Huiru Zheng

University of Ulster

In an era marked by unprecedented technological advancements, the 2023 Collaborative European Research Conference (CERC) convened in Barcelona, Spain, on June 9-10, 2023, as a hybrid event. This gathering underscored the imperative of interdisciplinary collaboration across Europe, bringing together researchers from diverse fields to address the mul...

Improving the ability to predict protein function can potentially facilitate research in the fields of drug discovery and precision medicine. Technically, the properties of proteins are directly or indirectly reflected in their sequence and structure information, especially as the protein function is largely determined by its spatial properties. Ex...

CERC 2021, the first online CERC conference, provided an opportunity to welcome not only our European friends and colleagues but also participants from across the globe. Munster Technological University has made a notable impact in Artificial Intelligence, Cybersecurity, and Computer Science research, largely due to national, European, and internat...

BACKGROUND There has been a call to improve training for healthcare professionals (HCPs) on communicating about overweight and obesity for at least ten years. Progress has been made on recognizing the impact of weight stigma and in pharmacotherapeutics, but challenges remain in standardizing the quality of HCP–patient discussions. In other chronic...

Measuring dairy cattle methane (CH4) emissions using traditional recording technologies is complicated and expensive. Prediction models, which estimate CH4 emissions based on proxy information, provide an accessible alternative. This review covers the different modeling approaches taken in the prediction of dairy cattle CH4 emissions and highlights...

Lower limb prostheses offer mobility restoration to individuals who underwent amputation, yet they often introduce movement alterations that can affect physical health over time. While monitoring and understanding these alterations are crucial for designing tailored rehabilitation plans, existing technologies are primarily confined to clinical sett...

A robotic exoskeleton enables individuals with limited or no mobility to engage in moderate exercises, promoting physical fitness and overall well-being. Exoskeletons, however, do not provide insights into gait patterns monitoring and analysis over time. This study proposes the integration of smart insoles as a cost-effective and non-invasive assis...

Gait analysis is a research field that aims to assess and analyse a person’s locomotion patterns. Traditional methods rely on visual evaluations by medical experts, but recent advances in biomechanics have introduced objective solutions such as motion capture systems, force plates, and pressure mats. However, these solutions are expensive, cumberso...

Recent years have witnessed the increasing literature on using smart insoles in health and well-being, and yet, their capability of daily living activity recognition has not been reviewed. This paper addressed this need and provided a systematic review of smart insole-based systems in the recognition of Activities of Daily Living (ADLs). The review...

Background This research is part of the STOP project, a H2020 RISE project funded by European Commission (GA No 823978) to address the challenge of preventing obesity in Europe. The interdisciplinary European STOP project aims to establish a data and knowledge ecosystem as a basis for the STOP Portal to enable healthcare professionals in decision s...

Under certain task conditions, error-related potential (ErrP) will be elicited, meaning that the subject is perceiving an error, responding to an external error, or engaging in a cognitive process of reinforcement learning. The detection of ErrP on a single trial basis has been studied and applied to improve all kinds of brain–computer interfaces (...

Metagenomics is an unobtrusive science linking microbial genes to biological functions or environmental states. Classifying microbial genes into their functional repertoire is an important task in the downstream analysis of Metagenomic studies. The task involves Machine Learning (ML) based supervised methods to achieve good classification performan...

Background Recent rumen microbiome studies are progressive due to the advent of next-generation sequencing technologies, computational models, and gene referencing databases. Rumen metagenomics enables the linking of the genetic structure and composition of the rumen microbial community to the functional role it plays in the ecosystem. Systematic i...

We sought to determine the most efficacious and cost-effective strategy to follow when developing a national screening programme by comparing and contrasting the national screening programmes of Norway, the Netherlands and the UK. Comparing the detection rates and screening profiles between the Netherlands, Norway, the UK and constituent nations (E...

Aims. We sought to determine the most efficacious and cost effective strategy to follow when developing a national screening programme by comparing and contrasting the national screening programmes of Norway, the Netherlands and the UK. Methods and results. Comparing the detection rates and screening profiles between the Netherlands, Norway, the UK...

There has been a consistent call for training over the last 10 years to help improve communication about weight and obesity in healthcare settings. Some training is available, but it doesn’t help healthcare professionals (HCPs) to develop the sensitive communication skills required. The study aim was to test the feasibility of a 3D-virtual learning...

Health monitoring, rehabilitation, and fitness are just a few domains where human activity recognition can be applied. In this study, a deep learning approach has been proposed to recognise ambulation and fitness activities from data collected by five participants using smart insoles. Smart insoles, consisting of pressure and inertial sensors, allo...

IMPORTANCE During the cold season, like other high-altitude mammals, Tibetan sheep have to adapt their physiological and nutritional strategies, as well as the structure and function of their rumen microbial community, to the seasonal variation of lower food availability and quality. This study focuses on the changes and adaptability in the rumen...

