The US currency rose 15.2% in the period and 5.87% during the Lula government; is at the highest value since January 2022
The commercial dollar closed at R$5.59 this Friday (June 28, 2024). The quote marks 1 and a half years of the government’s 3rd term Luiz Inácio Lula da Silva (PT). The US currency reached R$5.60 at the day’s high. It was the highest value since January 10, 2022, when it was R$5.67.
After the negotiations in the first half of the year ended, the US currency rose:
- in the week: 2.71%;
- in the month: 6.46%;
- in the semester: 15.17%;
- in the Lula government: 5.87%.
The currency jumped 1.46% this Friday (June 28) after Lula’s statements in a radio interview The timefrom Minas Gerais. At the time, the PT member stated that the Selic rate will fall with the appointment of the next president of the Central Bank. The term of the current head of the monetary authority, Roberto Campos Neto, ends in December 2024.
Lula also stated that the Central Bank has an obligation to investigate cases of speculation among financial agents to increase the value of the dollar.
The PT member and Campos Neto had a public clash on Thursday (June 28). With the escalation of Lula’s criticism of the monetary authority, Campos Neto said that he will leave soon and they will see that he had done some technical work. He also declared that the intervention in the exchange rate would have “little effectiveness” and that the rise of the dollar is related to Brazil’s risks.
Campos Neto responded that Lula’s statements make the work of monetary policy more difficult, since they impact variables such as the dollar and future interest rates traded on the market.
Nominated by Lula, the director of Monetary Policy at the Central Bank, Gabriel Galípolo, is one of the main candidates for the command of the Central Bank. At an event at the FGV (Getulio Vargas Foundation) this Friday (June 28), Galípolo stated that the autonomy of the Central Bank is a “institutional evolution”. He also said that the behavior of the dollar is closely monitored by the monetary authority.
#Dollar #closes #R5.59
African elephants use names to call each other, study suggests
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Wild African elephants may address each other using individualized calls that resemble the personal names used by humans, a new study suggests.
While dolphins are known to call one another by mimicking the signature whistle of the dolphin they want to address, and parrots have been found to address each other in a similar way, African elephants in Kenya may go a step further in identifying one another.
These elephants learn, recognize and use individualized name-like calls to address others of their kind, seemingly without using imitation, according to the study published Monday in the journal Nature Ecology and Evolution.
The most common type of elephant call is a rumble, of which there are three sub-categories. So-called contact rumbles are used to call another elephant that is far away or out of sight. Greeting rumbles are used when another elephant is within touching distance. Caregiver rumbles are used by an adolescent or adult female toward a calf she is caring for, according to the study.
The researchers looked at these three types of rumbles, using a machine-learning model to analyze recordings of 469 calls made by wild groups of females and calves in Amboseli National Park and Samburu and Buffalo Springs National Reserves between 1986 and 2022. All the elephants could be individually identified by the shape of their ears, as they had been monitored continuously for decades, according to the study.
The idea was that “if the calls contained something like a name, then you should be able to figure out who the call was addressed to just from the acoustic features of the call itself,” said lead study author Mickey Pardo, an animal behaviorist and postdoctoral fellow at Cornell University in New York.
The researchers found that the acoustic structure of calls varied depending on who the target of the call was.
The machine-learning model correctly identified the recipient of 27.5% of calls analyzed, “which may not sound like that much, but it was significantly more than what the model would have been able to do if we had just fed it random data,” Pardo told CNN.
“So that suggests that there’s something in the calls that’s allowing the model to identify who the intended receiver of the call was,” he added.