An agent approach to improving radio frequency identification enabled Returnable Transport Equipment

Returnable transport equipment (RTE) such as pallets form an integral part of the supply chain and poor management leads to costly losses. Companies often address this matter by outsourcing the management of RTE to logistics service providers (LSPs). LSPs are faced with the task to provide logistical expertise to reduce RTE related waste, whilst differentiating their own services to remain competitive. In the current challenging economic climate, the role of the LSP to deliver innovative ways to achieve competitive advantage has never been so important. It is reported that radio frequency identification (RFID) application to RTE enables LSPs such as DHL to gain competitive advantage and offer clients improvements such as loss reduction, process efficiency improvement and effective security. However, the increased visibility and functionality of RFID enabled RTE requires further investigation in regards to decision‐making. The distributed nature of the RTE network favours a decentralised decision‐making format. Agents are an effective way to represent objects from the bottom‐up, capturing the behaviour and enabling localised decision‐making. Therefore, an agent based system is proposed to represent the RTE network and utilise the visibility and data gathered from RFID tags. Two types of agents are developed in order to represent the trucks and RTE, which have bespoke rules and algorithms in order to facilitate negotiations. The aim is to create schedules, which integrate RTE pick‐ups as the trucks go back to the depot. The findings assert that: - agent based modelling provides an autonomous tool, which is effective in modelling RFID enabled RTE in a decentralised utilising the real‐time data facility. ‐ the RFID enabled RTE model developed enables autonomous agent interaction, which leads to a feasible schedule integrating both forward and reverse flows for each RTE batch. ‐ the RTE agent scheduling algorithm developed promotes the utilisation of RTE by including an automatic return flow for each batch of RTE, whilst considering the fleet costs andutilisation rates. ‐ the research conducted contributes an agent based platform, which LSPs can use in order to assess the most appropriate strategies to implement for RTE network improvement for each of their clients.

Identification of aspirin analogues that repress NF-κB signalling and demonstrate anti-proliferative activity towards colorectal cancer in vitro and in vivo

Substantial evidence indicates that aspirin and related non-steroidal anti-inflammatory drugs (NSAIDs) have potential as chemopreventative/therapeutic agents. However, these agents cannot be universally recommended for prevention purposes due to their potential side-effect profiles. Here, we compared the growth inhibitory and mechanistic activity of aspirin to two novel analogues, diaspirin (DiA) and fumaryl diaspirin (F-DiA). We found that the aspirin analogues inhibited cell proliferation and induced apoptosis of colorectal cancer cells at significantly lower doses than aspirin. Similar to aspirin, we found that an early response to the analogues was a reduction in levels of cyclin D1 and stimulation of the NF-κB pathway. This stimulation was associated with a significant reduction in basal levels of NF-κB transcriptional activity, in keeping with previous data for aspirin. However, in contrast to aspirin, DiA and F-DiA activity was not associated with nucleolar accumulation of RelA. For all assays, F-DiA had a more rapid and significant effect than DiA, identifying this agent as particularly active against colorectal cancer. Using a syngeneic colorectal tumour model in mice, we found that, while both agents significantly inhibited tumour growth in vivo, this effect was particularly pronounced for F-DiA. These data identify two compounds that are active against colorectal cancer in vitro and in vivo. They also identify a potential mechanism of action of these agents and shed light on the chemical structures that may be important for the antitumour effects of aspirin.

Classical and technological convergence:beyond the Solow-Swann model

Recent investigations into cross-country convergence follow Mankiw, Romer, and Weil (1992) in using a log-linear approximation to the Swan-Solow growth model to specify regressions. These studies tend to assume a common and exogenous technology. In contrast, the technology catch-up literature endogenises the growth of technology. The use of capital stock data renders the approximations and over-identification of the Mankiw model unnecessary and enables us, using dynamic panel estimation, to estimate the separate contributions of diminishing returns and technology transfer to the rate of conditional convergence. We find that both effects are important.

