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Nanoemulsions have attracted significant attention in food fields and can increase the functionality of the bioactive compounds contained within them. In this paper, the preparation methods, including low-energy and high-energy methods, were first reviewed. Second, the physical and chemical destabilization mechanisms of nanoemulsions, such as gravitational separation (creaming or sedimentation), flocculation, coalescence, Ostwald ripening, lipid oxidation and so on, were reviewed. Then, the impact of different stabilizers, including emulsifiers, weighting agents, texture modifiers (thickening agents and gelling agents), ripening inhibitors, antioxidants and chelating agents, on the physicochemical stability of nanoemulsions were discussed. Finally, the applications of nanoemulsions for the delivery of functional ingredients, including bioactive lipids, essential oil, flavor compounds, vitamins, phenolic compounds and carotenoids, were summarized. This review can provide some reference for the selection of preparation methods and stabilizers that will improve performance in nanoemulsion-based products and expand their usage.

Edible coatings and films (ECF) are employed as matrixes for incorporating antimicrobial nanoparticles (NPs), and then they are applied on the fruits and vegetables to prolong shelf life and enhance storage quality. This paper provides a comprehensive review on the preparation, antimicrobial properties and mechanisms, surface and physical qualities of ECF containing antimicrobial NPs, and its efficient application to vegetables and fruits as well. Following an introduction on the properties of the main edible coating materials, the preparation technologies of ECF with NPs are summarized. The antimicrobial activity of ECF with NPs against the tested microorganism was observed by many researchers. This might be mainly due to the electrostatic interaction between the cationic polymer or free metal ions and the charged cell membrane, the photocatalytic reaction of NPs, the detachment of free metal ion, and partly due to the antimicrobial activity of edible materials. Moreover, their physical, mechanical and releasing properties are discussed in detail, which might be influenced by the concentration of NPs. The preservation potential on the quality of fruits and vegetables indicates that various ECF with NPs might be used as the ideal materials for food application. Following the introduction on these characteristics, an attempt is made to predict future trends in this field.

According to the fifth Intergovernmental Panel on Climate Change (IPCC) assessment report, the urban environment is responsible for between 71% and 76% of carbon emissions from global final energy use and between 67% and 76% of global energy use. Two important and trending domains in urban environment are “resilience” and “net zero” associated with high-performance design, both of which have their origins in ecology. The ultimate goal of net zero energy has become the ultimate “high-performance” standard for buildings. Another emerging index is the measurement and improvement of the resilience of buildings. Despite the richness of research on net zero energy and resilience in the urban environment, literature that compares net zero energy and resilience is very limited. This paper provides an overview of research activities in those two research domains in the past 40 years. The purpose of this review is to (1) explore the shared ecological roots of the two domains, (2) identify the main research areas/clusters within each, (3) gain insight into the size of the different research topics, and (4) identify any research gaps. Finally, conclusions about the review focus on the major difference between the net zero movement and resilience theory in the urban environment and their respective relations to their ecological origins.

This paper focuses on extending drug release duration from contact lenses by incorporating catanionic aggregates. The aggregates consist of a long-chain cationic surfactant, i.e., cetalkonium chloride (CKC), and an oppositely charged anti-inflammatory amphiphilic drug. We studied three non-steroidal anti-inflammatory (NSAID) drugs with different octanol–water partition coefficients; diclofenac sodium (DFNa), flurbiprofen sodium (FBNa), and naproxen sodium (NPNa). Confirmation of catanionic aggregate formation in solution was determined by steady and dynamic shear rheology measurements. We observed the increased viscosity, shear thinning, and viscoelastic behavior characteristic of wormlike micelles; the rheological data are reasonably well described using a Maxwellian fluid model with a single relaxation time. In vitro release experiments demonstrated that the extension in the drug release time is dependent on the ability of a drug to form viscoelastic catanionic aggregates. Such aggregates retard the diffusive transport of drug molecules from the contact lenses. Our study revealed that the release kinetics depends on the CKC concentration and the alkyl chain length of the cationic surfactant. We demonstrated that more hydrophobic drugs such as diclofenac sodium show a more extended release than less hydrophobic drugs such as naproxen sodium.

