A regional digital bathymetric model fusion method based on topographic slope: A case study of the south China sea and surrounding waters.

High-resolution seafloor topography is important in scientific research and marine engineering in regard to marine resource development and environmental protection monitoring. In this study, multi-dimensional comparisons were made between GEBCO_2022, SRTM15_V2.5.5, SRTM30_PLUS, SYNBATH_V1.0, ETOPO_2022, and topo_25.1 in the South China Sea and surrounding waters (SCS). This study has found that ETOPO_2022 had the best overall accuracy and reliability. Based on the results of the model accuracy analysis and by considering the topographic slope, ETOPO_2022, GEBCO_2022, and SRTM15_V2.5.5 were weighted and fused to form a fusion model. The error of the fusion model was 94.80% concentrated in (-100-100 m). When compared with GEBCO_2022, SRTM15_V2.5.5, SRTM30_PLUS, SYNBATH_V1.0, ETOPO_2022, and topo_25.1, the RMSE was reduced by 2%, 9%, 62%, 15%, 1%, and 73%, respectively. The slope-based weighted fusion method has been shown that it can overcome the limitations of a single data source and provide a reference for timely reconstruction and updating of large-scale seafloor topography.

Reconsidering the syntactic complexity measures on L2 spoken English: A multi-dimensional perspective.

Based on a review of previous measures employed in English syntactic complexity investigation, this article, following Biber's Multi-dimensional approach, re-establishes a comprehensive new measure system which is composed of four dimensions i.e. Subordination, Length of Production, Coordination and Nominals using factor analysis upon a collection of indices in reference. Under the newly established framework, the research examines the effects of grade level and genre factors on second language English learners' syntactic complexity in oral English in terms of the four indices representing the four dimensions. ANOVA results show that all indices except C/T, the one representing the Subordination dimension, which shows stability across grade levels, are positively related with grade level and susceptible to genre. In the argumentative genre, students generally produce more complex sentences than in the narrative genre as regards all the four dimensions.

A corpus-based analysis of the stylistic features of Chinese and American diplomatic discourse.

The study investigates the linguistic aspects of Chinese and American diplomatic discourse using Biber's theoretical underpinnings of multi-dimensional (MD) analysis. The corpus of the study comprises texts taken from the official websites of the Chinese and US governments from 2011 to 2020. The study results show that China's diplomatic discourse falls into the text type of learned exposition which includes informational expositions focused on conveying information. In contrast, the United States diplomatic discourse falls into the text type of "involved persuasion," which is persuasive and argumentative. Furthermore, the two-way ANOVA test reveals few distinctions between spoken and written diplomatic discourse from the same country. Furthermore, T-tests demonstrate that the diplomatic discourse of the two countries differs significantly in three dimensions. In addition, the study highlights that China's diplomatic discourse is informationally dense and context independent. In contrast, the United States diplomatic discourse is emotive and interactional, strongly dependent on context, and created within time restrictions. Finally, the study's findings contribute to a systematic knowledge of the genre aspects of diplomatic discourse and are helpful for more effective diplomatic discourse system creation.

VIVID: A Web Application for Variant Interpretation and Visualization in Multi-dimensional Analyses.

Large-scale comparative genomics- and population genetic studies generate enormous amounts of polymorphism data in the form of DNA variants. Ultimately, the goal of many of these studies is to associate genetic variants to phenotypes or fitness. We introduce VIVID, an interactive, user-friendly web application that integrates a wide range of approaches for encoding genotypic to phenotypic information in any organism or disease, from an individual or population, in three-dimensional (3D) space. It allows mutation mapping and annotation, calculation of interactions and conservation scores, prediction of harmful effects, analysis of diversity and selection, and 3D visualization of genotypic information encoded in Variant Call Format on AlphaFold2 protein models. VIVID enables the rapid assessment of genes of interest in the study of adaptive evolution and the genetic load, and it helps prioritizing targets for experimental validation. We demonstrate the utility of VIVID by exploring the evolutionary genetics of the parasitic protist Plasmodium falciparum, revealing geographic variation in the signature of balancing selection in potential targets of functional antibodies.

