231 research outputs found
The tale of two countries: Modelling the effects of COVID-19 on shopping behaviour in Bangladesh and India
This paper explores the impact of COVID-19 on shopping behavior in two neighboring developing economies: Bangladesh and India. While the previous studies investigating the impact of COVID-19 on shopping behavior have relied on Revealed Preference (RP) data, this paper combines RP and Stated Preference (SP) data to develop joint RP-SP discrete choice models. This makes it possible to quantify the relative impact of the situational contexts on the choice of shopping modes of households and to capture the associated heterogeneity arising from the characteristics of the households. Further, comparison of the data and the estimated model parameters of the two countries with substantial socio-cultural similarities provide insights about how differences in the state of e-commerce can lead to different levels of inertia in continuing the pre-COVID behavior. The results will be useful to planners and policymakers for predicting the shopping modes in different future scenarios and formulating effective restriction measures
Living biointerfaces based on non-pathogenic bacteria to direct cell differentiation
Genetically modified Lactococcus lactis, non-pathogenic bacteria expressing the FNIII7-10 fibronectin fragment as a protein membrane have been used to create a living biointerface between synthetic materials and mammalian cells. This FNIII7-10 fragment comprises the RGD and PHSRN sequences of fibronectin to bind α5ÎČ1 integrins and triggers signalling for cell adhesion, spreading and differentiation. We used L. lactis strain to colonize material surfaces and produce stable biofilms presenting the FNIII7-10 fragment readily available to cells. Biofilm density is easily tunable and remains stable for several days. Murine C2C12 myoblasts seeded over mature biofilms undergo bipolar alignment and form differentiated myotubes, a process triggered by the FNIII7-10 fragment. This biointerface based on living bacteria can be further modified to express any desired biochemical signal, establishing a new paradigm in biomaterial surface functionalisation for biomedical applications
Dropout-permanence analysis of university students using data mining
Dropout is a rejection method present in every educational system,
related to the various selection processes, academic performance, and the efficiency of the system in general, that is, the result of the combination and effect
of different variables. In this sense, the dropout of university students related to
their academic performance is a matter of concern since several years ago.
Academic information is analyzed in order to identify factors that influence
studentsÂŽ dropout at the University of Mumbai, India, by using a data mining
technique. The data source contains information provided to the entrance
(personal and educational background) and that is generated during the study
period. The data selection and cleansing are made using different criteria of
representation and implementation of classification algorithms such as decision
trees, Bayesian networks, and rules. the following factors are identified as
influential variables in the desertion: approved courses, quantity and results of
attended courses, origin and age of entry of the student. Through this process, it
was possible to identify the attributes that characterize the dropout cases and
their relationship with the academic performance, especially in the first year of
the career
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Challenges in QCD matter physics --The scientific programme of the Compressed Baryonic Matter experiment at FAIR
Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is studied at very high temperatures and nearly vanishing net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was created at experiments at RHIC and LHC. The transition from the QGP back to the hadron gas is found to be a smooth cross over. For larger net-baryon densities and lower temperatures, it is expected that the QCD phase diagram exhibits a rich structure, such as a first-order phase transition between hadronic and partonic matter which terminates in a critical point, or exotic phases like quarkyonic matter. The discovery of these landmarks would be a breakthrough in our understanding of the strong interaction and is therefore in the focus of various high-energy heavy-ion research programs. The Compressed Baryonic Matter (CBM) experiment at FAIR will play a unique role in the exploration of the QCD phase diagram in the region of high net-baryon densities, because it is designed to run at unprecedented interaction rates. High-rate operation is the key prerequisite for high-precision measurements of multi-differential observables and of rare diagnostic probes which are sensitive to the dense phase of the nuclear fireball. The goal of the CBM experiment at SIS100 (sNN= 2.7--4.9 GeV) is to discover fundamental properties of QCD matter: the phase structure at large baryon-chemical potentials (ÎŒB> 500 MeV), effects of chiral symmetry, and the equation of state at high density as it is expected to occur in the core of neutron stars. In this article, we review the motivation for and the physics programme of CBM, including activities before the start of data taking in 2024, in the context of the worldwide efforts to explore high-density QCD matter
Intelligent and Distributed Data Warehouse for Studentâs Academic Performance Analysis
In the academic world, a large amount of data is handled each day, ranging from studentâs assessments to their socio-economic data. In order to analyze this historical information, an interesting alternative is to implement a Data Warehouse. However, Data Warehouses are not able to perform predictive analysis by themselves, so machine intelligence techniques can be used for sorting, grouping, and predicting based on historical information to improve the analysis quality. This work describes a Data Warehouse architecture to carry out an academic performance analysis of students
Human African trypanosomiasis in the Democratic Republic of the Congo: disease distribution and risk
Molecular cytogenetics (FISH, GISH) of Coccinia grandis: A ca. 3 myr-old species of Cucurbitaceae with the largest Y/autosome divergence in flowering plants
The independent evolution of heteromorphic sex chromosomes in 19 species from 4 families of flowering plants permits studying X/Y divergence after the initial recombination suppression. Here, we document autosome/Y divergence in the tropical Cucurbitaceae Coccinia grandis, which is ca. 3 myr old. Karyotyping and C-value measurements show that the C. grandis Y chromosome has twice the size of any of the other chromosomes, with a male/female C-value difference of 0.094 pg or 10% of the total genome. FISH staining revealed 5S and 45S rDNA sites on autosomes but not on the Y chromosome, making it unlikely that rDNA contributed to the elongation of the Y chromosome; recent end-to-end fusion also seems unlikely given the lack of interstitial telomeric signals. GISH with different concentrations of female blocking DNA detected a possible pseudo-autosomal region on the Y chromosome, and C-banding suggests that the entire Y chromosome in C. grandis is heterochromatic. During meiosis, there is an end-to-end connection between the X and the Y chromosome, but the X does not otherwise differ from the remaining chromosomes. These findings and a review of plants with heteromorphic sex chromosomes reveal no relationship between species age and degree of sex chromosome dimorphism. Its relatively small genome size (0.943 pg/2C in males), large Y chromosome, and phylogenetic proximity to the fully sequenced Cucumis sativus make C. grandis a promising model to study sex chromosome evolution.
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