951 resultados para Khatri-Rao product
Developing and evaluating approaches for utilising injury data to support product safety initiatives
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With increasing concern about consumer product-related injuries in Australia, product safety regulators need evidence-based research to understand risks and patterns to inform their decision making. This study analysed paediatric injury data to identify and quantify product-related injuries in children to inform product safety prioritisation. This study provides information on novel techniques for interrogating health data to identify trends and patterns in product-related injuries to inform strategic directions in this growing area of concern.
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New product innovation has been identified as the key to firms' marketplace success, profit and survival. Yet, the failure rate for new products is high. Because of the high costs associated with new product development, there is considerable theoretical and managerial interest in how to minimize the high failure rates of new products and what separates new product winners from losers. This study focuses on individual level ambidexterity – namely head of the R&D departments' capacity to engage in creativity and attention-to-detail simultaneously, a skill involving different centers of attention, and relying on somewhat incompatible behaviors and processes. The ability to engage in these behaviors simultaneously is seen as being ambidextrous. Drawing from the data of 150 advanced manufacturing firms in India (gathered from one CEO and one head of the R&D department for each firm), the results show that when an individual head of R&D engages heavily only in creativity, too many new, risky ideas may come and when he/she engages heavily only in attention-to-detail, he/she may suffer through a lack of novel ideas. Both approaches limit individual's contribution to enhancing product innovation – financial performance relationship. The results also show that an individual head of R&D needs to engage in high levels creativity and attention-to-detail in the pursuit of enhancing product innovation to achieve superior financial performance.
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To produce commercially valuable ketocarotenoids in Solanum tuberosum, the 4, 4′ β-oxygenase (crtW) and 3, 3′ β-hydroxylase (crtZ) genes from Brevundimonas spp. have been expressed in the plant host under constitutive transcriptional control. The CRTW and CRTZ enzymes are capable of modifying endogenous plant carotenoids to form a range of hydroxylated and ketolated derivatives. The host (cv. Désirée) produced significant levels of nonendogenous carotenoid products in all tissues, but at the apparent expense of the economically critical metabolite, starch. Carotenoid levels increased in both wild-type and transgenic tubers following cold storage; however, stability during heat processing varied between compounds. Subcellular fractionation of leaf tissues revealed the presence of ketocarotenoids in thylakoid membranes, but not predominantly in the photosynthetic complexes. A dramatic increase in the carotenoid content of plastoglobuli was determined. These findings were corroborated by microscopic analysis of chloroplasts. In tuber tissues, esterified carotenoids, representing 13% of the total pigment found in wild-type extracts, were sequestered in plastoglobuli. In the transgenic tubers, this proportion increased to 45%, with esterified nonendogenous carotenoids in place of endogenous compounds. Conversely, nonesterified carotenoids in both wild-type and transgenic tuber tissues were associated with amyloplast membranes and starch granules.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.