Synthesis of Alkyl Sulfur-Functionalized Oleic Acid-Based Polymethacrylates and Their Application as Viscosity Index Improvers in a Mineral Paraffinic Lube Oil

This work describes the synthesis of alkyl sulfur-functionalized polymethacrylate-based Viscosity Index Improvers (VII) derived from oleic acid (OLA) for mineral paraffinic lubricating oils. In this strategy, OLA was first quantitatively ramified by alkyl thiols containing long aliphatic chains through thiol-ene coupling as demonstrated by ¹H NMR spectroscopy with the complete consumption of OLA internal double bonds. The resulting alkyl sulfur-functionalized OLA-based derivatives were methacrylated through Steglich esterification in order to afford highly suitable hydrophobic OLA-based monomers which, as far as we know, have not been described yet in the current literature. High polymethacrylate molecular weights were reached through radical polymerization despite the long alkyl pendant chains contained in their backbones. Finally, the resulting alkyl sulfur-functionalized OLA-based polymethacrylates have been blended in a mineral paraffinic oil (MPO) of reference at 5 wt% and evaluated as VII. Rheological measurements revealed that polymer thickening powers were significantly improved in oil with temperature and promoted by increasing the pendant alkyl thiol contained in polymer backbones. Moreover, the viscosity index of MPO was significantly improved with the addition of both synthesized homopolymers which confirmed their efficiency as VII. In the meantime, these results have been compared with a previously reported polymer, the poly(2-[methacryloyloxy]ethyl oleate) (PMAEO), which demonstrated a lower VII efficiency compared with its analogous polymethacrylates containing an additional alkyl chain in their pendant chains.     

Robust robot control with bounded input torques

A new scheme is presented to achieve effective on-line tracking control of robot manipulators in the presence of model uncertainty and torque limitations. Pointwise optimization techniques are incorporated into a “slow” feedback loop in order to generate feasible desired trajectories, optimally close to the original desired trajectories. A suction controller is used in the “fast” main feedback loop, allowing to combine robust tracking with simple controller design. Simulations show very significant performance improvement over standard techniques. The algorithm is computationally cheap and can easily be implemented on-line.     

On-line compositional controller synthesis for AGV

This paper deals with the on-line design of a supervisor to coordinate an automated guided vehicle (AGV) fleet. This supervisor ensures the system safety (no collision) and a good coordination between vehicles (no blocking situations). It is the so-called Wonham-Ramadge supervisor, it is the least restrictive, and ensures controllability and nonblocking. We propose a compositional procedure to resolve this problem allowing an efficient on-line synthesis. A calculation on the fly is made at every attribution of a new mission for an AGV, to actualize the supervisor and adapt it to the new situation. This compositional approach allows to increase the number of AGV taken on compared to the monolithic approach. We show on some tests the efficiency of this method for the on-line synthesis of supervisor to coordinate a fleet of mobile robots for real cases.     

Synthesis of (polyethylene terephthalate/poly?-caprolactone) copolyesters

Polyethylene terephthalate (PET) was alcoholised with ethylene glycol to synthesize hydroxytelechelic oligomers of PET. On the other hand, commercial hydroxytelechelic poly?-caprolactone was modified in order to synthesize carboxytelechelic poly?-caprolactone. The chemical structure of the products was investigated by ¹H NMR. Multiblock copolyesters were then synthesized by polyesterification of hydroxytelechelic PET and carboxytelechelic poly?-caprolactone oligomers, using several catalysts and different reaction conditions, which have been linked with the average molecular weight of the obtained block copolyesters. It appeared that residual distannoxane species coming from glycolysis step are best catalyst for polyesterification reaction. The chemical structure of the synthesized copolyesters was investigated by size exclusion chromatography and ¹H NMR. The thermal and thermomechanical behavior of the synthesized copolyesters was investigated by differential scanning calorimetry and by dynamic mechanical analyses. The ester-ester interchange reaction between the two types of oligopolyesters has been enlightened and estimated taking in account the different reaction parameters. This side reaction led to the miscibility of the two phases of the oligomers, that can be explained by a random structure of the copolyester, and prevented to obtain multiblock copolymer.     

