What does Binned Contigs mean in genomics?5 answersBinned contigs in genomics refer to the process of clustering together contigs that are inferred to originate from the same organism within metagenomic data. This clustering is essential for reconstructing complete genomes from fragmented metagenomic assemblies. Various binning tools and algorithms have been developed to aid in this process, such as BinaRena, binny, Binnacle, and BinChecker, each offering unique approaches to improve the quality and completeness of metagenome-assembled genomes (MAGs). These tools utilize different strategies, including k-mer composition, coverage by metagenomic reads, assembly graphs, and protein domain searches, to accurately group contigs and identify high-quality genomes that may have been missed by other methods.
Is there a gender binary?5 answersYes, the concept of a gender binary, which traditionally categorizes individuals strictly as either male or female, has been challenged by various academic disciplines. Research has shown that the gender binary is not as clear-cut as previously believed. Studies have highlighted the inadequacy of binary-focused gender/sex measurement practices and the need to consider gender/sex as multidimensional, especially in understanding non-binary identities. Furthermore, the operationalization and assessment of binarist ideologies have been a struggle in psychology, with efforts to analyze and measure gender beliefs that align with the binary framework. Overall, these findings suggest that the gender binary is being increasingly questioned and that there is a growing recognition of the complexity and diversity of gender identities beyond the traditional binary classification.
4.2.what are the works that use Binary classification methods in Biomedical entity linking short text ?5 answersBinary classification methods have been used in several works for biomedical entity linking in short text. One study proposed a Bert-binary-based entity link method for Chinese text, which used a Bert-binary model to calculate the correct probability of candidate entities and select the entity with the highest score for linking. Another work introduced a BERT-based dual encoder model that resolves multiple mentions in a document simultaneously, making it faster and competitive in accuracy for biomedical entity linking. These studies demonstrate the effectiveness of binary classification methods in addressing the challenges of entity linking in biomedical text.
Who created the binary number system?5 answersThe binary number system was created by multiple individuals. Thomas Harriot, an English mathematician, geographer, and astronomer, described the binary number system earlier than Gottfried Wilhelm Leibniz, a German scientist, in his works. Juan Caramuel de Lobkowitz, a Spanish polymath, also contributed to the understanding of the binary system in his book "Mathesis biceps vetus et nova" published in 1670. However, Leibniz is often credited with the invention of the binary system and its development into a representational basis for digital computing. Leibniz's writings on the binary system have had a significant influence on shaping our modern computer age.
Why is state of the art for binary neural networks?5 answersBinary neural networks are currently at the state-of-the-art in artificial intelligence research. These networks have been applied in various contexts such as education, real-time monitoring of nuclear reactors, renewable energy systems, and review helpfulness evaluation on online platforms. The use of binary neural networks in education has shown promise in improving educational outcomes, particularly in online teaching practices. In the field of nuclear reactor monitoring, binary neural networks have been used to accurately estimate the outlet water temperature of cooling towers, reducing computational time significantly. In the renewable energy sector, binary neural networks have been employed to stabilize the output of solar photovoltaic systems and maximize energy harvesting. Additionally, binary neural networks have been utilized in evaluating the helpfulness of reviews on platforms like Steam, achieving high accuracy in predicting review helpfulness. These advancements highlight the effectiveness and versatility of binary neural networks in various domains.
How does binary code work?4 answersBinary code is a system of representing information using only two symbols, typically 0 and 1. It is widely used in various fields such as Chinese character input methods, communication systems, program analysis, image processing, and two-dimensional codes. In binary code, data is encoded into sequences of bits, where each bit represents a binary value of either 0 or 1. The encoding and decoding processes involve converting data into binary format and vice versa. Binary code allows for efficient storage, transmission, and processing of information, making it a fundamental concept in computer science and digital technology.