Enhancing competitive advantage with radio-frequency identification (RFID) enabled returnable transport equipment (RTE)

Fierce competition within the third party logistics (3PL) market has developed as providers compete to win customers and enhance their competitive advantage through cost reduction plans and creating service differentiation. 3PL providers are expected to develop advanced technological and logistical service applications that can support cost reduction while increasing service innovation. To enhance competitiveness, this paper proposes the implementation of radio-frequency identification (RFID) enabled returnable transport equipment (RTE) in combination with the consolidation of network assets and cross-docking. RFID enabled RTE can significantly improve network visibility of all assets with continuous real-time data updates. A four-level cyclic model aiding 3PL providers to achieve competitive advantage has been developed. The focus is to reduce assets, increase asset utilisation, reduce RTE cycle time and introduce real-time data in the 3PL network. Furthermore, this paper highlights the need for further research from the 3PL perspective. Copyright © 2013 Inderscience Enterprises Ltd.

Parametric Identification and Diagnosis of Integrated Navigation Systems in Bench Test Process

Growth of complexity and functional importance of integrated navigation systems (INS) leads to high losses at the equipment refusals. The paper is devoted to the INS diagnosis system development, allowing identifying the cause of malfunction. The proposed solutions permit taking into account any changes in sensors dynamic and accuracy characteristics by means of the appropriate error models coefficients. Under actual conditions of INS operation, the determination of current values of the sensor models and estimation filter parameters rely on identification procedures. The results of full-scale experiments are given, which corroborate the expediency of INS error models parametric identification in bench test process.

Towards the in silico identification of class II restricted T-cell epitopes:a partial least squares iterative self-consistent algorithm for affinity prediction

Motivation: The immunogenicity of peptides depends on their ability to bind to MHC molecules. MHC binding affinity prediction methods can save significant amounts of experimental work. The class II MHC binding site is open at both ends, making epitope prediction difficult because of the multiple binding ability of long peptides. Results: An iterative self-consistent partial least squares (PLS)-based additive method was applied to a set of 66 pep- tides no longer than 16 amino acids, binding to DRB1*0401. A regression equation containing the quantitative contributions of the amino acids at each of the nine positions was generated. Its predictability was tested using two external test sets which gave r pred =0.593 and r pred=0.655, respectively. Furthermore, it was benchmarked using 25 known T-cell epitopes restricted by DRB1*0401 and we compared our results with four other online predictive methods. The additive method showed the best result finding 24 of the 25 T-cell epitopes. Availability: Peptides used in the study are available from http://www.jenner.ac.uk/JenPep. The PLS method is available commercially in the SYBYL molecular modelling software package. The final model for affinity prediction of peptides binding to DRB1*0401 molecule is available at http://www.jenner.ac.uk/MHCPred. Models developed for DRB1*0101 and DRB1*0701 also are available in MHC- Pred

A predictive in vitro model of the impact of drugs with anticholinergic properties on human neuronal and astrocytic systems

The link between off-target anticholinergic effects of medications and acute cognitive impairment in older adults requires urgent investigation. We aimed to determine whether a relevant in vitro model may aid the identification of anticholinergic responses to drugs and the prediction of anticholinergic risk during polypharmacy. In this preliminary study we employed a co-culture of human-derived neurons and astrocytes (NT2.N/A) derived from the NT2 cell line. NT2.N/A cells possess much of the functionality of mature neurons and astrocytes, key cholinergic phenotypic markers and muscarinic acetylcholine receptors (mAChRs). The cholinergic response of NT2 astrocytes to the mAChR agonist oxotremorine was examined using the fluorescent dye fluo-4 to quantitate increases in intracellular calcium [Ca2+]i. Inhibition of this response by drugs classified as severe (dicycloverine, amitriptyline), moderate (cyclobenzaprine) and possible (cimetidine) on the Anticholinergic Cognitive Burden (ACB) scale, was examined after exposure to individual and pairs of compounds. Individually, dicycloverine had the most significant effect regarding inhibition of the astrocytic cholinergic response to oxotremorine, followed by amitriptyline then cyclobenzaprine and cimetidine, in agreement with the ACB scale. In combination, dicycloverine with cyclobenzaprine had the most significant effect, followed by dicycloverine with amitriptyline. The order of potency of the drugs in combination frequently disagreed with predicted ACB scores derived from summation of the individual drug scores, suggesting current scales may underestimate the effect of polypharmacy. Overall, this NT2.N/A model may be appropriate for further investigation of adverse anticholinergic effects of multiple medications, in order to inform clinical choices of suitable drug use in the elderly.

