Design and synthesis of a screening library using the natural product scaffold 3-chloro-4-hydroxyphenylacetic acid

The fungal metabolite 3-chloro-4-hydroxyphenylacetic acid (1) was utilized in the generation of a unique drug-like screening library using parallel solution-phase synthesis. A 20-membered amide library (3–22) was generated by first converting 1 to methyl (3-chloro-4-hydroxyphenyl)acetate (2), then reacting this scaffold with a diverse series of primary amines via a solvent-free aminolysis procedure. The structures of the synthetic analogues (3–22) were elucidated by spectroscopic data analysis. The structures of compounds 8, 12, and 22 were confirmed by single X-ray crystallographic analysis. All compounds were evaluated for cytotoxicity against a human prostate cancer cell line (LNCaP) and for antiparasitic activity toward Trypanosoma brucei brucei and Plasmodium falciparum and showed no significant activity at 10 μM. The library was also tested for effects on the lipid content of LNCaP and PC-3 prostate cancer cells, and it was demonstrated that the fluorobenzyl analogues (12–14) significantly reduced cellular phospholipid and neutral lipid levels.

Applying digital product memories in industrial production

Industrial production and supply chains face increased demands for mass customization and tightening regulations on the traceability of goods, leading to higher requirements concerning flexibility, adaptability, and transparency of processes. Technologies for the ’Internet of Things' such as smart products and semantic representations pave the way for future factories and supply chains to fulfill these challenging market demands. In this chapter a backend-independent approach for information exchange in open-loop production processes based on Digital Product Memories DPMs is presented. By storing order-related data directly on the item, relevant lifecycle information is attached to the product itself. In this way, information handover between several stages of the value chain with focus on the manufacturing phase of a product has been realized. In order to report best practices regarding the application of DPM in the domain of industrial production, system prototype implementations focusing on the use case of producing and handling a smart drug case are illustrated.

An empirical study of capability development within product innovation projects

The objective of this paper is to develop insights into firms’ strategic capability development processes within product innovation projects. In particular, the research aims at investigating the interactions among product innovation, knowledge processes, and capability development within firms. Building on qualitative data from the auto-industry, our analysis reveals that across four product innovation projects, the case company developed architectural knowledge and capability. Findings reveal that, along with changes at each level of product architecture, “design knowledge” and “design capability” have been developed at the same level of product architecture, leading to capability development at that level. Furthermore, findings suggest that such capability transformation resulting from knowledge and capability creation over the course of case projects leads to modularization of product architecture. Overall, the research contributes to identifying and emphasizing the role of micro processes in capability development and renewal, which in turn enhances our understanding of strategic capability development processes.

A normal-distribution based rating aggregation method for generating product reputations

With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.

User centred engineering in automotive design: A shift from technology-driven product development

The research assessed how best to transition engineering-based automotive firms towards more customer-orientated design and development approaches, whilst identifying the main barriers and concerns facing such a shift. The research investigates the ability of a firm to empower individual engineers with user centred design tools traditionally used by designers, whilst understanding the company-wide needs to facilitate their implementation.

A novel approach to increasing inventory with the current panel: Increasing donation frequency by asking for a different blood product

BACKGROUND Ongoing shortages of blood products may be addressed through additional donations. However, donation frequency rates are typically lower than medically possible. This preliminary study aims to determine voluntary nonremunerated whole blood (WB) and plasmapheresis donors' willingness, and subsequent facilitators and barriers, to make additional donations of a different type. STUDY DESIGN AND METHODS Forty individual telephone interviews were conducted posing two additional donation pattern scenarios: first, making a single and, second, making multiple plasmapheresis donations between WB donations. Stratified purposive sampling was conducted for four samples varying in donation experience: no-plasma, new-to-both-WB-and-plasma, new-to-plasma, and plasma donors. Interviews were analyzed yielding excellent (κ values > 0.81) inter-rater reliability. RESULTS Facilitators were more endorsed than barriers for a single but not multiple plasmapheresis donation. More new-to-both donors (n = 5) were willing to make multiple plasma donations between WB donations than others (n = 1 each) and identified fewer barriers (n = 3) than those more experienced in donation (n = 8 no plasma, n = 10 new to both, n = 11 plasma). Donors in the plasma sample were concerned about the subsequent reduced time between plasma donations by adding WB donations (n = 3). The no-plasma and new-to-plasma donors were concerned about the time commitment required (n = 3). CONCLUSION Current donors are willing to add different product donations but donation history influences their willingness to change. Early introduction of multiple donation types, variation in inventory levels, and addressing barriers will provide blood collection agencies with a novel and cost-effective inventory management strategy.

