The effect of Mg location on Co-Mg-Ru/γ-Al2O3 Fischer–Tropsch catalysts

© 2016 The Author(s) Published by the Royal Society. All rights reserved.The effectiveness of Mg as a promoter of Co-Ru/γ-Al2O3 Fischer-Tropsch catalysts depends on how and when the Mg is added. When the Mg is impregnated into the support before the Co and Ru addition, some Mg is incorporated into the support in the form of MgxAl2O3+x if the material is calcined at 550°C or 800°C after the impregnation, while the remainder is present as amorphous MgO/MgCO3 phases. After subsequent Co-Ru impregnation MgxCo3-xO4 is formed which decomposes on reduction, leading to Co(0) particles intimately mixed with Mg, as shown by high-resolution transmission electron microscopy. The process of impregnating Co into an Mg-modified support results in dissolution of the amorphous Mg, and it is this Mg which is then incorporated into MgxCo3-xO4. Acid washing or higher temperature calcination after Mg impregnation can remove most of this amorphous Mg, resulting in lower values of x in MgxCo3-xO4. Catalytic testing of these materials reveals that Mg incorporation into the Co oxide phase is severely detrimental to the site-Time yield, while Mg incorporation into the support may provide some enhancement of activity at high temperature

Determining EDS and EELS partial cross-sections from multiple calibration standards to accurately quantify bi-metallic nanoparticles using STEM

Spectroscopic signals such as EDS and EELS provide an effective way of characterising multi-element samples such as Pt-Co nanoparticles in STEM. The advantage of spectroscopy over imaging is the ability to decouple composition and mass-thickness effects for thin samples, into the number of various types of atoms in a sample. This is currently not possible for multi element samples using conventional ADF quantification techniques alone. With recent developments in microscope hardware and software, it is now possible to acquire the ADF, EDS and EELS signals simultaneously and at high speed. However, the methods of quantifying the signals emitted from the sample vary greatly. Most approaches use pure-element standards in the form of needles, nanoparticles and wedges to quantify the spectroscopic signal into either partial scattering cross-sections, zeta-factors or k-factors. But self-consistency between the different methods has not been verified and the units of the quantification are not standardised. We present a robust approach for measuring and combining ADF, EDS and EELS signals using needle and nanoparticle standards in units of the partial scattering cross-section. The partial scattering cross-section allows an easy interpretation of the signals emitted from the sample and enables accurate atom-counting of the sample

A live weight-heart girth relationship for accurate dosing of east African shorthorn zebu cattle

The accurate estimation of livestock weights is important for many aspects of livestock management including nutrition, production and appropriate dosing of pharmaceuticals. Subtherapeutic dosing has been shown to accelerate pathogen resistance which can have subsequent widespread impacts. There are a number of published models for the prediction of live weight from morphometric measurements of cattle, but many of these models use measurements difficult to gather and include complicated age, size and gender stratification. In this paper, we use data from the Infectious Diseases of East Africa calf cohort study and additional data collected at local markets in western Kenya to develop a simple model based on heart girth circumference to predict live weight of east African shorthorn zebu (SHZ) cattle. SHZ cattle are widespread throughout eastern and southern Africa and are economically important multipurpose animals. We demonstrate model accuracy by splitting the data into training and validation subsets and comparing fitted and predicted values. The final model is weight0.262 =0.95 + 0.022 × girth which has an R2 value of 0.98 and 95 % prediction intervals that fall within the ±20 % body weight error band regarded as acceptable when dosing livestock. This model provides a highly reliable and accurate method for predicting weights of SHZ cattle using a single heart girth measurement which can be easily obtained with a tape measure in the field setting

Towards in-situ TEM for Li-ion battery research

Due to recent developments in new battery materials for higher energy density applications there has been growing interest in new characterization techniques capable of time-resolved in situ/in operando analysis of dynamic Battery systems. This review provides an overview on recent development of liquid cell transmission electron microscopy (TEM) for Li-ion battery research and discusses the challenges, highlighting potential research areas. In-situ TEM offers the opportunity to study phenomena including solid electrolyte interphase (SEI) formation and phase changes during battery operation. There are two main challenging areas for in-situ TEM research (1) designing an in-situ TEM electrochemical cell that mimics a ‘real’ cell and (2) quantifying beam damage caused by electron irradiation of the electrolyte

Most complicated lock pattern-based seismological signal framework for automated earthquake detection

BACKGROUND : Seismic signals record earthquakes and also noise from different sources. The influence of noise makes it difficult to interpret seismograph signals correctly. This study aims to develop a computationally lightweight, accurate, and explainable machine learning model for the automated detection of seismogram signals that could serve as an effective warning system for earthquake prediction. MATERIAL AND METHOD : We developed a handcrafted model for earthquake detection using a balanced dataset of 5001 earthquakes and 5001 non-earthquake signal samples. The model included multilevel feature extraction, selectorbased feature selection, classification, and post-processing. Input signals were decomposed using tunable Q wave transform and fed to a statistical and textural feature extractor based on the most complicated lock pattern (MCLP). Four feature selectors were used to choose the most valuable features for the support vector machine classifier. Additionally, voted vectors were generated using iterative hard majority voting. Finally, the best model was chosen using a greedy algorithm. RESULTS : The presented self-organized MCLP-based feature engineering model yielded 96.82% classification accuracy with 10-fold cross-validation using the seismic signal dataset. CONCLUSIONS : Our model attained high seismological signal detection performance comparable with more computationally expensive deep learning models. Our handcrafted explainable feature engineering model is computationally less expensive and can be easily implemented. Furthermore, we have introduced a competitive feature engineering model to the deep learning models for the seismic signal classification model.The South African National Library and Information Consortium (SANLiC).https://www.elsevier.com/locate/jagam2024Electrical, Electronic and Computer EngineeringSDG-09: Industry, innovation and infrastructureSDG-13:Climate actio

