GRI: Graph-based Relative Isomorphism of Word Embedding Spaces

Automated construction of bilingual dictionaries using monolingual embedding spaces is a core challenge in machine translation. The end performance of these dictionaries relies upon the geometric similarity of individual spaces, i.e., their degree of isomorphism. Existing attempts aimed at controlling the relative isomorphism of different spaces fail to incorporate the impact of semantically related words in the training objective. To address this, we propose GRI that combines the distributional training objectives with attentive graph convolutions to unanimously consider the impact of semantically similar words required to define/compute the relative isomorphism of multiple spaces. Experimental evaluation shows that GRI outperforms the existing research by improving the average P@1 by a relative score of up to 63.6%. We release the codes for GRI at https://github.com/asif6827/GRI

New Construction of Identity-based Proxy Re-encryption

A proxy re-encryption (PRE) scheme involves three parties: Alice, Bob, and a proxy. PRE allows the proxy to translate a ciphertext encrypted under Alice\u27s public key into one that can be decrypted by Bob\u27s secret key. We present a general method to construct an identity-based proxy re-encryption scheme from an existing identity-based encryption scheme. The transformed scheme satisfies the properties of PRE, such as unidirectionality, non-interactivity and multi-use. Moreover, the proposed scheme has master key security, allows the encryptor to decide whether the ciphertext can be re-encrypted

MCNTs@MnO2 nanocomposite cathode integrated with soluble O2-carrier Co-salen in electrolyte for high-performance Li-air batteries

Li–air batteries (LABs) are promising because of their high energy density. However, LABs are troubled by large electrochemical polarization during discharge and charge, side reactions from both carbon cathode surface/peroxide product and electrolyte/superoxide intermediate, as well as the requirement for pure O2. Here we report the solution using multiwall carbon nanotubes (MCNTs)@MnO2 nanocomposite cathode integrated with N,N′-bis(salicylidene)ethylenediaminocobalt(II) (CoII-salen) in electrolyte for LABs. The advantage of such a combination is that on one hand, the coating layer of δ-MnO2 with about 2–3 nm on MCNTs@MnO2 nanocomposite catalyzes Li2O2 decomposition during charge and suppresses side reactions between product Li2O2 and MCNT surface. On the other hand, CoII-salen works as a mobile O2-carrier and accelerates Li2O2 formation through the reaciton of (CoIII-salen)2-O22– + 2Li+ + 2e– → 2CoII-salen + Li2O2. This reaction route overcomes the pure O2 limitation and avoids the formation of aggressive superoxide intermediate (O2– or LiO2), which easily attacks organic electrolyte. By using this double-catalyst system of Co-salen/MCNTs@MnO2, the lifetime of LABs is prolonged to 300 cycles at 500 mA g–1 (0.15 mA cm–2) with fixed capacity of 1000 mAh g–1 (0.30 mAh cm–2) in dry air (21% O2). Furthermore, we up-scale the capacity to 500 mAh (5.2 mAh cm–2) in pouch-type batteries (∼4 g, 325 Wh kg–1). This study should pave a new way for the design and construction of practical LABs

G2PTL: A Pre-trained Model for Delivery Address and its Applications in Logistics System

Text-based delivery addresses, as the data foundation for logistics systems, contain abundant and crucial location information. How to effectively encode the delivery address is a core task to boost the performance of downstream tasks in the logistics system. Pre-trained Models (PTMs) designed for Natural Language Process (NLP) have emerged as the dominant tools for encoding semantic information in text. Though promising, those NLP-based PTMs fall short of encoding geographic knowledge in the delivery address, which considerably trims down the performance of delivery-related tasks in logistic systems such as Cainiao. To tackle the above problem, we propose a domain-specific pre-trained model, named G2PTL, a Geography-Graph Pre-trained model for delivery address in Logistics field. G2PTL combines the semantic learning capabilities of text pre-training with the geographical-relationship encoding abilities of graph modeling. Specifically, we first utilize real-world logistics delivery data to construct a large-scale heterogeneous graph of delivery addresses, which contains abundant geographic knowledge and delivery information. Then, G2PTL is pre-trained with subgraphs sampled from the heterogeneous graph. Comprehensive experiments are conducted to demonstrate the effectiveness of G2PTL through four downstream tasks in logistics systems on real-world datasets. G2PTL has been deployed in production in Cainiao's logistics system, which significantly improves the performance of delivery-related tasks

