Students’ perception of privacy risks in using social networking sites for learning: a study of Uganda Christian University

Although social networking sites (SNSs) present a great deal of opportunities to support learning, the privacy risk is perceived by learners as a friction point that affects their full use for learning. Privacy risks in SNSs can be divided into risks that are posed by the SNS provider itself and risks that result from user’s social interactions. Using an online survey questionnaire, this study explored the students’ perception of the benefits in using social networking sites for learning purposes and their perceived privacy risks. A sample of 214 students from Uganda Christian University in Africa was studied. The results show that although 88 % of participants indicated the usefulness of SNSs for learning, they are also aware of the risks associated with these sites. Most of the participants are concerned with privacy risks such as identity theft, cyber bullying, and impersonation that might influence their online learning participation in SNSs.

Estrogen regulation of chicken riboflavin carrier protein gene is mediated by ERE half sites without direct binding of estrogen receptor

Estrogen is an important steroid hormone that mediates most of its effects on regulation of gene expression by binding to intracellular receptors. The consensus estrogen response element (ERE) is a 13 bp palindromic inverted repeat with a three nucleotide spacer. However, several reports suggest that many estrogen target genes are regulated by diverse elements, such as imperfect EREs and ERE half sites (ERE 1/2), which are either the proximal or the distal half of the palindrome. To gain more insight into ERE half site-mediated gene regulation, we used a region from the estrogen-regulated chicken riboflavin carrier protein (RCP) gene promoter that contains ERE half sites. Using moxestrol, an analogue of estrogen and transient transfection of deletion and mutation containing RCP promoter/reporter constructs in chicken hepatoma (LMH2A) cells, we identified an estrogen response unit (ERU) composed of two consensus ERE 1/2 sites and one non-consensus ERE 1/2 site. Mutation of any of these sites within this ERU abolishes moxestrol response. Further, the ERU is able to confer moxestrol responsiveness to a heterologous promoter. Interestingly, RCP promoter is regulated by moxestrol in estrogen responsive human MCF-7 cells, but not in other cell lines such as NIH3T3 and HepG2 despite estrogen receptor-alpha (ER-�) co transfection. Electrophoretic mobility shift assays (EMSAs) with promoter regions encompassing the half sites and nuclear extracts from LMH2A cells show the presence of a moxestrol-induced complex that is abolished by a polyclonal anti-ER� antibody. Surprisingly, estrogen receptor cannot bind to these promoter elements in isolation. Thus, there appears to be a definite requirement for some other factor(s) in addition to estrogen receptor, for the generation of a suitable response of this promoter to estrogen. Our studies therefore suggest a novel mechanism of gene regulation by estrogen, involving ERE half sites without direct binding of ER to the cognate elements.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Surface Urban Energy and Water Balance Scheme (SUEWS): development and evaluation at two UK sites

The Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated at two locations in the UK: a dense urban site in the centre of London and a residential suburban site in Swindon. Eddy covariance observations of the turbulent fluxes are used to assess model performance over a twoyear period (2011-2013). The distinct characteristics of the sites mean their surface energy exchanges differ considerably. The model suggests the largest differences can be attributed to surface cover (notably the proportion of vegetated versus impervious area) and the additional energy supplied by human activities. SUEWS performs better in summer than winter, and better at the suburban site than the dense urban site. One reason for this is the bias towards suburban summer field campaigns in observational data used to parameterise this (and other) model(s). The suitability of model parameters (such as albedo, energy use and water use) for the UK sites is considered and, where appropriate, alternative values are suggested. An alternative parameterisation for the surface conductance is implemented, which permits greater soil moisture deficits before evaporation is restricted at non-irrigated sites. Accounting for seasonal variation in the estimation of storage heat flux is necessary to obtain realistic wintertime fluxes.