Evapotranspiration (ET) is a major component of the global and regional water cycle. An operational Geostationary Operational Environmental Satellite (GOES) ET and Drought (GET-D) product system has been developed by the National Environmental Satellite, Data and Information Service (NESDIS) in the National Oceanic and Atmospheric Administration (NOAA) for numerical weather prediction model validation, data assimilation, and drought monitoring. GET-D system was generating ET and Evaporative Stress Index (ESI) maps at 8 km spatial resolution using thermal observations of the Imagers on GOES-13 and GOES-15 before the primary operational GOES satellites transitioned to GOES-16 and GOES-17 with the Advanced Baseline Imagers (ABI). In this study, the GET-D product system is upgraded to ingest the thermal observations of ABI with the best spatial resolution of 2 km. The core of the GET-D system is the Atmosphere-Land Exchange Inversion (ALEXI) model, which exploits the mid-morning rise in the land surface temperature to deduce the land surface fluxes including ET. Satellite-based land surface temperature and solar insolation retrievals from ABI and meteorological forcing from NOAA NCEP Climate Forecast System (CFS) are the major inputs to the GET-D system. Ancillary data required in GET-D include land cover map, leaf area index, albedo and cloud mask. This paper presents preliminary results of ET from the upgraded GET-D system after a brief introduction of the ALEXI model and the architecture of GET-D system. Comparisons with in situ ET measurements showed that the accuracy of the GOES-16 ABI based ET is similar to the results from the legacy GET-D ET based on GOES-13/15 Imager data. The agreement with the in situ measurements is satisfactory with a correlation of 0.914 averaged from three Mead sites. Further evaluation of the ABI-based ET product, upgrade efforts of the GET-D system for ESI products, and conclusions for the ABI-based GET-D products are discussed.

Memory institutions must be able to grow a fully-functional repository incrementally as collections grow, without expensive enterprise storage, massive data migrations, and the performance limits that stem from the vertical storage strategies. The Digital Repository at Scale that Invites Computation (DRAS-TIC) Fedora research project, funded by a two-year National Digital Platform grant from the Institute for Museum and Library Services (IMLS), is producing open-source software, tested cluster configurations, documentation, and best-practice guides that enable institutions to manage linked data repositories with petabyte-scale collections reliably. DRAS-TIC is a research initiative at the University of Maryland (UMD). The first DRAS-TIC repository system, named Indigo, was developed in 2015 and 2016 through a collaboration between U.K.-based storage company, Archive Analytics Ltd., and the UMD iSchool Digital Curation Innovation Center (DCIC), through funding from an NSF DIBBs (Data Infrastructure Building Blocks) grant (NCSA “Brown Dog”). DRAS-TIC Indigo leverages industry standard distributed database technology, in the form of Apache Cassandra, to provide open-ended scaling of repository storage without performance degradation. With the DRAS-TIC Fedora initiative, we make use of the Trellis Linked Data Platform (LDP), developed by Aaron Coburn at Amherst College, to add the LDP API over similar Apache Cassandra storage. This paper will explain our partner use cases, explore the system components, and showcase our performance-oriented approach, with the most emphasis given to performance measures available through the analytical dashboard on our testbed website.

Climate change is one of the prominent factors that causes an increased severity of extreme precipitation which, in turn, has a huge impact on drainage systems by means of flooding. Intensity–duration–frequency (IDF) curves play an essential role in designing robust drainage systems against extreme precipitation. It is important to incorporate the potential threat from climate change into the computation of IDF curves. Most existing works that have achieved this goal were based on Generalized Extreme Value (GEV) analysis combined with various circulation model simulations. Inspired by recent works that used machine learning algorithms for spatial downscaling, this paper proposes an alternative method to perform projections of precipitation intensity over short durations using machine learning. The method is based on temporal downscaling, a downscaling procedure performed over the time scale instead of the spatial scale. The method is trained and validated using data from around two thousand stations in the US. Future projection of IDF curves is calculated and discussed.

Lithium-ion batteries typically exhibit a transition to a more rapid capacity fade trend when subjected to extended charge–discharge cycles and storage conditions. The identification of the knee point can be valuable to identify the more severe degradation trend, and to provide guidance when scheduling battery replacements and planning secondary uses of the battery. However, a concise and repeatable determination of a knee point has not been documented. This paper provides a definition of the knee point which can be used as a degradation metric, and develops an algorithm to identify it. The algorithm is implemented on various data cases, and the results indicate that the approach provides repeatable knee point identification.

Enhanced cooling, coupled with novel designs and packaging of semiconductors, has revolutionized communications, computing, lighting, and electric power conversion. It is time for a similar revolution that will unleash the potential of electrified propulsion technologies to drive improvements in fuel-to-propulsion efficiency, emission reduction, and increased power and torque densities for aviation and beyond. High efficiency and high specific power (kW/kg) electric motors are a key enabler for future electrification of aviation. To improve cooling of emerging synchronous machines, and to realize performance and cost metrics of next-generation electric motors, electromagnetic and thermomechanical co-design can be enabled by innovative design topologies, materials, and manufacturing techniques. This paper focuses on the most recent progress in thermal management of electric motors with particular focus on electric motors of significance to aviation propulsion.