The antecedents and consequences of anticipatory identification

The aim of this thesis was to investigate anticipatory identification: newcomers’ identification with an organisation prior to entry; in particular by exploring the antecedents and consequences of the construct. Although organisational identification has been frequently investigated over the past 25 years, surprisingly little is known about what causes an individual to identify with a new organisation before entry and whether this has an impact on their relationship with the organisation after formally taking up membership. Drawing on a Social Identity approach to organisational identification, it was hypothesised that newcomers would more closely identify with an organisation prior to entry when the organisation was seen as a source of positive social identity and was situationally relevant and meaningful to the newcomer, i.e. salient, during the pre-entry period. It was also hypothesised that anticipatory identification would have post-entry consequences and would predict newcomers’ post-entry identification, turnover intentions and job satisfaction. An indirect relationship between anticipatory identification and post-entry identification through post-entry social identity judgements (termed a “feedback loop” mechanism) was additionally proposed. Finally anticipatory identification was also predicted to moderate the relationship between post-entry social identity judgements and post-entry identification (termed a “buffering” mechanism). Four studies were conducted to test these hypotheses. Study One served as a pilot study, using a retrospective self-report design with s sample of 124 university students to initially test the proposed conceptual model. Studies Two and Three adopted experimental designs. Each used a unique sample of 72 staff and students from Aston University to respectively test the hypothesised positive social identity motive and salience antecedents of anticipatory identification. Study Four explored the relationship between anticipatory identification, its antecedents and consequences longitudinally, using an organisational sample of 45 employees. Overall, these studies found support for a social identity motive antecedent of anticipatory identification, as well as more limited evidence that anticipatory identification was associated with the salience of an organisation prior to entry. Support was inconsistent for a direct relationship between anticipatory identification and post-entry identification and there was no evidence that anticipatory identification was a significant direct predictor of turnover intention and job satisfaction. Anticipatory identification was however found to act as a buffer in the relationship between post-entry social identity judgements and post-entry identification in all but one of the four samples measured. A feedback loop mechanism was observed within the experimental designs of Studies Two and Three, but not within the organisational samples of Studies One and Four. Overall the findings of these four studies highlight key ways through which anticipatory identification can develop prior to entry into an organisation. Moreover, the research observed several important post-entry consequences of anticipatory identification, indicating that an understanding of post-entry identification may be enriched by attending more closely to the extent to which newcomers identify with an organisation prior to entry.

Operating Model of Knowledge Quantum Engineering for Decision-Making in Conditions of Indeterminacy

The operating model of knowledge quantum engineering for identification and prognostic decision- making in conditions of α-indeterminacy is suggested in the article. The synthesized operating model solves three basic tasks: Аt-task to formalize tk-knowledge; Вt-task to recognize (identify) objects according to observed results; Сt-task to extrapolate (prognosticate) the observed results. Operating derivation of identification and prognostic decisions using authentic different-level algorithmic knowledge quantum (using tRAKZ-method) assumes synthesis of authentic knowledge quantum database (BtkZ) using induction operator as a system of implicative laws, and then using deduction operator according to the observed tk-knowledge and BtkZ a derivation of identification or prognostic decisions in a form of new tk-knowledge.

