Olfactory variation in mouse husbandry and its implications for refinement and standardisation: UK survey of non-animal scents

With their highly sensitive olfactory system, the behaviour and physiology of mice are not only influenced by the scents of conspecifics and other species, but also by many other chemicals in the environment. The constraints of laboratory housing limit a mouse’s capacity to avoid aversive odours that could be present in the environment. Potentially odorous items routinely used for husbandry procedures, such as sanitizing products and gloves, could be perceived by mice as aversive or attractive, and affect their behaviour, physiology and experimental results. A survey was sent to research institutions in the UK to enquire about husbandry practices that could impact on the olfactory environment of the mouse. Responses were obtained from 80 individuals working in 51 institutions. Husbandry practices varied considerably. Seventy percent of respondents reported always wearing gloves for handling mice, with nitrile being the most common glove material (94%) followed by latex (23%) and vinyl (14%). Over six different products were listed for cleaning surfaces, floors, anaesthesia and euthanasia chambers and behavioural apparatus. In all cases Trigene™ (now called Anistel™) was the most common cleaning product used (43, 41, 40 and 49%, respectively). Depending on the attribute considered, between 7 and 19% of respondents thought that cleaning products definitely, or were likely to, have strong effects on standardization, mouse health, physiology or behaviour. Understanding whether and how these odours affect mouse welfare will help to refine mouse husbandry and experimental procedures through practical recommendations, to improve the quality of life of laboratory animals and the experimental data obtained

Solvent dependence of the rheological properties in hydrogel magnetorheological plastomer

Chemically crosslinked hydrogel magnetorheological (MR) plastomer (MRP) embedded with carbonyl iron particles (CIPs) exhibits excellent magnetic performance (MR effect) in the presence of external stimuli especially magnetic field. However, oxidation and desiccation in hydrogel MRP due to a large amount of water content as a dispersing phase would limit its usage for long‐term applications, especially in industrial engineering. In this study, different solvents such as dimethyl sulfoxide (DMSO) are also used to prepare polyvinyl alcohol (PVA) hydrogel MRP. Thus, to understand the dynamic viscoelastic properties of hydrogel MRP, three different samples with different solvents: water, DMSO, and their binary mixtures (DMSO/water) were prepared and systematically carried out using the oscillatory shear. The outcomes demonstrate that the PVA hydrogel MRP prepared from precursor gel with water shows the highest MR effect of 15,544% among the PVA hydrogel MRPs. However, the samples exhibit less stability and tend to oxidise after a month. Meanwhile, the samples with binary mixtures (DMSO/water) show an acceptable MR effect of 11,024% with good stability and no CIPs oxidation. Otherwise, the sample with DMSO has the lowest MR effect of 7049% and less stable compared to the binary solvent samples. This confirms that the utilisation of DMSO as a new solvent affects the rheological properties and stability of the samples

Microaneurysms Segmentation in Retinal Images for Early Detection of Diabetic Retinopathy

Microaneurysms (MAs) are the tiny aneurysms which show the earliest sign of diabetic retinopathy (DR). MAs might progress and harm human eyes if not treated. This paper presents an automatic method for segmentation of MAs in order to control the progression of DR. MESSIDOR database of 40 random images were utilised for further processing. The proposed approach covered pre-processing steps, contrast enhancement, filtration and segmentation by h-maxima transform and multilevel thresholding. Some post-processing techniques also involved in this approach using morphological operation. The detected MAs determined the grade of disease severity. The result showed that the percentage of severity disease detected was 60%

Improving Vehicle Ride and Handling Using LQG CNF Fusion Control Strategy for an Active Antiroll Bar System

This paper analyses a comparison of performance for an active antiroll bar (ARB) system using two types of control strategy. First of all, the LQG control strategy is investigated and then a novel LQG CNF fusion control method is developed to improve the performances on vehicle ride and handling for an active antiroll bar system. However, the ARB system has to balance the trade-off between ride and handling performance, where the CNF consists of a linear feedback law and a nonlinear feedback law. Typically, the linear feedback is designed to yield a quick response at the initial stage, while the nonlinear feedback law is used to smooth out overshoots in the system output when it approaches the target reference. The half car model is combined with a linear single track model with roll dynamics which are used for the analysis and simulation of ride and handling. The performances of the control strategies are compared and the simulation results show the LQG CNF fusion improves the performances in vehicle ride and handling

The production of crude palm oil in Malaysia

Palm oil production contributes significantly to the Malaysian economy. Malaysia currently holds the position as the world's second-largest palm oil producer after Indonesia. This study intends to empirically test the Cobb- Douglas (C-D) production function for the palm oil production sector in Malaysia with the validity of C-D's assumptions. The significance of factors such as capital, labour and utilisation rate in the production of Crude Palm Oil (CPO) is also tested in the study. The data on the productivity of the Palm Oil (PO) mills are collected from the Malaysian Palm Oil Board (MPOB). The methods of Least Square (LS) and robustness check are carried out in the estimation of the production function. The results show a positive and significant relationship between the production of CPO and labour, capital, and the utilisation rate. This study suggests that increases in capital, labour employment and the utilisation rate will boost the production of CPO in Malaysia

The fusion of HRV and EMG signals for automatic gender recognition during stepping exercise

In this paper, a new gender recognition framework based on fusion of features extracted from healthy people electromyogram (EMG) and heart rate variability (HRV) during stepping activity using a stepper machine is proposed. An approach is investigated for the fusion of EMG and HRV which is feature fusion. The feature fusion is carried out by concatenating the feature vector extracted from the EMG and HRV signals. A proposed framework consists of a sequence of processing steps which are preprocessing, feature extraction, feature selection and lastly the fusion. The results shown that the fusion approach had improved the performance of gender recognition compared to solely on EMG or HRV based gender identifier

A review on recent progress in machine learning and deep learning methods for cancer classification on gene expression data

Data-driven model with predictive ability are important to be used in medical and healthcare. However, the most challenging task in predictive modeling is to construct a prediction model, which can be addressed using machine learning (ML) methods. The methods are used to learn and trained the model using a gene expression dataset without being programmed explicitly. Due to the vast amount of gene expression data, this task becomes complex and time consuming. This paper provides a recent review on recent progress in ML and deep learning (DL) for cancer classification, which has received increasing attention in bioinformatics and computational biology. The development of cancer classification methods based on ML and DL is mostly focused on this review. Although many methods have been applied to the cancer classification problem, recent progress shows that most of the successful techniques are those based on supervised and DL methods. In addition, the sources of the healthcare dataset are also described. The development of many machine learning methods for insight analysis in cancer classification has brought a lot of improvement in healthcare. Currently, it seems that there is highly demanded further development of efficient classification methods to address the expansion of healthcare applications