A study on machine translation of resultative constructions

Based on an empirical investigation on data collected from four popular machine translation systems, this paper explores the current problems machine translation is confronted with in translating Chinese resultative constructions into English. The paper analyzes their syntactic and semantic differences in construction and in verbal pattern. The paper then further elaborates on the problems and reveals a truth that Chinese resultative construction poses a great challenge to machine translation for being very productive and flexible. Its productivity is credited to the fact that the main verbs in Chinese are mostly implied-fulfillment verbs. Its flexibility could be attributed to the hypothesis that there are fewer constraints on the co-occurrence of the main verb and the resultative in Chinese resultative construction. Finally, possible solutions are proposed in an attempt to solve the problems.

Marked causative structures of Chinese verb-resultative construction

This paper aims to study the syntactic and semantic features of ‘marked VRC causative structures’, those special syntactic-semantic structures formed by verb-resultative constructions (VRCs) which violate both the Uniformity of Theta Assignment Hypothesis and the Thematic Hierarchy. Their syntactic and semantic features are defined as follows: 1) VRC has a causative relation within itself; 2) the argument in the object position is the causee and the only argument of the resultative complement; 3) the causer in the subject position is any conceptual component from the cause event other than the agent of the predicate verb. This paper then attempts to propose an extended account to expound how they are formed syntactically and semantically. On this account, a marked VRC causative structure is re-causativization of a VRC when the VRC is self-causative; it enables other conceptual components of the cause event than the agent to become the causer when a VRC is not self-causative. There are some constraints on what becomes the causer of a marked VRC causative structure

The positive response in grape secondary metabolites under controlled stresses: a review

Grapevine is cultivated worldwide with great economic importance. In recent years, our knowledge of the physiological and molecular basis of berry quality regulation has substantially increased. Abiotic and biotic stresses, such as deficit irrigation, low temperature, light/UV and microbes, to a certain extent, could improve grape berry quality by enhancing flavor metabolites, colorization or aroma compounds. This review summarizes recent data related to the stress of grape berry development, with special emphasis on secondary metabolism and its response to stresses. A full understanding of how grape berry metabolism responds to different stresses is important to improve the biochemical qualities of grapes and resultant products, such as wine in practice

Optimal Resource Allocation for U-Shaped Parallel Split Learning

Split learning (SL) has emerged as a promising approach for model training without revealing the raw data samples from the data owners. However, traditional SL inevitably leaks label privacy as the tail model (with the last layers) should be placed on the server. To overcome this limitation, one promising solution is to utilize U-shaped architecture to leave both early layers and last layers on the user side. In this paper, we develop a novel parallel U-shaped split learning and devise the optimal resource optimization scheme to improve the performance of edge networks. In the proposed framework, multiple users communicate with an edge server for SL. We analyze the end-to-end delay of each client during the training process and design an efficient resource allocation algorithm, called LSCRA, which finds the optimal computing resource allocation and split layers. Our experimental results show the effectiveness of LSCRA and that U-shaped PSL can achieve a similar performance with other SL baselines while preserving label privacy. Index Terms: U-shaped network, split learning, label privacy, resource allocation, 5G/6G edge networks.Comment: 6 pages, 6 figure

Capacity scaling of multihop cellular networks

Abstract—Wireless cellular networks are large-scale networks in which asymptotic capacity investigation is no longer a cliché. A substantial body of work has been carried out to improve the capacity of cellular networks by introducing ad hoc communica-tions, resulting in the so-called multihop cellular networks. Most of the previous research allows ad hoc transmissions between certain source and destination pairs to alleviate base stations’ relay burden. However, since reports show that Internet data traffic is becoming more and more dominant in cellular networks, we explore in this paper the capacity of multihop cellular networks with all traffic going through base stations and ad hoc transmissions only acting as relay. We first investigate the capacity of regular multihop cellular networks where both nodes and base stations are regularly placed. By fully exploiting the link rate variability, we find that multihop cellular networks can have higher per-node throughput than traditional cellular networks by a scaling factor of log 2 푛. Then, for the first time we extend our study to the capacity of heterogeneous multihop cellular networks where nodes are distributed according to a general Inhomogeneous Poisson Process and base stations are randomly placed. We show that under certain conditions multihop cellular networks can also outperform traditional cellular networks by a scaling factor of log 2 푛. Moreover, both throughput-fairness and bandwidth-fairness are considered as fairness constraints for both kinds of networks. I

