为了解黄芪多糖和法国索比亚(SORBIAL)生物科技公司生产的香肠乳酸杆菌及鼠李糖乳酸杆菌组成的益生菌制剂(简称:索比亚益生菌)防制口蹄疫(Foot and Mouth Disease,FMD)的临床协同作用,选用感染口蹄疫的某300头母猪规模猪场60头断奶仔猪...为了解黄芪多糖和法国索比亚(SORBIAL)生物科技公司生产的香肠乳酸杆菌及鼠李糖乳酸杆菌组成的益生菌制剂(简称:索比亚益生菌)防制口蹄疫(Foot and Mouth Disease,FMD)的临床协同作用,选用感染口蹄疫的某300头母猪规模猪场60头断奶仔猪为试验动物模型。在分别注射FMD合成肽疫苗进行紧急防制5d后,每组20头猪随机分为对照组、试验甲组和乙组;对照组使用普瑞纳乳猪饲料作为饲养基础日粮,试验甲组在基础日粮中添加索比亚益生菌2kg/t拌料,试验乙组在基础日粮中添加索比亚益生菌1.8kg/t及APS0.2kg/t拌料,试验时间32d。结果表明,对照组诊断为FMD的4只全部心源性猝死,试验甲组出现诊断为FMD的猝死1例,而试验乙组无FMD案例发生;试验甲组和乙组比对照组防制FMD效果分别提高75%和100%,试验甲组和乙组比对照组的FMD疫苗保护率分别提高15%和20%,这说明,索比亚益生菌具有显著的防制FMD和提高FMD疫苗保护的作用,添加APS对其具有明显的协同作用;同时,试验甲组和乙组比对照组的饲料利用率分别提高11.0%和12.1%,而日增质量分别提高2.86%和8.57%;可见,索比亚益生菌对断奶仔猪的生长有良好的促进作用,添加APS对其有明显的协同作用。展开更多
Clothing attribute recognition has become an essential technology,which enables users to automatically identify the characteristics of clothes and search for clothing images with similar attributes.However,existing me...Clothing attribute recognition has become an essential technology,which enables users to automatically identify the characteristics of clothes and search for clothing images with similar attributes.However,existing methods cannot recognize newly added attributes and may fail to capture region-level visual features.To address the aforementioned issues,a region-aware fashion contrastive language-image pre-training(RaF-CLIP)model was proposed.This model aligned cropped and segmented images with category and multiple fine-grained attribute texts,achieving the matching of fashion region and corresponding texts through contrastive learning.Clothing retrieval found suitable clothing based on the user-specified clothing categories and attributes,and to further improve the accuracy of retrieval,an attribute-guided composed network(AGCN)as an additional component on RaF-CLIP was introduced,specifically designed for composed image retrieval.This task aimed to modify the reference image based on textual expressions to retrieve the expected target.By adopting a transformer-based bidirectional attention and gating mechanism,it realized the fusion and selection of image features and attribute text features.Experimental results show that the proposed model achieves a mean precision of 0.6633 for attribute recognition tasks and a recall@10(recall@k is defined as the percentage of correct samples appearing in the top k retrieval results)of 39.18 for composed image retrieval task,satisfying user needs for freely searching for clothing through images and texts.展开更多
文摘为了解黄芪多糖和法国索比亚(SORBIAL)生物科技公司生产的香肠乳酸杆菌及鼠李糖乳酸杆菌组成的益生菌制剂(简称:索比亚益生菌)防制口蹄疫(Foot and Mouth Disease,FMD)的临床协同作用,选用感染口蹄疫的某300头母猪规模猪场60头断奶仔猪为试验动物模型。在分别注射FMD合成肽疫苗进行紧急防制5d后,每组20头猪随机分为对照组、试验甲组和乙组;对照组使用普瑞纳乳猪饲料作为饲养基础日粮,试验甲组在基础日粮中添加索比亚益生菌2kg/t拌料,试验乙组在基础日粮中添加索比亚益生菌1.8kg/t及APS0.2kg/t拌料,试验时间32d。结果表明,对照组诊断为FMD的4只全部心源性猝死,试验甲组出现诊断为FMD的猝死1例,而试验乙组无FMD案例发生;试验甲组和乙组比对照组防制FMD效果分别提高75%和100%,试验甲组和乙组比对照组的FMD疫苗保护率分别提高15%和20%,这说明,索比亚益生菌具有显著的防制FMD和提高FMD疫苗保护的作用,添加APS对其具有明显的协同作用;同时,试验甲组和乙组比对照组的饲料利用率分别提高11.0%和12.1%,而日增质量分别提高2.86%和8.57%;可见,索比亚益生菌对断奶仔猪的生长有良好的促进作用,添加APS对其有明显的协同作用。
基金National Natural Science Foundation of China(No.61971121)。
文摘Clothing attribute recognition has become an essential technology,which enables users to automatically identify the characteristics of clothes and search for clothing images with similar attributes.However,existing methods cannot recognize newly added attributes and may fail to capture region-level visual features.To address the aforementioned issues,a region-aware fashion contrastive language-image pre-training(RaF-CLIP)model was proposed.This model aligned cropped and segmented images with category and multiple fine-grained attribute texts,achieving the matching of fashion region and corresponding texts through contrastive learning.Clothing retrieval found suitable clothing based on the user-specified clothing categories and attributes,and to further improve the accuracy of retrieval,an attribute-guided composed network(AGCN)as an additional component on RaF-CLIP was introduced,specifically designed for composed image retrieval.This task aimed to modify the reference image based on textual expressions to retrieve the expected target.By adopting a transformer-based bidirectional attention and gating mechanism,it realized the fusion and selection of image features and attribute text features.Experimental results show that the proposed model achieves a mean precision of 0.6633 for attribute recognition tasks and a recall@10(recall@k is defined as the percentage of correct samples appearing in the top k retrieval results)of 39.18 for composed image retrieval task,satisfying user needs for freely searching for clothing through images and texts.
