Interval and fuzzy optimization. Applications to data envelopment analysis

Enhancing concern in the efficiency assessment of a set of peer entities termed Decision Making Units (DMUs) in many fields from industry to healthcare has led to the development of efficiency assessment models and tools. Data Envelopment Analysis (DEA) is one of the most important methodologies to measure efficiency assessment through the comparison of a group of DMUs. It permits the use of multiple inputs/outputs without any functional form. It is vastly applied to production theory in Economics and benchmarking in Operations Research. In conventional DEA models, the observed inputs and outputs possess precise and realvalued data. However, in the real world, some problems consider imprecise and integer data. For example, the number of defect-free lamps, the fleet size, the number of hospital beds or the number of staff can be represented in some cases as imprecise and integer data. This thesis considers several novel approaches for measuring the efficiency assessment of DMUs where the inputs and outputs are interval and fuzzy data. First, an axiomatic derivation of the fuzzy production possibility set is presented and a fuzzy enhanced Russell graph measure is formulated using a fuzzy arithmetic approach. The proposed approach uses polygonal fuzzy sets and LU-fuzzy partial orders and provides crisp efficiency measures (and associated efficiency ranking) as well as fuzzy efficient targets. The second approach is a new integer interval DEA, with the extension of the corresponding arithmetic and LU-partial orders to integer intervals. Also, a new fuzzy integer DEA approach for efficiency assessment is presented. The proposed approach considers a hybrid scenario involving trapezoidal fuzzy integer numbers and trapezoidal fuzzy numbers. Fuzzy integer arithmetic and partial orders are introduced. Then, using appropriate axioms, a fuzzy integer DEA technology can be derived. Finally, an inverse DEA based on the non-radial slacks-based model in the presence of uncertainty, employing both integer and continuous interval data is presented

The Effects of Storage on Germination Characteristics and Enzyme Activity of Sorghum Seeds

Seed moisture content (MC) and storage temperature are the most important factors affecting seed longevity and vigor. Exposure to warm, moist air is principally responsible for this. Proper storage and optimum seed moisture content can affect the grain quality significantly. The purpose of this study was to evaluate the different storage treatments on seed quality of sorghum. The seed materials were fresh without any storage period. For storage treatments, 3 seed moisture contents (6, 10, 14 %) were stored for 8 month in 0.5 L capacity sealed aluminum foil packet in 0.3 bar inside incubators set at 4 temperatures (5, 15, 25, 35 °C). After storage time, the higher the storage temperature, the lower was the grain quality of sorghum. The highest germination percentage, germination index, normal seedling percentage were achieved in control conditions (0 day of storage). Our results showed that increasing storage duration resulted higher reduction in germination characteristics. Also our results showed that, germination percentage, means time to germination, germination index, normal seedling percentage decrease significantly by storage. Enzyme activity decrease significantly by increased in storage

Preparation of silica powder from rice husk

Silicon dioxide (SiO2) is the most abundant mineral in the world.  Plants are the source of this mineral.  In recent decades, with the advent of nanotechnology, silica nanoparticles have been found new applications in chemical industry, textile, packaging, biotechnology, agriculture and medicine.  Rice husk and straw are rich sources of minerals.  Rice husk (RH) has more than 20% silica.  Using thermal process in presence of different gasses, the sample of ash of husk and bran of rice produced.  To investigate the effect of heat treatment in different conditions, the properties of the samples were determined. Rice husk ash solution was poured on soda solution.  Then silica was separated and sodium silicate was formed.  By separation and titration of the solution, silica was obtained.  The obtained silica washed by hydrochloric acid and purified.  By repeating process on soda solution and titration under controlled conditions and by adding the surfactants silica nanoparticles were obtained.  In this study, amorphous silica nanoparticles with an average size of 60 nm were produced by chemical reduction method.  Fourier transform infrared (FT-IR) was used for Infrared spectroscopy analysis and X-ray diffraction was used for identification phase.  For elemental analysis, the inductively coupled plasma emission spectrometer (ICP/ES) and energy dispersive X-ray analysis (EDAX) were used