Using an extended theory of planned behavior to predict a change in the type of blood product donated

Background Demand for essential plasma-derived products is increasing. Purpose This prospective study aims to identify predictors of voluntary non-remunerated whole blood (WB) donors becoming plasmapheresis donors. Methods Surveys were sent to WB donors who had recently (recent n = 1,957) and not recently donated (distant n = 1,012). Theory of Planned Behavior (TPB) constructs (attitude, subjective norm, self-efficacy) were extended with moral norm, anticipatory regret, and donor identity. Intentions and objective plasmapheresis donation for 527 recent and 166 distant participants were assessed. Results Multi-group analysis revealed that the model was a good fit. Moral norm and self-efficacy were positively associated while role identity (suppressed by moral norm) was negatively associated with plasmapheresis intentions. Conclusions The extended TPB was useful in identifying factors that facilitate conversion from WB to plasmapheresis donation. A superordinate donor identity may be synonymous with WB donation and, for donors with a strong moral norm for plasmapheresis, may inhibit conversion.

Disruptive innovations in complex product systems industries: A case study

We propose that disruptive changes pertaining to complex product systems (CoPS) will yield a different set of characteristics than those traditionally observed for commodity products, and seek evidence for this proposition in a case study of the Flash Converting technology, a disruptive CoPS innovation in the copper production industry. Our results show that unlike disruptions in commodity product industries, the incumbent CoPS technology does not overshoot mainstream market performance demand. Also, the disruptive CoPS innovation: (i) is not nurtured in low-end niche markets; (ii) initially satisfies mainstream market performance demand, and; (iii) has higher unit price than the incumbent technology.

Independent distractor frequency and age-of-acquisition dffects in picture-word interference: FMRI evidence for post-lexical and lexical accounts according to distractor type

In two fMRI experiments, participants named pictures with superimposed distractors that were high or low in frequency or varied in terms of age of acquisition. Pictures superimposed with low-frequency words were named more slowly than those superimposed with high-frequency words, and late-acquired words interfered with picture naming to a greater extent than early-acquired words. The distractor frequency effect (Experiment 1) was associated with increased activity in left premotor and posterior superior temporal cortices, consistent with the operation of an articulatory response buffer and verbal selfmonitoring system. Conversely, the distractor age-of-acquisition effect (Experiment 2) was associated with increased activity in the left middle and posterior middle temporal cortex, consistent with the operation of lexical level processes such as lemma and phonological word form retrieval. The spatially dissociated patterns of activity across the two experiments indicate that distractor effects in picture-word interference may occur at lexical or postlexical levels of processing in speech production.

Aspect-based opinion mining from product reviews using conditional random fields

Product reviews are the foremost source of information for customers and manufacturers to help them make appropriate purchasing and production decisions. Natural language data is typically very sparse; the most common words are those that do not carry a lot of semantic content, and occurrences of any particular content-bearing word are rare, while co-occurrences of these words are rarer. Mining product aspects, along with corresponding opinions, is essential for Aspect-Based Opinion Mining (ABOM) as a result of the e-commerce revolution. Therefore, the need for automatic mining of reviews has reached a peak. In this work, we deal with ABOM as sequence labelling problem and propose a supervised extraction method to identify product aspects and corresponding opinions. We use Conditional Random Fields (CRFs) to solve the extraction problem and propose a feature function to enhance accuracy. The proposed method is evaluated using two different datasets. We also evaluate the effectiveness of feature function and the optimisation through multiple experiments.

Quality-aware review selection based on product feature taxonomy

As of today, user-generated information such as online reviews has become increasingly significant for customers in decision making process. Meanwhile, as the volume of online reviews proliferates, there is an insistent demand to help the users tackle the information overload problem. In order to extract useful information from overwhelming reviews, considerable work has been proposed such as review summarization and review selection. Particularly, to avoid the redundant information, researchers attempt to select a small set of reviews to represent the entire review corpus by preserving its statistical properties (e.g., opinion distribution). However, one significant drawback of the existing works is that they only measure the utility of the extracted reviews as a whole without considering the quality of each individual review. As a result, the set of chosen reviews may consist of low-quality ones even its statistical property is close to that of the original review corpus, which is not preferred by the users. In this paper, we proposed a review selection method which takes review quality into consideration during the selection process. Specifically, we examine the relationships between product features based upon a domain ontology to capture the review characteristics based on which to select reviews that have good quality and preserve the opinion distribution as well. Our experimental results based on real world review datasets demonstrate that our proposed approach is feasible and able to improve the performance of the review selection effectively.