Cellular trafficking of Sn-2 phosphatidylcholine prodrugs studied with fluorescence lifetime imaging and super-resolution microscopy

While th

ανβ3-targeted copper nanoparticles incorporating an Sn 2 lipase-labile fumagillin prodrug for photoacoustic neovascular imaging and treatment

licenses/by-nc-nd/3.0/). Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited. Received: 2014.06.30; Accepted: 2014.09.18; Published: 2015.01.01 Photoacoustic (PA) tomography enables multiscale, multicontrast and high-resolution imaging of biological structures. In particular, contrast-enhanced PA imaging offers high-sensitivity noninva-sive imaging of neovessel sprout formation and nascent tubules, which are important biomarkers of malignant tumors and progressive atherosclerotic disease. While gold nanoparticles or nano-rods have been used as PA contrast agents, we utilized high-density copper oleate small molecules encapsulated within a phospholipid surfactant (CuNPs) to generate a soft nanoparticle with PA contrast comparable to that from gold. Within the NIR window, the copper nanoparticles pro-vided a 4-fold higher signal than that of blood. ανβ3-integrin targeting of CuNPs in a MatrigelTM angiogenesis mouse model demonstrated prominent (p<0.05) PA contrast enhancement of th

Photoacoustic molecular imaging of angiogenesis using theranostic α_νβ_3-targeted copper nanoparticles incorporating a sn-2 lipase-labile fumagillin prodrug

Photoacoustic (PA) tomography imaging is an emerging, versatile, and noninvasive imaging modality, which combines the advantages of both optical imaging and ultrasound imaging. It opens up opportunities for noninvasive imaging of angiogenesis, a feature of skin pathologies including cancers and psoriasis. In this study, high-density copper oleate encapsulated within a phospholipid surfactant (CuNPs) generated a soft nanoparticle with PA contrast comparable to gold. Within the near-infrared window, the copper nanoparticles can provide a signal more than 7 times higher that of blood. Α_νβ_3-targeted of CuNPs in a Matrigel mouse model demonstrated prominent PA contrast enhancement of the neovasculature compared to mice given nontargeted or competitively inhibited CuNPs. Incorporation of a sn-2 lipase-labile fumagillin prodrug into the CuNPs produced marked antiangiogenesis in the same model, demonstrating the theranostic potential of a PA agent for the first time in vivo. With a PA signal comparable to gold-based nanoparticles yet a lower cost and demonstrated drug delivery potential, α_νβ_3-targeted CuNPs hold great promise for the management of skin pathologies with neovascular features

α_νβ_3-targeted Copper Nanoparticles Incorporating an Sn 2 Lipase-Labile Fumagillin Prodrug for Photoacoustic Neovascular Imaging and Treatment

Photoacoustic (PA) tomography enables multiscale, multicontrast and high-resolution imaging of biological structures. In particular, contrast-enhanced PA imaging offers high-sensitivity noninvasive imaging of neovessel sprout formation and nascent tubules, which are important biomarkers of malignant tumors and progressive atherosclerotic disease. While gold nanoparticles or nanorods have been used as PA contrast agents, we utilized high-density copper oleate small molecules encapsulated within a phospholipid surfactant (CuNPs) to generate a soft nanoparticle with PA contrast comparable to that from gold. Within the NIR window, the copper nanoparticles provided a 4-fold higher signal than that of blood. Α_νβ_3-integrin targeting of CuNPs in a Matrigel™ angiogenesis mouse model demonstrated prominent (p<0.05) PA contrast enhancement of the neovasculature compared with mice given nontargeted or competitively inhibited CuNPs. Furthermore, incorporation of a Sn 2 lipase-labile fumagillin prodrug into the CuNP outer lipid membrane produced marked antiangiogenesis in the same model when targeted to the α_νβ_3-integrin, providing proof of concept in vivo for the first targeted PA - drug delivery agent