Multi-sensor systems are proliferating in the asset management industry. Industry 4.0, combined with the Internet of Things (IoT), has ushered in the requirements of prognostics and health management systems to predict the system’s reliability and assess maintenance decisions. State of the art systems now generate big machinery data and require multi-sensor fusion for integrated remaining useful life prognostic capabilities. When dealing with these data sets, traditional prediction methods are not equipped to handle the multiple sensor signals in unison. To address this challenge, this paper proposes a new, deep, adversarial approach to any remaining useful life prediction in which a novel, non-Markovian, variational, inference-based model, incorporating an adversarial methodology, is derived. To evaluate the proposed approach, two public multi-sensor data sets are used for the remaining useful life prediction applications: (1) CMAPSS turbofan engine dataset, and (2) FEMTO Pronostia rolling element bearing data set. The proposed approach obtains favorable results when against similar deep learning models.

A comprehensive case study on life-cycle cost analysis (LCCA) was conducted on a two- story education building with a projected 40-year lifespan in College Park, Maryland. The aim of this paper was to (1) create a life cycle assessment model, using an education building to test the model, (2) compare the life cycle cost (LCC) of different renovation scenarios, taking into account added renewable energy resources to achieve the university’s overall carbon neutrality goal, and (3) verify the robustness of the LCC model by conducting sensitivity analysis and studying the influence of different variables. Nine renovation scenarios were constructed by combining six renovation techniques and three renewable energy resources. The LCCA results were then compared to understand the cost-effective relation between implementing energy reduction techniques and renewable energy sources. The results indicated that investing in energy-efficient retrofitting techniques was more cost-effective than investments in renewable energy sources in the long term. In the optimum scenario, renovation and renewable energy, when combined, produced close to a 90% reduction in the life cycle cost compared to the baseline. The payback period for the initial investment cost, including avoided electricity costs, varies from 1.4 to 4.1 years. This suggests that the initial investment in energy-efficient renovation is the primary factor in the LCC of an existing building.

Creating a sense of place and community is a guiding principle in designing livable and high-quality built environments. This paper presents a framework for understanding the relationship between design and people’s perceptions about a place, within an urban design context. While a large volume of literature on sense of place (SOP) already exists, the proposed framework and its application in the design field present a unique opportunity to add new knowledge to this interdisciplinary topic. This research will investigate the empirical relationship between architecture/urban design and people’s perceptions about a place and their contributions to SOP. Urban designers and architects play important and determining roles in defining the physical qualities and the characteristics of a place. However, it has always been challenging to quantify the relationship between a physical environment and a person’s emotional experience. Three urban sites were analyzed to illustrate this framework, and four physical characteristics and four perceptual qualities were cross-investigated and analyzed. This proposed framework will help architects and urban designers to gain a better understanding of SOP and placemaking techniques, eventually helping to improve urban design quality.

The increasing demand for high food quality and safety, and concerns of environment sustainable development have been encouraging researchers in the food industry to exploit the robust and green biodegradable nanocomposites, which provide new opportunities and challenges for the development of nanomaterials in the food industry. This review paper aims at summarizing the recent three years of research findings on the new development of nanomaterials for food packaging. Two categories of nanomaterials (i.e., inorganic and organic) are included. The synthetic methods, physical and chemical properties, biological activity, and applications in food systems and safety assessments of each nanomaterial are presented. This review also highlights the possible mechanisms of antimicrobial activity against bacteria of certain active nanomaterials and their health concerns. It concludes with an outlook of the nanomaterials functionalized in food packaging.

Derating is widely applied to electronic components and products to ensure or extend their operational life for the targeted application. However, there are currently no derating guidelines for Li-ion batteries. This paper presents derating methodology and guidelines for Li-ion batteries using temperature, discharge C-rate, charge C-rate, charge cut-off current, charge cut-off voltage, and state of charge (SOC) stress factors to reduce the rate of capacity loss and extend battery calendar life and cycle life. Experimental battery degradation data from our testing and the literature have been reviewed to demonstrate the role of stress factors in battery degradation and derating for two widely used Li-ion batteries: graphite/LiCoO2 (LCO) and graphite/LiFePO4 (LFP). Derating factors have been computed based on the battery capacity loss to quantitatively evaluate the derating effects of the stress factors and identify the significant factors for battery derating.

