Measuring the difficulty of text translation: The combination of text-focused and translator-oriented approaches

This paper explores the impact of text complexity on translators’ subjective perception of translation difficulty and on their cognitive load. Twenty-six MA translation students from a UK university were asked to translate three English texts with different complexity into Chinese. Their eye movements were recorded by an eye-tracker, and their cognitive load was self-assessed with a Likert scale before translation and NASA-TLX scales after translation. The results show that: (i) the intrinsic complexity measured by readability, word frequency and non-literalness was in line with the results received from informants’ subjective assessment of translation difficulty; (ii) moderate and positive correlations existed between most items in the self-assessments and the indicator (fixation and saccade durations) obtained by the eye-tracking measurements; and (iii) the informants’ cognitive load as indicated by fixation and saccade durations (but not for pupil size) increased significantly in two of the three texts along with the increase in source text complexity

Real-time, noise and drift resilient formaldehyde sensing at room temperature with aerogel filaments

Formaldehyde, a known human carcinogen, is a common indoor air pollutant. However, its real-time and selective recognition from interfering gases remains challenging, especially for low-power sensors suffering from noise and baseline drift. We report a fully 3D-printed quantum dot/graphene-based aerogel sensor for highly sensitive and real-time recognition of formaldehyde at room temperature. By optimising the morphology and doping of the printed structures, we achieve a record-high response of 15.23 percent for 1 parts-per-million formaldehyde and an ultralow detection limit of 8.02 parts-per-billion consuming only 130 uW power. Based on measured dynamic response snapshots, we also develop an intelligent computational algorithm for robust and accurate detection in real time despite simulated substantial noise and baseline drift, hitherto unachievable for room-temperature sensors. Our framework in combining materials engineering, structural design and computational algorithm to capture dynamic response offers unprecedented real-time identification capabilities of formaldehyde and other volatile organic compounds at room temperature.Comment: Main manuscript: 21 pages, 5 figure. Supplementary: 21 pages. 13 Figures, 2 tabl

Diversity of NC10 bacteria associated with sediments of submerged Potamogeton crispus (Alismatales: Potmogetonaceae)

Background The nitrite-dependent anaerobic methane oxidation (N-DAMO) pathway, which plays an important role in carbon and nitrogen cycling in aquatic ecosystems, is mediated by “Candidatus Methylomirabilis oxyfera” (M. oxyfera) of the NC10 phylum. M. oxyfera-like bacteria are widespread in nature, however, the presence, spatial heterogeneity and genetic diversity of M. oxyfera in the rhizosphere of aquatic plants has not been widely reported. Method In order to simulate the rhizosphere microenvironment of submerged plants, Potamogeton crispus was cultivated using the rhizobox approach. Sediments from three compartments of the rhizobox: root (R), near-rhizosphere (including five sub-compartments of one mm width, N1–N5) and non-rhizosphere (>5 mm, Non), were sampled. The 16S rRNA gene library was used to investigate the diversity of M. oxyfera-like bacteria in these sediments. Results Methylomirabilis oxyfera-like bacteria were found in all three sections, with all 16S rRNA gene sequences belonging to 16 operational taxonomic units (OTUs). A maximum of six OTUs was found in the N1 sub-compartment of the near-rhizosphere compartment and a minimum of four in the root compartment (R) and N5 near-rhizosphere sub-compartment. Indices of bacterial community diversity (Shannon) and richness (Chao1) were 0.73–1.16 and 4–9, respectively. Phylogenetic analysis showed that OTU1-11 were classified into group b, while OTU12 was in a new cluster of NC10. Discussion Our results confirmed the existence of M. oxyfera-like bacteria in the rhizosphere microenvironment of the submerged plant P. crispus. Group b of M. oxyfera-like bacteria was the dominant group in this study as opposed to previous findings that both group a and b coexist in most other environments. Our results indicate that understanding the ecophysiology of M. oxyfera-like bacteria group b may help to explain their existence in the rhizosphere sediment of aquatic plant

Universal Murray's law for optimised fluid transport in synthetic structures

Materials following Murray's law are of significant interest due to their unique porous structure and optimal mass transfer ability. However, it is challenging to construct such biomimetic hierarchical channels with perfectly cylindrical pores in synthetic systems following the existing theory. Achieving superior mass transport capacity revealed by Murray's law in nanostructured materials has thus far remained out of reach. We propose a Universal Murray's law applicable to a wide range of hierarchical structures, shapes and generalised transfer processes. We experimentally demonstrate optimal flow of various fluids in hierarchically planar and tubular graphene aerogel structures to validate the proposed law. By adjusting the macroscopic pores in such aerogel-based gas sensors, we also show a significantly improved sensor response dynamic. Our work provides a solid framework for designing synthetic Murray materials with arbitrarily shaped channels for superior mass transfer capabilities, with future implications in catalysis, sensing and energy applications.Comment: 19 pages, 4 figure

