A selection of laboratory animals for complex behavioural experiments is of a significant importance for obtaining objective results. The problem of the selection seems to be solved by means of the proposed assessment of vertical learning of an habitable space. The assessment test is based on investigative activity of the animals under conditions of a new surrounding. The test allows to divide the rats into four types.

Download full-text PDF

Source

Publication Analysis

Top Keywords

vertical learning
8
learning habitable
8
habitable space
8
[evaluation velocity
4
velocity vertical
4
space complex
4
complex behavioral
4
behavioral experiments
4
experiments rats]
4
rats] selection
4

Similar Publications

Purpose: To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.

Methods: On lateral full-spine radiographs of 295 consecutive patients, a two-staged region-based convolutional neural network (R-CNN) was trained to detect anatomical landmarks and calculate thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), and sagittal vertical axis (SVA). Performance was evaluated on 65 radiographs not used for training, which were measured independently by 6 readers (3 radiologists, 3 surgeons), and the median per measurement was set as the reference standard.

View Article and Find Full Text PDF

Microplastics (MP) are known to be ubiquitous. The pathways and fate of these contaminants in the marine environment are receiving increasing attention, but still knowledge gaps exist. In particular, the link between mass-based MP quantification and oceanographic parameters is often lacking.

View Article and Find Full Text PDF

Vertical Federated Learning (VFL) is a promising category of Federated Learning that enables collaborative model training among distributed parties with data privacy protection. Due to its unique training architecture, a key challenge of VFL is high communication cost due to transmitting intermediate results between the Active Party and Passive Parties. Current communication-efficient VFL methods rely on using stale results without meticulous selection, which can impair model accuracy, particularly in noisy data environments.

View Article and Find Full Text PDF

Objective: This study evaluated ResNet-50 and U-Net models for detecting and segmenting vertical misfit in dental implant crowns using periapical radiographic images.

Methods: Periapical radiographs of dental implant crowns were classified by two experts based on the presence of vertical misfit (reference group). The misfit area was manually annotated in images exhibiting vertical misfit.

View Article and Find Full Text PDF

In the field of agriculture, particularly within the context of machine learning applications, quality datasets are essential for advancing research and development. To address the challenges of identifying different mango leaf types and recognizing the diverse and unique characteristics of mango varieties in Bangladesh, a comprehensive and publicly accessible dataset titled "BDMANGO" has been created. This dataset includes images essential for research, featuring six mango varieties: Amrapali, Banana, Chaunsa, Fazli, Haribhanga, and Himsagar, which were collected from different locations.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!