Detection of crowdedness in bus compartments based on ResNet algorithm and video images

Multimedia Tools and Applications - The crowding in bus is an important factor affecting passenger satisfaction and bus dispatching level. However, how to use video images to detect crowding...     

Double emulsion (W/O/W) gel stabilised by polyglycerol polyricinoleate and calcium caseinate as mangiferin carrier: insights on formulation and stability properties

Mangiferin (MGF) is a phenolic compound isolated from mango, but its poor solubility significantly limits its use. In this study, MGF was embedded into the inner aqueous phase of W₁/O/W₂ emulsions. Firstly, the dissolution method of MGF was determined. MGF remained stable in solution with pH 13 at 30 min, and its solubility reached 10 mg mL⁻¹. When the pH of MGF solutions was adjusted from pH 13 to pH 6, MGF did not immediately crystallise, providing sufficient time to construct the MGF-loaded W₁/O/W₂ emulsions. Subsequently, the MGF-loaded W₁/O/W₂ emulsions were constructed using polyglycerol polyricinoleate (PGPR) and calcium caseinate (CAS). The formation and stability of the W₁/O/W₂ emulsions were investigated. The MGF-loaded W₁/O/W₂ emulsions stabilised with 1% PGPR and 1% – 3% CAS exhibited a low viscosity, limited loading capacity, and poor stability. Conversely, the MGF-loaded W₁/O/W₂ emulsions stabilised by 3%PGPR–3%CAS exhibited optimal loading capacity (encapsulation efficiency = 95.31% and loading efficiency = 0.91%) and stability, which was attributed to the fact that high viscosity and gel state retarded the migration of inner aqueous phase. These results indicated that the W₁/O/W₂ emulsions stabilised by PGPR and CAS may be a potential alternative for encapsulating mangiferin.     

Eco-friendly and degradable red phosphorus nanoparticles for rapid microbial sterilization under visible light

Pathogens pose a serious challenge to environmental sanitation and a threat to public health.The frequent use of chemicals for sterilization in recent years has not only caused secondary damage to the environment but also increased pathogen resistance to drugs,which further threatens public health.To address this issue,the use of non-chemical antibacterial means has become a new trend for environmental disinfection.In this study,we developed red phosphorus nanoparticles(RPNPs),a safe and degradable photosensitive material with good photocatalytic and photothermal properties.The red phosphorus nanoparticles were prepared using a template method and ultrasonication.Under the irradiation of simulated sunlight for 20 min,the RPNPs exhibited an efficiency of 99.98%in killing Staphylococcus aureus due to their excellent photocatalytic and photothermal abilities.Transmission electron microscopy and ultraviolet–visible spectroscopy revealed that the RPNPs exhibited degradability within eight weeks.Both the RPNPs and their degradation products were nontoxic to fibroblast cells.Therefore,such RPNPs are expected to be used as a new type of low-cost,efficient,degradable,biocompatible,and eco-friendly photosensitive material for environmental disinfection.     

Facile preparation and strong adhesive strength of honeycomb polyurethane films with small pore diameter

With the continuous development of bionics, such as, geckos and virginia creeper with both superhydrophobic and super-adhesive, the surface wetting and super-adhesive properties of various porous materials have attracted extensive attention of the scientific and medical communities. Here, the honeycomb polyurethane (PU) porous films with strong adhesion were successfully prepared by microphase separation method and the effects of growth parameters on their microstructure and adhesive strength to ice were investigated. It was found that a high relative humidity (e.g., 100%) and a low solution concentration (e.g., 2%) facilitated the formation of ordered honeycomb PU porous films, and as-prepared PU pores with average pore diameter as small as 5 μm are better ordered and more uniform than these in related documents. Although the contact angle of water droplets on the surface of PU porous films increased from the premodification value of 85–130° to more than 160° after surface modification with polydopamine (PDA), the corresponding rolling angle remained approximately constant (180°), indicating that the surface of PU porous films has strong adhesion similar to geckos and virginia creeper. Furthermore, at lower temperature, the PU porous films exhibited the high adhesive strength of 142.13 kPa on ice, which was strongly dependent on the porous microstructures and surface compositions. The improved adhesive behavior to ice of honeycomb PU porous films modified with PDA provides new strategies for surface modification of materials and potential applications in medical domain.     

近源成藏——来自鄂尔多斯盆地延长组湖盆东部“边缘”延长组6段原油的地球化学证据

延安以东和以北的鄂尔多斯盆地东北部地区曾被认为位处三叠纪延长组7段（长7段）沉积期古湖盆的"边缘"，一些学者认为该区延长组烃源岩不发育，因而其油藏原油系湖盆中心生成的原油经长距离侧向运移而来；但也有研究认为，包括盆地边缘在内的整个鄂尔多斯盆地致密油藏均为近源成藏。为明确盆地东部地区延长组原油来源，对三叠纪湖盆"东缘"七里村油田的主力油层延长组6段（长6段）原油开展了原油地球化学和油源对比研究。七里村油田长6段原油具有高饱和烃、高饱芳比、低非烃和低沥青质的特征，正构烷烃呈前高单峰型，主峰碳为C₁₉，生物标志化合物分析显示长6段原油为同源成熟原油，生油母质以藻类等低等水生生物为主，混有陆源高等植物，母源沉积环境为偏还原性的淡水湖泊。七里村油田长6段原油与本地区长7段黑色泥页岩和暗色泥岩2种烃源岩均具有明显亲缘关系，而与志丹、富县等湖盆中心地区的长7段烃源岩在族组成、生物标志化合物和稳定碳同位素特征上均存在明显区别。综合分析认为七里村油田长6段原油并非湖盆中心长7段优质烃源岩所生油气经长距离运移而来，而主要为原位长7段烃源岩生成的原油经垂向运移和短距离侧向运移在长6段等储层中聚集成藏，属于近源成藏。     

Ensemble relation network with multi-level measure

Fine-grained few-shot learning is a difficult task in image classification. The reason is that the discriminative features of fine-grained images are often located in local areas of the image, while most of the existing few-shotlearning image classification methods only use top-level features and adopt a single measure. In that way, the localfeatures of the sample cannot be learned well. In response to this problem, ensemble relation network with multi-level measure (ERN-MM) is proposed in this paper. It adds the relation modules in the shallow feature space tocompare the similarity between the samples in the local features, and finally integrates the similarity scores from thefeature spaces to assign the label of the query samples. So the proposed method ERN-MM can use local details andglobal information of different grains. Experimental results on different fine-grained datasets show that the proposedmethod achieves good classification performance and also proves its rationality.