Neutron powder diffraction study on the iron-based nitride superconductor ThFeAsN

We report neutron diffraction and transport results on the newly discovered superconducting nitride ThFeAsN with $T_c=$ 30 K. No magnetic transition, but a weak structural distortion around 160 K, is observed cooling from 300 K to 6 K. Analysis on the resistivity, Hall transport and crystal structure suggests this material behaves as an electron optimally doped pnictide superconductors due to extra electrons from nitrogen deficiency or oxygen occupancy at the nitrogen site, which together with the low arsenic height may enhance the electron itinerancy and reduce the electron correlations, thus suppress the static magnetic order.Comment: 4 pages, 4 figures, Accepted by EP

Spin gap and magnetic resonance in superconducting BaFe1.9_{1.9}Ni%_{0.1}As2_{2}

We use neutron spectroscopy to determine the nature of the magnetic excitations in superconducting BaFe$_{1.9}$Ni$_{0.1}$As$_{2}$ ($T_{c}=20$ K). Above $T_{c}$ the excitations are gapless and centered at the commensurate antiferromagnetic wave vector of the parent compound, while the intensity exhibits a sinusoidal modulation along the c-axis. As the superconducting state is entered a spin gap gradually opens, whose magnitude tracks the $T$-dependence of the superconducting gap observed by angle resolved photoemission. Both the spin gap and magnetic resonance energies are temperature \textit{and} wave vector dependent, but their ratio is the same within uncertainties. These results suggest that the spin resonance is a singlet-triplet excitation related to electron pairing and superconductivity.Comment: 4 pages, 4 figure

Surgical treatment of spinal tenosynovial giant cell tumor: Experience from a single center and literature review

IntroductionSpinal tenosynovial giant cell tumor (TGCT) is a rare benign primary spinal tumor with aggressive behavior. The treatment strategy and prognosis of spinal TGCT remain unclear. This retrospective study aimed to evaluate the effectiveness of surgical treatment of spinal TGCT.MethodsWe enrolled 18 patients with spinal TGCT who underwent surgical treatment in our hospital between January 2002 and January 2021. Additionally, we reviewed 72 cases of spinal TGCT with surgical treatment reported in the previous literature. Therefore, a total of 90 cases of spinal TGCT were evaluated for their clinical characteristics, surgical details, radiotherapy, and prognosis.ResultsIn terms of the extent of resection, 73 cases (81.1%) underwent gross total resection (GTR), and 17 cases (18.9%) underwent subtotal resection (STR). Regarding the technique of GTR, 12 cases (16.7%) underwent en bloc resection, while 60 cases (83.3%) underwent piecemeal resection. During a median follow-up duration of 36 months (range: 3–528 months), 17.8% (16/90) cases experienced local recurrence/progression. The local recurrence/progression rate in cases that underwent GTR was 8.2% (6/73), which was significantly lower than that in cases with STR (58.8%, 10/17) (p<0.001). The local recurrence/progression rate of en bloc resection was 8.3% (1/12), and that of piecemeal resection was 8.3% (5/60). Twelve cases underwent perioperative adjuvant radiotherapy, and one (8.3%, 1/12) of them showed disease progression during follow-up. Six recurrent/progressive lesions were given radiotherapy and all of them remained stable in the subsequent follow-up. Eight recurrent/progressive lesions were only treated with re-operation without radiotherapy, and half of them (50.0%, 4/8) demonstrated repeated recurrence/progression in the subsequent follow-up.ConclusionSurgical treatment could be effective for spinal TGCT cases, and GTR is the preferred surgical strategy. Piecemeal resection may be appropriate for spinal TGCT cases with an acceptable local recurrence/progression rate. Perioperative adjuvant radiotherapy may reduce the risk of postoperative local recurrence/progression, and radiotherapy plays an important role in the treatment of recurrent/unresectable spinal TGCT lesions

