A comparative multidimensional study of the English translation of Lunyu (The Analects): a corpus-based analysis

Although Lunyu (The Analects) is well-known and often mentioned in Confucian scholarship, there have been no focused examinations of the comprehensive linguistic features of its English translations. This study seeks to report a comparative multidimensional investigation into the similarities and differences in the lexico-grammatical features of Lunyu (The Analects) translated by James Legge and Ku Hungming. The comparison is made along five functional dimensions (involved versus informational production, narrative versus nonnarrative concerns, explicit versus situation-dependent reference, overt expression of persuasion, and abstract versus non-abstract information), and the prominent lexicogrammatical features (based on a 67-item feature set) in the two texts are singled out. It is found that there are more private verbs, present tense verbs, be as main verb, past tense verbs, third-person pronouns, and public verbs in Legge’s The Analects of Confucius, whereas Ku’s The Discourses and Sayings of Confucius uses nouns, adjectives, long words, nominalisations, and time adverbials more often. The identified differences in lexico-grammatical patterns are related to the distinct goals of the two translators. The results demonstrate that the multidimensional (MD) approach is effective in differentiating the linguistic features of the two translation versions and motivating a micro-analysis of the texts, seeking to discern the translators’ underlying assumptions about the relations of Confucius and his followers. It is considered that these findings may have implications for the understanding of the translations of The Analects

A corpus-based collocational analysis of noun premodification types in academic writing

This study employs a corpus-based method in analysing the noun and noun premodification in journal articles relevant to the field of International Business Management. Following the frequency-based tradition, the noun and noun premodification are identified and extracted by using the node-and-collocate approach. The corpus is divided into five sub-corpora for the purpose of analysing the noun collocations and noun premodification types in each section and between different sections in the journal articles, namely, Introduction, Literature Review, Methods, Results and Discussion sections. The findings show that general adjective is the most common noun premodifier, followed by noun premodifier in both the Introduction and Literature Review sections, whereas general adjective and noun premodifier are both commonly used as premodifiers for nouns in Methods and Results sections. Besides, the general adjective is the most dominant premodifier in Discussion section. The findings also indicate that ed-participial and ing-participial premodifiers are not commonly used in the relevant journal articles. With regard to the use of noun premodification types between different sections in journal articles, general adjective+noun collocation is more pervasive in Introduction, Literature Review and Discussion sections. On the other hand, noun+noun collocation is more commonly found in Methods and Results sections. Following Hoey’s Lexical Priming, the results show that priming occurs at grammatical level within the discourse. The noun collocations identified are compiled for the possible use in the English for Academic Purposes Course

Compact hollow waveguide mid-infrared gas sensor for simultaneous measurements of ambient CO2 and water vapor

A compact, sensitive and stable hollow waveguide (HWG) mid-infrared gas sensor, based on gas absorption lines using wavelength modulation spectroscopy with a second harmonic (WMS-2f) detection scheme, was developed for simultaneous measurements of ambient CO 2 and water vapor. Optimization of the laser modulation parameters and pressure parameter in the HWG are performed to improve the strength of the WMS-2f signal and hence the detection limit, where 14.5-time for CO 2 and 8.5-time for water vapor improvement in system detection limit is achieved compared to those working at 1 atm. The stability of the sensor has been improved significantly by optimizing environmental disturbances, incoupling alignment of the HWG and laser scanning frequency. An Allan variance analysis shows detection limit of the developed sensor of ~3 ppmv for CO 2 and 0.018% for water vapor, which correspond to an absorbance of 2.4 × 10 -5 and 2.7 × 10 -5 , with a stability time of 160 s, respectively. Ambient CO 2 and water vapor measurement have been performed in two days in winter and spring separately. The measurement precision is further improved by applying a Kalman adaptive filter. The HWG gas sensor demonstrates the ability in environmental monitoring and the potential to be used in other areas, such as industrial production and biomedical diagnosis