Experimental study on mix proportion of transparent similar materials for rock mass

Traditional rock mass is opaque and the internal deformation and fracture process cannot be observed directly, using transparent materials to make similar models is an effective solution. E-44 type epoxy resin is used as aggregate, triethanolamine is used as curing agent, and alcohol rosin saturated solution (RSS) is added to adjust brittleness. Based on comprehensive experimental methods, the influence of the ratio of epoxy resin to triethanolamine and the content of RSS on the density, uniaxial compressive strength, peak strain, elastic modulus, tensile strength, cohesion and friction angle of transparent rock mass are studied in series. The results show that the ratio of epoxy resin to triethanolamine plays a leading role in the compressive strength, elastic modulus, tensile strength, cohesion and friction angle of similar transparent materials, while the content of the RSS plays a leading role in the density and peak strain. The density and peak strain is positively correlated with the ratio of epoxy resin to triethanolamine, and negatively correlated with the content of RSS. When the ratio of epoxy resin to triethanolamine is 3∶1, the compressive strength of the specimen is negatively correlated with the content of RSS, while at other ratios, the compressive strength does not change significantly. The elastic modulus and friction angle of the test piece is positively correlated with the ratio of epoxy resin and triethanolamine. When the ratio of epoxy resin to triethanolamine is 3∶1, the elastic modulus of the test piece is negatively correlated with the content of RSS. While at other ratios, the elastic modulus of the specimen is positively correlated with the content of RSS. The tensile strength and cohesion decreased with the increase of RSS content, and first increased and then decreased with the increase of the ratio of epoxy resin to triethanolamine. In the same ratio of epoxy resin to triethanolamine, the tensile strength was negatively correlated with RSS content. Based on multiple linear regression analysis, an empirical formula between the mechanical properties of transparent rock mass and the ratio of epoxy resin to triethanolamine and RSS content is established, which provides a reference for the proportion of similar materials in transparent rock mass

Perioperative probiotics attenuates postoperative cognitive dysfunction in elderly patients undergoing hip or knee arthroplasty: A randomized, double-blind, and placebo-controlled trial

BackgroundPostoperative cognitive dysfunction (POCD) is a common complication in elderly patients following surgery. The preventive and/or treatment strategies for the incidence remain limited.ObjectiveThis study aimed to investigate the preventive effect of perioperative probiotic treatment on POCD in elderly patients undergoing hip or knee arthroplasty.MethodsAfter obtaining ethical approval and written informed consent, 106 patients (age ≥60 years) were recruited, who scheduled elective hip or knee arthroplasty, from 16 March 2021 to 25 February 2022 for this randomized, double-blind, and placebo-controlled trial. They were randomly assigned with a 1:1 ratio to receive either probiotics or placebo treatment (four capsules, twice/day) from hospital admission until discharge. Cognitive function was assessed with a battery of 11 neuropsychological tests on the admission day and the seventh day after surgery, respectively.ResultsA total of 96 of 106 patients completed the study, and their data were finally analyzed. POCD occurred in 12 (26.7%) of 45 patients in the probiotic group and 29 (56.9%) of 51 patients in the placebo group (relative risk [RR], 0.47 [95% confidence interval [CI], 0.27 to 0.81]; P = 0.003). Among them, mild POCD occurred in 11 (24.4%) in the probiotic group and 24 (47.1%) in the placebo group (RR, 0.52 [95% CI, 0.29 to 0.94]; P = 0.022). No significant difference in severe POCD incidence was found between the two groups (P = 0.209). Compared with the placebo group, the verbal memory domain cognitive function was mainly improved in the probiotic group.ConclusionProbiotics may be used perioperatively to prevent POCD development and improve verbal memory performance in elderly patients receiving hip or knee arthroplasty.Clinical trial registrationwww.chictr.org.cn, identifier: ChiCTR2100045620