Description

PROBLEM BEING SOLVED

The invention addresses the challenge of automatically tagging electronic documents, particularly those containing financial data, which are a mix of structured tables and unstructured text. While tagging tables with XBRL (Extensive Business Reporting Language) can be done using templates, tagging text notes manually is time-consuming and error-prone. Existing methods for tagging documents with XBRL tags often deliver unsatisfactory results, especially for numerical or date values, highlighting the need for a more accurate and efficient tagging solution.

METHOD USED

The invention proposes a method for automatically tagging electronic documents using deep learning techniques. The process involves preprocessing the document by extracting text, replacing numbers or dates with special numeric and magnitude-preserving symbols, and tokenizing the text. A deep learning module then determines the appropriate tags for each token. This method allows for accurate tagging of numerical and date values in text notes, which has been a challenge for existing tagging methods. By leveraging deep learning and this new tokenization technique, the invention can efficiently assign tags to different pieces of information in the document, making the tagging process more reliable and precise.

ADVANTAGES

Compared to previous inventions, the current method offers several advantages. It streamlines the tagging process for electronic documents, especially those with a mix of structured and unstructured data, by automating the tagging of text notes containing numerical or date values. The deep learning approach enhances the accuracy of tagging, ensuring that the right tags are assigned based on context, while it also offers a computational time speedup since it alleviates any token overfragmentation. By reducing the need for manual intervention and improving the efficiency of tagging financial documents, the invention provides a more effective solution for annotating electronic documents with XBRL tags.

Description

PROBLEM BEING SOLVED

The present invention aims to address the high costs associated with the fabrication and sealing of microfluidic devices. Current methods involve lengthy thermal bonding processes, expensive master forms, and compatibility issues with lamination films, hindering mass production and practical use of microfluidic devices. The invention seeks to provide a more economical and efficient solution for manufacturing microfluidic devices with flexible network designs for various applications.

METHOD USED

The method proposed by the present invention involves ultrasonic welding of polymeric substrates without the need for energy directors. This unique approach allows for the rapid fabrication of closed microfluidic channels in just a few seconds, significantly reducing manufacturing time and costs. By utilizing a master form with rim protrusions, the invention enables the creation of microfluidic devices with enclosed channels between flexible and inflexible polymeric substrates, ensuring compatibility and efficient sealing without deformation or clogging of the channels.

ADVANTAGES

Compared to existing methods, the current invention offers several advantages. It allows for the fabrication of microfluidic devices with the same material at the top and bottom of the microfluidic channels, eliminating compatibility issues with lamination films. The ultrasonic welding process without energy directors provides a fast, reliable, and microscale accurate technology for manufacturing microfluidic devices with flexible network designs. By streamlining the fabrication process and reducing costs, this invention paves the way for widespread applications of microfluidic devices in various fields such as point of care analysis, environmental monitoring, drug discovery, and biological research, as well as cooling devices in electronics.

Description

PROBLEM BEING SOLVED

The invention aims to address the critical issue of drug-drug interactions (DDIs) that can lead to adverse effects, hospital admissions, and even death. Current methods for identifying interactions are complex, costly, and time-consuming, requiring clinical trials, laboratory tests, and expert knowledge. The need for a fast, reliable, and automated system to predict drug interactions is essential for patient safety and effective healthcare.

METHOD USED

The invention presents a method for estimating the likelihood of drug interactions by analyzing a variety of documents to extract relevant information about drug entities and their associations. This extracted information is then combined with supplementary data from structured sources to create a unified graph representation. Machine learning techniques are applied to analyze the graph and identify new edges, indicating potential interactions between drugs. By automating this process, the method can efficiently predict drug interactions without the need for extensive testing or human expertise.

ADVANTAGES

Compared to existing tools and methods, the invention offers several advantages in predicting drug interactions. By leveraging a combination of document analysis, structured data sources, and machine learning, the method can quickly and accurately identify potential interactions between drugs. This approach reduces the reliance on costly and time-consuming experimental procedures, making it a more efficient and cost-effective solution for clinicians and researchers. Ultimately, the invention provides a valuable tool for improving patient safety and healthcare outcomes by enabling the timely prediction and avoidance of harmful drug interactions.

Description

PROBLEM BEING SOLVED

Current concrete material technologies face limitations such as cracks of cement material,  short service life of cencrete, safety concerns for their structure, timely crack repair concerns and their susceptability to biological attacks.. Other limitations for existing concrete self-healing solutions are high costs due to issues with water reactivity, time-consuming process inappropriate for routine and large scale applications of existing technologies, bacterial survival, uneven distribution of healing agent and mechanical properties, particularly with mineral admixtures, bacteria-based systems, glass-based capsules, polymeric tubes, and nano/microcapsules, where the correct dosage of the healing agent and its leakage cannot be controlled.  The proposed encapsulated system efficiently overcome these drawbacks and achieves extended lifespan of concrete structures, reduced maintenance costs, and improved mechanical properties by ensuring efficient activation and distribution of healing agents, enhancing the durability and sustainability of cement

METHOD USED

The proposed encapsulated system comprise a cement-based active core and a cement-based protective shell.  The capsules protect a drastic healing agent made of cement-DNA until crack appearance. Upon crack appearance, they activate and allow the healing agent to react with moisture for closing the crack and attributing to the concrete structure the initial performance and functionality.

ADVANTAGES

The solution overcomes above listed limitations and problems. The admixtures are easily incorporated in small dosages into cement or concrete mixtures during the preparation phase in a timely manner, without needing any particular expertise or effort.