The ‘anthrobots’ were able to repair a scratch in a layer of neurons in the lab.

The whole genomes of 500,000 people in the UK Biobank will help researchers to probe our genetic code for links to disease.

The expansion of the neocortex, a hallmark of mammalian evolution1,2, was accompanied by an increase in cerebellar neuron numbers3. However, little is known about the evolution of the cellular programs underlying cerebellum development in mammals. In this study, we generated single-nucleus RNA-sequencing data for ~400,000 cells to trace cerebellum development from early neurogenesis to adulthood in

Hear the biggest stories from the world of science | 29 November 2023

The United States and China are pursuing parallel scientific tracks. To solve crises on multiple fronts, the two roads need to become one.

Firms commercializing perovskite–silicon ‘tandem’ photovoltaics say that the panels will be more efficient and could lead to cheaper electricity.

What more could you want?

Data from the Nature Index suggest China-based authors are increasingly publishing without international colleagues.

‘Thirsty’ computing hubs could put pressure on already stretched water resources in sub-Saharan Africa. Plus, GPT-4 generates fake data set to support bogus science and what the OpenAI drama means for AI progress — and safety.

The Universal Declaration of Human Rights — proclaimed 75 years ago — describes science as fundamental to humanity. Upholding this right has never been more relevant than it is now.

Under the proposal, technology with potential military use would need authorization to be shared with non-Australian colleagues.

A paper claiming that a structure in Indonesia is the oldest pyramid in the world has raised the eyebrows of archaeologists. Plus, some anglerfish species live life upside down and babies start learning language in the womb.

The trick baffles researchers — but they are getting closer to understanding how the songbird does it.

A spike in respiratory illnesses in children is the result of common winter infections — not a novel pathogen. Plus, how to stop waves in their tracks and why we might embrace the feeling of uncertainty.

Octopuses can whip their soft arms with a characteristic “bend propagation” motion to capture prey with sensitive suckers. This relatively simple strategy provides models for robotic grasping, controllable with a small number of inputs, and a highly deformable arm with sensing capabilities. Here, we implemented an electronics-integrated soft octopus arm (E-SOAM) capable of reaching, sensing, grasping

Letter to the Editor

Snippets from Nature’s past.

Letter to the Editor

Letter to the Editor

Letter to the Editor

California governor Gavin Newsom’s delegation is building on existing research and policy initiatives with China, showing that effective climate action can happen below the national level.

Why people take to the streets to march against global heating is relatively well documented. But it’s unclear why certain tactics work better than others in reaching the public and policymakers.

Putting the specific needs of individuals and communities at the heart of HIV/AIDS care, by harnessing behavioural science, is key to building on the progress already been made.

An advocacy group is pushing for more ‘human challenge’ trials to spur vaccine discovery. Following COVID-19 and Zika studies, hepatitis C could be next.

The massive buried structures at Gunung Padang in Indonesia would be far older than Egypt’s great pyramids — if they’re even human constructions at all.

Scientists expected a surge in respiratory disease, but what is happening in China is unusual.

Advances made since the era of genome analysis of cancer cells commenced.

Can the world get back on track with efforts to stay under 1.5 ℃ of warming? Plus: The US is set to announce its strategy for international partnerships to commercialize nuclear-fusion power.

Topic modeling includes a variety of machine learning techniques for identifying latent themes in a corpus of documents. Generating an exact solution (i.e., finding global optimum) is often computationally intractable. Various optimization techniques (e.g., Variational Bayes or Gibbs Sampling) are employed to generate topic solutions approximately by finding local optima. Such an approximation often

?pela Borko tells how cave-diving enhanced her appreciation of the myriad life forms that teem in underground lakes.

Severe wildfires expected to profoundly affect wildlife habitats.

From classrooms to laboratories and conferences, working in chemistry presents huge challenges to disabled, chronically ill and neurodivergent people. Some simple fixes can help to shift the dial.

The COVID-19 pandemic brought home the value of cheap, ‘good enough’ methods of detecting disease. Extending that approach to other illnesses could improve health care in low- and middle-income countries.

Deep learning is driving the rapid evolution of algorithms that can automatically find and trace cells in a wide range of microscopy experiments.