The tone atlas of perceptual discriminability and perceptual distance: Four tone languages and five language groups.

Some prior investigations suggest that tone perception is flexible, reasonably independent of native phonology, whereas others suggest it is constrained by native phonology. We address this issue in a systematic and comprehensive investigation of adult tone perception. Sampling from diverse tone and non-tone speaking communities, we tested discrimination of the three major tone systems (Cantonese, Thai, Mandarin) that dominate the tone perception literature, in relation to native language and language experience as well as stimulus variation (tone properties, presentation order, pitch cues) using linear mixed effect modelling and multidimensional scaling. There was an overall discrimination advantage for tone language speakers and for native tones. However, language- and tone-specific effects, and presentation order effects also emerged. Thus, over and above native phonology, stimulus variation exerts a powerful influence on tone discrimination. This study provides a tone atlas, a reference guide to inform empirical studies of tone sensitivity, both retrospectively and prospectively.

Analyzing vehicle-pedestrian interactions: Combining data cube structure and predictive collision risk estimation model.

Road traffic accidents are a severe threat to human lives, particularly to vulnerable road users (VRUs) such as pedestrians causing premature deaths. Therefore, it is necessary to devise systems to prevent accidents in advance and respond proactively, using potential risky situations as one of the surrogate safety measurements. This study introduces a new concept of a pedestrian safety system that combines the field and the centralized processes. The system can warn of upcoming risks immediately in the field and improve the safety of risk-frequent areas by assessing the safety levels of roads without actual collisions. In particular, this study focuses on the latter by introducing a new analytical framework for a crosswalk safety assessment with various behaviors of vehicles/pedestrians and environmental features. We obtain these behavioral features from actual traffic video footages in the city with complete automatic processing. The proposed framework mainly analyzes these behaviors in multi-dimensional perspectives by constructing a data cube structure, which combines the Long Short-Term Memory (LSTM)-based predictive collision risk (PCR) estimation model and the on-line analytical processing (OLAP) operations. From the PCR estimation model, we categorize the severity of risks as four levels; "relatively safe," "caution," "warning," and "danger," and apply the proposed framework to assess the crosswalk safety with behavioral features. With the proposed framework, the various descriptive results are harvested, but we aim at conducting analysis based on two scenarios in our analytic experiments; the movement patterns of vehicles and pedestrians by road environment and the relationships between risk levels and car speeds. Consequently, the proposed framework can support decision-makers (e.g., urban planners, safety administrators) by providing the valuable information to improve pedestrian safety for future accidents, and it can help us better understand cars' and pedestrians' proactive behavior near the crosswalks. In order to confirm the feasibility and applicability of the proposed framework, we implement and apply it to actual operating CCTVs in Osan City, Republic of Korea.

Characterising Online News Comments: A Multi-Dimensional Cruise Through Online Registers.

News organisations often allow public comments at the bottom of their news stories. These comments constitute a fruitful source of data to investigate linguistic variation online; their characteristics, however, are rather understudied. This paper thus contributes to the description of online news comments and online language in English. In this spirit, we apply multi-dimensional analysis to a large dataset of online news comments and compare them to a corpus of online registers, thus placing online comments in the space of register variation online. We find that online news comments are involved-evaluative and informational at the same time, but mostly argumentative in nature, with such argumentation taking an informal shape. Our analyses lead us to conclude that online registers are a different mode of communication, neither spoken nor written, with individual variation across different types of online registers.

SafetyCube: Framework for potential pedestrian risk analysis using multi-dimensional OLAP.

