An Exploratory Research on Online Music Piracy and Consumer Behavior

This paper explores consumer behaviour associated with the possibility of online music piracy. A research model has been systematically developed to examine a number of variables in relation to consumer attitudes towards online music piracy. The model has also been tested using empirical data collected from individual consumers. The results show that music content, Internet skill, convenience and potential penalty are major factors of individual attitudes towards online music piracy. In addition, these factors together with subjective norms have significant impacts on individual intentions to obtain music products through unjustified online channels. The findings have practical implications for managing online digital music products and services

Internet-based e-Media and Consumer Attitudes: An empirical Research

This paper empirically explores the attributes associated with Internet-based e-media using the survey data collected from the consumers in Hong Kong. It has been found that perceived convenience, user-friendly interface, contents, efficiency and image significantly influence perceived usefulness of Internet-based e-media. In addition, self-efficacy and design characteristics are positively associated with perceived ease of use of Internet-based e-media. Moreover, these attributes together with subjective norms considerably explain consumer attitudes and intentions to use Internet-based e-media. The findings have practically useful implications for managing Internet-based e-media and developing new media in different contexts

Consumer Trust in Internet-based Airline Reservations

This paper explores consumer trust in Internet-based airline reservations using the data collected from individual consumers in Hong Kong. The empirical analysis shows that such attributes as perceived usefulness, ease of use, reputation, privacy, security and responsibility significantly influence consumer attitudes towards online airline reservation services. In addition, consumer attitudes are related to integrity, benevolence and ability, which in turn affect consumer trusting intentions to use online airline reservations. The research results in practically useful implications for improving Internet-based airline reservation services

Hijacked then lost in translation:the plight of the recombinant host cell in membrane protein structural biology projects

Membrane protein structural biology is critically dependent upon the supply of high-quality protein. Over the last few years, the value of crystallising biochemically characterised, recombinant targets that incorporate stabilising mutations has been established. Nonetheless, obtaining sufficient yields of many recombinant membrane proteins is still a major challenge. Solutions are now emerging based on an improved understanding of recombinant host cells; as a 'cell factory' each cell is tasked with managing limited resources to simultaneously balance its own growth demands with those imposed by an expression plasmid. This review examines emerging insights into the role of translation and protein folding in defining high-yielding recombinant membrane protein production in a range of host cells

Diabetic foot ulcers segmentation challenge report: benchmark and analysis

Monitoring the healing progress of diabetic foot ulcers is a challenging process. Accurate segmentation of foot ulcers can help podiatrists to quantitatively measure the size of wound regions to assist prediction of healing status. The main challenge in this field is the lack of publicly available manual delineation, which can be time consuming and laborious. Recently, methods based on deep learning have shown excellent results in automatic segmentation of medical images, however, they require large-scale datasets for training, and there is limited consensus on which methods perform the best. The 2022 Diabetic Foot Ulcers segmentation challenge was held in conjunction with the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention, which sought to address these issues and stimulate progress in this research domain. A training set of 2000 images exhibiting diabetic foot ulcers was released with corresponding segmentation ground truth masks. Of the 72 (approved) requests from 47 countries, 26 teams used this data to develop fully automated systems to predict the true segmentation masks on a test set of 2000 images, with the corresponding ground truth segmentation masks kept private. Predictions from participating teams were scored and ranked according to their average Dice similarity coefficient of the ground truth masks and prediction masks. The winning team achieved a Dice of 0.7287 for diabetic foot ulcer segmentation. This challenge has now entered a live leaderboard stage where it serves as a challenging benchmark for diabetic foot ulcer segmentation

Overcoming bottlenecks in the membrane protein structural biology pipeline

Membrane proteins account for a third of the eukaryotic proteome, but are greatly under-represented in the Protein Data Bank. Unfortunately, recent technological advances in X-ray crystallography and EM cannot account for the poor solubility and stability of membrane protein samples. A limitation of conventional detergent-based methods is that detergent molecules destabilize membrane proteins, leading to their aggregation. The use of orthologues, mutants and fusion tags has helped improve protein stability, but at the expense of not working with the sequence of interest. Novel detergents such as glucose neopentyl glycol (GNG), maltose neopentyl glycol (MNG) and calixarene-based detergents can improve protein stability without compromising their solubilizing properties. Styrene maleic acid lipid particles (SMALPs) focus on retaining the native lipid bilayer of a membrane protein during purification and biophysical analysis. Overcoming bottlenecks in the membrane protein structural biology pipeline, primarily by maintaining protein stability, will facilitate the elucidation of many more membrane protein structures in the near future

A Subset of Replication Proteins Enhances Origin Recognition and Lytic Replication by the Epstein-Barr Virus ZEBRA Protein

ZEBRA is a site-specific DNA binding protein that functions as a transcriptional activator and as an origin binding protein. Both activities require that ZEBRA recognizes DNA motifs that are scattered along the viral genome. The mechanism by which ZEBRA discriminates between the origin of lytic replication and promoters of EBV early genes is not well understood. We explored the hypothesis that activation of replication requires stronger association between ZEBRA and DNA than does transcription. A ZEBRA mutant, Z(S173A), at a phosphorylation site and three point mutants in the DNA recognition domain of ZEBRA, namely Z(Y180E), Z(R187K) and Z(K188A), were similarly deficient at activating lytic DNA replication and expression of late gene expression but were competent to activate transcription of viral early lytic genes. These mutants all exhibited reduced capacity to interact with DNA as assessed by EMSA, ChIP and an in vivo biotinylated DNA pull-down assay. Over-expression of three virally encoded replication proteins, namely the primase (BSLF1), the single-stranded DNA-binding protein (BALF2) and the DNA polymerase processivity factor (BMRF1), partially rescued the replication defect in these mutants and enhanced ZEBRA's interaction with oriLyt. The findings demonstrate a functional role of replication proteins in stabilizing the association of ZEBRA with viral DNA. Enhanced binding of ZEBRA to oriLyt is crucial for lytic viral DNA replication

Bringing a Time–Depth Perspective to Collective Animal Behaviour

The field of collective animal behaviour examines how relatively simple, local interactions between individuals in groups combine to produce global-level outcomes. Existing mathematical models and empirical work have identified candidate mechanisms for numerous collective phenomena but have typically focused on one-off or short-term performance. We argue that feedback between collective performance and learning – giving the former the capacity to become an adaptive, and potentially cumulative, process – is a currently poorly explored but crucial mechanism in understanding collective systems. We synthesise material ranging from swarm intelligence in social insects through collective movements in vertebrates to collective decision making in animal and human groups, to propose avenues for future research to identify the potential for changes in these systems to accumulate over time

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery