Strangeness S=−1S=-1 hyperon-nucleon scattering in covariant chiral effective field theory

Motivated by the successes of covariant baryon chiral perturbation theory in one-baryon systems and in heavy-light systems, we study relevance of relativistic effects in hyperon-nucleon interactions with strangeness $S=-1$. In this exploratory work, we follow the covariant framework developed by Epelbaum and Gegelia to calculate the $YN$ scattering amplitude at leading order. By fitting the five low-energy constants to the experimental data, we find that the cutoff dependence is mitigated, compared with the heavy-baryon approach. Nevertheless, the description of the experimental data remains quantitatively similar at leading order.Comment: The manuscript has been largely rewritten but the results remain unchanged. To appear in Physical Review

Learning Semantically Enhanced Feature for Fine-Grained Image Classification

We aim to provide a computationally cheap yet effective approach for fine-grained image classification (FGIC) in this letter. Unlike previous methods that rely on complex part localization modules, our approach learns fine-grained features by enhancing the semantics of sub-features of a global feature. Specifically, we first achieve the sub-feature semantic by arranging feature channels of a CNN into different groups through channel permutation. Meanwhile, to enhance the discriminability of sub-features, the groups are guided to be activated on object parts with strong discriminability by a weighted combination regularization. Our approach is parameter parsimonious and can be easily integrated into the backbone model as a plug-and-play module for end-to-end training with only image-level supervision. Experiments verified the effectiveness of our approach and validated its comparable performance to the state-of-the-art methods. Code is available at https://github.com/cswluo/SEFComment: Accepted by IEEE Signal Processing Letters. 5 pages, 4 figures, 4 table

Deep Descriptor Transforming for Image Co-Localization

Reusable model design becomes desirable with the rapid expansion of machine learning applications. In this paper, we focus on the reusability of pre-trained deep convolutional models. Specifically, different from treating pre-trained models as feature extractors, we reveal more treasures beneath convolutional layers, i.e., the convolutional activations could act as a detector for the common object in the image co-localization problem. We propose a simple but effective method, named Deep Descriptor Transforming (DDT), for evaluating the correlations of descriptors and then obtaining the category-consistent regions, which can accurately locate the common object in a set of images. Empirical studies validate the effectiveness of the proposed DDT method. On benchmark image co-localization datasets, DDT consistently outperforms existing state-of-the-art methods by a large margin. Moreover, DDT also demonstrates good generalization ability for unseen categories and robustness for dealing with noisy data.Comment: Accepted by IJCAI 201

Porous amorphous Ge/C composites with excellent electrochemical properties

Porous amorphous germanium/carbon (Ge/C) composites, which were synthesized through the reduction/carbonization of germanium oxide/oleic acid precursors, could exhibit a high-capacity, high-rate and long-life performance due to the synergistic effect of the porous structure and carbon

Somatic mutations in FAT cadherin family members constitute an underrecognized subtype of colorectal adenocarcinoma with unique clinicopathologic features

BACKGROUND: The FAT cadherin family members (FAT1, FAT2, FAT3 and FAT4) are conserved tumor suppressors that are recurrently mutated in several types of human cancers, including colorectal carcinoma (CRC). AIM: To characterize the clinicopathologic features of CRC patients with somatic mutations in FAT cadherin family members. METHODS: We analyzed 526 CRC cases from The Cancer Genome Atlas PanCancer Atlas dataset. CRC samples were subclassified into 2 groups based on the presence or absence of somatic mutations in RESULTS: This CRC study cohort had frequent mutations in the CONCLUSION

Co-evolution of cancer microenvironment reveals distinctive patterns of gastric cancer invasion: laboratory evidence and clinical significance

<p>Abstract</p> <p>Background</p> <p>Cancer invasion results from constant interactions between cancer cells and their microenvironment. Major components of the cancer microenvironment are stromal cells, infiltrating inflammatory cells, collagens, matrix metalloproteinases (MMP) and newly formed blood vessels. This study was to determine the roles of MMP-9, MMP-2, type IV collagen, infiltrating macrophages and tumor microvessels in gastric cancer (GC) invasion and their clinico-pathological significance.</p> <p>Methods</p> <p>Paraffin-embedded tissue sections from 37 GC patients were studied by Streptavidin-Peroxidase (SP) immunohistochemical technique to determine the levels of MMP-2, MMP-9, type IV collagen, macrophages infiltration and microvessel density (MVD). Different invasion patterns were delineated and their correlation with major clinico-pathological information was explored.</p> <p>Results</p> <p>MMP2 expression was higher in malignant gland compared to normal gland, especially nearby the basement membrane (BM). High densities of macrophages at the interface of cancer nests and stroma were found where BM integrity was destroyed. MMP2 expression was significantly increased in cases with recurrence and distant metastasis (<it>P = </it>0.047 and 0.048, respectively). Infiltrating macrophages were correlated with serosa invasion (<it>P </it>= 0.011) and TNM stage (<it>P </it>= 0.001). MVD was higher in type IV collagen negative group compared to type IV collagen positive group (<it>P </it>= 0.026). MVD was related to infiltrating macrophages density (<it>P </it>= 0.040). Patients with negative MMP9 expression had better overall survival (OS) compared to those with positive MMP9 expression (Median OS 44.0 vs 13.5 mo, <it>P </it>= 0.036). Median OS was significantly longer in type IV collagen positive group than negative group (Median OS 25.5 vs 10.0 mo, <it>P </it>= 0.044). The cumulative OS rate was higher in low macrophages density group than in high macrophages density group (median OS 40.5 vs 13.0 mo, <it>P </it>= 0.056). Median OS was significantly longer in low MVD group than high MVD group (median OS 39.0 vs 8.5 mo, <it>P </it>= 0.001). The difference of disease-free survival (DFS) between low MVD group and high MVD group was not statistically significant (<it>P </it>= 0.260). Four typical patterns of cancer invasion were identified based on histological study of the cancer tissue, including Washing pattern, Ameba-like pattern, Spindle pattern and Linear pattern.</p> <p>Conclusions</p> <p>Proteolytic enzymes MMP9, MMP2 and macrophages in stroma contribute to GC progression by facilitating the angiogenesis. Cancer invasion patterns may help predict GC metastasis.</p

Starvation resistance of invasive lace bug Corythucha ciliata (Hemiptera: Tingidae) in China

Food shortage is a prevalent threat to insect survival and successful reproduction in natural settings. An insect species invading new areasmay have a high capacity to survive and adapt to starvation. To test these hypotheses, we assessed the survival time of Corythucha ciliata (Say), in a laboratory under two starvation conditions: complete starvation (no food supplied) and gradual starvation (food provided once and not replenished). Under complete starvation, survival of 3rd to 5th instar nymphs tended to decline steadily, whereas under gradual starvation this process was delayed in the initial stage. The average survival times increased as the instar increased under both conditions (14.0 h, 15.9 h and 24.4 h under complete starvation conditions; 27.8 h, 29.6 h and 33.6 h under gradual starvation conditions). The longest lived individual nymph survived for 49 hours. The results may partially explain the rapid global expansion of C. ciliata