E2-AEN: End-to-End Incremental Learning with Adaptively Expandable Network

Expandable networks have demonstrated their advantages in dealing with catastrophic forgetting problem in incremental learning. Considering that different tasks may need different structures, recent methods design dynamic structures adapted to different tasks via sophisticated skills. Their routine is to search expandable structures first and then train on the new tasks, which, however, breaks tasks into multiple training stages, leading to suboptimal or overmuch computational cost. In this paper, we propose an end-to-end trainable adaptively expandable network named E2-AEN, which dynamically generates lightweight structures for new tasks without any accuracy drop in previous tasks. Specifically, the network contains a serial of powerful feature adapters for augmenting the previously learned representations to new tasks, and avoiding task interference. These adapters are controlled via an adaptive gate-based pruning strategy which decides whether the expanded structures can be pruned, making the network structure dynamically changeable according to the complexity of the new tasks. Moreover, we introduce a novel sparsity-activation regularization to encourage the model to learn discriminative features with limited parameters. E2-AEN reduces cost and can be built upon any feed-forward architectures in an end-to-end manner. Extensive experiments on both classification (i.e., CIFAR and VDD) and detection (i.e., COCO, VOC and ICCV2021 SSLAD challenge) benchmarks demonstrate the effectiveness of the proposed method, which achieves the new remarkable results

Symmetry guaranteed Dirac-line semimetals in two-dimensions against strong spin-orbit coupling

Several intriguing electronic phenomena and electric properties were discovered in three-dimensional Dirac nodal line semimetals (3D-DNLSM), which are, however, easy to be perturbed under strong spin-orbit coupling (SOC). While two-dimensional (2D) layers are an emerging material category with many advantages, 2D-DNLSM against SOC is yet to be uncovered. Here, we report a 2D-DNLSM in odd-atomic-layer Bi (the brick phase, another Bi allotrope), whose robustness against SOC is protected by the little co-group C_2v \times Z^T_2, the unique protecting symmetry we found in 2D.Specially, (4n+2) valence electrons fill the electronic bands in the brick phase, so that the Dirac nodal line with fourfold degeneracy locates across the Fermi level. There are almost no other low energy states close to the Fermi level; this allows to feasibly observe the neat DNLSM-induced phenomena in transport measurements without being affected by other bands. In contrast, Other VA-group elements also form the brick phases, but their DNL states are mixed with the extra states around the Fermi level. This unprecedented category of layered materials allows for exploring nearly isolated 2DDNL states in 2D.Comment: Totally 25 pages including main text, methods and supporting information, 4 figures, 8 SI figure

Genome-wide comparative analysis of digital gene expression tag profiles during maize ear development

Background: Development of the maize (Zea mays L.) female inflorescence (ear) has an important impact on corn yield. However, the molecular mechanisms underlying maize ear development are poorly understood. Results: We profiled and analyzed gene expression of the maize ear at four developmental stages: elongation phase (I), spikelet differentiation phase (II), floret primordium differentiation phase (III), and floret organ differentiation phase (IV). Based on genome-wide profile analysis, we detected differential mRNA of maize genes. Among the ~6,800 differentially expressed genes (DEGs), 3,325 genes were differentially expressed in stage II, 3,765 genes in III, and 1,698 genes in IV, compared to its previous adjacent stages, respectively. Furthermore, some of DEGs were predicted to be potential candidates in maize ear development, such as AGAMOUS (GRMZM2G052890) and ATFP3 (GRMZM2G155281). Meanwhile, some genes were well-known annotated to the mutants during maize inflorescence development such as compact plant2 (ct2), zea AGAMOUS homolog1 (zag1), bearded ear (bde), and silky1 (si1). Some DEGs were predicted targets of microRNAs such as microRNA156. K-means clustering revealed that the DEGs showed 18 major expression patterns. Thirteen transcriptional factors from 10 families were differentially expressed across three comparisons of adjacent stages (II vs. I, III vs. II, IV vs. III). Antisense transcripts were widespread during all four stages, and might play important roles in maize ear development. Finally, we randomly selected 32 DEGs to validate their expression patterns using quantitative reverse-transcription polymerase chain reaction (qRT-PCR). The results were consistent with those from Solexa sequencing. Conclusions: DEGs technique had shown an advantage in detecting candidates, and some transcription factors during maize ear development. RT-PCR data were consistent with our sequencing data and supplied additional information on ear developmental processes. These results provide a molecular foundation for future research on maize ear development