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Tourist crowding degrades the visitor experience and negatively impacts the environment and the local population, potentially making tourism in popular destinations unsustainable. This motivated us to develop, within the framework of the European RESETTING project related to the digital transformation of tourism, a platform to visualize this crowding, exploring historical data, detecting patterns and trends and predicting future events. The ultimate goal is to support short- and medium-term decision-making to mitigate the phenomenon. To this end, the platform takes into account the carrying capacity of the target sites when calculating crowding density. The integration of data from different sources is achieved with an extensible, connector-based architecture. Three scenarios for using the platform are described, relating to major annual crowding events. Two of them, in the municipality of Lisbon, are based on data from a mobile network provided by the LxDataLab initiative. The third, in Melbourne, Australia, using public data from a network of movement sensors called the Pedestrian Counting System. An experiment to evaluate the usability of the proposed platform using NASA-TLX is

Machine-learning techniques, especially deep convolutional neural networks, are pivotal for image-based identification of biological species in many Citizen Science platforms. In this paper, we describe the construction of a dataset for the Portuguese native flora based on publicly available research-grade datasets, and the derivation of a high-accuracy model from it using off-the-shelf deep convolutional neural networks. We anchored the dataset in high-quality data provided by Sociedade Portuguesa de Botânica and added further sampled data from research-grade datasets available from GBIF. We find that with a careful dataset design, off-the-shelf machine-learning cloud services such as Google's AutoML Vision produce accurate models, with results comparable to those of Pl@ntNet, a state-of-the-art citizen science platform. The best model we derived, dubbed Floralens, has been integrated into the public website of Project Biolens, where we gather models for other taxa as well. The dataset used to train the model is also publicly available on Zenodo.

In the early phase of general relativity Elie Cartan and Hermann Weyl thought about the question of how the role of transformation groups could be transferred from classical geometry (Erlangen program) to differential geometry. They had different starting points and used different techniques, but both generalized the concept of connection arising from Levi-Civita's interpretation of the classical Christoffel symbols as parallel transfer in curved spaces. Their focus differed and Cartan headed toward a much more general framwork than Weyl (non-holonomous spaces versus scale gauge geometry). But there also was an overlap of topics (space problem) and, at the turn to the 1930s, they arrived at an agreement on how to deal with Cartan's infinitesimal geometric structures.

This note is a write-up of a talk given by the author at the Meeting of the Sociedade Portuguesa de Matematica in July 2012. We describe Jaeger's HOMFLY-PT expansion of the Kauffman polynomial and how to generalize it to other quantum invariants using the so-called "branching rules" for Lie algebra representations. We present a program which aims to construct Jaeger expansions for link homology theories.

Using the Keck Observatory, astronomers measured the spins of dozens of giant planets and brown dwarfs orbiting distant stars。 They found that giant planets can spin faster than much more massive brown dwarfs, challenging simple assumptions about mass and rotation。 The results suggest that magnetic fields and formation processes play a major role i

Scientists found that transfer learning can make the search for new physics in the universe much faster, slashing the need for expensive simulations。 Yet the approach can backfire when AI relies too heavily on familiar patterns, potentially missing evidence of something truly new

Scientists discovered that rice behaves in a highly unusual way: it weakens under rapid compression but stays stronger when pressure is applied slowly。 Using this effect, they engineered a new material that reacts differently to gentle movements and sudden impacts。 The material can adapt its stiffness automatically, opening the door to safer soft r

"Winning" bets were made on cloned website and would have lost money, WSJ finds

Critics saw the move as an underhanded way to steer them toward more costly chips

The US is one of a handful of countries that allow patents on plant varieties

Although it's on the smaller side, this electric vehicle is not very chill

Scientists have uncovered a surprising connection between quantum gravity and an exotic quantum state of matter that could explain why the universe isn’t expanding wildly fast。 The study suggests that the very shape of space-time may protect the cosmological constant from disruptive quantum effects

He had retinal tears and bruises from squishing his eyeballs with the gun

NASA’s upgraded Cold Atom Lab is turning the International Space Station into a frontier for quantum research, creating ultra-cold matter that behaves in astonishing ways。 The experiments could unlock new discoveries about the universe while paving the way for powerful future technologies in space and on Earth

SpaceX has told NASA it plans to launch Starship every eight days from Kennedy

The global cobalt supply chain is more interconnected—and more vulnerable—than previously thought, with disruptions capable of triggering far-reaching cascades across multiple countries and industries。 Researchers warn that protecting battery supply chains will require system-wide coordination because critical bottlenecks can turn local shocks into

White House spokesperson denied it was Trump only after story was published

us has now restored everything taken down by the government