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The management of a fishery is a complex task generally involving multiple, often conflicting, objectives. These objectives typically include economic, biological and social goals such as improving the income of fishers, reducing the catch of depleted species and maintaining employment.

The use of genetic algorithms (GA) for optimization problems offers an alternative approach to the traditional solution methods. GA follow the concept of solution evolution, by stochastically developing generations of solution populations using a given fitness statistic, for example the achievement function in goal programs. They are particularly applicable to problems which are large, non-linear and possibly discrete in nature, features that traditionally add to the degree of complexity of solution. Owing to the probabilistic development of populations, GA do not distinguish solutions, e.g. local optima from other solutions, and therefore cannot guarantee optimality even though a global optimum may be reached. In this paper, a non-linear goal program of the North Sea demersal fisheries is used to develop a genetic algorithm for optimization. Comparisons between the GA approach and traditional solution methods are made, in order to measure the relative effectiveness. General observations of the use of GA in multi-objective fisheries bioeconomic models, and other similar models, are discussed.

A series of N-phenylalkyl-substituted tropane analogs of boat conformation was synthesized, and these tropanes were evaluated for their ability to inhibit high affinity uptake of dopamine (DA) and serotonin (5-HT) into striatal nerve endings (synaptosomes). Some of these compounds exhibit high affinity for the DA transporter with a 5-HT/DA transporter selectivity ratio of >50.

A novel series of N-(phenylalkyl)cinnamides related to N-(4-phenylbutyl)-3,4-dihydroxy-beta-cyanocinnamide (6, an EGFR-K inhibitor with high antiproliferative activity) was synthesized and tested for antagonism at N-methyl-D-aspartate (NMDA) receptor subtypes. Potency and subunit selectivity were assayed by electrical recordings in Xenopus oocytes expressing three binary combinations of cloned rat NMDA receptor subunits: NR1A expressed in combination with either NR2A, NR2B, or NR2C. The N-(phenylalkyl)cinnamides are selective antagonists of NR1A/2B receptors. Assayed under steady-state conditions, N-(4-phenylbutyl)-4-hydroxycinnamide (16) has an IC(50) value of 77 nM and1000-fold selectivity with respect to NR1A/2A and NR1A/2C receptors. Potency at alpha(1) adrenergic receptors is low for the four cinnamides tested. Inhibition of NR1A/2B receptors does not correlate with EGFR and ErbB2/neu tyrosine kinase inhibitor activity. The N-(phenylalkyl)cinnamide series we describe provides a novel and structurally diverse framework for designing new NR2B-selective NMDA antagonists as potential CNS therapeutics.

A series of 2-substituted 1,2,3,4-tetrahydro-9H-pyrido[3,4-b]indoles was synthesized as potential antagonists for the NR1A/2B subtype of N-methyl-D-aspartate (NMDA) receptors. Assayed by electrical recording under steady-state conditions, 7-hydroxy-2-(4-phenylbutyl)- 1,2,3,4-tetrahydropyrido-[3,4-b]indole (30) was the most potent compound in the series having an IC50 value of 50 nM at the NR1A/2B receptors.

This paper focuses on the design, development and implementation of new Pareto efficiency detection and restoration techniques for integer goal programming. The design of the algorithms and their implementation issues within (an otherwise continuous) goal programming system are detailed. The differences between continuous and integer goal programming regarding Pareto efficiency detection and restoration analysis are described. The integer Pareto efficiency techniques have been applied to a selection of problems from different industrial contexts in order to assess their computational performance. Finally, Pareto restoration and detection techniques are applied to an integer goal programming problem to illustrate the methodology.

AT-1002 a 6-mer synthetic peptide belongs to an emerging novel class of compounds that reversibly increase paracellular transport of molecules across the epithelial barrier. The aim of this project was to elaborate on the structure-activity relationship of this peptide with the specific goal to replace the P2 cysteine amino acid. Herein, we report the discovery of peptides that exhibit reversible permeability enhancement properties with an increased stability profile.