Inertial sensors are widely used in human motion monitoring. Orientation and position are the two most widely used measurements for motion monitoring. Tracking with the use of multiple inertial sensors is based on kinematic modelling which achieves a good level of accuracy when biomechanical constraints are applied. More recently, there is growing...

Survey/review study A Mini Review of Node Centrality Metrics in Biological Networks Mengyuan Wang 1,2, Haiying Wang 1, and Huiru Zheng 1,* 1 School of Computing, Ulster University, Belfast, BT15 1ED, United Kingdom 2 Scotland’s Rural College, Edinburgh, EH25 9RG, United Kingdom * Correspondence: h.zheng@ulster.ac.uk Received: 31 October 2022 Accept...

Exploring efficient and high-accuracy computational drug repositioning methods has become a popular and attractive topic in drug development. This technology can systematically identify potential drug-disease interactions, which could greatly alleviate the pressures from the high cost and long period taken by traditional drug research and discovery...

This study aims to compare the performance of multiple linear regression and machine learning algorithms for predicting manure nitrogen excretion in lactating dairy cows, and to develop new machine learning prediction models for MN excretion. Dataset used were collated from 43 total diet digestibility studies with 951 lactating dairy cows. Predicti...

In the field of energy storage, it is very important to predict the state of charge and the state of health of lithium-ion batteries. In this paper, we review the current widely used equivalent circuit and electrochemical models for battery state predictions. The review demonstrates that machine learning and deep learning approaches can be used to...

Decision-making is a very important cognitive process in our daily life. There has been increasing interest in the discriminability of single-trial electroencephalogram (EEG) during decision-making. In this study, we designed a machine learning based framework to explore the discriminability of single-trial EEG corresponding to different decisions....

Musculoskeletal disorders (MSDs) are associated with sitting postures. The assessment and prevention of risk factors for workplace exposure are indispensable aspects of reducing the occurrence of MSDs. This paper proposes an ergonomic assessment method of risk factors for MSDs associated with sitting postures in the actual working conditions. A Kin...

Human Activity Recognition (HAR) is increasingly used in a variety of applications, including health care, fitness tracking, and rehabilitation. To reduce the impact on the user’s daily activities, wearable technologies have been advanced throughout the years. In this study, an improved smart insole-based HAR system is proposed. The impact of data...

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as cancer. Here, we review and discuss how to employ artificial intelligence ap...

Introduction: As a direct bridge between the brain and the outer world, brain–computer interface (BCI) is expected to replace, restore, enhance, supplement, or improve the natural output of brain. The prospect of BCI serving humans is very broad. However, the extensive applications of BCI have not been fully achieved. One of reasons is that the cos...

Purpose: The purpose of this research is to represent the complex system of the rumen microbiome through a multi-layer network, to explore the main biological functions related to methane metabolism. Methods: A three-layer heterogeneous network has been constructed based on rumen metabolites, rumen microbial genes and rumen microbial communities. N...

Accurate quantification of volatile fatty acid (VFA) concentrations in rumen fluid are essential for research on rumen metabolism. The study comprehensively investigated the pros and cons of High-performance liquid chromatography (HPLC) and ¹ H Nuclear magnetic resonance ( ¹ H-NMR) analysis methods for rumen VFAs quantification. We also investigate...

Metagenomics promises to provide new valuable insights into the role of microbiomes in eukaryotic hosts such as humans. Due to the decreasing costs for sequencing, public and private repositories for human metagenomic datasets are growing fast. Metagenomic datasets can contain terabytes of raw data, which is a challenge for data processing but also...

Non-coding RNAs are gaining prominence in biology and medicine, as they play major roles in cellular homeostasis among which the circRNA-miRNA-mRNA axes are involved in a series of disease-related pathways, such as apoptosis, cell invasion and metastasis. Recently, many computational methods have been developed for the prediction of the relationshi...

Aging refers to progressive physiological changes in a cell, an organ, or the whole body of an individual, over time. Aging-related diseases are highly prevalent and could impact an individual’s physical health. Recently, artificial intelligence (AI) methods have been used to predict aging-related diseases and issues, aiding clinical providers in d...

Disease similarity analysis impacts significantly in pathogenesis revealing, treatment recommending, and disease-causing genes predicting. Previous works study the disease similarity based on the semantics obtaining from biomedical ontologies (e.g., disease ontology) or the function of disease-causing molecules. However, such methods almost focus o...

Background Accurate quantification of volatile fatty acid (VFA) concentrations in rumen fluid are essential for research on rumen metabolism. HPLC analysis of VFAs has the advantages of relatively simple sample preparation, no derivatization and high sensitivity, but it can only be used to quantify metabolites when standards are used. ¹H Nuclear ma...