Exploration by Means of Computer Simulation of Nonlinear Hierarchical Structure of Neuronal Memory on the Model of Olfactory Bulb

Results of numerical experiments are introduced. Experiments were carried out by means of computer simulation on olfactory bulb for the purpose of checking of thinking mechanisms conceptual model, introduced in [2]. Key role of quasisymbol neurons in processes of pattern identification, existence of mental view, functions of cyclic connections between symbol and quasisymbol neurons as short-term memory, important role of synaptic plasticity in learning processes are confirmed numerically. Correctness of fundamental ideas put in base of conceptual model is confirmed on olfactory bulb at quantitative level.

EnDNA-Prot:identification of DNA-binding proteins by applying ensemble learning

DNA-binding proteins are crucial for various cellular processes, such as recognition of specific nucleotide, regulation of transcription, and regulation of gene expression. Developing an effective model for identifying DNA-binding proteins is an urgent research problem. Up to now, many methods have been proposed, but most of them focus on only one classifier and cannot make full use of the large number of negative samples to improve predicting performance. This study proposed a predictor called enDNA-Prot for DNA-binding protein identification by employing the ensemble learning technique. Experiential results showed that enDNA-Prot was comparable with DNA-Prot and outperformed DNAbinder and iDNA-Prot with performance improvement in the range of 3.97-9.52% in ACC and 0.08-0.19 in MCC. Furthermore, when the benchmark dataset was expanded with negative samples, the performance of enDNA-Prot outperformed the three existing methods by 2.83-16.63% in terms of ACC and 0.02-0.16 in terms of MCC. It indicated that enDNA-Prot is an effective method for DNA-binding protein identification and expanding training dataset with negative samples can improve its performance. For the convenience of the vast majority of experimental scientists, we developed a user-friendly web-server for enDNA-Prot which is freely accessible to the public. © 2014 Ruifeng Xu et al.

TQM in e-Learning: a Self-assessment Model and Questionnaire

Organizations are seeking new, integrated systems that enable rapid changes through early identification of opportunities and problems, tracking of progress against plans, flexible allocation of resources to achieve goals, and consistent operations. Total Quality Management (TQM) is an overall business strategy. It means that all activities of the company will be focused on satisfying all stakeholders of the company. TQM can be realised by using the EFQM model. The EFQM model is a tool that organizations may use as a framework for self-evaluation that enables an organization to identify its strengths and areas for improvement and the extent to which its operations and results are in line with the characteristics of an excellent organization. We focus on a training organisation or to the learning department of an organization. So we are limiting the EFQM model to the training /learning activities. We can apply EFQM perfect on the level of an activity (business line) of a company. We selected the main criteria for which the learner can play the role of assessor. So only three main criteria left: the enabling resources, the enabling processes and the (learning) results for the learner. We limited the last one to “learning results” based on the Kirkpatrick model.

Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.

Classification of Texts' Authorship Using a Regression Model on Compressed Data

2010 Mathematics Subject Classification: 68T50,62H30,62J05.

Maximising the efficiency of logistics operations with radio frequency identification technology

Radio frequency identification (RFID) technology has gained increasing popularity in businesses to improve operational efficiency and maximise costs saving. However, there is a gap in the literature exploring the enhanced use of RFID to substantially add values to the supply chain operations, especially beyond what the RFID vendors could offer. This paper presents a multi-agent system, incorporating RFID technology, aimed at fulfilling the gap. The system is developed to model supply chain activities (in particular, logistics operations) and is comprised of autonomous and intelligent agents representing the key entities in the supply chain. With the advanced characteristics of RFID incorporated, the agent system examines ways logistics operations (i.e. distribution network) particular) can be efficiently reconfigured and optimised in response to dynamic changes in the market, production and at any stage in the supply chain. © 2012 IEEE.