There have been significant advances in the theory of goal programming (GP) in recent years, particularly in the area of intelligent modelling and solution analysis. The intention of this paper is to provide an overview of these developments, to detail and assess the current state-of-the-art in the subject, and to highlight areas which seem promising for future research. Modelling techniques such as detection and restoration of pareto efficiency, normalisation, redundancy checking, and non-standard utility function modelling are overviewed. The connection between GP and other multi-objective-programming techniques as well as a utility interpretation of GP are examined. The rationality of ranking Multi-Criteria Decision Making techniques, and of placing GP in such a ranking, is discussed.

An overview of GPSYS, an intelligent linear and integer goal programming system is presented in this paper. The intelligent goal programming system is one which is designed to allow a non-specialist access to, and clear understanding of, goal programming solution and analysis techniques. GPSYS is equipped with GP speed up techniques and analysis tools such as Pareto detection and restoration, normalisation, automated lexicographic redundancy checking and an interactive facility.

This paper looks at connections between the multi-criteria techniques of goal programming, compromise programming, and the reference point method. The utility function structure of each method is examined and interpretation of the techniques in terms of pareto efficiency and the equilibrated nature of the solution is given. Means of ensuring pareto efficiency whilst maintaining as much as possible the equilibrated character are given for a certain class of model. Methods for ensuring conceptual correctness and computational accuracy by reducing reference point models to equivalent goal programmes are given. The findings are illustrated by means of an example.

The charge-transfer spectra of 1:1 molecular complexes of seven 1-alkyl-1-(2-naphthyl)ethenes (where R = alkyl group: H, Me, Et, n-Pr, i-Pr, t-Bu, Neopent) and 1-vinylnaphthalene with TCNE were determined in ClCH2CH2Cl as solvent at 27.1 °C. Equilibrium constants, K, for these complexes vary with R, as based on two opposing factors, viz. (a) the polar substituent factor σ* and (b) the angle-of-twist θ between the planes of the naphthyl and vinyl groups. For R = Neopent (σ* dominant) K is 50 times as large as for R = t-Bu (θ dominant). Except for R = t-Bu, kinetics of reaction conform with the equation D + TCNE ⇄ (K) D·TCNE ⇄ (k1/k-1) P, where D is the donor alkene, P is the Diels−Alder 1,4-cycloaddition product, and k1 and k-1 are first-order reaction rate constants. Values of k1 vary from 0.71 min-1 (R = H) to 55.5 min-1 (R = Neopent) and the corresponding relative second-order rate constants k2 (or k1K) from 1 to 4000. The rate constant k-1 was measured only for 1b (R = Me, 0.0017 min-1) in the solvent...

A series of bis(phenylalkyl)amines, structural analogues of ifenprodil and nylidrin, were synthesized and tested for antagonism of N-methyl-d-aspartate (NMDA) receptors. Potency and subunit selecti...

The biochemical basis of cancer and the biological rationale for use of hyperthermia in the treatment of malignancies are dlscussed. Multimodality therapy involving combination of hyperthermia (HT), chemotherapy and radiation is being widely used for management of cancer. The increasing use of HT In multimodality cancer therapy emphasizes the need to develop a rapid assay for predicting/assessing clinical response of tumors. The suitability of an in vitro cell death assay for assessment of thermochemosensitlvity of tumor cells is evaluated. It is proposed that this assay may be useful in predicting/assessing tumor response to HT.

Malignant melanoma are chemoresistent tumors with poor prognosis. The aim of this study was to determine whether multimodality therapy of murine melanoma involving a combination of radiation with thermosensitive-liposome-encapsulated melphalan and local hyperthermia would result in enhancement of therapeutic efficacy for a more effective management of melanoma. Melphalan was entrapped in thermosensitive liposomes prepared from natural lipids: egg phosphatidyl choline, cholesterol and ethanol to show phase transition at 42 +/- 0.5 degrees C and used in combination with localized heating of B16F10 murine melanoma transplanted into the legs of C57B1/6 mice for selective drug targeting at the tumors and/or radiation for treatment of melanoma. Murine melanoma transplanted into C57B1/6 mice were subjected to bimodality treatments involving a combination of radiation, hyperthermia or melphalan. Partial tumor regression was observed in mice receiving a combination of hyperthermia and radiation (median tumor volume 427.3 mm3) or a combination of free melphalan and radiation (512.1 mm3) as compared to untreated controls (630.9 mm3). Each group consisted of 18 animals, and the results are expressed as median tumor volume +/- SD. Animals receiving multimodality therapy comprising irradiation followed by injection of thermosensitive liposomal melphalan and hyperthermic treatment of the tumor-bearing leg at 42 +/- 0.5 degrees C for 1 h showed marked tumor regression in comparison with untreated controls or animals treated with a combination of radiation and hyperthermia or radiation and free-drug melphalan. Animals receiving thermoradiochemotherapy also showed prolonged survival; 70% of animals survived for more than 3 months. The study shows greater tumor cell killing, tumor growth delay and prolonged survival produced by a combination of radiation, thermosensitive-liposome-entrapped melphalan and hyperthermia compared with animals receiving single-modality or bimodality treatments. It is concluded that this multimodality approach will be potentially useful for more effective management of melanoma.