Revealing determinant factors for early breast cancer recurrence by decision tree

Early breast cancer recurrence is indicative of poor response to adjuvant therapy and poses threats to patients’ lives. Most existing prediction models for breast cancer recurrence are regression-based models and difficult to interpret. We apply a Decision Tree algorithm to the clinical information of a cohort of non-metastatic invasive breast cancer patients, to establish a classifier that categorizes patients based on whether they develop early recurrence and on similarities of their clinical and pathological diagnoses. The classifier predicts for whether a patient developed early disease recurrence; and is estimated to be about 70% accurate. For an independent validation cohort of 65 patients, the classifier predicts correctly for 55 patients. The classifier also groups patients based on intrinsic properties of their diseases; and for each subgroup lists the disease characteristics in a hierarchal order, according to their relevance to early relapse. Overall, it identifies pathological nodal stage, percentage of intra-tumor stroma and components of TGFβ-Smad signaling pathway as highly relevant factors for early breast cancer recurrence. Since most of the disease characteristics used by this classifier are results of standardized tests, routinely collected during breast cancer diagnosis, the classifier can easily be adopted in various research and clinical settings.     

METHODS FOR PROCESSING EXPERIMENTAL DRYING KINETICS DATA

This paper provides a review of methods for processing the data obtained from drying kinetics rigs and pilot-plant trials. Different methods for fitting and smoothing drying curves are compared, aiming to generate curves that are usable in industrial design without losing vital information by oversmoothing. Generally, plots of drying rate need more smoothing than moisture content data. Special care is needed at low drying rates and moisture contents. It is shown that some popular methods of processing data, including use of smoothing programs or fitting to equations, may generate drying curves which are seriously in error. Recommendations are made for reliable methods of processing data; cubic splines have been found to be effective for moisture-time curves. It is important to retain the original raw experimental data as a cross-check, as smoothing can conceal valuable information.     

Imaging E-selectin expression following traumatic brain injury in the rat using a targeted USPIO contrast agent

Introduction  The aim of this work was to map E-selectin expression in a traumatic brain injury model using a newly-designed MR contrast agent. Iron cores, responsible for susceptibility effects and therefore used as T2* contrast agents, need to be coated in order to be stabilized and need to be targeted to be useful. Methods  We have designed a molecule coating composed, at one end, of bisphosphonate to ensure anchorage of the coating on the iron core and, at the other end, of Fukuda’s defined heptapeptide known to target selectin binding sites. Conclusion  The synthesized nanoparticles were able to non-invasively target the traumatic brain lesion, inducing a specific T2* decrease of about 25% up to at least 70 min post-injection of the targeted contrast agent.     

A method for assessing the impact of product development on the company

Because of competitiveness, the problem of product and production system developments is becoming increasingly current. From the point of view of products and production systems, companies must have tools to redesign, analyse, choose and manage their developments. After analysing which tools and methods exist in the scientific literature, we present in this paper a general method for assessing the impact of product development on the company. This method can be applied for each criterion that the company wants to analyse (delay, cost, organization, resources, quality, etc); we choose here the delay criterion. The method features four steps. The first step aims to characterize the case study by representing it with generic parameters. The second step offers the construction of a matrix model (called a static model) in order to categorize the product developments. The third step proposes the construction of a Temporized Coloured Petri Net model (called a dynamic model) and the fourth step simulates this model in order to obtain the expected result: the assessment of impact of the product development. At the end of the paper, we propose a case study on a roller tapered bearing manufacturer-- the Timken company.     

Modeling the short-circuit current density of polymer solar cells based on P3HT:PCBM blend

We have investigated the short-circuit current density of organic solar cells based on poly (3-hexylthiophene)(P3HT)/6,6-phenyl C61-butyric acid methyl ester (PCBM) blend. In order to model charge collection efficiencies with respect to short circuit density in such blends, a full optical modeling of the cell is performed. From the distribution of the electromagnetic field, we compute the rate of exciton generation. This exciton generation rate is used as input in the transport equations of holes and electrons. Charge densities at steady state are obtained as solutions are used for computing short-circuit current densities generated in the cell. The dependence of short-circuit current densities versus the thickness of the blend is analyzed and compared with our experimental data and with data extracted from the literature.