BackgroundProtective respiratory face masks protect the nose and mouth of the wearer from vapor drops carrying viruses or other infectious pathogens. However, incorrect use and disposal may actually increase the risk of pathogen transmission, rather than reduce it, especially when masks are used by non-professionals such as the lay public. Copper oxide displays potent antiviral properties. A platform technology has been developed that permanently introduces copper oxide into polymeric materials, conferring them with potent biocidal properties.Methodology/Principal FindingsWe demonstrate that impregnation of copper oxide into respiratory protective face masks endows them with potent biocidal properties in addition to their inherent filtration properties. Both control and copper oxide impregnated masks filtered above 99.85% of aerosolized viruses when challenged with 5.66±0.51 and 6.17±0.37 log10TCID50 of human influenza A virus (H1N1) and avian influenza virus (H9N2), respectively, under simulated breathing conditions (28.3 L/min). Importantly, no infectious human influenza A viral titers were recovered from the copper oxide containing masks within 30 minutes (≤0.88 log10TCID50), while 4.67±1.35 log10TCID50 were recovered from the control masks. Similarly, the infectious avian influenza titers recovered from the copper oxide containing masks were ≤0.97±0.01 log10TCID50 and from the control masks 5.03±0.54 log10TCID50. The copper oxide containing masks successfully passed Bacterial Filtration Efficacy, Differential Pressure, Latex Particle Challenge, and Resistance to Penetration by Synthetic Blood tests designed to test the filtration properties of face masks in accordance with the European EN 14683:2005 and NIOSH N95 standards.Conclusions/SignificanceImpregnation of copper oxide into respiratory protective face masks endows them with potent anti-influenza biocidal properties without altering their physical barrier properties. The use of biocidal masks may significantly reduce the risk of hand or environmental contamination, and thereby subsequent infection, due to improper handling and disposal of the masks.

This research investigated a number of main areas of attachment in order to determine how consumer-product relationships are formed and to identify whether these feelings influence replacement decisions. Primary research comprised of interviews with consumers to discuss the topic area in relation to three possessions selected for their attachment qualities. The research highlighted how attachment is determined by multiple themes, many of which are circumstantial to consumers' experiences and therefore difficult for designers to control. Findings showed that memories were the most prominent theme of participants' attachment, closely followed by pleasure and usability. Enjoyment and pleasure were found to be the primary reason for attachment to newly purchased items, whereas nostalgia was highest for older possessions. Appearance and reliability were found to have considerable influence on participants' attitudes towards replacement.

This research aims to quantify the current market size for wearable technology, and determine why this market has struggled over the past decade. These are products which are worn on the body and enhanced using electronics. Forecasts have been made as to how this wearable technology is likely to develop in terms of market size and product design or function. It is predicted that in five years the wearable technology market will be several times larger than it is currently, and entertainment devices will overtake fitness to become the largest product category. Medical devices will be used to reduce healthcare costs by monitoring patients within their own home and wearable technology will allow businesses to improve customer relations and productivity.

No abstract

Firefly Algorithm (FA) is a nature-inspired optimization algorithm that can be successfully applied to continuous optimization problems. However, lot of practical problems are formulated as discrete optimization problems. In this paper a hybrid discrete firefly algorithm (HDFA) is proposed to solve the multi-objective flexible job shop scheduling problem (FJSP). FJSP is an extension of the classical job shop scheduling problem that allows an operation to be processed by any machine from a given set along different routes. Three minimization objectives -the maximum completion time, the workload of the critical machine and the total workload of all machines are considered simultaneously. This paper also proposes firefly algorithm's discretization which consists of constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. In the proposed algorithm discrete firefly algorithm (DFA) is combined with local search (LS) method to enhance the searching accuracy and information sharing among fireflies. The experimental results on the well-known benchmark instances and comparison with other recently published algorithms shows that the proposed algorithm is feasible and an effective approach for the multi-objective flexible job shop scheduling problems.