Yile Chen et al.

Road network representation learning aims to learn compressed and effective vectorized representations for road segments that are applicable to numerous tasks. In this paper, we identify the limitations of existing methods, particularly their overemphasis on the distance effect as outlined in the First Law of Geography. In response, we propose to endow road network representation with the principles of the recent Third Law of Geography. To this end, we propose a novel graph contrastive learning framework that employs geographic configuration-aware graph augmentation and spectral negative sampling, ensuring that road segments with similar geographic configurations yield similar representations, and vice versa, aligning with the principles stated in the Third Law. The framework further fuses the Third Law with the First Law through a dual contrastive learning objective to effectively balance the implications of both laws. We evaluate our framework on two real-world datasets across three downstream tasks. The results show that the integration of the Third Law significantly improves the performance of road segment representations in downstream tasks.

Simon Scheider, Harm Bartholomeus, Judith Verstegen

The recent success of large language models and AI chatbots such as ChatGPT in various knowledge domains has a severe impact on teaching and learning Geography and GIScience. The underlying revolution is often compared to the introduction of pocket calculators, suggesting analogous adaptations that prioritize higher-level skills over other learning content. However, using ChatGPT can be fraudulent because it threatens the validity of assessments. The success of such a strategy therefore rests on the assumption that lower-level learning goals are substitutable by AI, and supervision and assessments can be refocused on higher-level goals. Based on a preliminary survey on ChatGPT's quality in answering questions in Geography and GIScience, we demonstrate that this assumption might be fairly naive, and effective control in assessments and supervision is required.

James T. Murphy

A. V. Shmytkova, O. V. Ivlieva

Introduction: the aim of the study is to analyze the recreational needs of the population of the South of Russia, to study the geography of tourist flows in the macroregion, the ranking of preferences for tourist destinations, and motives for tourist trips. The importance of studying the recreational needs of the population as the main factor generating the demand for tourism services is substantiated. Materials and methods of the research: the study is based on a generalization of the results of a sociological survey of the population of seven subjects of Southern Russia. The survey was implemented using the Google Forms online service. The data obtained in the course of a sociological survey supplement statistical information and allow comprehensive study of various aspects of tourism in the macro-region. The results of the study and their discussion: as a result, the main directions of tourist lows in the South of Russia were identified, the most popular tourist centers were revealed, the most preferred types of transport and types of accommodation establishments were determined. The analysis of the main factors restraining the development of tourism in the South of Russia is presented. Conclusions: an analysis of the data of a sociological survey allows to identify: the neighboring position and transport accessibility as a key factor in choosing a destination for recreation; traditional high demand for resorts on the Black Sea coast of the Krasnodar Territory and the emerging demand for mountain climatic resorts, especially in the summer; insignificant interest of potential tourists in the excursion centers of the plain part of the South of Russia.

Agnese Mantione, Rafael Torres

We discuss the geography problem of closed oriented 4-manifolds that admit a Riemannian metric of positive scalar curvature, and use it to survey mathematical work employed to address Gromov's observation that manifolds with positive scalar curvature tend to be inessential by focusing on the four-dimensional case. We also point out an strengthening of a result of Carr and its extension to the non-orientable realm.

Vicente Lorenzo

In this note the geography of minimal surfaces of general type admitting $\mathbb{Z}_2^2$-actions is studied. More precisely, it is shown that Gieseker's moduli space $\mathfrak{M}_{K^2,χ}$ contains surfaces admitting a $\mathbb{Z}_2^2$-action for every admissible pair $(K^2, χ)$ such that $2χ-6\leq K^2\leq 8χ-8$ or $K^2=8χ$. The examples considered allow to prove that the locus of Gorenstein stable surfaces is not closed in the KSBA-compactification $\overline{\mathfrak{M}}_{K^2,χ}$ of Gieseker's moduli space $\mathfrak{M}_{K^2,χ}$ for every admissible pair $(K^2, χ)$ such that $2χ-6\leq K^2\leq 8χ-8$.

Steven Navarrete Cardona

En la base de datos del centro nacional de memoria Histórica reposa un dato preocupante. Entre 1980 y 2012 en Colombia tuvieron lugar 1.982 masacres (Centro Nacional de Memoria Histórica 2013). Para encontrar una explicación certera de las mismas, no basta simplemente con enunciar que responden a la agencia de los actores que han estado involucrados en el conflicto armado, ese mismo fenómeno que ha golpeado por décadas, a lo largo y ancho nuestro territorio nacional. Se hace necesario reconstruir los procesos, los contextos y las motivaciones.

Daniela Borcezi

Neste estudo propõe-se discutir a cobertura jornalística acerca da Covid-19, com foco nas comunidades mais vulneráveis à doença. Para isso, a pesquisa delimitou-se em duas reportagens da revista Radis – Vulnerabilidades que aproximam – e Favelas contra o vírus. No percurso metodológico foi aplicado a narratologia, para identificar os personagens e o enquadramento do problema de saúde pública. Com a análise foi possível constatar abordagens jornalísticas focadas na vida cotidiana do homem comum, e o nível de abrangência das políticas públicas sociais, desde as aldeias indígenas até as periferias.

Alan Wilson

Most epidemic models are spatially aggregate and the index which is most used for planning and policy numbers, the r number, typically refers to a single system of interest. Even if r numbers are calculated for each of adjacent areas, regions or countries for example, there is no interaction between them. Here we aim to offer a fine-grained geography: models of epidemics in spatially disaggregated systems with interactions. This offers the possibility of new insights into the dynamics of epidemics and of policies aimed at mitigation and control.

Samantha Allen

The nonorientable 4-genus is an invariant of knots which has been studied by many authors, including Gilmer and Livingston, Batson, and Ozsváth, Stipsicz, and Szabó. Given a nonorientable surface $F \subset B^4$ with $\partial F = K\subset S^3$ a knot, an analysis of the existing methods for bounding and computing the nonorientable 4-genus reveals relationships between the first Betti number $β_1$ of $F$ and the normal Euler class $e$ of $F$. This relationship yields a geography problem: given a knot $K$, what is the set of realizable pairs $(e(F), β_1(F))$ where $F\subset B^4$ is a nonorientable surface bounded by $K$? We explore this problem for families of torus knots. In addition, we use the Ozsváth-Szabó $d$-invariant of two-fold branched covers to give finer information on the geography problem. We present an infinite family of knots where this information provides an improvement upon the bound given by Ozsváth, Stipsicz, and Szabó using the Upsilon invariant.