In the past decade, the number of road traffic accidents and fatalities has remained about the same level. One of strategies to protect vulnerable road users (VRUs) is to analyze the factors that cause traffic accident and then to deploy safety facilities. However, most traffic safety systems currently in operation rely on historical data, which is post-facto approach. Thus, it is necessary to prevent accident in advance and to respond in proactive manner before the accident. In this study, we propose a framework for potential pedestrian risk analysis using a multi-dimensional on-line analytical processing (OLAP), called SafetyCube, which enables decision-makers to understand the situations by scrutinizing interactive behaviors between vehicle and pedestrian. First, we collect the behavioral features of traffic-related objects (e.g., vehicles and pedestrians) extracted from closed circuit televisions (CCTVs) deployed on crosswalks throughout the overall urban, and accumulate them in a data warehouse over an extended period in order to construct a data cube model. Then, we conduct comprehensive analyses in multi-dimensional perspective using OLAP operations by varying the abstraction levels. Our analytical experiments are based on three scenarios, and the results show that the vehicle's movement patterns before entering the crosswalk, patterns of changes in speed of vehicles approaching to pedestrians, and so on. Through these results from the proposed analytical system, decision-makers can gain a better understanding of how the vehicles and pedestrians behave near the crosswalk by visualizing their interactions. Further, these insights would be reflected to improve the road environment safer. In order to validate the feasibility and applicability of the proposed system, we apply it to various crosswalks in Osan city, South Korea.

Metabolic GWAS-based dissection of genetic bases underlying the diversity of plant metabolism.

Plants have served as sources providing humans with metabolites for food and nutrition, biomaterials for living, and treatment for pain and disease. Plants produce a huge array of metabolites, with an immense diversity at both the population and individual levels. Dissection of the genetic bases for metabolic diversity has attracted increasing research attention. The concept of genome-wide association study (GWAS) was extended to studies on the diversity of plant metabolome that benefitted from the development of mass-spectrometry-based analytical systems and genome sequencing technologies. Metabolic genome-wide association study (mGWAS) is one of the most powerful tools for global identification of genetic determinants for diversity of plant metabolism. Recently, mGWAS has been performed for various species with continuous improvements, providing deeper insights into the genetic bases of metabolic diversity. In this review, we discuss fully the achievements to date and remaining challenges that are associated with both mGWAS and mGWAS-based multi-dimensional analysis. We begin with a summary of GWAS and its development based on statistical methods and populations. As variation in targeted traits is essential for GWAS, we review metabolic diversity and its rise at both the population and individual levels. Subsequently, the application of mGWAS for plants and its corresponding achievements are fully discussed. We address the current knowledge on mGWAS-based multi-dimensional analysis and emerging insights into the diversity of metabolism.

Human Genetic Epidemiology Using R.

This chapter illustrates the biostatistical human genetics with an introduction to the T-Test, and the Manhattan Plots in statistics using Human Genetic Data concepts leading to procedures for Statistical Tests and Utilities for Genetic Association. Several R packages are chosen: iGasso, GenABEL, and HardyWeinberg. Other topics discussed include: Regression Decision Trees and Classifications Multi-dimensional Analysis in Genetic Epidemiology Regression Decision Trees and Classifications.

A high-throughput 2D-analytical technique to obtain single protein parameters from complex cell lysates for in silico process development of ion exchange chromatography.

The accelerating growth of the market for biopharmaceutical proteins, the market entry of biosimilars and the growing interest in new, more complex molecules constantly pose new challenges for bioseparation process development. In the presented work we demonstrate the application of a multidimensional, analytical separation approach to obtain the relevant physicochemical parameters of single proteins in a complex mixture for in silico chromatographic process development. A complete cell lysate containing a low titre target protein was first fractionated by multiple linear salt gradient anion exchange chromatography (AEC) with varying gradient length. The collected fractions were subsequently analysed by high-throughput capillary gel electrophoresis (HT-CGE) after being desalted and concentrated. From the obtained data of the 2D-separation the retention-volumes and the concentration of the single proteins were determined. The retention-volumes of the single proteins were used to calculate the related steric-mass action model parameters. In a final evaluation experiment the received parameters were successfully applied to predict the retention behaviour of the single proteins in salt gradient AEC.