Multifunctional Hybrid Nanoparticles for Traceable Drug Delivery and Intracellular Microenvironment‐Controlled Multistage Drug‐Release in Neurons

Innovative nanoparticles hold promising potential for disease therapy as drug delivery systems. For brain‐disease therapy, a drug delivery system that can sustainably control drug‐release and monitor fluorescence of the drug cargos is highly desirable. In this study, a light‐traceable and intracellular microenvironment‐responsive drug delivery system was developed based on the combination of glutathione‐responsive autoflurescent nanogel, dendrimer‐like mesoporous silica nanoparticles, and gold nanoparticles. The resulting hybrid nanoparticles represent a new class of delivery system that can efficiently load, transport, and control multistage‐release of sulfydryl‐containing drugs into neurons, with light‐traceable monitoring for future brain‐disease therapy.     

Polymeric Films Containing Sodium Chlorite That Release Disinfectant Gas upon Activation with UV Light

Polymeric films that release disinfectant gas on demand have the potential to be useful for management of microbial burden (e.g., sterilization). Past attempts to create such films, however, have suffered from the need for stringent control over moisture or exposure to visible light prior to use. It is reported that polyvinyl alcohol (PVA) or polyolefin (POD) films that contain NaClO₂ crystals can release ClO₂ gas upon UV‐activation and exposure to moisture. In addition to showing that the concentration of gaseous ClO₂ released from the polymeric films is sufficiently high for antimicrobial activity, fundamental insights into factors controlling ClO₂ release are provided by using atomic force microscopy, optical microscopy, Raman microscopy, and time‐of‐flight secondary ion mass spectrometry. Specifically, by determining the sizes of the polymer‐dispersed NaClO₂ particles, support for the hypothesis that UV light activates an interfacial layer of the NaClO₂ crystals to generate ClO₂ is obtained. Additionally, it is found that the half‐life of the UV‐activated state of NaClO₂ depends on the reactivity of the polymer matrix. Because both PVA and POD possess properties analogous to polymers used in packaging films, it is concluded that the approach described in this study may enable introduction of deodorizing or antimicrobial functional properties into polymeric packaging.     

Tunable Chemical and Topographic Patterns Based on Binary Colloidal Crystals (BCCs) to Modulate MG63 Cell Growth

More effective and diversified surface modification strategies are required for materials used in biomedical engineering. Combining surface modification involving bioactive signals or nonfouling polymers with tunable topography has the potential to meet this need. Here, a method is reported to generate bioactive surfaces having tunable topographies based on self‐assembled binary colloidal crystals (BCCs), where the colloids are premodified with nonfouling molecules or cell adhesive peptides. The BCCs are fabricated from silica (Si) microspheres and polymer nanospheres. The Si microspheres are either modified with poly(ethylene glycol) (PEG) or with the cell adhesive arginine–glycine–aspartic acid (RGD) peptide prior to BCC fabrication. Four types of BCCs are explored in cell studies using MG63 cells. BCC surfaces coupled with PEG or RGD peptides are found to significantly modulate cell adhesion, spreading, and morphology, which is attributed to the combination of BCC topography and the molecules at the particle surface within the BCC. PEG‐modified BCCs are expected to find applications where limited cell adhesion is required, while the RGD‐modified BCCs have the potential for enhancing cell growth on medical devices such as bone implants. More advanced cell biology applications such as controlled stem cell differentiation are also anticipated to find use from BCCs.     

Trust in sharing encounters among millennials

The sharing economy is a defining feature of the millennial generation. We report on a study of 1047 millennials and find that trust has more of an impact on their willingness to engage in some sharing encounters than in others. In particular, trust matters more in high‐dimensionality sharing encounters—those encounters that have a longer duration, require a greater financial investment, involve more social interaction, etc. Further, it is important to note that all sharing encounters take place through two‐sided intermediary platforms, and we find that the role of trust among the different types of sharing partners is not symmetrical across the two sides. Trust in the intermediary platform matters more to customers than to service providers in their willingness to engage in service encounters. Overall, this research contributes to existing literature by developing the notion of a service encounter and associated dimensionality and by demonstrating that service encounter dimensionality affects the importance of trust in the sharing economy. Also, we show how trust matters differently for different sides of two‐sided sharing platforms. Finally, this research focuses squarely on understanding the behaviours of millennials—the generation important to the sharing economy.     

Multimodal biometric system for ECG,ear and iris recognition based on local descriptors

Multimedia Tools and Applications - Combination of multiple information extracted from different biometric modalities in multimodal biometric recognition system aims to solve the different...     

