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4results about How to "Reduction factor" patented technology

Enzymatic shrimp paste composite aquatic food attractant and application thereof

PendingCN122250589AImprove stabilityAchieve synergistic improvement of umami flavor
The application discloses an enzymatic shrimp paste compound water product feeding attractant and application thereof, and belongs to the technical field of water animal feed additives, characterized in that the compound water product feeding attractant is composed of the following components in percentage by weight: 85% to 98% of enzymatic shrimp paste, 2% to 15% of food-grade eugenol, wherein the enzymatic shrimp paste is obtained by directional enzymolysis of shrimp head endocrine fluid through a four-component complex flavor protease containing endoprotease, aminopeptidase, carboxypeptidase and glutamine transaminase; the application further provides a preparation method of the enzymatic shrimp paste and application of the compound water product feeding attractant; and the advantages are that the enzymatic shrimp paste is rich in flavor peptides, after being compounded with eugenol, the eugenol can activate the olfactory receptor ion channel of water animals, amplify the sensing signal of flavor substances, and form a significant synergistic feeding effect, so that the feeding amount of the water animals can be effectively improved, and the feed coefficient can be reduced.
Owner:NINGBO UNIV

Polymersubstrate mit verbessertem thermischem ausdehnungskoeffizienten und verfahren zur herstellung davon

UndeterminedAT1893666Treduction of TECeasy to merge
A substrate and method for providing a thermoplastic composite having a fiberglass mat embedded within a thermoplastic polymer. The characteristics of the fiberglass mat combined with a thermal compression bonding method allow for a substantially improved and desirable thermal expansion coefficient over conventionally filled thermoplastic substrates or other fiberglass reinforced thermoplastics.
Owner:INTERFACIAL CONSULTANTS LLC

Leakage-proof ostomy bag convenient to replace and clean

PendingCN121987406AImprove leak-proof effectImprove sealingBodily discharge devicesWound.exudateSurgery
The invention provides a leakproof ostomy bag convenient to replace and clean, which comprises a bag body assembly and a sealing mechanism, the bag body assembly comprises an outer lining bag, a collecting bag and an ostomy base plate; wherein the collecting bag is fixedly connected to the inner side wall of the outer lining bag. The hydrocolloid dressing ring is used for absorbing wound exudate and expanding to form a gel barrier so as to improve the leakage-proof performance of the ostomy bag, the expansion characteristic of the hydrocolloid dressing ring can be used for being matched with the quick-release connecting mechanism to form mechanical pre-tightening force, and the sealing performance between the quick-release connecting mechanism and the artificial ostomy is improved; the collecting bag and the stoma base plate are connected through the quick-release connecting mechanism, so that when the stoma bag is replaced, axial stress is replaced with radial stress, or dismounting and mounting force does not directly act on the skin of a patient; or the dismounting force is concentrated in the mechanism; or a dismounting force reduction coefficient is increased; the traction force to the skin is reduced, and the disturbance to the stoma is reduced.
Owner:THE FOURTH HOSPITAL OF HEBEI MEDICAL UNIVERSITY (HEBEI CANCER HOSPITAL)

A sparse medical entity recognition method based on an attention mechanism

The application provides a sparse medical entity recognition method based on an attention mechanism, and comprises the following steps: S1, extracting a word vector through a BERT model and further extracting features by using a Bi-LSTM; S2, using an Attention mechanism to extract deep connections inside the word vector; S3, dynamically adjusting entity category weights and fusion weights in ensemble learning according to the entity sparsity characteristics of each batch; and S4, outputting a prediction result through a CRF layer. The named entity recognition model provided by the application can not only dynamically focus on difficult-to-identify samples to improve learning efficiency, but also introduce a reduction factor to reduce the interference caused by sparse entities during parameter updating. This makes the model have significantly improved performance in dealing with the problems of unbalanced entity quantity and sparse entities in medical named entity recognition.
Owner:CHONGQING UNIV