Re-valuing construction materials and components through design for disassembly

The construction industry accounts for a significant portion of the material consumption of our industrialised societies. That material consumption comes at an environmental cost, and when buildings and infrastructure projects are demolished and discarded, after their useful lifespan, that environmental cost remains largely unrecovered. The expected operational lifespan of modern buildings has become disturbingly short as buildings are replaced for reasons of changing cultural expectations, style, serviceability, locational obsolescence and economic viability. The same buildings however are not always physically or structurally obsolete; the materials and components within them are very often still completely serviceable. While there is some activity in the area of recycling of selected construction materials, such as steel and concrete, this is almost always in the form of down cycling or reprocessing. Very little of this material and component resource is reuse in a way that more effectively captures its potential. One significant impediment to such reuse is that buildings are not designed in a way that facilitates easy recovery of materials and components; they are designed and built for speed of construction and quick economic returns, with little or no consideration of the longer term consequences of their physical matter. This research project explores the potential for the recovery of materials and components if buildings were designed for such future recovery; a strategy of design for disassembly. This is not a new design philosophy; design for disassembly is well understood in product design and industrial design. There are also some architectural examples of design for disassembly; however these are specialist examples and there is no significant attempt to implement the strategy in the main stream construction industry. This paper presents research into the analysis of the embodied energy in buildings, highlighting its significance in comparison with operational energy. Analysis at material, component, and whole-of-building levels shows the potential benefits of strategically designing buildings for future disassembly to recover this embodied energy. Careful consideration at the early design stage can result in the deconstruction of significant portions of buildings and the recovery of their potential through higher order reuse and upcycling.

Adding paths to resilience and daily accounts to an already rich field of inquiry: A brief commentary on James Jackson's "Social structure and health disparities"

In absolute terms, there have been improvements in social resources for all racial and ethnic groups in the United States. The rise in education levels among blacks and Hispanics, for instance, suggests a lessening of the gap between classes, beginning in the later part of the 1960’s (Kao & Thompson, 2003). Yet the divide in income and to a lesser extent education between peoples who differ in gender, skin color and ethnic origin continues and in many ways is greater now than ever (Danziger & Gottschalk, 1997); (Gottschalk, 1997). The psychological distance between those high and those low in social-economic status continues unabated and threatens to undermine the capacity of communities to foster the positive architecture of hope, optimism and equal opportunity that holds us together as a nation...

The role of emotion in product, service and business model design

Designers have become aware of the importance of creating strong emotional experiences intertwined with new tangible products for the past decade, however an increased interest from firms has emerged in developing new service and business models as complimentary forms of emotion-driven innovation. This interdisciplinary study draws from the psychological sciences – theory of emotion – and the management sciences – business model literature to introduce this new innovation agenda. The term visceral hedonic rhetoric (VHR) is defined as the properties of a product, (and in this paper service and business model extensions) that persuasively induce the pursuit of pleasure at an instinctual level of cognition. This research paper lays the foundation for VHR beyond a product setting, presenting the results from an empirical study where organizations explored the possibilities for VHR in the context of their business. The results found that firms currently believe VHR is perceived in either their product and/or services they provide. Implications suggest shifting perspective surrounding the use of VHR across a firm’s business model design in order to influence the outcomes of their product and/or service design, resulting in an overall stronger emotional connection with the customer.

Predictive models for water sources with high susceptibility for bromine-containing disinfection by-product formation: Implications for water treatment

This study examines a matrix of synthetic water samples designed to include conditions that favour brominated disinfection by-product (Br-DBP) formation, in order to provide predictive models suitable for high Br-DBP forming waters such as salinity-impacted waters. Br-DBPs are known to be more toxic than their chlorinated analogues, in general, and their formation may be favoured by routine water treatment practices such as coagulation/flocculation under specific conditions; therefore, circumstances surrounding their formation must be understood. The chosen factors were bromide concentration, mineral alkalinity, bromide to dissolved organic carbon (Br/DOC) ratio and Suwannee River natural organic matter concentration. The relationships between these parameters and DBP formation were evaluated by response surface modelling of data generated using a face-centred central composite experimental design. Predictive models for ten brominated and/or chlorinated DBPs are presented, as well as models for total trihalomethanes (tTHMs) and total dihaloacetonitriles (tDHANs), and bromide substitution factors for the THMs and DHANs classes. The relationships described revealed that increasing alkalinity and increasing Br/DOC ratio were associated with increasing bromination of THMs and DHANs, suggesting that DOC lowering treatment methods that do not also remove bromide such as enhanced coagulation may create optimal conditions for Br-DBP formation in waters in which bromide is present.