This paper discusses means of introducing decision maker input into the goal programming model in order to produce more satisfactory solutions. Both formal interactive methods and informal trial-and-error approaches are discussed. The design criteria for the choice of the initial test solution and the stopping criteria for the final solution are detailed. The area of presentation of results to, and elicitation of preferences from, the decision maker is dealt with. Practical suggestions for means of parameter alteration to produce alternative solutions are given. Finally, the integration of the above issues into an integrated framework is discussed. © 1997 John Wiley & Sons, Ltd.

Attention control is one of the best ways to reduce information resources and processing. Discontinuous modeling has been used in attention control and has proven some advantages of attention control. In this paper we present an attention control architecture based on continuous modeling for mobile robot platforms. By using fuzzy neural network we construct efficient attention control which is capable of decreasing sensors sampling rate and also choosing the most efficient set of sensors. We also build a novel method for gathering information to construct fuzzy neural networks. We experimentally proved that fuzzy neural networks are very convenient ways for attention control. By using this method which changes the sampling rate of robot sensors, consumption of energy reduces slightly. This novel framework is implemented on Festo Robotino® mobile robot platform and the results show the efficiency of this attention control method which can select the best sensors during each task.

International audience; With the rise of global warming issues due to the increase of the greenhouse gas emission and more generally with growing importance granted to sustainable development, process system engineering (PSE) has turned to think more and more environmentally. Indeed, the chemical engineer has now taken into account not only the economic criteria of the process, but also its environmental and social performances. To evaluate such non-economic performances is challenging and arduous. For this purpose, many approaches could be taken into consideration like environmental impact assessment, environmental impact indices, environmental risk assessment, cost-benefit analysis, life cycle assessment (LCA) and Social LCA. Among these approaches, the coupling of PSE and LCA will be investigated here because it is viewed as a good instrument to evaluate the environmental performance of different unitary processes and whole process. The coupling can be of different nature depending on the focus of the study. Either the study is focused on PSE with an associated LCA study (LCA applied to PSE), or LCA study including mass balance and energy balance (PSE applied to LCA). PSE mainly focuses on design, operation, control and optimization of process with the help of computer based methods i.e. Computer Aided Process Engineering (CAPE). In this study we proceed to an environmental analysis of a non-food agro-process (i.e. biodiesel production from Jatropha) applying our CAPE based LCA proposal. To complement the experimental data the highly impactful unitary processes (i.e. transesterification) is selected for further analysis via simulation. A modelling tool on Microsoft Excel is developed to link LCA and process simulation. For results validation we also implement LCA in a dedicated tool (SIMAPRO) and simulation in a CAPE simulator (ProSim Plus). Furthermore this development of simulation based LCA framework can serve as a step forward for determination of sustainability and eco-efficient designing.

This paper examines the concepts of detection and restoration of pareto efficiency to pareto inefficient goal programmes. An overview of the subject is given and pareto efficiency is defined in terms of objectives, priority levels, and the overall model. The concept of pareto unboundedness in introduced. Simplex-based methods for efficient detection of inefficiency and unboundedness are given. Two new methods for restoration, based on preference information given by the decision maker are detailed. The performance of these techniques is analysed on a set of goal programmes.

This paper presents ideas from goal programming (GP) used as an accompaniment to linear programming (LP) for the analysis of LP infeasibility. A new algorithm (GPIIS) for the detection of irreducibly inconsistent systems (IIS) of constraints is presented using this approach. The structure necessary for implementing such a procedure into a commercial LP solver is outlined. Results for a selection of infeasible LP problems are given, and conclusions drawn.

A primary cellular site involved in heat shock response of eukaryotic cells is located in plasma membranes. The mechanism by which heat shock is sensed and the signals that trigger heat shock response remain an enigma. We aim to determine the role of guanine-nucleotide binding proteins (G)-proteins in mediating heat shock response in eukaryotic cells. The effect of heat shock on high affinity GTPase activity in presence or absence of modulators of G-proteins, such as pertussis toxin was studied by measuring GTPase catalyzed release of 32[Pi] from γ-32[P]GTP. The effect of pertussis toxin on induction of heat shock proteins in cells subjected to thermal stress was studied by SDS-PAGE analysis of 35[S]-methionine labelled cellular proteins. Exposure of cultured human malignant cells to thermal stress (43°C) resulted in a significant increase in activity of high affinity GTPase in the membranes (P < 0.001). This response to heat shock was inhibited by prior exposure of the cells to nanogram concentrations of pertussis toxin, suggesting the involvement of G-proteins in mediating heat shock response. To characterize this G-protein dependence further, we assayed thermal stress stimulated high affinity GTPase activity in cells pretreated with antisera (AS/7) raised against a synthetic peptide corresponding to the last 10 amino acids of α-subunit of inhibitory G-protein (Gi). A partial reduction in heat shock induced stimulation of GTPase activity was observed in the presence of this antisera. The pertussis toxin treated cells did not show induction of heat shock proteins in response to thermal stress. The inhibition of heat shock induced stimulation of high affinity GTPase by pretreatment of cells with pertussis toxin or antiserum against Gi and inhibition of induction of heat shock proteins in toxin treated heat shocked cells suggests that G-protein(s) play a role in mediating the heat shock response.

The standard goal programming model only allows linear continuous preference functions to be modelled. In this paper methods for formulating other possible preference structures, such as discontinuities and varying penalty levels dependent on the distance from the goals are proposed. Techniques for ensuring minimal model growth and ease of solution are discussed. An example to illustrate these methods is given.

This note presents some suggestions for technical improvement of the method given by Martel and Aouni for decision maker preference modelling within goal programming.

This paper presents a review of the current literature on the branch of multi-criteria decision modelling known as Goal Programming (GP). The result of our indepth investigations of the two main GP methods, lexicographic and weighted GP together with their distinct application areas is reported. Some guidelines to the scope of GP as an application tool are given and methods of determining which problem areas are best suited to the different GP approaches are proposed. The correlation between the method of assigning weights and priorities and the standard of the results is also ascertained.

Adjuvant hyperthermia enhances the response of melanoma to irradiation or antineoplastic drugs. Radiation in combination with a targeted drug delivery system combining a thermosensitive liposome-encapsulated antitumor drug with hyperthermia may thus result in enhancement of therapeutic efficacy for more effective management of melanoma. The present study was based on this rationale. The therapeutic effect of radiation alone, or in combination with thermosensitive liposome-encapsulated melphalan and hyperthermia, was determined on B16F10 murine melanoma transplanted into C57B1/6 mice. This multimodality regimen resulted in marked enhancement of the antitumor efficacy in treated animals, as determined by significant tumor growth regression (p

Structure-activity relationship (SAR) studies are essential in the generation of peptides with enhanced activity and efficacy as therapeutic agents. In this study, we report a Structure-activity relationship study for a family of mimetic peptides derived from type IV collagen with potent anti-angiogenic properties. The Structure-activity relationship study was conducted using a number of validated in vitro assays including cell proliferation, adhesion, migration, and tubule formation. We report a critical sequence (NINNV) within this peptide series, which is required for the potent anti-angiogenic activity. Detailed amino acid substitutions resulted in peptides with superior efficacy. Specifically, substitutions with isoleucine at positions 12 and 18 along with the substitution of the methionine at position 10 with the non-natural amino acid D-alanine led to an increase in potency by two orders of magnitude over the parent peptide. Several mimetic peptides in this series exhibit a significant improvement of activity over the parent peptide. This improved in vitro activity is expected to correlate with an increase in in vivo activity leading to effective peptides for anti-angiogenic therapy for different disease applications including cancer and age-related macular degeneration.

The study of self-efficacy and its impact on human performance has intrigued a lot of scholars during the last two decades (e.g. Clayson, D. & Sheffet, M. 2006; Nauta, M. 2001; Muijs R Bandura, 1997; Podell & Soodak, 1993). The objective of this research was to investigate the influence of teacher self-efficacy (TSE) on the students’ motivation and achievement. To this end, eighty senior high school teachers in four different cities in Iran, and one hundred and fifty senior high school students, based on their teachers’ level of self-efficacy, have been selected randomly. For data collection, two instruments were employed: Teacher Self-Efficacy and Students’ Motivation questionnaires. Data were analyzed through Pearson product-moment correlation coefficient and ANOVA. The results of the study revealed that teacher self-efficacy has a positive influence on the students’ motivation and achievement. The results of the study and their pedagogical implications are discussed, and recommendations for further research are provided.

Tight junctions (TJ) control paracellular permeability and apical-basolateral polarity of epithelial cells. Dysregulated permeability is associated with pathological conditions, such as celiac disease and inflammatory bowel disease. TJ formation is dependent on E-cadherin-mediated cell-cell adhesion and actin rearrangement, and is regulated by the Rho family GTPase and aPKC signaling pathways. Larazotide acetate, an 8-mer peptide and TJ modulator, inhibits TJ disassembly and dysfunction caused by endogenous and exogenous stimuli in intestinal epithelial cells. Here, we examined the effect of larazotide acetate on de novo TJ assembly using 2 different model systems. In MDCK cells, larazotide acetate promoted TJ assembly in a calcium switch assay. Larazotide acetate also promoted actin rearrangement, and junctional distribution of zonula occludens-1 (ZO-1), occludin, claudins, and E-cadherin. Larazotide acetate promoted TJ maturation and decreased paracellular permeability in "leaky" Caco-2 cells. Taken together, our data indicate that larazotide acetate enhances TJ assembly and barrier function by promoting actin rearrangement and redistribution of TJ and AJ proteins.

The importance of Life Cycle Assessment (LCA) as an environmental decision support tool continues to increase rapidly in the recent years. Research on the environmental impacts of chemical engineering has gain a lot of popularity but it still needs bundles of improvement and expansion for its implementation in the industrial process evaluation. In this study, Life Cycle Assessment of biofuel production from Jatropha Curcas L . was conducted using an attributional approach. The assessment encompasses the cultivation of the crop, the oil extraction stage and finally, the biofuel production stage. IMPACT 2002+ based on mid-point perspective was applied. This study demonstrates the potential of second generation biofuel production to reduce environmental impact. While LCA method is mainly focus on products and raw data collection, we want to define a new approach based on process system engineering. We suggest ways for an integrated LCA and CAPE approach especially for agro-chemical applications.

A series of N-(2-phenethyl)cinnamides was synthesized and assayed for antagonism at three N-methyl-D-asparate (NMDA) receptor subtypes (NR1A/2A-C). N-(2-(4-hydroxyphenyl)ethyl)-4-chlorocinnamide (6) was identified as a highly potent and selective antagonist of the NR1A/2B subtype.

A series of 2-substituted 1,2,3,4-tetrahydro-9H-pyrido[3,4-b]indoles was synthesized as potential antagonists for the NR1A/2B subtype of N-methyl-D-aspartate (NMDA) receptors. Assayed by electrical recording under steady-state conditions, 7-hydroxy-2-(4-phenylbutyl)- 1,2,3,4-tetrahydropyrido-[3,4-b]indole (30) was the most potent compound in the series having an IC50 value of 50 nM at the NR1A/2B receptors.

The synthesis and biological activity of a series of azatricyclodecane analogues of cocaine are described. All compounds studied in this series exhibit nanomolar potency and good selectivity for the serotonin transporter versus the dopamine transporter.