A Knowledge-based Integrative Modeling Approach for <em>In-Silico</em> Identification of Mechanistic Targets in Neurodegeneration with Focus on Alzheimer’s Disease

Dementia is the progressive decline in cognitive function due to damage or disease in the body beyond what might be expected from normal aging. Based on neuropathological and clinical criteria, dementia includes a spectrum of diseases, namely Alzheimer's dementia, Parkinson's dementia, Lewy Body disease, Alzheimer's dementia with Parkinson's, Pick's disease, Semantic dementia, and large and small vessel disease. It is thought that these disorders result from a combination of genetic and environmental risk factors. Despite accumulating knowledge that has been gained about pathophysiological and clinical characteristics of the disease, no coherent and integrative picture of molecular mechanisms underlying neurodegeneration in Alzheimer’s disease is available. Existing drugs only offer symptomatic relief to the patients and lack any efficient disease-modifying effects. The present research proposes a knowledge-based rationale towards integrative modeling of disease mechanism for identifying potential candidate targets and biomarkers in Alzheimer’s disease. Integrative disease modeling is an emerging knowledge-based paradigm in translational research that exploits the power of computational methods to collect, store, integrate, model and interpret accumulated disease information across different biological scales from molecules to phenotypes. It prepares the ground for transitioning from ‘descriptive’ to “mechanistic” representation of disease processes. The proposed approach was used to introduce an integrative framework, which integrates, on one hand, extracted knowledge from the literature using semantically supported text-mining technologies and, on the other hand, primary experimental data such as gene/protein expression or imaging readouts. The aim of such a hybrid integrative modeling approach was not only to provide a consolidated systems view on the disease mechanism as a whole but also to increase specificity and sensitivity of the mechanistic model by providing disease-specific context. This approach was successfully used for correlating clinical manifestations of the disease to their corresponding molecular events and led to the identification and modeling of three important mechanistic components underlying Alzheimer’s dementia, namely the CNS, the immune system and the endocrine components. These models were validated using a novel in-silico validation method, namely biomarker-guided pathway analysis and a pathway-based target identification approach was introduced, which resulted in the identification of the MAPK signaling pathway as a potential candidate target at the crossroad of the triad components underlying disease mechanism in Alzheimer’s dementia

Le foncier urbain entre opportunité et maîtrise. Cas de Sétif (Algérie).

International audienceL'action foncière est l'un des facteurs clés de la production urbaine. Les grandes orientations des actes d'aménagement et d'urbanisation futurs dépendront de la façon de gérer et de maîtriser l'assiette foncière. Dans ce domaine l'Algérie accuse un certain déficit et le cadastre, malgré son importance capitale dans la maîtrise foncière, n'a jamais été une priorité. L'analyse de la ville de Sétif en est une illustration

Preparation and Characterization of Nanozeolite NaA from Rice Husk at Room Temperature without Organic Additives

Nanozeolite NaA was synthesized by the hydrothermal method with silica extracted from rice husk as silica source. Amorphous silica with 87.988 wt%  SiO2 was extracted from rice husk ash by a suitable alkali solution. The effect of the crystallization time and the ratio of Na2O/SiO2 on the properties of the final product was investigated. The synthesized nanozeolite was characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray (EDX) techniques, and Brunauer-Emmett-Teller (BET) method. Results revealed that the crystallization time and alkalinity have significant effects on the structural properties of nanozeolite. Nanocrystals NaA with crystal sizes ranging from 50 to 120 nm were synthesized at room temperature with 3 days aging, without adding any organic additives

Investigating structures and optical properties of monolayer films prepared from a photo-polymerizable surfactant in 2D

