Ultraefficient Thermophotovoltaic Power Conversion By Band-Edge Spectral Filtering

Thermophotovoltaic power conversion utilizes thermal radiation from a local heat source to generate electricity in a photovoltaic cell. It was shown in recent years that the addition of a highly reflective rear mirror to a solar cell maximizes the extraction of luminescence. This, in turn, boosts the voltage, enabling the creation of record-breaking solar efficiency. Now we report that the rear mirror can be used to create thermophotovoltaic systems with unprecedented high thermophotovoltaic efficiency. This mirror reflects low-energy infrared photons back into the heat source, recovering their energy. Therefore, the rear mirror serves a dual function; boosting the voltage and reusing infrared thermal photons. This allows the possibility of a practical \u3e50% efficient thermophotovoltaic system. Based on this reflective rear mirror concept, we report a thermophotovoltaic efficiency of 29.1 ± 0.4% at an emitter temperature of 1,207 °C

Tetrazine-Triggered Release of Carboxylic-Acid-Containing Molecules for Activation of an Anti-inflammatory Drug.

In addition to its use for the study of biomolecules in living systems, bioorthogonal chemistry has emerged as a promising strategy to enable protein or drug activation in a spatially and temporally controlled manner. This study demonstrates the application of a bioorthogonal inverse electron-demand Diels-Alder (iEDDA) reaction to cleave trans-cyclooctene (TCO) and vinyl protecting groups from carboxylic acid-containing molecules. The tetrazine-mediated decaging reaction proceeded under biocompatible conditions with fast reaction kinetics (<2 min). The anti-inflammatory activity of ketoprofen was successfully reinstated after decaging of the nontoxic TCOprodrug in live macrophages. Overall, this work expands the scope of functional groups and the application of decaging reactions to a new class of drugs

The state of HRM in the Middle East:Challenges and future research agenda

Based on a robust structured literature analysis, this paper highlights the key developments in the field of human resource management (HRM) in the Middle East. Utilizing the institutional perspective, the analysis contributes to the literature on HRM in the Middle East by focusing on four key themes. First, it highlights the topical need to analyze the context-specific nature of HRM in the region. Second, via the adoption of a systematic review, it highlights state of development in HRM in the research analysis set-up. Third, the analysis also helps to reveal the challenges facing the HRM function in the Middle East. Fourth, it presents an agenda for future research in the form of research directions. While doing the above, it revisits the notions of “universalistic” and “best practice” HRM (convergence) versus “best-fit” or context distinctive (divergence) and also alternate models/diffusion of HRM (crossvergence) in the Middle Eastern context. The analysis, based on the framework of cross-national HRM comparisons, helps to make both theoretical and practical implications

Guidance on Noncorticosteroid Systemic Immunomodulatory Therapy in Noninfectious Uveitis: Fundamentals Of Care for UveitiS (FOCUS) Initiative

Topic: An international, expert-led consensus initiative to develop systematic, evidence-based recommendations for the treatment of noninfectious uveitis in the era of biologics. Clinical Relevance: The availability of biologic agents for the treatment of human eye disease has altered practice patterns for the management of noninfectious uveitis. Current guidelines are insufficient to assure optimal use of noncorticosteroid systemic immunomodulatory agents. Methods: An international expert steering committee comprising 9 uveitis specialists (including both ophthalmologists and rheumatologists) identified clinical questions and, together with 6 bibliographic fellows trained in uveitis, conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol systematic review of the literature (English language studies from January 1996 through June 2016; Medline [OVID], the Central Cochrane library, EMBASE, CINAHL, SCOPUS, BIOSIS, and Web of Science). Publications included randomized controlled trials, prospective and retrospective studies with sufficient follow-up, case series with 15 cases or more, peer-reviewed articles, and hand-searched conference abstracts from key conferences. The proposed statements were circulated among 130 international uveitis experts for review. A total of 44 globally representative group members met in late 2016 to refine these guidelines using a modified Delphi technique and assigned Oxford levels of evidence. Results: In total, 10 questions were addressed resulting in 21 evidence-based guidance statements covering the following topics: when to start noncorticosteroid immunomodulatory therapy, including both biologic and nonbiologic agents; what data to collect before treatment; when to modify or withdraw treatment; how to select agents based on individual efficacy and safety profiles; and evidence in specific uveitic conditions. Shared decision-making, communication among providers and safety monitoring also were addressed as part of the recommendations. Pharmacoeconomic considerations were not addressed. Conclusions: Consensus guidelines were developed based on published literature, expert opinion, and practical experience to bridge the gap between clinical needs and medical evidence to support the treatment of patients with noninfectious uveitis with noncorticosteroid immunomodulatory agents

Automatic identification of urban settlement boundaries for multiple representation databases

Intuitive and meaningful interpretation of geographical phenomena requires their representation at multiple levels of detail. This is due to the scale dependent nature of their properties. Considerable interest remains in capturing once geographical information at the fine scale, and from this, automatically deriving information at various levels of detail and scale via the process of generalisation. Prior to the cartographic portrayal of that information, model generalisation is required in order to derive higher order phenomena associated with the smaller scales. This paper presents a technique for automatically identifying settlement boundaries based on our understanding of what constitutes ‘citiness’. From this, partonomic structures can be created that link the broad settlement with its constituent parts. The benefits of the resultant system include the automated populating of multiple representation databases (MRDB), better spatial analysis and the creation of semantic reference systems capable of supporting intelligent query or zoom. The creation of such hierarchical partonomic structures provides a very useful framework within which generalisation can take place. The methodology and implementation are presented together with an evaluation of the results. Future developments are proposed

A functional perspective on map generalisation

In the context of map generalisation, the ambition is to store once and then maintain a very detailed geographic database. Using a mix of modelling and cartographic generalisation techniques, the intention is to derive map products at varying levels of detail – from the fine scale to the highly synoptic. We argue that in modelling this process, it is highly advantageous to take a ‘functional perspective’ on map generalisation – rather than a geometric one. In other words to model the function as it manifests itself in the shapes and patterns of distribution of the phenomena being mapped – whether it be hospitals, airports, or cities. By modelling the functional composition of such features we can create relationships (partonomic, taxonomic and topological) that lend themselves directly to modelling, to analysis and most importantly to the process of generalisation. Borrowing from ideas in robotic vision this paper presents an approach for the automatic identification of functional sites (a collection of topographic features that perform a collective function) and demonstrates their utility in multi-scale representation and generalisation

Representing forested regions at small scales: automatic derivation from very large scale data

As with any class of feature, it is important to be able to view woodland or forest at multiple levels of detail. At the detailed level, a map can show clusters of trees, tree types, tracks and paths; at the small scale, say 1:250 000, we can discern broad patterns of forests and other land use, which can inform planners and act as input to land resource models. Rather than store such information in separate databases (requiring multiple points of maintenance), the vision is that the information has a single point of storage and maintenance, and that from this detailed level, various, more generalised forms can be automatically derived. This paper presents a methodology and algorithm for automatically deriving forest patches suitable for representation at 1:250 000 scale directly from a detailed dataset. In addition to evaluation of the output, the paper demonstrates how such algorithms can be shared and utilised via 'generalisation web services', arguing that the sharing of such algorithms can help accelerate developments in map generalisation, and increase the uptake of research solutions within commercial systems