Tornadoes, earthquakes and wildfires don’t have to lead to death and destruction. Plus, the most powerful cosmic ray since the Oh-My-God particle and a ‘treasure trove’ of new CRISPR systems holds promise for genome editing.

Extended reality (XR) applications—encompassing virtual reality, augmented reality, and mixed reality—are finding their way into multiple domains. Each area has different motivations for employing and different criteria for evaluating XR. Multiple surveys describe XR and its evaluation in particular fields. However, these surveys do not always agree on the definition of XR. This lack of consensus makes

A vast amount of location information exists in unstructured texts, such as social media posts, news stories, scientific articles, web pages, travel blogs, and historical archives. Geoparsing refers to recognizing location references from texts and identifying their geospatial representations. While geoparsing can benefit many domains, a summary of its specific applications is still missing. Further

Predictive modeling of various systems around the world is extremely essential from the physics and engineering perspectives. The recognition of different systems and the capacity to predict their future behavior can lead to numerous significant applications. For the most part, physics is frequently used to model different systems. Using physical modeling can also very well help the resolution of complexity

The astounding success made by artificial intelligence in healthcare and other fields proves that it can achieve human-like performance. However, success always comes with challenges. Deep learning algorithms are data dependent and require large datasets for training. Many junior researchers face a lack of data for a variety of reasons. Medical image acquisition, annotation, and analysis are costly

Neural networks?(NN s) have become one of the most important tools for artificial intelligence. Well-designed and trained?NN s can perform inference?(e.g., make decisions or predictions) on unseen inputs with high accuracy. Using?NN s often involves sensitive data: Depending on the specific use case, the input to the?NN and/or the internals of the?NN (e.g., the weights and biases) may be sensitive

In the evolution of agriculture to its next stage, Agriculture 5.0, artificial intelligence will play a central role. Controlled-environment agriculture, or CEA, is a special form of urban and suburban agricultural practice that offers numerous economic, environmental, and social benefits, including shorter transportation routes to population centers, reduced environmental impact, and increased productivity

Outsourcing data to the cloud has become prevalent, so Searchable Symmetric Encryption (SSE), one of the methods for protecting outsourced data, has arisen widespread interest. Moreover, many novel technologies and theories have emerged, especially for the attacks on SSE and privacy-preserving. But most surveys related to SSE concentrate on one aspect (e.g., single keyword search, fuzzy keyword search)

As the adoption of IoT-based smart homes continues to grow, the importance of addressing potential conflicts becomes increasingly vital for ensuring seamless functionality and user satisfaction. In this survey, we introduce a novel conflict taxonomy, complete with formal definitions of each conflict type that may arise within the smart home environment. We design an advanced conflict model to effectively

Though the sheer volume of data that is collected is immense, it is the rare categories that are often the most important in many high-impact domains, ranging from financial fraud detection in online transaction networks to emerging trend detection in social networks, from spam image detection on social media platforms to rare disease diagnosis in medical decision support systems. The unique challenges

Quadrotor Unmanned Aerial Vehicle (UAV) is an unstable system, so it needs to be controlled efficiently and intelligently. Moreover, due to its non-linear, coupled, and under-actuated nature, the quadrotor has become an important research platform to study and validate various control theories. Different control approaches have been used to control the quadrotor UAV. In this context, a comprehensive

Automated co-located human–human interaction analysis has been addressed by the use of nonverbal communication as measurable evidence of social and psychological phenomena. We survey the computing studies (since 2010) detecting phenomena related to social traits (e.g., leadership, dominance, and personality traits), social roles/relations, and interaction dynamics (e.g., group cohesion, engagement

The Internet of Things (IoT) encompasses a network of physical objects embedded with sensors, software, and data processing technologies that can establish connections and exchange data with other devices and systems via the Internet. IoT devices are incorporated into various products, ranging from ordinary household items to complex industrial appliances. Despite the increasing demand for IoT, security

Object detection has achieved a huge breakthrough with deep neural networks and massive annotated data. However, current detection methods cannot be directly transferred to the scenario where the annotated data is scarce due to the severe overfitting problem. Although few-shot learning and zero-shot learning have been extensively explored in the field of image classification, it is indispensable to