The alpha7beta1 integrin mediates adhesion and migration of skeletal myoblasts on laminin

Many aspects of myogenesis are believed to be regulated by myoblast interactions with specific components of the extracellular matrix. For example, laminin has been found to promote adhesion, migration, and proliferation of mammalian myoblasts. Based on affinity chromatography, the alpha7beta1 integrin has been presumed to be the major receptor mediating myoblast interactions with laminin. We have prepared a monoclonal antibody, O26, that specifically reacts with both the X1 and the X2 extracellular splice variants of the alpha7 integrin chain. This antibody completely and selectively blocks adhesion and migration of rat L8E63 myoblasts on laminin-1, but not on fibronectin. In contrast, a polyclonal antibody to the fibronectin receptor, alpha5beta1 integrin, blocks myoblast adhesion on fibronectin, but not on laminin-1. The alpha7beta1 integrin also binds to a mixture of laminin-2 and laminin-4, the major laminin isoforms in developing and adult skeletal muscle, but O26 is a much less potent inhibitor of myoblast adhesion on the laminin-2/4 mixture than on laminin-1. Based on affinity chromatography, we suggest that this may be due to higher affinity binding of alpha7X1 to laminin-2/4 than to laminin-1.     

Nonlinear creep behavior of viscoelastic polycarbonate

A study of the tension behavior of polycarbonate (PC) under room temperature and various sustained loads is presented. Time-dependent axial elongations and transverse contractions of the specimen were simultaneously measured at nine different stress levels, from 15.89 to 59.4 MPa, and modeled according to a time-stress superposition principle. The test duration was only one hour. It was shown that creep compliance vs. log time curves at different stresses can be horizontally shifted to form a smooth master curve for one year at a reference stress of 30.97 MPa. Moreover, the stress shift factors for axial extension creep curves and transverse contraction creep curves are found to be identical for the stress levels considered, and this is verified using the Poisson's ratio measurements.     

Force control of hybrid actuator using learning vector quantization neural network

Hydraulic actuators are important in modern industry due to high power, fast response, and high stiffness. In recent years, hybrid actuation system, which combines electric and hydraulic technology in a compact unit, can be adapted to a wide variety of force, speed and torque requirements. Moreover, the hybrid actuation system has dealt with the energy consumption and noise problem existed in the conventional hydraulic system. Therefore, hybrid actuator has a wide range of application fields such as plastic injection-molding and metal forming technology, where force or pressure control is the most important technology. In this paper, the solution for force control of hybrid system is presented. However, some limitations still exist such as deterioration of the performance of transient response due to the variable environment stiffness. Therefore, intelligent switching control using Learning Vector Quantization Neural Network (LVQNN) is newly proposed in this paper in order to overcome these limitations. Experiments are carried out to evaluate the effectiveness of the proposed algorithm with large variation of stiffness of external environment. In addition, it is understood that the new system has energy saving effect even though it has almost the same response as that of valve controlled system.     

Minimizing Human-Exoskeleton Interaction Force Using Compensation for Dynamic Uncertainty Error with Adaptive RBF Network

A critical issue in the control of exoskeleton systems is unknown nonlinear dynamic properties of the system. The improper estimation of those unknown properties can cause considerable human-exoskeleton interaction force during human’s movements. It is really challenging to exactly estimate the parameters of dynamic models. In this paper, we propose a novel exoskeleton control algorithm to both compensate for the dynamic uncertainty error and minimize the human-exoskeleton interaction force. We have built a virtual torque controller based on dynamic models of a lower exoskeleton and have used an approximation of a Radial Basis Function (RBF) neural network to compensate for the dynamic uncertainty error. By doing so, we avoid using complicated force sensors installed on the human-exoskeleton interface and minimize the physical Human-Robot Interaction (pHRI) force. Moreover, we introduce the prototype of our exoskeleton system, called ‘PRMI’ exoskeleton system. Finally, we validated the proposed algorithm on this system, and the experimental results show that the proposed control algorithm provides a good control quality for the ‘PRMI’ exoskeleton system by compensating for dynamic uncertainty error.     