Effect of Body Mass Index on work related musculoskeletal discomfort and occupational stress of computer workers in a developed ergonomic setup

<p>Abstract</p> <p>Background</p> <p>Work urgency, accuracy and demands compel the computer professionals to spend longer hours before computers without giving importance to their health, especially body weight. Increase of body weight leads to improper Body Mass Index (BMI) may aggravate work related musculoskeletal discomfort and occupational-psychosocial stress. The objective of the study was to find out the effect of BMI on work related musculoskeletal discomforts and occupational stress of computer workers in a developed ergonomic setup.</p> <p>Methods</p> <p>A descriptive inferential study has been taken to analyze the effect of BMI on work related musculoskeletal discomfort and occupational-psychosocial stress. A total of 100 computer workers, aged 25-35 years randomly selected on convenience from software and BPO companies in Bangalore city, India for the participation in this study. BMI was calculated by taking the ratio of the subject's height (in meter) and weight (in kilogram). Work related musculoskeletal discomfort and occupational stress of the subjects was assessed by Cornell University's musculoskeletal discomfort questionnaire (CMDQ) and occupational stress index (OSI) respectively as well as a relationship was checked with their BMI.</p> <p>Results</p> <p>A significant association (p < 0.001) was seen among high BMI subjects with their increase scores of musculoskeletal discomfort and occupational stress.</p> <p>Conclusion</p> <p>From this study, it has been concluded that, there is a significant effect of BMI in increasing of work related musculoskeletal discomfort and occupational-psychosocial stress among computer workers in a developed ergonomic setup.</p

A Retrospective Overview of Enterovirus Infection Diagnosis and Molecular Epidemiology in the Public Hospitals of Marseille, France (1985–2005)

Human enteroviruses (HEV) are frequent human pathogens and, associated in particular with large outbreaks of aseptic meningitis. Here, we have compiled a database of clinical HEV isolates from the Public Hospitals of Marseille, from 1985 to 2005. Amongst 654 isolates that could be characterized by complete sequencing of the VP1 gene, 98% belonged to species HEV-B; the most frequently isolated serotypes were Echovirus E30, E11, E7, E6 and E4. The high incidence of E30 and the recent emergence of E13 are consistent with reports worldwide and peak HEV isolation occurred mostly in the late spring and summer months. The proportion of echoviruses has decreased across the years, while that of coxsackieviruses has increased. Stool (the most frequent sample type) allowed detection of all identified serotypes. MRC5 (Human lung fibroblasts) cell line was the most conducive cell line for HEV isolation (84.9% of 10 most common serotype isolates, 96.3% in association with BGM (Buffalo green monkey kidney cells)). Previous seroneutralization-based serotype identification demonstrated 55.4% accuracy when compared with molecular VP1 analysis. Our analysis of a large number of clinical strains over 20 years reinforced the validity of VP1 serotyping and showed that comparative p-distance scores can be coupled with phylogenetic analysis to provide non-ambiguous serotype identification. Phylogenetic analysis in the VP1, 2C and 3D regions also provided evidence for recombination events amongst clinical isolates. In particular, it identified isolates with dissimilar VP1 but almost identical nonstructural regions

Identifying risk factors for blood culture negative infective endocarditis: An international ID-IRI study

Background: Blood culture-negative endocarditis (BCNE) is a diagnostic challenge, therefore our objective was to pinpoint high-risk cohorts for BCNE. Methods: The study included adult patients with definite endocarditis. Data were collected via the Infectious Diseases International Research Initiative (ID-IRI). The study analysing one of the largest case series ever reported was conducted across 41 centers in 13 countries. We analysed the database to determine the predictors of BCNE using univariate and logistic regression analyses. Results: Blood cultures were negative in 101 (11.65 %) of 867 patients. We disclosed that as patients age, the likelihood of a negative blood culture significantly decreases (OR 0.975, 95 % CI 0.963–0.987, p &lt; 0.001). Additionally, factors such as rheumatic heart disease (OR 2.036, 95 % CI 0.970–4.276, p = 0.049), aortic stenosis (OR 3.066, 95 % CI 1.564–6.010, p = 0.001), mitral regurgitation (OR 1.693, 95 % CI 1.012–2.833, p = 0.045), and prosthetic valves (OR 2.539, 95 % CI 1.599–4.031, p &lt; 0.001) are associated with higher likelihoods of negative blood cultures. Our model can predict whether a patient falls into the culture-negative or culture-positive groups with a threshold of 0.104 (AUC±SE = 0.707 ± 0.027). The final model demonstrates a sensitivity of 70.3 % and a specificity of 57.0 %. Conclusion: Caution should be exercised when diagnosing endocarditis in patients with concurrent cardiac disorders, particularly in younger cases