Three new species of the Phaonia acerba group (Diptera: Muscidae) from Palaearctic and Oriental Regions

Three new species of the Phaonia acerba group fromthe Palaearctic and Oriental Regions are described: P. gaoligongshanensis Xue & Yu, sp. n., P. zhangxianggi Xue & Yu, sp. n. and P. hongkuii Xue & Yu, sp. n. An identification key to the males of 8 species of the Phaonia acerba group from the Palaearctic and Oriental Regions is provided

A Logic Petri Net-Based Repair Method of Process Models with Incomplete Choice and Concurrent Structures

Current model repair methods cannot repair incomplete choice and concurrent structures precisely and simply. This paper presents a repair method of process models with incomplete choice and concurrent structures via logic Petri nets. The relation sets are constructed based on process trees, including branch sets, choice activity sets and concurrent activity sets. The deviations are determined by analyzing the relation between relation sets and activities in the optimal alignment. The model repair method is proposed for models with incomplete choice and concurrent structures via logic Petri nets according to different deviation positions. Finally, the correctness and effectiveness of the logic Petri net-based repair method are illustrated by simulation experiments

Compound semiconductor nanotube materials grown and fabricated

A new GaAs/InGaAs/InGaP compound semiconductor nanotube material structure was designed and fabricated in this work. A thin, InGaAs-strained material layer was designed in the nanotube structure, which can directionally roll up a strained heterostructure through a normal wet etching process. The compound semiconductor nanotube structure was grown by gas-source molecular beam epitaxy. A good crystalline quality of InGaP, InGaAs, and GaAs materials was obtained through optimizing the growth condition. The fabricated GaAs/InGaAs/InGaP semiconductor nanotubes, with a diameter of 300 to 350 nm and a length of 1.8 to 2.0 μm, were achieved through normal device fabrication

Recurrent retroperitoneal Schwannomas displaying different differentiation from primary tumor: Case report and literature review

<p>Abstract</p> <p>Background</p> <p>Retroperitoneal Schwannomas are uncommonly found in the retroperitoneum and few of them show malignant transformation and invasion. Local recurrence are common in malignant Schwannomas with very few reports of tumor distinct differentiation at recurrences.</p> <p>Case presentation</p> <p>We report here a rare case of retroperitoneal schwannoma with multiple origins from retroperitoneum and pelvic wall. Pathological examination confirmed the case as a schwannoma with malignant transformation. Radical dissection of the tumors along with the sacrifice of adjacent sigmoid colon and left kidney failed to provide a cure for this patient. Due to tumor recurrence, a second and a third surgery of radical excision were performed 6 months and 17 months later after the first surgery, respectively. Histopathologic analysis identified that the recurrent tumors were different from the original schwannoma because of their smooth muscle-like differentiation.</p> <p>Conclusion</p> <p>Malignant schwannomas are uncommon sarcomas with a high incidence of local recurrence. Distinct immunohistochemical staining results of the tumors at recurrence indicate their potential of smooth-muscle like differentiation. Radical excision of the tumors may provide benefit for their local recurrences.</p

A brief overview about the adipokine: Isthmin-1

Isthmin-1 is a secreted protein with multiple capability; however, it truly attracts our attention since the definition as an adipokine in 2021, which exerts indispensable roles in various pathophysiological processes through the endocrine or autocrine manners. In this review, we summarize recent knowledge of isthmin-1, including its distribution, structure, receptor and potential function

Molecular Beam Epitaxy Growth of Superconducting LiFeAs Film on SrTiO3(001) Substrate

The stoichiometric "111" iron-based superconductor, LiFeAs, has attacted great research interest in recent years. For the first time, we have successfully grown LiFeAs thin film by molecular beam epitaxy (MBE) on SrTiO3(001) substrate, and studied the interfacial growth behavior by reflection high energy electron diffraction (RHEED) and low-temperature scanning tunneling microscope (LT-STM). The effects of substrate temperature and Li/Fe flux ratio were investigated. Uniform LiFeAs film as thin as 3 quintuple-layer (QL) is formed. Superconducting gap appears in LiFeAs films thicker than 4 QL at 4.7 K. When the film is thicker than 13 QL, the superconducting gap determined by the distance between coherence peaks is about 7 meV, close to the value of bulk material. The ex situ transport measurement of thick LiFeAs film shows a sharp superconducting transition around 16 K. The upper critical field, Hc2(0)=13.0 T, is estimated from the temperature dependent magnetoresistance. The precise thickness and quality control of LiFeAs film paves the road of growing similar ultrathin iron arsenide films.Comment: 7 pages, 6 figure

STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation

In Location-Based Services, Point-Of-Interest(POI) recommendation plays a crucial role in both user experience and business opportunities. Graph neural networks have been proven effective in providing personalized POI recommendation services. However, there are still two critical challenges. First, existing graph models attempt to capture users' diversified interests through a unified graph, which limits their ability to express interests in various spatial-temporal contexts. Second, the efficiency limitations of graph construction and graph sampling in large-scale systems make it difficult to adapt quickly to new real-time interests. To tackle the above challenges, we propose a novel Spatial-Temporal Graph Interaction Network. Specifically, we construct subgraphs of spatial, temporal, spatial-temporal, and global views respectively to precisely characterize the user's interests in various contexts. In addition, we design an industry-friendly framework to track the user's latest interests. Extensive experiments on the real-world dataset show that our method outperforms state-of-the-art models. This work has been successfully deployed in a large e-commerce platform, delivering a 1.1% CTR and 6.3% RPM improvement.Comment: accepted by CIKM 202