This volume shows the state-of-the-art in both theoretical development and application of multiple objective and goal programming. Applications from the fields of supply chain management, financial portfolio selection, financial risk management, insurance, medical imaging, sustainability, nurse scheduling, project management, water resource management, and the interface with data envelopment analysis give a good reflection of current usage. A pleasing variety of techniques are used including models with fuzzy, group-decision, stochastic, interactive, and binary aspects. Additionally, two papers from the upcoming area of multi-objective evolutionary algorithms are included. The book is based on the papers of the 8th International Conference on Multi-Objective and Goal Programming (MOPGP08) which was held in Portsmouth, UK, in September 2008.

This chapter introduces the major goal programming variants. The purpose and underlying philosophy of each variant are given. The three major variants in terms of underlying distance metric (and hence philosophy) used are introduced first. These are lexicographic, weighted, and Chebyshev goal programming. Then the variants in terms of the mathematical nature of the decision variables and/or goals used are introduced. These are fuzzy, integer, binary, and fractional goal programming.

Goal Programming (GP) is the most widely used approach in the field of multiple criteria decision making that enables the decision maker to incorporate numerous variations of constraints and goals, particularly in the field of Portfolio Selection (PS). This paper gives a brief review of the application of GP and its variants to Portfolio Selection and analysis problems. The paper firstly discusses the Multi-Criteria Decision Analysis in PS context in which GP is introduced as an important approach to PS Problems. An overview of performance measurement in portfolio selection context is also provided. Amongst the concluding remarks many issues in PS that may be addressed by GP such as multi-period, different measures of risk, and extended factors influencing portfolio selection are listed.

The purpose of this chapter is to explain how to ‘effectively’ solve and analyse goal programming models. The majority of the chapter will consider the solution and analysis of the three major goal programming variants using computerised software. The theory and methods of goal programming solution will also be detailed.

This chapter is concerned with the place of goal programming within the wider fields of multi-criteria decision making, operational research, and artificial intelligence. Modern operational research methodology no longer regards its constituent techniques as stand-alone modelling and solution tools but looks to combine them. Hence there is a growing body of research in fields such as systems and hyper-heuristics (Ozcan et al., 2008), which seek to intelligently select and mix techniques for symbiotic advantage.

This paper develops a fuzzy goal programming model to plan and allocate nurses to hospital wards. It is applied to a hospital ward in Kerman, Iran. The monthly schedule developed by the proposed model takes into account both hospital objectives and nurses’ preferences. First, the nurses’ preferences are obtained via a questionnaire. Then, the objectives and the nurses’ preferences are divided into two major parts in the proposed model: hard constraints and fuzzy goals. The resulting schedule, by solving the proposed model, is implemented and is much preferred to the current schedule. Moreover, the proposed model is easily applicable, takes a short time to solve, and can be extended to include other objectives or preferences.

The topic of how to formulate effective goal programmes using the major variants is covered in Chapter 3. This chapter expands on those concepts by introducing techniques developed to expand the flexibility of goal programming and enhance its use.

The above quote demonstrates that goal-based behaviour and decision making has a long history. This goal-based philosophy has been formalised in the modern field of operational research and management science by the technique of goal programming. The earliest goal programming formulation was introduced by Charnes et al.

As discussed in Chapter 1, the main philosophy underlying goal programming is the Simonian theory of satisficing (Simon, 1957). This philosophy is implemented by the selection of a set of target levels by the decision maker to be achieved as closely as possible. However, goal programming, arising from the field of optimisation, also encompasses elements from the optimising philosophy. The solution to a goal programming is, mathematically speaking, either a single optimisation or a series of linked optimisations. The similarities and differences between the economic theories of optimising and satisficing are well documented (Byron, 2004).

This chapter concerns methods and concepts that need to be considered in order to formulate effective goal programming models. There are many issues unique to goal programming that even those who are experienced in building other types of operational research and/or mathematical programming models need to be aware of. This chapter will address the modelling issues sequentially and show how to employ good goal programming practice and avoid common pitfalls.

A convenient synthesis of nonsymmetrical bivalent inhibitors of the serotonin transporter is described. The synthesis utilizes polymer-supported reagents that allow for rapid access to novel bivalent ligands without the need for isolation or purification of synthetic intermediates.