The long-nosed Pinocchio chameleon is multiple species. Biologists have finally solved the century-old reptilian mystery. Breakthroughs, discoveries, and DIY tips sent every weekday. For nearly 150 years, zoologists have taken the Pinocchio chameleon () at face value.. However, a recent reexamination detailed in reveals that the chameleon is actually multiple species with elongated snouts worthy of the nickname.

'Something special is happening on Madagascar.' Breakthroughs, discoveries, and DIY tips sent every weekday. Lemurs first arrived on the island of Madagascar 53.2 million years ago, probably hitching a ride on a vegetation raft from mainland Africa. The island was predator free, and the lemurs evolved into an abundance of species to thrive in its various habitats--an expansion that hasn't stopped since. Scientists typically expect such rapid species growth to eventually slow down. However, in a study recently published in the journal a team of researchers presents evidence that lemurs defy this evolutionary principle.

At least 60 people have been killed in a drone strike at a displacement shelter in el-Fasher, a besieged Sudanese city on the brink of collapse. The resistance committee for el-Fasher, made up of local citizens and activists, said the paramilitary Rapid Support Forces (RSF) hit Dar al-Arqam camp, located within a university, with two drone strikes and eight artillery shells. Children, women and the elderly were killed in cold blood, and many were completely burned, a statement from the group said. Eyewitnesses described scenes of panic as rescuers pulled bodies from the rubble. Hospitals already struggling under months of siege have been overwhelmed, with doctors treating the wounded on floors and in corridors.

While elephants have the reputation as animals who never forget, they may have some competition from some primates. Lemurs use their long-term memory in combination with smell and social cues to find hidden fruit. This technique may have deep evolutionary roots, according to a study published in the International Journal of Primatology. "Our study provides evidence that lemurs can integrate sensory information with ecological and social knowledge, which demonstrates their ability to consider multiple aspects of a problem," study co-author and New York University anthropologist Elena Cunningham said in a statement. Cunningham is a clinical professor of molecular pathobiology at NYU College of Dentistry.

The collaboration between communities and scientists aims to restore baobab forests in Madagascar to this natural state. Six of the world's eight baobab species are indigenous to Madagascar, where the distinctive trees with giant trunks have historically grown in huge forests. But these forests are threatened by slash-and-burn agriculture – 4,000 hectares of baobab forest in Madagascar are destroyed every year. Baobab trees can live for 1,000 years and one hectare of land can support eight fully grown baobab trees. But many have been left orphaned – standing alone in barren areas with no contact with the wild animals that spread their seeds, helping the baobabs to reproduce.

Artificial Intelligence (AI) – models that process large and diverse datasets and make predictions from them – can have many uses in nature conservation, such as remote monitoring (like the use of camera traps to study animals or plants) or data analysis. Some of these are controversial because AI can be trained to be biased, but others are valuable research tools. Biologist Daniele Silvestro has developed an AI tool that can help identify conservation and restoration priorities. We asked him to tell us more about how it works and what it offers. Artificial intelligence (AI) is a term indicating a broad family of models used to process large and diverse datasets and make predictions from them. We built a model using biodiversity datasets as well as socioeconomic data.

We investigate the predictive power of different machine learning algorithms to nowcast Madagascar's gross domestic product (GDP). We trained popular regression models, including linear regularized regression (Ridge, Lasso, Elastic-net), dimensionality reduction model (principal component regression), k-nearest neighbors algorithm (k-NN regression), support vector regression (linear SVR), and tree-based ensemble models (Random forest and XGBoost regressions), on 10 Malagasy quarterly macroeconomic leading indicators over the period 2007Q1--2022Q4, and we used simple econometric models as a benchmark. We measured the nowcast accuracy of each model by calculating the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Our findings reveal that the Ensemble Model, formed by aggregating individual predictions, consistently outperforms traditional econometric models. We conclude that machine learning models can deliver more accurate and timely nowcasts of Malagasy economic performance and provide policymakers with additional guidance for data-driven decision making.

The aim of this note is to identify the factors influencing renewable energy consumption in Madagascar. We tested 12 features covering macroeconomic, financial, social, and environmental aspects, including economic growth, domestic investment, foreign direct investment, financial development, industrial development, inflation, income distribution, trade openness, exchange rate, tourism development, environmental quality, and urbanization. To assess their significance, we assumed a linear relationship between renewable energy consumption and these features over the 1990-2021 period. Next, we applied different machine learning feature selection algorithms classified as filter-based (relative importance for linear regression, correlation method), embedded (LASSO), and wrapper-based (best subset regression, stepwise regression, recursive feature elimination, iterative predictor weighting partial least squares, Boruta, simulated annealing, and genetic algorithms) methods. Our analysis revealed that the five most influential drivers stem from macroeconomic aspects. We found that domestic investment, foreign direct investment, and inflation positively contribute to the adoption of renewable energy sources. On the other hand, industrial development and trade openness negatively affect renewable energy consumption in Madagascar.

Madagascar's critically endangered'singing' lemurs -- Indri indri -- have a natural ability to keep a beat, just like us humans do, a study has concluded. Researchers from the Max Planck Institute for Psycholinguistics and the University of Turin studied the songs of indri in the rainforests of the island country. They found that the lemurs' strange, wailing songs have the same kinds of universal, categorical rhythms found across human musical cultures. Outside of humans, having rhythm is a rare trait in mammals -- although it can be found elsewhere in the animal kingdom, perhaps most notably in songbirds. Madagascar's critically endangered'singing' lemurs -- Indri indri -- have a natural ability to keep a beat, just like us humans do, a study has concluded.

Most classical planners use grounding as a preprocessing step, reducing planning to propositional logic. However, grounding comes with a severe cost in memory, resulting in large encodings for SAT/QBF based planners. Despite the optimisations in SAT/QBF encodings such as action splitting, compact encodings and using parallel plans, the memory usage due to grounding remains a bottleneck when actions have many parameters, such as in the Organic Synthesis problems from the IPC 2018 planning competition (in its original non-split form). In this paper, we provide a compact QBF encoding that is logarithmic in the number of objects and avoids grounding completely by using universal quantification for object combinations. We compare the ungrounded QBF encoding with the simple SAT encoding and also show that we can solve some of the Organic Synthesis problems, which could not be handled before by any SAT/QBF based planners due to grounding.