Reliability-based design optimization of wind turbine drivetrain with integrated multibody gear dynamics simulation considering wind load uncertainty

This study aims to develop an integrated computational framework for the reliability-based design optimization (RBDO) of wind turbine drivetrains to assure the target reliability under wind load and gear manufacturing uncertainties. Gears in wind turbine drivetrains are subjected to severe cyclic loading due to highly variable wind loads that are stochastic in nature. Thus, the failure rate of drivetrain systems is reported to be higher than the other wind turbine components, and improving drivetrain reliability is critically important in reducing downtime caused by gear failures. In the numerical procedure developed in this study, a wide spatiotemporal variability for wind loads is considered using 249 sets of wind data to evaluate probabilistic contact fatigue life in the sampling-based RBDO. To account for wind load uncertainty in evaluation of the tooth contact fatigue, multiple drivetrain dynamics simulations need to be run under various wind load scenarios in the RBDO process. For this reason, a numerical procedure based on the multivariable tabular contact search algorithm is applied to the modeling of wind turbine drivetrains to reduce the overall computational time while retaining the precise contact geometry required for considering the gear tooth profile optimization. An integrated computational framework for the wind turbine drivetrain RBDO is then developed by incorporating the wind load uncertainty, the rotor blade aerodynamics model, the drivetrain dynamics model, and the probabilistic contact fatigue failure model. It is demonstrated that the RBDO optimum for a 750 kW wind turbine drivetrain obtained using the procedure developed in this study can achieve the target 97.725% reliability (2 sigma quality level) with only a 1.4% increase in the total weight from the baseline design, which had a reliability of 8.3%. Furthermore, it is shown that the tooth profile optimization, tip relief introduced as a design variable, prevents a large increase of the face width that would result in a large increase in the weight (cost) of the drivetrain in order to satisfy the target reliability against the tooth contact fatigue failure.     

Risk‐based Approach to Designing and Reviewing Pipeline Stream Crossings to Minimize Impacts to Aquatic Habitats and Species

Extensive new pipeline systems proposed to transport natural gas and oil throughout North America will potentially result in thousands of new stream crossings. The watercourses encountered at these crossings will range from small, ephemeral headwater streams to large, perennial mainstem rivers; from dynamic gravel‐bed streams to stable bedrock channels; and from steep, source reaches to low gradient, response reaches. Based on past experience at pipeline crossings, the potential for both short and long‐term negative impacts on aquatic habitat and species is substantial. In assessing potential hazards to aquatic habitat and species, the diverse physiography and ecology of the stream affected, combined with the number and range of new pipelines proposed, pose significant challenges for project developers charged with collecting, stratifying, evaluating, analysing, interpreting, and presenting stream crossing data in formats that are accessible, usable and useful. It is equally challenging for project reviewers to detect, distill and summarize potential project impacts and then identify reasonable options for their avoidance, minimization, and mitigation. To address these concerns, the US Fish and Wildlife Service, in conjunction with Ruby Pipeline, LLC, developed a pipeline crossing framework and risk analysis approach to stratify potential aquatic impacts, based on both stream characteristics and project types. In this approach, pipeline crossings are ranked in terms of relative short and long‐term risk to aquatic habitat and are then analysed, designed, and monitored in ways appropriate to their risk. This approach allows project developers and reviewers to focus resources and monitoring on the crossings that present the highest risks to aquatic habitat and species, while expediting design and construction, and minimizing the monitoring of low‐risk crossings. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.     

Optimized partial-coverage functional analysis pipeline (OPFAP): a semi-automated pipeline for skull stripping and co-registration of partial-coverage,ultra-high-field functional images

Objective

Ultra-high-field functional MRI (UHF-fMRI) allows for higher spatiotemporal resolution imaging. However, higher-resolution imaging entails coverage limitations. Processing partial-coverage images using standard pipelines leads to sub-optimal results. We aimed to develop a simple, semi-automated pipeline for processing partial-coverage UHF-fMRI data using widely used image processing algorithms.

Materials and methods

We developed automated pipelines for optimized skull stripping and co-registration of partial-coverage UHF functional images, using built-in functions of the Centre for Functional Magnetic Resonance Imaging of the Brain's (FMRIB’s) Software library (FSL) and advanced normalization tools. We incorporated the pipelines into the FSL’s functional analysis pipeline and provide a semi-automated optimized partial-coverage functional analysis pipeline (OPFAP).

Results

Compared to the standard pipeline, the OPFAP yielded images with 15 and 30% greater volume of non-zero voxels after skull stripping the functional and anatomical images, respectively (all p =?0.0004), which reflected the conservation of cortical voxels lost when the standard pipeline was used. The OPFAP yielded the greatest Dice and Jaccard coefficients (87 and 80%, respectively; all p <?0.0001) between the co-registered participant gyri maps and the template gyri maps, demonstrating the goodness of the co-registration results. Furthermore, the greatest volume of group-level activation in the most number of functionally relevant regions was observed when the OPFAP was used. Importantly, group-level activations were not observed when using the standard pipeline.

Conclusion

These results suggest that the OPFAP should be used for processing partial-coverage UHF-fMRI data for detecting high-resolution macroscopic blood oxygenation level-dependent activations.