In this work, a phosphine‐based covalent organic framework (Phos‐COF‐1) is successfully synthesized and employed as a template for the confined growth of broad‐scope nanoparticles (NPs). Ascribed to the ordered distribution of phosphine coordination sites in the well‐defined pores, various stable and well‐dispersed ultrafine metal NPs including Pd, Pt, Au, and bimetallic PdAuNPs with narrow size distributions are successfully prepared as determined by transmission electron microscopy, X‐ray photoelectron spectroscopy, inductively coupled plasma, and powder X‐ray diffraction analyses. It is also demonstrated that the as‐prepared Phos‐COF‐1‐supported ultrafine NPs exhibit excellent catalytic activities and recyclability toward the Suzuki–Miyaura coupling reaction, reduction of nitro‐phenol and 1‐bromo‐4‐nitrobenzene, and even tandem coupling and reduction of p‐nitroiodobenzene. This work will open many new possibilities for preparing COF‐supported ultrafine NPs with good dispersity and stability for a broad range of applications.

Food hoarding and pilferage in rodents may be regulated by intense competition between sympatric species that have similar habitats, diets and activity, but studies exploring this remain rare. Here, we used semi-natural enclosures to investigate food-hoarding and cache pilferage interactions between sympatric Korean field mice (KFM) (Apodemus peninsulae) and Chinese white-bellied rats (CWR) (Niviventer confucianus). KFM and CWR have similar diets, habitat and nocturnal activity, but the smaller KFM larder and scatter hoards and larger CWR larder hoard only. We found that KFM harvest, larder-hoard and eat seeds at a greater intensity when CWR are present as an audience (present but cannot pilfer). KFM ate 11.5%, re-larder-hoarded 17.9% and re-scatter-hoarded 1.3% of their scatter-hoarded seeds, and ate 29.3% of their larder-hoarded seeds when CWR were present as pilferers. A total of 12.8% of the seeds scatter-hoarded and 50% of seeds directly put on the ground by KFM were pilfered by CWR. CWR did not alter hoarding intensity in the presence of KFM and their stores cannot be pilfered by KFM. These results indicate that large-sized rodent species (more dominant) significantly increase the hoarding intensity of small-sized species and show a unidirectional pilferage of seeds cached by small-sized species. The behavioural differences between these two species may reduce competition for resources and promote coexistence between sympatric rodents.

No abstract

No abstract

No abstract

High false-positive (FP) rate remains to be one of the major problems to be solved in CAD study because too many false-positively cued signals will potentially degrade the performance of detecting true-positive regions and increase the call-back rate in CAD environment. In this paper, we proposed a novel classification method for FP reduction, where the conventional "hard" decision classifier is cascaded with a "soft" decision classification with the objective to reduce false-positives in the cases with multiple FPs retained after the "hard" decision classification. The "soft" classification takes a competitive classification strategy in which only the "best" ones are selected from the pre-classified suspicious regions as the true mass in each case. A neural network structure is designed to implement the proposed competitive classification. Comparative studies of FP reduction on a database of 79 images by a "hard" decision classification and a combined "hard"-"soft" classification method demonstrated the efficiency of the proposed classification strategy. For example, for the high FP sub-database which has only 31.7% of total images but accounts for 63.5% of whole FPs generated in single "hard" classification, the FPs can be reduced for 56% (from 8.36 to 3.72 per image) by using the proposed method at the cost of 1% TP loss (from 69% to 68%) in whole database, while it can only be reduced for 27% (from 8.36 to 6.08 per image) by simply increasing the threshold of "hard" classifier with a cost of TP loss as high as 14% (from 69% to 55%). On the average in whole database, the FP reduction by hybrid "hard"-"soft" classification is 1.58 per image as compared to 1.11 by "hard" classification at the TP costs described above. Because the cases with high dense tissue are of higher risk of cancer incidence and false-negative detection in mammogram screening, and usually generate more FPs in CAD detection, the method proposed in this paper will be very helpful in improving the performance of early detection of breast cancer with CAD.

No abstract

No abstract