Online Hedge Reservation for Diverse Plans and Competitive Analysis

In this paper, we investigate the plan reservation problem with diverse plans in mobile networks. The pricing scheme includes: 1) Pay-as-you-go (PAYG) payment; 2) All-in-one plan: an upfront fee is charged to cover data volume of a period of time; and 3) Directional plan: an upfront fee is charged to cover data volume of a specific app for a period of time. We investigate online plan reservation with competitive analysis, as the data volume is not known until an app is used. The problem is challenging as there are multiple directional plans and one all-in-one plan, creating a large decision space and complicated correlations among the decisions. We propose the Online Hedge Reservation (OHR) Algorithm to solve the problem and prove that it achieves e^beta/(e^beta-1) competitive ratio when each plan is valid till the end of each calendar month and 2e^beta/(e^beta-1) competitive ratio when each plan is valid for a full month, where beta is the ratio of prices of the directional plans and the all-in-one plan. This is an exciting neat extension of the competitive ratio e/(e-1) of the classic ski-rental problem. Finally, trace-driven simulation is conducted to further verify the advantages of the OHR Algorithm

Research advances on cytosine deaminase APOBEC1

In order to fully understand the mechanisms of Apolipoprotein B mRNA(ApoB mRNA)editing enzyme catalytic polypeptide-1(APOBEC1), this review introduced the amino acid and nucleic acid sequences of APOBEC1 and ApoB mRNA, summarized and mapped the binding models of APOBEC1 with different cofactors to explain the molecular mechanism of APOBEC1 catalyzing the deamination of the 6666 C of ApoB mRNA(C6666). The researches of rodent APOBEC1 inhibiting multiple retroviruses were exemplified here, and the related mechanisms of rabbit APOBEC1 binding to human immunodeficiency virus type 1(HIV-1)and editing the viral genome were discussed.This review also introduced APOBEC1 regulating the expression of cytokines related to cancers and other diseases by deamination editing or combining with AU-rich element (ARE)of RNAs

Controlling surface porosity of graphene-based printed aerogels

Abstract: The surface porosity of graphene-based aerogels strongly influences their performance in applications involving mass transfer. However, the factors determining the surface porosities are not well-understood, hindering their application-specific optimisation. Here, through experiments and hydrodynamic simulations, we show that the high shear stress during the graphene-based aerogel fabrication process via 3D printing leads to a non-porous surface. Conversely, crosslinking of the sheets hinders flake alignment caused by shearing, resulting in a porous surface. Our findings enable fine control of surface porosity of printed graphene-oxide aerogels (GOA) through regulation of the crosslinking agents and shear stress. Using this strategy, we demonstrate the performance advantages of GOA with porous surface over their non-porous counterpart in dye adsorption, underscoring the importance of surface porosity in certain application scenarios

Real-time, noise and drift resilient formaldehyde sensing at room temperature with aerogel filaments

Formaldehyde, a known human carcinogen, is a common indoor air pollutant. However, its real-time and selective recognition from interfering gases remains challenging, especially for low-power sensors suffering from noise and baseline drift. We report a fully 3D-printed quantum dot/graphene-based aerogel sensor for highly sensitive and real-time recognition of formaldehyde at room temperature. By optimising the morphology and doping of printed structures, we achieve a record-high and stable response of 15.23 % for 1 part-per-million formaldehyde and an ultralow detection limit of 8.02 parts-per-billion consuming only ∼130 μW power. Based on measured dynamic response snapshots, we also develop intelligent computational algorithms for robust and accurate detection in real time despite simulated substantial noise and baseline drift, hitherto unachievable for room- temperature sensors. Our framework in combining materials engineering, structural design and computational algorithm to capture dynamic response offers unprecedented real-time identification capabilities of formaldehyde and other volatile organic compounds at room temperature.EP/W024284/1, EP/W023229/1, EP/T014601/1, EP/P024947/1, EP/R00661X/

Real-time, noise and drift resilient formaldehyde sensing at room temperature with aerogel filaments

Formaldehyde, a known human carcinogen, is a common indoor air pollutant. However, its real-time and selective recognition from interfering gases remains challenging, especially for low-power sensors suffering from noise and baseline drift. We report a fully 3D-printed quantum dot/graphene-based aerogel sensor for highly sensitive and real-time recognition of formaldehyde at room temperature. By optimizing the morphology and doping of printed structures, we achieve a record-high and stable response of 15.23% for 1 part per million formaldehyde and an ultralow detection limit of 8.02 parts per billion consuming only ∼130-microwatt power. On the basis of measured dynamic response snapshots, we also develop intelligent computational algorithms for robust and accurate detection in real time despite simulated substantial noise and baseline drift, hitherto unachievable for room temperature sensors. Our framework in combining materials engineering, structural design, and computational algorithm to capture dynamic response offers unprecedented real-time identification capabilities of formaldehyde and other volatile organic compounds at room temperature