Self organization of exotic oil-in-oil phases driven by tunable electrohydrodynamics

Self organization of large-scale structures in nature - either coherent structures like crystals, or incoherent dynamic structures like clouds - is governed by long-range interactions. In many problems, hydrodynamics and electrostatics are the source of such long-range interactions. The tuning of electrostatic interactions has helped to elucidate when coherent crystalline structures or incoherent amorphous structures form in colloidal systems. However, there is little understanding of self organization in situations where both electrostatic and hydrodynamic interactions are present. We present a minimal two-component oil-in-oil model system where we can control the strength and lengthscale of the electrohydrodynamic interactions by tuning the amplitude and frequency of the imposed electric field. As a function of the hydrodynamic lengthscale, we observe a rich phenomenology of exotic structure and dynamics, from incoherent cloud-like structures and chaotic droplet dynamics, to polyhedral droplet phases, to coherent droplet arrays

Ingredient mix with recommender systems

The product owners and marketers are always looking to launch new products and are presented constantly with the problem of what products or the variants they should present to the consumer. We present modern aspects of studies in this regard and combine them. We look deeper in the problems pertaining to earlier researches on product choices. We also provide a framework to the solution of this problem using recommender systems

Graph Augmentation using Spectral moments

Graph representational learning focuses on learning real value vectors that for nodes,edges or the graph, such that these vectors capture adequate information about these entities. Graph data augmentation, focuses on changing the structure or features in a graph to help improve classification performance and become more generalizable. This can be broadly categorized into feature based augmentation and structure based augmentation. Feature augmentation focuses on changing the feature matrix, without changing the structure of the graph to help improve the performance of the graph neural network. Graph structure augmentation refers to the manipulation of the adjacency matrix of a given graph to achieve better classification performance. Our approach focuses on the problem of graph augmentation but from a spectral standpoint. More specifically, we attempt to augment a graph using spectral moments. Recent results have indicated that the second, third and fourth spectral moments of a graph, have strong connections to the graph\u27s properties, such as degree distribution, clustering coefficient, and connectivity[1]. Our contribution is two fold: First, we explain a formal method to find a spectral moment that helps maximize node classification performance. Second, we also provide an algorithm to augment the graph using it\u27s spectral moments, and therefore augment the graph to the spectral point that helps maximize classification performance while making the graph sparse. For the purpose of node classification, we use the GraphSAGE model with no node sampling and the mean aggregator. We notice that the node classification performance after augmentation goes up in a majority of our datasets, and furthermore, the graph also gets sparser across all our datasets

Understanding statistical concepts in laboratory quality control measures in biomedical research

The purpose of this article is to explore the quality assurance methods in carrying out laboratory investigations on various kits and biological products and analysing the results through statistical approach. This is commonly used in the health care industry where biological investigations have become a very important part. Quality Control/Quality Assurance (QC/QA) refers to the overall management system which includes the organization, planning, data collection, quality control, documentation, evaluation and reporting activities. With the emerging health issues and availability of modern treatment modalities, it is important to provide the patient, clinical diagnosis with the relevant laboratory investigations. It is therefore, important to maintain the quality control of the testing with a standard degree of precision, which in turn is essential for the delivery of the quality patient care. In view of this, statistical approaches that can be adopted to ascertain the quality of the test have been discussed. The communication also discusses components of validity of the biomedical test and its relevance in clinical settings