Accurate quantification of volatile fatty acid (VFA) concentrations in rumen fluid are essential for research on rumen metabolism. This study comprehensively investigated the pros and cons of High-performance liquid chromatography (HPLC) and ¹ H Nuclear magnetic resonance ( ¹ H-NMR) analysis methods for rumen VFAs quantification. We also investigat...

Selenium (Se) deficiency is a widespread and seasonally chronic phenomenon observed in Tibetan sheep (Ovis aries) traditionally grazed on the Qinghai–Tibet Plateau (QTP). Effects of the dietary addition of Se-enriched yeast (SeY) on the bacterial community in sheep rumen and rumen fermentation were evaluated with the aim of gaining a better underst...

Traditional approaches to the dynamics of the open quantum systems with high precision are often resource intensive. How to improve computation accuracy and efficiency for target systems is an extremely difficult challenge. In this work, combining unsupervised and supervised learning algorithms, a deep‐learning approach is introduced to simulate an...

Collaborative European Research Conference (CERC 2020) at Ulster Unviersity – Belfast, Northern-Ireland, September 10-11, 2020, https://www.cerc-conf.eu. Proceedings are online under: http://CEUR-WS.org/Vol-2815/

With the rapid decrease in sequencing costs there is an increased research interest in metagenomics, the study of the genomic content of microbial communities. Machine learning has also seen a revolution with regards to versatility and performance in the last decade using techniques like “Deep Learning”. Classical as well as modern machine learning...

Reducing rumen methane emissions based on the basal diet is one primary approach for livestock production. However, microbiological mechanisms of rumen methane emissions under different diets are very complex and lack comprehensive understanding. This research developed an innovative multilayer network framework to investigate relationships of rume...

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promi...

Analysis of gene similarity not only can provide information on the understanding of the biological roles and functions of a gene, but may also reveal the relationships among various genes. In this paper, we introduce a novel idea of mining similar aspects from a gene information network , i.e., for a given gene pair, we want to know in which asp...

Overweight and obesity are chronic disease risk factors, posing a significant global health challenge.(Reference Abdelaal, le Roux and Docherty1) Nutritional counselling is a key part of obesity prevention and treatment, but healthcare professionals receive little training in this area.(Reference Baute, Sampath-Kumar, Nelson and BasilGlob2) In part...

Mental health and mental wellbeing have become an important factor to many citizens navigating their way through their environment and in the work place. New technology solutions such as chatbots are potential channels for supporting and coaching users to maintain a good state of mental wellbeing. Chatbots have the added value of providing social c...

A better understanding of rumen microbial interactions is crucial for the study of rumen metabolism and methane emissions. Metagenomics-based methods can explore the relationship between microbial genes and metabolites to clarify the effect of microbial function on the host phenotype. This study investigated the rumen microbial mechanisms of methan...

Background: Glioblastoma multiforme (GBM) is one of the most common malignant brain tumors and its average survival time is less than 1 year after diagnosis. Results: Firstly, this study aims to develop the novel survival analysis algorithms to explore the key genes and proteins related to GBM. Then, we explore the significant correlation betwee...

The exponential growth of the technology industry over the past years has led to the development of a new paradigm. Pervasive Computing, which seeks to integrate computational capabilities into everyday objects so that they can communicate efficiently and perform useful tasks in a way that minimises the need for the end-users to interact with compu...

Metabolites are the final production of biochemical reactions in the rumen micro-ecological system and are very sensitive to changes in rumen microbes. Nuclear magnetic resonance (NMR) spectroscopy could both identify and quantify the metabolic composition of the ruminal fluid, which reflects the interaction between rumen microbes and diet. The mai...

Subarachnoid hemorrhage (SAH) is devastating disease with high mortality, high disability rate, and poor clinical prognosis. It has drawn great attentions in both basic and clinical medicine. Therefore, it is necessary to explore the therapeutic drugs and effective targets for early prediction of SAH. Firstly, we demonstrate that LCN2 can effective...

The objective was to determine whether modern Holstein-origin dairy cows, when managed within grassland-based systems, partitioned more feed nitrogen (N) into milk and excreted less in manure, in comparison to an earlier population of Holstein-origin dairy cows. Data used were collated from total diet digestibility studies undertaken in Northern Ir...

Visual inertial odometers (VIOs) have received increasing attention in the area of indoor positioning due to the universality and convenience of the camera. However, the visual observation of VIO is more susceptible to the environment, and the error of observation affects the final positioning accuracy. To address this issue, we analyzed the causes...

This paper presents a study into the use of wearable technologies by pregnant women with Type one diabetes (T1D). The World Health Organisation estimates the incidence of T1D globally to be more than 422 million. Wearable technologies can potentially improve decisions around self-management by providing regular feedback on physiological processes....