Premature battery drain, swelling and fires/explosions in lithium-ion batteries have caused wide-scale customer concerns, product recalls, and huge financial losses in a wide range of products including smartphones, laptops, e-cigarettes, hoverboards, cars, and commercial aircraft. Most of these problems are caused by defects which are difficult to detect using conventional nondestructive electrical methods and disassembly-based destructive analysis. This paper develops an effective computed tomography (CT)-based nondestructive approach to assess battery quality and identify manufacturing-induced defects and structural deformations in batteries. Several unique case studies from commercial e-cigarette and smartphone applications are presented to show where CT analysis methods work.

Solid oxide fuel cells (SOFCs) are a highly efficient chemical to electrical energy conversion devices that have potential in a global energy strategy. The wide adoption of SOFCs is currently limited by cost and concerns about cell durability. Improved understanding of their degradation modes and mechanisms combined with reduction–oxidation stable anodes via all-ceramic-anode cell technology are expected to lead to durability improvements, while economies of scale for production will mitigate cost of commercialization. This paper presents an Ishikawa analysis and a failure modes, mechanisms, effects, and criticality analysis (FMMECA) for all-ceramic anode based SOFCs. FMMECA takes into account the life cycle conditions, multiple failure mechanisms, and their potential effects on fuel-cell health and safety.

The aim of this paper is to propose a novel building information model (BIM)–building performance model (BPM)–building environmental model (BEM) framework to identify the most energy-efficient and cost-effective strategies for the renovation of existing education buildings to achieve the nearly zero-energy goal while minimizing the environmental impact. A case building, the University of Maryland’s Architecture Building, was used to demonstrate the validity of the framework and a set of building performance indicators—including energy performance, environmental impacts, and occupant satisfaction—were used to evaluate renovation strategies. Additionally, this novel framework further demonstrated the interoperability among different digital tools and platforms. Lastly, following a detailed analysis and measurements, the case study results highlighted a particular energy profile as well as the retrofit needs of education buildings. Eight different renovation packages were analyzed with the top-ranking package indicating an energy saving of 62%, carbon emissions reduction of 84%, and long-term cost savings of 53%, albeit with a relatively high initial cost. The most preferable package ranked second in all categories, with a moderate initial cost.

Sea-level rise (SLR) will magnify the impacts of storm surge; the resulting severe flooding and inundation can cause huge damage to coastal communities. Community leaders are considering implementing adaptation strategies, typically hard engineering projects, to protect coastal assets and resources. It is important to understand the costs and benefits of the proposed project before any decision is made. To mitigate the flooding impact of joint effects of storm surge and SLR, building levee segments is chosen to be a corresponding adaptation strategy to protect the real estate assets in the study area—the City of Miami, FL, USA. This paper uses the classic Cost-Benefit Analysis (CBA) to assess the cost efficiency and proposes corresponding improvements in the benefit estimation, by estimating the avoided damages of implementing levee projects. Results show that the city will benefit from implementing levee projects along the Miami River in both a one-time 10 year storm event with SLR and cumulative long-term damage scenarios. This study also suggests that conducting CBA is a critical process before making coastal adaptation planning investment. A more meaningful result of cost effectiveness is estimated by accounting for the appreciation and time value. In addition, a sensitivity analysis is conducted to verify how the choice of discount rate influences the result. Uncertain factors including the rate of SLR, storm intensification, land use changes, and real estate appreciation are further analyzed.

The aim of this paper is to propose a novel building information model (BIM)–building performance model (BPM)–building environmental model (BEM) framework to identify the most energy-efficient and cost-effective strategies for the renovation of existing education buildings to achieve the nearly zero-energy goal while minimizing the environmental impact. A case building, the University of Maryland’s Architecture Building, was used to demonstrate the validity of the framework and a set of building performance indicators—including energy performance, environmental impacts, and occupant satisfaction—were used to evaluate renovation strategies. Additionally, this novel framework further demonstrated the interoperability among different digital tools and platforms. Lastly, following a detailed analysis and measurements, the case study results highlighted a particular energy profile as well as the retrofit needs of education buildings. Eight different renovation packages were analyzed with the top-ranking package indicating an energy saving of 62%, carbon emissions reduction of 84%, and long-term cost savings of 53%, albeit with a relatively high initial cost. The most preferable package ranked second in all categories, with a moderate initial cost.

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 2000–2010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approachAn independent validation dataset was also developed using Google Earth™ imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 km2.