Clinical biomarkers in older patients with aortic stenosis

The incidence of degenerative aortic stenosis is increasing with an ageing population. Valve replacement is the only proven treatment, but this carries significant procedural risk in older people. Current guidelines advocate intervention in symptomatic severe aortic stenosis, but non-cardiac symptoms and comorbidity may obscure this assessment. Clinical biomarkers offer the potential for objective patient assessment. My aim was to firstly assess the validity and reproducibility of novel blood biomarkers of disease progression in aortic stenosis. Secondly, in older patients considered for valve replacement, my aim was to compare measures of frailty with conventional surgical risk assessment. In 265 patients with asymptomatic aortic stenosis and 46 healthy controls, I assessed serum concentrations of the sarcomeric protein cardiac myosin binding protein C (cMyC) and objective markers of disease progression and mortality. cMyC concentrations were independently associated with imaging evidence of left ventricular mass, fibrosis volume and extracellular volume. These relationships were not observed in healthy controls. cMyC concentrations were also associated with all-cause mortality over 11 years of follow-up. This suggests a role for cMyC as a novel objective biomarker of aortic stenosis disease severity. Other blood biomarkers including cardiac troponin, brain-type natriuretic peptide (BNP) and galectin-3 have been suggested as disease biomarkers in aortic stenosis. However, performance and precision of these assays has not been described in older patients. In a study of analytical and biological variability, I undertook repeated hourly and weekly blood sampling for cardiac troponin, BNP and galectin-3 in 14 subjects with severe asymptomatic aortic stenosis. These biomarkers demonstrated low indices of individuality, implying that interpretation requires serial testing for change rather than isolated elevated blood concentrations. The reference change values for weekly fresh sampling were 42% for cardiac troponin, 55% for BNP and 14% for galectin. These values for cardiac troponin and BNP were lower than equivalent studies in healthy controls and in stable heart failure. To assess the role of frailty in the assessment of patients for aortic valve replacement, I first performed a systematic review and meta-analysis of studies including frailty assessment before Transcatheter Aortic Valve Implantation (TAVI). This procedure is reserved for patients considered at prohibitive risk of complication from conventional open-heart surgery. Ten cohort studies with 4,592 TAVI patients were included. Frailty was associated with increased risk of early and late mortality, and use of an objective frailty tool rather than subjective assessment identified those at highest risk; these patients experienced greater than double the mortality risk of non-frail individuals. In 185 patients with severe aortic stenosis, I prospectively assessed frailty using four tools: the Fried phenotype, Edmonton Frail Scale, Short Physical Performance Battery and Clinical Frailty Scale. These measures were compared to surgical risk assessment scores from the Society of Thoracic Surgeons (STS) and EuroSCORE II. Agreement between frailty measures was moderate and unrelated to patient age or the degree of aortic valve severity. Frail patients had poorer physical and mental wellbeing. Frailty increased at higher STS and EuroSCORE estimates, but using principal components analysis I demonstrated divergence between frailty measures and surgical risk estimates. Outcomes after aortic valve replacement are now required to establish if this observation is meaningful for the improved prediction of outcomes after surgery. My findings suggest that serial testing of blood biomarkers of myocardial injury in patients with aortic stenosis may detect meaningful disease progression prior to decompensation. In patients considered for valve replacement, measurement of frailty differs from existing surgical risk tools and may add to the holistic assessment of older patients

Effect of Pretreatment and Packaging Materials on Quality of Spinach Powder During Storage

he study was conducted at School of Agriculture and Environmental Sciences, ShobhitUniversity, Gangoh, Saharanpur, U.P. to evaluate the effect of control sample (unblanched) spinachleaves and hot water blanched sample on shelf-life of spinach powder and to evaluate the effect of watertreatments, chemical composition such as moisture content, fat content and ash content were carried out.Sensory analysis of colour, texture, aroma and overall acceptability were carried out according to 9 pointhedonic scale. To evaluate the shelf-life of spinach powder packed in High Density Polyethylene (HDPE),Low Density Polyethylene (LDPE) and Poly propylene (PP) packaging materials, Total plate count (TPC)and yeast & mould counts were carried out. The results showed that unblanched sample was moresuitable according to fat and ash content. For moisture content hot water blanched sample was morefavourate. PP excelled than HDPE and LDPE as a packaging material to store spinach powder for a longperiod of time. According to sensory score, hot water blanched sample was more favourate by the panelistthan unblanched sample. With increase in storage period TPC and yeast & mould increased but hot waterblanched sample showed less growth of TPC and yeast & mould when compared to unblanched sample.PP showed less microbial count than the HDPE and LDPE, so it is most suitable for spinach powderpackaging for a long period of tim

Effect of Pretreatment and Packaging Materials on Quality of Spinach Powder During Storage

The study was conducted at School of Agriculture and Environmental Sciences, ShobhitUniversity, Gangoh, Saharanpur, U.P. to evaluate the effect of control sample (unblanched) spinachleaves and hot water blanched sample on shelf-life of spinach powder and to evaluate the effect of watertreatments, chemical composition such as moisture content, fat content and ash content were carried out.Sensory analysis of colour, texture, aroma and overall acceptability were carried out according to 9 pointhedonic scale. To evaluate the shelf-life of spinach powder packed in High Density Polyethylene (HDPE),Low Density Polyethylene (LDPE) and Poly propylene (PP) packaging materials, Total plate count (TPC)and yeast & mould counts were carried out. The results showed that unblanched sample was moresuitable according to fat and ash content. For moisture content hot water blanched sample was morefavourate. PP excelled than HDPE and LDPE as a packaging material to store spinach powder for a longperiod of time. According to sensory score, hot water blanched sample was more favourate by the panelistthan unblanched sample. With increase in storage period TPC and yeast & mould increased but hot waterblanched sample showed less growth of TPC and yeast & mould when compared to unblanched sample.PP showed less microbial count than the HDPE and LDPE, so it is most suitable for spinach powderpackaging for a long period of time