Reliable Intermodal Freight Network Expansion with Demand Uncertainties and Network Disruptions

This paper develops a robust Mixed-Integer Linear Program (MILP) to assist railroad operators with intermodal network expansion decisions. Specifically, the objective of the model is to identify critical rail links to retrofit, locations to establish new terminals, and existing terminals to expand, where the intermodal freight network is subject to demand and supply uncertainties. Additional considerations by the model include a finite overall budget for investment, limited capacities on network links and at intermodal terminals, and time window constraints for shipments. A hybrid Genetic Algorithm (GA) is developed to solve the proposed MILP. It utilizes a column generation algorithm to solve the freight flow assignment problem and a multi-modal shortest path label-setting algorithm to solve the pricing sub-problems. An exact exhaustive enumeration method is used to validate the GA results. Experimental results indicate that the developed algorithm is capable of producing optimal solutions efficiently for small-sized intermodal freight networks. The impact of uncertainty on network configuration is discussed for a larger-sized case study.     

pH/temperature sensitive poly(ethylene glycol)-based biodegradable polyester block copolymer hydrogels

Novel pH and temperature sensitive biodegradable block copolymers composed of poly(ethylene glycol) (PEG), polyglycolide (GA), ?-caprolactone (CL) and sulfamethazine oligomers (OSMs) were synthesized by ring opening polymerization and 1,3-dicyclohexyl-carbodiimide (DCC) mediated coupling reactions. Their physicochemical properties in aqueous media were characterized by ¹H NMR spectroscopy and gel permeation spectroscopy. The sol-gel phase transition behavior of OSM-PCGA-PEG-PCGA-OSM block copolymers was investigated both in solution and injection to PBS buffer at pH 7.4 and 37 °C. Aqueous solutions of OSM-PCGA-PEG-PCGA-OSM changed from a sol to a gel phase with increasing temperature and decreasing pH. The sol-gel transition properties of these block copolymers are influenced by the hydrophobic/hydrophilic balance of the copolymers, block length, hydrophobicity, stereoregularity of the hydrophobic components within the block copolymer, and the ionization of the pH functional groups in the copolymer, which depends on the environmental pH. Degradation of the triblock and pentablock copolymers at 37 °C (pH 7.4), and at 0 °C and 5 °C both at pH 8.0, was investigated. It was demonstrated here using the in vitro test method, that the anticancer agent paclitaxel (PTX) could be loaded and released by the pH and temperature sensitive OSM-PCGA-PEG-PCGA-OSM block copolymer, such that this could be used as a suitable matrix for subcutaneous injection in drug delivery systems.     

Pine forest investigation using high resolution P-band Pol-InSAR data

A Pol-InSAR dataset acquired at P-band over a maritime pine forest (Nezer forest of Landes, France) has been investigated and compared with tree structural ground measurements in order to identify scatterers associated with elementary scattering mechanisms in the canopy layer. Since this managed forest is constituted by different height stands, it allows to investigate mechanism change in the vertical direction during the forest growth. It has been observed that VV channel was the most elevated, which can be accounted for a maximum attenuation in the vertical direction and partially for the presence of sub-vertical branches in the top canopy layer, and that this channel was the most sensitive to the tree density in reason of an important ground reflectivity. The most pure double-bounce scattering mechanism component is received in HH-VV channel where the corresponding phase center reaches the ground level for large Diameter at Breast Height. It is also supposed that HH channel, which receives double bounce backscatter, was affected by the sub-horizontal primary branch development, which induces an elevation of the phase center over oldest trees while tree density diminution enhances backscatter from the ground level. Finally, the crosspolar channel appeared the less perturbed by the tree density than VV channel since it receives predominantly the canopy contribution.     

Complexity of the word problem for commutative semigroups of fixed dimension

Summary In this paper we investigate the computational complexity of the word problem for commutative semigroups of fixed dimension. It is shown that for commutative semigroups of dimension k, k 6, the word problem is complete for symmetric linear space, providing another complete problem for this symmetric complexity class. We also show that in the case of one generator, the word problem is solvable in polynomial time.