What has Changed? Stance and Engagement in Mahathir Mohamad’s UNGA Speeches

The analysis of language in communication is not only the analysis of propositional information, but also the analysis of how speakers and writers express their ideas (Hyland, 2008). The speaker/writer-audience interaction becomes an important site for language analysts as this interaction reflects the speakers and writers’ purposes and provides a tool in understanding language use. As Hyland (2001a) proposes that the success of a dialogue with the audience depends largely on a balance between the language users’ claims and their assumptions of the audiences. Stance and engagement commonly addressing to the audiences explicitly are rhetorical ways to achieve this interaction. These rhetorical strategies allow language users to invoke the readers and to include them as participants by assuming their possible reactions and knowledge. Past studies on stance and engagement have mainly focused on written discourse (e.g., Crosthwaite, Cheung, & Jiang, 2017; Hyland, 2001b; Hyland & Jiang, 2016; Jiang & Ma, 2018). These studies suggest something of writers’ senses to imagine the potential audiences. Despite the current massive interest in stance and engagement, spoken discourse is a disregarded discourse which has largely escaped the notice of language analysts. This study thus addresses this research gap, offering an account of Mahathir Mohamad’s two public speeches at United Nations General Assembly (UNGA) in the years of 1999 and 2018, respectively. This account will seek to establish if there exist certain interaction achieved by stance and engagement in his UNGA speeches. In addition, this study will try to determine whether there is any change of using these rhetorical strategies in the years of 1999 and 2018. Scholars concern the changes in written discourse. For instance, Hyland and Jiang (2017) investigate the changes of academic writing and find that academic writing has become more informal in recent years. We know little of the changes in the use of rhetorical strategies in spoken discourse. The interest in Mahathir Mohamad’s speeches lies in that his speeches gain attention from scholars, such as in the field of Critical Discourse Analaysis (CDA) (David & Dumanig, 2011; Mohammed Shukry, 2013), and politics (Milne & Mauzy, 1999; Hwang, 2003). Few studies have been found in examining rhetorical resources. Speeches at UNGA have enormous global significance. Does Mahathir Mohamad construct engagement with audiences in the years of 1999 and 2018 the same way? Are there similarities and differences in the use of stance and engagement between the two speeches? This study aims to address these questions. The following section discusses the methodology in this study

Modality in spoken Malaysian English: a comparison with the supervarieties

The interest in Malaysian English generated many studies on Malaysian English focusing on various grammatical features. However, modality in Malaysian English is still under-researched, especially in post-independence and new Englishes contexts. As a new variety of English, it raises questions on how Malaysian English has developed from the historical input variety, i.e., British English and how resistant or accepting Malaysian English is to American English which is highly influential globally. This study aimed to contribute to the development of Malaysian English studies by reporting a corpus-based research of the frequency and statistical differences of a set of modal and quasi-modal verbs in three spoken corpora representing Malaysian, British, and American English. AntConc software (Version 3.5.9) (Anthony, 2020) was used to explore and generate the relevant data in the spoken Malaysian English corpus, while the spoken British and American English corpora were accessed online using the tools on the respective websites. The findings show that the use of modal and quasi-modal verbs in spoken Malaysian English does not entirely resemble either of the Supervarieties, i.e., spoken British English and American English. Log-likelihood test carried out in the study shows significant differences in the use of certain modal and quasi-modal verbs between the varieties, suggesting that Supervarieties are not always in the lead in using quasi-modals. The results also suggest that these significant differences are mainly accounted for by the nativisation process and evolution of Malaysian English as a new English variety. The findings shed new light on the current knowledge of modal and quasi-modal verbs in post-independence spoken Malaysian English

Inferring Tabular Analysis Metadata by Infusing Distribution and Knowledge Information

Many data analysis tasks heavily rely on a deep understanding of tables (multi-dimensional data). Across the tasks, there exist comonly used metadata attributes of table fields / columns. In this paper, we identify four such analysis metadata: Measure/dimension dichotomy, common field roles, semantic field type, and default aggregation function. While those metadata face challenges of insufficient supervision signals, utilizing existing knowledge and understanding distribution. To inference these metadata for a raw table, we propose our multi-tasking Metadata model which fuses field distribution and knowledge graph information into pre-trained tabular models. For model training and evaluation, we collect a large corpus (~582k tables from private spreadsheet and public tabular datasets) of analysis metadata by using diverse smart supervisions from downstream tasks. Our best model has accuracy = 98%, hit rate at top-1 > 67%, accuracy > 80%, and accuracy = 88% for the four analysis metadata inference tasks, respectively. It outperforms a series of baselines that are based on rules, traditional machine learning methods, and pre-trained tabular models. Analysis metadata models are deployed in a popular data analysis product, helping downstream intelligent features such as insights mining, chart / pivot table recommendation, and natural language QA...Comment: 13pages, 7 figures, 9 table

MiRKAT-MC: A Distance-Based Microbiome Kernel Association Test With Multi-Categorical Outcomes

