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Abstract Shaped by human movement, place connectivity is quantified by the strength of spatial interactions among locations. For decades, spatial scientists have researched place connectivity, applications, and metrics. The growing popularity of social media provides a new data stream where spatial social interaction measures are largely devoid of privacy issues, easily assessable, and harmonized. In this study, we introduced a global multi-scale place connectivity index (PCI) based on spatial interactions among places revealed by geotagged tweets as a spatiotemporal-continuous and easy-to-implement measurement. The multi-scale PCI, demonstrated at the US county level, exhibits a strong positive association with SafeGraph population movement records (10% penetration in the US population) and Facebook’s social connectedness index (SCI), a popular connectivity index based on social networks. We found that PCI has a strong boundary effect and that it generally follows the distance decay, although this force is weaker in more urbanized counties with a denser population. Our investigation further suggests that PCI has great potential in addressing real-world problems that require place connectivity knowledge, exemplified with two applications: (1) modeling the spatial spread of COVID-19 during the early stage of the pandemic and (2) modeling hurricane evacuation destination choice. The methodological and contextual knowledge of PCI, together with the open-sourced PCI datasets at various geographic levels, are expected to support research fields requiring knowledge in human spatial interactions.

Obesity has a complex multifactorial etiology and is characterized by excessive accumulation of adipose tissue. Visceral adipose tissue has deleterious effects on health because it secretes large amounts of inflammatory cytokines. Nutritional calorie restriction associated with strength training may be useful in managing chronic systemic inflammation. This study aimed to evaluate the acute effect of a single strength-training session on plasma adipokine levels in sedentary, overweight, and obese young men. This study included twelve men (Age: [34.95 ​± ​9.77] years; Height: [174.16 ​± ​3.66] centimeter [cm]; Weight: [97.83 ​± ​12.87] kilogram (kg); body mass index [BMI]: [32.30 ​± ​4.51] kg/m2), who performed a single strength training session. The strength training protocol consisted of 4 sets of 12 repetitions in the following six exercises, 45° leg press, bench press, leg extension, machine row, leg curl, and shoulder press. Blood samples were collected before, immediately after, and 1-h subsequent after strength training. The plasma levels of resistin and leptin were measured. A significant decrease in resistin levels were found 1 ​h after the strength training session if compared to levels before the training session (pre-[before] [2 390 ​± ​1 199] picograms per milliliter [pg/mL] vs post-1 h [1-h subsequent] [1 523 ​± ​798],6 ​pg/mL, p ​= ​0.002 8). The plasma leptin levels did not differ at any time point. In conclusion, a very well controlled single session of strength training significantly decreased the plasma levels of resistin without altering the concentration of leptin in overweight and obese individuals. This effect, at least in part, supports the benefits of exercise by reducing the low grade inflammation and insulin resistance in obesity.

Urban areas are the foundation of modern economies worldwide and act as hubs for population and investments. The increasing importance of urban areas coincides with a rise of complex social and natural threats. Urban resilience has been an emerging concept for the last decade. The term has been widely accepted and used but that still faces a lack of consensus on its meaning and implications to policy and governance. This perspective article offers perspectives and conception of urban resilience, portrayed as a dynamic process that benefits from an interdisciplinary perspective and multi-stakeholder partnerships, and how it can help urban areas to prepare and adapt to absorb and recover from external and internal disturbances and reduce urban vulnerabilities with policies and governance.

Models of human-caused ignition probability are typically developed from static or structural points of view. This research analyzes the intra-annual dimension of fire occurrence and fire-triggering factors in NE Spain and moves forward towards more accurate predictions. Applying the Maximum Entropy algorithm (MaxEnt) and using wildfire data (2008–2011) and GIS and remote sensing data for the explanatory variables, we construct eight occurrence data scenarios by splitting wildfire records into the four seasons and then separating each season into working and non-working days. We assess model accuracy using a cross-validation k-fold procedure and an operational validation with 2012 data. Results report a substantial contribution of accessibility across models, often coupled with Land Surface Temperature. In addition, we observe great temporal variability, with WAI strongly influencing winter models, whereas distance to roads stands out during working days. Model performances stand consistently above 0.8 AUC in all temporal scenarios, with outstanding predictive effectiveness during summer months. The comparison among static-to-dynamic approaches reveals superior performance of simulations considering temporal scenarios, with AUC values from 0.7 to 0.85. Overall, we believe our approach is reliable enough to derive dynamic predictions of human-caused fire occurrence. Highlights Wildfires exhibit differential spatial patterns at seasonal and daily levels. Accessibility by road and human pressure on wildlands govern ignition probability. Dynamic modelling through temporal scenarios enhances prediction. Winter fires display a stronger relationship to agricultural activities (WAI).

