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Костел босих кармелітів.
#31
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#32
Will Russia’s Ukraine invasion push up oil prices and inflation? Russian President Vladimir Putin’s advances in Ukraine have put President Biden and the U.S. Now, some forecasters are expecting the average price to top $5 a gallon sooner rather than later. Chief among the reasons for the nationwide climb in gas prices is the threat of military conflict between Russia and Ukraine. Russia is the world’s third-largest producer of petroleum and other crude oil, according to 2020 data from the U.S. As the country takes steps toward a potential invasion of its former satellite republic, some fear it could cut off natural gas exports after sanctions by the U.S. Should that happen, European countries may be forced to turn to petroleum-based fuels to replace natural gas. That could send gasoline prices up by an additional 10%, said Shon Hiatt, an associate professor of management and organization at USC’s Marshall School of Business. “The geopolitical risks are very high,” he said. California doesn’t import any oil from Russia. On the other hand, the ease with which you can view RSS headlines may convince you that you can subscribe to even more sites. You may end up spending just as much time reading feeds as you used to on regular Web sites. Reading feeds requires a few simple things, many of which you already have. You'll need a computer -- or compatible electronic device -- and an Internet connection. After that, you need something that can read, or aggregate, RSS files. Aggregators collect. Interpret RSS feeds in one location. That way, you can see the latest headlines from HowStuffWorks, CNN, the BBC and Reuters, all in one place. Or do you just want the headlines? Do you want everything organized by date, with the feeds mixed by most recent, or would you prefer to keep each site separate? These are options that your aggregator will give you help you enjoy your reading. Aggregators take many forms.|While describing spatio-temporal events in natural language, video captioning models mostly rely on the encoder’s latent visual representation. Recent progress on the encoder-decoder model attends encoder features mainly in linear interaction with the decoder. However, growing model complexity for visual data encourages more explicit feature interaction for fine-grained information, which is currently absent in the video captioning domain. Moreover, feature aggregations methods have been used to unveil richer visual representation, either by the concatenation or using a linear layer. Though feature sets for a video semantically overlap to some extent, these approaches result in objective mismatch and feature redundancy. In addition, diversity in captions is a fundamental component of expressing one event from several meaningful perspectives, currently missing in the temporal, i.e., video captioning domain. To this end, we propose Variational Stacked Local Attention Network (VSLAN), which exploits low-rank bilinear pooling for self-attentive feature interaction and stacking multiple video feature streams in a discount fashion. Each feature stack’s learned attributes contribute to our proposed diversity encoding module, followed by the decoding query stage to facilitate end-to-end diverse and natural captions without any explicit supervision on attributes. trump press conference today

















































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#33
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#34
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