Increasing evidence has elucidated that the microbiome plays a critical role in many human diseases. Apart from continuous and binary traits that measure the extent or presence of a disease, multi-categorical outcomes including variations/subtypes of a disease or ordinal levels of disease severity are commonly seen in clinical studies. On top of that, studies with clustered design (i.e., family-based and longitudinal studies) are popular alternatives to population-based ones as they are able to identify characteristics on both individual and population levels and to investigate the trajectory of traits of interest over time. However, existing methods for microbiome association analysis are inadequate to handle multi-categorical outcomes, neither independent nor clustered data. We propose a microbiome kernel association test with multi-categorical outcomes (MiRKAT-MC). Our method is versatile to deal with both nominal and ordinal outcomes for independent and clustered data. In addition, it incorporates multiple ecological distances to allow for different association patterns between outcomes and microbiome compositions to be incorporated. A computationally efficient pseudo-permutation strategy is used to evaluate the statistical significance. Comprehensive simulations show that MiRKAT-MC preserves the nominal type I error and increases statistical powers under various scenarios and data types. We also apply MiRKAT-MC to real data sets with nominal and ordinal outcomes to gain biological insights. MiRKAT-MC is easy to implement, and freely available via an R package at https://github.com/Zhiwen-Owen-Jiang/MiRKATMC with a Graphical User Interface through R Shinny also available

Comparison of clinical outcomes in critical patients undergoing different mechanical ventilation modes: a systematic review and network meta-analysis

PurposeTo evaluate the effects of different mechanical ventilation modes on critical patients.MethodsPubMed, Embase, Web of science, and Cochrane Library databases were searched from their inception to November 15, 2022 for randomized controlled trials on the application of different mechanical ventilation modes in critical patients. Two researchers independently screened the literature, extracted data, and assessed the risk of bias in the included studies. R4.2.1 was used for this network meta-analysis.ResultsTwenty-eight RCTs involving 3,189 patients were included. The interventions in these RCTs included NAVA (neurally adjusted ventilatory assist), PAV (proportional assist ventilation), ASV (adaptive support ventilation), Smartcare/PS (Smartcare/pressure support), PSV (pressure support ventilation), PSV_ATC (pressure support ventilation_automatic tube compensation), and SIMV (synchronized intermittent mandatory ventilation). The network meta-analysis showed that, compared with the PSV group, there was no significant difference in duration of mechanical ventilation, duration of ICU stay, and hospital stay between NAVA, SIMV, AVS, PAV, Smartcare/PS, and PSV_ATC groups. Compared with PSV, PAV improved the success rate of withdrawal of ventilator [OR = 3.07, 95%CI (1.21, 8.52)]. Compared with PSV and PAV, NAVA reduced mortality in the ICU [OR = 0.63, 95%CI (0.43, 0.93); OR = 0.45, 95%CI (0.21, 0.97)].ConclusionNAVA can reduce mortality in ICU, and PAV may increase the risk of withdrawal of the ventilator. There was no significant difference between PSV and other mechanical ventilation modes (NAVA, SIMV, AVS, PAV, Smartcare/PS, and PSV_ATC) in the duration of mechanical ventilation, duration of ICU stay, or hospital stay. Due to the limitations, more high-quality studies are needed to verify these findings

Mg3(Bi,Sb)2 single crystals towards high thermoelectric performance

The rapid growth of the thermoelectric cooler market makes the development of novel room temperature thermoelectric materials of great importance. Ternary n-type Mg3(Bi,Sb)2 alloys are promising alternatives to the state-of-the-art Bi2(Te,Se)3 alloys but grain boundary resistance is the most important limitation. n-type Mg3(Bi,Sb)2 single crystals with negligible grain boundaries are expected to have particularly high zT but have rarely been realized due to the demanding Mg-rich growth conditions required. Here, we report, for the first time, the thermoelectric properties of n-type Mg3(Bi,Sb)2 alloyed single crystals grown by a one-step Mg-flux method using sealed tantalum tubes. High weighted mobility ∼140 cm2 V−1 s−1 and a high zT of 0.82 at 315 K are achieved in Y-doped Mg3Bi1.25Sb0.75 single crystals. Through both experimental angle-resolved photoemission spectroscopy and theoretical calculations, we denote the origin of the high thermoelectric performance from a point of view of band widening effect and electronegativity, as well as the necessity to form high Bi/Sb ratio ternary Mg3(Bi,Sb)2 alloys. The present work paves the way for further development of Mg3(Bi,Sb)2 for near room temperature thermoelectric applications