Multifunctional Organoboron Compounds and Boralactonate Salts

Organoboron compounds have gathered an important significance within the chemistry community on account of their wide range of applications in synthesis, catalysis, and medicinal chemistry. Even though the uses of boron compounds in drug discovery have been overlooked until the last several decades, boronic acid containing molecules have garnered increased attention due to the unique chemical properties of the boron center. Boron-functionalized ��-aryl propionic acid non-steroidal anti-inflammatory drug derivatives (bora-NSAIDs) can be accessed via copper(I)-catalyzed alkene boracarboxylation, using CO2 and B2pin2. To explore and expand the current synthetic and future medicinal chemistry applications of these bora-NSAIDs, methods to derivatize the boron center need to be developed. Here, boron containing ibuprofen (bora-ibuprofen) synthesis via benchtop copper(I)-catalyzed alkene boracarboxylation was developed. Transesterification and transamination strategies have been employed to deprotect boron pinacol ester group in bora-ibuprofen, to synthesize additional bora-ibuprofen derivatives and subsequently isolate ibuprofen lactone boronic acid. Boracarboxylated products can be further functionalized by reacting them with potassium bifluoride under mild reaction conditions to afford air and moisture stable difluoroboralactonate salts. These Difluoroborolactonate salts exhibited remarkable stability under both acidic and basic hydrolytic conditions

An Audience Centred Approach to Business Process Reengineering

This paper describes a method for process modelling which is designed to provide guidance to the business process modeller. The method has evolved from our experience of attempting to apply software process modelling approaches to business processes. A major influence on the method has been our observations that a pragmatic approach to notation selection is required in order to maintain a meaningful dialogue with end-users. Business process modelling methods typically fall into two camps. General methods attempt to describe the managerial activities which surround the modelling itself (Coulson-Thomas, 94; GISIP, 95). Specific methods, on the other hand, tend to concentrate on the details of a particular notational approach. However, as with programming languages or design methods, no single notational approach is best suited to all problems. Ideally, the process modeller should be able to incorporate the appropriate notational approach into some coherent generic modelling method.This paper addresses the needs of the modeller at the detailed level without prescribing a specific notation. This is achieved by describing categories of modelling activities which the modeller should undertake within process modelling, and suggesting how notations may be used within these categories. Our method is generally applicable, and is illustrated here by models of processes within the Construction industry

Utilizing Multi-modal Weak Signals to Improve User Stance Inference in Social Media

Social media has become an integral component of the daily life. There are millions of various types of content being released into social networks daily. This allows for an interesting view into a users\u27 view on everyday life. Exploring the opinions of users in social media networks has always been an interesting subject for the Natural Language Processing researchers. Knowing the social opinions of a mass will allow anyone to make informed policy or marketing related decisions. This is exactly why it is desirable to find comprehensive social opinions. The nature of social media is complex and therefore obtaining the social opinion becomes a challenging task. Because of how diverse and complex social media networks are, they typically resonate with the actual social connections but in a digital platform. Similar to how users make friends and companions in the real world, the digital platforms enable users to mimic similar social connections. This work mainly looks at how to obtain a comprehensive social opinion out of social media network. Typical social opinion quantifiers will look at text contributions made by users to find the opinions. Currently, it is challenging because the majority of users on social media will be consuming content rather than expressing their opinions out into the world. This makes natural language processing based methods impractical due to not having linguistic features. In our work we look to improve a method named stance inference which can utilize multi-domain features to extract the social opinion. We also introduce a method which can expose users opinions even though they do not have on-topical content. We also note how by introducing weak supervision to an unsupervised task of stance inference we can improve the performance. The weak supervision we bring into the pipeline is through hashtags. We show how hashtags are contextual indicators added by humans which will be much likelier to be related than a topic model. Lastly we introduce disentanglement methods for chronological social media networks which allows one to utilize the methods we introduce above to be applied in these type of platforms

Investigation of shock waves in explosive blasts using fibre optic pressure sensors

The published version of this article may be accessed at the link below. Copyright @ IOP Publishing, 2006.We describe miniature all-optical pressure sensors, fabricated by wafer etching techniques, less than 1 mm(2) in overall cross-section with rise times in the mu s regime and pressure ranges typically 900 kPa (9 bar). Their performance is suitable for experimental studies of the pressure-time history for test models exposed to shocks initiated by an explosive charge. The small size and fast response of the sensors promises higher quality data than has been previously available from conventional electrical sensors, with potential improvements to numerical models of blast effects. Results from blast tests are presented in which up to six sensors were multiplexed, embedded within test models in a range of orientations relative to the shock front.Support from the UK Engineering&Physical Sciences Research Council and Dstl Fort Halstead through the MoD Joint Grants Scheme are acknowledged. WN MacPherson is supported by an EPSRC Advanced Research Fellowship

Patterns of dominant flows in the world trade web

The large-scale organization of the world economies is exhibiting increasingly levels of local heterogeneity and global interdependency. Understanding the relation between local and global features calls for analytical tools able to uncover the global emerging organization of the international trade network. Here we analyze the world network of bilateral trade imbalances and characterize its overall flux organization, unraveling local and global high-flux pathways that define the backbone of the trade system. We develop a general procedure capable to progressively filter out in a consistent and quantitative way the dominant trade channels. This procedure is completely general and can be applied to any weighted network to detect the underlying structure of transport flows. The trade fluxes properties of the world trade web determines a ranking of trade partnerships that highlights global interdependencies, providing information not accessible by simple local analysis. The present work provides new quantitative tools for a dynamical approach to the propagation of economic crises

The International-Trade Network: Gravity Equations and Topological Properties

This paper begins to explore the determinants of the topological properties of the international - trade network (ITN). We fit bilateral-trade flows using a standard gravity equation to build a "residual" ITN where trade-link weights are depurated from geographical distance, size, border effects, trade agreements, and so on. We then compare the topological properties of the original and residual ITNs. We find that the residual ITN displays, unlike the original one, marked signatures of a complex system, and is characterized by a very different topological architecture. Whereas the original ITN is geographically clustered and organized around a few large-sized hubs, the residual ITN displays many small-sized but trade-oriented countries that, independently of their geographical position, either play the role of local hubs or attract large and rich countries in relatively complex trade-interaction patterns