Pterygoid implant-based maxillary full-arch rehabilitation using an autonomous robot system: A case report.

Pterygoid implant placement has been proven to be a viable option in full-arch implant rehabilitation for extremely atrophic maxillae. Nevertheless, the utilization of pterygoid implants remains a challenge for the dentist due to the difficulties of accessing the surgical site and poor visibility. To address these difficulties, digital techniques have been used to enhance the accuracy of pterygoid implant placement.

XElemNet: towards explainable AI for deep neural networks in materials science.

Recent progress in deep learning has significantly impacted materials science, leading to accelerated material discovery and innovation. ElemNet, a deep neural network model that predicts formation energy from elemental compositions, exemplifies the application of deep learning techniques in this field. However, the "black-box" nature of deep learning models often raises concerns about their interpretability and reliability.

MPpredictor: An Artificial Intelligence-Driven Web Tool for Composition-Based Material Property Prediction.

The applications of artificial intelligence, machine learning, and deep learning techniques in the field of materials science are becoming increasingly common due to their promising abilities to extract and utilize data-driven information from available data and accelerate materials discovery and design for future applications. In an attempt to assist with this process, we deploy predictive models for multiple material properties, given the composition of the material. The deep learning models described here are built using a cross-property deep transfer learning technique, which leverages source models trained on large data sets to build target models on small data sets with different properties.

Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design.

There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the causes that cannot be directly observed.

New horizons for building pyrenoid-based CO2-concentrating mechanisms in plants to improve yields.

Many photosynthetic species have evolved CO2-concentrating mechanisms (CCMs) to improve the efficiency of CO2 assimilation by Rubisco and reduce the negative impacts of photorespiration. However, the majority of plants (i.e.

The small subunit of Rubisco and its potential as an engineering target.

Rubisco catalyses the first rate-limiting step in CO2 fixation and is responsible for the vast majority of organic carbon present in the biosphere. The function and regulation of Rubisco remain an important research topic and a longstanding engineering target to enhance the efficiency of photosynthesis for agriculture and green biotechnology. The most abundant form of Rubisco (Form I) consists of eight large and eight small subunits, and is found in all plants, algae, cyanobacteria, and most phototrophic and chemolithoautotrophic proteobacteria.

CRISPR-Cas9-Mediated Mutagenesis of the Rubisco Small Subunit Family in .

Engineering the small subunit of the key CO-fixing enzyme Rubisco (SSU, encoded by ) in plants currently poses a significant challenge, as many plants have polyploid genomes and SSUs are encoded by large multigene families. Here, we used CRISPR-Cas9-mediated genome editing approach to simultaneously knock-out multiple homologs in the model tetraploid crop tobacco (. Petit Havana).

Condensation of Rubisco into a proto-pyrenoid in higher plant chloroplasts.

Photosynthetic CO fixation in plants is limited by the inefficiency of the CO-assimilating enzyme Rubisco. In most eukaryotic algae, Rubisco aggregates within a microcompartment known as the pyrenoid, in association with a CO-concentrating mechanism that improves photosynthetic operating efficiency under conditions of low inorganic carbon. Recent work has shown that the pyrenoid matrix is a phase-separated, liquid-like condensate.

ECG R-wave peaks marking with simultaneously recorded continuous blood pressure.

Background And Objectives: ECG signal is relatively weak and vulnerable to various noise interferences, such as electromyography. There will be robustness problems when detecting the instantaneous heart rate independently. In some cases, multiple human physiologic parameters are monitored to help in heart rate detection.

Automatic projection image registration for nanoscale X-ray tomographic reconstruction.

Novel developments in X-ray sources, optics and detectors have significantly advanced the capability of X-ray microscopy at the nanoscale. Depending on the imaging modality and the photon energy, state-of-the-art X-ray microscopes are routinely operated at a spatial resolution of tens of nanometres for hard X-rays or ∼10 nm for soft X-rays. The improvement in spatial resolution, however, has led to challenges in the tomographic reconstruction due to the fact that the imperfections of the mechanical system become clearly detectable in the projection images.

Mesoscale Battery Science: The Behavior of Electrode Particles Caught on a Multispectral X-ray Camera.

Functional materials and devices are usually morphologically complex and chemically heterogeneous. Their structures are often designed to be hierarchical because of the desired functionalities, which usually require many different components to work together in a coherent manner. The lithium ion battery, as an energy storage device, is a very typical example of this kind of structure.

[Preparation and characterization of salvianolic acids-tanshinones composite powder for inhalation via co-micronized method].

Salvianolic acids and tanshinones are main hydrophilic and lipophilic extracts from Salvia Miltiorrhiza with significant anti-pulmonary fibrosis effects. The aim of this study was to prepare a co-micronized salvianolic acids-tanshinones composite powder for inhalation using a planetary ball mill. The micronization process parameters were optimized by central composite design (CCD) and response surface methodology (RSM).