Múltiples investigadores creen que el estudio del comportamiento y movilidad espacial de la población ha alcanzado un cuello de botella debido a la rigidez de los métodos tradicionales de investigación en el campo y a la dificultad de acceso a información relevante y de confianza. La sombra digital geoespacial es una de las oportunidades más prometedoras para poder desarrollar y probar nuevas hipótesis en el estudio del comportamiento espacial, pero la aplicación de estos nuevos métodos todavía no ha sido suficientemente explorada en el campo de los riesgos y desastres. Este artículo recoge los últimos avances en este ámbito centrándose en la capacidad de la sombra digital geoespacial de redes sociales (Twitter) como un método innovador para el estudio del comportamiento espacial humano durante emergencias. Esta investigación rastrea las localizaciones de usuarios de Twitter durante el periodo pre-desastre para producir estimaciones del número de evacuados, y en los meses posteriores al desastre para estimaciones de desplazados y del impacto del evento en el turismo.

The study of migrations and mobility has historically been severely limited by the absence of reliable data or the temporal sparsity of available data. Using geospatial digital trace data, the study of population movements can be much more precisely and dynamically measured. Our research seeks to develop a near real-time (one-day lag) Twitter census that gives a more temporally granular picture of local and non-local population at the county level. Internal validation reveals over 80% accuracy when compared with users’ self-reported home location. External validation results suggest these stocks correlate with available statistics of residents/non-residents at the county level and can accurately reflect regular (seasonal tourism) and non-regular events such as the Great American Solar Eclipse of 2017. The findings demonstrate that Twitter holds the potential to introduce the dynamic component often lacking in population estimates. This study could potentially benefit various fields such as demography, tourism, emergency management, and public health and create new opportunities for large-scale mobility analyses.

Um dos grandes desafios da ciência política atual está no fato de que o pensamento político muitas vezes se manifesta como um substituto da religião: metanarrativas de um telos desmistificado para a história. Ao longo da produção literária da ciência política pós-iluminista, ideias de transformação social acabaram promovendo desejos de paraísos terrestres quase místicos, se não além-homem. As origens destes desejos seculares por um fim da história baseado em modificações econômicas são tanto psicológicas quanto históricas. Eric Voegelin, Martin Buber e Émile Cioran mostram como os socialismos desapossaram progressivamente a escatologia religiosa de sua esfera de atuação e a trouxeram à história comum, de forma a tornar cada vez mais possível para o homem acreditar que, em um momento futuro, qualquer ato político tornará lógico o absurdo, e harmônico o desarmônico. No presente trabalho, o autor visa apresentar uma crítica ao sistema utópico e à sua natureza de esperança religiosa, usando e avançando a proto-crítica austríaca.

Hurricane Matthew was the deadliest Atlantic storm since Katrina in 2005 and prompted one of the largest recent hurricane evacuations along the Southeastern coast of the United States. The storm and its projected landfall triggered a massive social media reaction. Using Twitter data, this paper examines the spatiotemporal variability in social media response and develops a novel approach to leverage geotagged tweets to assess the evacuation responses of residents. The approach involves the retrieval of tweets from the Twitter Stream, the creation and filtering of different datasets, and the statistical and spatial processing and treatment to extract, plot and map the results. As expected, peak Twitter response was reached during the pre-impact and preparedness phase, and decreased abruptly after the passage of the storm. A comparison between two time periods-pre-evacuation (October 2th-4th) and post-evacuation (October 7th-9th)-indicates that 54% of Twitter users moved away from the coast to a safer location, with observed differences by state on the timing of the evacuation. A specific sub-state analysis of South Carolina illustrated overall compliance with evacuation orders and detailed information on the timing of departure from the coast as well as the destination location. These findings advance the use of big data and citizen-as-sensor approaches for public safety issues, providing an effective and near real-time alternative for measuring compliance with evacuation orders.

A temática do preço justo é objeto de discussão tanto na tradição do pensamento cristão, quanto nas abordagens axiológicas proporcionadas pela Escola Austríaca de Economia. Por intermédio da apresentação e discussão da perspectiva bíblica a respeito do preço justo, bem como de reflexões de autores representativos do pensamento econômico escolástico e da Escola Austríaca de Economia, abordo e analiso os pontos de contato entre a Escola Austríaca e o Cristianismo Bíblico a respeito dessa temática.