The overall objective of this PhD thesis research is to characterize, understand and ultimately control phase-separated structures in mixed films consisting of a perfluorinated fatty acid and a photopolymerizable surfactant. In these systems, film morphology, mechanical properties and spectroscopic properties are inter-related and this thesis explores these relationships. In this context the interaction between perfluorotetradecanoic acid (C13F27COOH, referred to as PF in this dissertation), and 10,12-pentacosadynoic acid (CH3(CH2)11−C≡C−C≡C−(CH2)8COOH, referred to as PCDA in this dissertation) has been studied in monolayers using a combination of surface and spectroscopic characterization techniques. To investigate the inter-relationship of the properties described above, film behavior under a variety of conditions, including behavior at different interfaces (solid-liquid, air-liquid), different film compositions and under different conditions of photoillumination and mechanical stress were explored. Thermodynamic and morphological studies of mixed monolayer surfactant films of PF and the photo-polymerizable diacetylene molecule, PCDA, were carried out. The films were prepared at the air-water interface and transferred onto solid supports such as a glass slides via Langmuir-Blodgett (LB) deposition technique. The presence of the perfluoroacid helped to stabilize the diacetylene surfactant monolayer in comparison with the diacetylene alone, allowing film transfer onto solid substrates without needing to add cations to the sub-phase or photo-polymerize the components prior to deposition. Addition of the perfluorocarbon to PCDA resulted in films with the photopolymer strands oriented perpendicular to the direction of the film compression in a Langmuir trough. This is in contrast with film structures formed from pure PCDA. Formation of these features could be explained by a two-step process that happened sequentially: first, the compression of monolayer with trough barriers while trying to maintain the surface pressure constant induces stress on the film surface; second, additional film buckling which was enhanced by the strong cohesion between PF and PCDA. Film compression data, supported by in situ fluorescence spectrophotometry, Brewster angle microscope imaging and atomic force microscope images of deposited films, supported this mechanism. Factors that controlled the orientation of the photopolymer fibers were also investigated. Fibers were found to consist of multiple strands, with each strand having a different orientation. Our investigation also revealed there was a preferred orientation for fibers in the film as a whole. The angle of approximately 60o to the direction of film compression during deposition from a Langmuir trough has been calculated with the help of dual-view, polarized fluorescence microscopy. This orientation was attributed to the mechanical stress exerted by the trough compression barriers coupled with rotation of the polymer fibers during film draining. The combination of Atomic Force Microscope (AFM) and fluorescence microscopy (FM) provided a thorough and comprehensive mapping of fundamental properties of mixed monolayer system, and enabled a quantitative determination of the degree of selectivity of the polymerization process

Production of single cell protein from stickwater of kilka fish meal factory using Lactobacillus acidophilus and Aspergillus niger

We investigated production of single cell protein (SCP) from stickwater of kilka fish meal factory as medium using Lactobacillus acidophilus and Aspergillus niger. Stickwater was used instead of the standard media of bacterium and fungus in a batch culture method. Amount of biomass, COD, RNA and protein in the bacterium and fungus in control and stickwater treatments were investigated. In maximum growth time, amino acids profile of the bacterium and fungus were measured and compared between treatments. Bacterial biomass production in the control and stickwater treatments were 3.16 and 5.12g/l, COD reduction was 33270 and 53330mg/l, the measured RNA were 15.27% and 15.04%, the amount of protein were 71.13% and 68.37%, respectively. The difference between bacterium and fungus biomass production was slight. We found that the amount of the fungus biomass in control and stickwater were 6.31 and 7.28g/l, COD reduction were 47800 and 55200mg/l, RNA was 9.36% and 9.09%, the amount of protein were 51.36% and 48.66%, respectively. In both bacterium and fungus, the maximum and minimum amount of amino acid of the control and stickwater was glutamic acid and methionin. The amount of methionin in bacterium was not different with fish meal and FAO reference and in fungus was a little lower than FAO reference. According to the results, application of pure stickwater was suitable for productionof Lactobacillus acidophilus and Aspergillus niger